New resting-state fMRI related studies at PubMed

Altered Fractional Amplitude of Low-Frequency Fluctuation in Anxious Parkinson's Disease

Sat, 01/21/2023 - 11:00

Brain Sci. 2023 Jan 2;13(1):87. doi: 10.3390/brainsci13010087.

ABSTRACT

OBJECTIVE: Anxiety symptoms are persistent in Parkinson's disease (PD), but the underlying neural substrates are still unclear. In the current study, we aimed to explore the underlying neural mechanisms in PD patients with anxiety symptoms.

METHODS: 42 PD-A patients, 41 PD patients without anxiety symptoms (PD-NA), and 40 healthy controls (HCs) were recruited in the present study. All the subjects performed 3.0T fMRI scans. The fractional amplitude of low-frequency fluctuation (fALFF) analysis was used to investigate the alterations in neural activity among the three groups. A Pearson correlation analysis was performed between the altered fALFF value of the PD-A group and anxiety scores.

RESULTS: Compared with HCs, PD-A patients had higher fALFF values in the left cerebellum, cerebellum posterior lobe, bilateral temporal cortex, and brainstem and lower fALFF values in the bilateral inferior gyrus, bilateral basal ganglia areas, and left inferior parietal lobule. Moreover, between the two PD groups, PD-A patients showed higher fALFF values in the right precuneus and lower fALFF values in the bilateral inferior gyrus, bilateral basal ganglia areas, left inferior parietal lobule, and left occipital lobe. Furthermore, Pearson's correlation analysis demonstrated that the right precuneus and left caudate were correlated with the Hamilton Anxiety Rating Scale scores.

CONCLUSION: Our study found that anxiety symptoms in PD patients may be related to alterations of neurological activities in multiple brain regions. Furthermore, these may be critical radiological biomarkers for PD-A patients. Therefore, these findings can improve our understanding of the pathophysiological mechanisms underlying PD-A.

PMID:36672068 | DOI:10.3390/brainsci13010087

Resting-State Brain Activity Dysfunctions in Schizophrenia and Their Associations with Negative Symptom Domains: An fMRI Study

Sat, 01/21/2023 - 11:00

Brain Sci. 2023 Jan 1;13(1):83. doi: 10.3390/brainsci13010083.

ABSTRACT

The aim of the present study was to examine the neurobiological correlates of the two negative symptom domains of schizophrenia, the Motivational Deficit domain (including avolition, anhedonia, and asociality) and the Expressive Deficit domain (including blunted affect and alogia), focusing on brain areas that are most commonly found to be associated with negative symptoms in previous literature. Resting-state (rs) fMRI data were analyzed in 62 subjects affected by schizophrenia (SZs) and 46 healthy controls (HCs). The SZs, compared to the HCs, showed higher rs brain activity in the right inferior parietal lobule and the right temporoparietal junction, and lower rs brain activity in the right dorsolateral prefrontal cortex, the bilateral anterior dorsal cingulate cortex, and the ventral and dorsal caudate. Furthermore, in the SZs, the rs brain activity in the left orbitofrontal cortex correlated with negative symptoms (r = -0.436, p = 0.006), in particular with the Motivational Deficit domain (r = -0.424, p = 0.002), even after controlling for confounding factors. The left ventral caudate correlated with negative symptoms (r = -0.407, p = 0.003), especially with the Expressive Deficit domain (r = -0.401, p = 0.003); however, these results seemed to be affected by confounding factors. In line with the literature, our results demonstrated that the two negative symptom domains might be underpinned by different neurobiological mechanisms.

PMID:36672064 | DOI:10.3390/brainsci13010083

Functional Coherence in Intrinsic Frontal Executive Networks Predicts Cognitive Impairments in Alcohol Use Disorder

Sat, 01/21/2023 - 11:00

Brain Sci. 2022 Dec 26;13(1):45. doi: 10.3390/brainsci13010045.

ABSTRACT

Growing evidence highlights the potential of innovative rehabilitative interventions such as cognitive remediation and neuromodulation, aimed at reducing relapses in Alcohol Use Disorder (AUD). Enhancing their effectiveness requires a thorough description of the neural correlates of cognitive alterations in AUD. Past related attempts, however, were limited by the focus on selected neuro-cognitive variables. We aimed to fill this gap by combining, in 22 AUD patients and 18 controls, an extensive neuro-cognitive evaluation and metrics of intrinsic connectivity as highlighted by resting-state brain activity. We addressed an inherent property of intrinsic activity such as intra-network coherence, the temporal correlation of the slow synchronous fluctuations within resting-state networks, representing an early biomarker of alterations in the functional brain architecture underlying cognitive functioning. AUD patients displayed executive impairments involving working-memory, attention and visuomotor speed, reflecting abnormal coherence of activity and grey matter atrophy within default mode, in addition to the attentional and the executive networks. The stronger relationship between fronto-lateral coherent activity and executive performance in patients than controls highlighted possible compensatory mechanisms counterbalancing the decreased functionality of networks driving the switch from automatic to controlled behavior. These results provide novel insights into AUD patients' cognitive impairments, their neural bases, and possible targets of rehabilitative interventions.

PMID:36672027 | DOI:10.3390/brainsci13010045

Effects of Physiological Signal Removal on Resting-State Functional MRI Metrics

Sat, 01/21/2023 - 11:00

Brain Sci. 2022 Dec 20;13(1):8. doi: 10.3390/brainsci13010008.

ABSTRACT

Resting-state fMRIs (rs-fMRIs) have been widely used for investigation of diverse brain functions, including brain cognition. The rs-fMRI has easily elucidated rs-fMRI metrics, such as the fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), voxel-mirrored homotopic connectivity (VMHC), and degree centrality (DC). To increase the applicability of these metrics, higher reliability is required by reducing confounders that are not related to the functional connectivity signal. Many previous studies already demonstrated the effects of physiological artifact removal from rs-fMRI data, but few have evaluated the effect on rs-fMRI metrics. In this study, we examined the effect of physiological noise correction on the most common rs-fMRI metrics. We calculated the intraclass correlation coefficient of repeated measurements on parcellated brain areas by applying physiological noise correction based on the RETROICOR method. Then, we evaluated the correction effect for five rs-fMRI metrics for the whole brain: FC, fALFF, ReHo, VMHC, and DC. The correction effect depended not only on the brain region, but also on the metric. Among the five metrics, the reliability in terms of the mean value of all ROIs was significantly improved for FC, but it deteriorated for fALFF, with no significant differences for ReHo, VMHC, and DC. Therefore, the decision on whether to perform the physiological correction should be based on the type of metric used.

PMID:36671990 | DOI:10.3390/brainsci13010008

Dysfunction of the Lenticular Nucleus Is Associated with Dystonia in Wilson's Disease

Sat, 01/21/2023 - 11:00

Brain Sci. 2022 Dec 20;13(1):7. doi: 10.3390/brainsci13010007.

ABSTRACT

Dysfunction of the lenticular nucleus is thought to contribute to neurological symptoms in Wilson's disease (WD). However, very little is known about whether and how the lenticular nucleus influences dystonia by interacting with the cerebral cortex and cerebellum. To solve this problem, we recruited 37 WD patients (20 men; age, 23.95 ± 6.95 years; age range, 12-37 years) and 37 age- and sex-matched healthy controls (HCs) (25 men; age, 25.19 ± 1.88 years; age range, 20-30 years), and each subject underwent resting-state functional magnetic resonance imaging (RS-fMRI) scans. The muscle biomechanical parameters and Unified Wilson Disease Rating Scale (UWDRS) were used to evaluate the level of dystonia and clinical representations, respectively. The lenticular nucleus, including the putamen and globus pallidus, was divided into 12 subregions according to dorsal, ventral, anterior and posterior localization and seed-based functional connectivity (FC) was calculated for each subregion. The relationships between FC changes in the lenticular nucleus with muscle tension levels and clinical representations were further investigated by correlation analysis. Dystonia was diagnosed by comparing all WD muscle biomechanical parameters with healthy controls (HCs). Compared with HCs, FC decreased from all subregions in the putamen except the right ventral posterior part to the middle cingulate cortex (MCC) and decreased FC of all subregions in the putamen except the left ventral anterior part to the cerebellum was observed in patients with WD. Patients with WD also showed decreased FC of the left globus pallidus primarily distributed in the MCC and cerebellum and illustrated decreased FC from the right globus pallidus to the cerebellum. FC from the putamen to the MCC was significantly correlated with psychiatric symptoms. FC from the putamen to the cerebellum was significantly correlated with muscle tension and neurological symptoms. Additionally, the FC from the globus pallidus to the cerebellum was also associated with muscle tension. Together, these findings highlight that lenticular nucleus-cerebellum circuits may serve as neural biomarkers of dystonia and provide implications for the neural mechanisms underlying dystonia in WD.

PMID:36671989 | DOI:10.3390/brainsci13010007

Understanding the Role of Connectivity Dynamics of Resting-State Functional MRI in the Diagnosis of Autism Spectrum Disorder: A Comprehensive Study

Sat, 01/21/2023 - 11:00

Bioengineering (Basel). 2023 Jan 2;10(1):56. doi: 10.3390/bioengineering10010056.

ABSTRACT

In addition to the standard observational assessment for autism spectrum disorder (ASD), recent advancements in neuroimaging and machine learning (ML) suggest a rapid and objective alternative using brain imaging. This work presents a pipelined framework, using functional magnetic resonance imaging (fMRI) that allows not only an accurate ASD diagnosis but also the identification of the brain regions contributing to the diagnosis decision. The proposed framework includes several processing stages: preprocessing, brain parcellation, feature representation, feature selection, and ML classification. For feature representation, the proposed framework uses both a conventional feature representation and a novel dynamic connectivity representation to assist in the accurate classification of an autistic individual. Based on a large publicly available dataset, this extensive research highlights different decisions along the proposed pipeline and their impact on diagnostic accuracy. A large publicly available dataset of 884 subjects from the Autism Brain Imaging Data Exchange I (ABIDE-I) initiative is used to validate our proposed framework, achieving a global balanced accuracy of 98.8% with five-fold cross-validation and proving the potential of the proposed feature representation. As a result of this comprehensive study, we achieve state-of-the-art accuracy, confirming the benefits of the proposed feature representation and feature engineering in extracting useful information as well as the potential benefits of utilizing ML and neuroimaging in the diagnosis and understanding of autism.

PMID:36671628 | DOI:10.3390/bioengineering10010056

Sleep strengthens resting-state functional communication between brain areas involved in the consolidation of problem-solving skills

Fri, 01/20/2023 - 11:00

Learn Mem. 2023 Jan 20;30(1):25-35. doi: 10.1101/lm.053638.122. Print 2023 Jan.

ABSTRACT

Sleep consolidates procedural memory for motor skills, and this process is associated with strengthened functional connectivity in hippocampal-striatal-cortical areas. It is unknown whether similar processes occur for procedural memory that requires cognitive strategies needed for problem-solving. It is also unclear whether a full night of sleep is indeed necessary for consolidation to occur, compared with a daytime nap. We examined how resting-state functional connectivity within the hippocampal-striatal-cortical network differs after offline consolidation intervals of sleep, nap, or wake. Resting-state fMRI data were acquired immediately before and after training on a procedural problem-solving task that requires the acquisition of a novel cognitive strategy and immediately prior to the retest period (i.e., following the consolidation interval). ROI to ROI and seed to whole-brain functional connectivity analyses both specifically and consistently demonstrated strengthened hippocampal-prefrontal functional connectivity following a period of sleep versus wake. These results were associated with task-related gains in behavioral performance. Changes in functional communication were also observed between groups using the striatum as a seed. Here, we demonstrate that at the behavioral level, procedural strategies benefit from both a nap and a night of sleep. However, a full night of sleep is associated with enhanced functional communication between regions that support problem-solving skills.

PMID:36669853 | DOI:10.1101/lm.053638.122

Amplitude of low-frequency fluctuation after taste exposure revealed by resting-state fMRI

Fri, 01/20/2023 - 11:00

Physiol Behav. 2023 Jan 17:114091. doi: 10.1016/j.physbeh.2023.114091. Online ahead of print.

ABSTRACT

Taste perception has been deeply explored from the behavioural level to delineating neural mechanisms. However, most previous studies about the neural underpinnings of taste perception have focused on task-related brain activation. Notably, evidence indicates that task-induced brain activation often involves interference from irrelevant task materials and only accounts for a small fraction of the brain's energy consumption. Investigation of the resting-state spontaneous brain activity would bring us a comprehensive understanding of the neural mechanism of taste perception. Here we acquired resting-state functional magnetic resonance imaging (rs-fMRI) data from twenty-two participants immediately after they received sweet, sour and tasteless gustatory stimulation. Our results showed that, in contrast to the tasteless condition, the sour exposure induced decreased amplitude of low-frequency fluctuation (ALFF) in the somatosensory cortex in the left post-central gyrus, and the sweet exposure led to increased ALFF in the bilateral putamen involved in reward processing. Moreover, in contrast to the sweet stimulation condition, the sour stimulation condition showed increased ALFF in the right superior frontal gyrus, which has been linked to functioning in high-order cognitive control. Altogether, our data indicate that taste exposure may affect the spontaneous functional activity in brain regions, including the somatosensory areas, reward processing areas and high-order cognitive functioning areas. Our findings may contribute to a further understanding the neural network and mechanisms after taste exposure.

PMID:36669692 | DOI:10.1016/j.physbeh.2023.114091

Altered brain connectivity in hyperkinetic movement disorders: A review of resting-state fMRI

Fri, 01/20/2023 - 11:00

Neuroimage Clin. 2022 Dec 24;37:103302. doi: 10.1016/j.nicl.2022.103302. Online ahead of print.

ABSTRACT

BACKGROUND: Hyperkinetic movement disorders (HMD) manifest as abnormal and uncontrollable movements. Despite reported involvement of several neural circuits, exact connectivity profiles remain elusive.

OBJECTIVES: Providing a comprehensive literature review of resting-state brain connectivity alterations using resting-state fMRI (rs-fMRI). We additionally discuss alterations from the perspective of brain networks, as well as correlations between connectivity and clinical measures.

METHODS: A systematic review was performed according to PRISMA guidelines and searching PubMed until October 2022. Rs-fMRI studies addressing ataxia, chorea, dystonia, myoclonus, tics, tremor, and functional movement disorders (FMD) were included. The standardized mean difference was used to summarize findings per region in the Automated Anatomical Labeling atlas for each phenotype. Furthermore, the activation likelihood estimation meta-analytic method was used to analyze convergence of significant between-group differences per phenotype. Finally, we conducted hierarchical cluster analysis to provide additional insights into commonalities and differences across HMD phenotypes.

RESULTS: Most articles concerned tremor (51), followed by dystonia (46), tics (19), chorea (12), myoclonus (11), FMD (11), and ataxia (8). Altered resting-state connectivity was found in several brain regions: in ataxia mainly cerebellar areas; for chorea, the caudate nucleus; for dystonia, sensorimotor and basal ganglia regions; for myoclonus, the thalamus and cingulate cortex; in tics, the basal ganglia, cerebellum, insula, and frontal cortex; for tremor, the cerebello-thalamo-cortical circuit; finally, in FMD, frontal, parietal, and cerebellar regions. Both decreased and increased connectivity were found for all HMD. Significant spatial convergence was found for dystonia, FMD, myoclonus, and tremor. Correlations between clinical measures and resting-state connectivity were frequently described.

CONCLUSION: Key brain regions contributing to functional connectivity changes across HMD often overlap. Possible increases and decreases of functional connections of a specific region emphasize that HMD should be viewed as a network disorder. Despite the complex interplay of physiological and methodological factors, this review serves to gain insight in brain connectivity profiles across HMD phenotypes.

PMID:36669351 | DOI:10.1016/j.nicl.2022.103302

Cerebellar network changes in depressed patients with and without autism spectrum disorder: A case-control study

Fri, 01/20/2023 - 11:00

Psychiatry Res Neuroimaging. 2023 Jan 16;329:111596. doi: 10.1016/j.pscychresns.2023.111596. Online ahead of print.

ABSTRACT

Pathophysiological difference of depression in patients with and without autistic spectrum disorder (ASD) has not been investigated previously. Therefore, we sought to determine whether there were differences between non-ASD and ASD groups on resting-state functional magnetic resonance imaging (rs-fMRI) in patients with depression. We performed 3T MRI under resting state in 8 patients with depression and ASD and 12 patients with depression but without ASD. The ASD group showed increased functional connectivity in the cerebellar network of the left posterior inferior temporal gyrus and anterior cerebellar lobes compared to the non-ASD group in an analysis of covariance. Adding antipsychotics, antidepressants, benzodiazepines, nonbenzodiazepines, anxiolytics, hypnotics, or age as covariates showed a similar increase in functional connectivity. Thus, this study found that depressive patients with ASD had increased functional connectivity in the cerebellar network. Our findings suggest that fMRI may be able to evaluate differences in depressed patients with and without ASD.

PMID:36669239 | DOI:10.1016/j.pscychresns.2023.111596

The continuum of attention dysfunction: Evidence from dynamic functional network connectivity analysis in neurotypical adolescents

Fri, 01/20/2023 - 11:00

PLoS One. 2023 Jan 20;18(1):e0279260. doi: 10.1371/journal.pone.0279260. eCollection 2023.

ABSTRACT

The question of whether attention-related disorders such as attention-deficit/hyperactivity disorder (ADHD) are best understood as clinical categories or as extreme ends of a spectrum is an ongoing debate. Assessing individuals with varying degrees of attention problems and utilizing novel methodologies to assess relationships between attention and brain activity may provide key information to support the spectrum hypothesis. We scanned 91 neurotypical adolescents during rest using functional magnetic resonance imaging. We conducted static and dynamic functional network connectivity (FNC) analysis and correlated findings to behavioral metrics of ADHD, attention problems, and impulsivity. We found that dynamic FNC analysis detects significant differences in large-scale neural connectivity as a function of individual differences in attention and impulsivity that are obscured in static analysis. We show ADHD manifestations and attention problems are associated with diminished Salience Network-centered FNC and that ADHD manifestations and impulsivity are associated with prolonged periods of dynamically hyperconnected states. Importantly, our meta-state analysis results reveal a relationship between ADHD manifestations and exhibiting variable and volatile dynamic behavior such as changing meta-states more often and traveling over a greater dynamic range. These findings in non-clinical adolescents provide support for the continuum model of attention disorders.

PMID:36662797 | DOI:10.1371/journal.pone.0279260

Effect of regional intrinsic activity following two kinds of theta burst stimulation on precuneus

Fri, 01/20/2023 - 11:00

Hum Brain Mapp. 2023 Jan 20. doi: 10.1002/hbm.26207. Online ahead of print.

ABSTRACT

Theta burst stimulation (TBS) has been widely used in the treatment of mental disorders, but the cerebral functional difference between intermittent TBS (iTBS) and continuous TBS (cTBS) after one single session of stimulation is not clear. Here we applied resting-state functional magnetic resonance imaging (RS-FMRI) to evaluate the alterations in intrinsic brain activity after iTBS and cTBS in the precuneus. We recruited 32 healthy young adults and performed a single session each of iTBS and cTBS at a 1-week interval. RS-fMRI was collected at baseline before and immediately after the stimulation. Parameters for regional brain activity (ALFF/fALFF/ReHo) and functional connectivity (FC) with the stimulated site of the precuneus after iTBS and cTBS were calculated and compared between each stimulation using a paired t-test. Correlation analysis among those parameters was calculated to explore whether changes in functional connectivity were associated with local spontaneous activity. After iTBS stimulation, fALFF increased in the bilateral precuneus, while fALFF decreased in the bilateral middle temporal gyrus. Reductions in precuneus FC were found in the bilateral cuneus, superior occipital gyrus, superior temporal gyrus, precentral gyrus, and postcentral gyrus, which correlated with regional activity. After cTBS, fALFF decreased in the bilateral insula, and precuneus FC was decreased in the bilateral inferior occipital gyrus and increased in the thalamus. In the current study, we observed that one session of iTBS or cTBS could cause inhibitory effects in remote brain regions, but only iTBS caused significant local activation in the target region.

PMID:36661276 | DOI:10.1002/hbm.26207

Functional connectome automatically differentiates multiple system atrophy (parkinsonian type) from idiopathic Parkinson's disease at early stages

Fri, 01/20/2023 - 11:00

Hum Brain Mapp. 2023 Jan 20. doi: 10.1002/hbm.26201. Online ahead of print.

ABSTRACT

Differentiating the parkinsonian variant of multiple system atrophy (MSA-P) from idiopathic Parkinson's disease (IPD) is challenging, especially in the early stages. This study aimed to investigate differences and similarities in the brain functional connectomes of IPD and MSA-P patients and use machine learning methods to explore the diagnostic utility of these features. Resting-state fMRI data were acquired from 88 healthy controls, 76 MSA-P patients, and 53 IPD patients using a 3.0 T scanner. The whole-brain functional connectome was constructed by thresholding the Pearson correlation matrices of 116 regions, and topological properties were evaluated through graph theory approaches. Connectome measurements were used as features in machine learning models (random forest [RF]/logistic regression [LR]/support vector machine) to distinguish IPD and MSA-P patients. Regarding graph metrics, early IPD and MSA-P patients shared network topological properties. Both patient groups showed functional connectivity disruptions within the cerebellum-basal ganglia-cortical network, but these disconnections were mainly in the cortico-thalamo-cerebellar circuits in MSA-P patients and the basal ganglia-thalamo-cortical circuits in IPD patients. Among the connectome parameters, t tests combined with the RF method identified 15 features, from which the LR classifier achieved the best diagnostic performance on the validation set (accuracy = 92.31%, sensitivity = 90.91%, specificity = 93.33%, area under the receiver operating characteristic curve = 0.89). MSA-P and IPD patients show similar whole-brain network topological alterations. MSA-P primarily affects cerebellar nodes, and IPD primarily affects basal ganglia nodes; both conditions disrupt the cerebellum-basal ganglia-cortical network. Moreover, functional connectome parameters showed outstanding value in the differential diagnosis of early MSA-P and IPD.

PMID:36661217 | DOI:10.1002/hbm.26201

Evaluate the efficacy and reliability of functional gradients in within-subject designs

Fri, 01/20/2023 - 11:00

Hum Brain Mapp. 2023 Jan 20. doi: 10.1002/hbm.26213. Online ahead of print.

ABSTRACT

The cerebral cortex is characterized as the integration of distinct functional principles that correspond to basic primary functions, such as vision and movement, and domain-general functions, such as attention and cognition. Diffusion embedding approach is a novel tool to describe transitions between different functional principles, and has been successively applied to investigate pathological conditions in between-group designs. What still lacking and urgently needed is the efficacy of this method to differentiate within-subject circumstances. In this study, we applied the diffusion embedding to eyes closed (EC) and eyes on (EO) resting-state conditions from 145 participants. We found significantly lower within-network dispersion of visual network (VN) (p = 7.3 × 10-4 ) as well as sensorimotor network (SMN) (p = 1 × 10-5 ) and between-network dispersion of VN (p = 2.3 × 10-4 ) under EC than EO, while frontoparietal network (p = 9.2 × 10-4 ) showed significantly higher between-network dispersion during EC than EO. Test-retest reliability analysis further displayed fair reliability (intraclass correlation coefficient [ICC] < 0.4) of the network dispersions (mean ICC = 0.116 ± 0.143 [standard deviation]) except for the within-network dispersion of SMN under EO (ICC = 0.407). And the reliability under EO was higher but not significantly higher than reliability under EC. Our study demonstrated that the diffusion embedding approach that shows fair reliability is capable of distinguishing EC and EO resting-state conditions, such that this method could be generalized to other within-subject designs.

PMID:36661209 | DOI:10.1002/hbm.26213

Multimodal Brain Signal Complexity Predicts Human Intelligence

Thu, 01/19/2023 - 11:00

eNeuro. 2023 Jan 19:ENEURO.0345-22.2022. doi: 10.1523/ENEURO.0345-22.2022. Online ahead of print.

ABSTRACT

Spontaneous brain activity builds the foundation for human cognitive processing during external demands. Neuroimaging studies based on functional magnetic resonance imaging (fMRI) identified specific characteristics of spontaneous (intrinsic) brain dynamics to be associated with individual differences in general cognitive ability, i.e., intelligence. However, fMRI research is inherently limited by low temporal resolution, thus, preventing conclusions about neural fluctuations within the range of milliseconds. Here, we used resting-state electroencephalographical (EEG) recordings from 144 healthy adults to test whether individual differences in intelligence (Raven's Advanced Progressive Matrices scores) can be predicted from the complexity of temporally highly resolved intrinsic brain signals. We compared different operationalizations of brain signal complexity (multiscale entropy, Shannon entropy, Fuzzy entropy, and specific characteristics of microstates) regarding their relation to intelligence. The results indicate that associations between brain signal complexity measures and intelligence are of small effect sizes (r ∼ .20) and vary across different spatial and temporal scales. Specifically, higher intelligence scores were associated with lower complexity in local aspects of neural processing, and less activity in task-negative brain regions belonging to the default-mode network. Finally, we combined multiple measures of brain signal complexity to show that individual intelligence scores can be significantly predicted with a multimodal model within the sample (10-fold cross-validation) as well as in an independent sample (external replication, N = 57). In sum, our results highlight the temporal and spatial dependency of associations between intelligence and intrinsic brain dynamics, proposing multimodal approaches as promising means for future neuroscientific research on complex human traits.Significance StatementSpontaneous brain activity builds the foundation for intelligent processing - the ability of humans to adapt to various cognitive demands. Using resting-state EEG, we extracted multiple aspects of temporally highly resolved intrinsic brain dynamics to investigate their relationship with individual differences in intelligence. Single associations were of small effect sizes and varied critically across spatial and temporal scales. However, combining multiple measures in a multimodal cross-validated prediction model, allows to significantly predict individual intelligence scores in unseen participants. Our study adds to a growing body of research suggesting that observable associations between complex human traits and neural parameters might be rather small and proposes multimodal prediction approaches as promising tool to derive robust brain-behavior relations despite limited sample sizes.

PMID:36657966 | DOI:10.1523/ENEURO.0345-22.2022

Connectome-based predictive modeling predicts paranoid ideation in young men with paranoid personality disorder: a resting-state functional magnetic resonance imaging study

Thu, 01/19/2023 - 11:00

Cereb Cortex. 2023 Jan 19:bhac531. doi: 10.1093/cercor/bhac531. Online ahead of print.

ABSTRACT

Paranoid personality disorder (PPD), a mental disorder that affects interpersonal relationships and work, is frequently neglected during diagnosis and evaluation at the individual-level. This preliminary study aimed to investigate whether connectome-based predictive modeling (CPM) can predict paranoia scores of young men with PPD using whole-brain resting-state functional connectivity (rs-FC). College students with paranoid tendencies were screened using paranoia scores ≥60 derived from the Minnesota Multiphasic Personality Inventory; 18 participants were ultimately diagnosed with PPD according to the Diagnostic and Statistical Manual of Mental Disorders and subsequently underwent resting-state functional magnetic resonance imaging. Whole-brain rs-FC was constructed, and the ability of this rs-FC to predict paranoia scores was evaluated using CPM. The significance of the models was assessed using permutation tests. The model constructed based on the negative prediction network involving the limbic system-temporal lobe was observed to have significant predictive ability for paranoia scores, whereas the model constructed using the positive and combined prediction network had no significant predictive ability. In conclusion, using CPM, whole-brain rs-FC predicted the paranoia score of patients with PPD. The limbic system-temporal lobe FC pattern is expected to become an important neurological marker for evaluating paranoid ideation.

PMID:36657794 | DOI:10.1093/cercor/bhac531

Lower cerebello-cortical functional connectivity in veterans with reactive aggression symptoms: A pilot study

Thu, 01/19/2023 - 11:00

J Psychiatr Res. 2023 Jan 11;159:42-49. doi: 10.1016/j.jpsychires.2023.01.023. Online ahead of print.

ABSTRACT

A significant number of veterans experience irritability and aggression symptoms as a result of being exposed to extremely stressful and life-threatening situations. In addition to the well-established involvement of the brain's cortico-subcortical circuit in aggression-related behaviours, a role of the deep cerebellar nuclei (DCN) in reactive aggression has been suggested. In the present study, seed-based resting-state functional connectivity between the DCN and cortico-subcortical areas was explored in veterans with and without reactive aggression symptoms. Nineteen male veterans with reactive aggression symptoms and twenty-two control veterans without reactive aggression symptoms underwent 3T resting-state functional MRI scans. Region-of-interest (ROI) analyses that included the amygdala, hypothalamus and periaqueductal grey as ROIs did not yield significant group-related differences in resting-state functional connectivity with the DCN. However, exploratory whole-brain analysis showed that veterans with reactive aggression symptoms exhibited lower functional connectivity between the DCN and the orbitofrontal cortex compared to control veterans. Our findings provide preliminary evidence for the possible involvement of a cerebello-prefrontal pathway in reactive aggression in male veterans.

PMID:36657313 | DOI:10.1016/j.jpsychires.2023.01.023

Nutritional supplement induced modulations in the functional connectivity of a porcine brain

Thu, 01/19/2023 - 11:00

Nutr Neurosci. 2023 Jan 19:1-12. doi: 10.1080/1028415X.2023.2166803. Online ahead of print.

ABSTRACT

BACKGROUND: Functional connectivity (FC) measures statistical dependence between cortical brain regions. Studies of FC facilitate understanding of the brain's function and architecture that underpin normal cognition, behavior, and changes associated with various factors (e.g. nutritional supplements) at a large scale.

OBJECTIVE: We aimed to identify modifications in FC patterns and targeted brain anatomies in piglets following perinatal intake of different nutritional diets using a graph theory based approach.

METHODS: Forty-four piglets from four groups of pregnant sows, who were treated with nutritional supplements, including control diet, docosahexaenoic acid (DHA), egg yolk (EGG), and DHA + EGG, went through resting-state functional magnetic resonance imaging (rs-fMRI). We introduced the use of differential degree test (DDT) to identify differentially connected edges (DCEs). Simulation studies were first conducted to compare the DDT with permutation test, using three network structures at different noise levels. DDT was then applied to rs-fMRI data acquired from piglets.

RESULTS: In simulations, the DDT showed a greater accuracy in detecting DCEs when compared with the permutation test. For empirical data, we found that the strength of internodal connectivity is significantly increased for more than 6% of edges in the EGG group and more than 8% of edges in the DHA and DHA + EGG groups, all compared to the control group. Moreover, differential wiring diagrams between group comparisons provided means to pinpoint brain hubs affected by nutritional supplements.

CONCLUSION: DDT showed a greater accuracy of detection of DCEs and demonstrated EGG, DHA, and DHA + EGG supplemented diets lead to an improved internodal connectivity in the developing piglet brain.

PMID:36657164 | DOI:10.1080/1028415X.2023.2166803

Functional connectivity of the default mode network subsystems in patients with major depressive episodes with mixed features

Thu, 01/19/2023 - 11:00

Gen Psychiatr. 2022 Dec 16;35(6):e100929. doi: 10.1136/gpsych-2022-100929. eCollection 2022.

ABSTRACT

BACKGROUND: The neuroimaging mechanism of major depressive episodes with mixed features (MMF) is not clear.

AIMS: This study aimed to investigate the functional connectivity of the default mode network (DMN) subsystems among patients with MMF and patients with major depressive disorder without mixed features (MDDnoMF).

METHODS: This study recruited 47 patients with MDDnoMF and 27 patients with MMF from Beijing Anding Hospital, Capital Medical University, between April 2021 and June 2022. Forty-five healthy controls (HCs) were recruited. All subjects underwent resting-state functional magnetic resonance imaging scanning and clinical assessments. Intranetwork and internetwork functional connectivity were computed in the DMN core subsystem, dorsal medial prefrontal cortex (dMPFC) subsystem and medial temporal lobe (MTL) subsystem. Analysis of covariance method was performed to compare the intranetwork and internetwork functional connectivity in the DMN subsystems among the MDDnoMF, MMF and HC groups.

RESULTS: The functional connectivity within the DMN core (F=6.32, pFDR=0.008) and MTL subsystems (F=4.45, pFDR=0.021) showed significant differences among the MDDnoMF, MMF and HC groups. Compared with the HC group, the patients with MDDnoMF and MMF had increased functional connectivity within the DMN MTL subsystem, and the patients with MMF also showed increased functional connectivity within the DMN core subsystem. Meanwhile, compared with the MDDnoMF, the patients with MMF had increased functional connectivity within the DMN core subsystem (mean difference (MDDnoMF-MMF)=-0.08, SE=0.04, p=0.048). However, no significant differences were found within the DMN dMPFC subsystem and all the internetwork functional connectivity.

CONCLUSIONS: Our results indicated abnormal functional connectivity patterns of DMN subsystems in patients with MMF, findings potentially beneficial to deepen our understanding of MMF's neural basis.

PMID:36654667 | PMC:PMC9764607 | DOI:10.1136/gpsych-2022-100929

Activation of brain arousal networks coincident with eye blinks during resting state

Wed, 01/18/2023 - 11:00

Cereb Cortex. 2023 Jan 18:bhad001. doi: 10.1093/cercor/bhad001. Online ahead of print.

ABSTRACT

Eye-blinking has been implicated in arousal and attention. Here we test the hypothesis that blinking-moments represent arousal surges associated with activation of the ascending arousal network (AAN) and its thalamic projections. For this purpose, we explored the temporal relationship between eye-blinks and fMRI BOLD activity in AAN and thalamic nuclei, as well as whole brain cluster corrected activations during eyes-open, resting-state fMRI scanning. We show that BOLD activations in the AAN nuclei peaked prior to the eye blinks and in thalamic nuclei peaked prior to and during the blink, consistent with the role of eye blinking in arousal surges. Additionally, we showed visual cortex peak activation prior to the eye blinks, providing further evidence of the visual cortex's role in arousal, and document cerebellar peak activation post eye blinks, which might reflect downstream engagement from arousal surges.

PMID:36653022 | DOI:10.1093/cercor/bhad001

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