Intensive whole-brain 7T MRI case study of volitional control of brain activity in deep absorptive meditation states.

Jhanas are profound states of mind achieved through advanced meditation, offering valuable insights into the nature of consciousness and tools to enhance well-being. Yet, its neurophenomenology remains limited due to methodological difficulties and the rarity of advanced meditation practitioners. We conducted a highly exploratory study to investigate the neurophenomenology of jhanas in an intensively sampled adept meditator case study (4 hr 7T fMRI collected in 27 sessions) who performed jhana meditation and rated specific aspects of experience immediately thereafter. Linear mixed models and correlations were used to examine relations among brain activity and jhana phenomenology. We identified distinctive patterns of brain activity in specific cortical, subcortical, brainstem, and cerebellar regions associated with jhana. Furthermore, we observed correlations between brain activity and phenomenological qualities of attention, jhanic qualities, and narrative processing, highlighting the distinct nature of jhanas compared to non-meditative states. Our study presents the most rigorous evidence yet that jhana practice deconstructs consciousness, offering unique insights into consciousness and significant implications for mental health and well-being.

The effective connectivity analysis of fMRI based on asymmetric detection of transfer brain entropy.

It is important to explore causal relationships in functional magnetic resonance imaging study. However, the traditional effective connectivity analysis method is easy to produce false causality, and the detection accuracy needs to be improved. In this paper, we introduce a novel functional magnetic resonance imaging effective connectivity method based on the asymmetry detection of transfer entropy, which quantifies the disparity in predictive information between forward and backward time, subsequently normalizing this disparity to establish a more precise criterion for detecting causal relationships while concurrently reducing computational complexity. Then, we evaluate the effectiveness of this method on the simulated data with different level of nonlinearity, and the results demonstrated that the proposed method outperforms others methods on the detection of both linear and nonlinear causal relationships, including Granger Causality, Partial Granger Causality, Kernel Granger Causality, Copula Granger Causality, and traditional transfer entropy. Furthermore, we applied it to study the effective connectivity of brain functional activities in seafarers. The results showed that there are significantly different causal relationships between different brain regions in seafarers compared with non-seafarers, such as Temporal lobe related to sound and auditory information processing, Hippocampus related to spatial navigation, Precuneus related to emotion processing as well as Supp_Motor_Area associated with motor control and coordination, which reflects the occupational specificity of brain function of seafarers.

Experiential grounding of abstract concepts: Processing of abstract mental state concepts engages brain regions involved in mentalizing, automatic speech, and lip movements.

concepts like mental state concepts lack a physical referent, which can be directly perceived. Classical theories therefore claim that abstract concepts require amodal representations detached from experiential brain systems. However, grounded cognition approaches suggest an involvement of modal experiential brain regions in the processing of abstract concepts. In the present functional magnetic resonance imaging study, we investigated the relation of the processing of abstract mental state concepts to modal experiential brain systems in a fine-grained fashion. Participants performed lexical decisions on abstract mental state as well as on verbal association concepts as control category. Experiential brain systems related to the processing of mental states, generating verbal associations, automatic speech as well as hand and lip movements were determined by corresponding localizer tasks. Processing of abstract mental state concepts neuroanatomically overlapped with activity patterns associated with processing of mental states, generating verbal associations, automatic speech and lip movements. Hence, mental state concepts activate the mentalizing brain network, complemented by perceptual-motor brain regions involved in simulation of visual or action features associated with social interactions, linguistic brain regions as well as face-motor brain regions recruited for articulation. The present results provide compelling evidence for the rich grounding of abstract mental state concepts in experiential brain systems related to mentalizing, verbal communication and mouth action.

Neural mechanisms underlying placebo and nocebo effects in tonic muscle pain.

Pain is a highly subjective and multidimensional experience, significantly influenced by various psychological factors. Placebo analgesia and nocebo hyperalgesia exemplify this influence, where inert treatments result in pain relief or exacerbation, respectively. While extensive research has elucidated the psychological and neural mechanisms behind these effects, most studies have focused on transient pain stimuli. To explore these mechanisms in the context of tonic pain, we conducted a study using a 15-minute tonic muscle pain induction procedure, where hypertonic saline was infused into the left masseter of healthy participants. We collected real-time Visual Analogue Scale (VAS) scores and functional magnetic resonance imaging (fMRI) data during the induction of placebo analgesia and nocebo hyperalgesia via conditioned learning. Our findings revealed that placebo analgesia was more pronounced and lasted longer than nocebo hyperalgesia. Real-time pain ratings correlated significantly with neural activity in several brain regions. Notably, the putamen was implicated in both effects, while the caudate and other regions were differentially involved in placebo and nocebo effects. These findings confirm that the tonic muscle pain paradigm can be used to investigate the mechanisms of placebo and nocebo effects and indicate that placebo analgesia and nocebo hyperalgesia may have more distinct than common neural bases.

BPI-GNN: Interpretable brain network-based psychiatric diagnosis and subtyping.

Converging evidence increasingly suggests that psychiatric disorders, such as major depressive disorder (MDD) and autism spectrum disorder (ASD), are not unitary diseases, but rather heterogeneous syndromes that involve diverse, co-occurring symptoms and divergent responses to treatment. This clinical heterogeneity has hindered the progress of precision diagnosis and treatment effectiveness in psychiatric disorders. In this study, we propose BPI-GNN, a new interpretable graph neural network (GNN) framework for analyzing functional magnetic resonance images (fMRI), by leveraging the famed prototype learning. In addition, we introduce a novel generation process of prototype subgraph to discover essential edges of distinct prototypes and employ total correlation (TC) to ensure the independence of distinct prototype subgraph patterns. BPI-GNN can effectively discriminate psychiatric patients and healthy controls (HC), and identify biological meaningful subtypes of psychiatric disorders. We evaluate the performance of BPI-GNN against 11 popular brain network classification methods on three psychiatric datasets and observe that our BPI-GNN always achieves the highest diagnosis accuracy. More importantly, we examine differences in clinical symptom profiles and gene expression profiles among identified subtypes and observe that our identified brain-based subtypes have the clinical relevance. It also discovers the subtype biomarkers that align with current neuro-scientific knowledge.

Neurovascular coupling in eye-open-eye-close task and resting state: Spectral correspondence between concurrent EEG and fMRI.

Neurovascular coupling serves as an essential neurophysiological mechanism in functional neuroimaging, which is generally presumed to be robust and invariant across different physiological states, encompassing both task engagement and resting state. Nevertheless, emerging evidence suggests that neurovascular coupling may exhibit state dependency, even in normal human participants. To investigate this premise, we analyzed the cross-frequency spectral correspondence between concurrently recorded electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data, utilizing them as proxies for neurovascular coupling during the two conditions: an eye-open-eye-close (EOEC) task and a resting state. We hypothesized that given the state dependency of neurovascular coupling, EEG-fMRI spectral correspondences would change between the two conditions in the visual system. During the EOEC task, we observed a negative phase-amplitude-coupling (PAC) between EEG alpha-band and fMRI visual activity. Conversely, in the resting state, a pronounced amplitude-amplitude-coupling (AAC) emerged between EEG and fMRI signals, as evidenced by the spectral correspondence between the EEG gamma-band of the midline occipital channel (Oz) and the high-frequency fMRI signals (0.15-0.25 Hz) in the visual network. This study reveals distinct scenarios of EEG-fMRI spectral correspondence in healthy participants, corroborating the state-dependent nature of neurovascular coupling.

Lateralisation of nasal cycle is not reflected in the olfactory bulb volumes and cerebral activations.

Nasal cycle (NC) is a rhythmic change of lateralised nasal airflow mediated by the autonomous nervous system. Previous studies reported the dependence of NC dominance or more patent side on handedness and hemispheric cerebral activity. We aimed to investigate firstly the possible lateralised effect of NC on olfactory bulb volume and secondly the association of NC with the lateralised cerebral dominance in terms of olfactory processing. Thirty-five subjects (22 women and 13 men, mean age 26 ± 3 years) participated in the study. NC was ascertained using a portable rhino-flowmeter. Structural and functional brain measurements were assessed using a 3T MR scanner. Vanillin odorant was presented during functional scans using a computer-controlled olfactometer. NC was found to be independent of the olfactory bulb volumes. Also, cerebral activations were found independent of the NC during odorant perception. NC potency is not associated with lateralised structural or functional differences in the cerebral olfactory system.

Frequency-specific dual-attention based adversarial network for blood oxygen level-dependent time series prediction.

Functional magnetic resonance imaging (fMRI) is currently one of the most popular technologies for measuring brain activity in both research and clinical contexts. However, clinical constraints often result in short fMRI scan durations, limiting the diagnostic performance for brain disorders. To address this limitation, we developed an end-to-end frequency-specific dual-attention-based adversarial network (FDAA-Net) to extend the time series of existing blood oxygen level-dependent (BOLD) data, enhancing their diagnostic utility. Our approach leverages the frequency-dependent nature of fMRI signals using variational mode decomposition (VMD), which adaptively tracks brain activity across different frequency bands. We integrated the generative adversarial network (GAN) with a spatial-temporal attention mechanism to fully capture relationships among spatially distributed brain regions and temporally continuous time windows. We also introduced a novel loss function to estimate the upward and downward trends of each frequency component. We validated FDAA-Net on the Human Connectome Project (HCP) database by comparing the original and predicted time series of brain regions in the default mode network (DMN), a key network activated during rest. FDAA-Net effectively overcame linear frequency-specific challenges and outperformed other popular prediction models. Test-retest reliability experiments demonstrated high consistency between the functional connectivity of predicted outcomes and targets. Furthermore, we examined the clinical applicability of FDAA-Net using short-term fMRI data from individuals with autism spectrum disorder (ASD) and major depressive disorder (MDD). The model achieved a maximum predicted sequence length of 40% of the original scan durations. The prolonged time series improved diagnostic performance by 8.0% for ASD and 11.3% for MDD compared with the original sequences. These findings highlight the potential of fMRI time series prediction to enhance diagnostic power of brain disorders in short fMRI scans.

The truth is in there: Belief processes in the human brain.

Belief, defined by William James as the mental state or function of cognizing reality, is a core psychological function with strong influence on emotion and behavior. Furthermore, strong and aberrant beliefs about the world and oneself play important roles in mental disorders. The underlying processes of belief have been the matter of a long debate in philosophy and psychology, and modern neuroimaging techniques can provide insight into the underlying neural processes. Here, we conducted a functional magnetic resonance imaging study with N = 30 healthy participants in which we presented statements about facts, politics, religion, conspiracy theories, and superstition. Participants judged whether they considered them as true (belief) or not (disbelief) and reported their certainty in the decision. We found belief-associated activations in bilateral dorsolateral prefrontal cortex, left superior parietal cortex, and left lateral frontopolar cortex. Disbelief-associated activations were found in an anterior temporal cluster extending into the amygdala. We found a larger deactivation for disbelief than belief in the ventromedial prefrontal cortex that was most pronounced during decisions, suggesting a role of the vmPFC in belief-related decision-making. As a category-specific effect, we found disbelief-associated activation in retrosplenial cortex and parahippocampal gyrus for conspiracy theory statements. Exploratory analyses identified networks centered at anterior cingulate cortex for certainty, and dorsomedial prefrontal cortex for uncertainty. The uncertainty effect identifies a neural substrate for Alexander Bain's notion from 1859 of uncertainty as the real opposite of belief. Taken together, our results suggest a two-factor neural process model of belief with falsehood/veracity and uncertainty/certainty factors.

Topological Organization of the Brain Network in Patients with Primary Angle-closure Glaucoma Through Graph Theory Analysis.

Primary angle-closure glaucoma (PACG) is a sight-threatening eye condition that leads to irreversible blindness. While past neuroimaging research has identified abnormal brain function in PACG patients, the relationship between PACG and alterations in brain functional networks has yet to be explored. This study seeks to examine the influence of PACG on brain networks, aiming to advance knowledge of its neurobiological processes for better diagnostic and therapeutic approaches utilizing graph theory analysis. A cohort of 44 primary angle-closure glaucoma (PACG) patients and 44 healthy controls participated in this study. Functional brain networks were constructed using fMRI data and the Automated Anatomical Labeling 90 template. Subsequently, graph theory analysis was employed to evaluate global metrics, nodal metrics, modular organization, and network-based statistics (NBS), enabling a comparative analysis between PACG patients and the control group. The analysis of global metrics, including small-worldness and network efficiency, did not exhibit significant differences between the two groups. However, PACG patients displayed elevated nodal metrics, such as centrality and efficiency, in the left frontal superior medial, right frontal superior medial, and right posterior central brain regions, along with reduced values in the right temporal superior gyrus region compared to healthy controls. Furthermore, Module 5 showed notable disparities in intra-module connectivity, while Module 1 demonstrated substantial differences in inter-module connectivity with both Module 7 and Module 8. Noteworthy, the NBS analysis unveiled a significantly altered network when comparing the PACG and healthy control groups. The study proposes that PACG patients demonstrate variations in nodal metrics and modularity within functional brain networks, particularly affecting the prefrontal, occipital, and temporal lobes, along with cerebellar regions. However, an analysis of global metrics suggests that the overall connectivity patterns of the entire brain network remain unaltered in PACG patients. These results have the potential to serve as early diagnostic and differential markers for PACG, and interventions focusing on brain regions with high degree centrality and nodal efficiency could aid in optimizing therapeutic approaches.

Changes in the BOLD signal of S1 and BA3 per finger/phalanx as a response to high-frequency vibratory stimulation.

PURPOSE AND METHOD: The purpose of this study was to determine the changes in the Blood Oxygen Level Dependent signal of Primary somatosensory area (S1) and Brodmann area 3 (BA3) per finger and phalanx in comparison to the activation voxel when 250 Hz vibratory stimulation with high sensitivity for the Pacinian corpuscle was given to the four fingers and three phalanges. RESULTS: The result of analyzing the activation voxel showed a significant difference for S1 per finger and phalanx, but for BA3, no significant difference was observed despite a similar trend to S1. In contrast, the activation intensity (BOLD) displayed a significant difference for S1 per finger and phalanx and for BA3, where the activation voxel had no significant variation. In addition, while the result of S1 did not indicate whether the index or the little fingers had the highest sensitivity based on the BOLD signal per finger, the result of BA3 marked the strongest BOLD signal for the little finger as a response to 250 Hz vibratory stimulation. The activation intensity per phalanx was the highest for the intermediate phalanx for S1 and BA3, which was in line with a previous study comparing the activation voxel. CONCLUSIONS: The method based on the intensity of the nerve activation is presumed to have high sensitivity as the signal intensity is monitored within a specific, defined area. Thus, for the extraction of brain activation patterns of micro-domains, such as BA3, monitoring the BOLD signal that reflects the nerve activation intensity more sensitively is likely to be advantageous.

Pre-scan state anxiety is associated with greater right amygdala-hippocampal response to fearful versus happy faces among trait-anxious Latina girls.

BACKGROUND: Unfamiliarity with academic research may contribute to higher levels of anticipatory state anxiety about affective neuroimaging tasks. Children with high trait anxiety display differences in brain response to fearful facial affect compared to non-anxious youth, but little is known about the influence of state anxiety on this association. Because reduced engagement in scientific research and greater mistrust among minoritized groups may lead to systematic differences in pre-scan state anxiety, it is crucial to understand the neural correlates of state anxiety during emotion processing so as to disambiguate sources of individual differences. METHODS: The present study probed the interactive effects of pre-scan state anxiety, trait anxiety, and emotional valence (fearful vs. happy faces) on neural activation during implicit emotion processing in a community sample of 46 preadolescent Latina girls (8-13 years). RESULTS: Among girls with mean and high levels of trait anxiety, pre-scan state anxiety was associated with greater right amygdala-hippocampal and left inferior parietal lobe response to fearful faces relative to happy faces. CONCLUSIONS: Anticipatory state anxiety in the scanning context may cause children with moderate and high trait anxiety to be hypervigilant to threats, further compounding the effects of trait anxiety. Neuroimaging researchers should control for state anxiety so that systematic differences in brain activation resulting from MRI apprehension are not misleadingly attributed to demographic or environmental characteristics.

Neural adaptations to congenital deafness: enhanced tactile discrimination through cross-modal neural plasticity - an fMRI study.

BACKGROUND: This study explores the compensatory neural mechanisms associated with congenital deafness through an examination of tactile discrimination abilities using high-resolution functional magnetic resonance imaging (fMRI). OBJECTIVE: To analyze the neural substrates underlying tactile processing in congenitally deaf individuals and compare them with hearing controls. METHODS: Our participant pool included thirty-five congenitally deaf individuals and thirty-five hearing controls. All participants engaged in tactile discrimination tasks involving the identification of common objects by touch. We utilized an analytical suite comprising voxel-based statistics, functional connectivity multivariate/voxel pattern analysis (fc-MVPA), and seed-based connectivity analysis to examine neural activity. RESULTS: Our findings revealed pronounced neural activity in congenitally deaf participants within regions typically associated with auditory processing, including the bilateral superior temporal gyrus, right middle temporal gyrus, and right rolandic operculum. Additionally, unique activation and connectivity patterns were observed in the right insula and bilateral supramarginal gyrus, indicating a strategic reorganization of neural pathways for tactile information processing. Behaviorally, both groups demonstrated high accuracy in the tactile tasks, exceeding 90%. However, the deaf participants outperformed their hearing counterparts in reaction times, showcasing significantly enhanced efficiency in tactile information processing. CONCLUSION: These insights into the brain's adaptability to sensory loss through compensatory neural reorganization highlight the intricate mechanisms by which tactile discrimination is enhanced in the absence of auditory input. Understanding these adaptations can help develop strategies to harness the brain's plasticity to improve sensory processing in individuals with sensory impairments, ultimately enhancing their quality of life through improved tactile perception and sensory integration.

A comprehensive approach to lateral ventricular tumor resection: techniques, technologies, and outcomes.

This study reviews lateral ventricular tumors (LVTs), which are rare brain lesions accounting for 0.64-3.5% of brain tumors, and the unique challenges they present due to their location and growth patterns. Once deemed inoperable, advancements in microneurosurgery, imaging, and tumor pathobiology have significantly improved treatment outcomes. This letter summarizes recent studies and key findings in the management of LVTs. Research by S.A. Maryashev et al. identified risk factors for early hemorrhagic complications following the surgical resection of lateral ventricular neoplasms, highlighting the significance of patient characteristics, tumor location, and surgical approach. The study found that factors such as gender, hydrocephalus, tumor blood flow, and Evans index correlate with a higher risk of hemorrhage, with the transcallosal approach having a greater risk compared to the transcortical approach. The utilization of navigation technologies, including fMRI, neuronavigation, and intraoperative brain mapping, has been shown to reduce surgical complications and enhance patient outcomes in the treatment of lateral ventricular meningiomas. Moreover, endoscopic and endoport-assisted endoscopic techniques have proven to be valuable in intraventricular tumor surgery, enabling minimally invasive procedures with better visualization and fewer complications. The integration of advanced surgical techniques, neuroimaging, and neurophysiological monitoring emphasizes the necessity of a multidisciplinary approach to optimize patient outcomes. To improve the study's validity and applicability, further research with larger sample sizes and advanced statistical analyses is needed. This letter advocates for the continued exploration of innovative surgical techniques and technologies to enhance the management of lateral ventricular tumors.

Bibliometric analysis of functional magnetic resonance imaging studies on chronic pain over the past 20 years.

PURPOSE: The utilization of functional magnetic resonance imaging (fMRI) in studying the mechanisms and treatment of chronic pain has gained significant popularity. However, there is currently a dearth of literature conducting bibliometric analysis on fMRI studies focused on chronic pain. METHODS: All the literature included in this study was obtained from the Science Citation Index Expanded of Web of Science Core Collection. We used CiteSpace and VOSviewer to analyze publications, authors, countries or regions, institutions, journals, references and keywords. Additionally, we evaluated the timeline and burst analysis of keywords, as well as the timeline and burst analysis of references. The search was conducted from 2004 to 2023 and completed within a single day on October 4th, 2023. RESULTS: A total of 1,327 articles were retrieved. The annual publication shows an overall increasing trend. The United States has the highest number of publications and the main contributing institution is Harvard University. The journal PAIN produces the most articles. In recent years, resting-state fMRI, the prefrontal cortex, nucleus accumbens, thalamus, and migraines have been researched hotspots of fMRI studies on chronic pain. CONCLUSIONS: This study provides an in-depth perspective on fMRI for chronic pain research, revealing key points, research hotspots and research trends, which offers valuable ideas for future research activities. It concludes with a summary of advances in clinical practice in this area, pointing out the need for critical evaluation of these findings in the light of guidelines and expert recommendations. It is anticipated that further high-quality research outputs will be generated in the future, which will facilitate the utilization of fMRI in clinical decision-making for chronic pain.

Galantamine combined with cognitive rehabilitation on post-stroke cognitive impairment: a proof-of-concept study.

PURPOSE: We conducted a proof-of-concept study to evaluate the effects of galantamine treatment versus placebo combined to cognitive rehabilitation (CR) after stroke. MATERIALS AND METHODS: In this 12-week, double blinded, randomized, controlled trial, patients were assigned to either combined approach of galantamine and CR (G-CR) or placebo and CR (P-CR). Primary outcome was the proportion of patients who crossed over from vascular cognitive disorder (VCD) to no-VCD at 12 weeks. Secondary outcomes included changes in cognition, mood, quality of life and the N-back fMRI paradigm, assessed at baseline, 6 and 12 weeks and after an 8-week washout period. RESULTS: Ten patients were allocated to G-RC group, 12 to the P-RC group. After 12 weeks, 40.1% of all patients converted to no-VCD with similar proportions between groups. Both groups showed improvements in episodic and working memory, executive and quality of life after 6 weeks of CR. Decreased depression and anxiety were noted, and all benefits persisted after the washout period. An interaction effect was observed in the right parietal lobule during the N-back task. CONCLUSIONS: Interventions lead to improved cognition and distinct cortical reorganization without being able to establish correlation between neural changes and behavioral measures.

Unveiling Functional Biomarkers in Schizophrenia: Insights from Region of Interest Analysis Using Machine Learning.

BACKGROUND: Schizophrenia is a complex and disabling mental disorder that represents one of the most important challenges for neuroimaging research. There were many attempts to understand these basic mechanisms behind the disorder, yet we know very little. By employing machine learning techniques with age-matched samples from the auditory oddball task using multi-site functional magnetic resonance imaging (fMRI) data, this study aims to address these challenges. METHODS: The study employed a three-stage model to gain a better understanding of the neurobiology underlying schizophrenia and techniques that could be applied for diagnosis. At first, we constructed four-level hierarchical sets from each fMRI volume of 34 schizophrenia patients (SZ) and healthy controls (HC) individually in terms of hemisphere, gyrus, lobes, and Brodmann areas. Second, we employed statistical methods, namely, t-tests and Pearson's correlation, to assess the group differences in cortical activation. Finally, we assessed the predictive power of the brain regions for machine learning algorithms using K-nearest Neighbor (KNN), Naive Bayes, Decision Tree (DT), Random Forest (RF), Support Vector Machines (SVMs), and Extreme Learning Machine (ELM). RESULTS: Our investigation depicts promising results, obtaining an accuracy of up to 84% when applying Pearson's correlation-selected features at lobes and Brodmann region level (81% for Gyrus), as well as Hemispheres involving different stages. Thus, the results of our study were consistent with previous studies that have revealed some functional abnormalities in several brain regions. We also discovered the involvement of other brain regions which were never sufficiently studied in previous literature, such as the posterior lobe (posterior cerebellum), Pyramis, and Brodmann Area 34. CONCLUSIONS: We present a unique and comprehensive approach to investigating the neurological basis of schizophrenia in this study. By bridging the gap between neuroimaging and computable analysis, we aim to improve diagnostic accuracy in patients with schizophrenia and identify potential prognostic markers for disease progression.

A Multimodal Magnetic Resonance Imaging Study on Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: Feasibility and Clinical Correlation.

Background/Objectives: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a neurological disorder characterized by post-exertional malaise. Despite its clinical relevance, the disease mechanisms of ME/CFS are not fully understood. The previous studies targeting brain function or metabolites have been inconclusive in understanding ME/CFS complexity. We combined single-voxel magnetic resonance spectroscopy (SV-MRS) and functional magnetic resonance imaging (fMRI). Our objectives were to examine the feasibility of the multimodal MRI protocol, identify possible differences between ME/CFS and healthy controls (HCs), and relate MRI findings with clinical symptoms. Methods: We enrolled 18 female ME/CFS participants (mean age: 39.7 ± 12.0 years) and five HCs (mean age: 45.6 ± 14.5 years). SV-MRS spectra were acquired from three voxels of interest: the anterior cingulate gyrus (ACC), brainstem (BS), and left dorsolateral prefrontal cortex (L-DLPFC). Whole-brain fMRI used n-back task testing working memory and executive function. The feasibility was assessed as protocol completion rate and time. Group differences in brain metabolites and fMRI activation between ME/CFS and HCs were compared and correlated with behavioral and symptom severity measurements. Results: The completion rate was 100% regardless of participant group without causing immediate fatigue. ME/CFS appeared to show a higher N-Acetylaspartate in L-DLPFC compared to HCs (OR = 8.49, p = 0.040), correlating with poorer fatigue, pain, and sleep quality scores (p's = 0.001-0.015). An increase in brain activation involving the frontal lobe and the brainstem was observed in ME/CFS compared to HCs (Z > 3.4, p's < 0.010). Conclusions: The study demonstrates the feasibility of combining MRS and fMRI to capture neurochemical and neurophysiological features of ME/CFS in female participants. Further research with larger cohorts of more representative sampling and follow-ups is needed to validate these apparent differences between ME/CFS and HCs.

An In-depth Exploration of the Interplay between fMRI Methods and Theory in Cognitive Neuroscience.

Functional magnetic resonance imaging (fMRI) has been a cornerstone of cognitive neuroscience since its invention in the 1990s. The methods that we use for fMRI data analysis allow us to test different theories of the brain, thus different analyses can lead us to different conclusions about how the brain produces cognition. There has been a centuries-long debate about the nature of neural processing, with some theories arguing for functional specialization or localization (e.g., face and scene processing) while other theories suggest that cognition is implemented in distributed representations across many neurons and brain regions. Importantly, these theories have received support via different types of analyses; therefore, having students implement hands-on data analysis to explore the results of different fMRI analyses can allow them to take a firsthand approach to thinking about highly influential theories in cognitive neuroscience. Moreover, these explorations allow students to see that there are not clearcut "right" or "wrong" answers in cognitive neuroscience, rather we effectively instantiate assumptions within our analytical approaches that can lead us to different conclusions. Here, I provide Python code that uses freely available software and data to teach students how to analyze fMRI data using traditional activation analysis and machine-learning-based multivariate pattern analysis (MVPA). Altogether, these resources help teach students about the paramount importance of methodology in shaping our theories of the brain, and I believe they will be helpful for introductory undergraduate courses, graduate-level courses, and as a first analysis for people working in labs that use fMRI.

Enhanced neural synchrony associated with long-term ballroom dance training.

Long-term dance training offers numerous benefits, including improvements in physical health, posture, body coordination, and mental health and well-being. Since dance is an art form of body-to-body communication, professional dancers may share feelings and thoughts on dance with their partners, owing to their shared training experiences. Considering this perspective, one may expect that professional dancers would demonstrate pronounced neural similarities when viewing dancing videos, which could be associated with their training duration. To test these hypotheses, we collected functional magnetic resonance imaging (fMRI) data while presenting ballroom dancing and neutral video clips with long durations (∼100 s each) to 41 professional ballroom dancers (19 pairs of dance partners) and 39 age- and sex-matched nondancers. Our findings revealed that dancers exhibited broader and stronger neural similarities across the whole brain when watching dancing video clips, as compared to the control group. These increased neural similarities could be interpreted in at least two distinct ways. First, neural similarities in certain brain regions within the motor control circuit (i.e., frontal cortical-basal ganglia-thalamic circuit) were significantly correlated with dance-related information (e.g., dance partners' cooperation duration), which reinforced the impact of long-term dance training on neural synchronization. Second, neural similarities in other brain regions (e.g., memory-related brain regions) were significantly correlated with subjects' impression of the viewed videos (i.e., whether they have watched before, familiarity, and liking), which may not necessarily be directly linked to long-term dance training. Altogether, our study provided solid evidence for synchronized neural mechanisms in professional dancers due to long-term dance training.