A Weighted and Directed Interareal Connectivity Matrix for Macaque Cerebral Cortex

By Nikola T. Markov, Mária Ercsey-Ravasz, A. R. Ribeiro Gomes, C. Lamy, L. Magrou, Julien Vezoli, P. Misery, A. Falchier, René Quilodran, M. Gariel and 12 more. Cerebral Cortex, 2012

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Retrograde tracer injections in 29 of the 91 areas of the macaque cerebral cortex revealed 1,615 interareal pathways, a third of which have not previously been reported. A weight index (extrinsic fraction of labeled neurons [FLNe]) was determined for each area-to-area pathway. Newly found projections were weaker on average compared with the known projections; nevertheless, the 2 sets of pathways had extensively overlapping weight distributions. Repeat injections across individuals revealed modest FLNe variability given the range of FLNe values (standard deviation <1 log unit, range 5 log units). The connectivity profile for each area conformed to a lognormal distribution, where a majority of projections are moderate or weak in strength. In the G29 × 29 interareal subgraph, two-thirds of the connections that can exist do exist. Analysis of the smallest set of areas that collects links from all 91 nodes of the G29 × 91 subgraph (dominating set analysis) confirms the dense (66%) structure of the cortical matrix. The G29 × 29 subgraph suggests an unexpectedly high incidence of unidirectional links. The directed and weighted G29 × 91 connectivity matrix for the macaque will be valuable for comparison with connectivity analyses in other species, including humans. It will also inform future modeling studies that explore the regularities of cortical networks.

Subfields: Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/9d958a7205555e1c051b2e3bd05d99d61d360ba4

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Citations in the corpus

Cortical High-Density Counterstream Architectures (2013, methodology): “The SW hypothesis for interareal connectivity has been challenged by recent studies that used a consistent and optimized methodology to establish a quantitative data-base of macaque interareal connectivity (8, 11).”
Contributions and challenges for network models in cognitive neuroscience (2014, methodology): “More detailed analyses have employed labeling density 18 or, in the case of diffusion imaging, density of tractography streamlines, connection probabilities or indices of myelination status to estimate connections weights, although anatomical interpretations remain unclear 19 .”
Real-time classification and sensor fusion with a spiking deep belief network (2013, background): “…have revealed the existence of anatomical connections that would enable cross-modal interactions also at lower levels (Falchier et al., 2002; Markov et al., 2012), and functional studies have provided some (but not conclusive) evidence of co-activations of early sensory areas by stimulation…”
Morphometric Similarity Networks Detect Microscale Cortical Organisation And Predict Inter-Individual Cognitive Variation (2017, positive): “…91 nodes of the macaque cortex using a histologically-defined and anatomical landmark-based parcellation (Markov et al., 2014) that has been previously used to report retrograde axonal tract-tracing experiments on 29 of the 91 nodes (Markov et al., 2012; Markov et al., 2014) (see Figure 4B).”
Anatomy of hierarchy: Feedforward and feedback pathways in macaque visual cortex (2013, background): “…V2 V6A 38.10 22.7 V2 STPi 7.41 27 V2 STPc 0.00 28.2 V2 TPt 0.00 25.2 V2 PGa 2.33 24.6 V2 IPa 37.04 24.2 V2 FST 7.05 16.2 The Journal of Comparative Neurology |Research in Systems Neuroscience 233 1998; Barone et al., 2000; Falchier et al., 2002; Clavagnier et al., 2004; Markov et al., 2011, 2012).”
A Predictive Network Model of Cerebral Cortical Connectivity Based on a Distance Rule (2013, positive): “The G29x29 subgraph has M = 536 (binary) links out of the maximum possible of N(N 1) = 812; it is a very dense graph with a density ðr=M=1⁄2NðN 1Þ Þ of 66% (Markov et al., 2012).”
Network hubs in the human brain. (2013, background): “…central hub nodes has been established in virtually all brain networks across a wide range of species, ranging from the mammalian [32,61,63,67,73,143,161], rodent [162], and avian [163] brain to cellular networks in the zebrafish larva [164], the fruit fly Drosophila [165], and the nematode…”
Modular Brain Networks (2015, methodology): “…mapped using various techniques, including reconstruction from serially sectioned electron micrographs (White et al. 1986) or the aggregation of data from anatomical tract-tracing experiments (Kötter et al. 2004, Markov et al. 2014, Oh et al. 2014, Scannell et al. 1995, Stephan et al. 2001).”
Large-Scale Gradients in Human Cortical Organization. (2018, neutral): “, [9,10]), they have been proposed to extend to transmodal association areas [8,44,45].”
Network neuroscience (2017, background): “Quantitative assessment of tract tracing experiments reveals relatively dense networks that include projections ranging in strength over six orders of magnitude 21 .”