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  • prediction
  • This is a simple framework for time-series prediction of the time to the next event applicable when we have any or all of the problems of continuous or discrete time, right censoring, recurrent events, temporal patterns, time varying covariates or time series of varying lengths. (chalmers.se)
  • Martinsson2017, author={Martinsson, Egil}, title={WTTE-RNN : Weibull Time To Event Recurrent Neural Network A model for sequential prediction of time-to-event in the case of discrete or continuous censored data, recurrent events or time-varying covariates}, abstract={In this thesis we propose a new model for predicting time to events: the Weibull Time To Event RNN. (chalmers.se)
  • cognitive
  • If linguistic phenomena can be explained by sequential rather than hierarchical structure, this will have considerable impact in a wide range of fields, such as linguistics, ethology, cognitive neuroscience, psychology and computer science. (royalsocietypublishing.org)
  • From different perspectives, neural computation provides an alternative methodology to understand brain functions and cognitive process and to solve challenging real-world problems effectively. (springer.com)
  • Cognitive therapy displayed a similar prophylactic effect to maintenance medication.9 The criterion for recurrent depression (at least 1 previous episode of depression) was different, however, from that endorsed by Frank et al5 ( 3 episodes of unipolar depression, with the immediately preceding episode being no more than 2 years before the onset of the present episode). (scribd.com)
  • behavior
  • Just as human memory circulates invisibly within a body, affecting our behavior without revealing its full shape, information circulates in the hidden states of recurrent nets. (skymind.ai)
  • Neurodynamics …is a term used here to represent a level of abstraction in the study of information processing in neural network activity, and to use this perspective to bridge from neuroscience to conscious experience and behavior. (cerfnet.com)
  • neuron
  • A memory cell is composed of four main elements: an input gate, a neuron with a self-recurrent connection (a connection to itself), a forget gate and an output gate. (danmackinlay.name)
  • computation
  • Normalization is a widespread neural computation, mediating divisive gain control in sensory processing and implementing a context-dependent value code in decision-related frontal and parietal cortices. (jneurosci.org)
  • Pastor-Bernier and Cisek, 2011 ), where action value is encoded within the context of available options, reinforces the prevalent notion that normalization is a canonical neural computation ( Carandini and Heeger, 2012 ). (jneurosci.org)
  • Trend in Neural Computation includes twenty chapters either contributed from leading experts or formed by extending well selected papers presented in the 2005 International Conference on Natural Computation. (springer.com)
  • Researchers, graduate students and industrial practitioners in the broad areas of neural computation would benefit from the state-of-the-art work collected in this book. (springer.com)
  • major depressi
  • To challenge participants, sad mood was induced with keywords of personal negative life events in individuals with remitted depression [recurrent major depressive disorder (rMDD), n = and matched healthy controls (HCs, n = 30) during functional magnetic resonance imaging. (readbyqxmd.com)
  • arise
  • Here, we hypothesize that both transient dynamics and sustained delay-period value coding arise from a recurrent normalization circuit. (jneurosci.org)
  • This pattern may arise from recurrent systems such as the hippocampal CA3 region or the entorhinal cortex. (jneurosci.org)
  • mechanism
  • These results suggest that a single network mechanism can explain both transient and sustained decision activity, emphasizing the importance of a dynamic view of normalization in neural coding. (jneurosci.org)
  • deep
  • In the course project learner will implement deep neural network for the task of image captioning which solves the problem of giving a text description for an input image. (coursera.org)
  • In recent years, deep neural network based models have been developed to address such needs and they have made significant progress in relation identification. (biomedcentral.com)
  • This module is an introduction to the concept of a deep neural network. (coursera.org)
  • This complex neural organization gives rise to a massive signal-processing capability, but almost all of the output from the cerebellar cortex passes through a set of small deep nuclei lying in the white matter interior of the cerebellum. (wikipedia.org)
  • Elman
  • Here's a diagram of an early, simple recurrent net proposed by Elman , where the BTSXPE at the bottom of the drawing represents the input example in the current moment, and CONTEXT UNIT represents the output of the previous moment. (skymind.ai)
  • context
  • Most important is the potential to extend this idea to context dependent sequential activation of neural emsembles to account for serial order in thought and action . (cerfnet.com)
  • widespread
  • Conscious perception is robustly associated with sustained, recurrent interactions between widespread cortical regions. (ugent.be)
  • dynamics
  • Concepts from linear system theory were adapted to represent some aspects of neural dynamics, including solutions of simultaneous linear equations \(Y = AX\) using matrix theory, and concepts about cross-correlation. (scholarpedia.org)
  • We propose that neural dynamics provides a critical link to understanding the biophysical basis of value normalization. (jneurosci.org)
  • sensory
  • Decoding continuous hind limb joint angles from sensory recordings of neural system provides a feedback for closed-loop control of hind limb movement using functional electrical stimulation. (readbyqxmd.com)
  • representation
  • Recent evidence suggests that certain canonical neural computations play a crucial role in the neural representation of value. (jneurosci.org)
  • Similar to the address-event representation (AER) and virtual wires, developed at Caltech and U Delaware, respectively, Applied Neurodynamics in 1989 independently developed a communication scheme for neural event messages called the space-time attribute code (STA, 15). (cerfnet.com)
  • approach
  • The aim of this study was to test the effectiveness of this approach in patients with recurrent depression ( 3 episodes of depression). (scribd.com)
  • crucial
  • NC/IC discrimination is crucial for clinical BCIs, particularly when they provide neural control over complex effectors such as exoskeletons. (fichier-pdf.fr)