Cortical folding patterns are associated with impulsivity in healthy young adults

Associations between behavioral and self-reported impulsivity, brain structure, and genetic influences in middle childhood

Impulsivity undergoes a normative developmental trajectory from childhood to adulthood and is thought to be driven by maturation of brain structure. However, few large-scale studies have assessed associations between impulsivity, brain structure, and genetic susceptibility in children. In 9112 children ages 9-10 from the ABCD study, we explored relationships among impulsivity (UPPS-P impulsive behavior scale; delay discounting), brain structure (cortical thickness (CT), cortical volume (CV), and cortical area (CA)), and polygenic scores for externalizing behavior (PGSEXT). Both higher UPPS-P total scores and more severe delay-discounting had widespread, low-magnitude associations with smaller CA in frontal and temporal regions. No associations were seen between impulsivity and CV or CT. Additionally, higher PGSEXT was associated with both higher UPPS-P scores and with smaller CA and CV in frontal and temporal regions, but in non-overlapping cortical regions, underscoring the complex interplay between genetics and brain structure in influencing impulsivity. These findings indicate that, within large-scale population data, CA is significantly yet weakly associated with each of these impulsivity measures and with polygenic risk for externalizing behaviors, but in distinct brain regions. Future work should longitudinally assess these associations through adolescence, and examine associated functional outcomes, such as future substance use and psychopathology.

Modeling refined differences of cortical folding patterns via spatial, morphological, and temporal fusion representations

The gyrus, a pivotal cortical folding pattern, is essential for integrating brain structure-function. This study focuses on 2-Hinge and 3-Hinge folds, characterized by the gyral convergence from various directions. Existing voxel-level studies may not adequately capture the precise spatial relationships within cortical folding patterns, especially when relying solely on local cortical characteristics due to their variable shapes and homogeneous frequency-specific features. To overcome these challenges, we introduced a novel model that combines spatial distribution, morphological structure, and functional magnetic resonance imaging data. We utilized spatio-morphological residual representations to enhance and extract subtle variations in cortical spatial distribution and morphological structure during blood oxygenation, integrating these with functional magnetic resonance imaging embeddings using self-attention for spatio-morphological-temporal representations. Testing these representations for identifying cortical folding patterns, including sulci, gyri, 2-Hinge, and 2-Hinge folds, and evaluating the impact of phenotypic data (e.g. stimulus) on recognition, our experimental results demonstrate the model's superior performance, revealing significant differences in cortical folding patterns under various stimulus. These differences are also evident in the characteristics of sulci and gyri folds between genders, with 3-Hinge showing more variations. Our findings indicate that our representations of cortical folding patterns could serve as biomarkers for understanding brain structure-function correlations.

Identification for the cortical 3-Hinges folding pattern based on cortical morphological and structural features

The Cortical 3-Hinges Folding Pattern (i.e., 3-Hinges) is one of the brain's hallmarks, and it is of great reference for predicting human intelligence, diagnosing eurological diseases and understanding the brain functional structure differences among gender. Given the significant morphological variability among individuals, it is challenging to identify 3-Hinges, but current 3-Hinges researches are mainly based on the computationally expensive Gyral-net method. To address this challenge, this paper aims to develop a deep network model to realize the fast identification of 3-Hinges based on cortical morphological and structural features. The main work includes: (1) The morphological and structural features of the cerebral cortex are extracted to relieve the imbalance between the number of 3-Hinges and each brain image's voxels; (2) The feature vector is constructed with the K nearest neighbor algorithm from the extracted scattered features of the morphological and structural features to alleviate over-fitting in training; (3) The squeeze excitation module combined with the deep U-shaped network structure is used to learn the correlation of the channels among the feature vectors; (4) The functional structure roles that 3-Hinges plays between adolescent males and females are discussed in this work. The experimental results on both adolescent and adult MRI datasets show that the proposed model achieves better performance in terms of time consumption. Moreover, this paper reveals that cortical sulcus information plays a critical role in the procedure of identification, and the cortical thickness, cortical surface area, and volume characteristics can supplement valuable information for 3-Hinges identification to some extent. Furthermore, there are significant structural differences on 3-Hinges among adolescent gender.

Abnormal Brain Circuits Characterize Borderline Personality and Mediate the Relationship between Childhood Traumas and Symptoms: A mCCA+jICA and Random Forest Approach

Borderline personality disorder (BPD) is a severe personality disorder whose neural bases are still unclear. Indeed, previous studies reported inconsistent findings concerning alterations in cortical and subcortical areas. In the present study, we applied for the first time a combination of an unsupervised machine learning approach known as multimodal canonical correlation analysis plus joint independent component analysis (mCCA+jICA), in combination with a supervised machine learning approach known as random forest, to possibly find covarying gray matter and white matter (GM-WM) circuits that separate BPD from controls and that are also predictive of this diagnosis. The first analysis was used to decompose the brain into independent circuits of covarying grey and white matter concentrations. The second method was used to develop a predictive model able to correctly classify new unobserved BPD cases based on one or more circuits derived from the first analysis. To this aim, we analyzed the structural images of patients with BPD and matched healthy controls (HCs). The results showed that two GM-WM covarying circuits, including basal ganglia, amygdala, and portions of the temporal lobes and of the orbitofrontal cortex, correctly classified BPD against HC. Notably, these circuits are affected by specific child traumatic experiences (emotional and physical neglect, and physical abuse) and predict symptoms severity in the interpersonal and impulsivity domains. These results support that BPD is characterized by anomalies in both GM and WM circuits related to early traumatic experiences and specific symptoms.

Altered dynamic amplitude of low-frequency fluctuation between bipolar type I and type II in the depressive state

BACKGROUND

Bipolar disorder is a chronic and highly recurrent mental disorder that can be classified as bipolar type I (BD I) and bipolar type II (BD II). BD II is sometimes taken as a milder form of BD I or even doubted as an independent subtype. However, the fact that symptoms and severity differ in patients with BD I and BD II suggests different pathophysiologies and underlying neurobiological mechanisms. In this study, we aimed to explore the shared and unique functional abnormalities between subtypes.

METHODS

The dynamic amplitude of low-frequency fluctuation (dALFF) was performed to compare 31 patients with BD I, 32 with BD II, and 79 healthy controls (HCs). Global dALFF was calculated using sliding-window analysis. Group differences in dALFF among the 3 groups were compared using analysis of covariance (ANCOVA), with covariates of age, sex, years of education, and mean FD, and Bonferroni correction was applied for post hoc analysis. Pearson and Spearman's correlations were conducted between clusters with significant differences and clinical features in the BD I and BD II groups, after which false error rate (FDR) was used for correction.

RESULTS

We found a significant decrease in dALFF values in BD patients compared with HCs in the following brain regions: the bilateral-side inferior frontal gyrus (including the triangular, orbital, and opercular parts), inferior temporal gyrus, the medial part of the superior frontal gyrus, middle frontal gyrus, anterior cingulum, insula gyrus, lingual gyrus, calcarine gyrus, precuneus gyrus, cuneus gyrus, left-side precentral gyrus, postcentral gyrus, inferior parietal gyrus, superior temporal pole gyrus, middle temporal gyrus, middle occipital gyrus, superior occipital gyrus and right-side fusiform gyrus, parahippocampal gyrus, hippocampus, middle cingulum, orbital part of the medial frontal gyrus and superior frontal gyrus. Unique alterations in BD I were observed in the right-side supramarginal gyrus and postcentral gyrus. In addition, dALFF values in BD II were significantly higher than those in BD I in the right superior temporal gyrus and middle temporal gyrus. The variables of dALFF correlated with clinical characteristics differently according to the subtypes, but no correlations survived after FDR correction.

LIMITATIONS

Our study was cross-sectional. Most of our patients were on medication, and the sample was limited.

CONCLUSIONS

Our findings demonstrated neurobiological characteristics of BD subtypes, providing evidence for BD II as an independent existence, which could be the underlying explanation for the specific symptoms and/or severity and point to potential biomarkers for the differential diagnosis of bipolar subtypes.

Multigraph classification using learnable integration network with application to gender fingerprinting

Multigraphs with heterogeneous views present one of the most challenging obstacles to classification tasks due to their complexity. Several works based on feature selection have been recently proposed to disentangle the problem of multigraph heterogeneity. However, such techniques have major drawbacks. First, the bulk of such works lies in the vectorization and the flattening operations, failing to preserve and exploit the rich topological properties of the multigraph. Second, they learn the classification process in a dichotomized manner where the cascaded learning steps are pieced in together independently. Hence, such architectures are inherently agnostic to the cumulative estimation error from step to step. To overcome these drawbacks, we introduce MICNet (multigraph integration and classifier network), the first end-to-end graph neural network based model for multigraph classification. First, we learn a single-view graph representation of a heterogeneous multigraph using a GNN based integration model. The integration process in our model helps tease apart the heterogeneity across the different views of the multigraph by generating a subject-specific graph template while preserving its geometrical and topological properties conserving the node-wise information while reducing the size of the graph (i.e., number of views). Second, we classify each integrated template using a geometric deep learning block which enables us to grasp the salient graph features. We train, in end-to-end fashion, these two blocks using a single objective function to optimize the classification performance. We evaluate our MICNet in gender classification using brain multigraphs derived from different cortical measures. We demonstrate that our MICNet significantly outperformed its variants thereby showing its great potential in multigraph classification.

Correlations between cortical gyrification and schizophrenia symptoms with and without comorbid hostility symptoms

INTRODUCTION

Interest in identifying the clinical implications of the neuropathophysiological background of schizophrenia is rising, including changes in cortical gyrification that may be due to neurodevelopmental abnormalities. Inpatients with schizophrenia can show abnormal gyrification of cortical regions correlated with the symptom severity.

METHODS

Our study included 36 patients that suffered an acute episode of schizophrenia and have undergone structural magnetic resonance imaging (MRI) to calculate the local gyrification index (LGI).

RESULTS

In the whole sample, the severity of symptoms significantly correlated with higher LGI in different cortical areas, including bilateral frontal, cingulate, parietal, temporal cortices, and right occipital cortex. Among these areas, patients with low hostility symptoms (LHS) compared to patients with high hostility symptoms (HHS) showed significantly lower LGI related to the severity of symptoms in bilateral frontal and temporal lobes.

DISCUSSION

The severity of psychopathology correlated with higher LGI in large portions of the cerebral cortex, possibly expressing abnormal neural development in schizophrenia. These findings could pave the way for further studies and future tailored diagnostic and therapeutic strategies.

Heschl's gyrus duplication pattern and clinical characteristics in borderline personality disorder: A preliminary study

Inter-individual variations in the sulco-gyral pattern of Heschl's gyrus (HG) might contribute to emotional processing. However, it remains largely unknown whether borderline personality disorder (BPD) patients exhibit an altered HG gyrification pattern, compared with healthy individuals, and whether such a brain morphological feature, if present, might contribute to their clinical characteristics. The present study used magnetic resonance imaging to investigate the distribution of HG gyrification patterns (single or duplicated) and their relationship to clinical characteristics in teenage BPD patients with minimal treatment exposure. No significant difference was noted for the prevalence of HG patterns between 20 BPD and 20 healthy participants. However, the BPD participants with left duplicated HG were characterized by higher prevalence of comorbid disruptive behavior disorders, with higher externalizing score compared with those with left single HG. Our preliminary results suggest that neurodevelopmental pathology associated with gyral formation might be implicated in the neurobiology of early BPD, especially for emotional and behavioral control.

Structural correlates of sensorimotor dysfunction in heavy cannabis users

Sensorimotor dysfunction has been previously reported in persons with cannabis dependence. Such individuals can exhibit increased levels of neurological soft signs (NSS), particularly involving motor coordination and sensorimotor integration. Whether such abnormalities may also apply to non-dependent individuals with heavy cannabis use (HCU) is unknown, as much as the neural correlates underlying such deficits. In this study, we investigated associations between NSS and gray matter volume (GMV) in males with HCU and male controls. Twenty-four persons with HCU and 17 controls were examined using standardized assessment of NSS and structural magnetic resonance imaging (MRI) at 3 T. GMV was calculated using voxel-based morphometry algorithms provided by the Computational Anatomy Toolbox (CAT12). Individuals with HCU showed higher NSS total scores compared to controls. In particular, significant NSS-subdomain effects were found for "motor coordination" (MoCo), "complex motor tasks" (CoMT), and "hard signs" (HS) expression in HCU (p < 0.05, Bonferroni-corrected). Compared to controls, persons with HCU showed significant NSS/GMV interactions in putamen and inferior frontal cortex (MoCo), right cerebellum (CoMT) and middle and superior frontal cortices, and bilateral precentral cortex and thalamus (HS). In between-group analyses, individuals with HCU showed lower GMV in the right anterior orbital and precentral gyrus, as well as higher GMV in the right superior frontal gyrus and left supplementary motor cortex compared to controls. The data support the notion of abnormal sensorimotor performance associated with HCU. The data also provide a neuromechanistic understanding of such deficits, particularly with respect to aberrant cortical-thalamic-cerebellar-cortical circuit.

Looking at the bigger picture: Cortical volume, thickness and surface area characteristics in borderline personality disorder with and without posttraumatic stress disorder

Borderline personality disorder (BPD) is a severe psychiatric disorder accompanied by multiple comorbidities. Neuroimaging studies have identified structural abnormalities in BPD with most findings pointing to gray matter volume reductions in the fronto-limbic network, although results remain inconsistent. Similar alterations were found in posttraumatic stress disorder (PTSD), a common comorbidity of BPD. Only a small number of studies have investigated structural differences in BPD patients regarding comorbid PTSD specifically and studies conducting additional surface analyses are scarce. We investigated structural differences in women with BPD with and without PTSD and non-patient controls. Automated voxel-based and region-based volumetric analyses were applied. Additionally, four surface-based measures were analyzed: cortical thickness, gyrification index, fractal dimension, and sulcus depth. Analyses did not identify cortical volume alterations in the fronto-limbic network. Instead, hypergyrification was detected in the right superior parietal cortex in BPD patients compared to non-patient controls. No distinction was revealed between BPD patients with and without PTSD. These findings underline the importance of a holistic investigation examining volumetric and surface measures as these might enhance the understanding of structural alterations in BPD.

Brain gray matter structures associated with trait impulsivity: A systematic review and voxel-based meta-analysis

Trait impulsivity is a multifaceted personality characteristic that contributes to maladaptive life outcomes. Although a growing body of neuroimaging studies have investigated the structural correlates of trait impulsivity, the findings remain highly inconsistent and heterogeneous. Herein, we performed a systematic review to depict an integrated delineation of gray matter (GM) substrates of trait impulsivity and a meta‐analysis to examine concurrence across previous whole‐brain voxel‐based morphometry studies. The systematic review summarized the diverse findings in GM morphometry in the past literature, and the quantitative meta‐analysis revealed impulsivity‐related volumetric GM alterations in prefrontal, temporal, and parietal cortices. In addition, we identified the modulatory effects of age and gender in impulsivity‐GM volume associations. The present study advances understanding of brain GM morphometry features underlying trait impulsivity. The findings may have practical implications in the clinical diagnosis of and intervention for impulsivity‐related disorders.

The use of the orbitofrontal H-sulcus as a reference frame for value signals

Understanding the factors that drive organization and function of the brain is an enduring question in neuroscience. Using functional magnetic resonance imaging (fMRI), structure and function have been mapped in primary sensory cortices based on knowledge of the organizational principles that likely drive a given region (e.g., aspects of visual form in primary visual cortex and sound frequency in primary auditory cortex) and knowledge of underlying cytoarchitecture. The organizing principles of higher-order brain areas that encode more complex signals, such as the orbitofrontal cortex (OFC), are less well understood. One fundamental component that underlies the many functions of the OFC is the ability to compute the reward or value of a given object. There is evidence of variability in the spatial location of responses to specific categories of objects (or value of said objects) within the OFC, and several reference frames have been proposed to explain this variability, including topographic spatial gradients that correspond to axes of primary versus secondary rewards and positive versus negative reinforcers. One potentially useful structural morphometric reference frame in the OFC is the "H-sulcus," a pattern formed by medial orbital, lateral orbital and transverse orbital sulci. In 48 human subjects, we use a structural morphometric tracing procedure to localize functional activation along the H-sulcus for face and food stimuli. We report the novel finding that food-selective responses are consistently found within the caudal portion of the medial orbital sulcus, but no consistency within the H-sulcus for response to face stimuli. These results suggest that sulcogyral anatomy of the H-sulcus may be an important morphological metric that contributes to the organizing principles of the OFC response to certain stimulus categories, including food.

Cortical Contributions to Distinct Symptom Dimensions of Catatonia

Catatonia is a central aspect of schizophrenia spectrum disorders (SSD) and most likely associated with abnormalities in affective, motor, and sensorimotor brain regions. However, contributions of different cortical features to the pathophysiology of catatonia in SSD are poorly understood. Here, T1-weighted structural magnetic resonance imaging data at 3 T were obtained from 56 right-handed patients with SSD. Using FreeSurfer version 6.0, we calculated cortical thickness, area, and local gyrification index (LGI). Catatonic symptoms were examined on the Northoff catatonia rating scale (NCRS). Patients with catatonia (NCRS total score ≥3; n = 25) showed reduced surface area in the parietal and medial orbitofrontal gyrus and LGI in the temporal gyrus (P < .05, corrected for cluster-wise probability [CWP]) as well as hypergyrification in rostral cingulate and medial orbitofrontal gyrus when compared with patients without catatonia (n = 22; P < .05, corrected for CWP). Following a dimensional approach, a negative association between NCRS motor and behavior scores and cortical thickness in superior frontal, insular, and precentral cortex was found (34 patients with at least 1 motor and at least 1 other affective or behavioral symptom; P < .05, corrected for CWP). Positive associations were found between NCRS motor and behavior scores and surface area and LGI in superior frontal, posterior cingulate, precentral, and pericalcarine gyrus (P < .05, corrected for CWP). The data support the notion that cortical features of distinct evolutionary and genetic origin differently contribute to catatonia in SSD. Catatonia in SSD may be essentially driven by cortex variations in frontoparietal regions including regions implicated in the coordination and goal-orientation of behavior.

Brain structure and trait impulsivity: A comparative VBM study contrasting neural correlates of traditional and alternative concepts in healthy subjects

Impulsivity as a trait modulates a range of cognitive functions, e.g. planning, decision-making, or response inhibition. Recent behavioural and psychometric findings challenge both the neurobiological models as well as the conceptualisation of psychometric measures of impulsivity. In the present study, we aimed to test the association of brain structure with the Barratt Impulsiveness Scale (BIS-11), a commonly applied self-rating instrument for impulsivity, using both the classical three-factor-model for impulsive behaviour (motor (IM), attentional (IA) and non-planning impulsivity (INP)), as well as the recently proposed alternative model contrasting inability to wait for reward (IWR) as an index of impulsive choice and rapid response style (RRS) as an index of impulsive action. We analysed brain structural data in a community sample of 85 healthy individuals, who completed the BIS-11, using voxel-based morphometry (CAT12: Computational Anatomy Toolbox 12). Regional volumes were correlated with the three traditional BIS-11 subscales, as well as IWR and RRS. BIS-11 total score was positively correlated with right inferior parietal, postcentral, and supramarginal grey matter (p < 0.05, FWE cluster-level corrected). Attentional impulsivity (IA) was also positively correlated with right inferior and superior parietal and supramarginal gyri. Comparison of the other scales did show some divergence, but most correlations did not survive correction for multiple comparisons. Our findings suggest that difference facets of trait impulsivity might be related to different brain areas, and might thus dissociate along distinct but overlapping neural networks. In contrast to lesion or patient studies, these analyses delineate physiological variance, and can thus help to conceptualise network models in the absence of pathology.

Correlation of impulsivity with self-harm and suicidal attempt: a community study of adolescents in Taiwan

OBJECTIVES

The aim of this study was to investigate differences and similarities in risk factors for deliberate self-harm (DSH) and suicidal attempt (SA), and the role of impulsivity among a group of community adolescents.

SETTING

This is a cross-sectional study conducted at high schools in Northern Taiwan.

DATA AND PARTICIPANTS

We recruited grade 1 students from 14 high schools. A total of 5879 participants (mean age 16.02 years, female adolescents: 57.7%) completed the online assessment.

OUTCOME MEASURES

Participants completed online questionnaires about sociodemographic data, suicidality, history of DSH and SA, depressed mood, self-esteem, social support, family discord, impulsivity (Barratt Impulsiveness Scale Version 11 (BIS-11)) and the use of alcohol, tobacco and illicit drugs. A subsample was interviewed about lifetime SA, and the results were compared with those from the online questionnaires.

RESULTS

In our sample, 25% of the students had lifetime DSH and 3.5% had lifetime SA. Two hundred and seventy-two students received face-to-face interviews. The concordance between the online questionnaires and interviews in terms of ascertaining cases of SA was moderate (concordance rate 82.76%; kappa value 0.59). Similar risk factors for DSH/SA among the whole sample included female gender, lower academic performance, depression, substance use (tobacco and alcohol) and low self-esteem. The BIS-11 score was correlated with DSH. Factor 3 score of the BIS-11 (novelty seeking) was correlated with DSH in both boys and girls, whereas factor 2 score (lack of self-control) was correlated with SA in boys. Social support was a protective factor against SA among the female adolescents. Gender modulated the association of impulsivity and DSH/SA. Associations between impulsivity and DSH and SA were particularly strong among boys.

CONCLUSIONS

Risk factors for DSH and SA were similar, but not identical. Early identification of those at risk and appropriate interventions may be helpful.

Intrinsic Network Connectivity Patterns Underlying Specific Dimensions of Impulsiveness in Healthy Young Adults

Impulsiveness is a central human personality trait and of high relevance for the development of several mental disorders. Impulsiveness is a multidimensional construct, yet little is known about dimension-specific neural correlates. Here, we address the question whether motor, attentional and non-planning components, as measured by the Barratt Impulsiveness Scale (BIS-11), are associated with distinct or overlapping neural network activity. In this study, we investigated brain activity at rest and its relationship to distinct dimensions of impulsiveness in 30 healthy young adults (m/f = 13/17; age mean/SD = 26.4/2.6 years) using resting-state functional magnetic resonance imaging at 3T. A spatial independent component analysis and a multivariate model selection strategy were used to identify systems loading on distinct impulsivity domains. We first identified eight networks for which we had a-priori hypotheses. These networks included basal ganglia, cortical motor, cingulate and lateral prefrontal systems. From the eight networks, three were associated with impulsiveness measures (p < 0.05, FDR corrected). There were significant relationships between right frontoparietal network function and all three BIS domains. Striatal and midcingulate network activity was associated with motor impulsiveness only. Within the networks regionally confined effects of age and gender were found. These data suggest distinct and overlapping patterns of neural activity underlying specific dimensions of impulsiveness. Motor impulsiveness appears to be specifically related to striatal and midcingulate network activity, in contrast to a domain-unspecific right frontoparietal system. Effects of age and gender have to be considered in young healthy samples.

Cortical features of distinct developmental trajectories in patients with delusional infestation

BACKGROUND

Although there is strong neuroimaging evidence that cortical alterations are a core feature of schizophrenia spectrum disorders, it still remains unclear to what extent such abnormalities occur in monothematic delusional disorders. In individuals with delusional infestation (DI), the delusional belief to be infested with pathogens, previous structural MRI studies have shown prefrontal, temporal, parietal, insular, thalamic and striatal gray matter volume changes. Differential contributions of cortical features of evolutionary and genetic origin (such as cortical thickness, area and folding) which may distinctly contribute to DI pathophysiology are unclear at present.

METHODS

In this study, 18 patients with DI and 20 healthy controls (HC) underwent MRI scanning at 1.0T. Using surface-based analyses we calculated cortical thickness, surface area and local gyrification index (LGI). Whole-brain differences between patients and controls were investigated.

RESULTS

Surface analyses revealed frontoparietal patterns exhibiting altered cortical thickness, surface area and LGI in DI patients compared to controls. Higher cortical thickness was found in the right medial orbitofrontal cortex (p<0.05, cluster-wise probability [CWP] corrected). Smaller surface area in patients was found in the left inferior temporal gyrus, the precuneus, the pars orbitalis of the right frontal gyrus, and the lingual gyrus (p<0.05, CWP corr.). Lower LGI was found in the left postcentral, bilateral precentral, right middle temporal, inferior parietal, and superior parietal gyri (p<0.01, CWP corr.).

CONCLUSION

This study lends further support to the hypothesis that cortical features of distinct evolutionary and genetic origin differently contribute to the pathogenesis of delusional disorders. Regions in which atrophy was observed are part of neural circuits associated with perception, visuospatial control and self-awareness. The data are in line with the notion of a content-specific neural signature of DI.