Journal ArticleDOI
Neuronal circuits of the neocortex
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It is found that, as has long been suspected by cortical neuroanatomists, the same basic laminar and tangential organization of the excitatory neurons of the neocortex is evident wherever it has been sought.Abstract:
We explore the extent to which neocortical circuits generalize, i.e., to what extent can neocortical neurons and the circuits they form be considered as canonical? We find that, as has long been suspected by cortical neuroanatomists, the same basic laminar and tangential organization of the excitatory neurons of the neocortex is evident wherever it has been sought. Similarly, the inhibitory neurons show characteristic morphology and patterns of connections throughout the neocortex. We offer a simple model of cortical processing that is consistent with the major features of cortical circuits: The superficial layer neurons within local patches of cortex, and within areas, cooperate to explore all possible interpretations of different cortical input and cooperatively select an interpretation consistent with their various cortical and subcortical inputs.read more
Citations
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The abiding relevance of mouse models of rare mutations to psychiatric neuroscience and therapeutics.
TL;DR: Mouse models of rare mutations, paired with analysis of homologous cognitive and sensory processing deficits and state-of-the-art neuroscience methods to manipulate and record neuronal activity have started providing unprecedented insights into pathogenic mechanisms and building the foundation of a new biological framework for understanding mental illness.
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2009 Special Issue: Spatial attention in area V4 is mediated by circuits in primary visual cortex
Paul H. E. Tiesinga,Calin Buia +1 more
TL;DR: Simulations of a primary visual cortex (V1) model provide insight into the local circuit computation underlying stimulus selection in V4 and suggest that spatial attention at a resolution less than the size of the CRF of a V4 neuron is inherited from upstream areas like V1 and relies on circuits mediating surround suppression at the single neuron level.
Journal ArticleDOI
Rhythmic inhibition allows neural networks to search for maximally consistent states
TL;DR: The described networks are used to reproduce perceptual multistability phenomena with switching times that are a good match to experimental data and show that they provide a general neural framework that can be used to model other perceptual inference phenomena.
Journal ArticleDOI
How do high-level specifications of the brain relate to variational approaches?
TL;DR: This article describes how the variational framework, which encountered a large success in modeling computer vision tasks, has some interesting relationships, at a mesoscopic scale, with computational neuroscience.
Posted ContentDOI
Why Does the Neocortex Have Layers and Columns, A Theory of Learning the 3D Structure of the World
TL;DR: This paper proposes a network model composed of columns and layers that performs robust object learning and recognition and proposes that a representation of location relative to the object being sensed is calculated within the sub-granular layers of each column.
References
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Receptive fields, binocular interaction and functional architecture in the cat's visual cortex
David H. Hubel,Torsten N. Wiesel +1 more
TL;DR: This method is used to examine receptive fields of a more complex type and to make additional observations on binocular interaction and this approach is necessary in order to understand the behaviour of individual cells, but it fails to deal with the problem of the relationship of one cell to its neighbours.
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Distributed Hierarchical Processing in the Primate Cerebral Cortex
TL;DR: A summary of the layout of cortical areas associated with vision and with other modalities, a computerized database for storing and representing large amounts of information on connectivity patterns, and the application of these data to the analysis of hierarchical organization of the cerebral cortex are reported on.
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Hierarchical models of object recognition in cortex
TL;DR: A new hierarchical model consistent with physiological data from inferotemporal cortex that accounts for this complex visual task and makes testable predictions is described.
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Neuromorphic electronic systems
TL;DR: It is shown that for many problems, particularly those in which the input data are ill-conditioned and the computation can be specified in a relative manner, biological solutions are many orders of magnitude more effective than those using digital methods.
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