Functional organization of the fusiform gyrus revealed with connectivity profiles

The causal relationship between physical activity, sedentary behavior and brain cortical structure: a Mendelian randomization study

Physical activity and sedentary behavior, both distinct lifestyle behaviors associated with brain health, have an unclear potential relationship with brain cortical structure. This study aimed to determine the causal link between physical activity, sedentary behavior, and brain cortical structure (cortical surface area and thickness) through Mendelian randomization analysis. The inverse-variance weighted method was primarily utilized, accompanied by sensitivity analyses, to confirm the results' robustness and accuracy. Analysis revealed nominally significant findings, indicating a potential positive influence of physical activity on cortical thickness in the bankssts (β = 0.002 mm, P = 0.043) and the fusiform (β = 0.002 mm, P = 0.018), and a potential negative association of sedentary behavior with cortical surface area in the caudal middle frontal (β = -34.181 mm2, P = 0.038) and the pars opercularis (β = -33.069 mm2, P = 0.002), alongside a nominally positive correlation with the cortical surface area of the inferior parietal (β = 58.332 mm2, P = 0.035). Additionally, a nominally significant negative correlation was observed between sedentary behavior and cortical thickness in the paracentral (β = -0.014 mm, P = 0.042). These findings offer insights into how lifestyle behaviors may influence brain cortical structures, advancing our understanding of their interaction with brain health.

Differential role of fusiform gyrus coupling in depressive and anxiety symptoms during emotion perception

Anxiety and depression co-occur; the neural substrates of shared and unique components of these symptoms are not understood. Given emotional alterations in internalizing disorders, we hypothesized that function of regions associated with emotion processing/regulation, including the anterior cingulate cortex (ACC), amygdala and fusiform gyrus (FG), would differentiate these symptoms. Forty-three adults with depression completed an emotional functional magnetic resonance imaging task and the Hamilton Depression and Anxiety Scales. We transformed these scales to examine two orthogonal components, one representing internalizing symptom severity and the other the type of internalizing symptoms (anxiety vs depression). We extracted blood oxygen level dependent signal from FG subregions, ACC, and amygdala and performed generalized psychophysiological interaction analyses to assess relationships between symptoms and brain function. Type of internalizing symptoms was associated with FG3-FG1 coupling (F = 8.14, P = 0.007). More coupling was associated with a higher concentration of depression, demonstrating that intra-fusiform coupling is differentially associated with internalizing symptom type (anxiety vs depression). We found an interaction between task condition and internalizing symptoms and dorsal (F = 4.51, P = 0.014) and rostral ACC activity (F = 4.27, P = 0.012). Post hoc comparisons revealed that less activity was associated with greater symptom severity during emotional regulation. Functional coupling differences during emotional processing are associated with depressive relative to anxiety symptoms and internalizing symptom severity. These findings could inform future treatments for depression.

The anterior fusiform gyrus: The ghost in the cortical face machine

Face-selective regions in the human ventral occipito-temporal cortex (VOTC) have been defined for decades mainly with functional magnetic resonance imaging. This face-selective VOTC network is traditionally divided in a posterior 'core' system thought to subtend face perception, and regions of the anterior temporal lobe as a semantic memory component of an extended general system. In between these two putative systems lies the anterior fusiform gyrus and surrounding sulci, affected by magnetic susceptibility artifacts. Here we suggest that this methodological gap overlaps with and contributes to a conceptual gap between (visual) perception and semantic memory for faces. Filling this gap with intracerebral recordings and direct electrical stimulation reveals robust face-selectivity in the anterior fusiform gyrus and a crucial role of this region, especially in the right hemisphere, in identity recognition for both familiar and unfamiliar faces. Based on these observations, we propose an integrated theoretical framework for human face (identity) recognition according to which face-selective regions in the anterior fusiform gyrus join the dots between posterior and anterior cortical face memories.

MRgFUS of the nucleus ventralis intermedius in essential tremor modulates functional connectivity within the classical tremor network and beyond

BACKGROUND

Magnetic resonance-guided focused ultrasound (MRgFUS) of the thalamic ventral intermediate nucleus is an incisionless lesional treatment for essential tremor.

OBJECTIVE

To examine relationships between tremor severity and functional connectivity in patients with essential tremor and to assess long-term changes in the tremor network after sonication of the ventral intermediate nucleus.

METHODS

Twenty-one patients with essential tremor (70.33 ± 11.32 years) were included in the final analysis and underwent resting state functional magnetic resonance imaging at 3 T before and 6 months after treatment. Tremor severity (Fahn-Tolosa-Marin Clinical Rating Scale) was evaluated and functional connectivity was investigated using independent component analysis.

RESULTS

MRgFUS of the thalamic ventral intermediate nucleus reduced contralateral tremor effectively. Multiple regression analysis revealed exclusively negative correlations between FC and tremor severity, notably in the right cerebellar lobe VI and the left cerebellar lobe VIIIa (cerebellar network), in the left occipital fusiform gyrus (lateral visual network), the anterior division of the left superior temporal gyrus (fronto-parieto-temporal network), and in the posterior division of the left parahippocampal gyrus and the bilateral lingual gyri (default mode network). Six months after treatment, increased functional connectivity was observed in almost all tremor-associated clusters, except the cluster localized in the left cerebellum.

CONCLUSIONS

Our findings suggest that tremor-related activity in essential tremor extends beyond the classical cerebellar network, additionally involving areas related to visual processing. Functional restoration of network activity after sonication of the ventral intermediate nucleus is observed within the classical tremor network (cerebellum) and notably also in visual processing areas.

Comparing two picture naming tasks in primary progressive aphasia: Insights from behavioural and neural results

Picture naming tests are widely used to evaluate language impairments in neurodegenerative diseases, especially in Primary Progressive Aphasia (PPA). The available tests differ for many factors affecting the performance, e.g. format of stimuli and their psycholinguistic properties. We aim to identify the most appropriate naming test to be used on PPA according to the clinical and research demands. We investigated the behavioural characteristics, i.e. proportion of correct responses and error type, and their neural correlates in two Italian naming tests, CaGi naming (CaGi) and naming subtest of the Screening for Aphasia in NeuroDegeneration battery (SAND), administered to 52 PPA patients who underwent an FDG-PET scan. We analysed the effectiveness of the tests in distinguishing PPA versus controls and among PPA variants, considering the psycholinguistic variables affecting performance. We explored the brain metabolic correlates of behavioural performance in the tests. SAND, differently from CaGi, has time limits for the response and its items are less frequent and acquired later. SAND and CaGi differed in terms of number of correct responses and error profile, suggesting a higher difficulty to name SAND items compared to CaGi. Semantic errors predominated in CaGi, while anomic and semantic errors were equally frequent in SAND. Both tests distinguished PPA from controls, but SAND outperformed CaGi in discriminating among PPA variants. FDG-PET imaging revealed a shared metabolic involvement of temporal areas associated with lexico-semantic processing, encompassing anterior fusiform, temporal pole, and extending to posterior fusiform in sv-PPA. Concluding, a picture naming test with response time limit and items which are less frequent and acquired later in life, as SAND, may be effective at highlighting subtle distinctions between PPA variants, improving the diagnosis. Conversely, a naming test without time limit for the response, as CaGi, may be useful for a better characterization of the nature of the naming impairment at the behavioural level, eliciting more naming errors than anomia, possibly helping in the development of rehabilitation protocols.

Linking functional and structural brain organisation with behaviour in autism: a multimodal EU-AIMS Longitudinal European Autism Project (LEAP) study

Neuroimaging analyses of brain structure and function in autism have typically been conducted in isolation, missing the sensitivity gains of linking data across modalities. Here we focus on the integration of structural and functional organisational properties of brain regions. We aim to identify novel brain-organisation phenotypes of autism. We utilised multimodal MRI (T1-, diffusion-weighted and resting state functional), behavioural and clinical data from the EU AIMS Longitudinal European Autism Project (LEAP) from autistic (n = 206) and non-autistic (n = 196) participants. Of these, 97 had data from 2 timepoints resulting in a total scan number of 466. Grey matter density maps, probabilistic tractography connectivity matrices and connectopic maps were extracted from respective MRI modalities and were then integrated with Linked Independent Component Analysis. Linear mixed-effects models were used to evaluate the relationship between components and group while accounting for covariates and non-independence of participants with longitudinal data. Additional models were run to investigate associations with dimensional measures of behaviour. We identified one component that differed significantly between groups (coefficient = 0.33, padj = 0.02). This was driven (99%) by variance of the right fusiform gyrus connectopic map 2. While there were multiple nominal (uncorrected p < 0.05) associations with behavioural measures, none were significant following multiple comparison correction. Our analysis considered the relative contributions of both structural and functional brain phenotypes simultaneously, finding that functional phenotypes drive associations with autism. These findings expanded on previous unimodal studies by revealing the topographic organisation of functional connectivity patterns specific to autism and warrant further investigation.

Altered functional connectivity of the locus coeruleus in Alzheimer's disease patients with depression symptoms

Studies have shown that functional abnormalities in the locus coeruleus (LC) are strongly associated with depressive symptoms, but the pattern of LC functional connectivity in Alzheimer's disease patients with depressive symptoms (D-AD) remains unclear. The current study aimed to investigate the characteristics of LC functional connectivity (FC) in D-AD using resting-state functional magnetic resonance imaging (rsfMRI). We obtained rsfMRI data in 24 D-AD patients (aged 66-76 years), 14 non-depressive AD patients (nD-AD) (aged 69-79 years) and 20 normal controls (aged 67-74 years) using a 3 T scanner. We used the FC approach to investigate abnormalities in the LC brain network of D-AD patients. One-way ANCOVA and post-hoc two-sample t-tests were performed to compare the strength of functional connectivity from the LC among the three groups. Our results showed that, compared with normal controls, D-AD showed decreased left LC FC with the right caudate and left fusiform gyrus, whereas nD-AD showed decreased left LC FC with the right caudate, right middle frontal gyrus and left fusiform gyrus. Compared to nD-AD, D-AD showed increased left LC FC with right superior frontal gyrus and right precentral gyrus. These findings contribute to our understanding of the neural mechanisms of D-AD.

Changes in Functional Connectivity of Hippocampal Subregions in Patients with Obstructive Sleep Apnea after Six Months of Continuous Positive Airway Pressure Treatment

Previous studies have shown that the structural and functional impairments of hippocampal subregions in patients with obstructive sleep apnea (OSA) are related to cognitive impairment. Continuous positive airway pressure (CPAP) treatment can improve the clinical symptoms of OSA. Therefore, this study aimed to investigate functional connectivity (FC) changes in hippocampal subregions of patients with OSA after six months of CPAP treatment (post-CPAP) and its relationship with neurocognitive function. We collected and analyzed baseline (pre-CPAP) and post-CPAP data from 20 patients with OSA, including sleep monitoring, clinical evaluation, and resting-state functional magnetic resonance imaging. The results showed that compared with pre-CPAP OSA patients, the FC between the right anterior hippocampal gyrus and multiple brain regions, and between the left anterior hippocampal gyrus and posterior central gyrus were reduced in post-CPAP OSA patients. By contrast, the FC between the left middle hippocampus and the left precentral gyrus was increased. The changes in FC in these brain regions were closely related to cognitive dysfunction. Therefore, our findings suggest that CPAP treatment can effectively change the FC patterns of hippocampal subregions in patients with OSA, facilitating a better understanding of the neural mechanisms of cognitive function improvement, and emphasizing the importance of early diagnosis and timely treatment of OSA.

Cortical thickness is related to cognitive-motor automaticity and attention allocation in individuals with Alzheimer's disease: a regions of interest study

Alzheimer's disease (AD) is characterized by a distinct pattern of cortical thinning and resultant changes in cognition and function. These result in prominent deficits in cognitive-motor automaticity. The relationship between AD-related cortical thinning and decreased automaticity is not well-understood. We aimed to investigate the relationship between cortical thickness regions-of-interest (ROI) and automaticity and attention allocation in AD using hypothesis-driven and exploratory approaches. We performed an ROI analysis of 46 patients with AD. Data regarding MR images, demographic characteristics, cognitive-motor dual task performance, and cognition were extracted from medical records. Cortical thickness was calculated from MR T1 images using FreeSurfer. Data from the dual task assessment was used to calculate the combined dual task effect (cDTE), a measure of cognitive-motor automaticity, and the modified attention allocation index (mAAI). Four hierarchical multiple linear regression models were conducted regressing cDTE and mAAI separately on (1) hypothesis-generated ROIs and (2) exploratory ROIs. For cDTE, cortical thicknesses explained 20.5% (p = 0.014) and 25.9% (p = 0.002) variability in automaticity in the hypothesized ROI and exploratory models, respectively. The dorsal lateral prefrontal cortex (DLPFC) (β =  - 0.479, p = 0.018) and superior parietal cortex (SPC) (β = 0.467, p = 0.003), and were predictors of automaticity. For mAAI, cortical thicknesses explained 20.7% (p = 0.025) and 28.3% (p = 0.003) variability in attention allocation in the hypothesized ROI and exploratory models, respectively. Thinning of SPC and fusiform gyrus were associated with motor prioritization (β =  - 0.405, p = 0.013 and β =  - 0.632, p = 0.004, respectively), whereas thinning of the DLPFC was associated with cognitive prioritization (β = 0.523, p = 0.022). Cortical thinning in AD was related to cognitive-motor automaticity and task prioritization, particularly in the DLPFC and SPC. This suggests that these regions may play a primary role in automaticity and attentional strategy during dual-tasking.

ADHD-Gaming Disorder Comorbidity in Children and Adolescents: A Narrative Review

Attention Deficit/Hyperactivity Disorder (ADHD) is a neurobiological condition characterized by developmentally inadequate levels of inattention, hyperactivity, and impulsivity, and a neurobiological disruption in brain neurotransmitters and circuitry causing abnormal responses to rewards. Playing electronic games generates a biological response that activates the neuronal circuits linked to pleasure and reward, and there is a growing attention to this type of activity, which can also turn into a mental health condition. The existence and the boundaries between the functional and the dysfunctional are still a source of debate, with the recognition of 'Internet Gaming Disorder' (IGD) as a condition belonging to the broader area of addiction requiring more in-depth study with respect to the DSM-5, while 'Gaming Disorder' (GD) was officially recognized as a new diagnosis by the World Health Organization (WHO) in the updated revision of the International Classification of Diseases (ICD-11). Notwithstanding, the suggested criteria for the diagnosis of Gaming Disorder are still debated. Since ADHD has been reported as a risk factor for developing addictions, this narrative review aims to provide the current state-of-the art of the knowledge about the comorbidity between ADHD and Gaming Disorder. For this aim, a literature search was conducted using a combination of specific keywords and the results are discussed within the R-Do-C framework and dimensions, and implications for treatment are considered.

Parcellating the human brain using resting-state dynamic functional connectivity

Brain cartography has expanded substantially over the past decade. In this regard, resting-state functional connectivity (FC) plays a key role in identifying the locations of putative functional borders. However, scant attention has been paid to the dynamic nature of functional interactions in the human brain. Indeed, FC is typically assumed to be stationary across time, which may obscure potential or subtle functional boundaries, particularly in regions with high flexibility and adaptability. In this study, we developed a dynamic FC (dFC)-based parcellation framework, established a new functional human brain atlas termed D-BFA (DFC-based Brain Functional Atlas), and verified its neurophysiological plausibility by stereo-EEG data. As the first dFC-based whole-brain atlas, the proposed D-BFA delineates finer functional boundaries that cannot be captured by static FC, and is further supported by good correspondence with cytoarchitectonic areas and task activation maps. Moreover, the D-BFA reveals the spatial distribution of dynamic variability across the brain and generates more homogenous parcels compared with most alternative parcellations. Our results demonstrate the superiority and practicability of dFC in brain parcellation, providing a new template to exploit brain topographic organization from a dynamic perspective. The D-BFA will be publicly available for download at https://github.com/sliderplm/D-BFA-618.

Brain Functional Imaging Anatomy

Human brain function is an increasingly complex framework that has important implications in clinical medicine. In this review, the anatomy of the most commonly assessed brain functions in clinical neuroradiology, including motor, language, and vision, is discussed. The anatomy and function of the primary and secondary sensorimotor areas are discussed with clinical case examples. Next, the dual stream of language processing is reviewed, as well as its implications in clinical medicine and surgical planning. Last, the authors discuss the striate and extrastriate visual cortex and review the dual stream model of visual processing.

A strategy of model space search for dynamic causal modeling in task fMRI data exploratory analysis

Dynamic causal modeling (DCM) is a tool used for effective connectivity (EC) estimation in neuroimage analysis. But it is a model-driven analysis method, and the structure of the EC network needs to be determined in advance based on a large amount of prior knowledge. This characteristic makes it difficult to apply DCM to the exploratory brain network analysis. The exploratory analysis of DCM can be realized from two perspectives: one is to reduce the computational cost of the model; the other is to reduce the model space. From the perspective of model space reduction, a model space exploration strategy is proposed, including two algorithms. One algorithm, named GreedyEC, starts with reducing EC from full model, and the other, named GreedyROI, start with adding EC from one node model. Then the two algorithms were applied to the task state functional magnetic resonance imaging (fMRI) data of visual object recognition and selected the best DCM model from the perspective of model comparison based on Bayesian model compare method. Results show that combining the results of the two algorithms can further improve the effect of DCM exploratory analysis. For convenience in application, the algorithms were encapsulated into MATLAB function based on SPM to help neuroscience researchers to analyze the brain causal information flow network. The strategy provides a model space exploration tool that may obtain the best model from the perspective of model comparison and lower the threshold of DCM analysis.

Network analysis shows decreased ipsilesional structural connectivity in glioma patients

Gliomas that infiltrate networks and systems, such as the motor system, often lead to substantial functional impairment in multiple systems. Network-based statistics (NBS) allow to assess local network differences and graph theoretical analyses enable investigation of global and local network properties. Here, we used network measures to characterize glioma-related decreases in structural connectivity by comparing the ipsi- with the contralesional hemispheres of patients and correlated findings with neurological assessment. We found that lesion location resulted in differential impairment of both short and long connectivity patterns. Network analysis showed reduced global and local efficiency in the ipsilesional hemisphere compared to the contralesional hemispheric networks, which reflect the impairment of information transfer across different regions of a network.

Tumors and their location distinctly alter both local and global brain connectivity within the ipsilesional hemisphere of glioma patients.

Task modulates the orthographic and phonological representations in the bilateral ventral Occipitotemporal cortex

As a key area in word reading, the left ventral occipitotemporal cortex is proposed for abstract orthographic processing, and its middle part has even been labeled as the visual word form area. Because the definition of the VWFA largely varies and the reading task differs across studies, the function of the left ventral occipitotemporal cortex in word reading is continuingly debated on whether this region is specific for orthographic processing or be involved in an interactive framework. By using representational similarity analysis (RSA), this study examined information representation in the VWFA at the individual level and the modulatory effect of reading task. Twenty-four subjects were scanned while performing the explicit (i.e., the naming task) and implicit (i.e., the perceptual task) reading tasks. Activation analysis showed that the naming task elicited greater activation in regions related to phonological processing (e.g., the bilateral prefrontal cortex and temporoparietal cortex), while the perceptual task recruited greater activation in visual cortex and default mode network (e.g., the bilateral middle frontal gyrus, angular gyrus, and the right middle temporal gyrus). More importantly, RSA also showed that task modulated information representation in the bilateral anterior occipitotemporal cortex and VWFA. Specifically, ROI-based RSA revealed enhanced orthographic and phonological representations in the bilateral anterior fusiform cortex and VWFA in the naming task relative to the perceptual task. These results suggest that lexical representation in the VWFA is influenced by the demand of phonological processing, which supports the interactive account of the VWFA.

Musical memories in newborns: A resting-state functional connectivity study

Music is known to induce emotions and activate associated memories, including musical memories. In adults, it is well known that music activates both working memory and limbic networks. We have recently discovered that as early as during the newborn period, familiar music is processed differently from unfamiliar music. The present study evaluates music listening effects at the brain level in newborns, by exploring the impact of familiar or first‐time music listening on the subsequent resting‐state functional connectivity in the brain. Using a connectome‐based framework, we describe resting‐state functional connectivity (RS‐FC) modulation after music listening in three groups of newborn infants, in preterm infants exposed to music during their neonatal‐intensive‐care‐unit (NICU) stay, in control preterm, and full‐term infants. We observed modulation of the RS‐FC between brain regions known to be implicated in music and emotions processing, immediately following music listening in all newborn infants. In the music exposed group, we found increased RS‐FC between brain regions known to be implicated in familiar and emotionally arousing music and multisensory processing, and therefore implying memory retrieval and associative memory. We demonstrate a positive correlation between the occurrence of the prior music exposure and increased RS‐FC in brain regions implicated in multisensory and emotional processing, indicating strong engagement of musical memories; and a negative correlation with the Default Mode Network, indicating disengagement due to the aforementioned cognitive processing. Our results describe the modulatory effect of music listening on brain RS‐FC that can be linked to brain correlates of musical memory engrams in preterm infants.

Resting State Functional Connectivity Signatures of MRgFUS Vim Thalamotomy in Parkinson's Disease: A Preliminary Study

Magnetic Resonance-guided high-intensity Focused Ultrasound (MRgFUS) of the thalamic ventral intermediate nucleus (Vim) for tremor has increasingly gained interest as a new non-invasive alternative to standard neurosurgery. Resting state functional connectivity (rs-FC) correlates of MRgFUS have not been extensively investigated yet. A region of interest (ROI)-to-ROI rs-FC MRI “connectomic” analysis focusing on brain regions relevant for tremor was conducted on 15 tremor-dominant patients with Parkinson's disease who underwent MRgFUS. We tested whether rs-FC between tremor-related areas was modulated by MRgFUS at 1 and 3 months post-operatively, and whether such changes correlated with individual clinical outcomes assessed by the MDS-UPDRS-III sub items for tremor. Significant increase in FC was detected within bilateral primary motor (M1) cortices, as well as between bilateral M1 and crossed primary somatosensory cortices, and also between pallidum and the dentate nucleus of the untreated hemisphere. Correlation between disease duration and FC increase at 3 months was found between the putamen of both cerebral hemispheres and the Lobe VI of both cerebellar hemispheres, as well as between the Lobe VI of untreated cerebellar hemisphere with bilateral supplementary motor area (SMA). Drop-points value of MDS-UPDRS at 3 months correlated with post-treatment decrease in FC, between the anterior cingulate cortex and bilateral SMA, as well as between the Lobe VI of treated cerebellar hemisphere and the interpositus nucleus of untreated cerebellum. Tremor improvement at 3 months, expressed as percentage of intra-subject MDS-UPDRS changes, correlated with FC decrease between bilateral occipital fusiform gyrus and crossed Lobe VI and Vermis VI. Good responders (≥50% of baseline tremor improvement) showed reduced FC between bilateral SMA, between the interpositus nucleus of untreated cerebellum and the Lobe VI of treated cerebellum, as well as between the untreated SMA and the contralateral putamen. Good responders were characterized at baseline by crossed hypoconnectivity between bilateral putamen and M1, as well as between the putamen of the treated hemisphere and the contralateral SMA. We conclude that MRgFUS can effectively modulate brain FC within the tremor network. Such changes are associated with clinical outcome. The shifting mode of integration among the constituents of this network is, therefore, susceptible to external redirection despite the chronic nature of PD.

Intracerebral electrical stimulation of the right anterior fusiform gyrus impairs human face identity recognition

Brain regions located between the right fusiform face area (FFA) in the middle fusiform gyrus and the temporal pole may play a critical role in human face identity recognition but their investigation is limited by a large signal drop-out in functional magnetic resonance imaging (fMRI). Here we report an original case who is suddenly unable to recognize the identity of faces when electrically stimulated on a focal location inside this intermediate region of the right anterior fusiform gyrus. The reliable transient identity recognition deficit occurs without any change of percept, even during nonverbal face tasks (i.e., pointing out the famous face picture among three options; matching pictures of unfamiliar or familiar faces for their identities), and without difficulty at recognizing visual objects or famous written names. The effective contact is associated with the largest frequency-tagged electrophysiological signals of face-selectivity and of familiar and unfamiliar face identity recognition. This extensive multimodal investigation points to the right anterior fusiform gyrus as a critical hub of the human cortical face network, between posterior ventral occipito-temporal face-selective regions directly connected to low-level visual cortex, the medial temporal lobe involved in generic memory encoding, and ventral anterior temporal lobe regions holding semantic associations to people's identity.

Insular Dichotomy in the Implicit Detection of Emotions in Human Faces

The functional roles of the insula diverge between its posterior portion (PI), mainly connected with somato-sensory and motor areas, and its anterior section (AI) connected with the frontal, limbic, and cingulate regions. We report intracranial recordings of local field evoked potentials from PI, AI, and the visual fusiform gyrus to a full array of emotional faces including pain while the individuals' attention was diverted from emotions. The fusiform gyrus and PI responded equally to all types of faces, including neutrals. Conversely, the AI responded only to emotional faces, maximally to pain and fear, while remaining insensitive to neutrals. The two insular sectors reacted with almost identical latency suggesting their parallel initial activation via distinct functional routes. The consistent responses to all emotions, together with the absence of response to neutral faces, suggest that early responses in the AI reflect the immediate arousal value and behavioral relevance of emotional stimuli, which may be subserved by "fast track" routes conveying coarse-spatial-frequency information via the superior colliculus and dorsal pulvinar. Such responses precede the conscious detection of the stimulus' precise signification and valence, which need network interaction and information exchange with other brain areas, for which the AI is an essentialhub.

Correlations between sleep disturbance and brain cortical morphometry in healthy children

Background

While the importance of adequate sleep duration to normal brain development is well known, more studies are needed to characterize how undiagnosed sleep disturbance other than suboptimal sleep duration may impact brain development. In this study we aim to understand the relationships between sleep disturbance measures and cortical morphometry in typically-developing children without previous diagnoses of sleep pathology.

Methods

Healthy 8-year-old children (30 boys, 37 girls) without clinical diagnosis of sleep disorders were prospectively recruited for brain MRI and their parents completed the Children’s Sleep Habits Questionnaire (CSHQ). Total sleep disturbance score, as well as 8 subscales including bedtime resistance, sleep onset delay, sleep duration, sleep anxiety, night waking, parasomnias, sleep disordered breathing, and daytime sleepiness were calculated, and their relationships with cortical morphometry features including cortical gray matter volume, cortical thickness, and surface area were investigated, controlled for total cortical volume and sex.

Results

The CSHQ total sleep disturbance score significantly correlated with cortical surface area in a cluster in the left middle temporal gyrus (P < 0.001, R = -0.54). In addition, the bedtime resistance subscale negatively correlated with cortical surface area in a cluster in the right fusiform gyrus (P < 0.001, R = -0.50). No other clusters showed significant relationships between CSHQ total score or subscales and cortical features for this cohort.

Conclusion

Significant relationships between sleep disturbance scores in typically-developing children without clinical diagnosis of sleep pathology and their brain cortical surface area in two temporal lobe regions were identified, suggesting that undiagnosed sleep disturbance may potentially impact brain development even in healthy children.

Eye Direction Detection and Perception as Premises of a Social Brain: A Narrative Review of Behavioral and Neural Data

The eyes and the gaze are important stimuli for social interaction in humans. Impaired recognition of facial identity, facial emotions, and inference of the intentions of others may result from difficulties in extracting information relevant to the eye region, mainly the direction of gaze. Therefore, a review of these data is of interest. Behavioral data demonstrating the importance of the eye region and how humans respond to gaze direction are reviewed narratively, and several theoretical models on how visual information on gaze is processed are discussed to propose a unified hypothesis. Several issues that have not yet been investigated are identified. The authors tentatively suggest experiments that might help progress research in this area. The neural aspects are subsequently reviewed to best describe the low-level and higher-level visual information processing stages in the targeted subcortical and cortical areas. A specific neural network is proposed on the basis of the literature. Various gray areas, such as the temporality of the processing of visual information, the question of salience priority, and the coordination between the two hemispheres, remain unclear and require further investigations. Finally, disordered gaze direction detection mechanisms and their consequences on social cognition and behavior are discussed as key deficiencies in several conditions, such as autism spectrum disorder, 22q11.2 deletion, schizophrenia, and social anxiety disorder. This narrative review provides significant additional data showing that the detection and perception of someone's gaze is an essential part of the development of our social brain.

Professional chess expertise modulates whole brain functional connectivity pattern homogeneity and couplings

Previous studies have revealed changed functional connectivity patterns between brain areas in chess players using resting-state functional magnetic resonance imaging (rs-fMRI). However, how to exactly characterize the voxel-wise whole brain functional connectivity pattern changes in chess players remains unclear. It could provide more convincing evidence for establishing the relationship between long-term chess practice and brain function changes. In this study, we employed newly developed whole brain functional connectivity pattern homogeneity (FcHo) method to identify the voxel-wise changes of functional connectivity patterns in 28 chess master players and 27 healthy novices. Seed-based functional connectivity analysis was used to identify the alteration of corresponding functional couplings. FcHo analysis revealed significantly increased whole brain functional connectivity pattern similarity in anterior cingulate cortex (ACC), anterior middle temporal gyrus (aMTG), primary visual cortex (V1), and decreased FcHo in thalamus and precentral gyrus in chess players. Resting-state functional connectivity analyses identified chess players showing decreased functional connections between V1 and precentral gyrus. Besides, a linear support vector machine (SVM) based classification achieved an accuracy of 85.45%, a sensitivity of 85.71% and a specificity of 85.19% to differentiate chess players from novices by leave-one-out cross-validation. Finally, correlation analyses revealed that the mean FcHo values of thalamus were significantly negatively correlated with the training time. Our findings provide new evidences for the important roles of ACC, aMTG, V1, thalamus and precentral gyrus in chess players. The findings also indicate that long-term professional chess training may enhance the semantic and episodic processing, efficiency of visual-motor transformation, and cognitive ability.

Neural Mechanism of Noise Affecting Face Recognition

Face recognition is one of the most important cognitive functions for humans in social activities. The ability will be negatively affected when the face images deteriorate. However, the neural process of extracting facial information under challenging conditions is still poorly understood. Therefore, it is necessary to further understand the neurophysiological relevance of this effect. We examined patients with multiple subdural electrodes (ECoG) monitored for clinical purposes. During the experimental task, the patients were presented with face and house images with different noise levels and were asked to recognize the faces. We found a striking increase in high gamma band power (HGP; 60-160 Hz) when face images were shown. We localized the face-specific electrodes to the fusiform gyrus (FG) and surrounding cortices. For each subject, the behavioral performance and magnitudes of the HGP for the face-specific sites significantly both fit a sigmoid function and showed similar changes. Additionally, the curve profile of the average HGP magnitude across the face-specific sites was almost equal to the average behavior curve; the former could precisely track the behavioral performance. In general, these results suggest that the HGP in the FG is closely related to the performance of face image recognition.

Integrating Multimodal and Longitudinal Neuroimaging Data with Multi-Source Network Representation Learning

Uncovering the complex network of the brain is of great interest to the field of neuroimaging. Mining from these rich datasets, scientists try to unveil the fundamental biological mechanisms in the human brain. However, neuroimaging data collected for constructing brain networks is generally costly, and thus extracting useful information from a limited sample size of brain networks is demanding. Currently, there are two common trends in neuroimaging data collection that could be exploited to gain more information: 1) multimodal data, and 2) longitudinal data. It has been shown that these two types of data provide complementary information. Nonetheless, it is challenging to learn brain network representations that can simultaneously capture network properties from multimodal as well as longitudinal datasets. Here we propose a general fusion framework for multi-source learning of brain networks - multimodal brain network fusion with longitudinal coupling (MMLC). In our framework, three layers of information are considered, including cross-sectional similarity, multimodal coupling, and longitudinal consistency. Specifically, we jointly factorize multimodal networks and construct a rotation-based constraint to couple network variance across time. We also adopt the consensus factorization as the group consistent pattern. Using two publicly available brain imaging datasets, we demonstrate that MMLC may better predict psychometric scores than some other state-of-the-art brain network representation learning algorithms. Additionally, the discovered significant brain regions are synergistic with previous literature. Our new approach may boost statistical power and sheds new light on neuroimaging network biomarkers for future psychometric prediction research by integrating longitudinal and multimodal neuroimaging data.

Breathlessness in COPD: linking symptom clusters with brain activity

Background

Current models of breathlessness often fail to explain disparities between patients' experiences of breathlessness and objective measures of lung function. While a mechanistic understanding of this discordance has thus far remained elusive, factors such as mood, attention and expectation have all been implicated as important modulators of breathlessness. Therefore, we have developed a model to better understand the relationships between these factors using unsupervised machine learning techniques. Subsequently we examined how expectation-related brain activity differed between these symptom-defined clusters of participants.

Methods

A cohort of 91 participants with mild-to-moderate chronic obstructive pulmonary disease (COPD) underwent functional brain imaging, self-report questionnaires and clinical measures of respiratory function. Unsupervised machine learning techniques of exploratory factor analysis and hierarchical cluster modelling were used to model brain–behaviour–breathlessness links.

Results

We successfully stratified participants across four key factors corresponding to mood, symptom burden and two capability measures. Two key groups resulted from this stratification, corresponding to high and low symptom burden. Compared with the high symptom burden group, the low symptom burden group demonstrated significantly greater brain activity within the anterior insula, a key region thought to be involved in monitoring internal bodily sensations (interoception).

Conclusions

This is the largest functional neuroimaging study of COPD to date, and is the first to provide a clear model linking brain, behaviour and breathlessness expectation. Furthermore, it was possible to stratify participants into groups, which then revealed differences in brain activity patterns. Together, these findings highlight the value of multimodal models of breathlessness in identifying behavioural phenotypes and for advancing understanding of differences in breathlessness burden.

Towards individualised treatments for chronic breathlessness with functional neuroimaging: revealing the factors underlying the breathlessness experience in COPDhttps://bit.ly/3a8fXPt

Intracerebral electrical stimulation to understand the neural basis of human face identity recognition

Recognizing people's identity by their faces is a key function in the human species, supported by regions of the ventral occipito-temporal cortex (VOTC). In the last decade, there have been several reports of perceptual face distortion during direct electrical stimulation (DES) with subdural electrodes positioned over a well-known face-selective VOTC region of the right lateral middle fusiform gyrus (LatMidFG; i.e., the "Fusiform Face Area", FFA). However, transient impairments of face identity recognition (FIR) have been extremely rare and only behaviorally quantified during DES with intracerebral (i.e., depth) electrodes in stereo-electroencephalography (SEEG). The three detailed cases reported so far, summarized here, were specifically impaired at FIR during DES inside different anatomical VOTC regions of the right hemisphere: the inferior occipital gyrus (IOG) and the LatMidFG, as well as a region that lies at the heart of a large magnetic susceptibility artifact in functional magnetic resonance imaging (fMRI): the anterior fusiform gyrus (AntFG). In the first two regions, the eloquent electrode contacts were systematically associated with the highest face-selective and (unfamiliar) face individuation responses as measured with intracerebral electrophysiology. Stimulation in the right AntFG did not lead to perceptual changes but also caused an inability to remember having been presented face pictures, as if the episode was never recorded in memory. These observations support the view of an extensive network of face-selective VOTC regions subtending human FIR, with at least three critical nodes in the right hemisphere associated with differential intrinsic and extrinsic patterns of reentrant connectivity.

Temporal Dynamics in Degree Centrality of Brain Functional Connectome in First-Episode Schizophrenia with Different Short-Term Treatment Responses: A Longitudinal Study

PURPOSE

This study investigated temporal dynamics in degree centrality (DC) of the brain functional connectome in first-episode schizophrenia with different short-term treatment responses.

METHODS

A total of 127 first-episode patients (FEPs) with schizophrenia and 133 healthy controls (HCs) were recruited in this study. All subjects underwent resting-state functional magnetic resonance imaging. FEPs were scanned at baseline (pretreatment) and at follow-up (posttreatment), while HCs were scanned only at baseline. The patients were exposed to naturalistic antipsychotic treatment for 12 weeks, and classified as schizophrenia responders (SRs) or nonresponders (NRs). Voxel-wise dynamic DC analyses were conducted among the SRs (n=75), NRs (n=52), and HCs (n=133) to assess temporal variability in functional connectivity across the entire neuronal network.

RESULTS

The SRs and NRs showed dissimilar dynamic DC at baseline, with differences mainly involving the temporal lobe. Different DC alteration was observed in the left fusiform gyrus, right fusiform gyrus, left middle cingulate cortex, and left superior parietal gyrus in the SRs and NRs pre- and posttreatment. SRs group and NRs presented opposite changing patterns of dynamic DC in particular regions of the brain.

CONCLUSION

These findings indicate that dynamic DC abnormalities exist in unmedicated patients with schizophrenia. The NRs differed from the SRs in dynamic DC not only at baseline but in the characteristics of changes before and after treatment as well. Our study may contribute to understanding pathophysiology in schizophrenia with different treatment responses.

Structural and Functional Brain Abnormalities in Internet Gaming Disorder and Attention-Deficit/Hyperactivity Disorder: A Comparative Meta-Analysis

Background: Patients with Internet gaming disorder (IGD) and attention-deficit/hyperactivity disorder (ADHD) have high comorbidity but it is still unknown whether these disorders have shared and distinctive neuroimage alterations. Objective: The aim of this meta-analysis was to identify shared and disorder-specific structural, functional, and multimodal abnormalities between IGD and ADHD. Methods: A systematic literature search was conducted for whole-brain voxel-based morphometry (VBM) and functional magnetic resonance imaging (fMRI) studies comparing people with IGD or ADHD with healthy controls. Regional gray matter volume (GMV) and fMRI differences were compared over the patient groups and then a quantitative comparison was performed to find abnormalities (relative to controls) between IGD and ADHD using seed-based d mapping meta-analytic methods. Result: The meta-analysis contained 14 IGD VBM studies (contrasts covering 333 IGDs and 335 HCs), 26 ADHD VBM studies (1,051 patients with ADHD and 887 controls), 30 IGD fMRI studies (603 patients with IGD and 564 controls), and 29 ADHD fMRI studies (878 patients with ADHD and 803 controls). Structurally, VBM analysis showed disorder-specific GMV abnormality in the putamen among IGD subjects and orbitofrontal cortex in ADHD and shared GMV in the prefrontal cortex. Functionally, fMRI analysis discovered that IGD-differentiating increased activation in the precuneus and shared abnormal activation in anterior cingulate cortex, insular, and striatum. Conclusion: IGD and ADHD have shared and special structural and functional alterations. IGD has disorder-differentiating structural alterations in the putamen and ADHD has alterations in the orbitofrontal cortex. Disorder-differentiating fMRI activations were predominantly observed in the precuneus among IGD subjects and shared impairing function connection was in the rewards circuit (including ACC, OFC, and striatum).

Scalp Acupuncture Enhances the Functional Connectivity of Visual and Cognitive-Motor Function Network of Patients with Acute Ischemic Stroke

Design

A parallel-group randomized controlled trial. Participants. 30 hemiplegic patients with middle cerebral artery acute infarction of the dominant hemisphere. Interventions. 30 patients were divided into 2 groups randomly. 15 patients in the treatment group (TG) were treated with ISSA, needling at the parietal midline (MS5) and left anterior/posterior parietal-temporal oblique lines (MS6 and MS7), combined with western routine treatment. While another 15 patients in the control group (CG) received routine treatment only. Main Outcome Measures. (1) Functional connectivity (FC): patients received brain scan using 3.0 T MRI after the treatment for 1 week. Based on the Matlab2012a platform, SPM12 software and DPABI software were used to process the scanning data and finally the functional connectivity of the brain was obtained. (2) National Institute of Health Stroke Scale (NIHSS) score.

Results

The difference in the NIHSS score between the two groups of patients before and after treatment was statistically significant (tNIHSS = 2.225; PNIHSS = 0.038), indicating that TG had a better effect. Centered to the seed region of the left supplementary motor area (SMA) (-5.32, 4.85, 61.38), FC increased at the left middle cerebellar peduncle, left cerebellum posterior lobe (uvula and declive), vermis, fusiform gyrus, lingual gyrus, inferior occipital gyrus, calcarine, cuneus, precuneus, BA7, BA18 and BA19, etc. Centered to the seed region of the left parahippocampal gyrus (PG) (-21.17, -15.95, -20.70), FC increased at the left precuneus, inside-paracingulate, inferior parietal gyrus, paracentral lobule, BA5, BA6, BA7, and BA40, right median cingulate, precuneus, BA19, BA23, and BA31, etc.

Conclusions

It is indicated that ISSA can regulate the brain functional connection in patients with middle cerebral artery acute infarction in the dominant hemisphere and specifically strengthen the connections between visual, cognitive, motor control, and planning-related brain regions, which may be related to the recovery of movement in the mechanism. This trial is registered with ChiCTR-IOR-15007672.

Joint Multi-modal Parcellation of the Human Striatum: Functions and Clinical Relevance

The human striatum is essential for both low- and high-level functions and has been implicated in the pathophysiology of various prevalent disorders, including Parkinson's disease (PD) and schizophrenia (SCZ). It is known to consist of structurally and functionally divergent subdivisions. However, previous parcellations are based on a single neuroimaging modality, leaving the extent of the multi-modal organization of the striatum unknown. Here, we investigated the organization of the striatum across three modalities-resting-state functional connectivity, probabilistic diffusion tractography, and structural covariance-to provide a holistic convergent view of its structure and function. We found convergent clusters in the dorsal, dorsolateral, rostral, ventral, and caudal striatum. Functional characterization revealed the anterior striatum to be mainly associated with cognitive and emotional functions, while the caudal striatum was related to action execution. Interestingly, significant structural atrophy in the rostral and ventral striatum was common to both PD and SCZ, but atrophy in the dorsolateral striatum was specifically attributable to PD. Our study revealed a cross-modal convergent organization of the striatum, representing a fundamental topographical model that can be useful for investigating structural and functional variability in aging and in clinical conditions.

Abnormal Regional Neural Activity and Reorganized Neural Network in Obesity: Evidence from Resting-State fMRI

OBJECTIVE

This study aimed to investigate regional neural activity and regulation of patterns in the reorganized neural network of obesity and explore the correlation between brain activities and eating behavior.

METHODS

A total of 23 individuals with obesity and 23 controls with normal weight were enrolled. Functional magnetic resonance imaging (fMRI) data were acquired using 3.0-T MRI. Amplitude of low-frequency fluctuation and functional connectivity (FC) analyses were conducted using Data Processing Assistant for resting-state fMRI and Resting-State fMRI Data Analysis Toolkit (REST).

RESULTS

The group with obesity showed increased amplitude of low-frequency values in left fusiform gyrus/amygdala, inferior temporal gyrus (ITG), hippocampus/parahippocampal gyrus, and bilateral caudate but decreased values in right superior temporal gyrus. The group with obesity showed increased FC between left caudate and right superior temporal gyrus, left fusiform gyrus/amygdala and left ITG, right caudate and left fusiform gyrus/amygdala, and right caudate and left hippocampus/parahippocampal gyrus. Dutch Eating Behavior Questionnaire-Emotional scores were positively correlated with FC between left hippocampus/parahippocampal gyrus and right caudate but negatively correlated with FC between left fusiform gyrus/amygdala and left ITG.

CONCLUSIONS

The study indicated the reorganized neural network presented as a bilateral cross-regulation pattern across hemispheres between reward and various appetite-related functional processing, thus affecting emotional and external eating behavior. These results could provide further evidence for neuropsychological underpinnings of food intake and their neuromodulatory therapeutic potential in obesity.

Different Neural Correlates of Sexually Preferred and Sexually Nonpreferred Stimuli

BACKGROUND

The differences and relationships between stimulus-related brain activation for sexually preferred stimuli and sexually nonpreferred stimuli are still unclear.

AIM

This study aimed to identify brain regions that were mostly associated with sexual stimuli.

METHODS

We used the activation likelihood estimation, meta-analytic connectivity modelling, and behavioral domain metadata in the BrainMap database to perform this analysis.

OUTCOMES

We found convergent activation foci and created a model for the extended brain network involved in responses to sexual stimuli and also assessed the functional properties of these regions.

RESULTS

A total of 34 experiments from 15 studies including 368 subjects and 343 foci were analyzed. The results showed that sexual stimuli are related to the extensive activation of the occipital-temporal-limbic system and less extensive activation of the basal ganglia. Sexually preferred stimuli activated mainly the anterior cingulate cortex and right fusiform gyrus, while sexually nonpreferred stimuli activated the limbic system, occipital gyrus, and thalamus.

CLINICAL IMPLICATIONS

To have a further understanding of the central mechanisms of human sexuality.

STRENGTHS & LIMITATIONS

Patient characteristics and analysis techniques in the included studies were heterogeneous.

CONCLUSIONS

These findings suggest that the anterior cingulate cortex is an important cognitive control area for both sexually preferred and nonpreferred stimuli. Meta-analytic connectivity modelling analysis revealed a network of the core brain areas involved in response to sexual stimuli, and behavioral domain analysis indicated that these areas have both common and discrete functional properties. Long X, Tian F, Zhou Y, et al. Different Neural Correlates of Sexually Preferred and Sexually Nonpreferred Stimuli. J Sex Med 2020;17:1254-1267.

Geometric Brain Surface Network For Brain Cortical Parcellation

A large number of surface-based analyses on brain imaging data adopt some specific brain atlases to better assess structural and functional changes in one or more brain regions. In these analyses, it is necessary to obtain an anatomically correct surface parcellation scheme in an individual brain by referring to the given atlas. Traditional ways to accomplish this goal are through a designed surface-based registration or hand-crafted surface features, although both of them are time-consuming. A recent deep learning approach depends on a regular spherical parameterization of the mesh, which is computationally prohibitive in some cases and may also demand further post-processing to refine the network output. Therefore, an accurate and fully-automatic cortical surface parcellation scheme directly working on the original brain surfaces would be highly advantageous. In this study, we propose an end-to-end deep brain cortical parcellation network, called DBPN. Through intrinsic and extrinsic graph convolution kernels, DBPN dynamically deciphers neighborhood graph topology around each vertex and encodes the deciphered knowledge into node features. Eventually, a non-linear mapping between the node features and parcellation labels is constructed. Our model is a two-stage deep network which contains a coarse parcellation network with a U-shape structure and a refinement network to fine-tune the coarse results. We evaluate our model in a large public dataset and our work achieves superior performance than state-of-the-art baseline methods in both accuracy and efficiency.

Regional entropy of functional imaging signals varies differently in sensory and cognitive systems during propofol-modulated loss and return of behavioral responsiveness

The level and richness of consciousness depend on information integration in the brain. Altered interregional functional interactions may indicate disrupted information integration during anesthetic-induced unconsciousness. How anesthetics modulate the amount of information in various brain regions has received less attention. Here, we propose a novel approach to quantify regional information content in the brain by the entropy of the principal components of regional blood oxygen-dependent imaging signals during graded propofol sedation. Fifteen healthy individuals underwent resting-state scans in wakeful baseline, light sedation (conscious), deep sedation (unconscious), and recovery (conscious). Light sedation characterized by lethargic behavioral responses was associated with global reduction of entropy in the brain. Deep sedation with completely suppressed overt responsiveness was associated with further reductions of entropy in sensory (primary and higher sensory plus orbital prefrontal cortices) but not high-order cognitive (dorsal and medial prefrontal, cingulate, parietotemporal cortices and hippocampal areas) systems. Upon recovery of responsiveness, entropy was restored in the sensory but not in high-order cognitive systems. These findings provide novel evidence for a reduction of information content of the brain as a potential systems-level mechanism of reduced consciousness during propofol anesthesia. The differential changes of entropy in the sensory and high-order cognitive systems associated with losing and regaining overt responsiveness are consistent with the notion of "disconnected consciousness", in which a complete sensory-motor disconnection from the environment occurs with preserved internal mentation.

Altered whole brain functional connectivity pattern homogeneity in medication-free major depressive disorder

BACKGROUND

Many previous studies have revealed abnormal functional connectivity patterns between brain areas underlying the onset of major depressive disorder (MDD) using resting-state functional magnetic resonance imaging (rs-fMRI). However, how to exactly characterize the voxel-wise whole brain functional connectivity pattern changes in MDD remains unclear, which will provide more convincing evidence for localizing the exactly functional connectivity abnormality in MDD.

METHODS

In this study, we employed our newly developed whole brain functional connectivity homogeneity (FcHo) method to identify the voxel-wise changes of functional connectivity patterns in 27 medication-free MDD patients and 34 gender-, age-, and education level-matched healthy controls (HC). Furthermore, seed-based functional connectivity analysis was then used to identify the alteration of corresponding functional connectivity.

RESULTS

Significantly decreased FcHo values in right ventral anterior insula (INS) and medial prefrontal cortex (MPFC) were identified in MDD patients. The ensuing functional connectivity analyses identified decreased functional connectivity between MPFC and left angular gyrus (AG) in MDD patients. Moreover, both decreased FcHo values in INS, MPFC and functional connectivity between MPFC and left AG showed significant negative correlations with Hamilton depression rating scale (HDRS) scores. The FcHo values in INS were also negatively correlated with disease duration. Finally, meta-analysis based functional characterization found that these brain areas are mainly involved in emotion, theory of mind and reward processing.

CONCLUSIONS

Our findings revealed abnormal whole brain FcHo in INS and MPFC and functional interactions between MPFC and AG in MDD and suggested that dysfunctions of INS and MPFC play an important role in the neuropathology of MDD.

Activation-based association profiles differentiate network roles across cognitive loads

Working memory (WM) is a complex and pivotal cognitive system underlying the performance of many cognitive behaviors. Although individual differences in WM performance have previously been linked to the blood oxygenation level-dependent (BOLD) response across several large-scale brain networks, the unique and shared contributions of each large-scale brain network to efficient WM processes across different cognitive loads remain elusive. Using a WM paradigm and functional magnetic resonance imaging (fMRI) from the Human Connectome Project, we proposed a framework to assess the association and shared-association strength between imaging biomarkers and behavioral scales. Association strength is the capability of individual brain regions to modulate WM performance and shared-association strength measures how different regions share the capability of modulating performance. Under higher cognitive load (2-back), the frontoparietal executive control network (FPN), dorsal attention network (DAN), and salience network showed significant positive activation and positive associations, whereas the default mode network (DMN) showed the opposite pattern, namely, significant deactivation and negative associations. Comparing the different cognitive loads, the DMN and FPN showed predominant associations and globally shared-associations. When investigating the differences in association from lower to higher cognitive loads, the DAN demonstrated enhanced association strength and globally shared-associations, which were significantly greater than those of the other networks. This study characterized how brain regions individually and collaboratively support different cognitive loads.

Amygdala network in response to facial expression following neurofeedback training of emotion

Real-time functional magnetic resonance imaging (rtfMRI) has been applied to self-regulate activity in the amygdala and improve emotional perception and recognition as a novel neurofeedback training method. Previous studies have indicated that successful regulation of the target region led to changes in other brain regions as a network during neurofeedback training. However, it is unclear how neurofeedback training of the amygdala affects the network engaged in facial expression. In this study, we investigated the changes in the amygdala network involved in a facial expression task after rtfMRI training of the left amygdala. The amygdala network of pre- and post-training tasks with pleasant expression as the stimulus was extracted using group independent component analysis. The results showed that not only the activity of the amygdala network but also the functional connectivity of the fusiform with the amygdala within the network was enhanced by training. Moreover, increases in this connectivity were correlated with increases in behavioral performance. These findings suggest the functional significance of the connectivity of the fusiform with the amygdala engaged in facial emotional perception as well as their close correlation with behavior, thus providing new insights into the mechanisms of neurofeedback-based emotional regulation and clinical treatment of related emotional disorders.

Electroconvulsive Therapy Induces Cortical Morphological Alterations in Major Depressive Disorder Revealed with Surface-Based Morphometry Analysis

Although electroconvulsive therapy (ECT) is one of the most effective treatments for major depressive disorder (MDD), the mechanism underlying the therapeutic efficacy and side effects of ECT remains poorly understood. Here, we investigated alterations in the cortical morphological measurements including cortical thickness (CT), surface area (SA), and local gyrification index (LGI) in 23 MDD patients before and after ECT. Furthermore, multivariate pattern analysis using linear support vector machine (SVM) was applied to investigate whether the changed morphological measurements can be effective indicators for therapeutic efficacy of ECT. Surface-based morphometry (SBM) analysis found significantly increased vertex-wise and regional cortical thickness (CT) and surface area (SA) in widespread regions, mainly located in the left insula (INS) and left fusiform gyrus, as well as hypergyrification in the left middle temporal gyrus (MTG) in MDD patients after ECT. Partial correlational analyses identified associations between the morphological properties and depressive symptom scores and impaired memory scores. Moreover, SVM result showed that the changed morphological measurements were effective to classify the MDD patients before and after ECT. Our findings suggested that ECT may enhance cortical neuroplasticity to facilitate neurogenesis to remit depressive symptoms and to impair delayed memory. These findings indicated that the cortical morphometry is a good index for therapeutic efficacy of ECT.

Hypoconnectivity of insular resting-state networks in adolescents with Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is characterized by deficits in social interaction and communication. The anterior insula (AI) participates in emotional salience detection; and the posterior insula (PI) participates in sensorimotor integration and response selection. Meta-analyses have noted insula-based aberrant connectivity within ASD. Given the observed social impairments in ASD and the role of the insula in social information processing (SIP), investigating functional organization of this structure in ASD is important. We investigated differences in resting-state functional connectivity (RSFC) using fMRI in male youths with (N=13; mean=14.6 years; range: 10.2-18.0 years) and without ASD (N=17; mean=14.5 years; range: 10.0-17.5 years). With seed-based FC measures, we compared RSFC in insular networks. Hypoconnectivity was observed in ASD (AI-superior frontal gyrus (SFG); AI-thalamus; PI-inferior parietal lobule (IPL); PI-fusiform gyrus (FG); PI-lentiform nucleus/putamen). Using the Social Communication Questionnaire (SCQ) to assess social functioning, regression analyses yielded negative correlations between SCQ scores and RSFC (AI-SFG; AI-thalamus; PI-FG; PI-IPL). Given the insula's connections to limbic regions, and its role in integrating external sensory stimuli with internal states, atypical activity in this structure may be associated with social deficits characterizing ASD. Our results suggest further investigation of the insula's role in SIP across a continuum of social abilities is needed.

Changed hub and functional connectivity patterns of the posterior fusiform gyrus in chess experts

The hubs of the brain network play a key role in integrating and transferring information between different functional modules. However, the effects of long-term practice on functional network hubs in chess experts are largely undefined. Here, we investigated whether alterations of hubs can be detected in chess experts using resting-state functional magnetic resonance imaging (rs-fMRI) and graph theory methods. We first mapped the whole-brain voxel-wise functional connectivity and calculated the functional connectivity strength (FCS) map in each of the 28 chess players and 27 gender- and age-matched healthy novice players. Whole-brain resting-state functional connectivity analyses for the changed hub areas were conducted to further elucidate the corresponding changes of functional connectivity patterns in chess players. The hub analysis revealed increased FCS in the right posterior fusiform gyrus of the chess players, which was supported by analyses of this area's regional homogeneity (ReHo), amplitude of low frequency fluctuations (ALFF), and fractional amplitude of low frequency fluctuations (fALFF). The following functional connectivity analyses revealed increased functional connectivities between the right posterior fusiform gyrus and the visuospatial attention and motor networks in chess players. These findings demonstrate that cognitive expertise has a positive influence on the functions of the brain regions associated with the chess expertise and that increased functional connections might in turn facilitate within and between networks communication for expert behavior to get superior performance.

Abnormal Global Functional Connectivity Patterns in Medication-Free Major Depressive Disorder

Mounting studies have applied resting-state functional magnetic resonance imaging (rs-fMRI) to study major depressive disorder (MDD) and have identified abnormal functional activities. However, how the global functional connectivity patterns change in MDD is still unknown. Using rs-fMRI, we investigated the alterations of global resting-state functional connectivity (RSFC) patterns in MDD using weighted global brain connectivity (wGBC) method. First, a whole brain voxel-wise wGBC map was calculated for 23 MDD patients and 34 healthy controls. Two-sample t-tests were applied to compare the wGBC and RSFC maps and the significant level was set at p < 0.05, cluster-level correction with voxel-level p < 0.001. MDD patients showed significantly decreased wGBC in left temporal pole (TP) and increased wGBC in right parahippocampus (PHC). Subsequent RSFC analyses showed decreased functional interaction between TP and right posterior superior temporal cortex and increased functional interaction between PHC and right inferior frontal gyrus in MDD patients. These results revealed the abnormal global FC patterns and its corresponding disrupted functional connectivity in MDD. Our findings present new evidence for the functional interruption in MDD.

Multimodal Fusion of Brain Networks with Longitudinal Couplings

In recent years, brain network analysis has attracted considerable interests in the field of neuroimaging analysis. It plays a vital role in understanding biologically fundamental mechanisms of human brains. As the upward trend of multi-source in neuroimaging data collection, effective learning from the different types of data sources, e.g. multimodal and longitudinal data, is much in demand. In this paper, we propose a general coupling framework, the multimodal neuroimaging network fusion with longitudinal couplings (MMLC), to learn the latent representations of brain networks. Specifically, we jointly factorize multimodal networks, assuming a linear relationship to couple network variance across time. Experimental results on two large datasets demonstrate the effectiveness of the proposed framework. The new approach integrates information from longitudinal, multimodal neuroimaging data and boosts statistical power to predict psychometric evaluation measures.

Regional homogeneity and functional connectivity patterns in major depressive disorder, cognitive vulnerability to depression and healthy subjects

BACKGROUND

Cognitive vulnerability to depression (CVD) is a high risk for depressive disorder. Recent studies focus on individuals with CVD to determine the neural basis of major depressive disorder (MDD) neuropathology. However, whether CVD showed specific or similar brain functional activity and connectivity patterns, compared to MDD, remain largely unknown.

METHODS

Here, using resting-state functional magnetic resonance imaging in subjects with CVD, healthy controls (HC) and MDD, regional homogeneity (ReHo) and resting-state functional connectivity (R-FC) analyses were conducted to assess local synchronization and changes in functional connectivity patterns.

RESULTS

Significant ReHo differences were found in right posterior lobe of cerebellum (PLC), left lingual gyrus (LG) and precuneus. Compared to HC, CVD subjects showed increased ReHo in the PLC, which was similar to the difference found between MDD and HC. Compared to MDD patients, CVD subjects showed decreased ReHo in PLC, LG, and precuneus. R-FC analyses found increased functional connections between LG and left inferior parietal lobule, posterior cingulate cortex, and dorsolateral prefrontal cortex in CVD compared to both HC and MDD. Moreover, Regional mean ReHo values were positively correlated with Center for Epidemiologic Studies Depression Scale scores.

CONCLUSION

These analyses revealed that PLC and functional connections between LG and left inferior parietal lobule, posterior cingulate cortex, and dorsolateral prefrontal cortex may be a potential marker for CVD.

Striatal subdivisions that coherently interact with multiple cerebrocortical networks

The striatum constitutes the cortical‐basal ganglia loop and receives input from the cerebral cortex. Previous MRI studies have parcellated the human striatum using clustering analyses of structural/functional connectivity with the cerebral cortex. However, it is currently unclear how the striatal regions functionally interact with the cerebral cortex to organize cortical functions in the temporal domain. In the present human functional MRI study, the striatum was parcellated using boundary mapping analyses to reveal the fine architecture of the striatum by focusing on local gradient of functional connectivity. Boundary mapping analyses revealed approximately 100 subdivisions of the striatum. Many of the striatal subdivisions were functionally connected with specific combinations of cerebrocortical functional networks, such as somato‐motor (SM) and ventral attention (VA) networks. Time‐resolved functional connectivity analyses further revealed coherent interactions of multiple connectivities between each striatal subdivision and the cerebrocortical networks (i.e., a striatal subdivision‐SM connectivity and the same striatal subdivision‐VA connectivity). These results suggest that the striatum contains a large number of subdivisions that mediate functional coupling between specific combinations of cerebrocortical networks.

Electroconvulsive therapy selectively enhanced feedforward connectivity from fusiform face area to amygdala in major depressive disorder

Electroconvulsive therapy (ECT) has been widely used to treat the major depressive disorder (MDD), especially for treatment-resistant depression. However, the neuroanatomical basis of ECT remains an open problem. In our study, we combined the voxel-based morphology (VBM), resting-state functional connectivity (RSFC) and granger causality analysis (GCA) to identify the longitudinal changes of structure and function in 23 MDD patients before and after ECT. In addition, multivariate pattern analysis using linear support vector machine (SVM) was applied to classify 23 depressed patients from 25 gender, age and education matched healthy controls. VBM analysis revealed the increased gray matter volume of left superficial amygdala after ECT. The following RSFC and GCA analyses further identified the enhanced functional connectivity between left amygdala and left fusiform face area (FFA) and effective connectivity from FFA to amygdala after ECT, respectively. Moreover, SVM-based classification achieved an accuracy of 83.33%, a sensitivity of 82.61% and a specificity of 84% by leave-one-out cross-validation. Our findings indicated that ECT may facilitate the neurogenesis of amygdala and selectively enhance the feedforward cortical-subcortical connectivity from FFA to amygdala. This study may shed new light on the pathological mechanism of MDD and may provide the neuroanatomical basis for ECT.

Action and semantic tool knowledge - Effective connectivity in the underlying neural networks

Evidence from neuropsychological and imaging studies indicate that action and semantic knowledge about tools draw upon distinct neural substrates, but little is known about the underlying interregional effective connectivity. With fMRI and dynamic causal modeling (DCM) we investigated effective connectivity in the left-hemisphere (LH) while subjects performed (i) a function knowledge and (ii) a value knowledge task, both addressing semantic tool knowledge, and (iii) a manipulation (action) knowledge task. Overall, the results indicate crosstalk between action nodes and semantic nodes. Interestingly, effective connectivity was weakened between semantic nodes and action nodes during the manipulation task. Furthermore, pronounced modulations of effective connectivity within the fronto-parietal action system of the LH (comprising lateral occipito-temporal cortex, intraparietal sulcus, supramarginal gyrus, inferior frontal gyrus) were observed in a bidirectional manner during the processing of action knowledge. In contrast, the function and value knowledge tasks resulted in a significant strengthening of the effective connectivity between visual cortex and fusiform gyrus. Importantly, this modulation was present in both semantic tasks, indicating that processing different aspects of semantic knowledge about tools evokes similar effective connectivity patterns. Data revealed that interregional effective connectivity during the processing of tool knowledge occurred in a bidirectional manner with a weakening of connectivity between areas engaged in action and semantic knowledge about tools during the processing of action knowledge. Moreover, different semantic tool knowledge tasks elicited similar effective connectivity patterns.