Connecting multimodality in human communication

A successful reciprocal evaluation of social signals serves as a prerequisite for social coherence and empathy. In a previous fMRI study we studied naturalistic communication situations by presenting video clips to our participants and recording their behavioral responses regarding empathy and its components. In two conditions, all three channels transported congruent emotional or neutral information, respectively. Three conditions selectively presented two emotional channels and one neutral channel and were thus bimodally emotional. We reported channel-specific emotional contributions in modality-related areas, elicited by dynamic video clips with varying combinations of emotionality in facial expressions, prosody, and speech content. However, to better understand the underlying mechanisms accompanying a naturalistically displayed human social interaction in some key regions that presumably serve as specific processing hubs for facial expressions, prosody, and speech content, we pursued a reanalysis of the data. Here, we focused on two different descriptions of temporal characteristics within these three modality-related regions [right fusiform gyrus (FFG), left auditory cortex (AC), left angular gyrus (AG) and left dorsomedial prefrontal cortex (dmPFC)]. By means of a finite impulse response (FIR) analysis within each of the three regions we examined the post-stimulus time-courses as a description of the temporal characteristics of the BOLD response during the video clips. Second, effective connectivity between these areas and the left dmPFC was analyzed using dynamic causal modeling (DCM) in order to describe condition-related modulatory influences on the coupling between these regions. The FIR analysis showed initially diminished activation in bimodally emotional conditions but stronger activation than that observed in neutral videos toward the end of the stimuli, possibly by bottom-up processes in order to compensate for a lack of emotional information. The DCM analysis instead showed a pronounced top-down control. Remarkably, all connections from the dmPFC to the three other regions were modulated by the experimental conditions. This observation is in line with the presumed role of the dmPFC in the allocation of attention. In contrary, all incoming connections to the AG were modulated, indicating its key role in integrating multimodal information and supporting comprehension. Notably, the input from the FFG to the AG was enhanced when facial expressions conveyed emotional information. These findings serve as preliminary results in understanding network dynamics in human emotional communication and empathy.

[1]  Roland Neumann,et al.  Bottom-Up and Top-Down Influences of Beliefs on Emotional Responses: Fear of Heights in a Virtual Environment , 2012, Annual Review of Cybertherapy and Telemedicine.

[2]  Karl J. Friston,et al.  Post hoc Bayesian model selection , 2011, NeuroImage.

[3]  Marina De Vos,et al.  Newcastle University Eprints Date Deposited: 24 Effective Connectivity of the Human Cerebellum during Visual Attention Lum— during Attention—with Dorsal Visual Stream Regions including Posterior Parietal Cortex (ppc) and Left Secondary Visual Cortex (v5). Dynamic Causal Modeling Revealed a Modulatio , 2022 .

[4]  Daniel A. Schneider,et al.  The differential contribution of facial expressions, prosody, and speech content to empathy , 2012, Cognition & emotion.

[5]  F. Colavita Human sensory dominance , 1974 .

[6]  M. Peelen,et al.  Supramodal Representations of Perceived Emotions in the Human Brain , 2010, The Journal of Neuroscience.

[7]  M. Posner,et al.  The attention system of the human brain. , 1990, Annual review of neuroscience.

[8]  S. Campanella,et al.  Integrating face and voice in person perception , 2007, Trends in Cognitive Sciences.

[9]  D Mumford,et al.  On the computational architecture of the neocortex. II. The role of cortico-cortical loops. , 1992, Biological cybernetics.

[10]  Frank Schneider,et al.  Multimodal human communication — Targeting facial expressions, speech content and prosody , 2012, NeuroImage.

[11]  Karl J. Friston,et al.  Unified segmentation , 2005, NeuroImage.

[12]  S. Campanella,et al.  Integrating face and voice in person perception , 2007, Trends in Cognitive Sciences.

[13]  Henrik Walter,et al.  Functional relations of empathy and mentalizing: An fMRI study on the neural basis of cognitive empathy , 2011, NeuroImage.

[14]  D. Mumford On the computational architecture of the neocortex , 2004, Biological Cybernetics.

[15]  N. Kanwisher,et al.  The Fusiform Face Area: A Module in Human Extrastriate Cortex Specialized for Face Perception , 1997, The Journal of Neuroscience.

[16]  M. Wertheimer Untersuchungen zur Lehre von der Gestalt. II , 1923 .

[17]  J. Ridley Studies of Interference in Serial Verbal Reactions , 2001 .

[18]  Karl J. Friston,et al.  A theory of cortical responses , 2005, Philosophical Transactions of the Royal Society B: Biological Sciences.

[19]  Karl J. Friston The free-energy principle: a unified brain theory? , 2010, Nature Reviews Neuroscience.

[20]  Perrine Ruby,et al.  Distinct Regions of the Medial Prefrontal Cortex Are Associated with Self-referential Processing and Perspective Taking , 2007, Journal of Cognitive Neuroscience.

[21]  John H. R. Maunsell,et al.  The connections of the middle temporal visual area (MT) and their relationship to a cortical hierarchy in the macaque monkey , 1983, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[22]  Claus Lamm,et al.  How Do We Empathize with Someone Who Is Not Like Us? A Functional Magnetic Resonance Imaging Study , 2010, Journal of Cognitive Neuroscience.

[23]  Gabriele Lohmann,et al.  Critical comments on dynamic causal modelling , 2012, NeuroImage.

[24]  R. Dolan,et al.  Effects of Attention and Emotion on Face Processing in the Human Brain An Event-Related fMRI Study , 2001, Neuron.

[25]  Paul Wright,et al.  Dissociated responses in the amygdala and orbitofrontal cortex to bottom–up and top–down components of emotional evaluation , 2008, NeuroImage.

[26]  D. Schacter,et al.  Functional MRI evidence for a role of frontal and inferior temporal cortex in amodal components of priming. , 2000, Brain : a journal of neurology.

[27]  Hauke R. Heekeren,et al.  Neural correlates of social cognition in naturalistic settings: A model-free analysis approach , 2010, NeuroImage.

[28]  J. R. Simon,et al.  Reactions toward the source of stimulation. , 1969, Journal of experimental psychology.

[29]  Yang Seok Cho,et al.  Neural correlates of top–down processing in emotion perception: An ERP study of emotional faces in white noise versus noise-alone stimuli , 2010, Brain Research.

[30]  John J. Foxe,et al.  Multisensory interactions in early evoked brain activity follow the principle of inverse effectiveness , 2011, NeuroImage.

[31]  Pierre Baldi,et al.  Bayesian surprise attracts human attention , 2005, Vision Research.

[32]  R. Desimone,et al.  Neural mechanisms for visual memory and their role in attention. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[33]  Frank Schneider,et al.  Processing of disgusted faces is facilitated by odor primes: A functional MRI study , 2010, NeuroImage.

[34]  S. Eickhoff,et al.  Sustaining attention to simple tasks: a meta-analytic review of the neural mechanisms of vigilant attention. , 2013, Psychological bulletin.

[35]  T. Singer,et al.  The empathic brain: how, when and why? , 2006, Trends in Cognitive Sciences.

[36]  A. Borst Seeing smells: imaging olfactory learning in bees , 1999, Nature Neuroscience.

[37]  R. Desimone,et al.  Neural mechanisms of selective visual attention. , 1995, Annual review of neuroscience.

[38]  Karl J. Friston,et al.  Attention, Uncertainty, and Free-Energy , 2010, Front. Hum. Neurosci..

[39]  Jesper Andersson,et al.  Valid conjunction inference with the minimum statistic , 2005, NeuroImage.

[40]  Aina Puce,et al.  Inverse Effectiveness and Multisensory Interactions in Visual Event-Related Potentials with Audiovisual Speech , 2012, Brain Topography.