Most recent paper

Ketamine induces multiple individually distinct whole-brain functional connectivity signatures

Wed, 04/17/2024 - 18:00

Elife. 2024 Apr 17;13:e84173. doi: 10.7554/eLife.84173.


BACKGROUND: Ketamine has emerged as one of the most promising therapies for treatment-resistant depression. However, inter-individual variability in response to ketamine is still not well understood and it is unclear how ketamine's molecular mechanisms connect to its neural and behavioral effects.

METHODS: We conducted a single-blind placebo-controlled study, with participants blinded to their treatment condition. 40 healthy participants received acute ketamine (initial bolus 0.23 mg/kg, continuous infusion 0.58 mg/kg/hr). We quantified resting-state functional connectivity via data-driven global brain connectivity and related it to individual ketamine-induced symptom variation and cortical gene expression targets.

RESULTS: We found that: (i) both the neural and behavioral effects of acute ketamine are multi-dimensional, reflecting robust inter-individual variability; (ii) ketamine's data-driven principal neural gradient effect matched somatostatin (SST) and parvalbumin (PVALB) cortical gene expression patterns in humans, while the mean effect did not; and (iii) behavioral data-driven individual symptom variation mapped onto distinct neural gradients of ketamine, which were resolvable at the single-subject level.

CONCLUSIONS: These results highlight the importance of considering individual behavioral and neural variation in response to ketamine. They also have implications for the development of individually precise pharmacological biomarkers for treatment selection in psychiatry.

FUNDING: This study was supported by NIH grants DP5OD012109-01 (A.A.), 1U01MH121766 (A.A.), R01MH112746 (J.D.M.), 5R01MH112189 (A.A.), 5R01MH108590 (A.A.), NIAAA grant 2P50AA012870-11 (A.A.); NSF NeuroNex grant 2015276 (J.D.M.); Brain and Behavior Research Foundation Young Investigator Award (A.A.); SFARI Pilot Award (J.D.M., A.A.); Heffter Research Institute (Grant No. 1-190420) (FXV, KHP); Swiss Neuromatrix Foundation (Grant No. 2016-0111) (FXV, KHP); Swiss National Science Foundation under the framework of Neuron Cofund (Grant No. 01EW1908) (KHP); Usona Institute (2015 - 2056) (FXV).


PMID:38629811 | DOI:10.7554/eLife.84173

Non-invasive suppression of the human nucleus accumbens (NAc) with transcranial focused ultrasound (tFUS) modulates the reward network: a pilot study

Wed, 04/17/2024 - 18:00

Front Hum Neurosci. 2024 Apr 2;18:1359396. doi: 10.3389/fnhum.2024.1359396. eCollection 2024.


BACKGROUND: The nucleus accumbens (NAc) is a key node of the brain reward circuit driving reward-related behavior. Dysregulation of NAc has been demonstrated to contribute to pathological markers of addiction in substance use disorder (SUD) making it a potential therapeutic target for brain stimulation. Transcranial focused ultrasound (tFUS) is an emerging non-invasive brain stimulation approach that can modulate deep brain regions with a high spatial resolution. However, there is currently no evidence showing how the brain activity of NAc and brain functional connectivity within the reward network neuromodulated by tFUS on the NAc.

METHODS: In this pilot study, we carried out a single-blind, sham-controlled clinical trial using functional magnetic resonance imaging (fMRI) to investigate the underlying mechanism of tFUS neuromodulating the reward network through NAc in ten healthy adults. Specifically, the experiment consists of a 20-min concurrent tFUS/fMRI scan and two 24-min resting-state fMRI before and after the tFUS session.

RESULTS: Firstly, our results demonstrated the feasibility and safety of 20-min tFUS on NAc. Additionally, our findings demonstrated that bilateral NAc was inhibited during tFUS on the left NAc compared to sham. Lastly, increased functional connectivity between the NAc and medial prefrontal cortex (mPFC) was observed after tFUS on the left NAc, but no changes for the sham group.

CONCLUSION: Delivering tFUS to the NAc can modulate brain activations and functional connectivity within the reward network. These preliminary findings suggest that tFUS could be potentially a promising neuromodulation tool for the direct and non-invasive management of the NAc and shed new light on the treatment for SUD and other brain diseases that involve reward processing.

PMID:38628972 | PMC:PMC11018963 | DOI:10.3389/fnhum.2024.1359396

Resting state networks of awake adolescent and adult squirrel monkeys using ultra-high field (9.4T) functional magnetic resonance imaging

Tue, 04/16/2024 - 18:00

eNeuro. 2024 Apr 16:ENEURO.0173-23.2024. doi: 10.1523/ENEURO.0173-23.2024. Online ahead of print.


Resting state networks (RSNs) are increasingly forwarded as candidate biomarkers for neuropsychiatric disorders. Such biomarkers may provide objective measures for evaluating novel therapeutic interventions in nonhuman primates often used in translational neuroimaging research. This study aimed to characterize the RSNs of awake squirrel monkeys and compare the characteristics of those networks in adolescent and adult subjects. Twenty-seven squirrel monkeys (n=12 adolescents [6 male/6 female] ∼2.5 years and n=15 adults [7 male/8 female] ∼9.5 years) were gradually acclimated to awake scanning procedures; whole-brain fMRI images were acquired with a 9.4 Tesla scanner. Group level independent component (ICA) analysis (30 ICs) with dual regression was used to detect and compare RSNs. Twenty ICs corresponding to physiologically meaningful networks representing a range of neural functions, including motor, sensory, reward, and cognitive processes were identified in both adolescent and adult monkeys. The reproducibility of these RSNs was evaluated across several ICA model orders. Adults showed a trend for greater connectivity compared to adolescent subjects in two of the networks of interest: (1) in the right occipital region with the OFC network and (2) in the left temporal cortex, bilateral occipital cortex, and cerebellum with the posterior cingulate network. However, when age was entered into the above model, this trend for significance was lost. These results demonstrate that squirrel monkey RSNs are stable and consistent with RSNs previously identified in humans, rodents, and other nonhuman primate species. These data also identify several networks in adolescence that are conserved and others that may change into adulthood.Significance Statement Functional magnetic resonance imaging procedures have revealed important information about how the brain is modified by experimental manipulations, disease states, and aging throughout the lifespan. Preclinical neuroimaging, especially in nonhuman primates, has become a frequently used means to answer targeted questions related to brain resting-state functional connectivity. The present study characterized resting state networks (RSNs) in adult and adolescent squirrel monkeys; twenty RSNs corresponding to networks representing a range of neural functions were identified. The RSNs identified here can be utilized in future studies examining the effects of experimental manipulations on brain connectivity in squirrel monkeys. These data also may be useful for comparative analysis with other primate species to provide an evolutionary perspective for understanding brain function and organization.

PMID:38627065 | DOI:10.1523/ENEURO.0173-23.2024

Cost-Sensitive Weighted Contrastive Learning Based on Graph Convolutional Networks for Imbalanced Alzheimer's Disease Staging

Tue, 04/16/2024 - 18:00

IEEE Trans Med Imaging. 2024 Apr 16;PP. doi: 10.1109/TMI.2024.3389747. Online ahead of print.


Identifying the progression stages of Alzheimer's disease (AD) can be considered as an imbalanced multi-class classification problem in machine learning. It is challenging due to the class imbalance issue and the heterogeneity of the disease. Recently, graph convolutional networks (GCNs) have been successfully applied in AD classification. However, these works did not handle the class imbalance issue in classification. Besides, they ignore the heterogeneity of the disease. To this end, we propose a novel cost-sensitive weighted contrastive learning method based on graph convolutional networks (CSWCL-GCNs) for imbalanced AD staging using resting-state functional magnetic resonance imaging (rs-fMRI). The proposed method is developed on a multi-view graph constructed using the functional connectivity (FC) and high-order functional connectivity (HOFC) features of the subjects. A novel cost-sensitive weighted contrastive learning procedure is proposed to capture discriminative information from the minority classes, encouraging the samples in the minority class to provide adequate supervision. Considering the heterogeneity of the disease, the weights of the negative pairs are introduced into contrastive learning and they are computed based on the distance to class prototypes, which are automatically learned from the training data. Meanwhile, the cost-sensitive mechanism is further introduced into contrastive learning to handle the class imbalance issue. The proposed CSWCL-GCN is evaluated on 720 subjects (including 184 NCs, 40 SMC patients, 208 EMCI patients, 172 LMCI patients and 116 AD patients) from the ADNI (Alzheimer's Disease Neuroimaging Initiative). Experimental results show that the proposed CSWCL-GCN outperforms state-of-the-art methods on the ADNI database.

PMID:38625767 | DOI:10.1109/TMI.2024.3389747

Smoking Progression and Nicotine-Enhanced Reward Sensitivity Predicted by Resting-State Functional Connectivity in Salience and Executive Control Networks

Tue, 04/16/2024 - 18:00

Nicotine Tob Res. 2024 Apr 16:ntae084. doi: 10.1093/ntr/ntae084. Online ahead of print.


INTRODUCTION: The neural underpinnings underlying individual differences in nicotine-enhanced reward sensitivity and smoking progression are poorly understood. Thus, we investigated whether brain resting-state functional connectivity (rsFC) during smoking abstinence predicts nicotine-enhanced reward sensitivity and smoking progression in young light smokers. We hypothesized that high rsFC between brain areas with high densities of nicotinic receptors (insula, anterior cingulate cortex [ACC], hippocampus, thalamus) and areas involved in reward-seeking (nucleus accumbens [NAcc], prefrontal cortex [PFC]) would predict nicotine-enhanced reward sensitivity and smoking progression.

METHODS: Young light smokers (N=64, age 18-24, M = 1.89 cigarettes/day) participated in the study. These individuals smoked between 5 to 35 cigarettes per week and lifetime use never exceeded 35 cigarettes per week. Their rsFC was assessed using functional magnetic resonance imaging after 14-hour nicotine-deprivation. Subjects also completed a probabilistic reward task after smoking a placebo on one day and a regular cigarette on another day.

RESULTS: The probabilistic-reward-task assessed greater nicotine-enhanced reward sensitivity was associated with greater rsFC between the right anterior PFC and right NAcc, but with reduced rsFC between the ACC and left inferior prefrontal gyrus and the insula and ACC. Decreased rsFC within the salience network (ACC and insula) predicted increased smoking progression across 18 months and greater nicotine-enhanced reward sensitivity.

CONCLUSIONS: These findings provide the first evidence that differences in rsFCs in young light smokers are associated with nicotine-enhanced reward sensitivity and smoking progression.

IMPLICATIONS: Weaker rsFC within the salience network predicted greater nicotine-enhanced reward sensitivity and smoking progression. These findings suggest that salience network rsFC and drug-enhanced reward sensitivity may be useful tools and potential endophenotypes for reward sensitivity and drug-dependence research.

PMID:38624067 | DOI:10.1093/ntr/ntae084

Neurobehavioral mechanisms influencing the association between generativity, the desire to promote well-being of younger generations, and purpose in life in older adults at risk for Alzheimer's disease

Tue, 04/16/2024 - 18:00

J Gerontol B Psychol Sci Soc Sci. 2024 Apr 16:gbae060. doi: 10.1093/geronb/gbae060. Online ahead of print.


OBJECTIVES: Generativity, the desire and action to improve the well-being of younger generations, is associated with purpose in life among older adults. However, the neurobehavioral factors supporting the relationship between generativity and purpose in life remain unknown. This study aims to identify the functional neuroanatomy of generativity and mechanisms linking generativity with purpose in life in at-risk older adults.

METHODS: Fifty-eight older adults (mean age = 70.8, SD = 5.03, 45 females) with a family history of Alzheimer's disease (AD) were recruited from the PREVENT-AD cohort. Participants underwent brain imaging and completed questionnaires assessing generativity, social support, and purpose in life. Mediation models examined whether social support mediated the association between generativity and purpose in life. Seed-to-voxel analyses investigated the association between generativity and resting-state functional connectivity (rsFC) to the ventromedial prefrontal cortex (vmPFC) and ventral striatum (VS), and whether this rsFC moderated the relationship between generativity and purpose in life.

RESULTS: Affectionate social support mediated the association between generative desire and purpose in life. Generative desire was associated with rsFC between VS and precuneus, and, vmPFC and right dorsolateral prefrontal cortex (rdlPFC). The vmPFC-rdlPFC rsFC moderated the association between generative desire and purpose in life.

DISCUSSION: These findings provide insight into how the brain supports complex social behavior and, separately, purpose in life in at-risk aging. Affectionate social support may be a putative target process to enhance purpose in life in older adults. This knowledge contributes to future developments of personalized interventions that promote healthy aging.

PMID:38623965 | DOI:10.1093/geronb/gbae060

Fractional amplitude of low-frequency fluctuation and voxel-mirrored homotopic connectivity in patients with persistent postural-perceptual dizziness: resting-state functional magnetic resonance imaging study

Tue, 04/16/2024 - 18:00

Brain Connect. 2024 Apr 16. doi: 10.1089/brain.2023.0071. Online ahead of print.


PURPOSE: Persistent postural-perception dizziness (PPPD) is a chronic subjective form of dizziness characterized by the exacerbation of dizziness with active or passive movement, complex visual stimuli, and upright posture. Therefore, we aimed to analyze the resting-state functional magnetic resonance imaging (fMRI) in patients with PPPD using fractional amplitude of low-frequency fluctuation (fALFF) and voxel-mirrored homotopic connectivity (VMHC) and evaluate the correlation between abnormal regions in the brain and clinical features to investigate the pathogenesis of PPPD.

METHODS: Thirty patients with PPPD (19 females and 11 males) and 30 healthy controls (HC) (18 females and 12 males) were closely matched for age and sex. The fALFF and VMHC methods were used to investigate differences in fMRI (BOLD sequences) between the PPPD and HC groups and to explore the associations between areas of functional abnormality and clinical characteristics (Dizziness, Anxiety, Depression, and Duration).

RESULT: Compared to the HC group, patients with PPPD displayed different functional change patterns, with increased fALFF in the right precuneus and decreased VMHC in the bilateral precuneus. Additionally, patients with PPPD had a positive correlation between precuneus fALFF values and dizziness handicap inventory (DHI) scores, and a negative correlation between VMHC values and the disease duration.

CONCLUSIONS: Precuneus dysfunction was observed in patients with PPPD. The fALFF values correlated with the degree of dizziness in PPPD, and changes in VMHC values were associated with the duration of dizziness, suggesting that fMRI changes in the precuneus of patients could be used as a potential imaging marker for PPPD.

PMID:38623770 | DOI:10.1089/brain.2023.0071

Simultaneous EEG-fMRI Investigation of Rhythm-Dependent Thalamo-Cortical Circuits Alteration in Schizophrenia

Tue, 04/16/2024 - 18:00

Int J Neural Syst. 2024 Apr 13:2450031. doi: 10.1142/S012906572450031X. Online ahead of print.


Schizophrenia is accompanied by aberrant interactions of intrinsic brain networks. However, the modulatory effect of electroencephalography (EEG) rhythms on the functional connectivity (FC) in schizophrenia remains unclear. This study aims to provide new insight into network communication in schizophrenia by integrating FC and EEG rhythm information. After collecting simultaneous resting-state EEG-functional magnetic resonance imaging data, the effect of rhythm modulations on FC was explored using what we term "dynamic rhythm information." We also investigated the synergistic relationships among three networks under rhythm modulation conditions, where this relationship presents the coupling between two brain networks with other networks as the center by the rhythm modulation. This study found FC between the thalamus and cortical network regions was rhythm-specific. Further, the effects of the thalamus on the default mode network (DMN) and salience network (SN) were less similar under alpha rhythm modulation in schizophrenia patients than in controls ([Formula: see text]). However, the similarity between the effects of the central executive network (CEN) on the DMN and SN under gamma modulation was greater ([Formula: see text]), and the degree of coupling was negatively correlated with the duration of disease ([Formula: see text], [Formula: see text]). Moreover, schizophrenia patients exhibited less coupling with the thalamus as the center and greater coupling with the CEN as the center. These results indicate that modulations in dynamic rhythms might contribute to the disordered functional interactions seen in schizophrenia.

PMID:38623649 | DOI:10.1142/S012906572450031X

Modulate the impact of the drowsiness on the resting state functional connectivity

Mon, 04/15/2024 - 18:00

Sci Rep. 2024 Apr 15;14(1):8652. doi: 10.1038/s41598-024-59476-8.


This research explores different methodologies to modulate the effects of drowsiness on functional connectivity (FC) during resting-state functional magnetic resonance imaging (RS-fMRI). The study utilized a cohort of students (MRi-Share) and classified individuals into drowsy, alert, and mixed/undetermined states based on observed respiratory oscillations. We analyzed the FC group difference between drowsy and alert individuals after five different processing methods: the reference method, two based on physiological and a global signal regression of the BOLD time series signal, and two based on Gaussian standardizations of the FC distribution. According to the reference method, drowsy individuals exhibit higher cortico-cortical FC than alert individuals. First, we demonstrated that each method reduced the differences between drowsy and alert states. The second result is that the global signal regression was quantitively the most effective, minimizing significant FC differences to only 3.3% of the total FCs. However, one should consider the risks of overcorrection often associated with this methodology. Therefore, choosing a less aggressive form of regression, such as the physiological method or Gaussian-based approaches, might be a more cautious approach. Third and last, using the Gaussian-based methods, cortico-subcortical and intra-default mode network (DMN) FCs were significantly greater in alert than drowsy subjects. These findings bear resemblance to the anticipated patterns during the onset of sleep, where the cortex isolates itself to assist in transitioning into deeper slow wave sleep phases, simultaneously disconnecting the DMN.

PMID:38622265 | DOI:10.1038/s41598-024-59476-8

Subtitled speech: the neural mechanisms of ticker-tape synaesthesia

Mon, 04/15/2024 - 18:00

Brain. 2024 Apr 15:awae114. doi: 10.1093/brain/awae114. Online ahead of print.


Reading acquisition modifies areas of the brain associated with vision, with language, and their connections. Those changes enable reciprocal translation between orthography, and word sounds and meaning. Individual variability in the pre-existing cerebral substrate contributes to the range of eventual reading abilities, extending to atypical developmental patterns, including dyslexia and reading-related synesthesias. The present study is devoted to the little-studied but highly informative ticker-tape synesthesia (TTS), in which speech perception triggers the vivid and irrepressible perception of words in their written form in the mind's eye. We scanned a group of 17 synesthetes and 17 matched controls with functional MRI, while they listened to spoken sentences, words, numbers, or pseudowords (Experiment 1), viewed images and written words (Experiment 2), and were at rest (Experiment 3). First, we found direct correlates of the TTS phenomenon: during speech perception, as TTS was active, synesthetes showed over-activation of left perisylvian regions supporting phonology, and of the occipitotemporal Visual Word Form Area (VWFA), where orthography is represented. Second, we brought support to the hypothesis that TTS results from atypical relationships between spoken and written language processing: the TTS-related regions overlap closely with cortices activated during reading, and the overlap of speech-related and reading-related areas is larger in synesthetes than in controls. Furthermore the regions over-activated in TTS overlap with regions under-activated in dyslexia. Third, during resting state, that is in the absence of current TTS, synesthetes showed increased functional connectivity between left prefrontal and bilateral occipital regions. This pattern may reflect a lowered threshold for conscious access to visual mental contents, and may implement a non-specific predisposition to all synesthesias with a visual content. Those data provide a rich and coherent account of TTS as a non-detrimental developmental condition created by the interaction of reading acquisition with an atypical cerebral substrate.

PMID:38620012 | DOI:10.1093/brain/awae114

Integration of temporal & spatial properties of dynamic functional connectivity based on two-directional two-dimensional principal component analysis for disease analysis

Mon, 04/15/2024 - 18:00

PeerJ. 2024 Apr 9;12:e17078. doi: 10.7717/peerj.17078. eCollection 2024.


Dynamic functional connectivity, derived from resting-state functional magnetic resonance imaging (rs-fMRI), has emerged as a crucial instrument for investigating and supporting the diagnosis of neurological disorders. However, prevalent features of dynamic functional connectivity predominantly capture either temporal or spatial properties, such as mean and global efficiency, neglecting the significant information embedded in the fusion of spatial and temporal attributes. In addition, dynamic functional connectivity suffers from the problem of temporal mismatch, i.e., the functional connectivity of different subjects at the same time point cannot be matched. To address these problems, this article introduces a novel feature extraction framework grounded in two-directional two-dimensional principal component analysis. This framework is designed to extract features that integrate both spatial and temporal properties of dynamic functional connectivity. Additionally, we propose to use Fourier transform to extract temporal-invariance properties contained in dynamic functional connectivity. Experimental findings underscore the superior performance of features extracted by this framework in classification experiments compared to features capturing individual properties.

PMID:38618569 | PMC:PMC11011592 | DOI:10.7717/peerj.17078

Somatomotor-visual resting state functional connectivity increases after 2 years in the UK Biobank longitudinal cohort

Mon, 04/15/2024 - 18:00

J Med Imaging (Bellingham). 2024 Mar;11(2):024010. doi: 10.1117/1.JMI.11.2.024010. Epub 2024 Apr 12.


PURPOSE: Functional magnetic resonance imaging (fMRI) and functional connectivity (FC) have been used to follow aging in both children and older adults. Robust changes have been observed in children, in which high connectivity among all brain regions changes to a more modular structure with maturation. We examine FC changes in older adults after 2 years of aging in the UK Biobank (UKB) longitudinal cohort.

APPROACH: We process fMRI connectivity data using the Power264 atlas and then test whether the average internetwork FC changes in the 2722-subject longitudinal cohort are statistically significant using a Bonferroni-corrected t-test. We also compare the ability of Power264 and UKB-provided, independent component analysis (ICA)-based FC to determine which of a longitudinal scan pair is older. Finally, we investigate cross-sectional FC changes as well as differences due to differing scanner tasks in the UKB, Philadelphia Neurodevelopmental Cohort, and Alzheimer's Disease Neuroimaging Initiative datasets.

RESULTS: We find a 6.8% average increase in somatomotor network (SMT)-visual network (VIS) connectivity from younger to older scans (corrected p<10-15) that occurs in male, female, older subject (>65 years old), and younger subject (<55 years old) groups. Among all internetwork connections, the average SMT-VIS connectivity is the best predictor of relative scan age. Using the full FC and a training set of 2000 subjects, one is able to predict which scan is older 82.5% of the time using either the full Power264 FC or the UKB-provided ICA-based FC.

CONCLUSIONS: We conclude that SMT-VIS connectivity increases with age in the UKB longitudinal cohort and that resting state FC increases with age in the UKB cross-sectional cohort.

PMID:38618171 | PMC:PMC11009525 | DOI:10.1117/1.JMI.11.2.024010

Vulnerable brain regions in adolescent major depressive disorder: A resting-state functional magnetic resonance imaging activation likelihood estimation meta-analysis

Mon, 04/15/2024 - 18:00

World J Psychiatry. 2024 Mar 19;14(3):456-466. doi: 10.5498/wjp.v14.i3.456. eCollection 2024 Mar 19.


BACKGROUND: Adolescent major depressive disorder (MDD) is a significant mental health concern that often leads to recurrent depression in adulthood. Resting-state functional magnetic resonance imaging (rs-fMRI) offers unique insights into the neural mechanisms underlying this condition. However, despite previous research, the specific vulnerable brain regions affected in adolescent MDD patients have not been fully elucidated.

AIM: To identify consistent vulnerable brain regions in adolescent MDD patients using rs-fMRI and activation likelihood estimation (ALE) meta-analysis.

METHODS: We performed a comprehensive literature search through July 12, 2023, for studies investigating brain functional changes in adolescent MDD patients. We utilized regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF) and fractional ALFF (fALFF) analyses. We compared the regions of aberrant spontaneous neural activity in adolescents with MDD vs healthy controls (HCs) using ALE.

RESULTS: Ten studies (369 adolescent MDD patients and 313 HCs) were included. Combining the ReHo and ALFF/fALFF data, the results revealed that the activity in the right cuneus and left precuneus was lower in the adolescent MDD patients than in the HCs (voxel size: 648 mm3, P < 0.05), and no brain region exhibited increased activity. Based on the ALFF data, we found decreased activity in the right cuneus and left precuneus in adolescent MDD patients (voxel size: 736 mm3, P < 0.05), with no regions exhibiting increased activity.

CONCLUSION: Through ALE meta-analysis, we consistently identified the right cuneus and left precuneus as vulnerable brain regions in adolescent MDD patients, increasing our understanding of the neuropathology of affected adolescents.

PMID:38617984 | PMC:PMC11008390 | DOI:10.5498/wjp.v14.i3.456

Low and high-order topological disruption of functional networks in multiple system atrophy with freezing of gait: A resting-state study

Sun, 04/14/2024 - 18:00

Neurobiol Dis. 2024 Apr 12:106504. doi: 10.1016/j.nbd.2024.106504. Online ahead of print.


OBJECTIVE: Freezing of gait (FOG), a specific survival-threatening gait impairment, needs to be urgently explored in patients with multiple system atrophy (MSA), which is characterized by rapid progression and death within 10 years of symptom onset. The objective of this study was to explore the topological organisation of both low- and high-order functional networks in patients with MAS and FOG.

METHOD: Low-order functional connectivity (LOFC) and high-order functional connectivity FC (HOFC) networks were calculated and further analysed using the graph theory approach in 24 patients with MSA without FOG, 20 patients with FOG, and 25 healthy controls. The relationship between brain activity and the severity of freezing symptoms was investigated in patients with FOG.

RESULTS: Regarding global topological properties, patients with FOG exhibited alterations in the whole-brain network, dorsal attention network (DAN), frontoparietal network (FPN), and default network (DMN), compared with patients without FOG. At the node level, patients with FOG showed decreased nodal centralities in sensorimotor network (SMN), DAN, ventral attention network (VAN), FPN, limbic regions, hippocampal network and basal ganglia network (BG), and increased nodal centralities in the FPN, DMN, visual network (VIN) and, cerebellar network. The nodal centralities of the right inferior frontal sulcus, left lateral amygdala and left nucleus accumbens (NAC) were negatively correlated with the FOG severity.

CONCLUSION: This study identified a disrupted topology of functional interactions at both low and high levels with extensive alterations in topological properties in MSA patients with FOG, especially those associated with damage to the FPN. These findings offer new insights into the dysfunctional mechanisms of complex networks and suggest potential neuroimaging biomarkers for FOG in patients with MSA.

PMID:38615913 | DOI:10.1016/j.nbd.2024.106504

Quantifying Apathy in Late-Life Depression: Unraveling Neurobehavioral Links through Daily Activity Patterns and Brain Connectivity Analysis

Sun, 04/14/2024 - 18:00

Biol Psychiatry Cogn Neurosci Neuroimaging. 2024 Apr 12:S2451-9022(24)00102-2. doi: 10.1016/j.bpsc.2024.04.002. Online ahead of print.


BACKGROUND: Better understanding apathy in late-life depression (LLD) would help predicting poor prognosis of the disease such as dementia. Actimetry provides an objective and ecological measure of apathy from patients' daily motor activity. We aimed to determine if patterns of motor activity were associated with apathy and brain connectivity in networks underlying goal-directed behaviors.

METHODS: Resting-state functional MRI and diffusion MRI were collected from 38 non-demented LLD subjects. Apathy was evaluated using the diagnostic criteria for apathy, the apathy evaluation scale (AES) and the apathy motivation index (AMI). Functional principal components (fPC) of motor activity were derived from actimetry recordings of 72 hours. Associations between fPC and apathy were estimated by linear regression. Subnetworks whose connectivity was significantly associated with fPC were identified via the threshold-free network-based statistics. The relationship between apathy and microstructure metrics was estimated along fibers by diffusion tensor imaging and a multicompartment model called neurite orientation dispersion and density imaging via tractometry.

RESULTS: We found two fPC associated with apathy: mean diurnal activity, negatively associated with AES, and an early chronotype, negatively associated with AMI. Mean diurnal activity was associated with increased connectivity in the default-mode, the cingulo-opercular and the frontoparietal networks, while chronotype was associated with a more heterogenous connectivity pattern in the same networks. We did not find significant associations between microstructural metrics and fPCs.

CONCLUSION: Our findings suggest that mean diurnal activity and chronotype could provide indirect ambulatory measures of apathy in LLD, associated with modified functional connectivity of brain networks underlying goal-directed behaviors.

PMID:38615911 | DOI:10.1016/j.bpsc.2024.04.002

Abnormal functional connectivity of white-matter networks and gray-white matter functional networks in patients with NMOSD

Sun, 04/14/2024 - 18:00

Brain Res Bull. 2024 Apr 12:110949. doi: 10.1016/j.brainresbull.2024.110949. Online ahead of print.


Cognitive impairment (CI) has been reported in 29-70% of patients with neuromyelitis optica spectrum disorder (NMOSD). Abnormal white matter (WM) functional networks that correlate with cognitive functions have not been studied well in patients with NMOSD. The aim of the current study was to investigate functional connectivity (FC), spontaneous activity, and functional covariance connectivity (FCC) abnormalities of WM functional networks in patients with NMOSD and their correlation with cognitive performance. Twenty-four patients with NMOSD and 24 healthy controls (HCs) were included in the study. Participants underwent brain resting-state functional magnetic resonance imaging (fMRI) and the Montreal Cognitive Assessment (MoCA). Eight WM networks and nine gray matter (GM) networks were created. In patients, WM networks, including WM1-4, WM1-8, WM2-6, WM2-7, WM2-8, WM4-8, WM5-8 showed reduced FC (P < 0.05). All WM networks except WM1 showed decreased spontaneous activity (P < 0.05). The major GM networks demonstrated increased/decreased FC (P < 0.05), whereas GM7-WM7, GM8-WM4, GM8-WM6 and GM8-WM8 displayed decreased FC (P < 0.05). The MoCA results showed that two-thirds (16/24) of the patients had CI. FC and FCC in WM networks were correlated negatively with the MoCA scores (P < 0.05). WM functional networks are multi-layered. Abnormal FC of WM functional networks and GM functional networks may be responsible for CI.

PMID:38615889 | DOI:10.1016/j.brainresbull.2024.110949

Modular organization of functional brain networks in patients with degenerative cervical myelopathy

Sat, 04/13/2024 - 18:00

Sci Rep. 2024 Apr 13;14(1):8593. doi: 10.1038/s41598-024-58764-7.


Previous studies have indicated that brain functional plasticity and reorganization in patients with degenerative cervical myelopathy (DCM). However, the effects of cervical cord compression on the functional integration and separation between and/or within modules remain unclear. This study aimed to address these questions using graph theory. Functional MRI was conducted on 46 DCM patients and 35 healthy controls (HCs). The intra- and inter-modular connectivity properties of the whole-brain functional network and nodal topological properties were then calculated using theoretical graph analysis. The difference in categorical variables between groups was compared using a chi-squared test, while that between continuous variables was evaluated using a two-sample t-test. Correlation analysis was conducted between modular connectivity properties and clinical parameters. Modules interaction analyses showed that the DCM group had significantly greater inter-module connections than the HCs group (DMN-FPN: t = 2.38, p = 0.02); inversely, the DCM group had significantly lower intra-module connections than the HCs group (SMN: t = - 2.13, p = 0.036). Compared to HCs, DCM patients exhibited higher nodal topological properties in the default-mode network and frontal-parietal network. In contrast, DCM patients exhibited lower nodal topological properties in the sensorimotor network. The Japanese Orthopedic Association (JOA) score was positively correlated with inter-module connections (r = 0.330, FDR p = 0.029) but not correlated with intra-module connections. This study reported alterations in modular connections and nodal centralities in DCM patients. Decreased nodal topological properties and intra-modular connection in the sensory-motor regions may indicate sensory-motor dysfunction. Additionally, increased nodal topological properties and inter-modular connection in the default mode network and frontal-parietal network may serve as a compensatory mechanism for sensory-motor dysfunction in DCM patients. This could provide an implicative neural basis to better understand alterations in brain networks and the patterns of changes in brain plasticity in DCM patients.

PMID:38615051 | PMC:PMC11016091 | DOI:10.1038/s41598-024-58764-7

Causal Interactions in Brain Networks Predict Pain Levels in Trigeminal Neuralgia

Sat, 04/13/2024 - 18:00

Brain Res Bull. 2024 Apr 11:110947. doi: 10.1016/j.brainresbull.2024.110947. Online ahead of print.


Trigeminal neuralgia (TN) is a highly debilitating facial pain condition. Magnetic resonance imaging (MRI) is the main method for generating insights into the central mechanisms of TN pain in humans. Studies have found both structural and functional abnormalities in various brain structures in TN patients as compared with healthy controls. Whereas studies have also examined aberrations in brain networks in TN, no studies have to date investigated causal interactions in these brain networks and related these causal interactions to the levels of TN pain. We recorded fMRI data from 39 TN patients who either rested comfortably in the scanner during the resting state session or tracked their pain levels during the pain tracking session. Applying Granger causality to analyze the data and requiring consistent findings across the two scanning sessions, we found 5 causal interactions, including: (1) Thalamus → dACC, (2) Caudate → Inferior temporal gyrus, (3) Precentral gyrus → Inferior temporal gyrus, (4) Supramarginal gyrus → Inferior temporal gyrus, and (5) Bankssts → Inferior temporal gyrus, that were consistently associated with the levels of pain experienced by the patients. Utilizing these 5 causal interactions as predictor variables and the pain score as the predicted variable in a linear multiple regression model, we found that in both pain tracking and resting state sessions, the model was able to explain ~36% of the variance in pain levels, and importantly, the model trained on the 5 causal interaction values from one session was able to predict pain levels using the 5 causal interaction values from the other session, thereby cross-validating the models. These results, obtained by applying novel analytical methods to neuroimaging data, provide important insights into the pathophysiology of TN and could inform future studies aimed at developing innovative therapies for treating TN.

PMID:38614409 | DOI:10.1016/j.brainresbull.2024.110947

Inverted U-shape-like functional connectivity alterations in cognitive resting-state networks depending on exercise intensity: An fMRI study

Sat, 04/13/2024 - 18:00

Brain Cogn. 2024 Apr 12;177:106156. doi: 10.1016/j.bandc.2024.106156. Online ahead of print.


Acute physical activity influences cognitive performance. However, the relationship between exercise intensity, neural network activity, and cognitive performance remains poorly understood. This study examined the effects of different exercise intensities on resting-state functional connectivity (rsFC) and cognitive performance. Twenty male athletes (27.3 ± 3.6 years) underwent cycling exercises of different intensities (high, low, rest/control) on different days in randomized order. Before and after, subjects performed resting-state functional magnetic resonance imaging and a behavioral Attention Network Test (ANT). Independent component analysis and Linear mixed effects models examined rsFC changes within ten resting-state networks. No significant changes were identified in ANT performance. Resting-state analyses revealed a significant interaction in the Left Frontoparietal Network, driven by a non-significant rsFC increase after low-intensity and a significant rsFC decrease after high-intensity exercise, suggestive of an inverted U-shape relationship between exercise intensity and rsFC. Similar but trend-level rsFC interactions were observed in the Dorsal Attention Network (DAN) and the Cerebellar Basal Ganglia Network. Explorative correlation analysis revealed a significant positive association between rsFC increases in the right superior parietal lobule (part of DAN) and better ANT orienting in the low-intensity condition. Results indicate exercise intensity-dependent subacute rsFC changes in cognition-related networks, but their cognitive-behavioral relevance needs further investigation.

PMID:38613926 | DOI:10.1016/j.bandc.2024.106156

The relationship between the resting state functional connectivity and social cognition in schizophrenia: Results from the Italian Network for Research on Psychoses

Sat, 04/13/2024 - 18:00

Schizophr Res. 2024 Apr 12;267:330-340. doi: 10.1016/j.schres.2024.04.009. Online ahead of print.


Deficits in social cognition (SC) interfere with recovery in schizophrenia (SZ) and may be related to resting state brain connectivity. This study aimed at assessing the alterations in the relationship between resting state functional connectivity and the social-cognitive abilities of patients with SZ compared to healthy subjects. We divided the brain into 246 regions of interest (ROI) following the Human Healthy Volunteers Brainnetome Atlas. For each participant, we calculated the resting-state functional connectivity (rsFC) in terms of degree centrality (DC), which evaluates the total strength of the most powerful coactivations of every ROI with all other ROIs during rest. The rs-DC of the ROIs was correlated with five measures of SC assessing emotion processing and mentalizing in 45 healthy volunteers (HVs) chosen as a normative sample. Then, controlling for symptoms severity, we verified whether these significant associations were altered, i.e., absent or of opposite sign, in 55 patients with SZ. We found five significant differences between SZ patients and HVs: in the patients' group, the correlations between emotion recognition tasks and rsFC of the right entorhinal cortex (R-EC), left superior parietal lobule (L-SPL), right caudal hippocampus (R-c-Hipp), and the right caudal (R-c) and left rostral (L-r) middle temporal gyri (MTG) were lost. An altered resting state functional connectivity of the L-SPL, R-EC, R-c-Hipp, and bilateral MTG in patients with SZ may be associated with impaired emotion recognition. If confirmed, these results may enhance the development of non-invasive brain stimulation interventions targeting those cerebral regions to reduce SC deficit in SZ.

PMID:38613864 | DOI:10.1016/j.schres.2024.04.009