A Quantitative Map of the Circuit of Cat Primary Visual Cortex

By T. Binzegger, Rodney J. Douglas, Kevan A. C. Martin. Journal of Neuroscience, 2004

903 citations recorded by the source corpus.

We developed a quantitative description of the circuits formed in cat area 17 by estimating the “weight” of the projections between different neuronal types. To achieve this, we made three-dimensional reconstructions of 39 single neurons and thalamic afferents labeled with horseradish peroxidase during intracellular recordings in vivo. These neurons served as representatives of the different types and provided the morphometrical data about the laminar distribution of the dendritic trees and synaptic boutons and the number of synapses formed by a given type of neuron. Extensive searches of the literature provided the estimates of numbers of the different neuronal types and their distribution across the cortical layers. Applying the simplification that synapses between different cell types are made in proportion to the boutons and dendrites that those cell types contribute to the neuropil in a given layer, we were able to estimate the probable source and number of synapses made between neurons in the six layers. The predicted synaptic maps were quantitatively close to the estimates derived from the experimental electron microscopic studies for the case of the main sources of excitatory and inhibitory input to the spiny stellate cells, which form a major target of layer 4 afferents. The map of the whole cortical circuit shows that there are very few “strong” but many “weak” excitatory projections, each of which may involve only a few percentage of the total complement of excitatory synapses of a single neuron.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/65c8a4cef1508ce47792dcc25137b3b9ddfee167

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Citations in the corpus

Balanced amplification: a new mechanism of selective amplification of neural activity patterns (2009, neutral): “Even in early sensory areas receiving substantial feedforward input from subcortical areas, intracortical connections make up a large fraction of the input to cortical neurons (Thomson and Lamy, 2007; Binzegger et al., 2004; Stepanyants et al., 2008).”
Network anatomy and in vivo physiology of visual cortical neurons (2011, background): “Synaptic connectivity was originally inferred from the overlap of axonal and dendritic arbors (Ramon y Cajal, 1904), an approach that remains fruitful today (Binzegger et al., 2004; Stepanyants, 2008).”
Active properties of neocortical pyramidal neuron dendrites. (2013, background): “Pyramidal neurons are embedded in a layered structure (the cortex); the distribution of synaptic input is constrained, e.g., tuft dendrites are likely to receive long-range inputs (Binzegger et al. 2004).”
A Theory of Object Recognition: Computations and Circuits in the Feedforward Path of the Ventral Stream in Primate Visual Cortex (2005, background): “This version of the theory is restricted to the feedforward path in the ventral stream It is important to emphasize from the outset the basic assumption and the basic limitation of the current theory: we only consider the first 150 ms of the flow of information in the ventral stream — behaviorally e”
The excitatory neuronal network of the C2 barrel column in mouse primary somatosensory cortex. (2009, result): “These synaptic pathways, which we quantified in mouse C2 barrel cortex, are in qualitative agreement with the proposed ‘‘canonical’’ microcircuits of visual cortex (Binzegger et al., 2004) derived from anatomical overlap of axonal and dendritic arborizations, which often provides a good estimate of ”
A Scalable Multicore Architecture With Heterogeneous Memory Structures for Dynamic Neuromorphic Asynchronous Processors (DYNAPs) (2017, background): “The trade-offs and design points we chose for the prototype device built to validate our approach were determined by the study of cortical networks in mammalian brains [45]–[47].”
Neurophysiological and Computational Principles of Cortical Rhythms in Cognition (2010, background): “Entrainment involves unidirectional inhibitory-to-excitatory coupling, whereas in the hippocampus (305) and neocortex (85), interneurons and pyramidal cells are reciprocally connected.”
Cortical travelling waves: mechanisms and computational principles (2018, background): “Pyramidal cells in V1 have dense recurrent synaptic connectivity, each receiving from 6,000 to 13,000 inputs per cell 93 .”
Optimal Hierarchical Modular Topologies for Producing Limited Sustained Activation of Neural Networks (2009, positive): “A modular hierarchical organization of cortical architecture and connections is apparent across many scales, from cellular microcircuits in cortical columns (Mountcastle, 1997; Binzegger et al., 2004) at the lowest level, via cortical areas at the mesoscopic scale, to clusters of highly connected br”
Synchronization in complex networks (2008, background): “In the last years, significant progress has been made in the studies about the detailed interconnections of different types of neurons at the level of cellular circuits [190, 191, 192].”
The SpiNNaker Project (2014, methodology): “This choice is justified by studies on the structure of the central nervous systems, where functionally segregated areas are interconnected by axonal pathways [14], and where cortical areas show a remarkably regular laminar structure, with different layers of neurons stereotypically connected in a c”