Visual Information Routes in the Posterior Dorsal and Ventral Face Network Studied with Intracranial Neurophysiology and White Matter Tract Endpoints

Anatomo-functional basis of emotional and motor resonance elicited by facial expressions

Simulation theories predict that the observation of other's expressions modulates neural activity in the same centres controlling their production. This hypothesis has been developed by two models, postulating that the visual input is directly projected either to the motor system for action recognition (motor resonance) or to emotional/interoceptive regions for emotional contagion and social synchronization (emotional resonance). Here we investigated the role of frontal/insular regions in the processing of observed emotional expressions by combining intracranial recording, electrical stimulation and effective connectivity. First, we intracranially recorded from prefrontal, premotor or anterior insular regions of 44 patients during the passive observation of emotional expressions, finding widespread modulations in prefrontal/insular regions (anterior cingulate cortex, anterior insula, orbitofrontal cortex and inferior frontal gyrus) and motor territories (Rolandic operculum and inferior frontal junction). Subsequently, we electrically stimulated the activated sites, finding that (i) in the anterior cingulate cortex and anterior insula, the stimulation elicited emotional/interoceptive responses, as predicted by the 'emotional resonance model'; (ii) in the Rolandic operculum it evoked face/mouth sensorimotor responses, in line with the 'motor resonance' model; and (iii) all other regions were unresponsive or revealed functions unrelated to the processing of facial expressions. Finally, we traced the effective connectivity to sketch a network-level description of these regions, finding that the anterior cingulate cortex and the anterior insula are reciprocally interconnected while the Rolandic operculum is part of the parieto-frontal circuits and poorly connected with the former. These results support the hypothesis that the pathways hypothesized by the 'emotional resonance' and the 'motor resonance' models work in parallel, differing in terms of spatio-temporal fingerprints, reactivity to electrical stimulation and connectivity patterns.

From Motion to Emotion: Visual Pathways and Potential Interconnections

The two visual pathway description of [Ungerleider, L. G., & Mishkin, M. Two cortical visual systems. In D. J. Dingle, M. A. Goodale, & R. J. W. Mansfield (Eds.), Analysis of visual behavior (pp. 549-586). Cambridge, MA: MIT, 1982] changed the course of late 20th century systems and cognitive neuroscience. Here, I try to reexamine our laboratory's work through the lens of the [Pitcher, D., & Ungerleider, L. G. Evidence for a third visual pathway specialized for social perception. Trends in Cognitive Sciences, 25, 100-110, 2021] new third visual pathway. I also briefly review the literature related to brain responses to static and dynamic visual displays, visual stimulation involving multiple individuals, and compare existing models of social information processing for the face and body. In this context, I examine how the posterior STS might generate unique social information relative to other brain regions that also respond to social stimuli. I discuss some of the existing challenges we face with assessing how information flow progresses between structures in the proposed functional pathways and how some stimulus types and experimental designs may have complicated our data interpretation and model generation. I also note a series of outstanding questions for the field. Finally, I examine the idea of a potential expansion of the third visual pathway, to include aspects of previously proposed "lateral" visual pathways. Doing this would yield a more general entity for processing motion/action (i.e., "[inter]action") that deals with interactions between people, as well as people and objects. In this framework, a brief discussion of potential hemispheric biases for function, and different forms of neuropsychological impairments created by focal lesions in the posterior brain is highlighted to help situate various brain regions into an expanded [inter]action pathway.

"Calculating faces": can face perception paradigms enrich dyscalculia research?

Developmental dyscalculia (DD) is a subtype of learning disabilities, which is characterized by lower mathematical skills despite average intelligence and average or satisfactory performance in other academic areas. It is not fully understood how such deficits emerge in the course of brain development. When considering the mechanisms of dyscalculia, two domain-specific systems are distinguished. The Approximate Number System (ANS) is related to the approximate estimation of large sets, and the Object Tracking System (OTS) is responsible for subitizing, that is, the exact quantification of small sets. In recent years, the multiple-deficit framework has become increasingly popular. On the one hand, it explains the impairment of certain general cognitive functions in children with DD, such as executive functions, attention, visual-perceptual discrimination, processing speed, and rapid scanning of visual information. On the other hand, it provides a theoretical basis for explaining the simultaneous occurrence of the different types of other comorbid conditions (such as dyslexia and ADHD) and the relationship between them. We suggest that the face recognition could be considered as another, probably impaired function in dyscalculic individuals. We highlight several brain areas involved both in numerical and facial processing: intraparietal sulcus (IPS), fusiform gyrus (FFG), and hippocampus (HC). We consider the possibility of expanding the scope of dyscalculia research by application of face perception paradigms.

Real and Deepfake Face Recognition: An EEG Study on Cognitive and Emotive Implications

The human brain's role in face processing (FP) and decision making for social interactions depends on recognizing faces accurately. However, the prevalence of deepfakes, AI-generated images, poses challenges in discerning real from synthetic identities. This study investigated healthy individuals' cognitive and emotional engagement in a visual discrimination task involving real and deepfake human faces expressing positive, negative, or neutral emotions. Electroencephalographic (EEG) data were collected from 23 healthy participants using a 21-channel dry-EEG headset; power spectrum and event-related potential (ERP) analyses were performed. Results revealed statistically significant activations in specific brain areas depending on the authenticity and emotional content of the stimuli. Power spectrum analysis highlighted a right-hemisphere predominance in theta, alpha, high-beta, and gamma bands for real faces, while deepfakes mainly affected the frontal and occipital areas in the delta band. ERP analysis hinted at the possibility of discriminating between real and synthetic faces, as N250 (200-300 ms after stimulus onset) peak latency decreased when observing real faces in the right frontal (LF) and left temporo-occipital (LTO) areas, but also within emotions, as P100 (90-140 ms) peak amplitude was found higher in the right temporo-occipital (RTO) area for happy faces with respect to neutral and sad ones.

Electrical Stimulation of Temporal and Limbic Circuitry Produces Distinct Responses in Human Ventral Temporal Cortex

The human ventral temporal cortex (VTC) is highly connected to integrate visual perceptual inputs with feedback from cognitive and emotional networks. In this study, we used electrical brain stimulation to understand how different inputs from multiple brain regions drive unique electrophysiological responses in the VTC. We recorded intracranial EEG data in 5 patients (3 female) implanted with intracranial electrodes for epilepsy surgery evaluation. Pairs of electrodes were stimulated with single-pulse electrical stimulation, and corticocortical evoked potential responses were measured at electrodes in the collateral sulcus and lateral occipitotemporal sulcus of the VTC. Using a novel unsupervised machine learning method, we uncovered 2-4 distinct response shapes, termed basis profile curves (BPCs), at each measurement electrode in the 11-500 ms after stimulation interval. Corticocortical evoked potentials of unique shape and high amplitude were elicited following stimulation of several regions and classified into a set of four consensus BPCs across subjects. One of the consensus BPCs was primarily elicited by stimulation of the hippocampus; another by stimulation of the amygdala; a third by stimulation of lateral cortical sites, such as the middle temporal gyrus; and the final one by stimulation of multiple distributed sites. Stimulation also produced sustained high-frequency power decreases and low-frequency power increases that spanned multiple BPC categories. Characterizing distinct shapes in stimulation responses provides a novel description of connectivity to the VTC and reveals significant differences in input from cortical and limbic structures.SIGNIFICANCE STATEMENT Disentangling the numerous input influences on highly connected areas in the brain is a critical step toward understanding how brain networks work together to coordinate human behavior. Single-pulse electrical stimulation is an effective tool to accomplish this goal because the shapes and amplitudes of signals recorded from electrodes are informative of the synaptic physiology of the stimulation-driven inputs. We focused on targets in the ventral temporal cortex, an area strongly implicated in visual object perception. By using a data-driven clustering algorithm, we identified anatomic regions with distinct input connectivity profiles to the ventral temporal cortex. Examining high-frequency power changes revealed possible modulation of excitability at the recording site induced by electrical stimulation of connected regions.

Category-specific and category-general neural codes of recognition memory in the ventral visual pathway

Researchers have identified category-specific brain regions, such as the fusiform face area (FFA) and parahippocampal place area (PPA) in the ventral visual pathway, which respond preferentially to one particular category of visual objects. In addition to their category-specific role in visual object identification and categorization, regions in the ventral visual pathway play critical roles in recognition memory. Nevertheless, it is not clear whether the contributions of those brain regions to recognition memory are category-specific or category-general. To address this question, the present study adopted a subsequent memory paradigm and multivariate pattern analysis (MVPA) to explore category-specific and category-general neural codes of recognition memory in the visual pathway. The results revealed that the right FFA and the bilateral PPA showed category-specific neural patterns supporting recognition memory of faces and scenes, respectively. In contrast, the lateral occipital cortex seemed to carry category-general neural codes of recognition memory. These results provide neuroimaging evidence for category-specific and category-general neural mechanisms of recognition memory in the ventral visual pathway.

Effects of face repetition on ventral visual stream connectivity using dynamic causal modelling of fMRI data

Stimulus repetition normally causes reduced neural activity in brain regions that process that stimulus. Some theories claim that this "repetition suppression" reflects local mechanisms such as neuronal fatigue or sharpening within a region, whereas other theories claim that it results from changed connectivity between regions, following changes in synchrony or top-down predictions. In this study, we applied dynamic causal modeling (DCM) on a public fMRI dataset involving repeated presentations of faces and scrambled faces to test whether repetition affected local (self-connections) and/or between-region connectivity in left and right early visual cortex (EVC), occipital face area (OFA) and fusiform face area (FFA). Face "perception" (faces versus scrambled faces) modulated nearly all connections, within and between regions, including direct connections from EVC to FFA, supporting a non-hierarchical view of face processing. Face "recognition" (familiar versus unfamiliar faces) modulated connections between EVC and OFA/FFA, particularly in the left hemisphere. Most importantly, immediate and delayed repetition of stimuli were also best captured by modulations of connections between EVC and OFA/FFA, but not self-connections of OFA/FFA, consistent with synchronization or predictive coding theories, though also possibly reflecting local mechanisms like synaptic depression.

Face Processing in Developmental Prosopagnosia: Altered Neural Representations in the Fusiform Face Area

Rationale: Face expertise is a pivotal social skill. Developmental prosopagnosia (DP), i.e., the inability to recognize faces without a history of brain damage, affects about 2% of the general population, and is a renowned model system of the face-processing network. Within this network, the right Fusiform Face Area (FFA), is particularly involved in face identity processing and may therefore be a key element in DP. Neural representations within the FFA have been examined with Representational Similarity Analysis (RSA), a data-analytical framework in which multi-unit measures of brain activity are assessed with correlation analysis. Objectives: Our study intended to scrutinize modifications of FFA-activation during face encoding and maintenance based on RSA. Methods: Thirteen participants with DP (23-70 years) and 12 healthy control subjects (19-62 years) participated in a functional MRI study, including morphological MRI, a functional FFA-localizer and a modified Sternberg paradigm probing face memory encoding and maintenance. Memory maintenance of one, two, or four faces represented low, medium, and high memory load. We examined conventional activation differences in response to working memory load and applied RSA to compute individual correlation-matrices on the voxel level. Group correlation-matrices were compared via Donsker's random walk analysis. Results: On the functional level, increased memory load entailed both a higher absolute FFA-activation level and a higher degree of correlation between activated voxels. Both aspects were deficient in DP. Interestingly, control participants showed a homogeneous degree of correlation for successful trials during the experiment. In DP-participants, correlation levels between FFA-voxels were significantly lower and were less sustained during the experiment. In behavioral terms, DP-participants performed poorer and had longer reaction times in relation to DP-severity. Furthermore, correlation levels were negatively correlated with reaction times for the most demanding high load condition. Conclusion: We suggest that participants with DP fail to generate robust and maintained neural representations in the FFA during face encoding and maintenance, in line with poorer task performance and prolonged reaction times. In DP, alterations of neural coding in the FFA might therefore explain curtailing in working memory and contribute to impaired long-term memory and mental imagery.