Most recent paper

Involvement of the left uncinate fasciculus in the amyotrophic lateral sclerosis: an exploratory longitudinal multi-modal neuroimaging and neuropsychological study

Tue, 12/17/2024 - 19:00

Brain Struct Funct. 2024 Dec 17;230(1):8. doi: 10.1007/s00429-024-02884-3.

ABSTRACT

To investigate the microstructural integrity, tract volume analysis, and functional connectivity (FC) alterations of the left uncinate fasciculus (UF) in patients with amyotrophic lateral sclerosis (ALS) compared to healthy controls (HCs). Fourteen limb-onset ALS patients were recruited at baseline and ten at follow-up, along with 14 HCs. All participants underwent 3D T1-weighted, diffusion tensor imaging and kurtosis imaging (DTI/DKI), and resting-state functional MRI (rs-fMRI) using a 3 Tesla scanner with 64-channel coils. Eight metrics of diffusion, rs-FC of the left UF, and graph theory analyses were extracted. Statistical group comparisons and correlation analysis for significant diffusion metrics were also conducted. Significantly lower radial kurtosis (RK), mean kurtosis (MK), and higher DTI diffusivity metrics were observed in the left UF of ALS patients than in HCs. RK and MK were correlated with various cognitive scores, particularly executive function and visuospatial ability. The volume of the left UF was positively correlated only with RK and MK at follow-up. While rs-FC analysis did not reveal group differences, a negative functional link between the left UF and cerebellum was observed in HCs but not in patients. Graph theory analysis suggested decreased connectivity in baseline patients and potential compensatory effects during the follow-up. Our study reveals microstructural abnormalities and potential network changes in left UF. DKI metrics, especially RK and MK, may be more sensitive biomarkers than DTI metrics, particularly longitudinally. Diffusion changes appear to precede volume and functional connectivity alterations, suggesting diffusion as a potential early biomarker.

PMID:39688717 | DOI:10.1007/s00429-024-02884-3

Reduced brain network segregation in alcohol use disorder: Associations with neurocognition

Tue, 12/17/2024 - 19:00

Addict Biol. 2024 Dec;29(12):e13446. doi: 10.1111/adb.13446.

ABSTRACT

The human brain consists of functionally segregated networks, characterized by strong connections among regions belonging to the same network and weak connections between those of different networks. Alcohol use disorder (AUD) is associated with premature brain aging and neurocognitive impairments. Given the link between decreased brain network segregation and age-related cognitive decline, we hypothesized lower brain segregation in patients with AUD than healthy controls (HCs). Thirty AUD patients (9 females, 21 males) and 61 HCs (35 females, 26 males) underwent resting-state functional MRI (rs-fMRI), whose data were processed to assess segregation within the brain sensorimotor and association networks. We found that, compared to HCs, AUD patients had significantly lower segregation in both brain networks as well as poorer performance on a spatial working memory task. In the HC group, brain network segregation correlated negatively with age and positively with spatial working memory. Our findings suggest reduced brain network segregation in individuals with AUD that may contribute to cognitive impairment and is consistent with premature brain aging in this population.

PMID:39686721 | DOI:10.1111/adb.13446

Functional Connectivity Biomarker Extraction for Schizophrenia Based on Energy Landscape Machine Learning Techniques

Tue, 12/17/2024 - 19:00

Sensors (Basel). 2024 Dec 4;24(23):7742. doi: 10.3390/s24237742.

ABSTRACT

Brain connectivity represents the functional organization of the brain, which is an important indicator for evaluating neuropsychiatric disorders and treatment effects. Schizophrenia is associated with impaired functional connectivity but characterizing the complex abnormality patterns has been challenging. In this work, we used resting-state functional magnetic resonance imaging (fMRI) data to measure functional connectivity between 55 schizophrenia patients and 63 healthy controls across 246 regions of interest (ROIs) and extracted the disease-related connectivity patterns using energy landscape (EL) analysis. EL analysis captures the complexity of brain function in schizophrenia by focusing on functional brain state stability and region-specific dynamics. Age, sex, and smoker demographics between patients and controls were not significantly different. However, significant patient and control differences were found for the brief psychiatric rating scale (BPRS), auditory perceptual trait and state (APTS), visual perceptual trait and state (VPTS), working memory score, and processing speed score. We found that the brains of individuals with schizophrenia have abnormal energy landscape patterns between the right and left rostral lingual gyrus, and between the left lateral and orbital area in 12/47 regions. The results demonstrate the potential of the proposed imaging analysis workflow to identify potential connectivity biomarkers by indexing specific clinical features in schizophrenia patients.

PMID:39686279 | DOI:10.3390/s24237742

Functional Brain Network Disruptions in Parkinson's Disease: Insights from Information Theory and Machine Learning

Tue, 12/17/2024 - 19:00

Diagnostics (Basel). 2024 Dec 4;14(23):2728. doi: 10.3390/diagnostics14232728.

ABSTRACT

Objectives: This study investigates disruptions in functional brain networks in Parkinson's Disease (PD), using advanced modeling and machine learning. Functional networks were constructed using the Nonlinear Autoregressive Distributed Lag (NARDL) model, which captures nonlinear and asymmetric dependencies between regions of interest (ROIs). Key network metrics and information-theoretic measures were extracted to classify PD patients and healthy controls (HC), using deep learning models, with explainability methods employed to identify influential features. Methods: Resting-state fMRI data from the Parkinson's Progression Markers Initiative (PPMI) dataset were used to construct NARDL-based networks. Metrics, such as Degree, Closeness, Betweenness, and Eigenvector Centrality, along with Network Entropy and Complexity, were analyzed. Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Long Short-Term Memory (LSTM) models, classified PD and HC groups. Explainability techniques, including SHAP and LIME, identified significant features driving the classifications. Results: PD patients showed reduced Closeness (22%) and Betweenness Centrality (18%). CNN achieved 91% accuracy, with Network Entropy and Eigenvector Centrality identified as key features. Increased Network Entropy indicated heightened randomness in PD brain networks. Conclusions: NARDL-based analysis with interpretable deep learning effectively distinguishes PD from HC, offering insights into neural disruptions and potential personalized treatments for PD.

PMID:39682636 | DOI:10.3390/diagnostics14232728

Multimodal Neurophenomenology of Advanced Concentration Absorption Meditation: An Intensively Sampled Case Study of Jhana

Mon, 12/16/2024 - 19:00

Neuroimage. 2024 Dec 14:120973. doi: 10.1016/j.neuroimage.2024.120973. Online ahead of print.

ABSTRACT

Using a combination of fMRI, EEG, and phenomenology ratings, we examined the neurophenomenology of advanced concentrative absorption meditation, namely jhanas (ACAM-J), in a practitioner with over 23000 hours of meditation practice. Our study shows that ACAM-J states induce reliable changes in conscious experience and that these experiences are related to neural activity. Using resting-state fMRI functional connectivity, we found that ACAM-J is associated with decreased within-network modularity, increased global functional connectivity (GFC), and desegregation of the default mode and visual networks. Compared to control tasks, the ACAM-J were also related to widespread decreases in broadband EEG oscillatory power and increases in Lempel-Ziv complexity (LZ, a measure of brain entropy). Some fMRI findings varied by the control task used, while EEG results remained consistent, emphasizing both shared and unique neural features of ACAM-J. These differences in fMRI and EEG-measured neurophysiological properties correlated with specific changes in phenomenology - and especially with ACAM-J-induced states of bliss - enriching our understanding of these advanced meditative states. Our results show that advanced meditation practices markedly dysregulate high-level brain systems via practices of enhanced attention to sensations, corroborating recent neurocognitive theories of meditation as the deconstruction of the brain's cortical hierarchy. Overall, our results suggest that ACAM-J is associated with the modulation of large-scale brain networks in both fMRI and EEG, with potential implications for understanding the mechanisms of deep concentration practices and their effects on subjective experience.

PMID:39681243 | DOI:10.1016/j.neuroimage.2024.120973

Revisiting the standard for modeling functional brain network activity: Application to consciousness

Mon, 12/16/2024 - 19:00

PLoS One. 2024 Dec 16;19(12):e0314598. doi: 10.1371/journal.pone.0314598. eCollection 2024.

ABSTRACT

Functional connectivity (FC) of resting-state fMRI time series can be estimated using methods that differ in their temporal sensitivity (static vs. dynamic) and the number of regions included in the connectivity estimation (derived from a prior atlas). This paper presents a novel framework for identifying and quantifying resting-state networks using resting-state fMRI recordings. The study employs a linear latent variable model to generate spatially distinct brain networks and their associated activities. It specifically addresses the atlas selection problem, and the statistical inference and multivariate analysis of the obtained brain network activities. The approach is demonstrated on a dataset of resting-state fMRI recordings from monkeys under different anesthetics using static FC. Our results suggest that two networks, one fronto-parietal and cingular and another temporo-parieto-occipital (posterior brain) strongly influences shifts in consciousness, especially between anesthesia and wakefulness. Interestingly, this observation aligns with the two prominent theories of consciousness: the global neural workspace and integrated information theories of consciousness. The proposed method is also able to decipher the level of anesthesia from the brain network activities. Overall, we provide a framework that can be effectively applied to other datasets and may be particularly useful for the study of disorders of consciousness.

PMID:39680526 | DOI:10.1371/journal.pone.0314598

Flexible Bayesian Product Mixture Models for Vector Autoregressions

Mon, 12/16/2024 - 19:00

J Mach Learn Res. 2024 Apr;25:146.

ABSTRACT

Bayesian non-parametric methods based on Dirichlet process mixtures have seen tremendous success in various domains and are appealing in being able to borrow information by clustering samples that share identical parameters. However, such methods can face hurdles in heterogeneous settings where objects are expected to cluster only along a subset of axes or where clusters of samples share only a subset of identical parameters. We overcome such limitations by developing a novel class of product of Dirichlet process location-scale mixtures that enables independent clustering at multiple scales, which results in varying levels of information sharing across samples. First, we develop the approach for independent multivariate data. Subsequently we generalize it to multivariate time-series data under the framework of multi-subject Vector Autoregressive (VAR) models that is our primary focus, which go beyond parametric single-subject VAR models. We establish posterior consistency and develop efficient posterior computation for implementation. Extensive numerical studies involving VAR models show distinct advantages over competing methods in terms of estimation, clustering, and feature selection accuracy. Our resting state fMRI analysis from the Human Connectome Project reveals biologically interpretable connectivity differences between distinct intelligence groups, while another air pollution application illustrates the superior forecasting accuracy compared to alternate methods.

PMID:39679282 | PMC:PMC11646655

Brain Resilience to Targeted Attack of Resting BOLD Networks as a Measure of Cognitive Reserve

Mon, 12/16/2024 - 19:00

Res Sq [Preprint]. 2024 Dec 4:rs.3.rs-5356022. doi: 10.21203/rs.3.rs-5356022/v1.

ABSTRACT

Recent advancements in connectome analyses have enabled more precise measurements of brain network integrity. Identifying neural measures that can operate as mechanisms of cognitive reserve (CR) is integral for the study of individual variability in age-related cognitive changes. In the present study, we tested the hypothesis that network resilience, or the network's ability to maintain functionality when facing internal or external perturbations that cause damage or error, can function as a CR candidate, modifying the relationship between cognitive and brain changes in a lifespan cohort of cognitively healthy adults. One hundred cognitively healthy older adults from the Reference Ability Neural Network (RANN) longitudinal lifespan cohort (50-80 years) underwent resting-state fMRI and neuropsychological testing at baseline and five-year follow-up. Using undirected weighted adjacency matrices created from the Schaefer et al. (2018) 400-parcellation atlas and 19 additional subcortical regions (419 nodes in total), whole-brain network resilience was assessed through a targeted attack approach, where nodes were sequentially removed by nodal strength and resilience defined as the iteration of the steepest slope in the largest connected component (LCC) decay. We observed that brain resilience (BR) moderated the effect of cortical thickness (CT) changes on longitudinal changes in Fluid Reasoning performance, even after adjusting for baseline differences, demographic factors, and the initial LCC of the unlesioned matrix, indicating that individuals with greater resilience were less sensitive to the effect of cortical thickness changes on changes in cognition. These findings support the use of targeted attack as a measure of cognitive reserve, suggesting that higher brain network resilience may allow individuals with reduced brain integrity to better cope with structural loss and maintain cognitive function.

PMID:39678345 | PMC:PMC11643323 | DOI:10.21203/rs.3.rs-5356022/v1

Functional MRI-Specific Alternations in default mode network in obsessive-compulsive disorder: A voxel-based meta-analysis

Sun, 12/15/2024 - 19:00

Biol Psychiatry Cogn Neurosci Neuroimaging. 2024 Dec 13:S2451-9022(24)00377-X. doi: 10.1016/j.bpsc.2024.12.001. Online ahead of print.

ABSTRACT

BACKGROUND: Obsessive-compulsive disorder (OCD) is a common and debilitating mental disorder. Neuroimaging studies have highlighted that the dysfunctional default mode network (DMN) plays a key role in the pathophysiology mechanisms of OCD. However, the findings of impaired DMN regions have been inconsistent. We employed meta-analysis to identify the fMRI-specific abnormalities of the DMN in OCD.

METHODS: PubMed, Web of science and Embase were searched to screen resting-state functional magnetic resonance imaging (rs-fMRI) studies on the amplitude of low-frequency fluctuation/fractional amplitude of low-frequency fluctuation (ALFF/fALFF) and regional homogeneity (ReHo) of the DMN in OCD patients. Based on the activation likelihood estimation (ALE) algorithm, we compared all patients with OCD and control group in a primary meta-analysis, and analyzed the unmedicated OCD without comorbidities in secondary meta-analyses.

RESULTS: A total of 26 eligible studies with 1219 OCD patients (707men) and 1238 healthy controls (684 men) were included in the primary meta-analysis. We concluded specific changes in brain regions of DMN, mainly in the left medial frontal gurus (MFG), bilateral superior temporal gyrus (STG), bilateral inferior parietal lobule (IPL), bilateral precuneus (PCUN), bilateral posterior cingulate cortex (PCC), and right parahippocampal gyrus (PHG).

CONCLUSION: OCD patients showed dysfunction in the DMN, including impaired local important nodal brain regions. The PCC/PCUN appear to be the most affected regions within the DMN, providing valuable insights into understanding the potential pathophysiology of OCD and targets for clinical interventions.

PMID:39675630 | DOI:10.1016/j.bpsc.2024.12.001

HIPPOCAMPAL CONNECTIVITY DYNAMICS AND VOLUMETRIC ALTERATIONS PREDICT COGNITIVE STATUS IN MIGRAINE: A RESTING-STATE FMRI STUDY

Sun, 12/15/2024 - 19:00

Neuroimage. 2024 Dec 13:120961. doi: 10.1016/j.neuroimage.2024.120961. Online ahead of print.

ABSTRACT

The etiology of cognitive decline linked to migraine remains unclear, with a growing recurrence rate and potential increased dementia risk among sufferers. Cognitive dysfunction has recently gained attention as a significant problem among migraine sufferers that can be related to alterations in hippocampal function and structure. This study explores hippocampal subfield connectivity and volume changes in migraine patients. We recruited 90 individuals from Alanya University's Neurology Department, including 49 migraine patients and 41 controls, for functional and anatomical imaging. Using the CONN toolbox and FreeSurfer, we assessed functional connectivity and subfield volumes, respectively. Montreal Cognitive Assessment (MOCA) was used to assess cognition in the entire sample. As a result, migraine patients exhibited significantly lower MOCA scores compared to controls (p<.001). Also, we found significant differences in hippocampal subfields between migraine patients and control groups in terms of functional connectivity after adjusting for years of education; here we showed that the left CA3 showed higher connectivity with right MFG and right occipitolateral cortex. Furthermore, the connectivity of left fimbria with the left temporal lobe and hippocampus and the connectivity of the right hippocampal-tail with right insula, heschl's gyrus, and frontorbital cortex were lower in the migraineurs. Additionally, volumes of specific hippocampal subfields significantly lower in the migraineurs (whole hippocampus p=0.004, whole hippocampus head p=0.003, right CA1 head p=0.006, and right HATA p=0.005) compared to controls. In conclusion, these findings indicate that migraine-associated cognitive impairment involves significant functional and structural brain changes, particularly in the hippocampus, which may heighten dementia risk. This pioneering study unveils critical hippocampal alterations linked to cognitive function in migraine sufferers, underscoring the potential for these changes to impact dementia development.

PMID:39675538 | DOI:10.1016/j.neuroimage.2024.120961

Abnormal characteristics in disorders of consciousness: A resting-state functional magnetic resonance imaging study

Sat, 12/14/2024 - 19:00

Brain Res. 2024 Dec 12:149401. doi: 10.1016/j.brainres.2024.149401. Online ahead of print.

ABSTRACT

AIMS: To explore the functional brain imaging characteristics of patients with disorders of consciousness (DoC).

METHODS: This prospective cohort study consecutively enrolled 27 patients in minimally conscious state (MCS), 23 in vegetative state (VS), and 25 age-matched healthy controls (HC). Resting-state functional magnetic resonance imaging (rs-fMRI) was employed to evaluate the amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), degree centrality (DC), and functional connectivity (FC). Sliding windows approach was conducted to construct dynamic FC (dFC) matrices. Moreover, receiver operating characteristic analysis and Pearson correlation were used to distinguish these altered characteristics in DoC.

RESULTS: Both MCS and VS exhibited lower ALFF, ReHo, and DC values, along with reduced FC in multiple brain regions compared with HC. Furthermore, the values in certain regions of VS were lower than those in MCS. The primary differences in brain function between patients with varying levels of consciousness were evident in the cortico-striatopallidal-thalamo-cortical mesocircuit. Significant differences in the temporal properties of dFC (including frequency, mean dwell time, number of transitions, and transition probability) were also noted among the three groups. Moreover, these multimodal alterations demonstrated high classificatory accuracy (AUC > 0.8) and were correlated with the Coma Recovery Scale-Revised (CRS-R).

CONCLUSION: Patients with DoC displayed abnormal patterns in local and global dynamic and static brain functions. These alterations in rs-fMRI were closely related to the level of consciousness.

PMID:39674532 | DOI:10.1016/j.brainres.2024.149401

Salience Network in Autism: preliminary results on functional connectivity analysis in resting state

Sat, 12/14/2024 - 19:00

Eur Arch Psychiatry Clin Neurosci. 2024 Dec 14. doi: 10.1007/s00406-024-01949-y. Online ahead of print.

ABSTRACT

The literature suggests that alterations in functional connectivity (FC) of the Salience Network (SN) may contribute to the manifestation of some clinical features of Autism Spectrum Disorder (ASD). The SN plays a key role in integrating external sensory information with internal emotional and bodily information. An atypical FC of this network could explain some symptomatic features of ASD such as difficulties in self-awareness and emotion processing and provide new insights into the neurobiological basis of autism. Using the Autism Brain Imaging Data Exchange II we investigated the resting-state FC of core regions of SN and its association with autism symptomatology in 29 individuals with ASD compared with 29 typically developing (TD) individuals. In ASD compared to TD individuals, seed-based connectivity analysis showed a reduced FC between the rostral prefrontal cortex and left cerebellum and an increased FC between the right supramarginal gyrus and the regions of the middle temporal gyrus and angular gyrus. Finally, we found that the clinical features of ASD are mainly associated with an atypical FC of the anterior insula and the involvement of dysfunctional mechanisms for emotional and social information processing. These findings expand the knowledge about the differences in the FC of SN between ASD and TD, highlighting atypical FC between structures that play key roles in social cognition and complex cognitive processes. Such anomalies could explain difficulties in processing salient stimuli, especially those of a socio-affective nature, with an impact on emotional and behavioral regulation.

PMID:39673625 | DOI:10.1007/s00406-024-01949-y

The hidden link: Investigating functional connectivity of rarely explored sub-regions of thalamus and superior temporal gyrus in Schizophrenia

Fri, 12/13/2024 - 19:00

Transl Neurosci. 2024 Dec 11;15(1):20220356. doi: 10.1515/tnsci-2022-0356. eCollection 2024 Jan 1.

ABSTRACT

Functional magnetic resonance imaging (fMRI) stands as a pivotal tool in advancing our comprehension of Schizophrenia, offering insights into functional segregations and integrations. Previous investigations employing either task-based or resting-state fMRI primarily focused on large main regions of interest (ROI), revealing the thalamus and superior temporal gyrus (STG) as prominently affected areas. Recent studies, however, unveiled the cytoarchitectural intricacies within these regions, prompting a more nuanced exploration. In this study, resting-state fMRI was conducted on 72 schizophrenic patients and 74 healthy controls to discern whether distinct thalamic nuclei and STG sub-regions exhibit varied functional integrational connectivity to main networks and to identify the most affected sub-regions in Schizophrenia. Employing seed-based analysis, six sub-ROIs - four in the thalamus and two in the STG - were selected. Our findings unveiled heightened positive functional connectivity in Schizophrenic patients, particularly toward the anterior STG (aSTG) and posterior STG (pSTG). Notably, positive connectivity emerged between the medial division of mediodorsal thalamic nuclei (MDm) and the visual network, while increased functional connectivity linked the ventral lateral nucleus of the thalamus with aSTG. This accentuated functional connectivity potentially influences these sub-regions, contributing to dysfunctions and manifesting symptoms such as language and learning difficulties alongside hallucinations. This study underscores the importance of delineating sub-regional dynamics to enhance our understanding of the nuanced neural alterations in Schizophrenia, paving the way for more targeted interventions and therapeutic approaches.

PMID:39669226 | PMC:PMC11635424 | DOI:10.1515/tnsci-2022-0356

Unstable dynamic brain state and reduced cerebro-cerebellar modularity in old people with subjective cognitive decline

Thu, 12/12/2024 - 19:00

Neuroimage. 2024 Dec 10:120969. doi: 10.1016/j.neuroimage.2024.120969. Online ahead of print.

ABSTRACT

The preclinical stage of Alzheimer's Disease (AD) holds great potential for intervention, therefore, it is crucial to elucidate the neural mechanisms underlying the progression of subjective cognitive decline (SCD). Previous studies have predominantly focused on the neural changes in the cerebrum associated with SCD, but have relatively neglected the cerebellum, and the functional relationship between the cerebellum and the cerebrum. In the current study, we employed dynamic functional connectivity and large-scale brain network approaches to investigate the pathological characteristics of dynamic brain states and cerebro-cerebellar collaboration across different states between SCD (n = 32) and healthy elderly (n = 29) using resting-state fMRI. Two-way repeated measures ANOVA and permutation t-tests revealed significant group difference, with individuals with SCD exhibiting shorter state duration and more frequent transitions between states compared to healthy elderly individuals across three brain states. Additionally, individuals with SCD showed lower levels of intracerebellar functional connectivity, but higher levels of cerebellar-cerebral functional integration in the state representing cognitive processing. Furthermore, the hub nodes of the functional networks in SCD shifted between the cerebellum and cerebrum across different states. These findings indicate that SCD exhibits greater state instability but can compensate for the negative effects of early disease by integrating cerebellar and cerebral networks, thereby maintaining cognitive performance. This study enhances our theoretical understanding of cerebellar-cerebral relationship changes in the early stages of AD and provides evidence for early interventions targeting the cerebellum.

PMID:39667538 | DOI:10.1016/j.neuroimage.2024.120969

A Randomized Controlled Trial of Medial Prefrontal Cortex Theta Burst Stimulation for Cocaine Use Disorder: A Three-Month Feasibility and Brain Target-Engagement Study

Thu, 12/12/2024 - 19:00

Biol Psychiatry Cogn Neurosci Neuroimaging. 2024 Dec 10:S2451-9022(24)00376-8. doi: 10.1016/j.bpsc.2024.11.022. Online ahead of print.

ABSTRACT

BACKGROUND: Cue-induced craving precipitates relapse in drug and alcohol use disorders. Theta burst stimulation (TBS) to the left frontal pole of the medial prefrontal cortex (MPFC) has previously been shown to reduce drinking and brain reactivity to alcohol cues. This randomized, double-blind, sham-controlled target-engagement study aimed to assess whether TBS has similar effects in individuals with cocaine use disorder (CUD).

METHODS: Thirty-three participants in intensive outpatient treatment received either real or sham TBS over 10 sessions across 3 weeks (36,000 pulses total; continuous TBS, 110% resting motor threshold, 3600 pulses/session). TBS was administered on days of behavioral counseling. Twenty-five individuals completed all 10 TBS sessions. Brain reactivity to cocaine cues was measured using fMRI at baseline, 1-month, 2-months, and 3-months.

RESULTS: Cocaine abstinence during the 3-month follow-up period was greater in the real TBS group (1-month: 92.0%, 2-month: 100.0%, 3-month: 85.0%) compared to sham (1-month: 66.6%, 2-month: 66.6%, 3-month: 66.6%), though not statistically significant [1-month: 6.00, p=0.14; 2-month OR=:14.30, p=0.09, and 3-month OR=2.75, p=0.30]. However, there was a significant effect on cocaine cue reactivity (treatment effect: F1,365= 8.92, p=0.003; time*treatment interaction: F3,365=12.88, p<0.001). Real TBS reduced cocaine cue reactivity in the MPFC (F3,72=5.46, p=0.02) overall, and in the anterior cingulate (F3,72=3.03, p=0.04), and insula (F3,72=3.60, p=0.02).

CONCLUSIONS: This early-stage trial demonstrates TBS to the MPFC reduces brain reactivity to cocaine cues in key nodes of the Salience Network in treatment-seeking cocaine users. Future, well-powered trials are warranted to evaluate clinical efficacy outcomes.

PMID:39667495 | DOI:10.1016/j.bpsc.2024.11.022

A preliminary study of fMRI and the relationship with depression and anxiety in Meniere's patients

Thu, 12/12/2024 - 19:00

Am J Otolaryngol. 2024 Dec 3;46(1):104531. doi: 10.1016/j.amjoto.2024.104531. Online ahead of print.

ABSTRACT

PURPOSE: To examine alterations in Blood Oxygen Level-Dependent (BOLD) resting-state functional magnetic resonance imaging (rs-fMRI) signals, utilizing regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuation (fALFF) metrics, within activated brain regions. Additionally, this study aims to explore the relationship between these neural changes and clinical characteristics, as well as emotional states, in patients diagnosed with unilateral Meniere's disease (MD).

METHOD: The study included 24 patients diagnosed with left Meniere's disease (L-MD), 25 patients diagnosed with right Meniere's disease (R-MD), and 23 healthy control subjects. Resting-state blood‑oxygen-level-dependent functional magnetic resonance imaging (rest-BOLD-fMRI) data were preprocessed. A two-sample t-test was employed to compare the regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuation (fALFF) between the patient groups and the control group. Brain regions exhibiting significant differences were further analyzed for correlations with disease duration, vertigo severity, vertigo duration, hearing loss grade, and levels of anxiety and depression.

RESULTS: In patients with L-MD, fALFF values were significantly decreased in the right cerebellar hemisphere, middle occipital gyrus, among other regions. In patients with right-sided Ménière's disease (R-MD), fractional amplitude of low-frequency fluctuation (fALFF) values were elevated in the right middle inferior temporal gyrus and fusiform gyrus. Regional homogeneity (ReHo) values exhibited both increases and decreases in the temporal gyrus, parahippocampal gyrus, occipital gyrus, superior marginal gyrus, anterior central gyrus, and fusiform gyrus. In studies examining relational aspects, the parahippocampal gyrus, inferior temporal gyrus, middle occipital gyrus, superior middle occipital gyrus, superior marginal gyrus, and occipital gyrus demonstrated positive or negative correlations with clinical characteristics and emotional states.

CONCLUSIONS: Patients with unilateral Meniere's disease (MD) exhibited both increased and decreased activation in various brain regions when compared to control subjects. A correlation was identified between these neural activation patterns and clinical characteristics, as well as emotional state, which holds significant implications for clinical treatment, prognosis, and rehabilitation strategies for MD patients.

PMID:39667311 | DOI:10.1016/j.amjoto.2024.104531

Catecholaminergic Modulation of Large-Scale Network Dynamics Is Tied to the Reconfiguration of Corticostriatal Connectivity

Thu, 12/12/2024 - 19:00

Hum Brain Mapp. 2024 Dec 1;45(17):e70086. doi: 10.1002/hbm.70086.

ABSTRACT

Large-scale brain network function is critical for healthy cognition, yet links between such network function, neurochemistry, and smaller-scale neurocircuitry are unclear. Here, we evaluated 59 healthy individuals using resting-state fMRI to determine how network-level temporal dynamics were impacted by two well-characterized pharmacotherapies targeting catecholamines: methylphenidate (20 mg) and haloperidol (2 mg)-administered via randomized, double-blind, placebo-controlled design. Network temporal dynamic changes were tested for links with drug-induced alterations in complex corticostriatal connections as this circuit is a primary site of action for both drugs. Methylphenidate increased time in the default mode network state (DMN p < 0.001) and dorsal attention network state (DAN p < 0.001) and reduced time in the frontoparietal network state (p < 0.01). Haloperidol increased time in a sensory motor-DMN state (p < 0.01). The magnitude of change in network dynamics induced by methylphenidate vs. placebo correlated with the magnitude of methylphenidate-induced rearrangement of complex corticostriatal connectivity (R = 0.32, p = 0.014). Haloperidol did not alter complex corticostriatal connectivity. Methylphenidate enhanced time in network states involved in internal and external attention (DMN and DAN, respectively), aligning with methylphenidate's established role in attention. Methylphenidate also significantly changed complex corticostriatal connectivity by altering the relative strength between multiple corticostriatal connections, indicating that methylphenidate may shift which corticostriatal connections are prioritized relative to others. Findings show that these corticostriatal circuit changes are linked with large-scale network temporal dynamics. Collectively, these findings provide a deeper understanding of large-scale network function, set a stage for mechanistic understanding of network engagement, and provide useful information to guide medication use based on network-level effects. Trial Registration: Registry name: ClinicalTrials.gov; URL: Brain Networks and Addiction Susceptibility-Full Text View-ClinicalTrials.gov; URL Plain text: https://classic.clinicaltrials.gov/ct2/show/NCT01924468; Identifier: NCT01924468.

PMID:39665506 | DOI:10.1002/hbm.70086

Ketosis regulates K<sup>+</sup> ion channels, strengthening brain-wide signaling disrupted by age

Thu, 12/12/2024 - 19:00

Imaging Neurosci (Camb). 2024;2. doi: 10.1162/imag_a_00163. Epub 2024 May 8.

ABSTRACT

Aging is associated with impaired signaling between brain regions when measured using resting-state fMRI. This age-related destabilization and desynchronization of brain networks reverses itself when the brain switches from metabolizing glucose to ketones. Here, we probe the mechanistic basis for these effects. First, we confirmed their robustness across measurement modalities using two datasets acquired from resting-state EEG (Lifespan: standard diet, 20-80 years, N = 201; Metabolic: individually weight-dosed and calorically-matched glucose and ketone ester challenge, μ a g e = 26.9 ± 11.2 years , N = 36). Then, using a multiscale conductance-based neural mass model, we identified the unique set of mechanistic parameters consistent with our clinical data. Together, our results implicate potassium (K+) gradient dysregulation as a mechanism for age-related neural desynchronization and its reversal with ketosis, the latter finding of which is consistent with direct measurement of ion channels. As such, the approach facilitates the connection between macroscopic brain activity and cellular-level mechanisms.

PMID:39664914 | PMC:PMC11633768 | DOI:10.1162/imag_a_00163

Drivers of resting-state fMRI heterogeneity in traumatic brain injury across injury characteristics and imaging methods: a systematic review and semiquantitative analysis

Thu, 12/12/2024 - 19:00

Front Neurol. 2024 Nov 27;15:1487796. doi: 10.3389/fneur.2024.1487796. eCollection 2024.

ABSTRACT

Traumatic brain injury (TBI) is common and costly. Although neuroimaging modalities such as resting-state functional MRI (rsfMRI) promise to differentiate injured from healthy brains and prognosticate long-term outcomes, the field suffers from heterogeneous findings. To assess whether this heterogeneity stems from variability in the TBI populations studied or the imaging methods used, and to determine whether a consensus exists in this literature, we performed the first systematic review of studies comparing rsfMRI functional connectivity (FC) in patients with TBI to matched controls for seven canonical brain networks across injury severity, age, chronicity, population type, and various imaging methods. Searching PubMed, Web of Science, Google Scholar, and ScienceDirect, 1,105 manuscripts were identified, 50 fulfilling our criteria. Across these manuscripts, 179 comparisons were reported between a total of 1,397 patients with TBI and 1,179 matched controls. Collapsing across injury characteristics, imaging methods, and networks, there were roughly equal significant to null findings and increased to decreased connectivity differences reported. Whereas most factors did not explain these mixed findings, stratifying across severity and chronicity, separately, showed a trend of increased connectivity at higher severities and greater chronicities of TBI. Among methodological factors, studies were more likely to find connectivity differences when scans were longer than 360 s, custom image processing pipelines were used, and when patients kept their eyes open versus closed during scans. We offer guidelines to address this variability, focusing on aspects of study design and rsfMRI acquisition to move the field toward reproducible results with greater potential for clinical translation.

PMID:39664747 | PMC:PMC11631856 | DOI:10.3389/fneur.2024.1487796

The Impact of Hyperbaric Oxygen Therapy on Functional and Structural Plasticity in Rats With Spinal Cord Injury

Thu, 12/12/2024 - 19:00

Brain Behav. 2024 Dec;14(12):e70196. doi: 10.1002/brb3.70196.

ABSTRACT

INTRODUCTION: Spinal cord injury (SCI) can result in sensory and locomotor function loss below the injured segment. Hyperbaric oxygen therapy (HBOT) has been proven to alleviate SCI. This study aims to establish a reproducible rat model of SCI and investigate the impact of HBOT on alterations in brain neuronal activity and neuromotor function in this experimental rat SCI model using resting-state functional magnetic resonance imaging (rs-fMRI).

METHODS: This is a prospective randomized controlled animal trial. A total number of 27 female SD rats were randomly divided into three groups: sham (n = 9), SCI (n = 9), and HBO (n = 9). rs-fMRI was utilized to assess regional homogeneity (ReHo) values and functional connectivity (FC) strength over the whole brain with the motor cortex as seeds. Correlation between neuroimaging characteristics and behavioral assessment was calculated. We examined Nissl body, NeuN, and caspase-3 expression in relevant brain regions.

RESULTS: Following SCI, reduced ReHo values were observed in the left primary somatosensory cortex, left striatum, right agranular insular cortex, and partial cortex in the limbic system, which was reversed after HBOT. HBOT could increase FC strength between the motor cortex and other brain regions, including the left secondary motor cortex, right basal forebrain region, bilateral primary somatosensory cortex, bilateral thalamus, and another partial cortex in the limbic system. BBB scale scores showed that HBOT promoted motor function recovery in SCI rats. The ReHo and FC values in all positive clusters were positively correlated with BBB scores. By histopathological analysis, our study found that HBOT could reduce apoptotic proteins, increase the number of neurons, and protect neuronal function in brain regions with significant ReHo and FC alteration in SCI rats.

CONCLUSION: This study reveals that HBOT facilitates functional and structural plasticity in the brain, contributing to the recovery of motor function in rats with SCI.

PMID:39663753 | DOI:10.1002/brb3.70196