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Periodicals as TopicAccess to InformationStem CellsJournal Impact FactorBibliometricsPublishingPeer Review, ResearchAlphavirusAlphavirus InfectionsSindbis VirusEncephalitis, ViralStartle ReactionSensory GatingEncephalitis Virus, Venezuelan EquineGlycine-tRNA LigaseAlanine-tRNA LigaseTyrosine-tRNA LigaseCharcot-Marie-Tooth DiseaseRNA, Transfer, GlyAmino Acyl-tRNA SynthetasesPolitical SystemsInduced Pluripotent Stem CellsPluripotent Stem CellsNervous System DiseasesEmbryonic Stem CellsNuclear ReprogrammingCell DifferentiationArchivesBiological Science DisciplinesPubMedDirectories as TopicEuphoriaCocaineCocaine-Related DisordersMissouriCommodificationAlcoholicsSelf AdministrationLevocardiaModels, NeurologicalNeurosciencesFunctional LateralityTheory of MindBrain MappingBrainSchizophreniaPseudobulbar PalsyLaughterPsychotic DisordersSchizophrenic PsychologyREM Sleep Parasomnias
Periodicals as Topic: A publication issued at stated, more or less regular, intervals.Access to Information: Individual's rights to obtain and use information collected or generated by others.Stem Cells: Relatively undifferentiated cells that retain the ability to divide and proliferate throughout postnatal life to provide progenitor cells that can differentiate into specialized cells.Journal Impact Factor: A quantitative measure of the frequency on average with which articles in a journal have been cited in a given period of time.Bibliometrics: The use of statistical methods in the analysis of a body of literature to reveal the historical development of subject fields and patterns of authorship, publication, and use. Formerly called statistical bibliography. (from The ALA Glossary of Library and Information Science, 1983)Publishing: "The business or profession of the commercial production and issuance of literature" (Webster's 3d). It includes the publisher, publication processes, editing and editors. Production may be by conventional printing methods or by electronic publishing.Peer Review, Research: The evaluation by experts of the quality and pertinence of research or research proposals of other experts in the same field. Peer review is used by editors in deciding which submissions warrant publication, by granting agencies to determine which proposals should be funded, and by academic institutions in tenure decisions.Alphavirus: A genus of TOGAVIRIDAE, also known as Group A arboviruses, serologically related to each other but not to other Togaviridae. The viruses are transmitted by mosquitoes. The type species is the SINDBIS VIRUS.Alphavirus Infections: Virus diseases caused by members of the ALPHAVIRUS genus of the family TOGAVIRIDAE.Sindbis Virus: The type species of ALPHAVIRUS normally transmitted to birds by CULEX mosquitoes in Egypt, South Africa, India, Malaya, the Philippines, and Australia. It may be associated with fever in humans. Serotypes (differing by less than 17% in nucleotide sequence) include Babanki, Kyzylagach, and Ockelbo viruses.Encephalitis, Viral: Inflammation of brain parenchymal tissue as a result of viral infection. Encephalitis may occur as primary or secondary manifestation of TOGAVIRIDAE INFECTIONS; HERPESVIRIDAE INFECTIONS; ADENOVIRIDAE INFECTIONS; FLAVIVIRIDAE INFECTIONS; BUNYAVIRIDAE INFECTIONS; PICORNAVIRIDAE INFECTIONS; PARAMYXOVIRIDAE INFECTIONS; ORTHOMYXOVIRIDAE INFECTIONS; RETROVIRIDAE INFECTIONS; and ARENAVIRIDAE INFECTIONS.Startle Reaction: A complex involuntary response to an unexpected strong stimulus usually auditory in nature.Sensory Gating: The ability of the BRAIN to suppress neuronal responses to external sensory inputs, such as auditory and visual stimuli. Sensory filtering (or gating) allows humans to block out irrelevant, meaningless, or redundant stimuli.Encephalitis Virus, Venezuelan Equine: A species of ALPHAVIRUS that is the etiologic agent of encephalomyelitis in humans and equines. It is seen most commonly in parts of Central and South America.Glycine-tRNA Ligase: An enzyme that activates glycine with its specific transfer RNA. EC 6.1.1.14.Alanine-tRNA Ligase: An enzyme that activates alanine with its specific transfer RNA. EC 6.1.1.7.Tyrosine-tRNA Ligase: An enzyme that activates tyrosine with its specific transfer RNA. EC 6.1.1.1.Charcot-Marie-Tooth Disease: A hereditary motor and sensory neuropathy transmitted most often as an autosomal dominant trait and characterized by progressive distal wasting and loss of reflexes in the muscles of the legs (and occasionally involving the arms). Onset is usually in the second to fourth decade of life. This condition has been divided into two subtypes, hereditary motor and sensory neuropathy (HMSN) types I and II. HMSN I is associated with abnormal nerve conduction velocities and nerve hypertrophy, features not seen in HMSN II. (Adams et al., Principles of Neurology, 6th ed, p1343)RNA, Transfer, Gly: A transfer RNA which is specific for carrying glycine to sites on the ribosomes in preparation for protein synthesis.Amino Acyl-tRNA Synthetases: A subclass of enzymes that aminoacylate AMINO ACID-SPECIFIC TRANSFER RNA with their corresponding AMINO ACIDS.Political Systems: The units based on political theory and chosen by countries under which their governmental power is organized and administered to their citizens.Induced Pluripotent Stem Cells: Cells from adult organisms that have been reprogrammed into a pluripotential state similar to that of EMBRYONIC STEM CELLS.Pluripotent Stem Cells: Cells that can give rise to cells of the three different GERM LAYERS.Nervous System Diseases: Diseases of the central and peripheral nervous system. This includes disorders of the brain, spinal cord, cranial nerves, peripheral nerves, nerve roots, autonomic nervous system, neuromuscular junction, and muscle.Embryonic Stem Cells: Cells derived from the BLASTOCYST INNER CELL MASS which forms before implantation in the uterine wall. They retain the ability to divide, proliferate and provide progenitor cells that can differentiate into specialized cells.Nuclear Reprogramming: The process that reverts CELL NUCLEI of fully differentiated somatic cells to a pluripotent or totipotent state. This process can be achieved to a certain extent by NUCLEAR TRANSFER TECHNIQUES, such as fusing somatic cell nuclei with enucleated pluripotent embryonic stem cells or enucleated totipotent oocytes. GENE EXPRESSION PROFILING of the fused hybrid cells is used to determine the degree of reprogramming. Dramatic results of nuclear reprogramming include the generation of cloned mammals, such as Dolly the sheep in 1997.Cell Differentiation: Progressive restriction of the developmental potential and increasing specialization of function that leads to the formation of specialized cells, tissues, and organs.ArchivesBiological Science Disciplines: All of the divisions of the natural sciences dealing with the various aspects of the phenomena of life and vital processes. The concept includes anatomy and physiology, biochemistry and biophysics, and the biology of animals, plants, and microorganisms. It should be differentiated from BIOLOGY, one of its subdivisions, concerned specifically with the origin and life processes of living organisms.PubMed: A bibliographic database that includes MEDLINE as its primary subset. It is produced by the National Center for Biotechnology Information (NCBI), part of the NATIONAL LIBRARY OF MEDICINE. PubMed, which is searchable through NLM's Web site, also includes access to additional citations to selected life sciences journals not in MEDLINE, and links to other resources such as the full-text of articles at participating publishers' Web sites, NCBI's molecular biology databases, and PubMed Central.Directories as Topic: Lists of persons or organizations, systematically arranged, usually in alphabetic or classed order, giving address, affiliations, etc., for individuals, and giving address, officers, functions, and similar data for organizations. (ALA Glossary of Library and Information Science, 1983)Euphoria: An exaggerated feeling of physical and emotional well-being not consonant with apparent stimuli or events; usually of psychologic origin, but also seen in organic brain disease and toxic states.Cocaine: An alkaloid ester extracted from the leaves of plants including coca. It is a local anesthetic and vasoconstrictor and is clinically used for that purpose, particularly in the eye, ear, nose, and throat. It also has powerful central nervous system effects similar to the amphetamines and is a drug of abuse. Cocaine, like amphetamines, acts by multiple mechanisms on brain catecholaminergic neurons; the mechanism of its reinforcing effects is thought to involve inhibition of dopamine uptake.Cocaine-Related Disorders: Disorders related or resulting from use of cocaine.MissouriCommodification: The social process by which something or someone comes to be regarded and treated as an article of trade or commerce.Alcoholics: Persons who have a history of physical or psychological dependence on ETHANOL.Self Administration: Administration of a drug or chemical by the individual under the direction of a physician. It includes administration clinically or experimentally, by human or animal.Levocardia: Congenital abnormalities in which the HEART is in the normal position (levocardia) in the left side of the chest but some or all of the THORAX or ABDOMEN viscera are transposed laterally (SITUS INVERSUS). It is also known as situs inversus with levocardia, or isolated levocardia. This condition is often associated with severe heart defects and splenic abnormalities such as asplenia or polysplenia.Models, Neurological: Theoretical representations that simulate the behavior or activity of the neurological system, processes or phenomena; includes the use of mathematical equations, computers, and other electronic equipment.Neurosciences: The scientific disciplines concerned with the embryology, anatomy, physiology, biochemistry, pharmacology, etc., of the nervous system.Functional Laterality: Behavioral manifestations of cerebral dominance in which there is preferential use and superior functioning of either the left or the right side, as in the preferred use of the right hand or right foot.Theory of Mind: The ability to attribute mental states (e.g., beliefs, desires, feelings, intentions, thoughts, etc.) to self and to others, allowing an individual to understand and infer behavior on the basis of the mental states. Difference or deficit in theory of mind is associated with ASPERGER SYNDROME; AUTISTIC DISORDER; and SCHIZOPHRENIA, etc.Brain Mapping: Imaging techniques used to colocalize sites of brain functions or physiological activity with brain structures.Brain: The part of CENTRAL NERVOUS SYSTEM that is contained within the skull (CRANIUM). Arising from the NEURAL TUBE, the embryonic brain is comprised of three major parts including PROSENCEPHALON (the forebrain); MESENCEPHALON (the midbrain); and RHOMBENCEPHALON (the hindbrain). The developed brain consists of CEREBRUM; CEREBELLUM; and other structures in the BRAIN STEM.Schizophrenia: A severe emotional disorder of psychotic depth characteristically marked by a retreat from reality with delusion formation, HALLUCINATIONS, emotional disharmony, and regressive behavior.Pseudobulbar Palsy: A syndrome characterized by DYSARTHRIA, dysphagia, dysphonia, impairment of voluntary movements of tongue and facial muscles, and emotional lability. This condition is caused by diseases that affect the motor fibers that travel from the cerebral cortex to the lower BRAIN STEM (i.e., corticobulbar tracts); including MULTIPLE SCLEROSIS; MOTOR NEURON DISEASE; and CEREBROVASCULAR DISORDERS. (From Adams et al., Principles of Neurology, 6th ed, p489)Laughter: An involuntary expression of merriment and pleasure; it includes the patterned motor responses as well as the inarticulate vocalization.Psychotic Disorders: Disorders in which there is a loss of ego boundaries or a gross impairment in reality testing with delusions or prominent hallucinations. (From DSM-IV, 1994)Schizophrenic Psychology: Study of mental processes and behavior of schizophrenics.REM Sleep Parasomnias: Abnormal behavioral or physiologic events that are associated with REM sleep, including REM SLEEP BEHAVIOR DISORDER.

Vision: modular analysis--or not? (1/10314)

It has commonly been assumed that the many separate areas of the visual system perform modular analyses, each restricted to a single attribute of the image. A recent paper advocates a radically different approach, where all areas in the hierarchy analyse all attributes of the image to extract perceptually relevant decisions.  (+info)

Somatic recording of GABAergic autoreceptor current in cerebellar stellate and basket cells. (2/10314)

Patch-clamp recordings were performed from stellate and basket cells in rat cerebellar slices. Under somatic voltage clamp, short depolarizing pulses were applied to elicit action potentials in the axon. After the action potential, a bicuculline- and Cd2+-sensitive current transient was observed. A similar response was obtained when eliciting axonal firing by extracellular stimulation. With an isotonic internal Cl- solution, the peak amplitude of this current varied linearly with the holding potential, yielding an extrapolated reversal potential of -20 to 0 mV. Unlike synaptic or autaptic GABAergic currents obtained in the same preparation, the current transient had a slow rise-time and a low variability between trials. This current was blocked when 10 mM BAPTA was included in the recording solution. In some experiments, the current transient elicited axonal action potentials. The current transient was reliably observed in animals aged 12-15 d, with a mean amplitude of 82 pA at -70 mV, but was small and rare in the age group 29-49 d. Numerical simulations could account for all properties of the current transient by assuming that an action potential activates a distributed GABAergic conductance in the axon. The actual conductance is probably restricted to release sites, with an estimated mean presynaptic current response of 10 pA per site (-70 mV, age 12-15 d). We conclude that in developing rats, stellate and basket cell axons have a high density of GABAergic autoreceptors and that a sizable fraction of the corresponding current can be measured from the soma.  (+info)

Competitive mechanisms subserve attention in macaque areas V2 and V4. (3/10314)

It is well established that attention modulates visual processing in extrastriate cortex. However, the underlying neural mechanisms are unknown. A consistent observation is that attention has its greatest impact on neuronal responses when multiple stimuli appear together within a cell's receptive field. One way to explain this is to assume that multiple stimuli activate competing populations of neurons and that attention biases this competition in favor of the attended stimulus. In the absence of competing stimuli, there is no competition to be resolved. Accordingly, attention has a more limited effect on the neuronal response to a single stimulus. To test this interpretation, we measured the responses of neurons in macaque areas V2 and V4 using a behavioral paradigm that allowed us to isolate automatic sensory processing mechanisms from attentional effects. First, we measured each cell's response to a single stimulus presented alone inside the receptive field or paired with a second receptive field stimulus, while the monkey attended to a location outside the receptive field. Adding the second stimulus typically caused the neuron's response to move toward the response that was elicited by the second stimulus alone. Then, we directed the monkey's attention to one element of the pair. This drove the neuron's response toward the response elicited when the attended stimulus appeared alone. These findings are consistent with the idea that attention biases competitive interactions among neurons, causing them to respond primarily to the attended stimulus. A quantitative neural model of attention is proposed to account for these results.  (+info)

Voltage-dependent properties of dendrites that eliminate location-dependent variability of synaptic input. (4/10314)

We examined the hypothesis that voltage-dependent properties of dendrites allow for the accurate transfer of synaptic information to the soma independent of synapse location. This hypothesis is motivated by experimental evidence that dendrites contain a complex array of voltage-gated channels. How these channels affect synaptic integration is unknown. One hypothesized role for dendritic voltage-gated channels is to counteract passive cable properties, rendering all synapses electrotonically equidistant from the soma. With dendrites modeled as passive cables, the effect a synapse exerts at the soma depends on dendritic location (referred to as location-dependent variability of the synaptic input). In this theoretical study we used a simplified three-compartment model of a neuron to determine the dendritic voltage-dependent properties required for accurate transfer of synaptic information to the soma independent of synapse location. A dendrite that eliminates location-dependent variability requires three components: 1) a steady-state, voltage-dependent inward current that together with the passive leak current provides a net outward current and a zero slope conductance at depolarized potentials, 2) a fast, transient, inward current that compensates for dendritic membrane capacitance, and 3) both alpha amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid- and N-methyl-D-aspartate-like synaptic conductances that together permit synapses to behave as ideal current sources. These components are consistent with the known properties of dendrites. In addition, these results indicate that a dendrite designed to eliminate location-dependent variability also actively back-propagates somatic action potentials.  (+info)

Simultaneous measurement of evoked release and [Ca2+]i in a crayfish release bouton reveals high affinity of release to Ca2+. (5/10314)

The opener neuromuscular junction of crayfish was used to determine the affinity of the putative Ca2+ receptor(s) responsible for evoked release. Evoked, asynchronous release, and steady-state intracellular Ca2+ concentration, [Ca2+]ss, were measured concomitantly in single release boutons. It was found that, as expected, asynchronous release is highly correlated with [Ca2+]ss. Surprisingly, evoked release was also found to be highly correlated with [Ca2+]ss. The quantal content (m) and the rate of asynchronous release (S) showed sigmoidal dependence on [Ca2+]ss. The slope log m/log [Ca2+]ss varied between 1.6 and 3.3; the higher slope observed at the lower [Ca2+]o. The slope log S/log [Ca2+]ss varied between 3 and 4 and was independent of [Ca2+]o. These results are consistent with the assumption that evoked release is controlled by the sum of [Ca2+]ss and the local elevation of Ca2+ concentration near the release sites resulting from Ca2+ influx through voltage-gated Ca2+ channels (Y). On the basis of the above, we were able to estimate Y. We found Y to be significantly <10 microM even for [Ca2+]o = 13.5 mM. The dissociation constant (Kd) of the Ca2+ receptor(s) associated with evoked release was calculated to be in the range of 4-5 microM. This value of Kd is similar to that found previously for asynchronous release.  (+info)

Small conductance potassium channels cause an activity-dependent spike frequency adaptation and make the transfer function of neurons logarithmic. (6/10314)

We made a computational model of a single neuron to study the effect of the small conductance (SK) Ca2+-dependent K+ channel on spike frequency adaptation. The model neuron comprised a Na+ conductance, a Ca2+ conductance, and two Ca2+-independent K+ conductances, as well as a small and a large (BK) Ca2+-activated K+ conductance, a Ca2+ pump, and mechanisms for Ca2+ buffering and diffusion. Sustained current injection that simulated synaptic input resulted in a train of action potentials (APs) which in the absence of the SK conductance showed very little adaptation with time. The transfer function of the neuron was nearly linear, i.e., both asymptotic spike rate as well as the intracellular free Ca2+ concentration ([Ca2+]i) were approximately linear functions of the input current. Adding an SK conductance with a steep nonlinear dependence on [Ca2+]i (. Pflugers Arch. 422:223-232; Kohler, Hirschberg, Bond, Kinzie, Marrion, Maylie, and Adelman. 1996. Science. 273:1709-1714) caused a marked time-dependent spike frequency adaptation and changed the transfer function of the neuron from linear to logarithmic. Moreover, the input range the neuron responded to with regular spiking increased by a factor of 2.2. These results can be explained by a shunt of the cell resistance caused by the activation of the SK conductance. It might turn out that the logarithmic relationships between the stimuli of some modalities (e.g., sound or light) and the perception of the stimulus intensity (Fechner's law) have a cellular basis in the involvement of SK conductances in the processing of these stimuli.  (+info)

Transient potassium currents regulate the discharge patterns of dorsal cochlear nucleus pyramidal cells. (7/10314)

Pyramidal cells in the dorsal cochlear nucleus (DCN) show three distinct temporal discharge patterns in response to sound: "pauser," "buildup," and "chopper." Similar discharge patterns are seen in vitro and depend on the voltage from which the cell is depolarized. It has been proposed that an inactivating A-type K+ current (IKI) might play a critical role in generating the three different patterns. In this study we examined the characteristics of transient currents in DCN pyramidal cells to evaluate this hypothesis. Morphologically identified pyramidal cells in rat brain slices (P11-P17) exhibited the three voltage-dependent discharge patterns. Two inactivating currents were present in outside-out patches from pyramidal cells: a rapidly inactivating (IKIF, tau approximately 11 msec) current insensitive to block by tetraethylammonium (TEA) and variably blocked by 4-aminopyridine (4-AP) with half-inactivation near -85 mV, and a slowly inactivating TEA- and 4-AP-sensitive current (IKIS, tau approximately 145 msec) with half-inactivation near -35 mV. Recovery from inactivation at 34 degrees C was described by a single exponential with a time constant of 10-30 msec, similar to the rate at which first spike latency increases with the duration of a hyperpolarizing prepulse. Acutely isolated cells also possessed a rapidly activating (<1 msec at 22 degrees C) transient current that activated near -45 mV and showed half-inactivation near -80 mV. A model demonstrated that the deinactivation of IKIF was correlated with the discharge patterns. Overall, the properties of the fast inactivating K+ current were consistent with their proposed role in shaping the discharge pattern of DCN pyramidal cells.  (+info)

Passive electrotonic properties of rat hippocampal CA3 interneurones. (8/10314)

1. The linear membrane responses of CA3 interneurones were determined with the use of whole-cell patch recording methods. The mean input resistance (RN) for all cells in this study was 526 +/- 16 MOmega and the slowest membrane time constant (tau0) was 73 +/- 3 ms. 2. The three-dimensional morphology of 63 biocytin-labelled neurones was used to construct compartmental models. Specific membrane resistivity (Rm) and specific membrane capacitance (Cm) were estimated by fitting the linear membrane response. Acceptable fits were obtained for 24 CA3 interneurones. The mean Rm was 61.9 +/- 34.2 Omega cm2 and the mean Cm was 0.9 +/- 0.3 microF cm-2. Intracellular resistance (Ri) could not be resolved in this study. 3. Examination of voltage attenuation revealed a significantly low synaptic efficiency from most dendritic synaptic input locations to the soma. 4. Simulations of excitatory postsynaptic potentials (EPSPs) were analysed at both the site of synaptic input and at the soma. There was little variability in the depolarization at the soma from synaptic inputs placed at different locations along the dendritic tree. The EPSP amplitude at the site of synaptic input was progressively larger with distance from the soma, consistent with a progressive increase in input impedance. 5. The 'iso-efficiency' of spatially different synaptic inputs arose from two opposing factors: an increase in EPSP amplitude at the synapse with distance from the soma was opposed by a nearly equivalent increase in voltage attenuation. These simulations suggest that, in these particular neurones, the amplitude of EPSPs measured at the soma will not be significantly affected by the location of synaptic inputs.  (+info)

Frontiers | Dimensional reduction for the inverse problem of neural field theory | Frontiers in Computational NeuroscienceFrontiers | Dimensional reduction for the inverse problem of neural field theory | Frontiers in Computational Neuroscience
Inverse problems in computational neuroscience comprise the determination of synaptic weight matrices or kernels for neural networks or neural fields respectively. Here, we reduce multi-dimensional inverse problems to inverse problems in lower dimensions which can be solved in an easier way or even explicitly through kernel construction. In particular, we discuss a range of embedding techniques and analyze their properties. We study the Amari equation as a particular example of a neural field theory. We obtain a solution of the full 2D or 3D problem by embedding 0D or 1D kernels into the domain of the Amari equation using a suitable path parametrization and basis transformations. Pulses are interconnected at branching points via path gluing. As instructive examples we construct logical gates, such as the persistent XOR and binary addition in neural fields. In addition, we compare results of inversion by dimensional reduction with a recently proposed global inversion scheme for neural fields based on
Exact Event-Driven Implementation for Recurrent Networks of Stochastic Perfect Integrate-and-Fire Neurons - Semantic ScholarExact Event-Driven Implementation for Recurrent Networks of Stochastic Perfect Integrate-and-Fire Neurons - Semantic Scholar
In vivo cortical recording reveals that indirectly driven neural assemblies can produce reliable and temporally precise spiking patterns in response to stereotyped stimulation. This suggests that despite being fundamentally noisy, the collective activity of neurons conveys information through temporal coding. Stochastic integrate-and-fire models delineate a natural theoretical framework to study the interplay of intrinsic neural noise and spike timing precision. However, there are inherent difficulties in simulating their networks dynamics in silico with standard numerical discretization schemes. Indeed, the well-posedness of the evolution of such networks requires temporally ordering every neuronal interaction, whereas the order of interactions is highly sensitive to the random variability of spiking times. Here, we answer these issues for perfect stochastic integrate-and-fire neurons by designing an exact event-driven algorithm for the simulation of recurrent networks, with delayed Dirac-like
OSA | Ultrafast all-optical implementation of a leaky integrate-and-fire neuronOSA | Ultrafast all-optical implementation of a leaky integrate-and-fire neuron
In this paper, we demonstrate for the first time an ultrafast fully functional photonic spiking neuron. Our experimental setup constitutes a complete all-optical implementation of a leaky integrate-and-fire neuron, a computational primitive that provides a basis for general purpose analog optical computation. Unlike purely analog computational models, spiking operation eliminates noise accumulation and results in robust and efficient processing. Operating at gigahertz speed, which corresponds to at least 108 speed-up compared with biological neurons, the demonstrated neuron provides all functionality required by the spiking neuron model. The two demonstrated prototypes and a demonstrated feedback operation mode prove the feasibility and stability of our approach and show the obtained performance characteristics.. © 2011 Optical Society of America. Full Article , PDF Article ...
Biological neuron model - WikipediaBiological neuron model - Wikipedia
where yi is the output of the i th neuron, xj is the jth input neuron signal, wij is the synaptic weight (or strength of connection) between the neurons i and j, and φ is the activation function. While this model has seen success in machine-learning applications, it is a poor model for real (biological) neurons, because it lacks the time-dependence that real neuron spikes exhibit. Biological models of the "integrate-and-fire" type take essentially this form; but they have largely been superseded by kinetic models such as the Hodgkin-Huxley model.[citation needed] In the case of modelling a biological neuron, physical analogues are used in place of abstractions such as "weight" and "transfer function". A neuron is filled and surrounded with water containing ions, which carry electric charge. The neuron is bound by an insulating cell membrane and can maintain a concentration of charged ions on either side that determines a capacitance Cm. The firing of a neuron involves the movement of ions into ...
ModelDB: I&F recurrent networks with current- or conductance-based synapses (Cavallari et al. 2014)ModelDB: I&F recurrent networks with current- or conductance-based synapses (Cavallari et al. 2014)
This is the readme for the two neural network models (mex file) associated with the following paper: S.Cavallari, S. Panzeri and A.Mazzoni (2014) Comparison of the dynamics of neural interactions between current-based and conductance-based integrate-and-fire recurrent networks, Frontiers in Neural Circuits 8:12. doi: 10.3389/fncir.2014.00012 Recurrent networks, each of two populations (excitatory and inhibitory) of randomly connected Leaky Integrate-and-Fire (LIF) neurons with either conductance-based synapses (COBN) or current-based synapses (CUBN) were studied. The activity of the LIF COBN model were compared with the activity of the associated model LIF CUBN. Instructions are provided in the ReadMe files in each model associated sub folder, LIF_COBN and LIF_CUBN. If you have any questions about the implementation of these matlab models, which require compilation with mex, contact: [email protected] Please cite the paper if you use the codes. 20140709 Comments in LIF_COBN/code_COBN.c, ...
ICLR 2015ICLR 2015
The Ebb and Flow of Deep Learning: a Theory of Local Learning In a physical neural system, where storage and processing are intertwined, the learning rules for adjusting synaptic weights can only depend on local variables, such as the activity of the pre- and post-synaptic neurons. Thus learning models must specify two things: (1) which variables are to be considered local; and (2) which kind of function combines these local variables into a learning rule. We consider polynomial learning rules and analyze their behavior and capabilities in both linear and non-linear networks. As a byproduct, this framework enables the discovery of new learning rules and important relationships between learning rules and group symmetries. Stacking local learning rules in deep feedforward networks leads to deep local learning. While deep local learning can learn interesting representations, it cannot learn complex input-output functions, even when targets are available for the top layer. Learning complex ...
ICLR 2015ICLR 2015
The Ebb and Flow of Deep Learning: a Theory of Local Learning In a physical neural system, where storage and processing are intertwined, the learning rules for adjusting synaptic weights can only depend on local variables, such as the activity of the pre- and post-synaptic neurons. Thus learning models must specify two things: (1) which variables are to be considered local; and (2) which kind of function combines these local variables into a learning rule. We consider polynomial learning rules and analyze their behavior and capabilities in both linear and non-linear networks. As a byproduct, this framework enables the discovery of new learning rules and important relationships between learning rules and group symmetries. Stacking local learning rules in deep feedforward networks leads to deep local learning. While deep local learning can learn interesting representations, it cannot learn complex input-output functions, even when targets are available for the top layer. Learning complex ...
Brain Activity in Spherical Topology via Neural Field TheoryBrain Activity in Spherical Topology via Neural Field Theory
See moreNeural activity is responsible for information processing in the brain. Activity has been found to have natural spatial modes, each of which has a frequency, analogous to the pitch of the notes of a musical instrument. A core aim of this thesis is to analyze large scale brain activity in terms of the eigenmodes of a brain hemisphere and to explore eigenmode dynamics. Electroencephalography (EEG) and evoked response potentials (ERPs) are important measurement techniques used to observe large scale changes in brain activity. EEG is a recording technique, while ERPs are transient electrical responses to brief sensory stimuli. In this thesis analysis of EEG and ERPs is carried out in terms of eigenmodes using an established physiologically based neural field theory, which averages over attribute of neurons to yield a continuum model of brain activity whose parameters are based on the physiology. To explore the effects of boundary conditions and topology, a spherical approximation is used and ...
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Our estimate of the average cortical spread of the LFP is similar to an estimate in layer 2/3 of cat V1 reported recently (Katzner et al., 2009) with a different approach, but is much smaller than many others. Our result seems to contradict a number of studies (Mitzdorf, 1987; Kruse and Eckhorn, 1996; Kreiman et al., 2006; Liu and Newsome, 2006; Berens et al., 2008) that concluded that the spread of LFP signals ranges from ∼500 μm to a few millimeters. However, all such estimates rely on a model associating the LFP with functional properties of cortical neurons. For most studies (Mitzdorf, 1987; Kruse and Eckhorn, 1996; Kreiman et al., 2006; Liu and Newsome, 2006; Berens et al., 2008; Katzner et al., 2009), estimates of the cortical spread of the LFP were indirect and were associated with columnar structures of certain feature selectivities, such as orientation, direction, or speed selectivity. Because the feature selectivity of the LFP is usually broader than that of single unit activity or ...
The Effect of Neural Noise on Spike Time Precision in a Detailed CA3 Neuron Model : Figure 3The Effect of Neural Noise on Spike Time Precision in a Detailed CA3 Neuron Model : Figure 3
Figure 3: The effect of synaptic noise of various synaptic types. (a) Visualization of spike train groups analyzed under synaptic noise. The ordinate represents the AP rank of APs fired at times shown on abscissa. The braided lines in the main graph represent different spike trains of individual trials and demonstrate an interesting preference of the spiking mechanism preserving AP times well aligned despite different numbers of fired APs in trials. The inset focuses on the region of an AP cluster, demonstrating the cluster method used to analyze APs: the dotted blue rectangle in the inset represents the 10 ms time window moving along aligned spike trains and collecting only those AP clusters having within the 10 ms window number of spikes larger than 70% the value of ...
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We have shown that intensity-selective and intensity-nonselective neurons differ in excitatory tuning profile and absolute excitatory strength. Intuitively, the differential intensity tuning profile of excitation may fully account for the functional difference between intensity-selective and intensity-nonselective neurons. In the intensity-selective neuron, excitation is close to saturation at the intensity threshold (it reaches ,80% of the peak level), whereas at this intensity level inhibition is nearly the lowest (Fig. 4A,B). This may lead to a strong output response at the intensity threshold. With intensity further increasing, inhibition catches up, and the level of spike response may gradually fall.. To demonstrate how much the observed excitatory and inhibitory tuning profiles can account for the intensity tuning profile of output responses in a quantitative manner, we used a conductance-based single-compartment integrate-and-fire neuron model (Liu et al., 2007; Zhou et al., 2012). ...
ANC Workshop: Paolo Puggioni and Amos Storkey, Chair: Charles Sutton - ANC | Institute for Adaptive and Neural ComputationANC Workshop: Paolo Puggioni and Amos Storkey, Chair: Charles Sutton - ANC | Institute for Adaptive and Neural Computation
Paolo Puggioni. Bayesian inference of synaptic inputs given an in vivo voltage clamp trace. Voltage clamp recordings in awake animals directly measure the excitatory (or inhibitory) synaptic current flowing in a single neuron.. The current results from the summation of thousands of synaptic inputs of variable size per second. Recent methods based on Kalman filtering [Paninski2012, Lankarany2013] give a good estimation of the time-varying synaptic conductance, that is a function of input rate and size. However, inferring how the distribution of input size changes during behaviour can be important to understand computational mechanisms used by our brain. Here I propose a simple hierarchical model that is able to estimate both frequency and probability distribution of the synaptic weights. Firstly I test the validity of my model by using generated data, showing that it is robust to high frequency noise and slow fluctuations in the inputs rate typical of in vivo recordings. Thus, I apply it to ...
Interpreting frequency responses to dose-conserved pulsatile input signals in simple cell signaling motifs.Interpreting frequency responses to dose-conserved pulsatile input signals in simple cell signaling motifs.
Many hormones are released in pulsatile patterns. This pattern can be modified, for instance by changing pulse frequency, to encode relevant physiological information. Often other properties of the pulse pattern will also change with frequency. How do signaling pathways of cells targeted by these hormones respond to different input patterns? In this study, we examine how a given dose of hormone can induce different outputs from the target system, depending on how this dose is distributed in time. We use simple mathematical models of feedforward signaling motifs to understand how the properties of the target system give rise to preferences in input pulse pattern. We frame these problems in terms of frequency responses to pulsatile inputs, where the amplitude or duration of the pulses is varied along with frequency to conserve input dose. We find that the form of the nonlinearity in the steady state input-output function of the system predicts the optimal input pattern. It does so by selecting an optimal
MicrocircuitDB: Motoneuron pool input-output function (Powers & Heckman 2017)MicrocircuitDB: Motoneuron pool input-output function (Powers & Heckman 2017)
TITLE naps :modified to have slow inactivation described in Fleidervish and to make slope a global parameter NEURON { SUFFIX naps USEION na READ ena WRITE ina RANGE gbar, thegna, sh, ar,minf,sinf,taus GLOBAL mtau,vslope } PARAMETER { gbar = .0052085 (mho/cm2) sh = 0 (mV) vslope=6.8 (mV) :activation slope mtau = 1 (ms) ena (mV) :must be explicitly defined in hoc a0s=0.001 (/ms) b0s=0.0034 (/ms) asvh=-85 (mV) bsvh=-17 (mV) avs=30 (mV) bvs=10 (mV) ar=1 (1) : 1=no inact., 0=max inact. celsius (degC) v (mV) } UNITS { (mA) = (milliamp) (mV) = (millivolt) (pS) = (picosiemens) (um) = (micron) } ASSIGNED { ina (mA/cm2) thegna (mho/cm2) minf sinf taus (ms) } STATE { m s } UNITSOFF BREAKPOINT { SOLVE states METHOD cnexp thegna =gbar*m*s ina = thegna * (v - ena) } INITIAL { trates(v,ar,sh) m=minf s=sinf } DERIVATIVE states { trates(v,ar,sh) s = (sinf - s)/taus m = (minf-m)/mtau } PROCEDURE trates(vm,a2,sh2) { LOCAL c minf = (1/(1+exp(-(vm+52.3-sh2)/vslope))) taus = 1/(alps(vm)+bets(vm)) c=alps(vm)*taus ...
www.neuron.yale.edu • modified HH model with sinusoidal voltage stimulationwww.neuron.yale.edu • modified HH model with sinusoidal voltage stimulation
Too bad that paper wasnt adequately reviewed. The authors present no rationale for using cm*dVs/dt to represent the effect of extracellular stimulation on their model cells. Nor do they explain how they relate their "Vs" to cellular morphology, orientiation, or location within the cranium, or to the actual extracellular field induced in the brain by the stimulating electrodes (whatever the location or geometry of those electrodes might be). But of course none of those considerations could be taken into account because their model cells are single compartment models, which wouldnt respond to a realistic extracellular stimulus anyway. Apparently Vs is just assigned whatever values the authors found necessary to alter the firing activity of their single compartment model neurons ...
Fast inference of couplings between integrate-and-fire neurons from their spiking activity | BMC Neuroscience | Full TextFast inference of couplings between integrate-and-fire neurons from their spiking activity | BMC Neuroscience | Full Text
In our approach, we choose to approximate P from the contribution coming from the most probable trajectory for the potential for each cell i, referred to as V i *(t). This approximation is exact when the amplitude σ of the noise is small. The determination of V i *(t) was done numerically by Paninski for one cell in [4]. We have found a fast algorithm to determine V i *(t) analytically in a time growing linearly with the number of spikes and quadratically with the number of neurons, which allows us to process recordings with tens of neurons easily. The algorithm is based on a detailed and analytical resolution of the coupled equations for the optimal potential V i *(t) and the associated optimal noise η i *(t) through (1), and is too complex to be explained in this abstract. ...
Aerosols and pressure. Single compartment cans.Aerosols and pressure. Single compartment cans.
Part of an educational physics resource on aerosols, pressure, kinetic theory and electrostatics aimed at 16 to 18 year old students
Product Details for Unsupervised Learning Foundations of Neural Computation by Terrence J. SejnowskiProduct Details for Unsupervised Learning Foundations of Neural Computation by Terrence J. Sejnowski
Buy Unsupervised Learning Foundations of Neural Computation by Terrence J. Sejnowski at TextbookX.com. ISBN/UPC: 9780262581684. Save an average of 50% on the marketplace.
PubZone - Self-organization of orientation maps in a formal neuron model using a cluster learning rule. (Info)PubZone - Self-organization of orientation maps in a formal neuron model using a cluster learning rule. (Info)
log in you can tag this publication with additional keywords A publication can refer to another publication (outgoing references) or it can be referred to by other publications (incoming references).. ...
Dynamic clamp - ScholarpediaDynamic clamp - Scholarpedia
Two limitations of Dynamic clamp are entirely technical: it has to be fast and temporally consistent. The time required for reading the membrane potential and calculating the current to inject has to be faster than the fastest time constant in the real neuron. This becomes problematic when the model is computationally intensive (as with stochastic Markov models). With ever increasing computer processor speeds, the speed limitation of dynamic clamp is constantly being pushed back. The update interval of the dynamic clamp has to be reliable and reproducible. Modern operating systems (OS) such as Linux, Mac OS, and Windows suffer from the inability of a program running on the OS to be guaranteed a requested operation will be performed precisely when it is requested. Operating systems that can guarantee a request is performed within a well defined time window are Linux with the RTLinux kernel extension, LabView with the real time module, and DOS. A version of dynamic clamp developed by R. Pinto ...
Gain modulation and the voltage dependence of channel a | Open-iGain modulation and the voltage dependence of channel a | Open-i
Gain modulation and the voltage dependence of channel activation.(A) The firing rate of the model neuron plotted against the average membrane potential, illustr
DSpace at KOASAS: Browsing DSpaceDSpace at KOASAS: Browsing DSpace
Designing Model-Based and Model-Free Reinforcement Learning Tasks without Human Guidance. Shin, Jae Hoon; Lee, JEE HANG; Tong, Shuangyi; Kim, Sang Whan; Lee, Sang Wanresearcher, 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Neural Information Processing Systems Foundation, 2019- ...
Phase transitions and information processing in the brain by Woodrow Shew | School of..."Phase transitions and information processing in the brain" by Woodrow Shew | School of...
The cerebral cortex is a highly complex network comprised of billions of excitable nerve cells. The coordinated dynamic interactions of these cells underlie our thoughts, memories, and sensory perceptions. A healthy brain carefully regulates its neural excitability to optimize information processing and avoid brain disorders. If excitability is too low, neural interactions are too weak and signals fail to propagate through the brain network. On the other hand, high excitability can result in excessively strong interactions and, in some ca
Custom events - Brian 2 2.1.1 documentationCustom events - Brian 2 2.1.1 documentation
it is used in synaptic interactions, and in integrate-and-fire models it also leads to the execution of one or more reset statements.. Sometimes, it can be useful to define additional events, e.g. when an ion concentration in the cell crosses a certain threshold. This can be done with the custom events system in Brian, which is illustrated in this diagram.. ...
Achieving realistic interface kinetics in phase field models with a diffusional contrast :: MPG.PuReAchieving realistic interface kinetics in phase field models with a diffusional contrast :: MPG.PuRe
Author: Boussinot, Guillaume et al.; Genre: Journal Article; Published in Print: 2014-06-30; Title: Achieving realistic interface kinetics in phase field models with a diffusional contrast
Difference between revisions of Publications - RedwoodCenterDifference between revisions of 'Publications' - RedwoodCenter
G. Agarwal, I. H. Stevenson, A. Berényi, K. Mizuseki, G. Buzsáki, F. T. Sommer: Spatially distributed local fields in the hippocampus encode rat position. Science 344 (2014): 626-630. pdf Supplement J. P. Crutchfield, R. G. James, S. Marzen and D. P. Varn, "Understanding and Designing Complex Systems: Response to A framework for optimal high-level descriptions in science and engineering---preliminary report", (2014). arXiv link J. H. Engel, S. B. Eryilmaz, SangBum Kim, M. BrightSky, Chung Lam, H.-L. Lung, B. A. Olshausen, H.-S.P. Wong (2014) "Capacity optimization of emerging mem- ory systems: A shannon-inspired approach to device characterization," Electron Devices Meeting (IEDM), 2014 IEEE International , vol., no., pp.29.4.1,29.4.4, 15- 17 Dec. 2014 link A. K. Fletcher and S. Rangan, Scalable Inference for Neuronal Connectivity from Calcium Imaging, Proc. 28th Ann. Conf. Neural Information Processing Systems, NIPS (2014). Harper NS, Scott BH, Semple MN, McAlpine D (2014) The neural code ...
Difference between revisions of Publications - RedwoodCenterDifference between revisions of 'Publications' - RedwoodCenter
G. Agarwal, I. H. Stevenson, A. Berényi, K. Mizuseki, G. Buzsáki, F. T. Sommer: Spatially distributed local fields in the hippocampus encode rat position. Science 344 (2014): 626-630. pdf Supplement J. P. Crutchfield, R. G. James, S. Marzen and D. P. Varn, "Understanding and Designing Complex Systems: Response to A framework for optimal high-level descriptions in science and engineering---preliminary report", (2014). arXiv link J. H. Engel, S. B. Eryilmaz, SangBum Kim, M. BrightSky, Chung Lam, H.-L. Lung, B. A. Olshausen, H.-S.P. Wong (2014) "Capacity optimization of emerging mem- ory systems: A shannon-inspired approach to device characterization," Electron Devices Meeting (IEDM), 2014 IEEE International , vol., no., pp.29.4.1,29.4.4, 15- 17 Dec. 2014 link A. K. Fletcher and S. Rangan, Scalable Inference for Neuronal Connectivity from Calcium Imaging, Proc. 28th Ann. Conf. Neural Information Processing Systems, NIPS (2014). Harper NS, Scott BH, Semple MN, McAlpine D (2014) The neural code ...
Re: erfc() behavior changeRe: erfc() behavior change
On Thu, May 12, 2005 at 10:47:13AM +0200, Karim Belabas wrote: , Indeed. As for the ridiculous accuracy of %3 above, we have conflicting , specifications: , 1) PARI functions give as precise a result as is possible from the input, , 2) floating point computations are meant to foster speed by truncating , operands. , , Only 1) is specified in the documentation, 2) is only a general understanding. , And a rather misleading one as far as PARI is concerned; it is a common , source of misapprehension to assume that , , * realprecision is the relative accuracy used to truncate operands in 2). , Which it is not: it is used to convert exact objects to inexact ones. , , * operands with n digits of accuracy will yield a result with at most the , same accuracy. Which is wrong: indeed 1 + 1e-50000 may be computed to , more than 50000 digits of accuracy. The IEEE754 specification and the MPFR extension say the the correct result is the representable number the closest to the actual result, assuming the ...
Learning, self-organisation and homeostasis in spiking neuron networks using spike-timing dependent plasticityLearning, self-organisation and homeostasis in spiking neuron networks using spike-timing dependent plasticity
Spike-timing dependent plasticity is a learning mechanism used extensively within neural modelling. The learning rule has been shown to allow a neuron to find the onset of a spatio-temporal pattern repeated among its afferents. In this thesis, the first question addressed is what does this neuron learn? With a spiking neuron model and linear prediction, evidence is adduced that the neuron learns two components: (1) the level of average background activity and (2) specific spike times of a pattern. Taking advantage of these findings, a network is developed that can train recognisers for longer spatio-temporal input signals using spike-timing dependent plasticity. Using a number of neurons that are mutually connected by plastic synapses and subject to a global winner-takes-all mechanism, chains of neurons can form where each neuron is selective to a different segment of a repeating input pattern, and the neurons are feedforwardly connected in such a way that both the correct stimulus and the ...
Estimating Information Rates with Confidence Intervals in Neural Spike Trains | MIT CogNetEstimating Information Rates with Confidence Intervals in Neural Spike Trains | MIT CogNet
Information theory provides a natural set of statistics to quantify the amount of knowledge a neuron conveys about a stimulus. A related work (Kennel, Shlens, Abarbanel, & Chichilnisky, 2005) demonstrated how to reliably estimate, with a Bayesian confidence interval, the entropy rate from a discrete, observed time series. We extend this method to measure the rate of novel information that a neural spike train encodes about a stimulus-the average and specific mutual information rates. Our estimator makes few assumptions about the underlying neural dynamics, shows excellent performance in experimentally relevant regimes, and uniquely provides confidence intervals bounding the range of information rates compatible with the observed spike train. We validate this estimator with simulations of spike trains and highlight how stimulus parameters affect its convergence in bias and variance. Finally, we apply these ideas to a recording from a guinea pig retinal ganglion cell and compare results to a ...
A neuronal network model of macaque primary visual cortex (V1): Orientation selectivity and dynamics in the input layer 4Cα |...A neuronal network model of macaque primary visual cortex (V1): Orientation selectivity and dynamics in the input layer 4Cα |...
This paper describes the performance of a neuronal network model of the input layer 4Cα of macaque V1. This model differs from others in the literature in several ways. (i) It is designed largely from data for the anatomy and physiology of layer 4Cα of macaque (i.e., length scales and patterning of connectivity, and pinwheel centers). (ii) It uses cortical coordinates rather than idealized coordinates as in "ring models" (7, 8, 28) or "near-ring models" (9), whose coordinate labels are angles of orientation preference, rather than cortical locations within the layer. (iii) It has only short-range local inhibition, which is consistent with anatomical data, rather than an inhibition which is explicitly long-range in orientation preference, as is standard for many models (7-9, 31). (iv) It uses membrane potential, driven by synaptic conductances, as the fundamental variables, rather than activities or mean firing rates (7, 8, 32), or a probabilistic "population-density" representation (31, 33, ...
Non-smooth dynamics in integrate-and-fire neuron models with dynamic thresholdNon-smooth dynamics in integrate-and-fire neuron models with dynamic threshold
The aim of this work is to introduce and study simple neuron models with a dynamic threshold: The integrate and fire with dynamic threshold and a resonate and fire with dynamic threshold. The last model is a new model raised from an initial study of the integrate and fire with a dynamic threshold. The characteristics of the new model are studied from a mathematical point of view specially concerning the dynamical systems theory of the non-smooth systems. . In this project we will study analytically and computationally integrate-and-fire models with dynamic threshold, reproducing behaviors observed in the real nervoussystems, using techniques from non-smooth systems. Our goal is to describe the types of spiking patterns that can generate in response to steady and periodic current ...
Map-Seeking Circuits in Visual Cognition: A Computational Mechanism for Biological and Machine VisionMap-Seeking Circuits in Visual Cognition: A Computational Mechanism for Biological and Machine Vision
Finden Sie alle Bücher von Arathorn, David Y.; Arathorn, D. W. - Map-Seeking Circuits in Visual Cognition: A Computational Mechanism for Biological and Machine Vision. Bei der Büchersuchmaschine eurobuch.com können Sie antiquarische und Neubücher VERGLEICHEN UND SOFORT zum Bestpreis bestellen. 9780804742771
SNSF | P3 Research Database | Project 118395SNSF | P3 Research Database | Project 118395
Background. Synaptic plasticity is thought to be the cellular correlate for the formation of memory traces in the brain. Recently, spike-timing dependent plasticity has gained increased interest as a plausible physiological mechanism for the activity-dependent modification of synaptic strength. It might be fundamental for circuit refinement, map plasticity and the explanation of higher brain functions. It is not clear if spike-timing dependent plasticity is a universal learning rule based on simple biophysical mechanisms. The molecular signalling pathways involved are quite diverse and apparently use-dependent. The fundamental question is what determines the molecular machinery at a synaptic contact that translates electrical activity into a change in synaptic strength.Specific Aims. (1) The influence of active dendritic properties, which can result in the generation of local dendritic spikes, on changes in synaptic strength will be studied. They will have an important impact on the local ...
PPT - WK7 - Hebbian Learning PowerPoint Presentation - ID:6779351PPT - WK7 - Hebbian Learning PowerPoint Presentation - ID:6779351
WK7 - Hebbian Learning. CS 476: Networks of Neural Computation WK7 - Hebbian Learning Dr. Stathis Kasderidis Dept. of Computer Science University of Crete Spring Semester, 2009. Contents. Introduction to Hebbian Learning Definitions on Pattern Association Pattern Association Network Slideshow 6779351 by sylvana-silas
Awesome Computational Neuroscience | Curated list of awesome lists | Project-Awesome.orgAwesome Computational Neuroscience | Curated list of awesome lists | Project-Awesome.org
To contribute, see :pencil2: code of contribution. Computational neuroscience is a multidisciplinary science that joins biology/neuroscience, medicine, biophysics, psychology, computer science, mathematics, and statistics to study the nervous system using computational approaches.. This list of schools and researchers in computational neuroscience, theoretical neuroscience, (and systems neuroscience) aims to give a global perspective of researchers in the field, make it easier to apply to the listed institutions, and also provide a reasonable way to find an advisor.. In addition to names of PIs, excerpts of their academic biographies, and links to their publications, many of the researchers are qualified with a small scale "+/=/- computational." The metric is subjective to the editor of that material but it generally breaks down as: (+) refers to a researcher the university identifies as a computational neuroscientist, their bio consistently identifies a significant component of their research ...
Frontiers | Stochastic variational learning in recurrent spiking networks | Frontiers in Computational NeuroscienceFrontiers | Stochastic variational learning in recurrent spiking networks | Frontiers in Computational Neuroscience
The ability to learn and perform statistical inference with biologically plausible recurrent network of spiking neurons is an important step towards understanding perception and reasoning. Here we derive and investigate a new learning rule for recurrent spiking networks with hidden neurons, combining principles from variational learning and reinforcement learning. Our network defines a generative model over spike train histories and the derived learning rule has the form of a local Spike Timing Dependent Plasticity rule modulated by global factors (neuromodulators) conveying information about ``novelty on a statistically rigorous ground.Simulations show that our model is able to learn bothstationary and non-stationary patterns of spike trains.We also propose one experiment that could potentially be performed with animals in order to test the dynamics of the predicted novelty signal.
Computational Neuroscience (ebook) by Jianfeng Feng | 9780203494462Computational Neuroscience (ebook) by Jianfeng Feng | 9780203494462
Buy, download and read Computational Neuroscience ebook online in PDF format for iPhone, iPad, Android, Computer and Mobile readers. Author: Jianfeng Feng. ISBN: 9780203494462. Publisher: CRC Press. How does the brain work? After a century of research, we still lack a coherent view of how neurons process signals and control our activities. But as the field of computational neuroscience continues
Emergent auditory feature tuning in a real-time neuromorphic VLSI systemEmergent auditory feature tuning in a real-time neuromorphic VLSI system
Many sounds of ecological importance, such as communication calls, are characterised by time-varying spectra. However, most neuromorphic auditory models to date have focused on distinguishing mainly static patterns, under the assumption that dynamic patterns can be learned as sequences of static ones. In contrast, the emergence of dynamic feature sensitivity through exposure to formative stimuli has been recently modeled in a network of spiking neurons based on the thalamocortical architecture. The proposed network models the effect of lateral and recurrent connections between cortical layers, distance-dependent axonal transmission delays, and learning in the form of Spike Timing Dependent Plasticity (STDP), which effects stimulus-driven changes in the pattern of network connectivity. In this paper we demonstrate how these principles can be efficiently implemented in neuromorphic hardware. In doing so we address two principle problems in the design of neuromorphic systems: real-time event-based ...
Response of integrate-and-fire neurons to noisy inputs filtered by synapses with arbitrary timescales: firing rate and...Response of integrate-and-fire neurons to noisy inputs filtered by synapses with arbitrary timescales: firing rate and...
Here, based on our previous work on linear synaptic filtering [1-3], we build a general theory for the stationary firing response of integrate-and-fire (IF) neurons receiving stochastic inputs filtered by one, two or multiple synaptic channels each characterized by an arbitrary timescale. The formalism applies to arbitrary IF model neurons, and to arbitrary forms of input noise (i.e., not required to be Gaussian or to have small amplitude), as well as to any form of synaptic filtering (linear or non-linear). The theory determines with exact analytical expressions the firing rate of an IF neuron for long synaptic time constants using the adiabatic approach. The correlated spiking (cross-correlations function) of two neurons receiving common as well as independent sources of noise is also described (see figure 1). The theory is exemplified using leaky, quadratic and noise thresholded IF neurons (LIF, QIF, NTIF). Although the adiabatic approach is exact when at least one of the synaptic timescales ...
Fundamentals of Computational Neuroscience - Thomas Trappenberg - Oxford University PressFundamentals of Computational Neuroscience - Thomas Trappenberg - Oxford University Press
Computational neuroscience is the theoretical study of the brain to uncover the principles and mechanisms that guide the development, organization, information processing, and mental functions of the nervous system. Although not a new area, it is only recently that enough knowledge has been gathered to establish computational neuroscience as a scientific discipline in its own right.
Novel VLSI implementation for triplet-based spike-timing dependent plasticityNovel VLSI implementation for triplet-based spike-timing dependent plasticity
A free platform for explaining your research in plain language, and managing how you communicate around it - so you can understand how best to increase its impact.
Reliability of Spike Timing Is a General Property of Spiking Model Neurons | MIT CogNetReliability of Spike Timing Is a General Property of Spiking Model Neurons | MIT CogNet
The responses of neurons to time-varying injected currents are reproducible on a trial-by-trial basis in vitro, but when a constant current is injected, small variances in interspike intervals across trials add up, eventually leading to a high variance in spike timing. It is unclear whether this difference is due to the nature of the input currents or the intrinsic properties of the neurons. Neuron responses can fail to be reproducible in two ways: dynamical noise can accumulate over time and lead to a desynchronization over trials, or several stable responses can exist, depending on the initial condition. Here we show, through simulations and theoretical considerations, that for a general class of spiking neuron models, which includes, in particular, the leaky integrate-and-fire model as well as nonlinear spiking models, aperiodic currents, contrary to periodic currents, induce reproducible responses, which are stable under noise, change in initial conditions and deterministic perturbations of ...
State-Space Analysis of Time-Varying Higher-Order Spike Correlation for Multiple Neural Spike Train DataState-Space Analysis of Time-Varying Higher-Order Spike Correlation for Multiple Neural Spike Train Data
Precise spike coordination between the spiking activities of multiple neurons is suggested as an indication of coordinated network activity in active cell assemblies. Spike correlation analysis aims to identify such cooperative network activity by detecting excess spike synchrony in simultaneously recorded multiple neural spike sequences. Cooperative activity is expected to organize dynamically during behavior and cognition; therefore currently available analysis techniques must be extended to enable the estimation of multiple time-varying spike interactions between neurons simultaneously. In particular, new methods must take advantage of the simultaneous observations of multiple neurons by addressing their higher-order dependencies, which cannot be revealed by pairwise analyses alone. In this paper, we develop a method for estimating time-varying spike interactions by means of a state-space analysis. Discretized parallel spike sequences are modeled as multi-variate binary processes using a ...
Stationary and nonstationary nonlinear dynamic modeling of hippocampal neural population activity :: University of Southern...Stationary and nonstationary nonlinear dynamic modeling of hippocampal neural population activity :: University of Southern...
The brain orchestrates perceptions, thoughts, and actions through the ensemble spiking activity of its neurons. Biological processes underlying spike transformations across brain regions, including synaptic transmissions, dendritic integrations, and spike generations, are highly nonlinear dynamical processes and are often nonstationary. For example, it is well established that certain forms of plasticity, such as long-term potentiation (LTP) and long-term depression (LTD), occur in response to specific input patterns, and plasticity is manifested as a change in input-output function that can be viewed as a system nonstationarity. Quantitative studies of how such functions of information transmission across brain regions evolve during behavior are required in order to understand the brain. In this project, we developed a nonstationary modeling framework for the multiple-spike activity propagations between brain regions. ❧ In this study, in order to analyze the nonlinear dynamics underlying ...
Stationary and nonstationary nonlinear dynamic modeling of hippocampal neural population activity :: University of Southern...Stationary and nonstationary nonlinear dynamic modeling of hippocampal neural population activity :: University of Southern...
The brain orchestrates perceptions, thoughts, and actions through the ensemble spiking activity of its neurons. Biological processes underlying spike transformations across brain regions, including synaptic transmissions, dendritic integrations, and spike generations, are highly nonlinear dynamical processes and are often nonstationary. For example, it is well established that certain forms of plasticity, such as long-term potentiation (LTP) and long-term depression (LTD), occur in response to specific input patterns, and plasticity is manifested as a change in input-output function that can be viewed as a system nonstationarity. Quantitative studies of how such functions of information transmission across brain regions evolve during behavior are required in order to understand the brain. In this project, we developed a nonstationary modeling framework for the multiple-spike activity propagations between brain regions. ❧ In this study, in order to analyze the nonlinear dynamics underlying ...
Link to this page, e.g. for bookmarkingLink to this page, e.g. for bookmarking
Transmission of signals within the brain is essential for cognitive function, but it is not clear how neural circuits support reliable and accurate signal propagation over a sufficiently large dynamic range. Two modes of propagation have been studied: synfire chains, in which synchronous activity travels through feedforward layers of a neuronal network, and the propagation of fluctuations in firing rate across these layers. In both cases, a sufficient amount of noise, which was added to previous models from an external source, had to be included to support stable propagation. Sparse, randomly connected networks of spiking model neurons can generate chaotic patterns of activity. We investigate whether this activity, which is a more realistic noise source, is sufficient to allow for signal transmission. We find that, for rate-coded signals but not for synfire chains, such networks support robust and accurate signal reproduction through up to six layers if appropriate adjustments are made in ...
User:Andrey Shilnikov/Proposed/Multi-stability in neuronal models - ScholarpediaUser:Andrey Shilnikov/Proposed/Multi-stability in neuronal models - Scholarpedia
Multistability remains an intriguing phenomenon for neuroscience. The functional roles of multistability in neural systems are not well understood. On the other hand, its pathological roles are widely discussed in recent studies. Knowledge of the dynamic mechanisms supporting multistability opens new horizons for medical applications. It has been intensively targeted in a search for new treatments of the medical conditions which are caused by malfunction of the dynamics of the CNS. Sudden infant death syndrome, epilepsy and Parkinsons disease are examples of such conditions. Recent progress in the modern technology of computer-brain interface based on real time systems allows to utilize complex feedback stimulation algorithms suppressing pathological regime co-existing with the normal one. It still remains a challenge to identify the scenarios leading to the multistability in the neuronal dynamics and discuss what are potential roles of the multistability in the operation of the central nervous ...
Galves-Löcherbach model - WikipediaGalves-Löcherbach model - Wikipedia
The GL model was defined in 2013 by mathematicians Antonio Galves and Eva Löcherbach.[1] Its inspirations included Frank Spitzers interacting particle system and Jorma Rissanens notion of stochastic chain with memory of variable length. Another work that influenced this model was Bruno Cessacs study on the leaky integrate-and-fire model, who himself was influenced by Hédi Soula.[4] Galves and Löcherbach referred to the process that Cessac described as "a version in a finite dimension" of their own probabilistic model. Prior integrate-and-fire models with stochastic characteristics relied on including a noise to simulate stochasticity.[5] The Galves-Löcherbach model distinguishes itself because it is inherently stochastic, incorporating probabilistic measures directly in the calculation of spikes. It is also a model that may be applied relatively easily, from a computational standpoint, with a good ratio between cost and efficiency. It remains a non-Markovian model, since the probability ...
Patent US7590728 - System and method for detection of aberrant network behavior by clients of a ... - Google PatentsPatent US7590728 - System and method for detection of aberrant network behavior by clients of a ... - Google Patents
A system and method for detecting aberrant network behavior. One embodiment provides a system of detecting aberrant network behavior behind a network access gateway comprising a processor, a first network interface coupled to the processor, a second network interface coupled to the processor, a storage media accessible by the processor and a set of computer instructions executable by the processor. The computer instructions can be executable to observe network communications arriving at the first network interface from multiple clients and determine when the traffic of a particular client is indicative of malware infection or other hostile network activity. If the suspicious network communication is determined to be of a sufficient volume, type, or duration the computer instructions can be executable to log such activity to storage media, or to notify an administrative entity via either the first network interface or second network interface, or to make the computer instructions be executable to perform
PPT - Correlated neuronal activity and the flow of neural information PowerPoint Presentation - ID:6735842PPT - Correlated neuronal activity and the flow of neural information PowerPoint Presentation - ID:6735842
Correlated neuronal activity and the flow of neural information. Jaeseung Jeong, Ph.D Department of Bio and Brain Engineering. Nonlinear information transmission of the cerebral cortex. Conventional measure: cross-correlation. Slideshow 6735842 by alana-fulton
DSpace@MIT: A hierarchical model of peripheral vision[email protected]: A hierarchical model of peripheral vision
We present a peripheral vision model inspired by the cortical architecture discovered by Hubel and Wiesel. As with existing cortical models, this model contains alternating layers of simple cells, which employ tuning functions to increase specificity, and complex cells, which pool over simple cells to increase invariance. To extend the traditional cortical model, we introduce the option of eccentricity-dependent pooling and tuning parameters within a given model layer. This peripheral vision system can be used to model physiological data where receptive field sizes change as a function of eccentricity. This gives the user flexibility to test different theories about filtering and pooling ranges in the periphery. In a specific instantiation of the model, pooling and tuning parameters can increase linearly with eccentricity to model physiological data found in different layers of the visual cortex. Additionally, it can be used to introduce pre-cortical model layers such as retina and LGN. We have ...
MSc Systems Neuroscience - Masters courses - Postgraduate study - Psychology - The University of SheffieldMSc Systems Neuroscience - Masters courses - Postgraduate study - Psychology - The University of Sheffield
This 12-month course is designed to provide you with in-depth training into the core problems in systems neuroscience, and will develop your understanding of the disciplines and techniques used to address these problems such as computer simulation modelling, data visualisation and neuroanatomy.. In semester one youll build on your existing knowledge, giving you a thorough understanding of the fundamentals of neuroscience, computational neuroscience and mathematical modelling. Once youve developed a solid foundation in these areas at the core of systems neuroscience, semester two will be devoted to advanced modules where youll tailor your learning and choose to specialise in one of two distinct routes of study: pathway 1 or pathway 2.. Pathway 1 will train you in methods for visualising brain networks, including electrophysiology, optical imaging, and functional magnetic resonance imaging, as well as experimental protocols. Pathway 2 will build on your theoretical skills in this area of ...
Chemical Aspects of Neuronal Information Transmission in Synapses | SpringerLinkChemical Aspects of Neuronal Information Transmission in Synapses | SpringerLink
The totality of mechanisms involved in the process of information transmission is immensely complex, comprised as it is of biochemical, biophysical, and ultrastructural elements. More-over, these are...
Tinnitus Measured by MEG and Synchronous Neural Interaction™ Test: Template Development - Full Text View - ClinicalTrials.govTinnitus Measured by MEG and Synchronous Neural Interaction™ Test: Template Development - Full Text View - ClinicalTrials.gov
The study is designed to identify specific patterns of brain functional activity associated with chronic, moderate to severe tinnitus through the use of resting-state MEG scans. Robust patterns identified in this study will be used as a biomarker for subsequent clinical evaluation of experimental drug treatments for tinnitus. This study will conduct MEG scans on approximately 30 to 75 subjects with tinnitus and approximately 15 healthy control subjects. MEG scans will be obtained for each subject following screening, clinical and tinnitus evaluations. A subset of 6 subjects from the tinnitus cohort will be invited to undergo evoked auditory assessment during an extended MEG scan session to identify cortical regions that respond to the auditory stimulus. These six subjects also will be evaluated with a single structural MRI scan to support high-resolution mapping of the localized cortical regions. MEG data will be analyzed to identify patterns of brain activity that are specifically associated ...
Spatiotemporal Stochastic Resonance and its consequences in a neural systemSpatiotemporal Stochastic Resonance and its consequences in a neural system
Biological neurons are good examples of a threshold deviceâ€"this is why neural systems are in the focus when looking for realization of Stochastic Resonance (SR) and Spatiotemporal Stochastic Resonance (STSR) phenomena. There are two different ways to simulate neural systemsâ€"one based on differential equations, the other based on a simple threshold model. In this talk the effect of noise on neural systems will be discussed using both ways of modelling. The results so far suggest that SR and STSR do occur in models of neural systems. However, how significant is the role played by these phenomena and what implications might they have on neurobiology is still a question. © 2000 American Institute of Physics ...
Neural Information Processing | Springer for Research & DevelopmentNeural Information Processing | Springer for Research & Development
It is our great pleasure to welcome you to the 11th International Conference on Neural Information Processing (ICONIP 2004) to be held in Calcutta. ICONIP 2004 is organized jointly by the Indian Stati
Learning & MemoryLearning & Memory
20) Spike-timing dependent plasticity: Getting the brain from correlation to causation (Levy - 1983, Sakmann - 1994, Bi & Poo - 1998, Dan - 2002). Hebbs original proposal was worded as such: When an axon of cell A is near enough to excite a cell B and repeatedly or persistently takes part in firing it, some growth process or metabolic change takes place in one or both cells such that As efficiency, as one of the cells firing B, is increased. [emphasis added]. The phrase takes part in firing implies causation of Bs activity via As activity, not simply a correlation of the two.. There are several ways to go beyond correlation to infer causation. One method is to observe that one event (e.g., cell As activity) comes just before the caused event (e.g., cell Bs activity).. In 1983 Levy showed with hippocampal slices that electrically stimulating cell A to fire before cell B will cause long-lasting strengthening of the synapse from cell A to cell B. However, when the opposite occurs, and ...
Neural Interaction in Periods of SilenceNeural Interaction in Periods of Silence
Scientists from the Max Planck Institute for Biological Cybernetics have now developed a novel multimodal methodology called "neural event-triggered functional magnetic resonance imaging" (NET-fMRI) and presented the very first results obtained using it in experiments with both anesthetized and awake, behaving monkeys. The new methodology uses multiple-contact electrodes in combination with functional magnetic resonance imaging (fMRI) of the entire brain to map widespread networks of neurons that are activated by local, structure-specific neural events. Many invasive studies in nonhuman primates and clinical investigations in human patients have demonstrated that the hippocampus, one of the oldest, most primitive brain structures, is largely responsible for the long term retention of information regarding places, specific events, and their contexts, that is, for the retention of so-called declarative memories. Without the hippocampus a person may be able to learn a manual task over a period of ...
Computational Neuroscience: [Comp-neuro] 2 Postdoc positions, Insect Robotics Group, EdinburghComputational Neuroscience: [Comp-neuro] 2 Postdoc positions, Insect Robotics Group, Edinburgh
RA1 will take a leading role in the development of the neural circuit model. This will be a spiking neural model that copies one-to-one the neurons in the olfactory learning pathway of Drosophila larvae. It will be interfaced to a behavioural simulation, and to a robot model, and will be used to test hypotheses about the key mechanisms and locations of synaptic modification, and how the acquisition of associations interacts with behavioural control. Predictions from the model will be tested by our project partners using neurogenetic methods to measure and alter neural function in freely behaving animals ...
Trevor Bekolay - MendeleyTrevor Bekolay - Mendeley
Connect and collaborate with Trevor Bekolay, with research interests in Long-term memory and Spike-timing dependent plasticity, on Mendeley.
home [Computational neurophysiology group]home [Computational neurophysiology group]
In particular, we would like to understand how neurons are optimized for their computational task. Therefore, we investigate the relationship between intrinsic neuronal properties and the signaling mechanisms shaped by them, as well as their relevance for network behavior. The aim is to link the molecular level of ion channels to characteristics of neuronal firing, focusing on topics like information transfer, synchronization, energy efficiency, and temperature robustness. To identify computational principles, conductance-based and phenomenological models are used in combination with data evaluation techniques and analytical approaches. We closely cooperate with experimental groups in order to test theoretical predictions ...
References for dependencies in statistics of spike trains?References for dependencies in statistics of spike trains?
schmitt at cs.unc.edu (Charles Schmitt) wrote: ,Can anyone suggest what would be good review articles or book (chapters) ,describing how measured postsynaptic spike trains have been observed ,to be dependent on presynaptic spike trains. What Im searching for ,is to strengthen my knowledge of what statistical measures of spike trains, ,such as mean frequency, inter-spike interval, etc..., have been used ,to describe postsynaptic spike trains and how these statistics have any ,observed dependency on the same presynaptic statistics. Im particularly ,interested in such observed dependencies in visual cortex. ,Thanks, Charlie. The initial work here was done for the spinomotor system. A good paper is by Cope, Fetz, and Matsumura, Cross-correlation assessment of synaptic strength of single Ia fibre connections with triceps surae motorneurons in cats, J. Physiol., 390:161-188, 1982. This is not an easy read, at first, but is worth it. (There is an older literature for this system: search Kirkwood, ...
entry - Computational Neuroscience Group (UPF)entry - Computational Neuroscience Group (UPF)
In my ongoing Ph.D. project, titled "Exploring the effective communication of brain network dynamics under different states", we carried the first research to demonstrate significant brain-wide integration changes during three cognitive tasks using intracranial EEG [1]. In a second study, we provided the first demonstration of a whole-brain model integrating anatomical connectivity, functional activity and neuromodulator receptor density from multimodal imaging of healthy human participants [2], and in a third study, we investigated the relevant timescale for understanding spatiotemporal dynamics across the whole brain. We introduced a novel way to generate whole-brain neural dynamical activity at the millisecond scale from fMRI signals, and using the independent measures of entropy and hierarchy to characterize the richness of the dynamical repertoire, we showed that both methods find a similar optimum at a timescale of around 200 ms in resting state and in task data [3].. 1. Cruzat, J., Deco, ...
Download Dynamic Neural Field Theory For Motion Perception 1999Download Dynamic Neural Field Theory For Motion Perception 1999
download Dynamic birth, confidence, limestone, oscillation, purpose and accordance floors. helicopter of an fourth download company of intentions, things, set events, 1960s and book, taken in Prophecy and large Consulting. published to Need children be the contemporary, new, custodial, chapters and people, displayed and other challenges.
Self-orthogonalizing strategies for enhancing Hebbian learning in recurrent neural networks - UBC Library Open CollectionsSelf-orthogonalizing strategies for enhancing Hebbian learning in recurrent neural networks - UBC Library Open Collections
Learning, knowledge, research, insight: welcome to the world of UBC Library, the second-largest academic research library in Canada.
Mechanisms underlying cortical activity during value-guided choice. - Oxford NeuroscienceMechanisms underlying cortical activity during value-guided choice. - Oxford Neuroscience
When choosing between two options, correlates of their value are represented in neural activity throughout the brain. Whether these representations reflect activity that is fundamental to the computational process of value comparison, as opposed to other computations covarying with value, is unknown. We investigated activity in a biophysically plausible network model that transforms inputs relating to value into categorical choices. A set of characteristic time-varying signals emerged that reflect value comparison. We tested these model predictions using magnetoencephalography data recorded from human subjects performing value-guided decisions. Parietal and prefrontal signals matched closely with model predictions. These results provide a mechanistic explanation of neural signals recorded during value-guided choice and a means of distinguishing computational roles of different cortical regions whose activity covaries with value.
Following stage II retinal waves during development with a biophysical modelFollowing stage II retinal waves during development with a biophysical model
Retinal waves are bursts of activity occurring spontaneously in the developing retina of vertebrate species, contributing to the shaping of the visual system organization and disappear short after birth. Waves during development are a transient process which evolves dynamically exhibiting different features. Based on our previous modelling work [1,2], we now propose a classification of stage II retinal waves patterns as a function of acetylcholine coupling strength and a possible mechanism for waves generation. Our model predicts that spatiotemporal patterns evolve upon maturation or pharmacological manipulation and that waves emerge from a complete homogeneous state without the need of the variability of a neural population. Context & Motivation SACs dynamically change their synaptic coupling upon maturation Coupled cholinergic SACs [3] Cholinergic current evolution upon maturation [4]-70 mV 60mV 0 0.8 88 nM 300 nM 0.2 0.4 0.4 0.2 Bursting sAHP Increase of Calcium load during bursting Calcium controls
Integrative Pharmacology and Systems NeuroscienceIntegrative Pharmacology and Systems Neuroscience
The Integrative Pharmacology and Systems Neuroscience Groups main line of research is the development of pharmacological and non-pharmacological (cognitive/electrical stimulation) approaches for the treatment of diseases that cause intellectual disability or cognitive impairment and psychiatric disorders (including Down syndrome, drug addiction, depression, schizophrenia, or dementia). Our emphasis is on understanding the underlying mechanisms of action and on developing treatments, biomarkers of exposure, efficacy and toxicity.. Moreover, the group is responsible for providing instruction in pharmacology, chemistry and toxicology to graduate and undergraduate students of both human biology and medicine tracks (Pompeu Fabra University, Autonomous University of Barcelona), and to train pre-doctoral and postdoctoral researchers.. The Integrative Pharmacology and Systems Neuroscience Group and the Proteomics Research Group from the Pompeu Fabra University constitute the BAPP (Bioanalysis, ...
Systems neuroscience (eBook, 2018) [WorldCat.org]Systems neuroscience (eBook, 2018) [WorldCat.org]
Get this from a library! Systems neuroscience. [Albert C H Yu; Lina Li;] -- This edition of Advances in Neurobiology brings together experts in the emerging field of Systems Neuroscience to present an overview of this area of research. Topics covered include: how different ...
Otsikoimaton raporttiOtsikoimaton raportti
Acimovic, J., Mäki-Marttunen, T., & Linne, M-L. (2011). Computational study of structural changes in neuronal networks during growth: a model of dissociated neocortical cultures. teoksessa J-M. Fellous, & A. Prinz (Toimittajat), Twentieth Annual Computational Neuroscience Meeting: CNS*2011 (Vuosikerta 12 (Suppl 1), Sivut P203). [P203] (Annual Computational Neuroscience Meeting CNS; Vuosikerta 12). Stockholm: BioMed Central. https://doi.org/10.1186/1471-2202-12-S1-P203 ...
Why neurons mix: high dimensionality for higher cognitionWhy neurons mix: high dimensionality for higher cognition
Neurons often respond to diverse combinations of task-relevant variables. This form of mixed selectivity plays an important computational role which is related to the dimensionality of the neural representations: high-dimensional representations with mixed selectivity allow a simple linear readout t …
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Deep brain stimulation - Simple English Wikipedia, the free encyclopediaDeep brain stimulation - Simple English Wikipedia, the free encyclopedia
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ICD-10 Chapter V: Mental and behavioural disordersICD-10 Chapter V: Mental and behavioural disorders
Schizophrenia - Simple English Wikipedia, the free encyclopediaSchizophrenia - Simple English Wikipedia, the free encyclopedia
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The Silent ScreamThe Silent Scream
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Outline of brain mappingOutline of brain mapping
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Kasutaja:Mariina/Lapseea aktiivsus- ja tähelepanuhäire - VikipeediaKasutaja:Mariina/Lapseea aktiivsus- ja tähelepanuhäire - Vikipeedia
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Periodicals as TopicAccess to InformationStem CellsJournal Impact FactorBibliometricsPublishingPeer Review, ResearchAlphavirusAlphavirus InfectionsSindbis VirusEncephalitis, ViralStartle ReactionSensory GatingEncephalitis Virus, Venezuelan EquineGlycine-tRNA LigaseAlanine-tRNA LigaseTyrosine-tRNA LigaseCharcot-Marie-Tooth DiseaseRNA, Transfer, GlyAmino Acyl-tRNA SynthetasesPolitical SystemsInduced Pluripotent Stem CellsPluripotent Stem CellsNervous System DiseasesEmbryonic Stem CellsNuclear ReprogrammingCell DifferentiationArchivesBiological Science DisciplinesPubMedDirectories as TopicEuphoriaCocaineCocaine-Related DisordersMissouriCommodificationAlcoholicsSelf AdministrationLevocardiaModels, NeurologicalNeurosciencesFunctional LateralityTheory of MindBrain MappingBrainSchizophreniaPseudobulbar PalsyLaughterPsychotic DisordersSchizophrenic PsychologyREM Sleep Parasomnias
Data-driven models for Progression Of Neurological Disease | Projects | H2020 | CORDIS | European CommissionData-driven models for Progression Of Neurological Disease | Projects | H2020 | CORDIS | European Commission
Phenogenetic map created for stem cells models of neurological diseases | EurekAlert! Science NewsPhenogenetic map created for stem cells models of neurological diseases | EurekAlert! Science News
Stem Cells in Large Animal Models of Retinal and Neurological DiseaseStem Cells in Large Animal Models of Retinal and Neurological Disease
Modeling Neurological Disorders by Human Induced Pluripotent Stem CellsModeling Neurological Disorders by Human Induced Pluripotent Stem Cells
Novel stem cell-derived model created of inflammatory neurological disorder | EurekAlert! Science NewsNovel stem cell-derived model created of inflammatory neurological disorder | EurekAlert! Science News
NINDS Supports Outstanding Projects Using Invertebrate Model Systems | National Institute of Neurological Disorders and StrokeNINDS Supports Outstanding Projects Using Invertebrate Model Systems | National Institute of Neurological Disorders and Stroke
Toxin-Induced Models of Neurological Disorders | Springer for Research & DevelopmentToxin-Induced Models of Neurological Disorders | Springer for Research & Development
Frontiers | Mouse Model of Neurological Complications Resulting from Encephalitic Alphavirus Infection | MicrobiologyFrontiers | Mouse Model of Neurological Complications Resulting from Encephalitic Alphavirus Infection | Microbiology
British Library EThOS: Glycyl-tRNA synthetase mutations in neurological disease : mechanisms and modelsBritish Library EThOS: Glycyl-tRNA synthetase mutations in neurological disease : mechanisms and models
Frontiers | Stem cell transplantation in neurological diseases: improving effectiveness in animal models | Cell and...Frontiers | Stem cell transplantation in neurological diseases: improving effectiveness in animal models | Cell and...
DTI connectomics in mouse models of neurological disorders - Webinars | BrukerDTI connectomics in mouse models of neurological disorders - Webinars | Bruker
Carondelet Becomes Global Model for Neurological Care - BizTUCSONCarondelet Becomes Global Model for Neurological Care - BizTUCSON
Cellular reprogramming: recent advances in modeling neurological diseasesCellular reprogramming: recent advances in modeling neurological diseases
Computer Modeling Shows Neurological Changes in Cocaine AddictsComputer Modeling Shows Neurological Changes in Cocaine Addicts
Accelerated Tau Aggregation, Apoptosis and Neurological Dysfunction Caused by Chronic Oral Administration of Aluminum in a...Accelerated Tau Aggregation, Apoptosis and Neurological Dysfunction Caused by Chronic Oral Administration of Aluminum in a...
Neuroscience Confirms Julian Jayness Neurological Model | Julian Jaynes SocietyNeuroscience Confirms Julian Jaynes's Neurological Model | Julian Jaynes Society
Medicines | Free Full-Text | Zebrafish as an Emerging Model for Bioassay-Guided Natural Product Drug Discovery for Neurological...Medicines | Free Full-Text | Zebrafish as an Emerging Model for Bioassay-Guided Natural Product Drug Discovery for Neurological...
Animal Models of Neurological Disease, II: Metabolic Encephalopathies and Epilepsies - Alan A. Boulton; Glen B. Baker; Roger F....Animal Models of Neurological Disease, II: Metabolic Encephalopathies and Epilepsies - Alan A. Boulton; Glen B. Baker; Roger F....
From Pluripotent Stem Cells to Neurons and Astrocytes - Modeling Human Neurological DiseaseFrom Pluripotent Stem Cells to Neurons and Astrocytes - Modeling Human Neurological Disease
JDB | Free Full-Text | Drosophila as a Model for Assessing the Function of RNA-Binding Proteins during Neurogenesis and...JDB | Free Full-Text | Drosophila as a Model for Assessing the Function of RNA-Binding Proteins during Neurogenesis and...
Modeling the Neurological Basis and Characterizing the Neurological Phenotype of Obesity Using Human Neural Stem Cells - Full...Modeling the Neurological Basis and Characterizing the Neurological Phenotype of Obesity Using Human Neural Stem Cells - Full...
Researchers develop new model to study schizophrenia and other neurological conditionsResearchers develop new model to study schizophrenia and other neurological conditions
Phenogenetic Map Created For Stem Cell Models Of Neurological DiseasesPhenogenetic Map Created For Stem Cell Models Of Neurological Diseases
Emotional processing in functional neurological disorder: a review, biopsychosocial model and research agenda | Journal of...Emotional processing in functional neurological disorder: a review, biopsychosocial model and research agenda | Journal of...
Wavelet-Chaos-Neural Network Models for EEG-Based Diagnosis of Neurological Disorders | Springer for Research & DevelopmentWavelet-Chaos-Neural Network Models for EEG-Based Diagnosis of Neurological Disorders | Springer for Research & Development
Defining limits of treatment with humanized neutralizing monoclonal antibody for West Nile virus neurological infection in a...Defining limits of treatment with humanized neutralizing monoclonal antibody for West Nile virus neurological infection in a...
Building-associated neurological damage modeled in human cells: a mechanism of neurotoxic effects by exposure to mycotoxins in...Building-associated neurological damage modeled in human cells: a mechanism of neurotoxic effects by exposure to mycotoxins in...
iPhemap: an atlas of phenotype to genotype relationships of human iPSC models of neurological diseases | EMBO Molecular MedicineiPhemap: an atlas of phenotype to genotype relationships of human iPSC models of neurological diseases | EMBO Molecular Medicine
Investigation into the effects and mechanisms of rapamycin treatment in two mouse models of Complex I-deficient neurological...Investigation into the effects and mechanisms of rapamycin treatment in two mouse models of Complex I-deficient neurological...
FARA - Clinical data and characterization of the liver conditional mouse model exclude neoplasia as a non-neurological...FARA - Clinical data and characterization of the liver conditional mouse model exclude neoplasia as a non-neurological...
AnatomyOrganismsDiseasesChemicals and DrugsAnalytical, Diagnostic and Therapeutic Techniques and EquipmentPsychiatry and PsychologyPhenomena and ProcessesDisciplines and OccupationsAnthropology, Education, Sociology and Social PhenomenaTechnology, Industry, AgricultureHumanitiesInformation ScienceNamed GroupsHealth CareGeographicals
Periodicals as TopicAccess to InformationStem CellsJournal Impact FactorBibliometricsPublishingPeer Review, ResearchAlphavirusAlphavirus InfectionsSindbis VirusEncephalitis, ViralStartle ReactionSensory GatingEncephalitis Virus, Venezuelan EquineGlycine-tRNA LigaseAlanine-tRNA LigaseTyrosine-tRNA LigaseCharcot-Marie-Tooth DiseaseRNA, Transfer, GlyAmino Acyl-tRNA SynthetasesPolitical SystemsInduced Pluripotent Stem CellsPluripotent Stem CellsNervous System DiseasesEmbryonic Stem CellsNuclear ReprogrammingCell DifferentiationArchivesBiological Science DisciplinesPubMedDirectories as TopicEuphoriaCocaineCocaine-Related DisordersMissouriCommodificationAlcoholicsSelf AdministrationLevocardiaModels, NeurologicalNeurosciencesFunctional LateralityTheory of MindBrain MappingBrainSchizophreniaPseudobulbar PalsyLaughterPsychotic DisordersSchizophrenic PsychologyREM Sleep Parasomnias
Parkinson'sNeuronsDeficitsRodent modelsTherapiesAbstractStrokeLong-term neurologicalSchizophreniaIPSCLead to neurologicalMiceCerebralPhenotypeHumanBicameral mind theoryJaynes'sProgressionTumorAnimalPredictionBiomarkersComputationalCognitionNeuroscienceAbnormalitiesDisorderResearchHuntington's DiseaseStatisticalIPSCsInfectionExperimentalPhenotypesResearchersProgenitor cellsClinicalAutismAmeliorateMutationsStudyPathologyCellsPatient'sDysfunctionCharacterizeMouse models
Parkinson's6
Neurons4
  • Unfortunately, by the time the symptoms are evident, the neurological damage is already severe, with a massive loss of dopaminergic neurons in the substantia nigra ( Double, 2012 ). (frontiersin.org)
  • Now, University of Missouri researchers Ashwin Mohan and Sandeep Pendyam, doctoral students in the Department of Electrical and Computer Engineering , are utilizing computational models to study how the brain's chemicals and synaptic mechanisms, or connections between neurons, react to cocaine addiction and what this could mean for future therapies. (missouri.edu)
  • A study describing the characterization and validation of two neural progenitor cell models and their ability to differentiate into multiple types of neurons. (atcc.org)
  • Considering the sensitivity of neurons to hypoxic insult, the most beneficial therapeutic window for minimizing neurological deficit from stroke is the hyperacute period. (openneurologyjournal.com)
Deficits7
Rodent models3
Therapies4
Abstract2
Stroke9
  • Gait analysis as a method for assessing neurological outcome in a mouse model of stroke. (nih.gov)
  • In order to improve stroke outcome, novel treatment approaches as well as animal stroke models predictive for the clinical setting are of urgent need. (nih.gov)
  • One of the main obstacles in experimental stroke research is measuring long-term outcome, in particular in mouse models of stroke. (nih.gov)
  • After completing a PhD in the physics department of the University of Cologne and the Max-Planck-Institute for Neurological Research in Cologne, he transferred to the Experimental Neurology Department and the Center for Stroke Research at the Charité in Berlin to offer his expertise in small animal MRI and quickly became the scientific lead of the imaging core facility. (bruker.com)
  • Monoclonal antibody to the ICAM-1 adhesion site reduces neurological damage in a rabbit cerebral embolism stroke model. (curehunter.com)
  • We evaluated the effect of antibodies directed against a leukocyte adhesion molecule (ICAM-1) in an embolic model of stroke followed by thrombolysis with tissue plasminogen activator (tPA). (curehunter.com)
  • In an animal model for stroke, delta opioid peptide reduced by as much as 75 percent the damage to the brain's striatum, the deeper region of the brain and a major target for strokes, according to researchers. (scienceblog.com)
  • Recent animal experiments demonstrated that basic fibroblast growth factor-2 (FGF-2) can improve neurological function after stroke by the neuroprotective effect or vasodilating effect. (ahajournals.org)
  • Test DDFPe as neuroprotective agent in permanent occlusion rat stroke models in Sprague Dawley (SD) and Spontaneously Hypertensive Rats (SHR) measuring both %SV and neurological assessment scores (NAS). (openneurologyjournal.com)
Long-term neurological3
Schizophrenia1
IPSC1
Lead to neurological1
  • The constant activation of inflammatory and apoptotic pathways at low levels of exposure in human brain capillary endothelial cells, astrocytes, and neural progenitor cells may amplify devastation to neurological tissues and lead to neurological system cell damage from indirect events triggered by the presence of trichothecenes. (biomedsearch.com)
Mice10
  • Upon low-dose infection of wild-type C57B/6 mice, asymptomatic and symptomatic groups were established and compared to mock-infected mice to measure general health and baseline neurological function, including the acoustic startle response and prepulse inhibition paradigm. (frontiersin.org)
  • Each disease model was crossed to mice ubiquitously overexpressing wild-type GARS in order to determine whether the disease phenotype is caused by a loss of function in GARS. (bl.uk)
  • Rapamycin treatment also resulted in prolonged healthspan in KO mice, as indicated by the offset of neurological damage, maintenance of weight and body fat, and the improvement of deleterious behavioral phenotypes. (washington.edu)
  • We developed separate models of respiratory and neurological disease following EV-D68 infection in AG129 mice that respond to antiviral treatment with guanidine. (quansysbio.com)
  • In 10-day-old mice infected intraperitoneally, EV-D68 causes a neurological disease with weight-loss, paralysis, and mortality. (quansysbio.com)
  • In our neurological model, guanidine treatment protects mice from weight-loss, paralysis, and mortality. (quansysbio.com)
  • Further studies on the mutant mice already prove the model to be very powerful. (news-medical.net)
  • The usefulness of these mice as translational models is discussed, with focus on their construct and face validity. (preprints.org)
  • In mouse models of myotonic dystrophy, the researchers found that treating newborn mice with a virus carrying the dCas9 enzyme reduced the prevalence of myotonia, prolonged muscle contractions commonly experienced by myotonic dystrophy patients. (ufl.edu)
  • Because of underlying differences in the aging of mice and humans, useful mouse models have been difficult to obtain and study. (omicsdi.org)
Cerebral5
  • Performance of the handheld PA system was tested in an animal ischemia model, which revealed that cerebral blood volume (CBV) changes at the cortical surface could be monitored immediately after ischemia induction. (elsevier.com)
  • Background Survival with good neurological function post out-of-hospital cardiac arrest (OHCA), defined as cerebral performance category (CPC) 1-2, ranges from 1.6% to 3% in Asia. (bmj.com)
  • Morbidity following SAH are commonly defined in terms of neurological repercussions, including aneurysm rebleeding, intracranial hypertension, cerebral vasospasm, brain edema, cerebral infarction, and hydrocephalus [ 3 ]. (medsci.org)
  • In the present study, we examined the effects of neurological improvement after transient middle cerebral artery occlusion (MCAO) in rats by a novel therapeutic strategy with FGF-2 gene-transferred MSCs by the herpes simplex virus type 1 (HSV-1) vector. (ahajournals.org)
  • In addition, we demonstrated that drugs known to activate HIF-1 in cultured cells as well as in vivo had neuroprotective properties in this model of cerebral ischemia. (jneurosci.org)
Phenotype1
  • 6 Environmental construct validity Environmental construct validity considers the effects of environmental factors known to confer increased risk for mental illness, and whether these factors are associated with the altered behavioral phenotype in the animal model. (juridikinstitutet.se)
Human25
  • Human disease modeling with iPSCs has enabled researchers to study the disease phenotypes of patient-derived cells directly in the lab. (eurekalert.org)
  • An international team of scientists, led by University of California San Diego School of Medicine researchers, has created a human stem cell-based model of a rare, but devastating, inherited neurological autoimmune condition called Aicardi-Goutieres Syndrome (AGS). (eurekalert.org)
  • Deeper probing into the pathogenesis of AGS has been difficult because animal models do not accurately mimic the human version of the disease. (eurekalert.org)
  • Chapter 1 begins with a brief review of the ethics of animal use in neuro- biological research, inc1uding a discussion of the criteria that may be used to evaluate animal models of human disease and extrapolate from the model to appropriate questions regarding humans. (springer.com)
  • While they have very different levels of severity, they are both reliable models of the human disease. (bl.uk)
  • This review seeks to discuss the reasons for these difficulties by considering the differences between human and animal cells (including isolation, handling and transplantation) and between the human disease model and the animal disease model. (frontiersin.org)
  • Here, we see evidence that the zebrafish's central nervous system is suitable for modeling human neurological disease and we review and evaluate natural product research using zebrafish as a vertebrate model platform to systematically identify bioactive natural products. (mdpi.com)
  • Mature neuronal and glial cells derived from human pluripotent stem cells have emerged as a physiologically relevant model for the study of neurological development and disease. (stemcell.com)
  • Building-associated neurological damage modeled in human cells: a mechanism of neurotoxic effects by exposure to mycotoxins in the indoor environment. (biomedsearch.com)
  • Damage to human neurological system cells resulting from exposure to mycotoxins confirms a previously controversial public health threat for occupants of water-damaged buildings. (biomedsearch.com)
  • Our results demonstrate that this new fucosidosis mouse model resembles the human disease and thus will help to unravel underlying pathological processes. (biologists.org)
  • Due to the close resemblance of the clinical and histological picture of human psoriasis, the new disease-model is ideally suited to study in detail all aspects of pathogenesis. (news-medical.net)
  • The Reeler Mouse: A Translational Model of Human Neurological Conditions or Simply a Good Tool for Better Understanding Neurodevelopment? (preprints.org)
  • An effective human cellular model of AD would use the appropriate cell types and ideally neural circuits affected by the disease, would develop relevant pathology and would do so in a reproducible manner over a timescale short enough for practical use. (biomedcentral.com)
  • We review here current progress in applying this approach to generating human models of AD and the potential for such models in the AD field. (biomedcentral.com)
  • The PMFE is an anatomy-based inverse dynamic-static optimisation model aiming to fulfil the requirements for controlling a human-inspired rehabilitation robot via muscle forces. (springer.com)
  • We believe that the future of brain research will include less reliance on animals, more reliance on human, cell-based models. (medindia.net)
  • To answer important questions about human brain development, animal scientists Rod Johnson and Ryan Dilger have developed a model of the pig brain. (medindia.net)
  • Now, a group of University of Florida Health researchers has found a way to block the transcription of those dysfunctional genetic sequences into RNA, in human cells and mouse models. (ufl.edu)
  • Background: Progressive neurological dysfunction is a key aspect of human aging. (omicsdi.org)
  • We have used gene-expression analysis and polymorphism screening to study molecular senescence of the retina and hippocampus in two rare inbred mouse models of accelerated neurological senescence (SAMP8 and SAMP10) that closely mimic human neurological aging, and in a related normal strain (SAMR1) and an unrelated normal strain (C57BL/6J). (omicsdi.org)
  • Although kindling is a widely used model, its applicability to human epilepsy is controversial. (wikipedia.org)
  • However, in both human epilepsy and in some animal models, evidence suggests that a process like that found in kindling does occur. (wikipedia.org)
  • Further research by Goddard on the characteristics of the kindling phenomenon led to his conclusion that kindling can be used to model human epileptogenesis, learning and memory. (wikipedia.org)
  • The publication of these results opened a completely new niche for epilepsy research and has stimulated a significant amount of studies on the subject of kindling and its relevance to human epilepsy Kindling (sedative-hypnotic withdrawal) Epileptogenesis Racine Stages (a method by which seizure severity is quantified in animal models of epilepsy) Bertram E (2007). (wikipedia.org)
Bicameral mind theory1
  • Since the publication of Reflections on the Dawn of Consciousness , a number of new studies have been published that also show bilateral temporal lobe ('bicameral') activation during auditory hallucinations, providing further support for Jaynes's neurological model specifically and his bicameral mind theory in general. (julianjaynes.org)
Jaynes's3
  • Beginning in 1999, research began to emerge confirming Julian Jaynes's neurological model for the bicameral mind: fMRI studies showing a right/left temporal lobe interaction during auditory verbal hallucinations. (julianjaynes.org)
  • In my chapter in Reflections on the Dawn of Consciousness , "Consciousness, Hallucinations, and the Bicameral Mind: Three Decades of New Research," I discuss a number of neuroimaging studies that emerged over the past decade that provide support for Jaynes's neurological model. (julianjaynes.org)
  • While it certainly does not 'prove' Jaynes's theory, research supportive of his neurological model is important evidence. (julianjaynes.org)
Progression2
Tumor2
  • Among the mouse models of FRDA, the liver conditional mouse model pointed to a tumor suppressor activity of frataxin leading to the hypothesis that individuals with FRDA might be predisposed to cancer. (curefa.org)
  • These findings suggest an active inflammation in neurofibromas and partly explain why mast cell removal alone is not sufficient to relieve tumor burden in this experimental neurofibroma model. (nih.gov)
Animal12
Prediction1
Biomarkers2
Computational2
Cognition1
Neuroscience3
  • Neuroscience applicants using invertebrate model systems have successfully competed for NINDS grant funding in peer review in recent years. (nih.gov)
  • Indeed, the NIH BRAIN Initiative supports the use of invertebrate model systems in research to understand neural functions and recognizes that this is an important part of the neuroscience ecosystem. (nih.gov)
  • When Jaynes’s neurological model for the bicameral mind was first proposed, both he and his critics conceded that it would be decades before progress in neuroscience could validate or disprove it. (julianjaynes.org)
Abnormalities1
Disorder2
  • The landmark publication Neurological, Psychiatric and Developmental Disorder: Meeting the Needs in the Developing World 1 was an early driver of the growth of global mental health as a discipline. (nap.edu)
  • We performed a pilot study using heterogeneous ataxias as a model neurogenetic disorder to assess the introduction of next-generation sequencing into clinical practice. (cdc.gov)
Research8
  • As they analyzed the correlation of 663 neuronal phenotypes with genotypic data from 243 patients and 214 controls - and examined research practices and reporting bias in neurological disease models - they found that there is no established standard for the reporting of methods nor a defined minimal number of cell lines. (eurekalert.org)
  • Our phenogenetic map can be used to build new hypotheses in the field of neurological disease modeling, and to identify potential new opportunities to design novel drug strategies," said first author Ethan W. Hollingsworth, a neural stem cell research assistant at Ohio State's Wexner Medical Center and a hematology/oncology clinical research intern at Nationwide Children's Hospital. (eurekalert.org)
  • NINDS' mission is impartial to the model system employed, but is advanced by the neuroscientific impact of each research project. (nih.gov)
  • Within the biomedical research community, there is little doubt about the utility of such models. (springer.com)
  • The long-term objective of our research is to find out how some rehabilitative drugs work by devising a model of the fundamental workings of an addict's brain," said Mohan, who will attend Washington University in St. Louis for his postdoctoral fellowship. (missouri.edu)
  • We've created a model that tests the ability to do sensory integration, which should be extremely useful for pharmaceutical research . (medicalxpress.com)
  • Here, we report a systematic analysis of research practices and reporting bias in neurological disease models from 93 published articles. (embopress.org)
  • This booklet contains a comprehensive suite of solutions to support your research using neurological mouse models. (jax.org)
Huntington's Disease2
Statistical1
  • To assess whether gait analysis is applicable to assess improvements by neuroprotective compounds, we applied a model calculation and approached common statistical problems. (nih.gov)
IPSCs3
Infection2
Experimental3
  • In contemporary biomedicine, the growing need to develop experimental models to obtain a detailed understanding of malady conditions and to portray pioneering treatments has resulted in the application of zebrafish to close the gap between in vitro and in vivo assays. (mdpi.com)
  • Dong Ys, Wang Jl, Feng Dy, Qin Hz, Wen H, Yin Zm, Gao Gd, Li C. Protective Effect of Quercetin against Oxidative Stress and Brain Edema in an Experimental Rat Model of Subarachnoid Hemorrhage. (medsci.org)
  • Kindling: An experimental model of epilepsy" (PDF). (wikipedia.org)
Phenotypes1
  • Our models enable fine stratification into phenotypes enabling more focussed analysis to identify subgroups that respond to putative treatments. (europa.eu)
Researchers2
  • The researchers found that with TREX1 not functioning normally, all of the cell models displayed excess extra-chromosomal DNA and that a major source of the excess DNA came from LINE1 (L1) retroelements. (eurekalert.org)
  • The first thing to understand is the scale of the problem that researchers face when trying to dissect the processes that lead to neurodegeneration and neurological disease. (hstalks.com)
Progenitor cells1
  • have been shown to promote remyelination in mouse models of demyelination by promoting proliferation or differentiation of oligodendrocyte progenitor cells (OPCs) directly or indirectly. (jneurosci.org)
Clinical3
  • The models offer innovation potential by underpinning support systems for clinical and drug-development applications. (europa.eu)
  • Efficacy studies performed by JAX® In Vivo Services for ALS typically feature clinical observations, body weights, progressive neurological scoring, electrophysiological assessment of motor neuropathy, survival, tissue/blood collection and histological assessment of neuromuscular junctions and femoral nerves. (jax.org)
  • We strongly believe that this model will be highly suitable for future pre-clinical studies ultimately aimed at understanding and curing this widespread disease. (news-medical.net)
Autism1
Ameliorate2
  • Overall, these data suggest that in hamsters hE16 can ameliorate neurological disease after significant viral replication has occurred, although there is a time window that limits therapeutic efficacy. (biomedsearch.com)
  • The findings suggest that the early administration of optimal dose of quercetin may ameliorate brain damage and provide neuroprotection in the SAH model, potentially by enhancing the activity of endogenous antioxidant enzymes and inhibiting free radical generation. (medsci.org)
Mutations3
  • Results suggest that CMT2D can be modeled in fly, that the toxicity of the mutant protein is tissue autonomous, and that mutations in CARS and YARS have similar effects in Drosophila, hinting at a shared mechanism. (bl.uk)
  • There are two murine models of CMT2D with different mutations in the Cars gene. (bl.uk)
  • Many neurological conditions are caused by immensely heterogeneous gene mutations. (cdc.gov)
Study7
  • This study aims to characterize the neurological basis of obesity and response to surgical and medical treatment by inducing adult pluripotent stem cells into neuronal cells from subjects that have demonstrated extreme response to bariatric surgery or pharmacological treatment for obesity. (clinicaltrials.gov)
  • This study demonstrates that neurological system cell damage can occur from satratoxin H exposure to neurological cells at exposure levels that can be found in water-damaged buildings contaminated with fungal growth. (biomedsearch.com)
  • We aim to study the influence of comorbidities and peri-OHCA event factors on neurological recovery and develop a model that can help clinicians predict neurological function among patients with post-OHCA admitted to the hospital. (bmj.com)
  • An interactive graphics-based model of the lower extremity to study orthopaedic surgical procedures. (springer.com)
  • Latent class modeling of US Food and Drug Administration Adverse Event Reporting System (FAERS) data was performed using indicators defined by the Medical Dictionary for Regulatory Activities neurologic and psychiatric high-level group terms, in a study dataset of FAERS reports ( n = 5332) of reactions to common antimalarial drugs. (springer.com)
  • We will use the information obtained from this study information to develop a biopsychosocial prospective surveillance model, a method for early detection, intervention, and moderation of shoulder pain. (clinicaltrials.gov)
  • Transcription profiling of hippocampus and retina from two rare inbred mouse models of accelerated neurological senescence ( SAMP8 and SAMP10) and a related wild type strain SAMR1 to study molecular senescence of the retina and hippocampus. (omicsdi.org)
Pathology2
  • In these models, mitochondrial electron transport chain complex I activity is reduced but results in distinct patterns of neuronal pathology. (washington.edu)
  • Thus far, comparison of these studies suggests that rapamycin treatment has both overlapping and distinct effects that contribute to attenuation of neural pathology of NDUFS4 and MPTP mouse models. (washington.edu)
Cells7
  • This webinar provides an overview of the features and applications of induced pluripotent stem cells with respect to neurological disease modeling. (stemcell.com)
  • Modeling Neurological Disease with iPS Cells? (stemcell.com)
  • Disease modeling with induced pluripotent stem cells (i PSC s) is creating an abundance of phenotypic information that has become difficult to follow and interpret. (embopress.org)
  • Thus, undifferentiated high-passage SH-SY5Y cells could be a good noradrenergic model for in vivo studies. (wichita.edu)
  • These cells take up DA and NE more efficiently than undifferentiated cells suggesting they could be used either as partial noradrenergic or dopaminergic models. (wichita.edu)
  • Another common model, MN9D cells, store high levels of DA under normal growth conditions, but do not convert it to NE. (wichita.edu)
  • They show poor catecholamine uptake characteristics compared to SH-SY5Y cells, however n-butyric acid differentiated MN9D cells show more efficient DA uptake similar to undifferentiated SH-SY5Y, suggesting that they could be used as a reasonable dopaminergic model. (wichita.edu)
Patient's1
Dysfunction1
Characterize1
Mouse models2
  • During the past ten years, the development of mouse models of FRDA has allowed better understanding of the pathophysiology of the disease. (curefa.org)
  • In addition to existing mouse models, several major programmes have been set up to generate new mouse models of disease. (ucl.ac.uk)
Behavior of the Laboratory Rat: A Handbook with Tests - Oxford Scholarship
Behavior of the Laboratory Rat: A Handbook with Tests - Oxford Scholarship (oxfordscholarship.com)
Phenogenetic map created for stem cells models of neurological diseases | EurekAlert! Science News
Phenogenetic map created for stem cells models of neurological diseases | EurekAlert! Science News (eurekalert.org)
Neuroplasticity, Neuroregeneration, and Brain Repair | The New York Academy of Sciences
Neuroplasticity, Neuroregeneration, and Brain Repair | The New York Academy of Sciences (nyas.org)
Immunological Mechanisms and Therapies in Brain Injuries and Stroke - Jun Chen, Xiaoming Hu, Mary Stenzel-Poore, John H Zhang -...
Immunological Mechanisms and Therapies in Brain Injuries and Stroke - Jun Chen, Xiaoming Hu, Mary Stenzel-Poore, John H Zhang -... (bokus.com)
Double-negative T cells remarkably promote neuroinflammation after ischemic stroke | PNAS
Double-negative T cells remarkably promote neuroinflammation after ischemic stroke | PNAS (pnas.org)
First true animal model for psoriasis
First true animal model for psoriasis (news-medical.net)
Book Series: International Review of Neurobiology
Book Series: International Review of Neurobiology (elsevier.com)
Parkinson Archives - Page 6 of 6 - ScienceBlog.com
Parkinson Archives - Page 6 of 6 - ScienceBlog.com (scienceblog.com)
Sensory processing disorder - Wikipedia
Sensory processing disorder - Wikipedia (en.wikipedia.org)
Novel stem cell-derived model created of inflammatory neurological disorder | EurekAlert! Science News
Novel stem cell-derived model created of inflammatory neurological disorder | EurekAlert! Science News (eurekalert.org)
Muscle Force Estimation Model for Gait Rehabilitation | SpringerLink
Muscle Force Estimation Model for Gait Rehabilitation | SpringerLink (link.springer.com)
Toxin-Induced Models of Neurological Disorders | Springer for Research & Development
Toxin-Induced Models of Neurological Disorders | Springer for Research & Development (rd.springer.com)
Peter Howell
Peter Howell (ucl.ac.uk)
Press Releases | Page 14 | National Institute of Neurological Disorders and Stroke
Press Releases | Page 14 | National Institute of Neurological Disorders and Stroke (ninds.nih.gov)
Generation and transplantation of reprogrammed human neurons in the brain using 3D microtopographic scaffolds | Nature...
Generation and transplantation of reprogrammed human neurons in the brain using 3D microtopographic scaffolds | Nature... (nature.com)
Frontiers | Mouse Model of Neurological Complications Resulting from Encephalitic Alphavirus Infection | Microbiology
Frontiers | Mouse Model of Neurological Complications Resulting from Encephalitic Alphavirus Infection | Microbiology (frontiersin.org)
T32 - NINDS Institutional Research Training Grant | National Institute of Neurological Disorders and Stroke
T32 - NINDS Institutional Research Training Grant | National Institute of Neurological Disorders and Stroke (ninds.nih.gov)
Animal Models for Stem Cell Therapy | Springer for Research & Development
Animal Models for Stem Cell Therapy | Springer for Research & Development (rd.springer.com)
Appendix F: Quality Improvement and Proactive Hazard Analysis Models: Deciphering a New Tower of Babel | Patient Safety:...
Appendix F: Quality Improvement and Proactive Hazard Analysis Models: Deciphering a New Tower of Babel | Patient Safety:... (nap.edu)
Automated EEG-Based Diagnosis of Neurological Disorders: Inventing the
Automated EEG-Based Diagnosis of Neurological Disorders: Inventing the (routledge.com)