Journal ArticleDOI
Neuronal circuits of the neocortex
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TLDR
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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A review of learning in biologically plausible spiking neural networks
TL;DR: A review of recent developments in learning of spiking neurons and a critical review of the state-of-the-art learning algorithms for SNNs using single and multiple spikes is presented.
Journal ArticleDOI
Optogenetic dissection of medial prefrontal cortex circuitry.
Danai Riga,Mariana R. Matos,Annet Glas,August B. Smit,Sabine Spijker,Michel C. van den Oever +5 more
TL;DR: The current knowledge obtained with optogenetic methods concerning mPFC function and dysfunction are presented and findings from traditional intervention approaches used to investigate themPFC circuitry in animal models of cognitive processing and psychiatric disorders are integrated.
Journal ArticleDOI
Cell Type–Specific Thalamic Innervation in a Column of Rat Vibrissal Cortex
HS Meyer,Verena C. Wimmer,Mike Hemberger,Randy M. Bruno,Christiaan P. J. de Kock,Andreas Frick,Bert Sakmann,Moritz Helmstaedter +7 more
TL;DR: The substantial potential TC innervation of all excitatory neuron types in a cortical column constitutes an anatomical basis for the initial near-simultaneous representation of a sensory stimulus in different neuron types.
Journal ArticleDOI
A canonical neural circuit for cortical nonlinear operations
Minjoon Kouh,Tomaso Poggio +1 more
TL;DR: It is shown that when the two operations of the gaussian-like and max-like model are approximated by the circuit proposed here, the model is capable of generating selective and invariant neural responses and performing object recognition, in good agreement with neurophysiological data.
Journal ArticleDOI
Mean-driven and fluctuation-driven persistent activity in recurrent networks
TL;DR: Overall it is found that fluctuation-driven persistent activity in the very simplified type of models the authors analyze is not a robust phenomenon.
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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