Effective connectivity of depth-structure-selective patches in the lateral bank of the macaque intraparietal sulcus

Abstract

Extrastriate cortical areas are frequently composed of subpopulations of neurons encoding specific features or stimuli, such as color, disparity, or faces, and patches of neurons encoding similar stimulus properties are typically embedded in interconnected networks, such as the attention or face-processing network. The goal of the current study was to examine the effective connectivity of subsectors of neurons in the same cortical area with highly similar neuronal response properties. We first recorded single- and multi-unit activity to identify two neuronal patches in the anterior part of the macaque intraparietal sulcus (IPS) showing the same depth structure selectivity and then employed electrical microstimulation during functional magnetic resonance imaging in these patches to determine the effective connectivity of these patches. The two IPS subsectors we identified-with the same neuronal response properties and in some cases separated by only 3 mm-were effectively connected to remarkably distinct cortical networks in both dorsal and ventral stream in three macaques. Conversely, the differences in effective connectivity could account for the known visual-to-motor gradient within the anterior IPS. These results clarify the role of the anterior IPS as a pivotal brain region where dorsal and ventral visual stream interact during object analysis. Thus, in addition to the anatomical connectivity of cortical areas and the properties of individual neurons in these areas, the effective connectivity provides novel key insights into the widespread functional networks that support behavior.

Fig 1. Functional properties of IPS subsectors.

A. aAIP. Example neuron showing selectivity for disparity-defined depth-structure (convex versus concave; rows), across different positions in depth (columns). B. Example neuron in pAIP showing selectivity for disparity-defined depth-structure (convex versus concave), across different positions in depth (columns). C. LIP. Example neuron with target-selective responses in a visually guided saccade task. Histograms demonstrate the seven possible target locations, positioned as shown on the screen. The position of the central fixation point is marked with the red dot.

Fig 2. Microstimulation of area aAIP.

A. T-score maps for the contrast EM-NoEM, for individual animals, represented on coronal sections (template anatomy). Leftmost columns show data for monkey M in the sedated and awake states, respectively; rightmost columns show results for monkeys C and K. See files aAIP* in [25]. B. T-score maps for the contrast EM-NoEM, group data, represented on a flat map. a: anterior; d: dorsal. C. Percent signal change calculated in the predefined ROIs. * p < 0.05; corrected for multiple comparisons (32 ROIs). Black lines indicate standard error of the mean.

Fig 3. Microstimulation of area pAIP.

A. T-score maps for the contrast EM-NoEM for individual animals, represented on coronal sections (template anatomy). Leftmost columns show data for monkey M in the sedated and the awake state, respectively; rightmost columns show results for monkey C and K. See files pAIP* in [25]. B. T-score maps for the contrast EM-NoEM, group data, represented on a flat map. a: anterior; d: dorsal. C. Percent signal change. * p < 0.05; corrected for multiple comparisons (32 ROIs). Black lines indicate standard error of the mean.

Fig 4. Microstimulation of area LIP.

A. T-score maps for the contrast EM-NoEM, for individual animals, represented on coronal sections (template anatomy). See files LIP* in [25]. B. T-score maps for the contrast EM-NoEM, data from individual sessions, showing EM-induced FEF activations. C. T-score maps for the contrast EM-NoEM, group data, represented on a flat map. a: anterior; d: dorsal. D. Percent signal change * p < 0.05; corrected for multiple comparisons (32 ROIs). Black lines indicate standard error of the mean.