Seeing biological actions in 3 D : An f MRI study

Abstract

Precise kinematics or body configuration cannot be recovered from visual input without disparity information. Yet, no imaging study has investigated the role of disparity on action observation. Here, we investigated the interaction between disparity and the main cues of biological motion, kinematics and configuration, in two fMRI experiments. Stimuli were presented as point‐light figures, depicting complex action sequences lasting 21 s. We hypothesized that interactions could occur at any of the three levels of the action observation network, comprising occipitotemporal, parietal and premotor cortex, with premotor cortex being the most likely location. The main effects of kinematics and configuration confirmed that the biological motion sequences activated all three levels of the action observation network, validating our approach. The interaction between configuration and disparity activated only premotor cortex, whereas interactions between kinematics and disparity occurred at all levels of the action observation network but were strongest at the premotor level. Control experiments demonstrated that these interactions could not be accounted for by low level motion in depth, task effects, spatial attention, or eye movements, including vergence. These results underscore the role of premotor cortex in action observation, and in imitating others or responding to their actions. Hum Brain Mapp 37:203–219, 2016. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

The topographical organization of motor processing: An ALE meta-analysis on six action domains and the relevance of Broca’s region

“…As expected, the main cluster involved during action observation spans across the occipital and temporal lobes, reaching the left inferior and superior temporal gyri, the fusiform gyrus and the insula. The occipito-temporal regions and the fusiform gyrus are thought to be involved in processing biological motion, of both conspecifics and nonconspecifics (Buccino et al, 2004;Georgescu et al, 2014;Jastorff et al, 2016). Consistently with the proposal of an action observation network (Grafton, 2009), we also found an involvement of the bilateral premotor cortex, BA9 and right-hemispheric convergence across BA44 and BA46.…”

Mapping effective connectivity between the frontal and contralateral primary motor cortex using dual-coil transcranial magnetic stimulation

“…S1). However, others have argued that this region is found more anteriorly and in the depth of the junction between the dorsal precentral gyrus and superior frontal sulcus (Jastorff et al, 2016). Our cluster was found on the bank of the dorsal precentral gyrus near the putative boundary between dorsal and ventral PM (Tomassini et al, 2007), since it is slightly more dorsal it has been defined as the ventral part of PMd (Avanzini et al, 2016;Avanzini et al, 2018;Fan et al, 2016;Tomassini et al, 2007), and therefore labelled Area 6d/FEF.…”

“…In area 6d/FEF, there was a tendency for a facilitatory effect at rest, which switched to inhibition during prep-ABD, these effects were only shown in a small number of vertices, whereas a larger cluster of vertices showed a switch back to facilitation during prep-PG. We argue this cluster occupies the ventral part of PMd (Avanzini et al, 2016;Avanzini et al, 2018;Fan et al, 2016;Tomassini et al, 2007) and not FEF (Jastorff et al, 2016), especially since there is no evidence of connections between FEF and M1 (Huerta et al, 1987;Dum and Strick, 2002). Thus, differential interactions between this region and cM1 from rest to preparing to move might seem less surprising since PMd is involved in the preparation of upper limb movement (Ariani et al, 2015;Baumer et al, 2006;Begliomini et al, 2007;Begliomini et al, 2014;Gallivan et al, 2011;Rizzolatti et al, 2014).…”

Disparity level identification using the voxel‐wise Gabor model of fMRI data

“…The functional magnetic resonance imaging (fMRI) technique can be used to characterize the population‐level disparity responses. Several fMRI studies investigated population‐level disparity responses in the human cortex and revealed that V1, V2, V3, V3A, V3B, V7, hMT+/V5 (human motion complex), hV4 (human area V4), lateral occipital cortex, parietal cortex, and premotor cortex were selective for binocular disparities (Backus, Fleet, Parker, & Heeger, ; Brouwer, Van Ee, & Schwarzbach, ; Georgieva, Peeters, Kolster, Todd, & Orban, ; Gilaie‐Dotan, Ullman, Kushnir, & Malach, ; Jastorff, Abdollahi, Fasano, & Orban, ; Li et al, ; Minini, Parker, & Bridge, ; Neri, Bridge, & Heeger, ; Tsao et al, ; Welchman, Deubelius, Conrad, Bülthoff, & Kourtzi, ). Moreover, some studies applied multivoxel pattern analysis (MVPA) methods to explore the neural mechanisms that discriminate disparity levels and found that dorsal areas and posterior parietal areas had a higher predictive accuracy for decoding the disparity magnitude or depth sign than ventral areas (Patten & Welchman, ; Preston, Li, Kourtzi, & Welchman, ).…”

“…Several fMRI studies investigated population-level disparity responses in the human cortex and revealed that V1, V2, V3, V3A, V3B, V7, hMT+/V5 (human motion complex), hV4 (human area V4), lateral occipital cortex, parietal cortex, and premotor cortex were selective for binocular disparities (Backus, Fleet, Parker, & Heeger, 2001;Brouwer, Van Ee, & Schwarzbach, 2005;Georgieva, Peeters, Kolster, Todd, & Orban, 2009;Gilaie-Dotan, Ullman, Kushnir, & Malach, 2002;Jastorff, Abdollahi, Fasano, & Orban, 2016;Li et al, 2017;Minini, Parker, & Bridge, 2010;Neri, Bridge, & Heeger, 2004;Tsao et al, 2003;Welchman, Deubelius, Conrad, Bülthoff, & Kourtzi, 2005).…”