Magnetic Resonance Imaging Session Research Articles

Dysfunction of the magnocellular subdivision of the visual thalamus in developmental dyslexia.

Developmental dyslexia (DD) is one of the most common learning disorders, affecting millions of children and adults worldwide. To date, scientific research has attempted to explain DD primarily based on pathophysiological alterations in the cerebral cortex. In contrast, several decades ago, pioneering research on five post-mortem human brains suggested that a core characteristic of DD might be morphological alterations in a specific subdivision of the visual thalamus - the magnocellular LGN (M-LGN). However, due to considerable technical challenges in investigating LGN subdivisions non-invasively in humans, this finding was never confirmed in-vivo, and its relevance for DD pathology remained highly controversial. Here, we leveraged recent advances in high-resolution magnetic resonance imaging (MRI) at high field strength (7 Tesla) to investigate the M-LGN in DD in-vivo. Using a case-control design, we acquired data from a large sample of young adults with DD (n = 26; age 28 ± 7 years; 13 females) and matched control participants (n = 28; age 27 ± 6 years; 15 females). Each participant completed a comprehensive diagnostic behavioral test battery and participated in two MRI sessions, including three functional MRI experiments and one structural MRI acquisition. We measured blood-oxygen-level-dependent responses and longitudinal relaxation rates to compare both groups on LGN subdivision function and myelination. Based on previous research, we hypothesized that the M-LGN is altered in DD and that these alterations are associated with a key DD diagnostic score, i.e., rapid letter and number naming (RANln). The results showed aberrant responses of the M-LGN in DD compared to controls, which was reflected in a different functional lateralization of this subdivision between groups. These alterations were associated with RANln performance, specifically in male DD. We also found lateralization differences in the longitudinal relaxation rates of the M-LGN in DD relative to controls. Conversely, the other main subdivision of the LGN, the parvocellular LGN (P-LGN), showed comparable blood-oxygen-level-dependent responses and longitudinal relaxation rates between groups. The present study is the first to unequivocally show that M-LGN alterations are a hallmark of DD, affecting both the function and microstructure of this subdivision. It further provides a first functional interpretation of M-LGN alterations and a basis for a better understanding of sex-specific differences in DD with implications for prospective diagnostic and treatment strategies.

The effects of N-acetyl cysteine on intrinsic functional connectivity and neural alcohol cue reactivity in treatment-seeking individuals with alcohol use disorder: a preliminary study.

N-acetyl cysteine (NAC) is a potential pharmacotherapy for alcohol use disorder (AUD), but it is not known whether it modulates neural activation to alcohol cues or intrinsic functional connectivity. We investigated whether NAC attenuates (i) alcohol cue-elicited activation, and (ii) intrinsic functional connectivity compared to placebo in patients with AUD. In this preliminary study, twenty-three individuals (7 females) with moderate-severe AUD received daily NAC (2400mg/day, n = 9), or a placebo (n = 14) for at least 2 weeks. Participants completed a pre-treatment functional magnetic resonance imaging session (T0) and a post-treatment session (T1) comprising resting-state and visual alcohol cue reactivity task acquisitions. Activation differences between sessions, treatment, and session-by-treatment interaction were assessed. Resting-state functional connectivity examined using 377 node ROI-to-ROIs evaluated whether NAC reduced intrinsic functional connectivity after treatment. There were no differences in alcohol cue reactivity for brain activation or subjective craving between NAC and placebo during treatment or across sessions, or significant interaction. A significant treatment-by-time interaction, with reduced intrinsic connectivity was observed after treatment (T1) for NAC-treated compared to placebo-treated patients in the posterior cingulate node (9, left hemisphere) of the dorsal attentional network and connections to salience, ventral-attentional, somatosensory, and visual-peripheral networks implicated in AUD. NAC reduced intrinsic functional connectivity in patients with moderate-severe AUD after treatment compared to placebo, but did not attenuate alcohol cue-elicited activation. However, the absence of cue reactivity findings may result from low power, rather than the absence of cue reactivity findings associated with NAC. These results provide preliminary evidence that NAC treatment may modulate intrinsic functional connectivity brain activation in patients with alcohol use disorder, but replication in larger studies are required to determine the strength of this effect and any associations with clinical outcomes. Clinical Trials Registration: ClinicalTrials.gov Identifier: NCT03879759.

The causal role of the subthalamic nucleus in the inhibitory network.

The neural network mediating successful response inhibition mainly includes right hemisphere activation of the pre-supplementary motor area, inferior frontal gyrus (IFG), subthalamic nucleus (STN), and caudate nucleus. However, the causal role of these regions in the inhibitory network is undefined. Five patients with Parkinson's disease were assessed prior to and after therapeutic thermal ablation of the right STN in two separate functional magnetic resonance imaging (fMRI) sessions while performing a stop-signal task. Initiation times were faster but motor inhibition with the left hand (contralateral to the lesion) was significantly impaired as evident in prolonged stop-signal reaction times. Reduced inhibition after right subthalamotomy was associated (during successful inhibition) with the recruitment of basal ganglia regions outside the established inhibitory network. They included the putamen and caudate together with the anterior cingulate cortex and IFG of the left hemisphere. Subsequent network connectivity analysis (with the seed over the nonlesioned left STN) revealed a new inhibitory network after right subthalamotomies. Our results highlight the causal role of the right STN in the neural network for motor inhibition and the possible basal ganglia mechanisms for compensation upon losing a key node of the inhibition network.

Evolving brain network dynamics in early childhood: Insights from modular graph metrics

Modular dynamic graph theory metrics effectively capture the patterns of dynamic information interaction during human brain development. While existing research has employed modular algorithms to examine the overall impact of dynamic changes in community structure throughout development, there is a notable gap in understanding the cross-community dynamic changes within different functional networks during early childhood and their potential contributions to the efficiency of brain information transmission. This study seeks to address this gap by tracing the trajectories of cross-community structural changes within early childhood functional networks and modeling their contributions to information transmission efficiency. We analyzed 194 functional imaging scans from 83 children aged 2 to 8 years, who participated in passive viewing functional magnetic resonance imaging sessions. Utilizing sliding windows and modular algorithms, we evaluated three spatiotemporal metrics—temporal flexibility, spatiotemporal diversity, and within-community spatiotemporal diversity—and four centrality metrics: within-community degree centrality, eigenvector centrality, between-community degree centrality, and between-community eigenvector centrality. Mixed-effects linear models revealed significant age-related increases in the temporal flexibility of the default mode network (DMN), executive control network (ECN), and salience network (SN), indicating frequent adjustments in community structure within these networks during early childhood. Additionally, the spatiotemporal diversity of the SN also displayed significant age-related increases, highlighting its broad pattern of cross-community dynamic interactions. Conversely, within-community spatiotemporal diversity in the language network exhibited significant age-related decreases, reflecting the network's gradual functional specialization. Furthermore, our findings indicated significant age-related increases in between-community degree centrality across the DMN, ECN, SN, language network, and dorsal attention network, while between-community eigenvector centrality also increased significantly for the DMN, ECN, and SN. However, within-community eigenvector centrality remained stable across all functional networks during early childhood. These results suggest that while centrality of cross-community interactions in early childhood functional networks increases, centrality within communities remains stable. Finally, mediation analysis was conducted to explore the relationships between age, brain dynamic graph metrics, and both global and local efficiency based on community structure. The results indicated that the dynamic graph metrics of the SN primarily mediated the relationship between age and the decrease in global efficiency, while those of the DMN, language network, ECN, dorsal attention network, and SN primarily mediated the relationship between age and the increase in local efficiency. This pattern suggests a developmental trajectory in early childhood from global information integration to local information segregation, with the SN playing a pivotal role in this transformation. This study provides novel insights into the mechanisms by which early childhood brain functional development impacts information transmission efficiency through cross-community adjustments in functional networks.

The rhythmic mind: brain functions of percussionists in improvisation.

Percussionists stand out for their expertise in rhythm, with the network for musical rhythm (NMR) serving a vital neurological function in their improvisation, which is deeply rooted in comprehensive musical knowledge. Our research examines the central representations of various improvisation tactics used by percussionists and investigates the interactions between the NMR and other relevant neural networks. Twenty-five percussionists participated in functional magnetic resonance imaging (fMRI) sessions, which included two cognitive strategies of improvisation. Structural improvisation (SIMP) emphasized rhythmic patterns, while free improvisation (FIMP) focused on musical spontaneity. Sight-reading scenario served as the reference condition. Paired t-tests were utilized for comparative analyses. The findings revealed a dynamic interplay characterized by increased activity in the executive control network and NMR, along with decreased activity in the default mode network during SIMP. During FIMP, heightened activity was observed in the executive control network, NMR, limbic, and memory systems. In both SIMP vs. sight-reading and FIMP vs. sight-reading comparisons, the visual network's activity decreased, a trend also observed in the comparative analysis of FIMP vs. SIMP. In SIMP, percussionists leverage external rhythmic signals, resulting in heightened NMR and ECN activity and reduced DMN activity. In contrast, FIMP is characterized by a rise in activity within the NMR, ECN, limbic system, memory system, and reward system, underscoring the vital roles of motivation and memory in the rapid production of spontaneous musical ideas within set frameworks. The diminished activity in the visual network during FIMP compared to SIMP suggests less reliance on visual stimuli in FIMP. These findings suggest that various improvisational tactics may engage different neural pathways.

Get out of my head: social evaluative brain states carry over into post-feedback rest and influence remembering how others view us.

Learning how others perceive us helps us tune our behavior to form adaptive relationships. But which perceptions stick with us? And when in the learning process are they codified in memory? We leveraged a popular television series-The Office-to answer these questions. Prior to their functional magnetic resonance imaging (fMRI) session, viewers of The Office reported which characters they identified with, as well as which characters they perceived another person (i.e. counterpart) was similar to. During their fMRI scan, participants found out which characters other people thought they and the counterpart were like, and also completed rest scans. Participants remembered more feedback inconsistent with their self-views (vs. views of the counterpart). Although neural activity while encoding self-inconsistent feedback did not meaningfully predict memory, returning to the inconsistent self feedback during subsequent rest did. During rest, participants reinstated neural patterns engaged while receiving self-inconsistent feedback in the dorsomedial prefrontal cortex (DMPFC). DMPFC reinstatement also quadratically predicted self-inconsistent memory, with too few or too many reinstatements compromising memory performance. Processing social feedback during rest may impact how we remember and integrate the feedback, especially when it contradicts our self-views.

Automatic segmentation of the spinal cord nerve rootlets

Abstract Precise identification of spinal nerve rootlets is relevant to delineate spinal levels for the study of functional activity in the spinal cord. The goal of this study was to develop an automatic method for the semantic segmentation of spinal nerve rootlets from T2-weighted magnetic resonance imaging (MRI) scans. Images from two open-access 3T MRI datasets were used to train a 3D multi-class convolutional neural network using an active learning approach to segment C2-C8 dorsal nerve rootlets. Each output class corresponds to a spinal level. The method was tested on 3T T2-weighted images from three datasets unseen during training to assess inter-site, inter-session, and inter-resolution variability. The test Dice score was 0.67 ± 0.16 (mean ± standard deviation across testing images and rootlets levels), suggesting a good performance. The method also demonstrated low inter-vendor and inter-site variability (coefficient of variation ≤ 1.41%), as well as low inter-session variability (coefficient of variation ≤ 1.30%), indicating stable predictions across different MRI vendors, sites, and sessions. The proposed methodology is open-source and readily available in the Spinal Cord Toolbox (SCT) v6.2 and higher.

Sheep (Ovis aries) training protocol for voluntary awake and unrestrained structural brain MRI acquisitions

Magnetic resonance imaging (MRI) is a non-invasive technique that requires the participant to be completely motionless. To date, MRI in awake and unrestrained animals has only been achieved with humans and dogs. For other species, alternative techniques such as anesthesia, restraint and/or sedation have been necessary. Anatomical and functional MRI studies with sheep have only been conducted under general anesthesia. This ensures the absence of movement and allows relatively long MRI experiments but it removes the non-invasive nature of the MRI technique (i.e., IV injections, intubation). Anesthesia can also be detrimental to health, disrupt neurovascular coupling, and does not permit the study of higher-level cognition. Here, we present a proof-of-concept that sheep can be trained to perform a series of tasks, enabling them to voluntarily participate in MRI sessions without anesthesia or restraint. We describe a step-by-step training protocol based on positive reinforcement (food and praise) that could be used as a basis for future neuroimaging research in sheep. This protocol details the two successive phases required for sheep to successfully achieve MRI acquisitions of their brain. By providing structural brain MRI images from six out of ten sheep, we demonstrate the feasibility of our training protocol. This innovative training protocol paves the way for the possibility of conducting animal welfare-friendly functional MRI studies with sheep to investigate ovine cognition.

Hippocampal gray matter volume in young adulthood varies with adolescent alcohol use.

Adolescent substance use is linked with negative future outcomes (e.g., depression, anxiety, substance use disorder). Given that the brain undergoes significant maturation during adolescence, this developmental period may represent a time of particular vulnerability to substance use. Neuroimaging research has largely focused on heavy or binge patterns of substance use; thus, relatively less is known about the neural impact of a broader range of adolescent substance use. Characterizing the neural impact of a broader range of adolescent substance use may inform prevention and treatment efforts. The present study investigated relationships between adolescent substance use trajectories (i.e., alcohol, tobacco, and cannabis) and gray matter volume in young adulthood. Substance use was assessed in 1,594 participants at ages 11, 13, 16, and 19. Following the last assessment, 320 participants completed a single magnetic resonance imaging session to assess brain gray matter volume. Latent growth curve models were used to estimate growth parameters characterizing alcohol, tobacco, and cannabis use trajectories for each participant. These growth parameters (i.e., intercept, linear slope, and quadratic slope) were then used as predictors of gray matter volume. The gray matter volume of the hippocampus was positively associated with age 14 alcohol use (i.e., intercept) but not other trajectories (i.e., progression or acceleration) or substances (tobacco or cannabis). These results provide new insight into the neural impact of distinct adolescent alcohol, tobacco, and cannabis use trajectories, which may help to refine prevention and treatment efforts. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Cortical Lesions as an Early Hallmark of Multiple Sclerosis: Visualization by 7 T MRI.

Compelling evidence indicates a significant involvement of cortical lesions in the progressive phase of multiple sclerosis (MS), significantly contributing to late-stage disability. Despite the promise of ultra-high-field magnetic resonance imaging (MRI) in detecting cortical lesions, current evidence falls short in providing insights into the existence of such lesions during the early stages of MS or their underlying cause. This study delineated, at the early stage of MS, (1) the prevalence and spatial distribution of cortical lesions identified by 7 T MRI, (2) their relationship with white matter lesions, and (3) their clinical implications. Twenty individuals with early-stage relapsing-remitting MS (disease duration <1 year) underwent a 7 T MRI session involving T1-weighted MP2RAGE, T2*-weighted multiGRE, and T2-weighted FLAIR sequences for cortical and white matter segmentation. Disability assessments included the Expanded Disability Status Scale, the Multiple Sclerosis Functional Composite, and an extensive evaluation of cognitive function. Cortical lesions were detected in 15 of 20 patients (75%). MP2RAGE revealed a total of 190 intracortical lesions (median, 4 lesions/case [range, 0-44]) and 216 leukocortical lesions (median, 2 lesions/case [range, 0-75]). Although the number of white matter lesions correlated with the total number of leukocortical lesions (r = 0.91, P < 0.001), no correlation was observed between the number of white matter or leukocortical lesions and the number of intracortical lesions. Furthermore, the number of leukocortical lesions but not intracortical or white-matter lesions was significantly correlated with cognitive impairment (r = 0.63, P = 0.04, corrected for multiple comparisons). This study highlights the notable prevalence of cortical lesions at the early stage of MS identified by 7 T MRI. There may be a potential divergence in the underlying pathophysiological mechanisms driving distinct lesion types, notably between intracortical lesions and white matter/leukocortical lesions. Moreover, during the early disease phase, leukocortical lesions more effectively accounted for cognitive deficits.

Mindfulness-based cognitive therapy neurobiology in treatment-resistant obsessive-compulsive disorder: A domain-related resting-state networks approach

Mindfulness-based cognitive therapy (MBCT) stands out as a promising augmentation psychological therapy for patients with obsessive-compulsive disorder (OCD). To identify potential predictive and response biomarkers, this study examines the relationship between clinical domains and resting-state network connectivity in OCD patients undergoing a 3-month MBCT programme. Twelve OCD patients underwent two resting-state functional magnetic resonance imaging sessions at baseline and after the MBCT programme. We assessed four clinical domains: positive affect, negative affect, anxiety sensitivity, and rumination. Independent component analysis characterised resting-state networks (RSNs), and multiple regression analyses evaluated brain-clinical associations. At baseline, distinct network connectivity patterns were found for each clinical domain: parietal-subcortical, lateral prefrontal, medial prefrontal, and frontal-occipital. Predictive and response biomarkers revealed significant brain-clinical associations within two main RSNs: the ventral default mode network (vDMN) and the frontostriatal network (FSN). Key brain nodes —the precuneus and the frontopolar cortex— were identified within these networks. MBCT may modulate vDMN and FSN connectivity in OCD patients, possibly reducing symptoms across clinical domains. Each clinical domain had a unique baseline brain connectivity pattern, suggesting potential symptom-based biomarkers. Using these RSNs as predictors could enable personalised treatments and the identification of patients who would benefit most from MBCT.

Neurite Orientation Dispersion and Density Imaging (NODDI) of Brain Microstructure in Adolescent Cannabis and Nicotine Use.

Despite evidence suggesting deleterious effects of cannabis and nicotine tobacco product (NTP) use on white matter integrity, there have been limited studies examining white matter integrity among users of both cannabis and nicotine. Further, updated white matter methodology provides opportunities to investigate use patterns on neurite orientation dispersion and density (NODDI) indices and subtle tissue changes related to the intra- and extra-neurite compartment. We aimed to investigate how cannabis and NTP use among adolescents and young adults interacts to impact the white matter integrity microstructure. A total of 221 participants between the ages of 16 and 22 completed the Customary Drinking and Drug Use Record (CDDR) to measure substance use, and underwent a magnetic resonance imaging (MRI) session. Participants were divided into NTP-control and NTP groupings and cannabis-control and cannabis groupings (≥26 NTP/cannabis uses in past 6 months). Tract-Based Spatial Statistics (TBSS) and two-way between-subjects ANOVA investigated the effects of NTP use group, cannabis use group, and their interaction on fractional anisotropy (FA) and NODDI indices while controlling for age and biological sex. NTP use was associated with decreased FA values and increased orientation dispersion in the left anterior capsule. There were no significant effects of cannabis use or the interaction of NTP and cannabis use on white matter outcomes. NTP use was associated with altered white matter integrity in an adolescent and young adult sample. Findings suggest that NTP-associated alterations may be linked to altered fiber tract geometry and dispersed neurite structures versus myelination, as well as differential effects of NTP and cannabis use on white matter structure. Future work is needed to investigate how altered white matter is related to downstream behavioral effects from NTP use.

Inner sense of rhythm: percussionist brain activity during rhythmic encoding and synchronization.

The main objective of this research is to explore the core cognitive mechanisms utilized by exceptionally skilled percussionists as they navigate complex rhythms. Our specific focus is on understanding the dynamic interactions among brain regions, respectively, related to externally directed cognition (EDC), internally directed cognition (IDC), and rhythm processing, defined as the neural correlates of rhythm processing (NCRP). The research involved 26 participants each in the percussionist group (PG) and control group (CG), who underwent task-functional magnetic resonance imaging (fMRI) sessions focusing on rhythm encoding and synchronization. Comparative analyses were performed between the two groups under each of these conditions. Rhythmic encoding showed decreased activity in EDC areas, specifically in the right calcarine cortex, left middle occipital gyrus, right fusiform gyrus, and left inferior parietal lobule, along with reduced NCRP activity in the left dorsal premotor, right sensorimotor cortex, and left superior parietal lobule. During rhythmic synchronization, there was increased activity in IDC areas, particularly in the default mode network, and in NCRP areas including the left inferior frontal gyrus and bilateral putamen. Conversely, EDC areas like the right dorsolateral prefrontal gyrus, right superior temporal gyrus, right middle occipital gyrus, and bilateral inferior parietal lobule showed decreased activity, as did NCRP areas including the bilateral dorsal premotor cortex, bilateral ventral insula, bilateral inferior frontal gyrus, and left superior parietal lobule. PG's rhythm encoding is characterized by reduced cognitive effort compared to CG, as evidenced by decreased activity in brain regions associated with EDC and the NCRP. Rhythmic synchronization reveals up-regulated IDC, down-regulated EDC involvement, and dynamic interplay among regions with the NCRP, suggesting that PG engages in both automatic and spontaneous processing simultaneously. These findings provide valuable insights into expert performance and present opportunities for improving music education.

Cerebral MRI in a prospective cohort study on depression and atherosclerosis: the BiDirect sample, processing pipelines, and analysis tools

BackgroundThe use of cerebral magnetic resonance imaging (MRI) in observational studies has increased exponentially in recent years, making it critical to provide details about the study sample, image processing, and extracted imaging markers to validate and replicate study results. This article reviews the cerebral MRI dataset from the now-completed BiDirect cohort study, as an update and extension of the feasibility report published after the first two examination time points.MethodsWe report the sample and flow of participants spanning four study sessions and twelve years. In addition, we provide details on the acquisition protocol; the processing pipelines, including standardization and quality control methods; and the analytical tools used and markers available.ResultsAll data were collected from 2010 to 2021 at a single site in Münster, Germany, starting with a population of 2,257 participants at baseline in 3 different cohorts: a population-based cohort (n = 911 at baseline, 672 with MRI data), patients diagnosed with depression (n = 999, 736 with MRI data), and patients with manifest cardiovascular disease (n = 347, 52 with MRI data). During the study period, a total of 4,315 MRI sessions were performed, and over 535 participants underwent MRI at all 4 time points.ConclusionsImages were converted to Brain Imaging Data Structure (a standard for organizing and describing neuroimaging data) and analyzed using common tools, such as CAT12, FSL, Freesurfer, and BIANCA to extract imaging biomarkers. The BiDirect study comprises a thoroughly phenotyped study population with structural and functional MRI data.Relevance statementThe BiDirect Study includes a population-based sample and two patient-based samples whose MRI data can help answer numerous neuropsychiatric and cardiovascular research questions.Key points• The BiDirect study included characterized patient- and population-based cohorts with MRI data.• Data were standardized to Brain Imaging Data Structure and processed with commonly available software.• MRI data and markers are available upon request.Graphical

Higher Regional Gray Matter Volume and White Matter Integrity in Individuals With Central Neuropathic Pain After Spinal Cord Injury.

Spinal cord injury (SCI) is a debilitating neurological condition that often leads to central neuropathic pain (CNP). As the fundamental mechanism of CNP is not fully established, its management is one of the most challenging problems among people with SCI. To shed more light on CNP mechanisms, the aim of this cross-sectional study was to compare the brain structure between individuals with SCI and CNP and those without CNP by examining the gray matter (GM) volume and the white matter (WM) integrity. Fifty-two individuals with SCI-28 with CNP and 24 without CNP-underwent a magnetic resonance imaging (MRI) session, including a T1-weighted scan for voxel-based morphometry, and a diffusion-weighted imaging (DWI) scan for WM integrity analysis, as measured by fractional anisotropy (FA) and mean diffusivity (MD). We found significantly higher GM volume in individuals with CNP compared with pain-free individuals in the right superior (p < 0.0014) and middle temporal gyri (p < 0.0001). Moreover, individuals with CNP exhibited higher WM integrity in the splenium of the corpus callosum (p < 0.0001) and in the posterior cingulum (p < 0.0001), compared with pain-free individuals. The results suggest that the existence of CNP following SCI is associated with GM and WM structural abnormalities in regions involved in pain intensification and spread, and which may reflect maladaptive neural plasticity in CNP.

Longitudinal changes in resting state fMRI brain self-similarity of asymptomatic high school American football athletes

American football has become the focus of numerous studies highlighting a growing concern that cumulative exposure to repetitive, sports-related head acceleration events (HAEs) may have negative consequences for brain health, even in the absence of a diagnosed concussion. In this longitudinal study, brain functional connectivity was analyzed in a cohort of high school American football athletes over a single play season and compared against participants in non-collision high school sports. Football athletes underwent four resting-state functional magnetic resonance imaging sessions: once before (pre-season), twice during (in-season), and once 34–80 days after the contact activities play season ended (post-season). For each imaging session, functional connectomes (FCs) were computed for each athlete and compared across sessions using a metric reflecting the (self) similarity between two FCs. HAEs were monitored during all practices and games throughout the season using head-mounted sensors. Relative to the pre-season scan session, football athletes exhibited decreased FC self-similarity at the later in-season session, with apparent recovery of self-similarity by the time of the post-season session. In addition, both within and post-season self-similarity was correlated with cumulative exposure to head acceleration events. These results suggest that repetitive exposure to HAEs produces alterations in functional brain connectivity and highlight the necessity of collision-free recovery periods for football athletes.

Study protocol - elucidating the neural correlates of functional remediation for older adults with bipolar disorder.

Beyond mood abnormalities, bipolar disorder (BD) includes cognitive impairments that worsen psychosocial functioning and quality of life. These deficits are especially severe in older adults with BD (OABD), a condition expected to represent most individuals with BD in the upcoming years. Restoring the psychosocial functioning of this population will thus soon represent a public health priority. To help tackle the problem, the Bipolar and Depressive Disorders Unit at the Hospital Clínic of Barcelona has recently adapted its Functional Remediation (FR) program to that population, calling it FROA-BD. However, while scarce previous studies localize the neural mechanisms of cognitive remediation interventions in the dorsal prefrontal cortex, the specific mechanisms are seldom unknown. In the present project, we will investigate the neural correlates of FR-OABD to understand its mechanisms better and inform for potential optimization. The aim is to investigate the brain features and changes associated with FROA-BD efficacy. Thirty-two individuals with OABD in full or partial remission will undergo a magnetic resonance imaging (MRI) session before receiving FR-OABD. After completing the FR-OABD intervention, they will undergo another MRI session. The MRI sessions will include structural, diffusion-weighted imaging (DWI), functional MRI (fMRI) with working memory (n-back) and verbal learning tasks, and frontal spectroscopy. We will correlate the pre-post change in dorsolateral and dorsomedial prefrontal cortices activation during the n-back task with the change in psychosocial functioning [measured with the Functioning Assessment Short Test (FAST)]. We will also conduct exploratory whole-brain correlation analyses between baseline or pre-post changes in MRI data and other clinical and cognitive outcomes to provide more insights into the mechanisms and explore potential brain markers that may predict a better treatment response. We will also conduct separate analyses by sex. The results of this study may provide insights into how FROA-BD and other cognitive remediations modulate brain function and thus could optimize these interventions.

Language and gesture neural correlates: A meta-analysis of functional magnetic resonance imaging studies.

Humans often use co-speech gestures to promote effective communication. Attention has been paid to the cortical areas engaged in the processing of co-speech gestures. To investigate the neural network underpinned in the processing of co-speech gestures and to observe whether there is a relationship between areas involved in language and gesture processing. We planned to include studies with neurotypical and/or stroke participants who underwent a bimodal task (i.e., processing of co-speech gestures with relative speech) and a unimodal task (i.e., speech or gesture alone) during a functional magnetic resonance imaging (fMRI) session. After a database search, abstract and full-text screening were conducted. Qualitative and quantitative data were extracted, and a meta-analysis was performed with the software GingerALE 3.0.2, performing contrast analyses of uni- and bimodal tasks. The database search produced 1024 records. After the screening process, 27 studies were included in the review. Data from 15 studies were quantitatively analysed through meta-analysis. Meta-analysis found three clusters with a significant activation of the left middle frontal gyrus and inferior frontal gyrus, and bilateral middle occipital gyrus and inferior temporal gyrus. There is a close link at the neural level for the semantic processing of auditory and visual information during communication. These findings encourage the integration of the use of co-speech gestures during aphasia treatment as a strategy to foster the possibility to communicate effectively for people with aphasia. What is already known on this subject Gestures are an integral part of human communication, and they may have a relationship at neural level with speech processing. What this paper adds to the existing knowledge During processing of bi- and unimodal communication, areas related to semantic processing and multimodal processing are activated, suggesting that there is a close link between co-speech gestures and spoken language at a neural level. What are the potential or actual clinical implications of this work? Knowledge of the functions related to gesture and speech processing neural networks will allow for the adoption of model-based neurorehabilitation programs to foster recovery from aphasia by strengthening the specific functions of these brain networks.

Toward precision brain health: accurate prediction of a cognitive index trajectory using neuroimaging metrics.

The goal of precision brain health is to accurately predict individuals' longitudinal patterns of brain change. We trained a machine learning model to predict changes in a cognitive index of brain health from neurophysiologic metrics. A total of 48 participants (ages 21-65) completed a sensorimotor task during 2 functional magnetic resonance imaging sessions 6 mo apart. Hemodynamic response functions (HRFs) were parameterized using traditional (amplitude, dispersion, latency) and novel (curvature, canonicality) metrics, serving as inputs to a neural network model that predicted gain on indices of brain health (cognitive factor scores) for each participant. The optimal neural network model successfully predicted substantial gain on the cognitive index of brain health with 90% accuracy (determined by 5-fold cross-validation) from 3 HRF parameters: amplitude change, dispersion change, and similarity to a canonical HRF shape at baseline. For individuals with canonical baseline HRFs, substantial gain in the index is overwhelmingly predicted by decreases in HRF amplitude. For individuals with non-canonical baseline HRFs, substantial gain in the index is predicted by congruent changes in both HRF amplitude and dispersion. Our results illustrate that neuroimaging measures can track cognitive indices in healthy states, and that machine learning approaches using novel metrics take important steps toward precision brain health.

Detection of Brain Metastases by Contrast-Enhanced MRI: Comparison of Gadopiclenol and Gadobenate in a Mouse Model.

The aim of this study was to evaluate the capacity of gadopiclenol, a high-relaxivity gadolinium-based contrast agent to detect brain metastases in mice as a function of dose (0.08 mmol/kg or 0.1 mmol/kg) compared with gadobenate at 0.1 mmol/kg. Brain metastases were induced by ultrasound-guided intracardiac implantation of 1.10 5 MDA-MB-231Br cells in the left ventricle of 18 anesthetized Balb/c Nude nu/nu female mice. At day 28 ± 3 after cell injection, each mouse received 2 crossover intravenous injections at 24-hour intervals, randomly selected from 2 doses of gadopiclenol (0.08 mmol/kg or 0.1 mmol/kg) and gadobenate (0.1 mmol/kg) with n = 6 mice/group (3 groups). Brain magnetic resonance imaging sessions were performed at 4 weeks on a 2.35 T magnet with a 3-dimensional T1-weighted high-resolution gradient echo sequence, before and after each injection. Images were blindly and randomly analyzed to detect enhancing lesions. Contrast-to-noise ratio between the metastases and the surrounding healthy parenchyma was calculated, based on region-of-interest signal measurements. In 2 animals per group, an early time point was added to the protocol (day 22 ± 3) to evaluate the sensitivity of detection as a function of time. After the last imaging session, the presence and location of whole-brain metastases were confirmed by histology in 4 mice. After gadopiclenol, approximately twice as many metastases were detected compared with gadobenate, regardless of the dose. Contrast-to-noise ratios of the detected metastases were 2.3 and 3.3 times higher with gadopiclenol at 0.08 mmol/kg and 0.1 mmol/kg, respectively, compared with gadobenate at 0.1 mmol/kg ( P < 0.0001). Gadopiclenol at the dose of 0.1 mmol/kg resulted in a 1.4-fold higher contrast compared with gadopiclenol at 0.08 mmol/kg ( P < 0.02). In a subset of mice that were imaged 1 week earlier, 2 metastases were detected with gadopiclenol and not with gadobenate. The high-relaxivity macrocyclic gadolinium-based contrast agent gadopiclenol allowed higher diagnostic performance for detecting brain enhancing metastases in terms of contrast-to-noise ratio and number of detected metastases compared with gadobenate, at both equal (0.1 mmol/kg) dose and 20% lower Gd dose (0.08 mmol/kg). Tumor detection was higher after gadopiclenol at the dose of 0.1 mmol/kg compared with 0.08 mmol/kg.