Anatomy of hierarchy: Feedforward and feedback pathways in macaque visual cortex

By Nikola T. Markov, Julien Vezoli, P. Chameau, A. Falchier, René Quilodran, C. Huissoud, C. Lamy, P. Misery, P. Giroud, Shimon Ullman and 4 more. 2013

722 citations recorded by the source corpus.

The laminar location of the cell bodies and terminals of interareal connections determines the hierarchical structural organization of the cortex and has been intensively studied. However, we still have only a rudimentary understanding of the connectional principles of feedforward (FF) and feedback (FB) pathways. Quantitative analysis of retrograde tracers was used to extend the notion that the laminar distribution of neurons interconnecting visual areas provides an index of hierarchical distance (percentage of supragranular labeled neurons [SLN]). We show that: 1) SLN values constrain models of cortical hierarchy, revealing previously unsuspected areal relations; 2) SLN reflects the operation of a combinatorial distance rule acting differentially on sets of connections between areas; 3) Supragranular layers contain highly segregated bottom‐up and top‐down streams, both of which exhibit point‐to‐point connectivity. This contrasts with the infragranular layers, which contain diffuse bottom‐up and top‐down streams; 4) Cell filling of the parent neurons of FF and FB pathways provides further evidence of compartmentalization; 5) FF pathways have higher weights, cross fewer hierarchical levels, and are less numerous than FB pathways. Taken together, the present results suggest that cortical hierarchies are built from supra‐ and infragranular counterstreams. This compartmentalized dual counterstream organization allows point‐to‐point connectivity in both bottom‐up and top‐down directions. J. Comp. Neurol. 522:225–259, 2014. © 2013 Wiley Periodicals, Inc.

Subfields: Biophysics, Cognitive Neuroscience

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Citations in the corpus

Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Ventral Stream (2014, background): “This shows that information flow mainly takes place between neighboring visual areas, providing quantitative evidence for the thesis that the visual ventral stream is hierarchically organized (Markov et al., 2014), with downstream areas processing increasingly complex features of the retinal input.”
Working Memory 2.0 (2018, neutral): “It shares many aspects with previously proposed circuits for visual sensory function (Bastos et al., 2015b; Mejias et al., 2016).”
Predictive Processing: A Canonical Cortical Computation (2018, positive): “Cortical areas receive bottom-up input from the thalamus or other cortical areas, as well as extensive top-down inputs from many nearby and distal cortical areas, and higher-order thalamic nuclei (Felleman and Van Essen, 1991; Markov et al., 2014; Oh et al., 2014; Sherman, 2016; Zingg et al., 2014),”
Deep Learning With Spiking Neurons: Opportunities and Challenges (2018, background): “One insight from biology is that feedback connections, i.e., connections projecting from higher to lower layers, are common and important in hierarchically organized networks for information processing, such as the cortex (Markov et al., 2014).”
A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation (2020, neutral): “Extensive connectivity tracing studies and in vivo neural imaging studies have shown that these neocortical areas together form a hierarchical neural network with functionally distinct modules and feedforward and feedback pathways both within and between modules (Coogan and Burkhalter, 1993; Fellema”
Alpha-beta and gamma rhythms subserve feedback and feedforward influences among human visual cortical areas (2016, neutral): “, frontal cortex and ventral visual areas (Markov et al., 2014), possibly allowing frontal areas to change their functional hierarchical level dynamically (Bastos et al.”
Neural Elements for Predictive Coding (2016, background): “%) of forward-projecting layer 5 neurons (Markov et al., 2014).”
Hierarchical Heterogeneity across Human Cortex Shapes Large-Scale Neural Dynamics (2018, positive): “Hierarchical organization provides a parsimonious principle for the anatomical properties of long-range inter-areal connections in primate cortex (Felleman and Van Essen, 1991; Dombrowski et al., 2001; Markov et al., 2014).”
A voxel-wise encoding model for early visual areas decodes mental images of remembered scenes (2014, neutral): “Anatomical studies have revealed that EVA receives feedback projections from higher-order visual areas (Rockland and Pandya, 1979; Felleman and Van Essen, 1991; Markov et al., 2014a).”