Brain Connectomes Come of Age

TL;DR

This paper discusses the use of recent connectome databases to build hierarchical and laminar models of primate brains, revealing insights into neural dynamics, signal propagation, and conscious perception, and emphasizing the synergy between empirical data and computational modeling.

Contribution

It introduces large-scale, laminar-structured models of macaque cortex based on connectome data, linking structural connectivity to neural dynamics and consciousness phenomena.

Findings

Layer-dependent and frequency-modulated cortical interactions.

Threshold phenomenon for stimulus access to prefrontal cortex.

Connectomics informs theoretical understanding of brain function.

Abstract

Databases of directed- and weighted- connectivity for mouse, macaque and marmoset monkeys, have recently become available and begun to be used to build dynamical models. A hierarchical organization can be defined based on laminar patterns of cortical connections, possibly improved by thalamocortical projections. A large-scale model of the macaque cortex endowed with a laminar structure accounts for layer-dependent and frequency-modulated interplays between bottom-up and top-down processes. Signal propagation in a version of the model with spiking neurons displays a threshold of stimulus amplitude for the activity to gain access to the prefrontal cortex, reminiscent of the ignition phenomenon associated with conscious perception. These two examples illustrate how connectomics may inform theory leading to discoveries. Computational modeling raises open questions for future empirical research, in a back-and-forth collaboration of experimentalists and theorists.