Fig. 2 |. Timescale hierarchies and their implications for functional connectivity,

a | Connections between 29 areas in an anatomically constrained dynamical model of macaque cortex. Strong connections are indicated by lines, with line thickness determined by connection strength, b | The model shows a hierarchy of timescales, with sensory areas and association areas characterized by short and long timescales, respectively. The left graph depicts the autocorrelation function of neural activity in each of a subset of areas. From these functions, a dominant time constant was extracted (displayed as a function of the area’s hierarchical position on the right), c | The functional connectivity matrix of the macaque cortex model where areas are assumed to be identical (left) is compared to the matrix when the model includes a macroscopic gradient (right). A gradient of synaptic excitation enhances functional connectivity especially for association areas with slow time constants, whereas functional connectivity of early visual areas (upper left corner of the matrix) is similar with or without a macroscopic gradient. 2, somatosensory area 2; 5, somatosensory area 5; 7A, area 7A; 7B, area 7B; 7m, area 7m; 8B, area 8B; 81, lateral part of area 8; 8m, medial part of area 8; 9/46d, dorsal part of area 9/46; 9/46v, ventral part of area 9/46; 10, area 10; 24c, area 24c; 46d, dorsal part of area 46; DP, dorsal prelunate area; FI, frontal area FI; F2, frontal area F2; F5, frontal area F5; F7, frontal area F7; MT, middle temporal area; PBr, rostral part of the parabelt area; ProM, area ProM; STPc, caudal part of the superior temporal polysensory area; STPi, intermediate part of the superior temporal polysensory area; STPr, rostral part of the superior temporal polysensory area; TEO, area TEO; TEpd, posterior-dorsal part of area TE; VI, primary visual cortex; V2, visual area 2; V4, visual area 4. Parts a-c are adapted from Chaudhuri et al.³⁰.