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

   https://doi.org/10.1093/cercor/bhab212  

   Babo-Rebelo, M; Puce, A; Bullock, D; Hugueville, L; Pestilli, F; Adam, C; Lehongre, K; Lambrecq, V; Dinkelacker, V; George, N (July 2021, Cerebral Cortex)

   null (Ed.)

   Abstract Occipitotemporal regions within the face network process perceptual and socioemotional information, but the dynamics and information flow between different nodes of this network are still debated. Here, we analyzed intracerebral EEG from 11 epileptic patients viewing a stimulus sequence beginning with a neutral face with direct gaze. The gaze could avert or remain direct, while the emotion changed to fearful or happy. N200 field potential peak latencies indicated that face processing begins in inferior occipital cortex and proceeds anteroventrally to fusiform and inferior temporal cortices, in parallel. The superior temporal sulcus responded preferentially to gaze changes with augmented field potential amplitudes for averted versus direct gaze, and large effect sizes relative to other network regions. An overlap analysis of posterior white matter tractography endpoints (from 1066 healthy brains) relative to active intracerebral electrodes in the 11 patients showed likely involvement of both dorsal and ventral posterior white matter pathways. Overall, our data provide new insight into the timing of face and social cue processing in the occipitotemporal brain and anchor the superior temporal cortex in dynamic gaze processing. 

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2. The Role of Unimodal Feedback Pathways in Gender Perception During Activation of Voice and Face Areas

   https://doi.org/10.3389/fnsys.2021.669256  

   Abbatecola, Clement; Gerardin, Peggy; Beneyton, Kim; Kennedy, Henry; Knoblauch, Kenneth (May 2021, Frontiers in Systems Neuroscience)

   Cross-modal effects provide a model framework for investigating hierarchical inter-areal processing, particularly, under conditions where unimodal cortical areas receive contextual feedback from other modalities. Here, using complementary behavioral and brain imaging techniques, we investigated the functional networks participating in face and voice processing during gender perception, a high-level feature of voice and face perception. Within the framework of a signal detection decision model, Maximum likelihood conjoint measurement (MLCM) was used to estimate the contributions of the face and voice to gender comparisons between pairs of audio-visual stimuli in which the face and voice were independently modulated. Top–down contributions were varied by instructing participants to make judgments based on the gender of either the face, the voice or both modalities ( N = 12 for each task). Estimated face and voice contributions to the judgments of the stimulus pairs were not independent; both contributed to all tasks, but their respective weights varied over a 40-fold range due to top–down influences. Models that best described the modal contributions required the inclusion of two different top–down interactions: (i) an interaction that depended on gender congruence across modalities (i.e., difference between face and voice modalities for each stimulus); (ii) an interaction that depended on the within modalities’ gender magnitude. The significance of these interactions was task dependent. Specifically, gender congruence interaction was significant for the face and voice tasks while the gender magnitude interaction was significant for the face and stimulus tasks. Subsequently, we used the same stimuli and related tasks in a functional magnetic resonance imaging (fMRI) paradigm ( N = 12) to explore the neural correlates of these perceptual processes, analyzed with Dynamic Causal Modeling (DCM) and Bayesian Model Selection. Results revealed changes in effective connectivity between the unimodal Fusiform Face Area (FFA) and Temporal Voice Area (TVA) in a fashion that paralleled the face and voice behavioral interactions observed in the psychophysical data. These findings explore the role in perception of multiple unimodal parallel feedback pathways. 

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3. Challenging the Classical View: Recognition of Identity and Expression as Integrated Processes

   https://doi.org/10.3390/brainsci13020296  

   Schwartz, Emily; O’Nell, Kathryn; Saxe, Rebecca; Anzellotti, Stefano (February 2023, Brain Sciences)

   Recent neuroimaging evidence challenges the classical view that face identity and facial expression are processed by segregated neural pathways, showing that information about identity and expression are encoded within common brain regions. This article tests the hypothesis that integrated representations of identity and expression arise spontaneously within deep neural networks. A subset of the CelebA dataset is used to train a deep convolutional neural network (DCNN) to label face identity (chance = 0.06%, accuracy = 26.5%), and the FER2013 dataset is used to train a DCNN to label facial expression (chance = 14.2%, accuracy = 63.5%). The identity-trained and expression-trained networks each successfully transfer to labeling both face identity and facial expression on the Karolinska Directed Emotional Faces dataset. This study demonstrates that DCNNs trained to recognize face identity and DCNNs trained to recognize facial expression spontaneously develop representations of facial expression and face identity, respectively. Furthermore, a congruence coefficient analysis reveals that features distinguishing between identities and features distinguishing between expressions become increasingly orthogonal from layer to layer, suggesting that deep neural networks disentangle representational subspaces corresponding to different sources. 

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4. The Role of the Right Hemisphere in Processing Phonetic Variability Between Talkers

   https://doi.org/10.1162/nol_a_00028  

   Luthra, Sahil (January 2021, Neurobiology of Language)

   null (Ed.)

   Abstract Neurobiological models of speech perception posit that both left and right posterior temporal brain regions are involved in the early auditory analysis of speech sounds. However, frank deficits in speech perception are not readily observed in individuals with right hemisphere damage. Instead, damage to the right hemisphere is often associated with impairments in vocal identity processing. Herein lies an apparent paradox: The mapping between acoustics and speech sound categories can vary substantially across talkers, so why might right hemisphere damage selectively impair vocal identity processing without obvious effects on speech perception? In this review, I attempt to clarify the role of the right hemisphere in speech perception through a careful consideration of its role in processing vocal identity. I review evidence showing that right posterior superior temporal, right anterior superior temporal, and right inferior / middle frontal regions all play distinct roles in vocal identity processing. In considering the implications of these findings for neurobiological accounts of speech perception, I argue that the recruitment of right posterior superior temporal cortex during speech perception may specifically reflect the process of conditioning phonetic identity on talker information. I suggest that the relative lack of involvement of other right hemisphere regions in speech perception may be because speech perception does not necessarily place a high burden on talker processing systems, and I argue that the extant literature hints at potential subclinical impairments in the speech perception abilities of individuals with right hemisphere damage. 

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5. Intracranial Electroencephalography and Deep Neural Networks Reveal Shared Substrates for Representations of Face Identity and Expressions

   https://doi.org/10.1523/JNEUROSCI.1277-22.2023  

   Schwartz, Emily; Alreja, Arish; Richardson, R. Mark; Ghuman, Avniel; Anzellotti, Stefano (May 2023, The Journal of Neuroscience)

   According to a classical view of face perception (Bruce and Young, 1986; Haxby et al., 2000), face identity and facial expression recognition are performed by separate neural substrates (ventral and lateral temporal face-selective regions, respectively). However, recent studies challenge this view, showing that expression valence can also be decoded from ventral regions (Skerry and Saxe, 2014; Li et al., 2019), and identity from lateral regions (Anzellotti and Caramazza, 2017). These findings could be reconciled with the classical view if regions specialized for one task (either identity or expression) contain a small amount of information for the other task (that enables above-chance decoding). In this case, we would expect representations in lateral regions to be more similar to representations in deep convolutional neural networks (DCNNs) trained to recognize facial expression than to representations in DCNNs trained to recognize face identity (the converse should hold for ventral regions). We tested this hypothesis by analyzing neural responses to faces varying in identity and expression. Representational dissimilarity matrices (RDMs) computed from human intracranial recordings (n= 11 adults; 7 females) were compared with RDMs from DCNNs trained to label either identity or expression. We found that RDMs from DCNNs trained to recognize identity correlated with intracranial recordings more strongly in all regions tested—even in regions classically hypothesized to be specialized for expression. These results deviate from the classical view, suggesting that face-selective ventral and lateral regions contribute to the representation of both identity and expression. SIGNIFICANCE STATEMENTPrevious work proposed that separate brain regions are specialized for the recognition of face identity and facial expression. However, identity and expression recognition mechanisms might share common brain regions instead. We tested these alternatives using deep neural networks and intracranial recordings from face-selective brain regions. Deep neural networks trained to recognize identity and networks trained to recognize expression learned representations that correlate with neural recordings. Identity-trained representations correlated with intracranial recordings more strongly in all regions tested, including regions hypothesized to be expression specialized in the classical hypothesis. These findings support the view that identity and expression recognition rely on common brain regions. This discovery may require reevaluation of the roles that the ventral and lateral neural pathways play in processing socially relevant stimuli. 

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