Most recent paper

Eur Arch Psychiatry Clin Neurosci. 2025 Jan 3. doi: 10.1007/s00406-024-01955-0. Online ahead of print.

ABSTRACT

Auditory verbal hallucinations (AVHs) in schizophrenia are hypothesized to involve alterations in hemispheric lateralization, but the specific neural mechanisms remain unclear. This study investigated functional intra- and inter-hemispheric connectivity to identify lateralization patterns unique to AVHs. Resting-state fMRI data were collected from 60 schizophrenia patients with persistent AVHs (p-AVH group), 39 patients without AVHs (n-AVH group), and 59 healthy controls (HC group). Using a homotopic atlas, we quantified lateralization indices of functional segregation and integration across 200 homotopic ROI pairs. Segregation was defined as the degree of preferential intra-hemispheric communication within each hemisphere versus inter-hemispheric communication. Integration was used to assess the extent of inter-hemispheric communication between the two hemispheres. Our findings revealed a significant rightward lateralization of segregation in two lateral prefrontal cortex homotopic pairs in the p-AVH group. Additionally, we observed a leftward lateralization of integration in an inferior parietal lobule homotopic pair within the temporoparietal junction region, specifically in the p-AVH group. Importantly, the lateralization index of segregation in the prefrontal cortex was negatively correlated with AVH severity, indicating that greater rightward lateralization is associated with more severe AVHs. These lateralization changes were absent when comparing the n-AVH group to HC group, suggesting they are unique to AVHs in schizophrenia. Our results underscore the pivotal role of altered hemispheric lateralization of functional segregation and integration in the etiology of AVHs, providing new insights into the neural mechanisms underlying these symptoms.

PMID:39751656 | DOI:10.1007/s00406-024-01955-0

Alzheimers Dement. 2024 Dec;20 Suppl 1:e087315. doi: 10.1002/alz.087315.

ABSTRACT

BACKGROUND: Frontotemporal dementia (FTD) and Progressive Supranuclear Palsy (PSP) have distinct molecular pathologies, with Tau and TDP43 aggregation, and distinct patterns of regional brain atrophy. However, they share the synaptotoxicity of protein aggregation, and neurotransmitter loss (including GABA), which contribute to clinical and neurophysiological similarities. Defining the relationships between synaptic loss, network physiology and cognition builds bridges between preclinical and clinical studies, and facilitates early phase trials.

METHOD: We quantified the effect of behavioural variant frontotemporal dementia (±parkinsonism) and progressive supranuclear palsy (Richardson's syndrome, and PSP-F), and controls with Magnetoencephalography (resting state, mismatch task, and motor control task); 11-C-UCBJ PET estimation of synaptic density; 3T T1w and fMRI.

RESULT: Participants with bvFTD showed severe synaptic loss compared to controls which correlated strongly with baseline cognitive function (ACE-r r∼0.8, p<0.001). Participants with PSP showed severe synaptic loss, which progressed over 12 months; the degree of synaptic loss over prefrontal cortex correlated with functional decline (PSPRS, r∼0.47, p<0.03. In both PSP and FTD, synaptic loss was more severe and widespread than cortical atrophy; prefrontal/ACC atrophy was significant in PSP, but less than in bvFTD. Synaptic loss correlated with the loss of weighted dress of fMRI-based cortical network measures. On MEG, deviant-versus-repeat tones evoked the frontotemporal peak 160-200ms and induced loss of beta-power (∼20Hz) during this window. Both bvFTD and PSP reduced/abolished the effect of deviant stimuli on prefrontal beta power, and this reduction in beta-power correlated with clinical severity, as FRS (in bvFTD) and PSPRS (in PSP). Inversion of the MEG response to biophysically informed dynamic causal models accurately explained the causes of the evoked response (r>0.9). Bayesian Model Comparison and second level parametric empirical Bayes analysis with UCBJ priors indicated the effect of bvFTD and PSP was attributable to loss of synapses from superficial cortical layers.

CONCLUSION: MEG, PET and MRI are each well tolerated by people with PSP/bvFTD. These methods indicate severe and progressive synaptic loss, more than atrophy, with resulting behaviourally-relevant changes in prefrontal network beta-power and connectivity. Biophysical modelling confirms in vivo the post mortem observation of superficial cortical vulnerability to PSP/bvFTD.

PMID:39750986 | DOI:10.1002/alz.087315

Alzheimers Dement. 2024 Dec;20 Suppl 1:e090713. doi: 10.1002/alz.090713.

ABSTRACT

BACKGROUND: Neuroimaging studies have revealed age and sex-specific differences in Alzheimer's disease (AD) trajectories. However, how age and sex modulate tau spreading remains unclear. Thus, we investigated how age and sex modulate the amyloid-beta (Aβ)-induced accumulation and spreading of tau pathology from local epicenters across connected brain regions.

METHOD: We included 313 ADNI participants (female/male, n = 167/146), i.e. 110 cognitively normal (CN) Aβ-negative, and 203 Aβ-positive subjects across the AD spectrum (i.e. CN/MCI/Dementia, n = 98/70/35) with baseline amyloid-PET and longitudinal Flortaucipir tau-PET. Annual tau-PET change rates for 200 cortical regions of the Schaefer atlas were calculated. Sex-specific resting-state fMRI-connectivity templates across the 200 Schaefer regions were determined in independent Aβ-negative controls (female/male, n = 118/82) to determine the connectivity of tau epicenters to the rest of the brain. Using linear regression, we investigated interactions between age, sex and Aβ on tau accumulation and spread, controlling for APOE4-status and diagnosis.

RESULT: Higher Aβ (i.e. centiloid) predicted faster tau accumulation, where this association was pronounced in younger individuals (i.e. age x centiloid interaction, b = -3.64, p<0.001, Fig. 1A). This age x centiloid interaction was stronger in men (b = -4.82, p<0.001, Fig. 1B) vs. women (b = -1.67, p = 0.029, Fig. 1C), suggesting that younger age promotes Aβ-related tau accumulation predominantly in men. Bootstrapping analysis further confirmed this effect (Fig. 1D). In Aβ+, epicenters with highest baseline tau-PET showed a similar temporal-lobe distribution in men and women (Fig. 2A&B), yet epicenter connectivity to the rest of the brain was stronger in men vs. women (Fig. 2C). Stronger connectivity of tau epicenters to the rest of the brain was linked to faster tau accumulation especially in younger Aβ+ subjects (i.e. interaction age x epicenter connectivity, b = 4.41, p<0.001, Fig. 3A). However, this effect was clearly driven by men (b = 6.13, p<0.001, Fig. 3B) and not observed when tested in women only (b = 1.55, p = 0.252, Fig. 3C).

CONCLUSION: Aβ drives faster tau accumulation and this effect is particularly strong at younger age and even further pronounced in men, whose tau epicenters are more densely interconnected with the rest of the brain. Together, age and sex have clear modulating effects on tau spreading, and heterogeneous AD trajectories may be partly arisen due to sex-specific differences in brain network architecture.

PMID:39750727 | DOI:10.1002/alz.090713

Alzheimers Dement. 2024 Dec;20 Suppl 3:e087960. doi: 10.1002/alz.087960.

ABSTRACT

BACKGROUND: Recent evidence suggests that unawareness in Alzheimer's disease (AD) continuum can be explained by a failure of the connections between brain regions involved in accessing and monitoring self and other information. It has been demonstrated that AD patients with anosognosia have reduced network connectivity in the default mode network (DMN); in addition, stronger connectivity of bilateral anterior cingulate cortex (ACC) was showed to be associated with anosognosia in prodromal AD suggesting a possible role of this region in mechanisms of "adaptation" to anosognosia early in the disease. Therefore, we hypothesized that anosognosia in AD could be associated with an imbalance between the activity of the DMN and the salience network (SN) detectable using resting state functional magnetic resonance imaging (fMRI).

METHODS: Sixty patients with MCI and AD dementia underwent fMRI and neuropsychological assessment including the Anosognosia Questionnaire Dementia (AQ-D), a measure of anosognosia based on a discrepancy score between the patient's and carer's judgments. Independent component analysis was applied and: i) correlation analyses between the AQ-D score and functional connectivity in SN and DMN, and ii) comparison analyses of functional connectivity in DMN and SN between aware or unaware patients were performed.

RESULTS: AQ-D scores negatively correlated with intrinsic functional connectivity within the DMN in the retrosplenial cortex and precuneus, irrespective of cognitive impairment stage and age. We also found that unaware patients had higher connectivity within the SN in the anterior cingulate cortex compared to aware patients.

CONCLUSION: in patients with MCI and AD dementia, higher degrees of anosognosia are associated with lower functional connectivity within the DMN in the retrosplenial cortex and higher functional connectivity within the SN in the anterior cingulate cortex. This suggests that DMN and salience network might interplay in anosognosia expression in the AD continuum.

PMID:39750703 | DOI:10.1002/alz.087960

Front Psychol. 2024 Dec 19;15:1458339. doi: 10.3389/fpsyg.2024.1458339. eCollection 2024.

ABSTRACT

OBJECTIVES: The neural mechanism associated with impaired consciousness is not fully clear. We aim to explore the association between static and dynamic minimum spanning tree (MST) characteristics and neural mechanism underlying impaired consciousness.

METHODS: MSTs were constructed based on full-length functional magnetic resonance imaging (fMRI) signals and fMRI signal segments within each time window. Global and local measures of static MSTs, as well as spatio-temporal interaction characteristics of dynamic MSTs were investigated.

RESULTS: A disruption or an alteration in the functional connectivity, the decreased average coupling strength and the reorganization of hub nodes were observed in patients with minimally conscious state (MCS) and patients with vegetative state (VS). The analysis of global and local measures quantitatively supported altered static functional connectivity patterns and revealed a slower information transmission efficiency in both patient groups. From a dynamic perspective, the spatial distribution of hub nodes exhibited relative stability over time in both normal and patient populations. The increased temporal variability in multiple brain regions within resting-state networks associated with consciousness was detected in MCS patients and VS patients, especially thalamus. As well, the increased spatial variability in multiple brain regions within these resting-state networks was detected in MCS patients and VS patients. In addition, local measure and spatio-temporal variability analysis indicated that the differences in network structure between two groups of patients were mainly in frontoparietal network and auditory network.

CONCLUSION: Our findings suggest that altered static and dynamic MST characteristics may shed some light on neural mechanism underlying impaired consciousness.

PMID:39749272 | PMC:PMC11693494 | DOI:10.3389/fpsyg.2024.1458339

Sci Rep. 2025 Jan 2;15(1):363. doi: 10.1038/s41598-024-82769-x.

ABSTRACT

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by memory impairment and cognitive decline, ultimately culminating in dementia. This study aims to evaluate cerebrovascular reactivity (CVR) and functional connectivity (FC) in patients with AD and mild cognitive impairment (MCI) using resting-state functional magnetic resonance imaging (rs-fMRI), bypassing the requirement for hypercapnia. The study cohort comprised 53 AD patients, 38 MCI patients, and 39 normal control (NC) subjects. CVR is derived by extracting signals within specific frequency bands of rs-fMRI. This study compares the differences in CVR and FC among the three groups, using the brain regions with CVR differences as region of interest (ROI) for FC analysis. The correlation between CVR and FC and cognitive scale score was discussed. Compared with NC subjects, AD patients exhibited a decrease in CVR in the PCUN.L, whereas MCI patients showed an increase in CVR in the PCUN.R. With PCUN.L as ROI, FC in PCUN.R decreased in AD patients, and FC in SFGmed.R and other brain regions increased in MCI patients compared with NC subjects. The results of the correlation analysis indicate that CVR in all patients, as well as FC with the PCUN.L as the ROI to the PCUN.R and SFGmed.R, show positive correlations with MMSE and MoCA scores. These results suggest that there are significant differences between CVR and FC with CVR differential brain regions as ROI among the AD, MCI, and NC groups, which may help to explain the hemodynamic mechanism. CVR obtained with rs-fMRI may be a potential biomarker for assessing cognitive impairment.

PMID:39747269 | DOI:10.1038/s41598-024-82769-x

Neonatology. 2025 Jan 2:1-20. doi: 10.1159/000543277. Online ahead of print.

ABSTRACT

INTRODUCTION: The Central Autonomic Network (CAN), which involves complex interconnected brain regions that modulate the autonomic nervous system, may be key to understanding higher risk for psychosocial and behavioral challenges in preterm neonates.

METHODS: We compared resting state functional connectivity of the CAN in 94 healthy term-born controls and 94 preterm infants at term-equivalent age (TEA). In preterm infants we correlated CAN connectivity with postmenstrual age (PMA). The preterm cohort underwent the Infant Toddler Social and Emotional Assessment at 18-month follow-up and these scores were correlated with CAN connectivity.

RESULTS: CAN connectivity at the amygdala (p<.001), hippocampus (p<.001), insula (p<.001), brainstem (p=.003), and thalamus (p= .032) was significantly higher in term (n=94) than preterm (n=94) neonates. In preterm neonates, CAN connectivity positively correlated with PMA at the thalamus (r= .438, p< .001), insula (r= .304, p< .001), precuneus (r= .288, p<.001), hippocampus (r= .283, p< .001), and amygdala (r= .142, p=.034). At 18-month follow-up, (n=30, mean age 19.8 ± 3.4 months), CAN connectivity at the insula was negatively correlated with externalizing behaviors (r= -.529, p= .003).

CONCLUSION: In preterm neonates, the CAN evolves dynamically over the extrauterine third trimester and is measurably different compared to term-born neonates in ways that impact developmental outcomes. This is the first study to describe CAN connectivity using fMRI in large cohort of term and preterm neonates, and to report an association of CAN connectivity and behavioral outcomes.

PMID:39746339 | DOI:10.1159/000543277

Int J Neurosci. 2025 Jan 2:1-13. doi: 10.1080/00207454.2024.2449382. Online ahead of print.

ABSTRACT

PURPOSE: To investigate the activity of default mode network (DMN), frontoparietal network (FPN) and cerebellar network (CN) in drug-resistant epilepsy (DRE) patients undergoing vagus nerve stimulation (VNS).

METHODS: Fifteen patients were recruited and underwent resting-state fMRI scans. Independent component analysis and paired sample t-tests were used to examine activity changes of DMN, FPN and CN before and after VNS.

RESULTS: Compared with preoperative patients, DMN exhibited decreased activity in left cuneus/precuneus, left median cingulate gyrus, left superior/middle occipital gyrus, right superior parietal gyrus, right precentral/postcentral gyrus, right rolandic operculum and right insula, while increased activity was observed in right supramarginal gyrus, left fusiform gyrus, right supplementary motor area, left amygdala, and right inferior frontal gyrus. FPN displayed decreased activity in left cuneus, left anterior cingulate gyrus, right precentral gyrus, left middle/inferior frontal gyrus, right middle frontal gyrus, left superior/middle temporal gyrus, left superior/middle occipital gyrus, and right superior parietal gyrus, but increased activity in right inferior temporal gyrus. CN showed decreased activity in left superior/middle frontal gyrus, right inferior frontal gyrus, left supplementary motor area, left precuneus, left postcentral gyrus, left middle occipital gyrus, right middle temporal gyrus, and left inferior cerebellum, while increased activity was detected in bilateral superior cerebellum and right fusiform gyrus.

CONCLUSIONS: DMN, FPN and CN exhibited distinct changes in DRE patients following VNS. The suppression or activation of sensorimotor, language, memory and emotion-related regions may represent the underlying neurological mechanisms of VNS. However, the contrasting activity patterns between superior and inferior cerebellum require further investigation.

PMID:39745504 | DOI:10.1080/00207454.2024.2449382

Neurotrauma Rep. 2024 Nov 6;5(1):1048-1059. doi: 10.1089/neur.2024.0098. eCollection 2024.

ABSTRACT

Neurological recovery in individuals with spinal cord injury (SCI) is multifaceted, involving mechanisms such as remyelination and perilesional spinal neuroplasticity, with cortical reorganization being one contributing factor. Cortical reorganization, in particular, can be evaluated through network (graph) analysis of interregional functional connectivity. This study aimed to investigate cortical reorganization patterns in persons with chronic SCI using a multilayer community detection approach on resting-state functional MRI data. Thirty-eight participants with chronic cervical or thoracic SCI and 32 matched healthy controls were examined. Significant alterations in brain community structures were observed in the SCI cohort, particularly within the sensorimotor network (SMN). Importantly, this revealed a pattern of segregation within the SMN, aligning with borders of representations of the upper and lower body and orofacial regions. The SCI cohort showed reduced recruitment and integration coefficients across multiple brain networks, indicating impaired internetwork communication that may underlie sensory and motor deficits in persons with SCI. These findings highlight the impact of SCI on brain connectivity and suggest potential compensatory mechanisms.

PMID:39744611 | PMC:PMC11685503 | DOI:10.1089/neur.2024.0098

Biol Psychol. 2024 Dec 30:108979. doi: 10.1016/j.biopsycho.2024.108979. Online ahead of print.

ABSTRACT

Previous research has found functional connectivity in various networks to be altered in psychopathy and has theorised a link between these networks and the self-control-related deficits observed in psychopathy. However, this theory has yet to be tested adequately and empirically. The present study investigated the association between psychopathy, self-control, and intrinsic functional connectivity in 179 healthy adults from the MPI Leipzig Mind Brain Body dataset. Participants completed an affective switching task and questionnaires relating to psychopathy and self-control and underwent resting-state fMRI scans. Functional connectivity matrices were extracted for each subject, and network-based statistics was used to identify intrinsic resting-state functional networks associated with psychopathy scores. Significant networks that are positively and negatively associated with psychopathy emerged in the analyses. The functional connections that correlated positively with psychopathy was mostly characterised by strong connections between the default mode network and salience network, while the functional connections negatively correlated with psychopathy was largely characterised by strong within-dorsal attention network connectivity. Both the psychopathy-associated positive and negative networks were significantly correlated with measures of self-control and impulsivity. Furthermore, the negative network mediated the relationship between psychopathy and affective task-switching. Findings suggest that alterations in intrinsic functional connectivity are significantly implicated in psychopathy; these alterations possibly account for some self-control related deficits observed in psychopathy.

PMID:39743174 | DOI:10.1016/j.biopsycho.2024.108979

J Affect Disord. 2024 Dec 30:S0165-0327(24)02083-4. doi: 10.1016/j.jad.2024.12.095. Online ahead of print.

ABSTRACT

Generalized anxiety disorder (GAD) is a common anxiety disorder characterized by excessive, uncontrollable worry and physical symptoms such as difficulty concentrating and sleep disturbances. Although functional magnetic resonance imaging (fMRI) studies have reported aberrant network-level activity related to cognition and emotion in GAD, its low temporal resolution restricts its ability to capture the rapid neural activity in mental processes. EEG microstate analysis offers millisecond-resolution for tracking the dynamic changes in brain electrical activity, thereby illuminating the neurophysiological mechanisms underlying the cognitive and emotional dysfunctions in GAD. This study collected 64-channel resting-state EEG data from 28 GAD patients and 28 healthy controls (HC), identifying five microstate classes (A-E) in both groups. Results showed that GAD patients exhibited significantly lower duration (p < 0.01), occurrence (p < 0.05), and coverage (p < 0.01) of microstate class D, potentially reflecting deficits in attention-related networks. Such alterations may contribute to the impairments in attention maintenance and cognitive control. Additionally, GAD patients displayed reduced transition probabilities in A → D, B → D, C → D, and E → D (all corrected p < 0.05), but increased in C → E (corrected p < 0.05) and E → C (corrected p < 0.01). These results highlight a significant reduction in the brain's ability to transition into microstate class D, alongside overactivity in switching between the default mode network and the salience network. Such neurophysiological changes may underlie cognitive control deficits, increased spontaneous rumination, and emotional regulation challenges observed in GAD. Together, these insights provide a new perspective for understanding the neurophysiological and pathological mechanisms underlying GAD.

PMID:39743145 | DOI:10.1016/j.jad.2024.12.095

J Psychiatr Res. 2024 Dec 22;181:663-672. doi: 10.1016/j.jpsychires.2024.12.038. Online ahead of print.

ABSTRACT

BACKGROUND: Clinical guidelines recommend nonpharmacological treatment (nPHT) as the primary intervention for subthreshold depression management. Counseling (CS) and electroacupuncture (EA) are two promising nonpharmacological approaches for improving both depression and sleep disturbance. However, the intrinsic neuroimaging mechanisms underlying the antidepressant effects of these nPHTs are not yet fully understood.

METHODS: We analyzed longitudinal resting-state functional magnetic resonance imaging (rs-fMRI) data from a randomized, single-blind clinical trial involving 96 first-episode, drug-naïve college students with subclinical depression and sleep disorders (sDSD; mean age 20.43 ± 2.72 years; 66.7% female) and 90 healthy controls (HCs; mean age 21.02 ± 2.68 years; 61.1% female). Participants with sDSD were randomly assigned to receive either scalp EA (n = 47) or CS (n = 49) for six weeks. The regional homogeneity (ReHo) and amplitude of low-frequency fluctuation (ALFF) before and after nPHT were calculated. Correlation and mediation analyses were performed to investigate the complex relationships between fMRI indicators and clinical symptoms.

RESULTS: The ALFF in the left paracentral lobule in sDSD patients presented an interaction effect between group and time following six weeks of nPHT. In the CS group, the ALFF in the left paracentral lobule decreased (p < 0.001), and in the EA group, it increased (p < 0.05). Compared with HCs, the baseline sDSD has many abnormal brain regions in terms of ALFF and ReHo. The whole-brain average ReHo was negatively correlated with depression scores (r = -0.26, p < 0.001) and sleep quality scores (r = -0.25, p < 0.001) and mediated the association between depression and sleep disorders [β = 0.2857, p < 0.001, 95% CI (0.23, 0.35)].

CONCLUSIONS: Nonpharmacological therapies provide different therapeutic outcomes in terms of the same rs-fMRI indicator. ALFF in the left paracentral lobule could be used as an imaging biomarker in nPHT selection. Rs-fMRI indicators are promising for understanding the neural basis of the complex relationship between subclinical depression and insomnia comorbidities in young adults.

PMID:39742797 | DOI:10.1016/j.jpsychires.2024.12.038

Front Neuroimaging. 2024 Dec 17;3:1481858. doi: 10.3389/fnimg.2024.1481858. eCollection 2024.

ABSTRACT

OBJECTIVE: Resting-state functional MRI (rs-fMRI) may localize the seizure onset zone (SOZ) for epilepsy surgery, when compared to intracranial EEG and surgical outcomes, per a prior meta-analysis. Our goals were to further characterize this agreement, by broadening the queried rs-fMRI analysis subtypes, comparative modalities, and same-modality comparisons, hypothesizing SOZ-signal strength may overcome this heterogeneity.

METHODS: PubMed, Embase, Scopus, Web of Science, and Google Scholar between April 2010 and April 2020 via PRISMA guidelines for SOZ-to-established-modalities were screened. Odd ratios measured agreement between SOZ and other modalities. Fixed- and random-effects analyses evaluated heterogeneity of odd ratios, with the former evaluating differences in agreement across modalities and same-modality studies.

RESULTS: In total, 9,550 of 14,384 were non-duplicative articles and 25 met inclusion criteria. Comparative modalities were EEG 7, surgical outcome 6, intracranial EEG 5, anatomical MRI 4, EEG-fMRI 2, and magnetoencephalography 1. Independent component analysis 9 and seed-based analysis 8 were top rs-fMRI methods. Study-level odds ratio heterogeneity in both the fixed- and random-effects analysis was significant (p < 0.001). Marked cross-modality and same-modality systematic differences in agreement between rs-fMRI and the comparator were present (p = 0.005 and p = 0.002), respectively, with surgical outcomes having higher agreement than EEG (p = 0.002) and iEEG (p = 0.007). The estimated population mean sensitivity and specificity were 0.91 and 0.09, with predicted values across studies ranging from 0.44 to 0.96 and 0.02 to 0.67, respectively.

SIGNIFICANCE: We evaluated centrality and heterogeneity in SOZ agreement between rs-fMRI and comparative modalities using a wider variety of rs-fMRI analyzing subtypes and comparative modalities, compared to prior. Strong evidence for between-study differences in the agreement odds ratio was shown by both the fixed- and the random-effects analyses, attributed to rs-fMRI analysis variability. Agreement with rs-fMRI differed by modality type, with surgical outcomes having higher agreement than EEG and iEEG. Overall, sensitivity was high, but specificity was low, which may be attributed in part to differences between other modalities.

PMID:39742390 | PMC:PMC11685199 | DOI:10.3389/fnimg.2024.1481858

BMC Psychiatry. 2024 Dec 31;24(1):963. doi: 10.1186/s12888-024-06427-2.

ABSTRACT

BACKGROUND: Cognitive impairment is prevalent in bipolar disorder (BD), and has negative impacts on functional impairments and quality of life, despite euthymic states in most individuals. The underlying neurobiological basis of cognitive impairment in BD is still unclear.

METHODS: To further explore potential connectivity abnormalities and their associations with cognitive impairment, we conducted a degree centrality (DC) analysis and DC (seed)-based functional connectivity (FC) approach in unmedicated, euthymic individuals with BD. Our study included 34 euthymic BD patients and 35 healthy controls (HC) matched for age, gender, and education years.

RESULTS: We found extensive DC changes in brain activity, with lower DC values in the left medial frontal gyrus, inferior frontal gyrus, and middle frontal gyrus, and increased DC values in the left insula, bilateral precentral gyrus, and right medial frontal gyrus in BD patients compared to HC. Furthermore, we observed positive or negative correlations between DC values of the inferior frontal gyrus, insula_L, precentral gyrus (L), precentral gyrus (R), and medial frontal gyrus and multiple-domain cognitive assessment scores. Additionally, we identified intranetwork and internetwork functional connectivity alterations in the default mode network (DMN), fronto-parietal network (FPN), and central executive network (CEN) in euthymic BD patients compared to HC.

CONCLUSION: Our findings highlight abnormal neuronal networks involving multiple frontal brain regions and thalamus, which may contribute to cognitive deficits in individuals with euthymic BD. These findings may serve as potential hallmarks of BD, contributing to a better understanding of the neural mechanism of cognitive impairment during euthymia.

PMID:39741246 | DOI:10.1186/s12888-024-06427-2

Brain Behav. 2025 Jan;15(1):e70219. doi: 10.1002/brb3.70219.

ABSTRACT

PURPOSE: The neurobiological heterogeneity present in schizophrenia remains poorly understood. This likely contributes to the limited success of existing treatments and the observed variability in treatment responses. Our objective was to employ magnetic resonance imaging (MRI) and machine learning (ML) algorithms to improve the classification of schizophrenia and its subtypes.

METHOD: We utilized a public dataset provided by the UCLA (University of California, Los Angeles) Consortium for Neuropsychiatric Research, containing structural MRI and resting-state fMRI (rsfMRI) data. We integrated all individuals within the dataset diagnosed with schizophrenia (N = 50), along with age- and gender-matched healthy individuals (N = 50). We extracted volumetrics of 66 subcortical and thickness of 72 cortical regions. Additionally, we obtained four graph-based measures for 116 intracranial regions from rsfMRI data, including degree, betweenness centrality, participation coefficient, and local efficiency. Employing conventional ML methods, we sought to distinguish the patients with schizophrenia from healthy individuals. Furthermore, we applied the methods for discriminating subtypes of schizophrenia. To streamline the feature set, various feature selection techniques were applied. Moreover, a validation phase involved employing the model on a dataset domestically acquired using the same imaging assessments (N = 13). Finally, we explored the correlation between neuroimaging features and behavioral assessments.

FINDING: The classification accuracy reached as high as 79% in distinguishing schizophrenia patients from healthy in the UCLA dataset. This result was achieved by the k-nearest neighbor algorithm, utilizing 12 brain neuroimaging features, selected by the feature selection method of minimum redundancy maximum relevance (MRMR). The model demonstrated effectiveness (72% accuracy) in estimating the patient's label for a new dataset acquired domestically. Using a linear support vector machine (SVM) on 62 features obtained from MRMR, patients with schizophrenic subtypes were classified with an accuracy of 64%. The highest Spearman correlation coefficient between the neuroimaging features and behavioral assessments was observed between the degree of the postcentral gyrus and mean reaction time in the verbal capacity task (r = 0.49, p = 0.001).

CONCLUSION: The findings of this study underscore the utility of MRI and ML algorithms in enhancing the diagnostic process for schizophrenia. Furthermore, these methods hold promise for detecting both brain-related abnormalities and cognitive impairments associated with this disorder.

PMID:39740776 | DOI:10.1002/brb3.70219

Neural Netw. 2024 Dec 25;184:107100. doi: 10.1016/j.neunet.2024.107100. Online ahead of print.

ABSTRACT

The human brain exhibits heterogeneity across regions and network connectivity patterns; However, how these heterogeneities contribute to whole-brain network functions and cognitive capacities remains unclear. In this study, we focus on the regional heterogeneity reflected in local dynamics and study how it contributes to the emergence of functional connectivity patterns, network ignition dynamics of the empirical brains. We find that the level of synchrony among voxelwise neural activities measured from the fMRI data is significantly correlated with the transcriptional variations in excitatory and inhibitory receptor gene expression. Consequently, we construct heterogeneous whole-brain network models with nodal excitability calibrated by the synchronization measure of regional dynamics. We demonstrate that as the extent of heterogeneity increases, the models operating around the critical point between order and disorder generate simulated functional connectivity networks increasingly similar to empirical resting-state or working memory task-evoked function connectivity networks. Furthermore, the heterogeneous models can predict individual differences in resting-state and task-evoked reconfiguration of the functional connectivity, as well as the comparative causal effect of empirical brain networks-that is, how the dynamics of one brain region affect whole-brain synchronization. Overall, this work demonstrates the viability of using regional heterogeneous functional signals to improve the performance of the whole-brain models, and illustrates how regional heterogeneity in human brains interplays with structural connections and critical dynamics to contribute to the emergence of functional connectivity networks.

PMID:39740389 | DOI:10.1016/j.neunet.2024.107100

Cortex. 2024 Dec 17;183:220-231. doi: 10.1016/j.cortex.2024.10.024. Online ahead of print.

ABSTRACT

The role of the medial part of the thalamus, and in particular the mediodorsal nucleus (MD) and the mammillothalamic tract (MTT), in memory has long been studied, but their contribution remains unclear. While the main functional hypothesis regarding the MTT focuses on memory, some authors postulate that the MD plays a supervisory executive role (indirectly affecting memory retrieval) due to its dense structural connectivity with the prefrontal cortex (PFC). Recently, it has been proposed that the MD, MTT and PFC form part of the DMN the default mode network (DMN). Due to the theoretical presence of MD and MTT in the DMN, we aimed to show the effect of thalamic lesions on functional connectivity (FC) and its putative role in cognitive impairment. We recruited 12 patients with left thalamic infarction and 12 matched healthy controls. They underwent neuropsychological assessment including memory tasks, morphological 3D MRI and resting state fMRI. A ROI-to-ROI method was used for group-level FC analyses. Patients had lesions in the MD and ventrolateral nuclei, with a damaged mammillothalamic tract (MTT) in seven of them. They showed lower performance than controls on verbal memory, executive function and language tests, with more impairment in memory, working memory, semantic verbal fluency and attention in the MTT-damaged patients. Contrast analyses between patients and matched controls showed lower FC in the ventral and dorsal DMN. Correlation analyses (patients and controls pooled) showed i/a positive correlation between memory and DMN, and ii/that MTT volume correlated with decreased functional connectivity in the dorsal DMN, whereas there was no correlation with MD lesion volume. These results suggest that both the memory impairment and the DMN functional change we observed may reflect an effect of the MTT lesion rather than MD damage.

PMID:39740264 | DOI:10.1016/j.cortex.2024.10.024

Hum Brain Mapp. 2025 Jan;46(1):e70107. doi: 10.1002/hbm.70107.

ABSTRACT

Disruptions to brain networks, measured using structural (sMRI), diffusion (dMRI), or functional (fMRI) MRI, have been shown in people with multiple sclerosis (PwMS), highlighting the relevance of regions in the core of the connectome but yielding mixed results depending on the studied connectivity domain. Using a multilayer network approach, we integrated these three modalities to portray an enriched representation of the brain's core-periphery organization and explore its alterations in PwMS. In this retrospective cross-sectional study, we selected PwMS and healthy controls with complete multimodal brain MRI acquisitions from 13 European centers within the MAGNIMS network. Physical disability and cognition were assessed with the Expanded Disability Status Scale (EDSS) and the symbol digit modalities test (SDMT), respectively. SMRI, dMRI, and resting-state fMRI data were parcellated into 100 cortical and 14 subcortical regions to obtain networks of morphological covariance, structural connectivity, and functional connectivity. Connectivity matrices were merged in a multiplex, from which regional coreness-the probability of a node being part of the multiplex core-and coreness disruption index (κ)-the global weakening of the core-periphery structure-were computed. The associations of κ with disease status (PwMS vs. healthy controls), clinical phenotype, level of physical disability (EDSS ≥ 4 vs. EDSS < 4), and cognitive impairment (SDMT z-score < -1.5) were tested within a linear model framework. Using random forest permutation feature importance, we assessed the relative contribution of κ in the multiplex and single-layer domains, in addition to conventional MRI measures (brain and lesion volumes), in predicting disease status, physical disability, and cognitive impairment. We studied 1048 PwMS (695F, mean ± SD age: 43.3 ± 11.4 years) and 436 healthy controls (250F, mean ± SD age: 38.3 ± 11.8 years). PwMS showed significant disruption of the multiplex core-periphery organization (κ = -0.14, Hedges' g = 0.49, p < 0.001), correlating with clinical phenotype (F = 3.90, p = 0.009), EDSS (Hedges' g = 0.18, p = 0.01), and SDMT (Hedges' g = 0.30, p < 0.001). Multiplex κ was the only connectomic measure adding to conventional MRI in predicting disease status and cognitive impairment, while physical disability also depended on single-layer contributions. In conclusion, we show that multilayer networks represent a biologically and clinically meaningful framework to model multimodal MRI data, with disruption of the core-periphery structure emerging as a potential connectomic biomarker for disease severity and cognitive impairment in PwMS.

PMID:39740239 | DOI:10.1002/hbm.70107

Sci Rep. 2024 Dec 30;14(1):32032. doi: 10.1038/s41598-024-83696-7.

ABSTRACT

Network energy has been conceptualized based on structural balance theory in the physics of complex networks. We utilized this framework to assess the energy of functional brain networks under cognitive control and to understand how energy is allocated across canonical functional networks during various cognitive control tasks. We extracted network energy from functional connectivity patterns of subjects who underwent fMRI scans during cognitive tasks involving working memory, inhibitory control, and cognitive flexibility, in addition to task-free scans. We found that the energy of the whole-brain network increases when exposed to cognitive control tasks compared to the task-free resting state, which serves as a reference point. The brain selectively allocates this elevated energy to canonical functional networks; sensory networks receive more energy to support flexibility for processing sensory stimuli, while cognitive networks relevant to the task, functioning efficiently, require less energy. Furthermore, employing network energy, as a global network measure, improves the performance of predictive modeling, particularly in classifying cognitive control tasks and predicting chronological age. Our results highlight the robustness of this framework and the utility of network energy in understanding brain and cognitive mechanisms, including its promising potential as a biomarker for mental conditions and neurological disorders.

PMID:39738735 | DOI:10.1038/s41598-024-83696-7

Brain Struct Funct. 2024 Dec 30;230(1):22. doi: 10.1007/s00429-024-02888-z.

ABSTRACT

The default mode network (DMN) is a singular pattern of synchronization between brain regions, usually observed using resting-state functional magnetic resonance imaging (rs-fMRI) and functional connectivity analyses. In comparison to other brain networks that are primarily involved in attentional-demanding tasks (such as the frontoparietal network), the DMN is linked with self-referential activities, and alterations in its pattern of connectivity have been related to a wide range of disorders. Structural connectivity analyses have highlighted the vital role of the posterior cingulate cortex and the precuneus as integrative hubs, and advanced parcellation methods have further contributed to elucidate the DMN's regions, enriching its explanatory potential across cognitive functions and dysfunctions. Interestingly, the study of its temporal characteristics - the specific frequency spectrum of BOLD signal oscillations -, its developmental trajectory over the course of life, and its interaction with other networks, provides new insight into the DMN's defining features. In this context, this review aims to synthesize the state of the art in the study of the DMN to provide the most updated findings to anyone interested in its research. Finally, some weaknesses in the current state of knowledge and some interesting lines of work for further progress in the study of the DMN are presented.

PMID:39738718 | DOI:10.1007/s00429-024-02888-z