Literature DB >> 23818068

A single functional model of drivers and modulators in cortex.

M W Spratling1.   

Abstract

A distinction is commonly made between synaptic connections capable of evoking a response ("drivers") and those that can alter ongoing activity but not initiate it ("modulators"). Here it is proposed that, in cortex, both drivers and modulators are an emergent property of the perceptual inference performed by cortical circuits. Hence, it is proposed that there is a single underlying computational explanation for both forms of synaptic connection. This idea is illustrated using a predictive coding model of cortical perceptual inference. In this model all synaptic inputs are treated identically. However, functionally, certain synaptic inputs drive neural responses while others have a modulatory influence. This model is shown to account for driving and modulatory influences in bottom-up, lateral, and top-down pathways, and is used to simulate a wide range of neurophysiological phenomena including surround suppression, contour integration, gain modulation, spatio-temporal prediction, and attention. The proposed computational model thus provides a single functional explanation for drivers and modulators and a unified account of a diverse range of neurophysiological data.

Mesh:

Year:  2013        PMID: 23818068     DOI: 10.1007/s10827-013-0471-7

Source DB:  PubMed          Journal:  J Comput Neurosci        ISSN: 0929-5313            Impact factor:   1.621


  135 in total

1.  Effects of attention on the reliability of individual neurons in monkey visual cortex.

Authors:  C J McAdams; J H Maunsell
Journal:  Neuron       Date:  1999-08       Impact factor: 17.173

2.  Integrating top-down and bottom-up sensory processing by somato-dendritic interactions.

Authors:  M Siegel; K P Körding; P König
Journal:  J Comput Neurosci       Date:  2000 Mar-Apr       Impact factor: 1.621

Review 3.  Reaching beyond the classical receptive field of V1 neurons: horizontal or feedback axons?

Authors:  Alessandra Angelucci; Jean Bullier
Journal:  J Physiol Paris       Date:  2003 Mar-May

4.  Geometrical computations explain projection patterns of long-range horizontal connections in visual cortex.

Authors:  Ohad Ben-Shahar; Steven Zucker
Journal:  Neural Comput       Date:  2004-03       Impact factor: 2.026

5.  Neural correlates of sustained spatial attention in human early visual cortex.

Authors:  Michael A Silver; David Ress; David J Heeger
Journal:  J Neurophysiol       Date:  2006-09-13       Impact factor: 2.714

Review 6.  Feedforward, horizontal, and feedback processing in the visual cortex.

Authors:  V A Lamme; H Supèr; H Spekreijse
Journal:  Curr Opin Neurobiol       Date:  1998-08       Impact factor: 6.627

7.  Extraction of perceptually salient contours by striate cortical networks.

Authors:  S C Yen; L H Finkel
Journal:  Vision Res       Date:  1998-03       Impact factor: 1.886

8.  Figure-ground organization and object recognition processes: an interactive account.

Authors:  S P Vecera; R C O'Reilly
Journal:  J Exp Psychol Hum Percept Perform       Date:  1998-04       Impact factor: 3.332

Review 9.  Corticocortical connections in the visual system: structure and function.

Authors:  P A Salin; J Bullier
Journal:  Physiol Rev       Date:  1995-01       Impact factor: 37.312

Review 10.  Gain modulation in the central nervous system: where behavior, neurophysiology, and computation meet.

Authors:  E Salinas; T J Sejnowski
Journal:  Neuroscientist       Date:  2001-10       Impact factor: 7.519

View more
  5 in total

1.  Predictive coding as a model of cognition.

Authors:  M W Spratling
Journal:  Cogn Process       Date:  2016-04-27

2.  Adaptive learning in a compartmental model of visual cortex-how feedback enables stable category learning and refinement.

Authors:  Georg Layher; Fabian Schrodt; Martin V Butz; Heiko Neumann
Journal:  Front Psychol       Date:  2014-12-05

3.  Reversal Learning in Humans and Gerbils: Dynamic Control Network Facilitates Learning.

Authors:  Christian Jarvers; Tobias Brosch; André Brechmann; Marie L Woldeit; Andreas L Schulz; Frank W Ohl; Marcel Lommerzheim; Heiko Neumann
Journal:  Front Neurosci       Date:  2016-11-17       Impact factor: 4.677

4.  Reinforcement Learning of Linking and Tracing Contours in Recurrent Neural Networks.

Authors:  Tobias Brosch; Heiko Neumann; Pieter R Roelfsema
Journal:  PLoS Comput Biol       Date:  2015-10-23       Impact factor: 4.475

5.  Toward a Unified Sub-symbolic Computational Theory of Cognition.

Authors:  Martin V Butz
Journal:  Front Psychol       Date:  2016-06-21
  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.