Connected Brain Regions Research Articles

Decoding Autism: Uncovering patterns in brain connectivity through sparsity analysis with rs-fMRI data

Background:In the realm of neuro-disorders, precise diagnosis and treatment rely heavily on objective imaging-based biomarker identification. This study employs a sparsity approach on resting-state fMRI to discern relevant brain region connectivity for predicting Autism. New method:The proposed methodology involves four key steps: (1) Utilizing three probabilistic brain atlases to extract functionally homogeneous brain regions from fMRI data. (2) Employing a hybrid approach of Graphical Lasso and Akaike Information Criteria to optimize sparse inverse covariance matrices for representing the brain functional connectivity. (3) Employing statistical techniques to scrutinize functional brain structures in Autism and Control subjects. (4) Implementing both autoencoder-based feature extraction and entire feature-based approach coupled with AI-based learning classifiers to predict Autism. Results:The ensemble classifier with the extracted feature set achieves a classification accuracy of 84.7% ± 0.3% using the MSDL atlas. Meanwhile, the 1D-CNN model, employing all features, exhibits superior classification accuracy of 88.6% ± 1.7% with the Smith 2009 (rsn70) atlas. Comparison with existing method (s):The proposed methodology outperforms the conventional correlation-based functional connectivity approach with a notably high prediction accuracy of more than 88%, whereas considering all direct and noisy indirect region-based functional connectivity, the traditional methods bound the prediction accuracy within 70% to 79%. Conclusions:This study underscores the potential of sparsity-based FC analysis using rs-fMRI data as a prognostic biomarker for detecting Autism.

Between neurons and networks: investigating mesoscale brain connectivity in neurological and psychiatric disorders.

The study of brain connectivity has been a cornerstone in understanding the complexities of neurological and psychiatric disorders. It has provided invaluable insights into the functional architecture of the brain and how it is perturbed in disorders. However, a persistent challenge has been achieving the proper spatial resolution, and developing computational algorithms to address biological questions at the multi-cellular level, a scale often referred to as the mesoscale. Historically, neuroimaging studies of brain connectivity have predominantly focused on the macroscale, providing insights into inter-regional brain connections but often falling short of resolving the intricacies of neural circuitry at the cellular or mesoscale level. This limitation has hindered our ability to fully comprehend the underlying mechanisms of neurological and psychiatric disorders and to develop targeted interventions. In light of this issue, our review manuscript seeks to bridge this critical gap by delving into the domain of mesoscale neuroimaging. We aim to provide a comprehensive overview of conditions affected by aberrant neural connections, image acquisition techniques, feature extraction, and data analysis methods that are specifically tailored to the mesoscale. We further delineate the potential of brain connectivity research to elucidate complex biological questions, with a particular focus on schizophrenia and epilepsy. This review encompasses topics such as dendritic spine quantification, single neuron morphology, and brain region connectivity. We aim to showcase the applicability and significance of mesoscale neuroimaging techniques in the field of neuroscience, highlighting their potential for gaining insights into the complexities of neurological and psychiatric disorders.

Longitudinal monitoring of the mouse brain reveals heterogenous network trajectories during aging

The human aging brain is characterized by changes in network efficiency that are currently best captured through longitudinal resting-state functional MRI (rs-fMRI). These studies however are challenging due to the long human lifespan. Here we show that the mouse animal model with a much shorter lifespan allows us to follow the functional network organization over most of the animal’s adult lifetime. We used a longitudinal study of the functional connectivity of different brain regions with rs-fMRI under anesthesia. Our analysis uncovers network modules similar to those reported in younger mice and in humans (i.e., prefrontal/default mode network (DMN), somatomotor and somatosensory networks). Statistical analysis reveals different patterns of network reorganization during aging. Female mice showed a pattern akin to human aging, with de-differentiation of the connectome, mainly due to increases in connectivity of the prefrontal/DMN cortical networks to other modules. Our male cohorts revealed heterogenous aging patterns with only one group confirming the de- differentiation, while the majority showed an increase in connectivity of the somatomotor cortex to the Nucleus accumbens. In summary, in line with human work, our analysis in mice supports the concept of de-differentiation in the aging mammalian brain and reveals additional trajectories in aging mice networks.

Beyond boundaries: investigating shared and divergent connectivity in the pre-/postcentral gyri and supplementary motor area.

This study aimed to comprehensively investigate the functional connectivity of key brain regions involved in motor and sensory functions, namely the precentral gyrus, postcentral gyrus and supplementary motor area (SMA). Using advanced MRI, the objective was to understand the neurophysiological integrative characterizations of these regions by examining their connectivity with eight distinct functional brain networks. The goal was to uncover their roles beyond conventional motor and sensory functions, contributing to a more holistic understanding of brain functioning. The study involved 198 healthy volunteers, with the primary methodology being functional connectivity analysis using advanced MRI techniques. The bilateral precentral gyrus, postcentral gyrus and SMA served as seed regions, and their connectivity with eight distinct brain regional functional networks was investigated. This approach allowed for the exploration of synchronized activity between these critical brain areas, shedding light on their integrated functioning and relationships with other brain networks. The study revealed a nuanced landscape of functional connectivity for the precentral gyrus, postcentral gyrus and SMA with the main functional brain networks. Despite their high functional connectedness, these regions displayed diverse functional integrations with other networks, particularly in the salience, visual, cerebellar and language networks. Specific data and statistical significance were not provided in the abstract, but the results suggested unique and distinct roles for each brain area in sophisticated cognitive tasks beyond their conventional motor and sensory functions. The study emphasized the multifaceted roles of the precentral gyrus, postcentral gyrus and SMA. Beyond their crucial involvement in motor and sensory functions, these regions exhibited varied functional integrations with different brain networks. The observed disparities, especially in the salience, visual, cerebellar and language networks, indicated a nuanced and specialized involvement of these regions in diverse cognitive functions. The study underscores the importance of considering the broader neurophysiological landscape to comprehend the intricate roles of these brain areas, contributing to ongoing efforts in unraveling the complexities of brain function.

Combining multimodal connectivity information improves modelling of pathology spread in Alzheimer's disease.

Cortical atrophy and aggregates of misfolded tau proteins are key hallmarks of Alzheimer's disease. Computational models that simulate the propagation of pathogens between connected brain regions have been used to elucidate mechanistic information about the spread of these disease biomarkers, such as disease epicentres and spreading rates. However, the connectomes that are used as substrates for these models are known to contain modality-specific false positive and false negative connections, influenced by the biases inherent to the different methods for estimating connections in the brain. In this work, we compare five types of connectomes for modelling both tau and atrophy patterns with the network diffusion model, which are validated against tau PET and structural MRI data from individuals with either mild cognitive impairment or dementia. We then test the hypothesis that a joint connectome, with combined information from different modalities, provides an improved substrate for the model. We find that a combination of multimodal information helps the model to capture observed patterns of tau deposition and atrophy better than any single modality. This is validated with data from independent datasets. Overall, our findings suggest that combining connectivity measures into a single connectome can mitigate some of the biases inherent to each modality and facilitate more accurate models of pathology spread, thus aiding our ability to understand disease mechanisms, and providing insight into the complementary information contained in different measures of brain connectivity.

Abstract WP293: Elucidating the Neuronal Basis of Diaschisis in Stroke Recovery

Numerous studies have shown that focal ischemic stroke changes cortical activity patterns, metabolism and blood flow not only in peri-infarct regions, but also in remote regions connected to the ischemic core. This phenomenon known as “diaschesis”, was predicted over 100 years ago and is presumed to play an important role in dictating the extent of stroke recovery. Although regional brain imaging studies provide some support to this idea (with caveats), direct examination of the structure and function of neurons connected to neurons lost in the infarct core, has not been adequately addressed. One reason for our lack of a detailed understanding is the methodologies to trace connected neurons and track their function/activity patterns over weeks and months time after stroke, did not exist until recently. To address this issue, we injected adeno-associated virus (AAV) into the adult mouse primary forelimb somatosensory cortex (FLS1) 2-3 weeks before induction of photothrombotic stroke. These AAVs could either be transported in a retrograde fashion to label neural inputs to the FLS1 (retro pAAV.CAG.GFP), or conversely move in an anterograde, trans-synaptic manner (AAV.Syn.Cre) to label neurons downstream of FLS1 neurons, such as in motor cortex. In the latter case, we utilized a transgenic mouse that co-expressed a cre-recombinase dependent fluorescent reporter (tdTomato), as well as a genetically encoded calcium sensor (GCaMP6s) in neurons. These dual reporters (tdTomato and GCaMP6s) allowed us to examine changes in dendritic structure as well as functional activity patterns in downstream motor neurons. Our initial findings using confocal microscopy to assess dendritic structure, indicate subtle changes in spine density in neuronal inputs and outputs of the FLS1, within the first week after stroke. Repeated in vivo imaging of calcium transients in downstream motor cortex neurons in awake mice before and after FLS1 cortex stroke, suggested a long lasting disruption in neuronal and ensemble activity patterns. These preliminary findings provide direct evidence that neurons in remotely connected brain regions suffer long-lasting impairments after stroke, thereby providing another potential target or substrate for future therapeutics to consider.

P346 Assessing Brain Morphology in Functional Gastrointestinal and Inflammatory Bowel Disorders Using Functional Magnetic Resonance Imaging (fMRI)

Abstract Background Functional gastrointestinal disorders (FGIDs) and non-specific inflammatory bowel diseases (IBD) are increasingly common in young adults. Studies have shown abnormal interhemispheric interactions in FGIDs and altered Default Mode Network (DMN) connectivity in brain regions linked to gastric sensations and emotional regulation. This study explores these neural mechanisms in FGIDs and IBDs, focusing on chronic visceral pain and its association with DMN reorganization. Methods The study included patients with functional dyspepsia (FD), N=18; irritable bowel syndrome (IBS), N=20 and IBD, N=18 alongside a control group of 18 healthy volunteers. Selection criteria included the Rome III Criteria for FGIDs and various diagnostic tests for IBDs. MRI scans were conducted using a 3T Achieva TX Scanner, applying standard T1 and T2 sequences without contrast agents. Functional imaging utilized T2 Gradient Echo-Planar Imaging. Results DMN analysis showed no anterior-posterior split. Significant differences were observed in the IBD group compared to controls, particularly in the left superior frontal gyrus. When comparing all patient groups with controls, increased DMN connectivity was noted in the left cingulum and supplementary motor area. These areas were also significant when comparing only FGIDs patients with controls, indicating altered DMN connectivity in these disorders. Please see: Figure 1 and Table 1. Conclusion The study highlights differences in DMNs between patient and control groups, especially in the left superior frontal gyrus, left cingulum, and left supplementary motor area. All disease groups showed variations from controls in the DMN pattern within the left cingulum. Significant differences in the DMN of the supplementary motor area were observed in functional gastric disease groups compared to controls. These findings suggest a link between brain areas involved in sensorimotor processes and symptoms of FD and IBS, providing insights into the neural basis of these conditions. Despite varied changes, common features differentiating the entire study group from healthy controls were identified. This condensed version focuses on the key aspects of your original text, ensuring that the main findings and methodology are clearly presented within the character limit.

CHANGES IN FUNCTIONAL CONNECTIVITY FOLLOWING INTENSIVE ATTENTION TRAINING IN PATIENTS WITH TRAUMATIC BRAIN INJURY. A PILOT STUDY.

To explore functional connectivity after intensive attention training in the chronic phase after traumatic brain injury as clinical evidence indicates that intensive attention training improves attention dysfunction in persons with traumatic brain injury. A case series study. Two young adults, 13- and 18-months post traumatic brain injury, with traumatic brain injury induced attention deficits were assigned to 20 h of intensive attention training and neuroimaging. Functional magnetic resonance imaging during a psychomotor vigilance test was conducted pre- and post-intervention. The neuroimaging indicated both increased and decreased connectivity density in frontal, posterior and subcortical brain regions, for some regions with separate change patterns for left and right hemisphere respectively, and an overall reduction in variability in functional connectivity. The changed and decreased variability of functional connectivity in various brain regions, captured by fMRI during a psychomotor vigilance test after direct attention training in a small sample of persons with traumatic brain injury, suggests further studies of functional connectivity changes in neural networks.

Utilizing fNIRS to investigate the impact of Baduanjin training on attentional function in post-stroke cognitive impairment patients: a study protocol for a randomized controlled trial

BackgroundPost-stroke cognitive impairment (PSCI) is a prevalent complication among stroke survivors. It not only directly impacts patients' cognitive abilities but also hampers their capacity to regain independence in daily activities, consequently diminishing their quality of life. Among the various cognitive deficits following stroke, impaired attention is the most frequently observed, influencing not only daily functioning but also higher cognitive functions like working memory, executive functioning, and language.Emerging evidence indicates that Baduanjin, a traditional Chinese exercise, may have a positive impact on enhancing attention in older adults with mild cognitive impairment and stroke survivors. However, the precise mechanisms behind this effect remain unclear. In this study, we employed Baduanjin training as an intervention to address attention decline in post-stroke cognitive impairment patients and to delve into the potential mechanisms through which Baduanjin training may enhance attention in individuals with PSCI.MethodsIn this prospective randomized controlled trial, we plan to recruit 72 participants diagnosed with post-stroke cognitive impairment (PSCI). These participants will be randomly assigned in a 1:1:1 ratio to one of three groups: Baduanjin training(left hemisphere stroke and right hemisphere stroke) and conventional treatment.The conventional treatment group will receive standard rehabilitation sessions. In addition to conventional treatment, participants in the octogenarian training groups will undergo octogenarian training sessions lasting 40 min, five times a week, over a total period of 12 weeks.The primary outcome measures will include the Montreal Cognitive Assessment (MoCA) scale and the Attentional Lateralization Index. These assessments will be conducted by a trained evaluator before the start of the intervention and at weeks 6 and 12 after the intervention begins.Secondary outcome measures will be assessed using the baseline Mandarin version of the Oxford Cognitive Screening (OCS-P) scale, the simplified Fugl-Meyer Motor Function Assessment (FMA) scale, the Pittsburgh Rehabilitation Participation (PRPS) scale, and the Activities of Daily Living (ADL) scale before and after the intervention, respectively.DiscussionThis trial aims to examine the impact of Baduanjin training on attentional lateralization among patients with post-stroke cognitive impairment (PSCI). Functional brain imaging utilizing near-infrared spectroscopy will be employed to investigate how Baduanjin exercise influences the structural and functional connectivity of distinct brain regions or brain networks.Trial registrationChictr.org.cn, ID: ChiCTR2300076533. Registered on 11 October 2023.

Reward anticipation-related neural activation following cued reinforcement in adults with psychotic psychopathology and biological relatives.

Schizophrenia is associated with hypoactivation of reward sensitive brain areas during reward anticipation. However, it is unclear whether these neural functions are similarly impaired in other disorders with psychotic symptomatology or individuals with genetic liability for psychosis. If abnormalities in reward sensitive brain areas are shared across individuals with psychotic psychopathology and people with heightened genetic liability for psychosis, there may be a common neural basis for symptoms of diminished pleasure and motivation. We compared performance and neural activity in 123 people with a history of psychosis (PwP), 81 of their first-degree biological relatives, and 49 controls during a modified Monetary Incentive Delay task during fMRI. PwP exhibited hypoactivation of the striatum and anterior insula (AI) during cueing of potential future rewards with each diagnostic group showing hypoactivations during reward anticipation compared to controls. Despite normative task performance, relatives demonstrated caudate activation intermediate between controls and PwP, nucleus accumbens activation more similar to PwP than controls, but putamen activation on par with controls. Across diagnostic groups of PwP there was less functional connectivity between bilateral caudate and several regions of the salience network (medial frontal gyrus, anterior cingulate, AI) during reward anticipation. Findings implicate less activation and connectivity in reward processing brain regions across a spectrum of disorders involving psychotic psychopathology. Specifically, aberrations in striatal and insular activity during reward anticipation seen in schizophrenia are partially shared with other forms of psychotic psychopathology and associated with genetic liability for psychosis.

Effectiveness and mechanism of action of rTMS combined with quadriceps strength training in individuals with knee osteoarthritis: study protocol for a randomized controlled trial

BackgroundQuadriceps training is necessary in function and activity of daily living for patients with knee osteoarthritis (KOA). However, it did not reduce the rate of surgical treatment for end-stage KOA in the long term. This may be related to brain structure changes and maladaptive plasticity in KOA patients. Transcranial Magnetic Stimulation (TMS) could enhance the functional connectivity of brain regions and improves maladaptive plasticity. However, the synergistic effect of the combination of the two for treat KOA is still unclear. Therefore, the purpose of this study is to investigate whether the High-Frequency rTMS combined with quadriceps strength training can improve the pain and function in KOA more effectively than quadriceps training alone and explore the mechanism of action.MethodsThis study is an assessor-blind, sham-controlled, randomized controlled trial involving 12 weeks of intervention and 6 months follow-up. 148 participants with KOA will receive usual care management and be randomized into four subgroups equally, including quadriceps strength training, high-frequency rTMS training, sham rTMS and quadriceps strength training, high-frequency rTMS and quadriceps strength training. The rehabilitation interventions will be carried out 5 days per week for a total of 12 weeks. All outcomes will be measured at baseline, 4 weeks, 8 weeks, and 12 weeks during the intervention and 1 month, 3 months and 6 months during the follow-up period. The effectiveness outcomes will be included visual analog scale, isokinetic knee muscle strength, Knee Injury and Osteoarthritis Outcome score and 36-Item Short-Form Health Survey score; The act mechanism outcomes will be included motor evoked potential, grey matter density, white matter, subcortical nuclei volumes, cortical thickness and functional connectivity by MRI. Two-way of variance with repeated measures will be used to test the group and time effect for outcome measures.DiscussionThe study will be the first protocol to examine whether there are synergistic effects following high-frequency rTMS combined with quadriceps strength training for treat KOA and clarify the mechanism of action. High-frequency rTMS can be added into the training program for KOA patients if it is proven effective.Trial registrationChinese Clinical Trial Registry ChiCTR2300067617. Registered on Jan.13,2023.

Association between urban upbringing and functional brain connectivity in schizophrenia.

Environmental factors considerably influence the development of the human cortex during the perinatal period, early childhood, and adolescence. Urban upbringing in the first 15 years of life is a known risk factor for schizophrenia (SCZ). Though the risk of urban birth and upbringing is well-examined from an epidemiological perspective, the biological mechanisms underlying urban upbringing remain unknown. The effect of urban birth and upbringing on functional brain connectivity in SCZ patients is not yet examined. This is a secondary data analysis of three studies that included 87 patients with SCZ and 70 healthy volunteers (HV) aged 18 to 50 years. We calculated the developmental urbanicity index using a validated method in earlier studies. Following standard pre-processing of resting functional magnetic resonance imaging (fMRI) scans, seed-return on investment (ROI) functional connectivity analysis was performed. The results showed a significant association between urban birth and upbringing on functional connectivity in SCZ patients and HV (P < 0.05). In SCZ patients, connections from the right caudate, anterior cingulate cortex, left and right intracalcarine cortices, left and right lingual gyri, left posterior parahippocampal cortex to the cerebellum, fusiform gyri, lateral occipital cortex, and amygdala were significantly associated with the urbanicity index (P < 0.05). These study findings suggest a significant association between urban birth and upbringing on functional brain connectivity in regions involved in reward processing and social cognition in SCZ. Assessment of social cognition could have implications in developing an in-depth understanding of this impairment in persons with SCZ.

Impaired effective functional connectivity in the social preference of children with autism spectrum disorder.

The medial prefrontal cortex (mPFC), amygdala (Amyg), and nucleus accumbens (NAc) have been identified as critical players in the social preference of individuals with ASD. However, the specific pathophysiological mechanisms underlying this role requires further clarification. In the current study, we applied Granger Causality Analysis (GCA) to investigate the neural connectivity of these three brain regions of interest (ROIs) in patients with ASD, aiming to elucidate their associations with clinical features of the disorder. Resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired from the ABIDE II database, which included 37 patients with ASD and 50 typically developing (TD) controls. The mPFC, Amyg, and NAc were defined as ROIs, and the differences in fractional amplitude of low-frequency fluctuations (fALFF) within the ROIs between the ASD and TD groups were computed. Subsequently, we employed GCA to investigate the bidirectional effective connectivity between the ROIs and the rest of the brain. Finally, we explored whether this effective connectivity was associated with the social responsiveness scale (SRS) scores of children with ASD. The fALFF values in the ROIs were reduced in children with ASD when compared to the TD group. In terms of the efferent connectivity from the ROIs to the whole brain, the ASD group exhibited increased connectivity in the right cingulate gyrus and decreased connectivity in the right superior temporal gyrus. Regarding the afferent connectivity from the whole brain to the ROIs, the ASD group displayed increased connectivity in the right globus pallidus and decreased connectivity in the right cerebellar Crus 1 area and left cingulate gyrus. Additionally, we demonstrated a positive correlation between effective connectivity derived from GCA and SRS scores. Impairments in social preference ASD children is linked to impaired effective connectivity in brain regions associated with social cognition, emotional responses, social rewards, and social decision-making. This finding further reveals the potential neuropathological mechanisms underlying ASD.

Association between cannabis use and brain structure and function: an observational and Mendelian randomisation study.

Cannabis use during adolescence and young adulthood has been associated with brain harm, yet despite a rapid increase in cannabis use among older adults in the past decade, the impact on brain health in this population remains understudied. To explore observational and genetic associations between cannabis use and brain structure and function. We examined 3641 lifetime cannabis users (mean (SD) age 61.0 (7.1) years) and 12 255 controls (mean (SD) age 64.5 (7.5) years) from UK Biobank. Brain structure and functional connectivity were measured using multiple imaging-derived phenotypes. Associations with cannabis use were assessed using multiple linear regression controlling for potential confounds. Bidirectional two-sample Mendelian randomisation analyses were used to investigate potential causal relationships. Cannabis use was associated with multiple measures of brain structure and function. Participants with a history of cannabis use had poorer white matter integrity, as assessed by lower fractional anisotropy and higher mean diffusivity in the genu of the corpus callosum, as well as weaker resting-state functional connectivity in brain regions underlying the default mode and central executive networks. Mendelian randomisation analyses found no support for causal relationships underlying associations between cannabis use and brain structure or function. Associations between lifetime cannabis use and brain structure and function in later life are probably not causal in nature and might represent residual confounding. Cannabis use is associated with differences in brain structure and function. Further research is needed to understand the mechanisms underlying these associations, which do not appear to be causal.

Vagus nerve stimulation in dementia: A scoping review of clinical and pre-clinical studies.

Dementia is a prevalent, progressive, neurodegenerative condition with multifactorial causes. Due to the lack of effective pharmaceutical treatments for dementia, there are growing clinical and research interests in using vagus nerve stimulation (VNS) as a potential non-pharmacological therapy for dementia. However, the extent of the research volume and nature into the effects of VNS on dementia is not well understood. This study aimed to examine the extent and nature of research activities in relation to the use of VNS in dementia and disseminate research findings for the potential utility in dementia care. We performed a scoping review of literature searches in PubMed, HINARI, Google Scholar, and the Cochrane databases from 1980 to November 30th, 2023, including the reference lists of the identified studies. The following search terms were utilized: brain stimulation, dementia, Alzheimer's disease, vagal stimulation, memory loss, Deme*, cognit*, VNS, and Cranial nerve stimulation. The included studies met the following conditions: primary research articles pertaining to both humans and animals for both longitudinal and cross-sectional study designs and published in English from January 1st, 1980, to November 30th, 2023; investigated VNS in either dementia or cognitive impairment; and were not case studies, conference proceedings/abstracts, commentaries, or ordinary review papers. We identified 8062 articles, and after screening for eligibility (sequentially by titles, abstracts and full text reading, and duplicate removal), 10 studies were included in the review. All the studies included in this literature review were conducted over the last three decades in high-income geographical regions (i.e., Europe, the United States, the United Kingdom, and China), with the majority of them (7/10) being performed in humans. The main reported outcomes of VNS in the dementia cases were enhanced cognitive functions, an increased functional connectivity of various brain regions involved in learning and memory, microglial structural modifications from neurodestructive to neuroprotective configurations, a reduction of cerebral spinal fluid tau-proteins, and significant evoked brain tissue potentials that could be utilized to diagnose neurodegenerative disorders. The study outcomes highlight the potential for VNS to be used as a non-pharmacological therapy for cognitive impairment in dementia-related diseases such as Alzheimer's disease.

Exploring protocol development: Implementing systematic contextual memory to enhance real-time fMRI neurofeedback.

The goal of this study was to explore the development and implementation of a protocol for real-time fMRI neurofeedback (rtfMRI-nf) and to assess the potential for enhancing the selective brain activation using stimuli from Virtual Reality (VR). In this study we focused on two specific brain regions, supplementary motor area (SMA) and right inferior frontal gyrus (rIFG). Publications by other study groups have suggested impaired function in these specific brain regions in patients with the diagnoses Attention Deficit Hyperactivity Disorder (ADHD) and Tourette's Syndrome (TS). This study explored the development of a protocol to investigate if attention and contextual memory may be used to systematically strengthen the procedure of rtfMRI-nf. We used open-science software and platforms for rtfMRI-nf and for developing a simulated repetition of the rtfMRI-nf brain training in VR. We conducted seven exploratory tests in which we updated the protocol at each step. During rtfMRI-nf, MRI images are analyzed live while a person is undergoing an MRI scan, and the results are simultaneously shown to the person in the MRI-scanner. By focusing the analysis on specific regions of the brain, this procedure can be used to help the person strengthen conscious control of these regions. The VR simulation of the same experience involved a walk through the hospital toward the MRI scanner where the training sessions were conducted, as well as a subsequent simulated repetition of the MRI training. The VR simulation was a 2D projection of the experience.The seven exploratory tests involved 19 volunteers. Through this exploration, methods for aiming within the brain (e.g. masks/algorithms for coordinate-system control) and calculations for the analyses (e.g. calculations based on connectivity versus activity) were updated by the project team throughout the project. The final procedure involved three initial rounds of rtfMRI-nf for learning brain strategies. Then, the volunteers were provided with VR headsets and given instructions for one week of use. Afterward, a new session with three rounds of rtfMRI-nf was conducted. Through our exploration of the indirect effect parameters - brain region activity (directed oxygenated blood flow), connectivity (degree of correlated activity in different regions), and neurofeedback score - the volunteers tended to increase activity in the reinforced brain regions through our seven tests. Updates of procedures and analyses were always conducted between pilots, and never within. The VR simulated repetition was tested in pilot 7, but the role of the VR contribution in this setting is unclear due to underpowered testing. This proof-of-concept protocol implies how rtfMRI-nf may be used to selectively train two brain regions (SMA and rIFG). The method may likely be adapted to train any given region in the brain, but readers are advised to update and adapt the procedure to experimental needs.

Connectome architecture modulates the gray matter atrophy in major depression disorder patients with diverse suicidal ideations.

Gray matter (GM) atrophy is well documented in patients with major depressive disorder (MDD), but its underlying mechanism remains unknown. This study aimed to examine the GM atrophy in MDD patients with diverse suicidal ideations (SIs) and to explore whether those alterations were driven by connections.GM volume was estimated in 163 patients with recurrent MDD (comprising 122 with SI [MDDSI] and 41 without SI [MDDNSI]) and 134 health controls (HCs). A two-sample t-test was used to identify GM volume abnormalities in MDD patients and their subgroups. Functional connectivity was computed between pairs of aberrant GM in both patients and HCs, which were further compared with the connectivity of random brain regions. A permutation test was performed to assess its significance. Propensity score matching (PSM) was further performed to validate the main results.Compared with HCs, the MDDNSI group exhibited GM atrophy in 24 regions, with the largest effect sizes found in the frontal and parietal lobes, while the MDDSI group exhibited more widespread GM atrophy involving 49 regions, with the largest effect sizes in the frontal lobe, parietal lobe, temporal lobe, and the limbic system. Furthermore, patients and HCs exhibited significantly increased functional connectivity between regions with GM atrophy compared with randomly selected regions (p < 0.05). PSM analysis presented similar results to the main analysis.MDD patients had diverse GM atrophy features according to their SI tendency. Moreover, connectome architecture modulates the GM atrophy in MDD patients, implying the possibility that connections drive these pathological changes.

Graph theory analysis reveals an assortative pain network vulnerable to attacks

The neural substrate of pain experience has been described as a dense network of connected brain regions. However, the connectivity pattern of these brain regions remains elusive, precluding a deeper understanding of how pain emerges from the structural connectivity. Here, we employ graph theory to systematically characterize the architecture of a comprehensive pain network, including both cortical and subcortical brain areas. This structural brain network consists of 49 nodes denoting pain-related brain areas, linked by edges representing their relative incoming and outgoing axonal projection strengths. Within this network, 63% of brain areas share reciprocal connections, reflecting a dense network. The clustering coefficient, a measurement of the probability that adjacent nodes are connected, indicates that brain areas in the pain network tend to cluster together. Community detection, the process of discovering cohesive groups in complex networks, successfully reveals two known subnetworks that specifically mediate the sensory and affective components of pain, respectively. Assortativity analysis, which evaluates the tendency of nodes to connect with other nodes that have similar features, indicates that the pain network is assortative. Finally, robustness, the resistance of a complex network to failures and perturbations, indicates that the pain network displays a high degree of error tolerance (local failure rarely affects the global information carried by the network) but is vulnerable to attacks (selective removal of hub nodes critically changes network connectivity). Taken together, graph theory analysis unveils an assortative structural pain network in the brain that processes nociceptive information. Furthermore, the vulnerability of this network to attack presents the possibility of alleviating pain by targeting the most connected brain areas in the network.

Resting state functional connectivity associated with impaired proprioception post-stroke.

Deficits in proprioception, the knowledge of limb position and movement in the absence of vision, occur in ~50% of all strokes; however, our lack of knowledge of the neurological mechanisms of these deficits diminishes the effectiveness of rehabilitation and prolongs recovery. We performed resting-state functional magnetic resonance imaging (fMRI) on stroke patients to determine functional brain networks that exhibited changes in connectivity in association with proprioception deficits determined by a Kinarm robotic exoskeleton assessment. Thirty stroke participants were assessed for proprioceptive impairments using a Kinarm robot and underwent resting-state fMRI at 1 month post-stroke. Age-matched healthy control (n = 30) fMRI data were also examined and compared to stroke data in terms of the functional connectivity of brain regions associated with proprioception. Stroke patients exhibited reduced connectivity of the supplementary motor area and the supramarginal gyrus, relative to controls. Functional connectivity of these regions plus primary somatosensory cortex and parietal opercular area was significantly associated with proprioceptive function. The parietal lobe of the lesioned hemisphere is a significant node for proprioception after stroke. Assessment of functional connectivity of this region after stroke may assist with prognostication of recovery. This study also provides potential targets for therapeutic neurostimulation to aid in stroke recovery.

Characterization of various type of cognitive impairment using multiomics – a pilot imaging study from a local institution

AbstractBackgroundIn addition to clinical diagnosis, multi‐modal imaging has been employed for early detection of various types of dementia. Image features from various types of images provided information for accurate diagnosis. This study aimed to evaluate the role of multiple imaging, including MRI T1W, T2W, resting state functional MRI (rs‐fMRI) and 18‐F Flutemetamol PET image in diagnosis of various types of cognitive impairments.Methods56 participants (16 Alzheimer’s Disease (AD), 10 AD type Mild Cognitive impairment (A‐MCI), 18 vascular type MCI (V‐MCI), 12 Vascular dementia (VD) and 25 Healthy Control (HC) were recruited in an local memory clinic. All types of images were re‐orientated, segmentation and normalized to the whole brain mask template. 45 brain regional volumes (Vol) were calculated from T1w using Freesurfer. Brain regional white matter hyperintensities (WMH) were obtained from T2w images. Interhemispheric functional connectivity (IFC) of brain regions were measured from rs‐fMRI. Standard uptake value (SUV) were measured and calculated from the PET images. Also, patient demographics including age, sex and HK‐MoCa score (Demo) were recorded. 70% of each group of participants were assigned to the training group, whereas the rest 30% were assigned to test group. The neural network toolbox of MATLAB was employed to build four characterization models: Model 1 based Vol and WMH; Model 2 based on Vol, WMH and IFC; Model 3 based on Vol, WMH, IFC, and demo; Model 4 based on Vol, WMH, IFC, demo and SUV.ResultsThe receiver operating characteristics (ROC) curves showed that the Model 1, 2 and 3 achieved satisfactory accuracy, with 79%, 68% and 70% respectively. While Model 4 achieved excellent accuracy of 100%. The sensitivity and specificity of each model for each group was over 75% to 100%. The model with more image features attained higher accuracy in dementia diagnosis.ConclusionArtificial neural network model with multiomics can accurately differentiate AD, A‐MCI, V‐MCI, VD and HC. Further study is suggested with more participants for models verification.