fMRI Analysis Research Articles

High magnitude exposure to repetitive head impacts alters female adolescent brain activity for lower extremity motor control

Contact and collision sport participation among adolescent athletes has raised concerns about the potential negative effects of cumulative repetitive head impacts (RHIs) on brain function. Impairments from RHIs and sports-related concussions (SRC) may propagate into lingering neuromuscular control. However, the neural mechanisms that link RHIs to altered motor control processes remain unknown. The purpose of this study was to isolate changes in neural activity for a lower extremity motor control task associated with the frequency and magnitude of RHI exposure. A cohort of fifteen high school female soccer players participated in a prospective longitudinal study and underwent pre- and post-season functional magnetic resonance imaging (fMRI). During fMRI, athletes completed simultaneous bilateral ankle, knee, and hip flexion/extension movements against resistance (bilateral leg press) to characterize neural activity associated with lower extremity motor control. RHI data were binned into continuous categories between 20 g − 120 g (defined by progressively greater intervals), with the number of impacts independently modeled within the fMRI analyses. Results revealed that differential exposure to high magnitude RHIs (≥90 g - < 110 g and ≥ 110 g) was associated with acute changes in neural activity for the bilateral leg press (broadly inclusive of motor, visual, and cognitive regions; all p < 0.05 & z > 3.1). Greater exposure to high magnitude RHIs may impair lower extremity motor control through maladaptive neural mechanisms. Future work is warranted to extend these mechanistic findings and examine the linkages between RHI exposure and neural activity as it relates to subsequent neuromuscular control deficits.

Reward Learning as a Potential Mechanism for Improvement in Schizophrenia Spectrum Disorders Following Cognitive Remediation: Protocol for a Clinical, Nonrandomized, Pre-Post Pilot Study.

Cognitive impairment is common with schizophrenia spectrum disorders. Cognitive remediation (CR) is effective in improving global cognition, but not all individuals benefit from this type of intervention. A better understanding of the potential mechanism of action of CR is needed. One proposed mechanism is reward learning (RL), the cognitive processes responsible for adapting behavior following positive or negative feedback. It is proposed that the structure of CR enhances RL and motivation to engage in increasingly challenging tasks, and this is a potential mechanism by which CR improves cognitive functioning in schizophrenia. Our primary objective is to examine reward processing in individuals with schizophrenia before and after completing CR and to compare this with a group of matched clinical controls. We will assess whether RL mediates the relationship between CR and improved cognitive function and reduced negative symptoms. Potential differences in social RL and nonsocial RL in individuals with schizophrenia will also be investigated and compared with a healthy matched control group. We propose a clinical, nonrandomized, pre-post pilot study comparing the impact of CR on RL and neurocognitive outcomes. The study will use a combination of objective and subjective measures to assess neurocognitive, psychiatric symptoms, and neurophysiological domains. A total of 40 individuals with schizophrenia spectrum disorders (aged 18-35 years) will receive 12 weeks of CR therapy (n=20) or treatment as usual (n=20). Reward processing will be evaluated using a reinforcement learning task with 2 conditions (social reward vs nonsocial reward) at baseline and the 12-week follow-up. Functional magnetic resonance imaging responses will be measured during this task. To validate the reinforcement learning task, RL will also be assessed in 20 healthy controls, matched for age, sex, and premorbid functioning. Mixed-factorial ANOVAs will be conducted to evaluate treatment group differences. For the functional magnetic resonance imaging analysis, computational modeling will allow the estimation of learning parameters at each point in time, during each task condition, for each participant. We will use a variational Bayesian framework to measure how learning occurred during the experimental task and the subprocesses that underlie this learning. Second-level group analyses will examine how learning in patients differs from that observed in control participants and how CR alters learning efficiency and the underlying neural activity. As of September 2023, this study has enrolled 15 participants in the CR group, 1 participant in the treatment-as-usual group, and 11 participants in the healthy control group. Recruitment is expected to be completed by September 2024. Data analysis is expected to be completed and published in early 2025. The results of this study will contribute to the knowledge of CR and RL processes in severe mental illness and the understanding of the systems that impact negative symptoms and cognitive impairments within this population. DERR1-10.2196/52505.

Evidence of mirror therapy for recruitment of ipsilateral motor pathways in stroke recovery: A resting fMRI study

Mirror therapy (MT) has been proposed to promote motor recovery post-stroke through activation of mirror neuron system, recruitment of ipsilateral motor pathways, or/and increasing attention toward the affected limb. However, neuroimaging evidence for these mechanisms is still lacking. To uncover the underlying mechanisms, we designed a randomized controlled study and used a voxel-based whole-brain analysis of resting-state fMRI to explore the brain reorganizations induced by MT. Thirty-five stroke patients were randomized to an MT group (n ​= ​16) and a conventional therapy (CT) group (n ​= ​19) for a 4-week intervention. Before and after the intervention, the Fugl-Meyer Assessment Upper Limb subscale (FMA-UL) and resting-state fMRI were collected. A healthy cohort (n ​= ​16) was established for fMRI comparison. The changes in fractional amplitude of low-frequency fluctuation (fALFF) and seed-based functional connectivity were analyzed to investigate the impact of intervention. Results showed that greater FMA-UL improvement in the MT group was associated with the compensatory increase of fALFF in the contralesional precentral gyrus (M1) region and the re-establishment of functional connectivity between the bilateral M1 regions, which facilitate motor signals transmission via the ipsilateral motor pathways from the ipsilesional M1, contralesional M1, to the affected limb. A step-wise linear regression model revealed these two brain reorganization patterns collaboratively contributed to FMA-UL improvement. In conclusion, MT achieved motor rehabilitation primarily by recruitment of the ipsilateral motor pathways. Trial Registration Information: http://www.chictr.org.cn. Unique Identifier. ChiCTR-INR-17013644, submitted on December 2, 2017.

Effects of Savoring Meditation on Positive Emotions and Pain-Related Brain Function: A Mechanistic Randomized Controlled Trial in People With Rheumatoid Arthritis

Positive emotions are a promising target for intervention in chronic pain, but mixed findings across trials to date suggest that existing interventions may not be optimized to efficiently engage the target. The aim of the current pilot mechanistic randomized controlled trial was to test the effects of a positive emotion-enhancing intervention called Savoring Meditation on pain-related neural and behavioral targets in patients with rheumatoid arthritis. Participants included 44 patients with a physician-confirmed diagnosis of rheumatoid arthritis (n = 29 included in functional magnetic resonance imaging (fMRI) analyses), who were randomized to either Savoring Meditation or a Slow Breathing control. Both meditation interventions were brief (four 20-minute sessions). Self-report measures were collected pre-and post-intervention. An fMRI task was conducted at post-intervention, during which participants practiced the meditation technique on which they had been trained while exposed to non-painful and painful thermal stimuli. Savoring significantly reduced experimental pain intensity ratings relative to rest (P < .001). Savoring also increased cerebral blood flow in the ventromedial prefrontal cortex and increased connectivity between the ventromedial prefrontal cortex and caudate during noxious thermal stimulation relative to Slow Breathing (z = 2.3 voxelwise, false discovery rate cluster corrected P = .05). Participants in the Savoring condition also reported significantly increased positive emotions (ps < .05) and reduced anhedonic symptoms (P < .01) from pre- to post-intervention. These findings suggest that Savoring recruits reward-enhancing corticostriatal circuits in the face of pain, and future work should extend these findings to evaluate if these mechanisms of Savoring are associated with improved clinical pain outcomes in diverse patient populations. PerspectiveSavoring Meditation is a novel positive emotion-enhancing intervention designed for patients with chronic pain. The present findings provide preliminary evidence that Savoring Meditation is acutely analgesic, and engages neural and subjective emotional targets that are relevant to pain self-management. Future work should evaluate the clinical translation of these findings.

Exploring the impact of intensified multiple session tDCS over the left DLPFC on brain function in MCI: a randomized control trial

Transcranial direct current stimulation combined with cognitive training (tDCS-cog) represents a promising approach to combat cognitive decline among healthy older adults and patients with mild cognitive impairment (MCI). In this 5-day-long double-blinded randomized trial, we investigated the impact of intensified tDCS-cog protocol involving two trains of stimulation per day on working memory (WM) enhancement in 35 amnestic and multidomain amnestic MCI patients. Specifically, we focused to improve WM tasks relying on top-down attentional control and hypothesized that intensified tDCS would enhance performance of visual object matching task (VOMT) immediately after the stimulation regimen and at a 1-month follow-up. Secondarily, we explored whether the stimulation would augment online visual working memory training. Using fMRI, we aimed to elucidate the neural mechanisms underlying the intervention effects by analyzing BOLD activations during VOMT. Our main finding revealed no superior after-effects of tDCS-cog over the sham on VOMT among individuals with MCI as indicated by insignificant immediate and long-lasting after-effects. Additionally, the tDCS-cog did not enhance online training as predicted. The fMRI analysis revealed brain activity alterations in right insula that may be linked to tDCS-cog intervention. In the study we discuss the insignificant behavioral results in the context of the current evidence in tDCS parameter space and opening the discussion of possible interference between trained cognitive tasks.

Cortical quantity representations of visual numerosity and timing overlap increasingly into superior cortices but remain distinct

Many sensory brain areas are organized as topographic maps where neural response preferences change gradually across the cortical surface. Within association cortices, 7-Tesla fMRI and neural model-based analyses have also revealed many topographic maps for quantities like numerosity and event timing, often in similar locations. Numerical and temporal quantity estimations also show behavioral similarities and even interactions. For example, the duration of high-numerosity displays is perceived as longer than that of low-numerosity displays. Such interactions are often ascribed to a generalized magnitude system with shared neural responses across quantities. Anterior quantity responses are more closely linked to behavior. Here, we investigate whether common quantity representations hierarchically emerge by asking whether numerosity and timing maps become increasingly closely related in their overlap, response preferences, and topography. While the earliest quantity maps do not overlap, more superior maps overlap increasingly. In these overlapping areas, some intraparietal maps have consistently correlated numerosity and timing preferences, and some maps have consistent angles between the topographic progressions of numerosity and timing preferences. However, neither of these relationships increases hierarchically like the amount of overlap does. Therefore, responses to different quantities are initially derived separately, then progressively brought together, without generally becoming a common representation. Bringing together distinct responses to different quantities may underlie behavioral interactions and allow shared access to comparison and action planning systems.

A practical guide for combining functional regions of interest and white matter bundles.

Diffusion-weighted imaging (DWI) is the primary method to investigate macro- and microstructure of neural white matter in vivo. DWI can be used to identify and characterize individual-specific white matter bundles, enabling precise analyses on hypothesis-driven connections in the brain and bridging the relationships between brain structure, function, and behavior. However, cortical endpoints of bundles may span larger areas than what a researcher is interested in, challenging presumptions that bundles are specifically tied to certain brain functions. Functional MRI (fMRI) can be integrated to further refine bundles such that they are restricted to functionally-defined cortical regions. Analyzing properties of these Functional Sub-Bundles (FSuB) increases precision and interpretability of results when studying neural connections supporting specific tasks. Several parameters of DWI and fMRI analyses, ranging from data acquisition to processing, can impact the efficacy of integrating functional and diffusion MRI. Here, we discuss the applications of the FSuB approach, suggest best practices for acquiring and processing neuroimaging data towards this end, and introduce the FSuB-Extractor, a flexible open-source software for creating FSuBs. We demonstrate our processing code and the FSuB-Extractor on an openly-available dataset, the Natural Scenes Dataset.

Neural sensitivity to translational self- and object-motion velocities.

The ability to detect and assess world-relative object-motion is a critical computation performed by the visual system. This computation, however, is greatly complicated by the observer's movements, which generate a global pattern of motion on the observer's retina. How the visual system implements this computation is poorly understood. Since we are potentially able to detect a moving object if its motion differs in velocity (or direction) from the expected optic flow generated by our own motion, here we manipulated the relative motion velocity between the observer and the object within a stationary scene as a strategy to test how the brain accomplishes object-motion detection. Specifically, we tested the neural sensitivity of brain regions that are known to respond to egomotion-compatible visual motion (i.e., egomotion areas: cingulate sulcus visual area, posterior cingulate sulcus area, posterior insular cortex [PIC], V6+, V3A, IPSmot/VIP, and MT+) to a combination of different velocities of visually induced translational self- and object-motion within a virtual scene while participants were instructed to detect object-motion. To this aim, we combined individual surface-based brain mapping, task-evoked activity by functional magnetic resonance imaging, and parametric and representational similarity analyses. We found that all the egomotion regions (except area PIC) responded to all the possible combinations of self- and object-motion and were modulated by the self-motion velocity. Interestingly, we found that, among all the egomotion areas, only MT+, V6+, and V3A were further modulated by object-motion velocities, hence reflecting their possible role in discriminating between distinct velocities of self- and object-motion. We suggest that these egomotion regions may be involved in the complex computation required for detecting scene-relative object-motion during self-motion.

Connecting the dots: Motor and default mode network crossroads in post-stroke motor learning deficits

BackgroundStrokes frequently result in long-term motor deficits, imposing significant personal and economic burdens. However, our understanding of the underlying neural mechanisms governing motor learning in stroke survivors remains limited - a fact that poses significant challenges to the development and optimisation of therapeutic strategies. ObjectiveThis study investigates the diversity in motor learning aptitude and its associated neurological mechanisms. We hypothesised that stroke patients exhibit compromised overall motor learning capacity, which is associated with altered activity and connectivity patterns in the motor- and default-mode-network in the brain. MethodsWe assessed a cohort of 40 chronic-stage, mildly impaired stroke survivors and 39 age-matched healthy controls using functional Magnetic Resonance Imaging (fMRI) and connectivity analyses. We focused on neural activity and connectivity patterns during an unilateral motor sequence learning task performed with the unimpaired or non-dominant hand. Primary outcome measures included task-induced changes in neural activity and network connectivity. ResultsCompared to controls, stroke patients showed significantly reduced motor learning capacity, associated with diminished cerebral lateralization. Task induced activity modulation was reduced in the motor network but increased in the default mode network. The modulated activation strength was associated with an opposing trend in task-induced functional connectivity, with increased connectivity in the motor network and decreased connectivity in the DMN. ConclusionsStroke patients demonstrate altered neural activity and connectivity patterns during motor learning with their unaffected hand, potentially contributing to globally impaired motor learning skills. The reduced ability to lateralize cerebral activation, along with the enhanced connectivity between the right and left motor cortices in these patients, may signify maladaptive neural processes that impede motor adaptation, possibly affecting long-term rehabilitation post-stroke. The contrasting pattern of activity modulation and connectivity alteration in the default mode network suggests a nuanced role of this network in post-stroke motor learning. These insights could have significant implications for the development of customised rehabilitation strategies for stroke patients.

Impaired flexible reward learning in ADHD patients is associated with blunted reinforcement sensitivity and neural signals in ventral striatum and parietal cortex

Reward-based learning and decision-making are prime candidates to understand symptoms of attention deficit hyperactivity disorder (ADHD). However, only limited evidence is available regarding the neurocomputational underpinnings of the alterations seen in ADHD. This concerns flexible behavioral adaption in dynamically changing environments, which is challenging for individuals with ADHD. One previous study points to elevated choice switching in adolescent ADHD, which was accompanied by disrupted learning signals in medial prefrontal cortex.Here, we investigated young adults with ADHD (n = 17) as compared to age- and sex-matched controls (n = 17) using a probabilistic reversal learning experiment during functional magnetic resonance imaging (fMRI). The task requires continuous learning to guide flexible behavioral adaptation to changing reward contingencies. To disentangle the neurocomputational underpinnings of the behavioral data, we used reinforcement learning (RL) models, which informed the analysis of fMRI data.ADHD patients performed worse than controls particularly in trials before reversals, i.e., when reward contingencies were stable. This pattern resulted from ‘noisy’ choice switching regardless of previous feedback. RL modelling showed decreased reinforcement sensitivity and enhanced learning rates for negative feedback in ADHD patients. At the neural level, this was reflected in a diminished representation of choice probability in the left posterior parietal cortex in ADHD. Moreover, modelling showed a marginal reduction of learning about the unchosen option, which was paralleled by a marginal reduction in learning signals incorporating the unchosen option in the left ventral striatum.Taken together, we show that impaired flexible behavior in ADHD is due to excessive choice switching (‘hyper-flexibility’), which can be detrimental or beneficial depending on the learning environment. Computationally, this resulted from blunted sensitivity to reinforcement of which we detected neural correlates in the attention-control network, specifically in the parietal cortex. These neurocomputational findings remain preliminary due to the relatively small sample size.

Wearing a KN95/FFP2 facemask has no measureable effect on functional activity in a challenging working memory n-back task.

Wide use of facemasks is one of the many consequences of the COVID-19 pandemic. We used an established working memory n-back task in functional magnetic resonance imaging (fMRI) to explore whether wearing a KN95/FFP2 facemask affects overall performance and brain activation patterns. We provide here a prospective crossover design 3 T fMRI study with/without wearing a tight FFP2/KN95 facemask, including 24 community-dwelling male healthy control participants (mean age ± SD = 37.6 ± 12.7 years) performing a 2-back task. Data analysis was performed using the FSL toolbox, performing both task-related and functional connectivity independent component analyses. Wearing an FFP2/KN95 facemask did not impact behavioral measures of the 2-back task (response time and number of errors). The 2-back task resulted in typical activations in working-memory related areas in both MASK and NOMASK conditions. There were no statistically significant differences in MASK versus NOMASK while performing the 2-back task in both task-related and functional connectivity fMRI analyses. The effect of wearing a tight FFP2/KN95 facemasks did not significantly affect working memory performance and brain activation patterns of functional connectivity.

Constrained Independent Vector Analysis with Reference for Multi-Subject fMRI Analysis.

Independent component analysis (ICA) is now a widely used solution for the analysis of multi-subject functional magnetic resonance imaging (fMRI) data. Independent vector analysis (IVA) generalizes ICA to multiple datasets (multi-subject data). Along with higher-order statistical information in ICA, it leverages the statistical dependence across the datasets as an additional type of statistical diversity. As such, IVA preserves variability in the estimation of single-subject maps but its performance might suffer when the number of datasets increases. Constrained IVA is an effective way to bypass computational issues and improve the quality of separation by incorporating available prior information. Existing constrained IVA approaches often rely on user-defined threshold values to define the constraints. However, an improperly selected threshold can have a negative impact on the final results. This paper proposes two novel methods for constrained IVA: one using an adaptive-reverse scheme to select variable thresholds for the constraints and a second one based on a threshold-free formulation by leveraging the unique structure of IVA. Notably, the proposed algorithms do not require all components to be constrained, utilizing free components to model interferences and components that might not be in the reference set. We demonstrate that our solutions provide an attractive solution to multi-subject fMRI analysis both by simulations and through analysis of resting state fMRI data collected from 98 subjects - the highest number of subjects ever used by IVA algorithms. Our results show that both proposed approaches obtain significantly better separation quality and model match while providing computationally efficient and highly reproducible solutions.

A whole-brain neuromark resting-state fMRI analysis of first-episode and early psychosis: Evidence of aberrant cortical-subcortical-cerebellar functional circuitry

Psychosis (including symptoms of delusions, hallucinations, and disorganized conduct/speech) is a main feature of schizophrenia and is frequently present in other major psychiatric illnesses. Studies in individuals with first-episode (FEP) and early psychosis (EP) have the potential to interpret aberrant connectivity associated with psychosis during a period with minimal influence from medication and other confounds. The current study uses a data-driven whole-brain approach to examine patterns of aberrant functional network connectivity (FNC) in a multi-site dataset comprising resting-state functional magnetic resonance images (rs-fMRI) from 117 individuals with FEP or EP and 130 individuals without a psychiatric disorder, as controls. Accounting for age, sex, race, head motion, and multiple imaging sites, differences in FNC were identified between psychosis and control participants in cortical (namely the inferior frontal gyrus, superior medial frontal gyrus, postcentral gyrus, supplementary motor area, posterior cingulate cortex, and superior and middle temporal gyri), subcortical (the caudate, thalamus, subthalamus, and hippocampus), and cerebellar regions. The prominent pattern of reduced cerebellar connectivity in psychosis is especially noteworthy, as most studies focus on cortical and subcortical regions, neglecting the cerebellum. The dysconnectivity reported here may indicate disruptions in cortical-subcortical-cerebellar circuitry involved in rudimentary cognitive functions which may serve as reliable correlates of psychosis.

Stereotaxic Coordinates of Human Hypothalamic Nuclei Used for Region of Interest Analyses in Functional Magnetic Resonance Imaging.

The hypothalamus maintains homeostasis by controlling various organs and the central nervous system, but analyzing the human hypothalamic nuclei is challenging. Our previous studies applied areal parcellation to high-resolution functional magnetic resonance imaging (fMRI) data to delineate hypothalamic nuclei boundaries. This article presents stereotaxic coordinates of these nuclei for fMRI analyses, offering guidance on defining regions of interest and appropriate spatial smoothing kernel sizes. The provided coordinates aid future research in nuclear level hypothalamus analyses.

The imprint of dissociative seizures on the brain

BackgroundIncreased resting state functional connectivity between regions involved in emotion control with regions with other specializations, e.g. motor control (emotional hyperconnectivity) is one of the most consistent imaging findings in persons suffering from dissociative seizures (DS). The overall goal of this study was to better characterize DS-related emotional hyperconnectivity using dynamic resting state analysis combined with brainstem volumetry to investigate 1. If emotional hyperconnectivity is restricted to a single state. 2. How volume losses within the modulatory and emotional motor subnetworks of the neuromodulatory system influence the expression of the emotional hyperconnectivity. Methods13 persons with dissociative seizures (PDS) (f/m:10/3, mean age (SD) 44.6 (11.5)) and 15 controls (CON) (f/m:10/5, mean age (SD) 41.7 (13.0)) underwent a mental health test battery and structural and functional imaging at 3 T. Deformation based morphometry was used to assess brain volume loss by extracting the mean Jacobian determinants from 457 brain, forebrain and brainstem structures. The bold signals from 445 brainstem and brain rois were extracted with CONN and a dynamic fMRI analysis combined with graph and hierarchical analysis was used to identify and characterize 9 different brain states. Welch’s t tests and Kendall tau tests were used for group comparisons and correlation analyses. ResultsThe duration of Brain state 6 was longer in PDS than in CON (93.1(88.3) vs. 23.4(31.2), p = 0.01) and positively correlated with higher degrees of somatization, depression, PTSD severity and dissociation. Its global connectivity was higher in PDS than CON (90.4(3.2) vs 86.5(4.2) p = 0.01) which was caused by an increased connectivity between regions involved in emotion control and regions involved in sense of agency/body control. The brainstem and brainstem-forebrain modulatory and emotional motor subnetworks of the neuromodulatory system were atrophied in PDS. Atrophy severity within the brainstem-forebrain subnetworks was correlated with state 6 dwell time (modulatory: tau = -0.295, p = 0.03; emotional motor: tau = -0.343, p = 0.015) and atrophy severity within the brainstem subnetwork with somatization severity (modulatory: tau = -0.25, p = 0.036; emotional motor: tau = -0.256, p = 0.033). ConclusionDS-related emotional hyperconnectivity was restricted to state 6 episodes. The remaining states were not different between PDS and CON. The modulatory subnetwork synchronizes brain activity across brain regions. Atrophy and dysfunction within that subnetwork could facilitate the abnormal interaction between regions involved in emotion control with those controlling sense of agency/body ownership during state 6 and contribute to the tendency for somatization in PDS. The emotional motor subnetwork controls the activity of spinal motoneurons. Atrophy and dysfunction within this subnetwork could impair that control resulting in motor symptoms during DS. Taken together, these findings indicate that DS have a neurophysiological underpinning.

Neural correlates of episodic memory decline following electroconvulsive therapy: An exploratory functional magnetic resonance imaging study.

Electroconvulsive therapy (ECT) is an efficient and rapid-acting treatment indicated for severe depressive disorders. While ECT is commonly accompanied by transient memory decline, the brain mechanisms underlying these side effects remain unclear. In this exploratory functional magnetic resonance (fMRI) study, we aimed to compare effects of ECT versus pharmacological treatment on neural response during episodic memory encoding in patients with affective disorders. This study included 32 ECT-treated patients (major depressive disorder (MDD), n = 23; bipolar depression, n = 9) and 40 partially remitted patients in pharmacological treatment (MDD, n = 24; bipolar disorder, n = 16). Participants underwent neuropsychological assessment, a strategic picture encoding fMRI scan paradigm, and mood rating. The ECT group was assessed before ECT (pre-ECT) and 3 days after their eighth ECT session (post-ECT). Groups were comparable on age, gender, and educational years (ps ⩾ 0.05). Within-group analyses revealed a selective reduction in verbal learning and episodic memory pre- to post-ECT (p = 0.012) but no decline in global cognitive performance (p = 0.3). Functional magnetic resonance imaging analyses adjusted for mood symptoms revealed greater activity in ECT-treated patients than pharmacologically treated No-ECT patients across left precentral gyrus (PCG), right dorsomedial prefrontal cortex (dmPFC), and left middle frontal gyrus (MFG). In ECT-treated patients, greater decline in verbal learning and memory performance from pre- to post-ECT correlated with higher PCG response (r = -0.46, p = 0.008), but not with dmPFC or MFG activity (ps ⩾ 0.1), post-ECT. Episodic memory decline was related to greater neural activity in the left PCG, but unrelated to increased dmPFC and MFG activity, immediately after ECT.

Neurological mechanism and efficacy of acupuncture for breast cancer-related insomnia: a study protocol for randomized clinical trial.

Breast cancer survivors (BCSs) are at a higher risk of developing insomnia. The negative effects of cancer-related insomnia (CRI) include depression, anxiety, fatigue, aggressive pain, impaired immune functioning, decreased quality of life, and even increased cancer mortality. Although preliminary progress has been made in the treatment of CRI with acupuncture, the evidence is insufficient and the neurological mechanism underlying the effect of acupuncture is still unclear. The study employs a single-blinded, randomized, controlled trial design. A total of 80 participants will be randomly allocated in a 1:1 ratio to either the treatment group (n = 40) or the control group (n = 40). The former will receive acupuncture treatment, while the latter will receive sham acupuncture treatment. Both groups will receive 12 sessions over a 4-week period, three times per week (every other day), and each session will last for 30 min. Follow-up assessments will be conducted in week 8. The primary outcome will be the treatment response rate. Secondary outcomes include the change in Insomnia Severity Index (ISI), the treatment remission rate, actigraphy sleep assessment, Generalized Anxiety Disorder Scale (GAD-7), Patient Health Questionnaire-9 (PHQ-9), Quality of Life Core Scale (QLQ-C30), the weekly usage of remedial drugs, and functional magnetic resonance imaging (fMRI) analysis. Data for the outcomes will be collected at week 0 (the baseline), week 1 (the intervention period), week 4 (the post-treatment period), and week 8 (the follow-up period). The objective of this study is to assess the efficacy of acupuncture for patients with CRI in comparison with sham acupuncture. Additionally, the research aims to explore the neuropathological mechanisms of CRI and provide the first evidence on the characteristics of acupuncture treatment using fMRI. We expect that the results of this study will provide valuable scientific evidence of acupuncture treatment for CRI.Clinical trial registration: Chinese Clinical Trial Registry, identifier ChiCTR2300070349: https://www.chictr.org.cn/showproj.html?proj=188677.

Insights from simultaneous EEG-fMRI and patient data illuminate the role of the anterior medial temporal lobe in N400 generation

The N400, a negative event-related potential (ERP) peaking approximately 400 ms after stimulus onset, is known to reflect the processing of semantic information. While scalp recordings have contributed to understanding the psychological processes underlying the N400, they have been limited in identifying its neural basis. However, recent intracranial ERP recordings and fMRI studies have shed light on the crucial role of the anterior medial temporal lobe (AMTL) in semantic information processing. These findings suggest that the N400 partially represents activity in the AMTL structures. To investigate the neural underpinnings of the N400 effect, we simultaneously recorded ERPs and event-related fMRI during a semantic priming paradigm in a sample of 12 young, healthy subjects. Additionally, we collected ERPs and structural brain data from older healthy adults and patients with amnestic mild cognitive impairment (aMCI), a population characterized by neurodegenerative changes in the AMTL. In our fMRI results, we identified bilateral loci in the AMTL as the global maxima. Employing an EEG-informed fMRI analysis, we explored trial-to-trial fluctuations in semantic processing by linking single-trial N400 amplitudes to the Blood Oxygen Level Dependent (BOLD) signal. This approach provided the first direct evidence linking the N400 recorded at the scalp level to the corresponding BOLD signal in the AMTL. Consistent with these findings, patients with aMCI exhibited a diminished N400 effect compared to healthy older adults. Furthermore, voxel-based morphometry analysis revealed a correlation between the magnitude of the N400 effect and the integrity of the AMTL. By integrating data from simultaneous EEG-fMRI, and patient studies, our research advances our understanding of the neural substrate of the N400 and highlights the critical involvement of the AMTL in semantic processing.

Neurophysiological hallmarks of Huntington's disease progression: an EEG and fMRI connectivity study.

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) can provide corroborative data on neurophysiological alterations in Huntington's disease (HD). However, the alterations in EEG and fMRI resting-state functional connectivity (rsFC), as well as their interrelations, at different stages of HD remain insufficiently investigated. This study aimed to identify neurophysiological alterations in individuals with preclinical HD (preHD) and early manifest HD (EMHD) by analyzing EEG and fMRI rsFC and examining their interrelationships. We found significant differences in EEG power between preHD individuals and healthy controls (HC), with a decrease in power in a specific frequency range at the theta-alpha border and slow alpha activity. In EMHD patients, in addition to the decrease in power in the 7-9 Hz range, a reduction in power within the classic alpha band compared to HC was observed. The fMRI analysis revealed disrupted functional connectivity in various brain networks, particularly within frontal lobe, putamen-cortical, and cortico-cerebellar networks, in individuals with the HD mutation compared to HC. The analysis of the relationship between EEG and fMRI rsFC revealed an association between decreased alpha power, observed in individuals with EMHD, and increased connectivity in large-scale brain networks. These networks include putamen-cortical, DMN-related and cortico-hippocampal circuits. Overall, the findings suggest that EEG and fMRI provide valuable information for monitoring pathological processes during the development of HD. A decrease in inhibitory control within the putamen-cortical, DMN-related and cortico-hippocampal circuits, accompanied by a reduction in alpha and theta-alpha border oscillatory activity, could potentially contribute to cognitive decline in HD.

The neurocognitive role of working memory load when Pavlovian motivational control affects instrumental learning.

Research suggests that a fast, capacity-limited working memory (WM) system and a slow, incremental reinforcement learning (RL) system jointly contribute to instrumental learning. Thus, situations that strain WM resources alter instrumental learning: under WM loads, learning becomes slow and incremental, the reliance on computationally efficient learning increases, and action selection becomes more random. It is also suggested that Pavlovian learning influences people's behavior during instrumental learning by providing hard-wired instinctive responses including approach to reward predictors and avoidance of punishment predictors. However, it remains unknown how constraints on WM resources affect instrumental learning under Pavlovian influence. Thus, we conducted a functional magnetic resonance imaging (fMRI) study (N = 49) in which participants completed an instrumental learning task with Pavlovian-instrumental conflict (the orthogonalized go/no-go task) both with and without extra WM load. Behavioral and computational modeling analyses revealed that WM load reduced the learning rate and increased random choice, without affecting Pavlovian bias. Model-based fMRI analysis revealed that WM load strengthened RPE signaling in the striatum. Moreover, under WM load, the striatum showed weakened connectivity with the ventromedial and dorsolateral prefrontal cortex when computing reward expectations. These results suggest that the limitation of cognitive resources by WM load promotes slow and incremental learning through the weakened cooperation between WM and RL; such limitation also makes action selection more random, but it does not directly affect the balance between instrumental and Pavlovian systems.