Mechanisms of hemispheric lateralization: Asymmetric interhemispheric recruitment in the face perception network

Hemispheric dominance in reading system alters contribution to face processing lateralization across development

Face processing dominates the right hemisphere. This lateralization can be affected by co-lateralization within the same system and influence between different systems, such as neural competition from reading acquisition. Yet, how the relationship pattern changes through development remains unknown. This study examined the lateralization of core face processing and word processing in different age groups. By comparing fMRI data from 36 school-aged children and 40 young adults, we investigated whether there are age and regional effects on lateralization, and how relationships between lateralization within and between systems change across development. Our results showed significant right hemispheric lateralization in the core face system and left hemispheric lateralization in reading-related areas for both age groups when viewing faces and texts passively. While all participants showed stronger lateralization in brain regions of higher functional hierarchy when viewing faces, only adults exhibited this lateralization when viewing texts. In both age cohorts, there was intra-system co-lateralization for face processing, whereas an inter-system relationship was only found in adults. Specifically, functional lateralization of Broca's area during reading negatively predicted functional asymmetry in the FFA during face perception. This study initially provides neuroimaging evidence for the reading-induced neural competition theory from a maturational perspective in Chinese cohorts.

Altered Functional Connectivity of the Multisensory Vestibular Cortex in Patients with Chronic Unilateral Vestibulopathy

Background: Chronic unilateral vestibulopathy (CUVP) is a common chronic vestibular syndrome; the mechanisms of central vestibular compensation in CUVP are rarely studied. Methods: This study analyzed the data of 18 patients with CUVP and 18 healthy controls (HCs) and used seed-based functional connectivity (FC) and voxel-mirrored homotopic connectivity (VMHC) analyses to explore the FC alterations. Results: Compared with HCs, patients with CUVP showed decreased FC between the left dorsolateral superior frontal gyrus and the right hippocampus; the left middle frontal gyrus and the right posterior cingulate gyrus, the right hippocampus, the right parahippocampal gyrus. There is also a reduction in FC between the left and right insula. There was enhanced FC between the left supplementary motor area (SMA) and the bilateral superior occipital gyrus, the left hippocampus and the left posterior cingulate gyrus, as well as a the left middle temporal gyrus (p = 0.03). Additionally,VMHC was decreased between the bilateral medial superior frontal gyrus, the bilateral precentral gyrus, and the bilateral postcentral gyrus (p = 0.001). The zVMHC values in the bilateral superior frontal gyrus and the precentral gyrus were both negatively corrected with the Dizziness Handicap Inventory (DHI) score.well as Conclusions: Altered FC in regions of bilateral multisensory vestibular cortex existed in patients with CUVP. Decreased FC and VMHC in the bilateral multisensory vestibular cortex may affect vestibular information integration, thus affecting self-motion perception, spatial orientation, and postural control.

Modeling the association between functional connectivity and lateralization with the activity flow framework

The human brain is localized and distributed. On the one hand, each cognitive function tends to involve one hemisphere more than the other, also known as the principle of lateralization. On the other hand, interactions among brain regions in the form of functional connectivity (FC) are indispensable for intact function. Recent years have seen growing interest in the association between lateralization and FC. However, FC metrics vary from spurious correlation to causal associations. If lateralization manifests local processing and causal network interactions, more causally valid FC metrics should predict lateralization index (LI) better than FC based on simple correlations. The present study directly investigates this hypothesis within the activity flow framework to compare the association between lateralization and four brain connectivity metrics: correlation-based FC, multiple-regression FC, partial-correlation FC, and combinedFC. We propose two modeling approaches: the one-step approach, which models the relationship between LI and FC directly, and the two-step approach, which predicts the brain activation and calculates the LI. Our results indicated that multiple-regression FC, partial-correlation FC, and combinedFC could significantly improve the model prediction compared to correlation-based FC, which was consistent in a spatial working memory task (typically right-lateralized) and a language task (typically left-lateralized). The one-step and two-step approach yielded similar conclusions. In addition, the finding was replicated in a clinical sample of schizophrenia (SZ), bipolar disorder (BP), and attention deficit hyperactivity disorder (ADHD). The present study suggests that the causal interactions among brain regions help shape the lateralization pattern.

Unconscious face processing shows a different lateralisation pattern

Faces contain rich information and play a pivotal role in human daily social interactions. Previous studies have provided evidence for the left-visual-field-advantage in face perception. The current study investigated lateralisation when face stimuli were unconsciously presented using interocular suppression methods. The results showed that when an unconscious face stimulus was presented in one side of the visual field without other face stimuli, the unconscious face in the right visual field could break through interocular suppression faster than that in the left (Experiments 1 and 2). However, this right visual field processing advantage reversed to the left when a face stimulus either with (Experiment 2) or without (Experiment 3) visual awareness was presented concurrently with or prior to (Experiment 4) the unconscious face stimuli. These results showed that the unconscious face might have a different processing pattern compared with the conscious face. The relationship between this novel behavioural observation and known functional lateralisation of the fusiform face areas is discussed, suggesting a dynamic interaction between the two cortical hemispheres may underlie the formation of visual awareness for faces. The current study expands our understanding of face processing lateralisation and provided evidence on the asymmetric inter-hemisphere interaction patterns in forming visual awareness.

Lateralized Learning to Solve Complex Boolean Problems

Modern classifier systems can effectively classify targets that consist of simple patterns. However, they can fail to detect hierarchical patterns of features that exist in many real-world problems, such as understanding speech or recognizing object ontologies. Biological nervous systems have the ability to abstract knowledge from simple and small-scale problems in order to then apply it to resolve more complex problems in similar and related domains. It is thought that lateral asymmetry of biological brains allows modular learning to occur at different levels of abstraction, which can then be transferred between tasks. This work develops a novel evolutionary machine-learning (EML) system that incorporates lateralization and modular learning at different levels of abstraction. The results of analyzable Boolean tasks show that the lateralized system has the ability to encapsulate underlying knowledge patterns in the form of building blocks of knowledge (BBK). Lateralized abstraction transforms complex problems into simple ones by reusing general patterns (e.g., any parity problem becomes a sequence of the 2-bit parity problem). By enabling abstraction in evolutionary computation, the lateralized system is able to identify complex patterns (e.g., in hierarchical multiplexer (HMux) problems) better than existing systems.

Apperceptive and Associative Forms of Phonagnosia

PURPOSE OF REVIEW

Pronagnosia is a rare acquired or developmental pathological condition that consists of a selective difficulty to recognize familiar people by their voices. It can be distinguished into two different categories: apperceptive phonagnosia, which denotes a purely perceptual form of voice recognition disorder; and associative phonagnosia, in which patients have no perceptual defects, but cannot evaluate if the voice of a known person is or not familiar. The neural substrate of these two forms of voice recognition is still controversial, but it could concern different components of the core temporal voice areas and of extratemporal voice processing areas. This article reviews recent research on the neuropsychological and anatomo-clinical aspects of this condition.

RECENT FINDINGS

Data obtained in group studies or single case reports of phonagnosic patients suggest that apperceptive phonagnosia might be due to disruption of the core temporal voice areas, bilaterally located in the posterior parts of the superior temporal gyrus, whereas associative phonagnosia might result from impaired access to structures where voice representations are stored, due to a disconnection of these areas from structures of the voice extended system. Although these results must be confirmed by further investigations, they represent an important step toward understanding the nature and neural substrate of apperceptive and associative forms of phonagnosia.

Atypical responses to faces during binocular rivalry in early glaucoma

Purpose

Glaucoma is a progressive optic neuropathy that damages retinal ganglion cells and a neurodegenerative disease as it affects neural structures throughout the brain. In this study, we examined binocular rivalry responses in patients with early glaucoma in order to probe the function of stimulus-specific cortical areas involved in face perception.

Methods

Participants included 14 individuals (10 females, mean age 65 ± 7 years) with early pre-perimetric glaucoma and 14 age-matched healthy controls (7 females, mean age 59 ± 11 years). The 2 groups were equivalent in visual acuity and stereo-acuity. Three binocular rivalry stimulus pairs were used: (1) real face/house, (2) synthetic face/noise patch, and (3) synthetic face/spiral. For each stimulus pair, the images were matched in size and contrast level; they were viewed dichotically, and presented centrally and eccentrically at 3 degrees in the right (RH) and in the left hemifield (LH), respectively. The outcome measures were rivalry rate (i.e., perceptual switches/min) and time of exclusive dominance of each stimulus.

Results

For the face/house stimulus pair, rivalry rate of the glaucoma group (11 ± 6 switches/min) was significantly lower than that of the control group (15 ± 5 switches/min), but only in the LH location. The face dominated longer than the house in the LH for both groups. Likewise, for the synthetic face/noise patch stimulus pair, rivalry rate of the glaucoma group (11 ± 6 switches/min) was lower than that of the control group (16 ± 7 switches/min) in the LH, but the difference failed to reach significance. Interestingly, the mixed percept dominated less in glaucoma than in the control group. For the synthetic face/spiral stimulus pair, the glaucoma group had lower rivalry rate at all 3 stimulus locations.

Conclusion

This study reveals atypical responses to faces during binocular rivalry in patients with early glaucoma. The results may be suggestive of early neurodegeneration affecting stimulus-specific neural structures involved in face processing starting in the pre-perimetric phase of the disease.

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.

Modulation of Asymmetry in Auditory Perception through a Bilateral Auditory Intervention

The objective of this work was to analyze the modulating effect of an auditory intervention (AI) on the threshold and symmetry of auditory perception in people with different emotional states. The effects of AI were compared 3 months after using threshold audiometry (air conduction). The studied groups were emotional well-being (EWB) (n = 50, 14 with AI, 36 without AI); anxiety (ANX) (n = 31, 10 with AI, 21 without AI); and mixed group (MIX) (n = 45, 19 with AI, 26 without AI). The EWB group with AI lost the advantage of the left ear due to the hearing gain of the right ear, whereas in EWB without AI, no changes were observed. The ANX group with AI showed a non-significant improvement in both ears, maintaining the left interaural advantage. Interestingly, in the group without AI, the interaural difference was lost. The MIX group did not show interaural differences either with or without AI. However, the AI group showed a lower left ear threshold than that of the right ear, in contrast to the non-AI group. In conclusion, the application of this AI manages to decrease the prioritization of high frequencies, in addition to balance hearing between ears, which could decrease activation in states of anxiety.

The hidden face of hemispherectomy: Visuo-spatial and visuo-perceptive processing after left or right functional hemispherectomy in 40 children

Functional hemispherectomy results in good outcomes in cases of refractory epilepsy and constitutes a unique situation in which to study cerebral plasticity and the reorganization of lateralized functions of the brain, especially in cases of infancy or childhood surgery. Previous studies have highlighted the remarkable ability of the brain to recover language after left hemispherectomy. This leads to a reorganization of language networks toward right hemisphere, causing limitation in the development of visuo-spatial abilities, known as a crowding effect in the right hemisphere. Deficits in nonverbal functions have also been described as a more direct consequence of right hemipherectomy, but the results from case studies have sometimes been contradictory. We conducted a group study which may effectively compare patients with left and right hemispherectomy and address the effects of the age of seizure onset and surgery. We analyzed the general visuo-spatial and visuo-perceptive abilities, including face and emotional facial expression processing, in a group of 40 patients aged 7-16 years with left (n = 24) or right (n = 16) functional hemispherectomy. Although the groups did not differ, on average, in general visuo-spatial and visuo-perceptive skills, patients with right hemispherectomy were more impaired in the processing of faces and emotional facial expressions compared with patients with left hemispherectomy. This may reflect a specific deficit in the perceptual processing of faces after right hemispherectomy. Results are discussed in terms of limited plasticity of the left hemisphere for facial and configural processing.

Let's face it: The lateralization of the face perception network as measured with fMRI is not clearly right dominant

The neural face perception network is distributed across both hemispheres. However, the dominant role in humans is virtually unanimously attributed to the right hemisphere. Interestingly, there are, to our knowledge, no imaging studies that systematically describe the distribution of hemispheric lateralization in the core system of face perception across subjects in large cohorts so far. To address this, we determined the hemispheric lateralization of all core system regions (i.e., occipital face area (OFA), fusiform face area (FFA), posterior superior temporal sulcus (pSTS)) in 108 healthy subjects using functional magnetic resonance imaging (fMRI). We were particularly interested in the variability of hemispheric lateralization across subjects and explored how many subjects can be classified as right-dominant based on the fMRI activation pattern. We further assessed lateralization differences between different regions of the core system and analyzed the influence of handedness and sex on the lateralization with a generalized mixed effects regression model. As expected, brain activity was on average stronger in right-hemispheric brain regions than in their left-hemispheric homologues. This asymmetry was, however, only weakly pronounced in comparison to other lateralized brain functions (such as language and spatial attention) and strongly varied between individuals. Only half of the subjects in the present study could be classified as right-hemispheric dominant. Additionally, we did not detect significant lateralization differences between core system regions. Our data did also not support a general leftward shift of hemispheric lateralization in left-handers. Only the interaction of handedness and sex in the FFA revealed that specifically left-handed men were significantly more left-lateralized compared to right-handed males. In essence, our fMRI data did not support a clear right-hemispheric dominance of the face perception network. Our findings thus ultimately question the dogma that the face perception network - as measured with fMRI - can be characterized as "typically right lateralized".

From descriptive connectome to mechanistic connectome: Generative modeling in functional magnetic resonance imaging analysis

As a newly emerging field, connectomics has greatly advanced our understanding of the wiring diagram and organizational features of the human brain. Generative modeling-based connectome analysis, in particular, plays a vital role in deciphering the neural mechanisms of cognitive functions in health and dysfunction in diseases. Here we review the foundation and development of major generative modeling approaches for functional magnetic resonance imaging (fMRI) and survey their applications to cognitive or clinical neuroscience problems. We argue that conventional structural and functional connectivity (FC) analysis alone is not sufficient to reveal the complex circuit interactions underlying observed neuroimaging data and should be supplemented with generative modeling-based effective connectivity and simulation, a fruitful practice that we term "mechanistic connectome." The transformation from descriptive connectome to mechanistic connectome will open up promising avenues to gain mechanistic insights into the delicate operating principles of the human brain and their potential impairments in diseases, which facilitates the development of effective personalized treatments to curb neurological and psychiatric disorders.

Subliminal Emotional Faces Elicit Predominantly Right-Lateralized Amygdala Activation: A Systematic Meta-Analysis of fMRI Studies

Prior research suggests that conscious face processing occurs preferentially in right hemisphere occipito-parietal regions. However, less is known about brain regions associated with non-conscious processing of faces, and whether a right-hemispheric dominance persists in line with specific affective responses. We aim to review the neural responses systematically, quantitatively, and qualitatively underlying subliminal face processing. PubMed was searched for Functional Magnetic Resonance Imaging (fMRI) publications assessing subliminal emotional face stimuli up to March 2022. Activation Likelihood Estimation (ALE) meta-analyses and narrative reviews were conducted on all studies that met ALE requirements. Risk of bias was assessed using the AXIS tool. In a meta-analysis of all 22 eligible studies (merging clinical and non-clinical populations, whole brain and region of interest analyses), bilateral amygdala activation was reported in the left (x = −19.2, y = 1.5, z = −17.1) in 59% of studies, and in the right (x = 24.4, y = −1.7, z = −17.4) in 68% of studies. In a second meta-analysis of non-clinical participants only (n = 18), bilateral amygdala was again reported in the left (x = −18, y = 3.9, z = −18.4) and right (x = 22.8, y = −0.9, z = −17.4) in 56% of studies for both clusters. In a final meta-analysis of whole-brain studies only (n=14), bilateral amygdala was also reported in the left (x = −20.2, y = 2.9, z = −17.2) in 64% of studies, and right (x = 24.2, y = −0.7, z = −17.8) in 71% of studies. The findings suggest that non-consciously detected emotional faces may influence amygdala activation, especially right-lateralized (a higher percentage of convergence in studies), which are integral for pre-conscious affect and long-term memory processing.

Alpha-2 Adrenoreceptor Antagonist Yohimbine Potentiates Consolidation of Conditioned Fear

BACKGROUND

Hyperconsolidation of aversive associations and poor extinction learning have been hypothesized to be crucial in the acquisition of pathological fear. Previous animal and human research points to the potential role of the catecholaminergic system, particularly noradrenaline and dopamine, in acquiring emotional memories. Here, we investigated in a between-participants design with 3 groups whether the noradrenergic alpha-2 adrenoreceptor antagonist yohimbine and the dopaminergic D2-receptor antagonist sulpiride modulate long-term fear conditioning and extinction in humans.

METHODS

Fifty-five healthy male students were recruited. The final sample consisted of n = 51 participants who were explicitly aware of the contingencies between conditioned stimuli (CS) and unconditioned stimuli after fear acquisition. The participants were then randomly assigned to 1 of the 3 groups and received either yohimbine (10 mg, n = 17), sulpiride (200 mg, n = 16), or placebo (n = 18) between fear acquisition and extinction. Recall of conditioned (non-extinguished CS+ vs CS-) and extinguished fear (extinguished CS+ vs CS-) was assessed 1 day later, and a 64-channel electroencephalogram was recorded.

RESULTS

The yohimbine group showed increased salivary alpha-amylase activity, confirming a successful manipulation of central noradrenergic release. Elevated fear-conditioned bradycardia and larger differential amplitudes of the N170 and late positive potential components in the event-related brain potential indicated that yohimbine treatment (compared with a placebo and sulpiride) enhanced fear recall during day 2.

CONCLUSIONS

These results suggest that yohimbine potentiates cardiac and central electrophysiological signatures of fear memory consolidation. They thereby elucidate the key role of noradrenaline in strengthening the consolidation of conditioned fear associations, which may be a key mechanism in the etiology of fear-related disorders.

Twenty years of investigation with the case of prosopagnosia PS to understand human face identity recognition. Part II: Neural basis

Patient PS sustained her dramatic brain injury in 1992, the same year as the first report of a neuroimaging study of human face recognition. The present paper complements the review on the functional nature of PS's prosopagnosia (part I), illustrating how her case study directly, i.e., through neuroimaging investigations of her brain structure and activity, but also indirectly, through neural studies performed on other clinical cases and neurotypical individuals, inspired and constrained neural models of human face recognition. In the dominant right hemisphere for face recognition in humans, PS's main lesion concerns (inputs to) the inferior occipital gyrus (IOG), in a region where face-selective activity is typically found in normal individuals ('Occipital Face Area', OFA). Her case study initially supported the criticality of this region for face identity recognition (FIR) and provided the impetus for transcranial magnetic stimulation (TMS), intracerebral electrical stimulation, and cortical surgery studies that have generally supported this view. Despite PS's right IOG lesion, typical face-selectivity is found anteriorly in the middle portion of the fusiform gyrus, a hominoid structure (termed the right 'Fusiform Face Area', FFA) that is widely considered to be the most important region for human face recognition. This finding led to the original proposal of direct anatomico-functional connections from early visual cortices to the FFA, bypassing the IOG/OFA (lulu), a hypothesis supported by further neuroimaging studies of PS, other neurological cases and neuro-typical individuals with original visual stimulation paradigms, data recordings and analyses. The proposal of a lack of sensitivity to face identity in PS's right FFA due to defective reentrant inputs from the IOG/FFA has also been supported by other cases, functional connectivity and cortical surgery studies. Overall, neural studies of, and based on, the case of prosopagnosia PS strongly question the hierarchical organization of the human neural face recognition system, supporting a more flexible and dynamic view of this key social brain function.

Pre-stimulus Alpha Activity Modulates Face and Object Processing in the Intra-Parietal Sulcus, a MEG Study

Face perception is crucial in all social animals. Recent studies have shown that pre-stimulus oscillations of brain activity modulate the perceptual performance of face vs. non-face stimuli, specifically under challenging conditions. However, it is unclear if this effect also occurs during simple tasks, and if so in which brain regions. Here we used magnetoencephalography (MEG) and a 1-back task in which participants decided if the two sequentially presented stimuli were the same or not in each trial. The aim of the study was to explore the effect of pre-stimulus alpha oscillation on the perception of face (human and monkey) and non-face stimuli. Our results showed that pre-stimulus activity in the left occipital face area (OFA) modulated responses in the intra-parietal sulcus (IPS) at around 170 ms after the presentation of human face stimuli. This effect was also found after participants were shown images of motorcycles. In this case, the IPS was modulated by pre-stimulus activity in the right OFA and the right fusiform face area (FFA). We conclude that pre-stimulus modulation of post-stimulus response also occurs during simple tasks and is therefore independent of behavioral responses.

Modular community structure of the face network supports face recognition

Face recognition is dependent on computations conducted in specialized brain regions and the communication among them, giving rise to the face-processing network. We examined whether modularity of this network may underlie the vast individual differences found in human face recognition abilities. Modular networks, characterized by strong within and weaker between-network connectivity, were previously suggested to promote efficacy and reduce interference among cognitive systems and also correlated with better cognitive abilities. The study was conducted in a large sample (n = 409) with diffusion-weighted imaging, resting-state fMRI, and a behavioral face recognition measure. We defined a network of face-selective regions and derived a novel measure of communication along with structural and functional connectivity among them. The modularity of this network was positively correlated with recognition abilities even when controlled for age. Furthermore, the results were specific to the face network when compared with the place network or to spatially permuted null networks. The relation to behavior was also preserved at the individual-edge level such that a larger correlation to behavior was found within hemispheres and particularly within the right hemisphere. This study provides the first evidence of modularity-behavior relationships in the domain of face processing and more generally in visual perception.

Modulation of Auditory Perception Laterality under Anxiety and Depression Conditions

The objective of this work is to confirm the asymmetry in non-linguistic auditory perception, as well as the influence of anxiety-depressive disorders on it. Eighty-six people were recruited in the emotional well-being group, fifty-six in the anxiety group, fourteen in the depression group, and seventy-seven in the mixed group. In each group, audiograms were obtained from both ears and the differences were statistically analyzed. Differences in hearing sensitivity were found between both ears in the general population, such differences increased in people with anxiety-depressive disorders. When faced with anxiety-depressive disorders, the right ear suffered greater hearing loss than the left, showing peaks of hyper-hearing at the frequency of 4000 Hz in the anxiety subgroup, and hearing loss in the depression subgroup. In relation to anxiety, the appearance of the 4:8 pattern was observed in the right ear when the person had suffered acute stress in the 2 days prior to the audiometry, and in both ears if they had suffered stress in the 3–30 days before said stress. In conclusion, the advantage of the left ear in auditory perception was increased with these disorders, showing a hyperaudition peak in anxiety and a hearing loss in depression.

"I Spy with my Little Eye, Something that is a Face…": A Brain Network for Illusory Face Detection

The most basic aspect of face perception is simply detecting the presence of a face, which requires the extraction of features that it has in common with other faces. Putatively, it is caused by matching high-dimensional sensory input with internal face templates, achieved through a top-down mediated coupling between prefrontal regions and brain areas in the occipito-temporal cortex ("core system of face perception"). Illusory face detection tasks can be used to study these top-down influences. In the present functional magnetic resonance imaging study, we showed that illusory face perception activated just as real faces the core system, albeit with atypical left-lateralization of the occipital face area. The core system was coupled with two distinct brain regions in the lateral prefrontal (inferior frontal gyrus, IFG) and orbitofrontal cortex (OFC). A dynamic causal modeling (DCM) analysis revealed that activity in the core system during illusory face detection was upregulated by a modulatory face-specific influence of the IFG, not as previously assumed by the OFC. Based on these findings, we were able to develop the most comprehensive neuroanatomical framework of illusory face detection until now.

Dynamic Causal Modeling on the Identification of Interacting Networks in the Brain: A Systematic Review

Dynamic causal modeling (DCM) has long been used to characterize effective connectivity within networks of distributed neuronal responses. Previous reviews have highlighted the understanding of the conceptual basis behind DCM and its variants from different aspects. However, no detailed summary or classification research on the task-related effective connectivity of various brain regions has been made formally available so far, and there is also a lack of application analysis of DCM for hemodynamic and electrophysiological measurements. This review aims to analyze the effective connectivity of different brain regions using DCM for different measurement data. We found that, in general, most studies focused on the networks between different cortical regions, and the research on the networks between other deep subcortical nuclei or between them and the cerebral cortex are receiving increasing attention, but far from the same scale. Our analysis also reveals a clear bias towards some task types. Based on these results, we identify and discuss several promising research directions that may help the community to attain a clear understanding of the brain network interactions under different tasks.

Decreased frontotemporal connectivity in patients with parkinson's disease experiencing face pareidolia

The precise neural underpinnings of face pareidolia in patients with Parkinson’s disease (PD) remain unclear. We aimed to clarify face recognition network abnormalities associated with face pareidolia in such patients. Eighty-three patients with PD and 40 healthy controls were recruited in this study. Patients with PD were classified into pareidolia and nonpareidolia groups. Volumetric analyses revealed no significant differences between the pareidolia (n = 39) and nonpareidolia (n = 44) patient groups. We further observed decreased functional connectivity among regions of interest in the bilateral frontotemporal lobes in patients with pareidolia. Seed-based analysis using bilateral temporal fusiform cortices as seeds revealed significantly decreased connectivity with the bilateral inferior medial prefrontal cortices in the pareidolia group. Post hoc regression analysis further demonstrated that the severity of face pareidolia was negatively correlated with functional connectivity between the bilateral temporal fusiform and medial prefrontal cortices. Our findings suggest that top-down modulation of the face recognition network is impaired in patients with PD experiencing face pareidolia.

Ocular Asymmetry in Electrooculographic Responses

Between the cornea and the posterior pole of the eye, there is a transepithelial potential capable of being registered through an electrooculogram (EOG). It is questionable whether electrooculographic responses are similar in both eyes despite ocular dominance in human beings. We studied the effect of different electrooculographic stimulation parameters, in terms of directionality, linear and angular velocity, contrast, and state of adaptation to light/dark, that may induce possible interocular differences in visual function. The study was carried out with electroencephalography-type surface electrodes placed in the medial, lateral, superior, and inferior positions of both human eyes to record the eye movements. We found a greater amplitude of the EOG response in the left eye than to the right eye for light bars moving from right to left (p < 0.01; t-test). The EOG response amplitude was similar in both eyes for light bars moving in vertical directions, but greater than horizontal or rotational stimuli. We conclude that vertical stimuli should be used for EOG functional evaluation of eye movements, since horizontal stimuli generate significant interocular differences.

The role of the left and right inferior frontal gyrus in processing metaphoric and unrelated co-speech gestures

Gestures are an integral part of in-person conversations and complement the meaning of the speech they accompany. The neural processing of co-speech gestures is supported by a mostly left-lateralized network of fronto-temporal regions. However, in contrast to iconic gestures, metaphoric as well as unrelated gestures have been found to more strongly engage the left and right inferior frontal gyrus (IFG), respectively. With this study, we conducted the first systematic comparison of all three types of gestures and resulting potential laterality effects. During collection of functional imaging data, 74 subjects were presented with 5 s videos of abstract speech with related metaphoric gestures, concrete speech with related iconic gestures and concrete speech with unrelated gestures. They were asked to judge whether the content of the speech and gesture matched or not. Differential contrasts revealed that both abstract related and concrete unrelated compared to concrete related stimuli elicited stronger activation of the bilateral IFG. Analyses of lateralization indices for IFG activation further showed a left hemispheric dominance for metaphoric gestures and a right hemispheric dominance for unrelated gestures. Our results give support to the hypothesis that the bilateral IFG is activated specifically when processing load for speech-gesture combinations is high. In addition, laterality effects indicate a stronger involvement of the right IFG in mismatch detection and conflict processing, whereas the left IFG performs the actual integration of information from speech and gesture.

Inhibition of the occipital face area modulates the electrophysiological signals of face familiarity: A combined cTBS-EEG study

The occipital face area (OFA) is hierarchically one of the first stages of the face processing network. It has originally been thought to be involved in early, structural processing steps, but currently more and more studies challenge this view and propose that it also takes part in higher level face processing, such as identification and recognition. Here we tested whether the OFA is involved in the initial steps of recognition memory and plays a causal role in the differential processing of familiar and unfamiliar faces. We used an offline, inhibitory continuous theta-burst stimulation (cTBS) protocol over the right OFA and the vertex as control site. Electroencephalographic (EEG) recording of event-related potentials (ERPs), elicited by visually presented familiar (famous) and unfamiliar faces was performed before and after stimulation. We observed a difference in ERPs for famous and unfamiliar faces in a time-window corresponding to the N250 component. Importantly, this difference was significantly increased by cTBS of the right OFA, suggesting its causal role in the differential processing of familiar and unfamiliar faces. The enhancement occurred focally, at electrodes close to the right hemispheric cTBS site, as well as over similar occipito-temporal sites of the contralateral hemisphere. To the best of our knowledge, this is the first study showing the causal role of the rOFA in the differential processing of familiar and unfamiliar faces, using combined cTBS and EEG recording methods. These results are discussed with respect to the nature of familiar face representations, supported by an extensive, bilateral network.

Differential Modulation of Effective Connectivity in the Brain's Extended Face Processing System by Fearful and Sad Facial Expressions

The processing of emotional facial expressions is underpinned by the integration of information from a distributed network of brain regions. Despite investigations into how different emotional expressions alter the functional relationships within this network, there remains limited research examining which regions drive these interactions. This study investigated effective connectivity during the processing of sad and fearful facial expressions to better understand how these stimuli differentially modulate emotional face processing circuitry. Ninety-eight healthy human adolescents and young adults, aged between 15 and 25 years, underwent an implicit emotional face processing fMRI task. Using dynamic causal modeling (DCM), we examined five brain regions implicated in face processing. These were restricted to the right hemisphere and included the occipital and fusiform face areas, amygdala, and dorsolateral prefrontal cortex (dlPFC) and ventromedial prefrontal cortex (vmPFC). Processing sad and fearful facial expressions were associated with greater positive connectivity from the amygdala to dlPFC. Only the processing of fearful facial expressions was associated with greater negative connectivity from the vmPFC to amygdala. Compared with processing sad faces, processing fearful faces was associated with significantly greater connectivity from the amygdala to dlPFC. No difference was found between the processing of these expressions and the connectivity from the vmPFC to amygdala. Overall, our findings indicate that connectivity from the amygdala and dlPFC appears to be responding to dimensional features which differ between these expressions, likely those relating to arousal. Further research is necessary to examine whether this relationship is also observable for positively valenced emotions.

Exploratory factor analysis with structured residuals for brain network data

Dimension reduction is widely used and often necessary to make network analyses and their interpretation tractable by reducing high-dimensional data to a small number of underlying variables. Techniques such as exploratory factor analysis (EFA) are used by neuroscientists to reduce measurements from a large number of brain regions to a tractable number of factors. However, dimension reduction often ignores relevant a priori knowledge about the structure of the data. For example, it is well established that the brain is highly symmetric. In this paper, we (a) show the adverse consequences of ignoring a priori structure in factor analysis, (b) propose a technique to accommodate structure in EFA by using structured residuals (EFAST), and (c) apply this technique to three large and varied brain-imaging network datasets, demonstrating the superior fit and interpretability of our approach. We provide an R software package to enable researchers to apply EFAST to other suitable datasets.

Regression dynamic causal modeling for resting-state fMRI

“Resting‐state” functional magnetic resonance imaging (rs‐fMRI) is widely used to study brain connectivity. So far, researchers have been restricted to measures of functional connectivity that are computationally efficient but undirected, or to effective connectivity estimates that are directed but limited to small networks. Here, we show that a method recently developed for task‐fMRI—regression dynamic causal modeling (rDCM)—extends to rs‐fMRI and offers both directional estimates and scalability to whole‐brain networks. First, simulations demonstrate that rDCM faithfully recovers parameter values over a wide range of signal‐to‐noise ratios and repetition times. Second, we test construct validity of rDCM in relation to an established model of effective connectivity, spectral DCM. Using rs‐fMRI data from nearly 200 healthy participants, rDCM produces biologically plausible results consistent with estimates by spectral DCM. Importantly, rDCM is computationally highly efficient, reconstructing whole‐brain networks (>200 areas) within minutes on standard hardware. This opens promising new avenues for connectomics.

Distinct mechanisms drive hemispheric lateralization of object recognition in the visual word form and fusiform face areas

The Visual Word Form Area (VWFA) and the Fusiform Face Area (FFA) represent classical examples of functional lateralization. The known hypothesis that lateralization of the VWFA and FFA are related remains controversial. We hypothesized that lateralization is independent and might be associated with lateralized high-level top-down mechanisms. For the VWFA this could emerge from left-lateralized language regions. This driving force might modulate local reorganization/recycling of function. Using an fMRI recognition paradigm, we quantified lateralization and investigated effective connectivity to examine mechanisms associated with lateralization in these regions (n = 58). Laterality patterns were more pronounced for VWFA than for FFA. Granger Causality Analysis found top-down effects only for the VWFA (left-lateralized, stemming from Broca's area). FFA exerted top-down effects on low-level visual areas. These findings suggest that distinct mechanisms are associated with hemispheric lateralization in object recognition: left lateralized top-down for VWFA and only early visual top-down effects concerning the FFA.

Whole-brain estimates of directed connectivity for human connectomics

Connectomics is essential for understanding large-scale brain networks but requires that individual connection estimates are neurobiologically interpretable. In particular, a principle of brain organization is that reciprocal connections between cortical areas are functionally asymmetric. This is a challenge for fMRI-based connectomics in humans where only undirected functional connectivity estimates are routinely available. By contrast, whole-brain estimates of effective (directed) connectivity are computationally challenging, and emerging methods require empirical validation. Here, using a motor task at 7T, we demonstrate that a novel generative model can infer known connectivity features in a whole-brain network (>200 regions, >40,000 connections) highly efficiently. Furthermore, graph-theoretical analyses of directed connectivity estimates identify functional roles of motor areas more accurately than undirected functional connectivity estimates. These results, which can be achieved in an entirely unsupervised manner, demonstrate the feasibility of inferring directed connections in whole-brain networks and open new avenues for human connectomics.

The Trajectory of Hemispheric Lateralization in the Core System of Face Processing: A Cross-Sectional Functional Magnetic Resonance Imaging Pilot Study

Face processing is mediated by a distributed neural network commonly divided into a “core system” and an “extended system.” The core system consists of several, typically right-lateralized brain regions in the occipito-temporal cortex, including the occipital face area (OFA), the fusiform face area (FFA) and the posterior superior temporal sulcus (pSTS). It was recently proposed that the face processing network is initially bilateral and becomes right-specialized in the course of the development of reading abilities due to the competition between language-related regions in the left occipito-temporal cortex (e.g., the visual word form area, VWFA) and the FFA for common neural resources. In the present pilot study, we assessed the neural face processing network in 12 children (aged 7–9 years) and 10 adults with functional magnetic resonance imaging (fMRI). The hemispheric lateralization of the core face regions was compared between both groups. The study had two goals: First, we aimed to establish an fMRI paradigm suitable for assessing activation in the core system of face processing in young children at the single subject level. Second, we planned to collect data for a power analysis to calculate the necessary group size for a large-scale cross-sectional imaging study assessing the ontogenetic development of the lateralization of the face processing network, with focus on the FFA. It was possible to detect brain activity in the core system of 75% of children at the single subject level. The average scan-to-scan motion of the included children was comparable to adults, ruling out that potential activation differences between groups are caused by unequal motion artifacts. Hemispheric lateralization of the FFA was 0.07 ± 0.48 in children (indicating bilateral activation) and −0.32 ± 0.52 in adults (indicating right-hemispheric dominance). These results thus showed, as expected, a trend for increased lateralization in adults. The estimated effect size for the FFA lateralization difference was d = 0.78 (indicating medium to large effects). An adequately powered follow-up study (sensitivity 0.8) testing developmental changes of FFA lateralization would therefore require the inclusion of 18 children and 26 adults.

Predicting individual clinical trajectories of depression with generative embedding

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Patients with major depressive disorder (MDD) show variable clinical trajectories.

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Generative embedding (GE) is used to predict clinical trajectories in MDD patients.

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GE classifies patients with chronic depression vs. fast remission with 79% accuracy.

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GE provides mechanistic interpretability and outperforms conventional measures.

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Proof-of-concept that illustrates the potential of GE for clinical prediction.

Patients with major depressive disorder (MDD) show heterogeneous treatment response and highly variable clinical trajectories: while some patients experience swift recovery, others show relapsing-remitting or chronic courses. Predicting individual clinical trajectories at an early stage is a key challenge for psychiatry and might facilitate individually tailored interventions. So far, however, reliable predictors at the single-patient level are absent. Here, we evaluated the utility of a machine learning strategy – generative embedding (GE) – which combines interpretable generative models with discriminative classifiers. Specifically, we used functional magnetic resonance imaging (fMRI) data of emotional face perception in 85 MDD patients from the NEtherlands Study of Depression and Anxiety (NESDA) who had been followed up over two years and classified into three subgroups with distinct clinical trajectories. Combining a generative model of effective (directed) connectivity with support vector machines (SVMs), we could predict whether a given patient would experience chronic depression vs. fast remission with a balanced accuracy of 79%. Gradual improvement vs. fast remission could still be predicted above-chance, but less convincingly, with a balanced accuracy of 61%. Generative embedding outperformed classification based on conventional (descriptive) features, such as functional connectivity or local activation estimates, which were obtained from the same data and did not allow for above-chance classification accuracy. Furthermore, predictive performance of GE could be assigned to a specific network property: the trial-by-trial modulation of connections by emotional content. Given the limited sample size of our study, the present results are preliminary but may serve as proof-of-concept, illustrating the potential of GE for obtaining clinical predictions that are interpretable in terms of network mechanisms. Our findings suggest that abnormal dynamic changes of connections involved in emotional face processing might be associated with higher risk of developing a less favorable clinical course.

LAB-QA2GO: A Free, Easy-to-Use Toolbox for the Quality Assessment of Magnetic Resonance Imaging Data

Image characteristics of magnetic resonance imaging (MRI) data (e.g., signal-to-noise ratio, SNR) may change over the course of a study. To monitor these changes a quality assurance (QA) protocol is necessary. QA can be realized both by performing regular phantom measurements and by controlling the human MRI datasets (e.g., noise detection in structural or movement parameters in functional datasets). Several QA tools for the assessment of MRI data quality have been developed. Many of them are freely available. This allows in principle the flexible set-up of a QA protocol specifically adapted to the aims of one’s own study. However, setup and maintenance of these tools takes substantial time, in particular since the installation and operation often require a fair amount of technical knowledge. In this article we present a light-weighted virtual machine, named LAB–QA2GO, which provides scripts for fully automated QA analyses of phantom and human datasets. This virtual machine is ready for analysis by starting it the first time. With minimal configuration in the guided web-interface the first analysis can start within 10 min, while adapting to local phantoms and needs is easily possible. The usability and scope of LAB–QA2GO is illustrated using a data set from the QA protocol of our lab. With LAB–QA2GO we hope to provide an easy-to-use toolbox that is able to calculate QA statistics without high effort.

Are global and specific interindividual differences in cortical thickness associated with facets of cognitive abilities, including face cognition?

Face cognition (FC) is a specific ability that cannot be fully explained by general cognitive functions. Cortical thickness (CT) is a neural correlate of performance and learning. In this registered report, we used data from the Human Connectome Project (HCP) to investigate the relationship between CT in the core brain network of FC and performance on a psychometric task battery, including tasks with facial content. Using structural equation modelling (SEM), we tested the existence of face-specific interindividual differences at behavioural and neural levels. The measurement models include general and face-specific factors of performance and CT. There was no face-specificity in CT in functionally localized areas. In post hoc analyses, we compared the preregistered, small regions of interest (ROIs) to larger, non-individualized ROIs and identified a face-specific CT factor when large ROIs were considered. We show that this was probably due to low reliability of CT in the functional localization (intra-class correlation coefficients (ICC) between 0.72 and 0.85). Furthermore, general cognitive ability, but not face-specific performance, could be predicted by latent factors of CT with a small effect size. In conclusion, for the core brain network of FC, we provide exploratory evidence (in need of cross-validation) that areas of the cortex sharing a functional purpose did also share morphological properties as measured by CT.

The peripheral preview effect with faces: Combined EEG and eye-tracking suggests multiple stages of trans-saccadic predictive and non-predictive processing

The world appears stable despite saccadic eye-movements. One possible explanation for this phenomenon is that the visual system predicts upcoming input across saccadic eye-movements based on peripheral preview of the saccadic target. We tested this idea using concurrent electroencephalography (EEG) and eye-tracking. Participants made cued saccades to peripheral upright or inverted face stimuli that changed orientation (invalid preview) or maintained orientation (valid preview) while the saccade was completed. Experiment 1 demonstrated better discrimination performance and a reduced fixation-locked N170 component (fN170) with valid than with invalid preview, demonstrating integration of pre- and post-saccadic information. Moreover, the early fixation-related potentials (FRP) showed a preview face inversion effect suggesting that some pre-saccadic input was represented in the brain until around 170 ms post fixation-onset. Experiment 2 replicated Experiment 1 and manipulated the proportion of valid and invalid trials to test whether the preview effect reflects context-based prediction across trials. A whole-scalp Bayes factor analysis showed that this manipulation did not alter the fN170 preview effect but did influence the face inversion effect before the saccade. The pre-saccadic inversion effect declined earlier in the mostly invalid block than in the mostly valid block, which is consistent with the notion of pre-saccadic expectations. In addition, in both studies, we found strong evidence for an interaction between the pre-saccadic preview stimulus and the post-saccadic target as early as 50 ms (Experiment 2) or 90 ms (Experiment 1) into the new fixation. These findings suggest that visual stability may involve three temporal stages: prediction about the saccadic target, integration of pre-saccadic and post-saccadic information at around 50-90 ms post fixation onset, and post-saccadic facilitation of rapid categorization.

Evaluating the organizational structure and specificity of network topology within the face processing system

There is increasing appreciation that network-level interactions among regions produce components of face processing previously ascribed to individual regions. Our goals were to use an exhaustive data-driven approach to derive and quantify the topology of directed functional connections within a priori defined nodes of the face processing network and evaluate whether the topology is category-specific. Young adults were scanned with fMRI as they viewed movies of faces, objects, and scenes. We employed GIMME to model effective connectivity among core and extended face processing regions, which allowed us to evaluate all possible directional connections, under each viewing condition (face, object, place). During face processing, we observed directional connections from the right posterior superior temporal sulcus to both the right occipital face area and right fusiform face area (FFA), which does not reflect the topology reported in prior studies. We observed connectivity between core and extended regions during face processing, but this limited to a feed-forward connection from the FFA to the amygdala. Finally, the topology of connections was unique to face processing. These findings suggest that the pattern of directed functional connections within the face processing network, particularly in the right core regions, may not be as hierarchical and feed-forward as described previously. Our findings support the notion that topologies of network connections are specialized, emergent, and dynamically responsive to task demands.

Illusory face detection in pure noise images: The role of interindividual variability in fMRI activation patterns

Illusory face detection tasks can be used to study the neural correlates of top-down influences on face perception. In a typical functional magnetic resonance imaging (fMRI) study design, subjects are presented with pure noise images, but are told that half of the stimuli contain a face. The illusory face perception network is assessed by comparing blood oxygenation level dependent (BOLD) responses to images in which a face has been detected against BOLD activity related to images in which no face has been detected. In the present study, we highlight the existence of strong interindividual differences of BOLD activation patterns associated with illusory face perception. In the core system of face perception, 4 of 9 subjects had highly significant (p<0.05, corrected for multiple comparisons) activity in the bilateral occipital face area (OFA) and fusiform face area (FFA). In contrast, 5 of 9 subjects did not show any activity in these regions, even at statistical thresholds as liberal as p = 0.05, uncorrected. At the group level, this variability is reflected by non-significant activity in all regions of the core system. We argue that these differences might be related to individual differences in task execution: only some participants really detected faces in the noise images, while the other subjects simply responded in the desired way. This has several implications for future studies on illusory face detection. First, future studies should not only analyze results at the group level, but also for single subjects. Second, subjects should be explicitly queried after the fMRI experiment about whether they really detected faces or not. Third, if possible, not only the overt response of the subject, but also additional parameters that might indicate the perception of a noise stimulus as face should be collected (e.g., behavioral classification images).

Visual Fixation Patterns During Viewing of Half-Face Stimuli in Adults: An Eye-Tracking Study

Human faces play a special role in social cognition, since as a core signal of interpersonal communication, they convey various kinds of information (e.g., about sex, age, race, emotions, intentions). Study 1 aimed to explore how this specialization manifests itself in eye movements when looking at neutral, static, female faces. We monitored the gaze pattern of 23 adult participants using eye-tracking method. To test if template-driven processes are involved in face perception, and to see how inversion affects fixations on special facial stimuli, we presented vertically cut half-faces in upright and inverted positions (so half of each stimulus represented a half-face, whereas the other half was left blank). Our results corroborate prior findings consistently demonstrating the dominance of the triangular area marked by the eyes and the mouth, measured by the number and duration of fixations. In addition, we found evidence for so-called complementary fixations, targeted at the non-informative parts (i.e., the half that does not contain any facial information) of the pictures, suggesting that other mechanisms beyond purely stimulus-driven ones might drive looking behavior when scanning faces. Study 2 was intended to test if these systematic eye movements are face-specific or occur in case of other visual objects as well.

Aging modulates fronto-temporal cortical interactions during lexical production. A dynamic causal modeling study

In this dynamic causal modeling (DCM) study, we evaluated the effect of age on the effective connectivity of a cerebral network involved in lexical production. Younger and older adults performed an object naming task during fMRI. The DCM was used to explore the interactions between four regions of interest: the occipital cortex, OC; the lateral temporal cortex, LTC; the medial temporal cortex, MTC; and the inferior frontal cortex, IFC. We mainly focused on the modulation of the fronto-temporal interaction, according to the hypothesis that aging requires strategies that modulate the access to the semantic knowledge, either through a neural reserve mechanism (increased MTC-LTC connectivity) or through a neural compensation mechanism (supplementary IFC-MTC connectivity). For younger adults, our results indicated a bi-directional interaction between the left IFC and LTC suggesting a typical activation related to lexico-semantic representations. For older adults, our results reveal the existence of bi-directional interaction between the IFC and MTC, but not between the IFC and LTC - which in turn suggests that older adults adapt a new strategy, via supplemental access to conceptual access and semantic retrieval processes. This neural compensation strategy would be facilitated by a top-down mechanism from the IFC to the MTC. We discuss our results in the context of the possible additional strategies used by older compared to younger adults, to retrieve and produce words.

Selective Attention to Faces in a Rapid Visual Stream: Hemispheric Differences in Enhancement and Suppression of Category-selective Neural Activity

In daily life, efficient perceptual categorization of faces occurs in dynamic and highly complex visual environments. Yet the role of selective attention in guiding face categorization has predominantly been studied under sparse and static viewing conditions, with little focus on disentangling the impact of attentional enhancement and suppression. Here we show that attentional enhancement and suppression exert a differential impact on face categorization supported by the left and right hemispheres. We recorded 128-channel EEG while participants viewed a 6-Hz stream of object images (buildings, animals, objects, etc.) with a face image embedded as every fifth image (i.e., OOOOFOOOOFOOOOF…). We isolated face-selective activity by measuring the response at the face presentation frequency (i.e., 6 Hz/5 = 1.2 Hz) under three conditions: Attend Faces, in which participants monitored the sequence for instances of female faces; Attend Objects, in which they responded to instances of guitars; and Baseline, in which they performed an orthogonal task on the central fixation cross. During the orthogonal task, face-specific activity was predominantly centered over the right occipitotemporal region. Actively attending to faces enhanced face-selective activity much more evidently in the left hemisphere than in the right, whereas attending to objects suppressed the face-selective response in both hemispheres to a comparable extent. In addition, the time courses of attentional enhancement and suppression did not overlap. These results suggest the left and right hemispheres support face-selective processing in distinct ways—where the right hemisphere is mandatorily engaged by faces and the left hemisphere is more flexibly recruited to serve current tasks demands.

Brain gray matter structural network in myotonic dystrophy type 1

This study aimed to investigate abnormalities in structural covariance network constructed from gray matter volume in myotonic dystrophy type 1 (DM1) patients by using graph theoretical analysis for further clarification of the underlying mechanisms of central nervous system involvement. Twenty-eight DM1 patients (4 childhood onset, 10 juvenile onset, 14 adult onset), excluding three cases from 31 consecutive patients who underwent magnetic resonance imaging in a certain period, and 28 age- and sex- matched healthy control subjects were included in this study. The normalized gray matter images of both groups were subjected to voxel based morphometry (VBM) and Graph Analysis Toolbox for graph theoretical analysis. VBM revealed extensive gray matter atrophy in DM1 patients, including cortical and subcortical structures. On graph theoretical analysis, there were no significant differences between DM1 and control groups in terms of the global measures of connectivity. Betweenness centrality was increased in several regions including the left fusiform gyrus, whereas it was decreased in the right striatum. The absence of significant differences between the groups in global network measurements on graph theoretical analysis is consistent with the fact that the general cognitive function is preserved in DM1 patients. In DM1 patients, increased connectivity in the left fusiform gyrus and decreased connectivity in the right striatum might be associated with impairment in face perception and theory of mind, and schizotypal-paranoid personality traits, respectively.

Functional organization of the face-sensitive areas in human occipital-temporal cortex

Human occipital-temporal cortex features several areas sensitive to faces, presumably forming the biological substrate for face perception. To date, there are piecemeal insights regarding the functional organization of these regions. They have come, however, from studies that are far from homogeneous with regard to the regions involved, the experimental design, and the data analysis approach. In order to provide an overall view of the functional organization of the face-sensitive areas, it is necessary to conduct a comprehensive study that taps into the pivotal functional properties of all the face-sensitive areas, within the context of the same experimental design, and uses multiple data analysis approaches. In this study, we identified the most robustly activated face-sensitive areas in bilateral occipital-temporal cortices (i.e., AFP, aFFA, pFFA, OFA, pcSTS, pSTS) and systemically compared their regionally averaged activation and multivoxel activation patterns to 96 images from 16 object categories, including faces and non-faces. This condition-rich and single-image analysis approach critically samples the functional properties of a brain region, allowing us to test how two basic functional properties, namely face-category selectivity and face-exemplar sensitivity are distributed among these regions. Moreover, by examining the correlational structure of neural responses to the 96 images, we characterize their interactions in the greater face-processing network. We found that (1) r-pFFA showed the highest face-category selectivity, followed by l-pFFA, bilateral aFFA and OFA, and then bilateral pcSTS. In contrast, bilateral AFP and pSTS showed low face-category selectivity; (2) l-aFFA, l-pcSTS and bilateral AFP showed evidence of face-exemplar sensitivity; (3) r-OFA showed high overall response similarities with bilateral LOC and r-pFFA, suggesting it might be a transitional stage between general and face-selective information processing; (4) r-aFFA showed high face-selective response similarity with r-pFFA and r-OFA, indicating it was specifically involved in processing face information. Results also reveal two properties of these face sensitive regions across the two hemispheres: (1) the averaged left intra-hemispheric response similarity for the images was lower than the averaged right intra-hemispheric and the inter-hemispheric response similarity, implying convergence of face processing towards the right hemisphere, and (2) the response similarities between homologous regions in the two hemispheres decreased as information processing proceeded from the early, more posterior, processing stage (OFA), indicating an increasing degree of hemispheric specialization and right hemisphere bias for face information processing. This study contributes to an emerging picture of how faces are processed within the occipital and temporal cortex.

Mechanisms of hemispheric lateralization: A replication study

It has been shown, using functional magnetic resonance imaging (fMRI), that hemispheric lateralization of brain activity depends on the requirements of the cognitive task performed during the processing of a sensory stimulus rather than on the intrinsic characteristics of that stimulus [Stephan et al., 2003, Science 301 (5631): 384-6]. Task-dependent increase in the coupling of the anterior cingulate cortex (ACC), a region involved in cognitive control, and brain areas in the left prefrontal and right parietal cortex, respectively, regions involved in task execution, was proposed as the mechanism underlying this task-dependency of hemispheric lateralization. The aim of the present study was two-fold: First, we aimed for a conceptual replication of these findings in an independent sample of subjects. Second, we investigated the test-retest reliability of the imaging paradigm to assess whether the task can be used to capture reliable measures of inter-individual differences in hemispheric lateralization. We were able to confirm previous findings showing that hemispheric lateralization depends on the nature of the cognitive task rather than on the nature of the processed stimuli. The task-related brain activation patterns were highly reliable across sessions (as indicated by intra-class correlation coefficients - ICCs, ≥.51). We could, however, not replicate previous results proposing task-dependent changes in the coupling between ACC and brain regions for task execution as the mechanism underlying hemispheric lateralization. This re-opens the question which mechanisms could determine the task-dependent functional asymmetries that were observed previously and replicated in this study.

An fMRI study of visual hemifield integration and cerebral lateralization

The human brain integrates hemifield-split visual information via interhemispheric transfer. The degree to which neural circuits involved in this process behave differently during word recognition as compared to object recognition is not known. Evidence from neuroimaging (fMRI) suggests that interhemispheric transfer during word viewing converges in the left hemisphere, in two distinct brain areas, an "occipital word form area" (OWFA) and a more anterior occipitotemporal "visual word form area" (VWFA). We used a novel fMRI half-field repetition technique to test whether or not these areas also integrate nonverbal hemifield-split string stimuli of similar visual complexity. We found that the fMRI responses of both the OWFA and VWFA while viewing nonverbal stimuli were strikingly different than those measured during word viewing, especially with respect to half-stimulus changes restricted to a single hemifield. We conclude that normal reading relies on left-lateralized neural mechanisms, which integrate hemifield-split visual information for words but not for nonverbal stimuli.

Regression DCM for fMRI

The development of large-scale network models that infer the effective (directed) connectivity among neuronal populations from neuroimaging data represents a key challenge for computational neuroscience. Dynamic causal models (DCMs) of neuroimaging and electrophysiological data are frequently used for inferring effective connectivity but are presently restricted to small graphs (typically up to 10 regions) in order to keep model inversion computationally feasible. Here, we present a novel variant of DCM for functional magnetic resonance imaging (fMRI) data that is suited to assess effective connectivity in large (whole-brain) networks. The approach rests on translating a linear DCM into the frequency domain and reformulating it as a special case of Bayesian linear regression. This paper derives regression DCM (rDCM) in detail and presents a variational Bayesian inversion method that enables extremely fast inference and accelerates model inversion by several orders of magnitude compared to classical DCM. Using both simulated and empirical data, we demonstrate the face validity of rDCM under different settings of signal-to-noise ratio (SNR) and repetition time (TR) of fMRI data. In particular, we assess the potential utility of rDCM as a tool for whole-brain connectomics by challenging it to infer effective connection strengths in a simulated whole-brain network comprising 66 regions and 300 free parameters. Our results indicate that rDCM represents a computationally highly efficient approach with promising potential for inferring whole-brain connectivity from individual fMRI data.

Handedness is related to neural mechanisms underlying hemispheric lateralization of face processing

While the right-hemispheric lateralization of the face perception network is well established, recent evidence suggests that handedness affects the cerebral lateralization of face processing at the hierarchical level of the fusiform face area (FFA). However, the neural mechanisms underlying differential hemispheric lateralization of face perception in right- and left-handers are largely unknown. Using dynamic causal modeling (DCM) for fMRI, we aimed to unravel the putative processes that mediate handedness-related differences by investigating the effective connectivity in the bilateral core face perception network. Our results reveal an enhanced recruitment of the left FFA in left-handers compared to right-handers, as evidenced by more pronounced face-specific modulatory influences on both intra- and interhemispheric connections. As structural and physiological correlates of handedness-related differences in face processing, right- and left-handers varied with regard to their gray matter volume in the left fusiform gyrus and their pupil responses to face stimuli. Overall, these results describe how handedness is related to the lateralization of the core face perception network, and point to different neural mechanisms underlying face processing in right- and left-handers. In a wider context, this demonstrates the entanglement of structurally and functionally remote brain networks, suggesting a broader underlying process regulating brain lateralization.

Electrophysiological Evidence for Domain-General Processes in Task-Switching

The ability to flexibly switch between tasks is a hallmark of cognitive control. Despite previous studies that have investigated whether different task-switching types would be mediated by distinct or overlapping neural mechanisms, no definitive consensus has been reached on this question yet. Here, we aimed at directly addressing this issue by recording the event-related potentials (ERPs) elicited by two types of task-switching occurring in the context of spatial and verbal cognitive domains. Source analysis was also applied to the ERP data in order to track the spatial dynamics of brain activity underlying task-switching abilities. In separate blocks of trials, participants had to perform either spatial or verbal switching tasks both of which employed the same type of stimuli. The ERP analysis, which was carried out through a channel- and time-uninformed mass univariate approach, showed no significant differences between the spatial and verbal domains in the modulation of switch and repeat trials. Specifically, relative to repeat trials, switch trials in both domains were associated with a first larger positivity developing over left parieto-occipital electrodes and with a subsequent larger negativity distributed over mid-left fronto-central sites. The source analysis reconstruction for the two ERP components complemented these findings by highlighting the involvement of left-lateralized prefrontal areas in task-switching. Overall, our results join and extend recent research confirming the existence of left-lateralized domain-general task-switching processes.

Test-retest reliability of effective connectivity in the face perception network

Computational approaches have great potential for moving neuroscience toward mechanistic models of the functional integration among brain regions. Dynamic causal modeling (DCM) offers a promising framework for inferring the effective connectivity among brain regions and thus unraveling the neural mechanisms of both normal cognitive function and psychiatric disorders. While the benefit of such approaches depends heavily on their reliability, systematic analyses of the within-subject stability are rare. Here, we present a thorough investigation of the test-retest reliability of an fMRI paradigm for DCM analysis dedicated to unraveling intra- and interhemispheric integration among the core regions of the face perception network. First, we examined the reliability of face-specific BOLD activity in 25 healthy volunteers, who performed a face perception paradigm in two separate sessions. We found good to excellent reliability of BOLD activity within the DCM-relevant regions. Second, we assessed the stability of effective connectivity among these regions by analyzing the reliability of Bayesian model selection and model parameter estimation in DCM. Reliability was excellent for the negative free energy and good for model parameter estimation, when restricting the analysis to parameters with substantial effect sizes. Third, even when the experiment was shortened, reliability of BOLD activity and DCM results dropped only slightly as a function of the length of the experiment. This suggests that the face perception paradigm presented here provides reliable estimates for both conventional activation and effective connectivity measures. We conclude this paper with an outlook on potential clinical applications of the paradigm for studying psychiatric disorders. Hum Brain Mapp 37:730-744, 2016. © 2015 Wiley Periodicals, Inc.