Bilateral Inferior Parietal Cortex Research Articles

Quantitative Assessment of Brain Structural Abnormalities in Children with Autism Spectrum Disorder Based on Artificial Intelligence Automatic Brain Segmentation Technology and Machine Learning Methods

Rationale and Objectives: To explore the characteristics of brain structure in Chinese children with autism spectrum disorder (ASD) using artificial intelligence automatic brain segmentation technique, and to diagnose children with ASD using machine learning (ML) methods in combination with structural magnetic resonance imaging (sMRI) features. Methods: A total of 60 ASD children and 48 age- and sex-matched typically developing (TD) children were prospectively enrolled from January 2023 to April 2024. All subjects were scanned using 3D-T1 sequences. Automated brain segmentation techniques were utilized to obtain the standardized volume of each brain structure (the ratio of the absolute volume of brain structure to the whole brain volume). The standardized volumes of each brain structure in the two groups were statistically compared, and the volume data of brain areas with significant differences were combined with ML methods to diagnose and predict ASD patients. Results: Compared with the TD group, the volumes of the right lateral orbitofrontal cortex, right medial orbitofrontal cortex, right pars opercularis, right pars triangularis, left hippocampus, bilateral parahippocampal gyrus, left fusiform gyrus, right superior temporal gyrus, bilateral insula, bilateral inferior parietal cortex, right precuneus cortex, bilateral putamen, left pallidum, and right thalamus were significantly increased in the ASD group (P < 0.05). Among six ML algorithms, support vector machine (SVM) and adaboost (AB) had better performance in differentiating subjects with ASD from those TD children, with their average area under curve (AUC) reaching 0.91 and 0.92, respectively. Conclusion: Automatic brain segmentation technology based on artificial intelligence can rapidly and directly measure and display the volume of brain structures in children with autism spectrum disorder and typically developing children. Children with ASD show abnormalities in multiple brain structures, and when paired with sMRI features, ML algorithms perform well in the diagnosis of ASD.

Facial emotion recognition deficits are associated with hypomimia and related brain correlates in Parkinson's disease.

Hypomimia is a frequent manifestation in Parkinson's disease (PD) that can affect interpersonal relationships and quality of life. Recent studies have suggested that hypomimia is not only related to motor dysfunction but also to impairment in emotional processing networks. Therefore, we hypothesized that the severity of hypomimia could be associated with performance on a task aimed at assessing facial emotion recognition. In this study, we explored the association between hypomimia, recognition of facial expressions of basic emotions using the Ekman 60 Faces Test (EF), and brain correlates of both hypomimia and performance on the EF. A total of 94 subjects underwent clinical assessments (neurological and neuropsychological examinations), and 56 of them participated in the neuroimaging study. We found significant correlation between hypomimia, EF Disgust (r = -0.242, p = 0.022) and EF Happiness (r = -0.264, p = 0.012); an independent reduction in Cortical Thickness (Cth) in the postcentral gyrus, insula, middle and superior temporal gyri, supramarginal gyrus, banks of the superior temporal sulcus, bilateral fusiform gyri, entorhinal cortex, parahippocampal gyrus, inferior and superior parietal cortex, and right cuneus and precuneus; and multiple correlations between negative emotions such as EF Disgust or EF Anger and a reduced Cth in fronto-temporo-parietal regions. In conclusion, these results suggest that the association between hypomimia and emotion recognition deficits in individuals with PD might be mediated by shared circuits, supporting the concept that hypomimia is not only the result of the dysfunction of motor circuits, but also of higher cognitive functions.

The visuo-sensorimotor substrate of co-speech gesture processing

Co-speech gestures are integral to human communication and exhibit diverse forms, each serving a distinct communication function. However, existing literature has focused on individual gesture types, leaving a gap in understanding the comparative neural processing of these diverse forms. To address this, our study investigated the neural processing of two types of iconic gestures: those representing attributes or event knowledge of entity concepts, beat gestures enacting rhythmic manual movements without semantic information, and self-adaptors. During functional magnetic resonance imaging, systematic randomization and attentive observation of video stimuli revealed a general neural substrate for co-speech gesture processing primarily in the bilateral middle temporal and inferior parietal cortices, characterizing visuospatial attention, semantic integration of cross-modal information, and multisensory processing of manual and audiovisual inputs. Specific types of gestures and grooming movements elicited distinct neural responses. Greater activity in the right supramarginal and inferior frontal regions was specific to self-adaptors, and is relevant to the spatiomotor and integrative processing of speech and gestures. The semantic and sensorimotor regions were least active for beat gestures. The processing of attribute gestures was most pronounced in the left posterior middle temporal gyrus upon access to knowledge of entity concepts. This fMRI study illuminated the neural underpinnings of gesture-speech integration and highlighted the differential processing pathways for various co-speech gestures.

Mild behavioral impairment linked to phenoconversion to Alzheimer’s disease and cortical thinning in mild cognitive impairment

AbstractBackgroundMild Behavioral Impairment (MBI) is a neurobehavioral syndrome characterized by later life emergence of sustained neuropsychiatric symptoms, as an at‐risk state for dementia (Ismail Z, Alzheimers Dement, 2016). However, the associations between MBI and a risk of phenocoversion to dementia and its neuroanatomical correlates in MCI are still unclear.MethodA total 1326 older adults with MCI was followed for a mean of 3.0 ± 2.0 years. MBI was approximated using a transformation algorithm for the neuropsychiatric inventory at baseline. Two‐step cluster analysis was used to explore classes of 5 MBI domains (decreased motivation, affective dysregulation, impulse dyscontrol, social inappropriateness, abnormal perception/thought content). A Cox regression analysis was applied to investigate the association between the clusters and phenoconversion to AD. A subset of participants (n = 225) underwent 3D T1‐weighted MRI scans and cortical thickness was compared among the clusters of MBI domains.ResultThe cluster analysis identified 3 groups of participants: (1) people without MBI (47.8%, asymptomatic); (2) people with only affective dysregulation (29.3%, affective dysregulation); (3) people with relatively high probability of affective dysregulation, followed by impulse dyscontrol and affective dysregulation (22.9%, multiple domains). Compared to the asymptomatic, multiple domains was associated with a higher risk of phenoconversion to AD (hazard ratio = 2.589 [1.981 – 3.385], p = &lt; 0.001), but affective dysregulation did not predict phenoconversion (1.204 [0.896 – 1.620], p = 0.219) (Fig 1). MCI individuals with symptoms in multiple domains revealed thinning in the bilateral superior and inferior parietal, superior temporal, and prefrontal cortex, and the right precuneus compared to those with only affective dysregulation (Fig 2). We did not find differences in cortical thickness between phenocoverter and non‐phenoconverter, and interaction of clusters of MBI domains and phenoconversion.ConclusionThe multiple co‐occuring MBI domains in individuals with MCI are associated with a higher risk of phenoconversion to AD. Moreover, MCI individuals with symptoms in multiple domains revealed cortical thinning in the superior parietal and precuneus, which have suggested as AD signatures (Dickerson BC, Cereb Cortex, 2009). These results suggest that evaluation of MBI and neuroimaging characteristics could be useful for risk stratification in MCI individuals.

Functional and effective connectivity analysis of drug-resistant epilepsy: a resting-state fMRI analysis.

Epilepsy is considered as a neural network disorder. Seizure activity in epilepsy may disturb brain networks and damage brain functions. We propose using resting-state functional magnetic resonance imaging (rs-fMRI) data to characterize connectivity patterns in drug-resistant epilepsy. This study enrolled 47 participants, including 28 with drug-resistant epilepsy and 19 healthy controls. Functional and effective connectivity was employed to assess drug-resistant epilepsy patients within resting state networks. The resting state functional connectivity (FC) analysis was performed to assess connectivity between each patient and healthy controls within the default mode network (DMN) and the dorsal attention network (DAN). In addition, dynamic causal modeling was used to compute effective connectivity (EC). Finally, a statistical analysis was performed to evaluate our findings. The FC analysis revealed significant connectivity changes in patients giving 64.3% (18/28) and 78.6% (22/28) for DMN and DAN, respectively. Statistical analysis of FC was significant between the medial prefrontal cortex, posterior cingulate cortex, and bilateral inferior parietal cortex for DMN. For DAN, it was significant between the left and the right intraparietal sulcus and the frontal eye field. For the DMN, the patient group showed significant EC connectivity in the right inferior parietal cortex and the medial prefrontal cortex for the DMN. There was also bilateral connectivity between the medial prefrontal cortex and the posterior cingulate cortex, as well as between the left and right inferior parietal cortex. For DAN, patients showed significant connectivity in the right frontal eye field and the right intraparietal sulcus. Bilateral connectivity was also found between the left frontal eye field and the left intraparietal sulcus, as well as between the right frontal eye field and the right intraparietal sulcus. The statistical analysis of the EC revealed a significant result in the medial prefrontal cortex and the right intraparietal cortex for the DMN. The DAN was found significant in the left frontal eye field, as well as the left and right intraparietal sulcus. Our results provide preliminary evidence to support that the combination of functional and effective connectivity analysis of rs-fMRI can aid in diagnosing epilepsy in the DMN and DAN networks.

Conduct problems are associated with accelerated thinning of emotion-related cortical regions in a community-based sample of adolescents.

Few studies have examined the association between conduct problems and cerebral cortical development. Herein, we characterize the association between age-related brain change and conduct problems in a large longitudinal, community-based sample of adolescents. 1,039 participants from the IMAGEN study possessed psychopathology and surface-based morphometric data at study baseline (M=14.42 years, SD=0.40; 559 females) and 5-year follow-up. Self-reports of conduct problems were obtained using the Strengths and Difficulties Questionnaire (SDQ). Vertex-level linear mixed effects models were implemented using the Matlab toolbox, SurfStat. To investigate the extent to which cortical thickness maturation was qualified by dimensional measures of conduct problems, we tested for an interaction between age and SDQ Conduct Problems (CP) score. There was no main effect of CP score on cortical thickness; however, a significant "Age by CP" interaction was revealed in bilateral insulae, left inferior frontal gyrus, left rostral anterior cingulate, left posterior cingulate, and bilateral inferior parietal cortices. Across regions, follow-up analysis revealed higher levels of CP were associated with accelerated age-related thinning. Findings were not meaningfully altered when controlling for alcohol use, co-occurring psychopathology, and socioeconomic status. Results may help to further elucidate neurodevelopmental patterns linking adolescent conduct problems with adverse adult outcomes.

Cerebrovascular Reactivity Has Negligible Contribution to Hemodynamic Lag After Stroke: Implications for Functional Magnetic Resonance Imaging Studies.

Functional magnetic resonance imaging (fMRI) is ubiquitously used to study poststroke recovery. However, the fMRI-derived hemodynamic responses are vulnerable to vascular insult which can result in reduced magnitude and temporal delays (lag) in the hemodynamic response function (HRF). The cause of HRF lag remains controversial, and a better understanding of it is required to ensure accurate interpretation of poststroke fMRI studies. In this longitudinal study, we investigate the relationship between hemodynamic lag and cerebrovascular reactivity (CVR) following stroke. Voxel-wise lag maps were calculated relative to a mean gray matter reference signal for 27 healthy controls and 59 patients with stroke across 2 time points (≈2 weeks and ≈4 months poststroke) and 2 conditions: resting-state and breath-holding. The breath-holding condition was additionally used to calculate CVR in response to hypercapnia. HRF lag was computed for both conditions across tissue compartments: lesion, perilesional tissue, unaffected tissue of the lesioned hemisphere, and their homolog regions in the unaffected hemisphere. CVR and lag maps were correlated. Group, condition, and time effects were assessed using ANOVA analyses. Compared with the average gray matter signal, a relative hemodynamic lead was observed in the primary sensorimotor cortices in resting-state and bilateral inferior parietal cortices in the breath-holding condition. Whole-brain hemodynamic lag was significantly correlated across conditions irrespective of group, with regional differences across conditions suggestive of a neural network pattern. Patients showed relative lag in the lesioned hemisphere which significantly reduced over time. Breath-hold derived lag and CVR had no significant voxel-wise correlation in controls, or patients within the lesioned hemisphere or the homologous regions of the lesion and perilesional tissue in the right hemisphere (mean r<0.1). The contribution of altered CVR to HRF lag was negligible. We suggest that HRF lag is largely independent of CVR, and could partly reflect intrinsic neural network dynamics among other factors.

Neural responding during uncertain threat anticipation in pediatric anxiety.

Excessive fear responses to uncertain threat are a key feature of anxiety disorders (ADs), though most mechanistic work considers adults. As ADs onset in childhood and confer risk for later psychopathology, we sought to identify conditions of uncertain threat that distinguish 8-17-year-old youth with AD (n = 19) from those without AD (n = 33), and assess test-retest reliability of such responses in a companion sample of healthy adults across three sites (n = 19). In an adapted uncertainty of threat paradigm, visual cues parametrically signaled threat of aversive stimuli (fear faces) in 25 % increments (0 %, 25 %, 50 %, 100 %), while participants underwent functional magnetic resonance imaging (fMRI). We compared neural response elicited by cues signaling different degrees of probability regarding the subsequent delivery of fear faces. Overall, youth displayed greater engagement of bilateral inferior parietal cortex, fusiform gyrus, and lingual gyrus during uncertain threat anticipation in general. Relative to healthy youth, AD youth exhibited greater activation in ventrolateral prefrontal cortex (vlPFC)/BA47 during uncertain threat anticipation in general. Further, AD differed from healthy youth in scaling of ventral striatum/sgACC activation with threat probability and attenuated flexibility of responding during parametric uncertain threat. Complementing these results, significant, albeit modest, cross-site test-retest reliability in these regions was observed in an independent sample of healthy adults. While preliminary due to a small sample size, these findings suggest that during uncertainty of threat, AD youth engage vlPFC regions known to be involved in fear regulation, response inhibition, and cognitive control. Findings highlight the potential of isolating neural correlates of threat anticipation to guide treatment development and translational work in youth.

The impact of visual cross-modal conflict with semantic and nonsemantic distractors on working memory task: A functional near-infrared spectroscopy study.

Cross-modal conflicts arise when information from multisensory modalities is incongruent. Most previous studies investigating audiovisual cross-modal conflicts have focused on visual targets with auditory distractors, and only a few studies have focused on auditory targets with visual distractors. Moreover, no study has investigated the differences in the impact of visual cross-modal conflict with semantic and nonsemantic competition and its neural basis. This cross-sectional study aimed to characterize the impact of 2 types of visual cross-modal conflicts with semantic and nonsemantic distractors through a working memory task and associated brain activities. The participants were 33 healthy, right-handed, young male adults. The paced auditory serial addition test was performed under 3 conditions: no-distractor and 2 types of visual distractor conditions (nonsemantic and semantic distractor conditions). Symbols and numbers were used as nonsemantic and semantic distractors, respectively. The oxygenated hemoglobin (Oxy-Hb) concentration in the frontoparietal regions, bilateral ventrolateral prefrontal cortex (VLPFC), dorsolateral prefrontal cortex, and inferior parietal cortex (IPC) were measured during the task under each condition. The results showed significantly lower paced auditory serial addition test performances in both distractor conditions than in the no-distractor condition, but no significant difference between the 2 distractor conditions. For brain activity, a significantly increased Oxy-Hb concentration in the right VLPFC was only observed in the nonsemantic distractor condition (corrected P = .015; Cohen d = .46). The changes in Oxy-Hb in the bilateral IPC were positively correlated with changes in task performance for both types of visual cross-modal distractor conditions. Visual cross-modal conflict significantly impairs auditory working memory task performance, regardless of the presence of semantic or nonsemantic distractors. The right VLPFC may be a crucial region to inhibit visual nonsemantic information in cross-modal conflict situations, and bilateral IPC may be closely linked with the inhibition of visual cross-modal distractor, regardless of the presence of semantic or nonsemantic distractors.

Effect of Audiovisual Cross-Modal Conflict during Working Memory Tasks: A Near-Infrared Spectroscopy Study.

Cognitive conflict effects are well characterized within unimodality. However, little is known about cross-modal conflicts and their neural bases. This study characterizes the two types of visual and auditory cross-modal conflicts through working memory tasks and brain activities. The participants consisted of 31 healthy, right-handed, young male adults. The Paced Auditory Serial Addition Test (PASAT) and the Paced Visual Serial Addition Test (PVSAT) were performed under distractor and no distractor conditions. Distractor conditions comprised two conditions in which either the PASAT or PVSAT was the target task, and the other was used as a distractor stimulus. Additionally, oxygenated hemoglobin (Oxy-Hb) concentration changes in the frontoparietal regions were measured during tasks. The results showed significantly lower PASAT performance under distractor conditions than under no distractor conditions, but not in the PVSAT. Oxy-Hb changes in the bilateral ventrolateral prefrontal cortex (VLPFC) and inferior parietal cortex (IPC) significantly increased in the PASAT with distractor compared with no distractor conditions, but not in the PVSAT. Furthermore, there were significant positive correlations between Δtask performance accuracy and ΔOxy-Hb in the bilateral IPC only in the PASAT. Visual cross-modal conflict significantly impairs auditory task performance, and bilateral VLPFC and IPC are key regions in inhibiting visual cross-modal distractors.

Negative schizophrenic symptoms as prefrontal cortex dysfunction: Examination using a task measuring goal neglect

BackgroundThe negative symptoms of schizophrenia have been proposed to reflect prefrontal cortex dysfunction. However, this proposal has not been consistently supported in functional imaging studies, which have also used executive tasks that may not capture key aspects of negative symptoms such as lack of volition. MethodTwenty-four DSM-5 schizophrenic patients with high negative symptoms (HNS), 25 with absent negative symptoms (ANS) and 30 healthy controls underwent fMRI during performance of the Computerized Multiple Elements Test (CMET), a task designed to measure poor organization of goal directed behaviour or ‘goal neglect’. Negative symptoms were rated using the PANSS and the Clinical Assessment Interview for Negative Symptoms (CAINS). ResultsOn whole brain analysis, the ANS patients showed no significant clusters of reduced activation compared to the healthy controls. In contrast, the HNS patients showed hypoactivation compared to the healthy controls in the left anterior frontal cortex, the right dorsolateral prefrontal cortex (DLPFC), the anterior insula bilaterally and the bilateral inferior parietal cortex. When compared to the ANS patients, the HNS patients showed reduced activation in the left anterior frontal cortex, the left DLPFC and the left inferior parietal cortex. After controlling for disorganization scores, differences remained in clusters in the left anterior frontal cortex and the bilateral inferior parietal cortex. ConclusionsThis study provides evidence that reduced prefrontal activation, perhaps especially in the left anterior frontal cortex, is a brain functional correlate of negative symptoms in schizophrenia. The simultaneous finding of reduced inferior parietal cortex activation was unexpected, but could reflect this region’s involvement in cognitive control, particularly the ‘regulative’ component of this.

Repetitive transcranial magnetic stimulation modulates coupling among large-scale brain networks in heroin-dependent individuals: A randomized resting-state functional magnetic resonance imaging study.

The abnormal interactions of three key large-scale brain networks (default mode [DMN], salience and executive control [ECN]) were showed underlie dysfunctions in heroin addiction. Repetitive transcranial magnetic stimulation (rTMS) targeting the left dorsolateral prefrontal cortex (DLPFC) is a potential treatment for heroin addiction. It is unclear whether impaired coupling among the large-scale brain networks would be improved by rTMS in treated heroin-dependent individuals. Thirty-five heroin-dependent individuals were included in this sham-controlled, randomized study. The patients received either active or sham rTMS for 1week. The craving for heroin and resting-state functional magnetic resonance imaging data were collected before and after 1-week rTMS. Twenty-two healthy subjects were included as controls not receiving rTMS. After 1-week rTMS, only the active rTMS group showed a significant decrease in spontaneous and heroin cue-induced craving. The coupling between left DLPFC (a key node of left ECN) and left parahippocampal gyrus (PHG, included in DMN) significantly increased for the active group with a tendency towards that of controls. The coupling between the right precentral gyrus and three key regions included in DMN (posterior cingulate cortex/precuneus and bilateral inferior parietal cortex) significantly decreased for the active group with a tendency towards that of healthy controls. For the active rTMS individuals, the left DLPFC-PHG coupling negatively correlated with the spontaneous craving and the drug cue-induced craving. It suggested that the rTMS could reduce heroin craving, which might be related to the modulation of ECN-DMN coupling. This finding might shed light on the mechanism of rTMS for heroin addiction treatment.

Polygenic risk for obsessive-compulsive disorder (OCD) predicts brain response during working memory task in OCD, unaffected relatives, and healthy controls

Alterations in frontal and parietal neural activations during working memory task performance have been suggested as a candidate endophenotype of obsessive-compulsive disorder (OCD) in studies involving first-degree relatives. However, the direct link between genetic risk for OCD and neuro-functional alterations during working memory performance has not been investigated to date. Thus, the aim of the current functional magnetic resonance imaging (fMRI) study was to test the direct association between polygenic risk for OCD and neural activity during the performance of a numeric n-back task with four working memory load conditions in 128 participants, including patients with OCD, unaffected first-degree relatives of OCD patients, and healthy controls. Behavioral results show a significant performance deficit at high working memory load in both patients with OCD and first-degree relatives (p < 0.05). A whole-brain analysis of the fMRI data indicated decreased neural activity in bilateral inferior parietal lobule and dorsolateral prefrontal cortex in both patients and relatives. Most importantly, OCD polygenic risk scores predicted neural activity in orbitofrontal cortex. Results indicate that genetic risk for OCD can partly explain alterations in brain response during working memory performance, supporting the notion of a neuro-functional endophenotype for OCD.

Functional Brain Networks of Trait and State Anxiety in Late-Life Depression

<h3>Introduction</h3> Late-life depression (LLD) is associated with psychiatric comorbidities that may worsen mood outcomes in older adults, yet the neural mechanisms that underlie these comorbid conditions remain understudied. Anxiety and neuroticism have been independently associated with LLD, and its mood and cognitive outcomes. In a preliminary behavioral data analysis we found that anxiety measures correlated with depression measures in older adults. We also found that several baseline neuroticism and anxiety traits predicted depression scores over time. In this study, we analyzed neuroimaging data in the setting of anxiety and neuroticism measures in LLD and hypothesized that there would be differences in resting state activity patterns in the Salience network (SN), Default-Mode network (DMN) and Executive Control network (ECN) related to severity of: (1) generalized anxiety, (2) state and trait anxiety, and (3) neuroticism. <h3>Methods</h3> This was a cross-sectional secondary data analysis on clinical and MRI data collected from our NBOLD project. LLD patients without dementia were included. Generalized anxiety disorder (GAD) symptoms, state and trait anxiety, neuroticism and depression were assessed using a GAD questionnaire, State-Trait Anxiety Inventory (STAI), NEO Personality Inventory (NEO PI), and Montgomery-Asberg Depression Rating Scale (MADRS), respectively. A study psychiatrist confirmed or ruled out diagnosis of depression. There were 102 older adults with LLD, and among them, 87 subjects who had measures of STAI-trait, STAI-state anxiety, GAD symptoms and neuroticism as well as usable neuroimaging data were included into our final analyses. The neuroimaging data was collected from 3T Siemens Skyra scanner. The imaging parameters for T1-weighted images were: TR/TE=2200/2.8ms, flip angle=13^o, matrix = 256 × 256 × 169, Voxelsize=1×1×1mm³. The 7-min resting-state fMRI data was collected using EPI sequence with FOV=240mm, flip angle=90^o, TR/TE=2000/31ms, matrix=64×64×34, voxelsize = 3.8×3.8×3.75mm³. The fMRI data was preprocessed using the default protocol setting recommend by DPABI software. The Amplitude of Low-Frequency Fluctuations (ALFF) was calculated using DPABI. Multiple regression model was used to examine the association between ALFF and GAD, state and trait anxiety as well as neuroticism controlled for age, gender and depression severity (MADRS) using SPM12. Significance was set at p<0.05 with FDR correction for multiple comparisons. <h3>Results</h3> Data analyses revealed that trait anxiety was positively correlated with greater ALFF in the ECN (left dorsolateral prefrontal cortex - dlPFC, bilateral inferior parietal cortex - IPS, and precuneus) and lateral orbitofrontal cortex (OFC). Higher state anxiety was correlated with lower ALFF in bilateral OFC and frontal pole. GAD symptom severity was positively correlated with ALFF in the right superior temporal cortex (STG), Heschl's gyrus, and dorsomedial frontal cortex (dMFC). The GAD symptom severity was also negatively correlated with ALFF in the right hippocampus, parahippocampus and temporal pole (TP), whereas there was no significant clusters found between ALFF and neuroticism after regressing out the covariates. <h3>Conclusions</h3> This is one the few studies that examined resting state neural oscillation pattern (ALFF) specific to state and trait anxiety and GAD symptoms in LLD. Higher trait anxiety was associated with greater ALFF in the ECN and OFC, all of which are related to emotion regulation, whereas higher state anxiety was correlated with lower ALFF in regions related to emotion regulation. Higher GAD was specifically correlated with higher ALFF in brain regions related to sound and social information processing, but with lower ALFF in regions related to memory. No significant clusters were found related to neuroticism suggesting that neuroticism might be able explained by trait and state anxiety as well as GAD. These results suggests a distinct neural construct that may distinguish state and trait anxiety in LLD. Uncovering the brain connectivity changes related to state and trait anxiety would deepen our understanding in the neural mechanisms and mood outcomes of LLD. Future studies are needed to determine differences in these networks between depressed and non-depressed individuals. <h3>Funding</h3> The Leo and Anne Albert Charitable Trust, National Institute of Mental Health Grant R01 MH108578, The University of Connecticut Department of Psychiatry

Oscillatory Bursts in Parietal Cortex Reflect Dynamic Attention between Multiple Objects and Ensembles.

The visual system uses two complimentary strategies to process multiple objects simultaneously within a scene and update their spatial positions in real time. It either uses selective attention to individuate a complex, dynamic scene into a few focal objects (i.e., object individuation), or it represents multiple objects as an ensemble by distributing attention more globally across the scene (i.e., ensemble grouping). Neural oscillations may be a key signature for focal object individuation versus distributed ensemble grouping, because they are thought to regulate neural excitability over visual areas through inhibitory control mechanisms. We recorded whole-head MEG data during a multiple-object tracking paradigm, in which human participants (13 female, 11 male) switched between different instructions for object individuation and ensemble grouping on different trials. The stimuli, responses, and the demand to keep track of multiple spatial locations over time were held constant between the two conditions. We observed increased α-band power (9-13 Hz) packed into oscillatory bursts in bilateral inferior parietal cortex during multiple-object processing. Single-trial analysis revealed greater burst occurrences on object individuation versus ensemble grouping trials. By contrast, we found no differences using standard analyses on across-trials averaged α-band power. Moreover, the bursting effects occurred only below/at, but not above, the typical capacity limits for multiple-object processing (at ∼4 objects). Our findings reveal the real-time neural correlates underlying the dynamic processing of multiple-object scenarios, which are modulated by grouping strategies and capacity. They support a rhythmic, α-pulsed organization of dynamic attention to multiple objects and ensembles.SIGNIFICANCE STATEMENT Dynamic multiple-object scenarios are an important problem in real-world and computer vision. They require keeping track of multiple objects as they move through space and time. Such problems can be solved in two ways: One can individuate a scene object by object, or alternatively group objects into ensembles. We observed greater occurrences of α-oscillatory burst events in parietal cortex for processing objects versus ensembles and below/at versus above processing capacity. These results demonstrate a unique top-down mechanism by which the brain dynamically adjusts its computational level between objects and ensembles. They help to explain how the brain copes with its capacity limitations in real-time environments and may lead the way to technological innovations for time-critical video analysis in computer vision.

EEG gamma activity to emotional movies in individuals with high traits of primary “successful” psychopathy

This study aimed to investigate emotional alterations in a community sample with primary psychopathic traits. Sixty males selected from a larger sample and divided in two groups, High (HP) and Low (LP) primary Psychopathy, watched 15 validated emotional movies divided in five categories (Erotic, Neutral, Fear, and the new Scenery and Compassion). Subjective responses and cortical activity in the EEG Gamma band (30–49 Hz) were recorded. Concerning self-reports, HP participants felt less anxious and anguished in response to Fear clips and less sad, touched and anguished by Compassion excerpts. Negative clips induced larger EEG Gamma activity in both groups compared to neutral and erotic movies, but Gamma activity to Fear movies was reduced in HP. This group showed also a small cortical response to positive Scenery movies, at the level of the Neutral ones. Source analysis showed in HP participants a reduced cortical activation to Fear in a large brain network, comprising the right prefrontal and temporal cortices and bilateral inferior parietal cortex. Results showed that primary psychopathy, in addition to the impaired response to Fear, was associated with a reduced response also to other specific categories of emotional stimuli, suggesting an altered affect on a broader scale.

Cortical Thickness in Alcohol Dependent Patients With Apathy.

ObjectivesMany studies reported structural brain changes in patients with alcohol dependence (PADs). However, no studies identified structural correlates of apathy that might aggravate alcohol misuse. Here, we explored regional differences in cortical thickness in PADs relative to healthy controls (HCs), and examined the potential correlation of regional thickness with the severity of apathy.MethodsMagnetic resonance imaging data were collected from 33 male PADs and 35 male age- and education-matched HCs. We used the FreeSurfer software to investigate group differences in cortical thickness across 148 regions. Apathy was evaluated using the Lille Apathy Rating Scale-Informant (LARS-I). Regression analyses examined the relationship between cortical thickness of regions of interest and apathy score in PADs.ResultsCompared to HCs, PADs showed significant decreases in the cortical thickness of occipito-temporal cortex (OTC), including the left middle occipital gyrus and occipital pole, right superior occipital gyri, and bilateral lingual gyrus; bilateral superior parietal cortex (SPC), including the right intraparietal sulcus; and bilateral inferior parietal cortex (IPC). Furthermore, the cortical thickness of all of the three regions was negatively correlated with the apathy total scores. The cortical thickness of the IPC was also negatively correlated with the action initiation subscore of the LARS-I.ConclusionsThe current results suggest the thickness of bilateral parietal and occipital temporal cortices as neural markers of apathy in PADs. These findings add to the literature by identifying the neural bases of a critical clinical feature of individuals with alcoholism.

Stereoscopic Rendering via Goggles Elicits Higher Functional Connectivity During Virtual Reality Gaming.

Virtual reality (VR) simulates real-world scenarios by creating a sense of presence in its users. Such immersive scenarios lead to behavior that is more similar to that displayed in real world settings, which may facilitate the transfer of knowledge and skills acquired in VR to similar real world situations. VR has already been used in education, psychotherapy, rehabilitation and it comes as an appealing choice for training intervention purposes. The aim of the present study was to investigate to what extent VR technology for games presented via goggles can be used in a magnetic resonance imaging scanner (MRI), addressing the question of whether brain connectivity differs between VR stimulation via goggles and a presentation from a screen via mirror projection. Moreover, we wanted to investigate whether stereoscopic goggle stimulation, where both eyes receive different visual input, would elicit stronger brain connectivity than a stimulation in which both eyes receive the same visual input (monoscopic). To our knowledge, there is no previous research using games and functional connectivity (FC) in MRI to address this question. Multiple analyses approaches were taken so that different aspects of brain connectivity could be covered: fractional low-frequency fluctuation, independent component analysis (ICA), seed-based FC (SeedFC) and graph analysis. In goggle presentation (mono and stereoscopic) as contrasted to screen, we found differences in brain activation in left cerebellum and postcentral gyrus as well as differences in connectivity in the visual cortex and frontal inferior cortex [when focusing on the visual and default mode network (DMN)]. When considering connectivity in specific areas of interest, we found higher connectivity between bilateral superior frontal cortex and the temporal lobe, as well as bilateral inferior parietal cortex with right calcarine and right lingual cortex. Furthermore, we found superior frontal cortex and insula/putamen to be more strongly connected in goggle stereoscopic vs. goggle monoscopic, in line with our hypothesis. We assume that the condition that elicits higher brain connectivity values should be most suited for long-term brain training interventions given that, extended training under these conditions could permanently improve brain connectivity on a functional as well as on a structural level.

Reduced synchronized brain activity in schizophrenia during viewing of comedy movies

Previous evaluation of brain function in schizophrenia has focused on standard experimental tasks, with cerebral response to natural stimuli less clear. This study employed inter-subject correlation (ISC) analysis to investigate the neural basis of humor processing during free viewing of comedy movies in patients with schizophrenia. We recruited 29 patients diagnosed with schizophrenia and 29 healthy, age- and sex-matched controls. Each participant underwent fMRI scanning during two viewings of three comedy movie clips. The ISC map from each participant pair within each population group and each movie viewing was separately derived. The significance of ISC within a group and between two groups were assessed by bootstrapping. The ISC map from each patient pair were also correlated with the product of Positive and Negative Syndrome Scale (PANSS) rating between the same participant pair in schizophrenia patients. Schizophrenia patients showed significant ISC in bilateral lateraloccipital, bilateral superior frontal, left supramarginal, and right lateralorbiofrontal cortices. Compared with the controls, the schizophrenia group exhibited significantly lower ISC in the left superior temporal sulcus, bilateral supramarginal, and bilateral inferiorparietal cortices. Higher clinical severity (higher total PANSS rating) was associated with lower ISC in the middle frontal and middle temporal regions, and also higher ISC in the visual cortex, inferior temporal gyrus, and anterior cingulate. The findings indicated that patients with schizophrenia are characterized by lower ISC in a frontal parietal network while viewing comedy film clips, which implicated a deficit in the cognitive component of humor processing. The lower synchronization in parts of the frontal parietal network also correlated with symptom severity.

Processing symbolic and non-symbolic proportions: Domain-specific numerical and domain-general processes in intraparietal cortex

Previous studies on the processing of fractions and proportions focused mainly on the processing of their overall magnitude information in the intraparietal sulcus (IPS). However, the IPS is also associated with domain-general cognitive functions beyond processing overall magnitude, which may nevertheless be involved in operating on magnitude information of proportions. To pursue this issue, the present study aimed at investigating whether there is a shared neural correlate for proportion processing in the intraparietal cortex beyond overall magnitude processing and how part-whole relations are processed on the neural level. Across four presentation formats (i.e., fractions, decimals, dot patterns, and pie charts) we observed a shared neural substrate in bilateral inferior parietal cortex, slightly anterior and inferior to IPS areas recently found for overall magnitude proportion processing. Nevertheless, when evaluating the neural correlates of part-whole processing (i.e., contrasting fractions, dot patterns, and pie charts vs. decimals), we found wide-spread activation in fronto-parietal brain areas. These results indicate involvement of domain-general cognitive processes in part-whole processing beyond processing the overall magnitude of proportions. The dissociation between proportions involving part-whole relations and decimals was further substantiated by a representational similarity analysis, which revealed common neural processing for fractions, pie charts, and dot patterns, possibly representing their bipartite part-whole structure. In contrast, decimals seemed to be processed differently on the neural level, possibly reflecting missing processes of actual proportion calculation in decimals.