Identifying a whole‐brain connectome‐based model in drug‐naïve Parkinson's disease for predicting motor impairment

Identifying a whole‐brain connectome‐based predictive model in drug‐naïve patients with Parkinson''s disease and verifying its predictions on drug‐managed patients would be useful in determining the intrinsic functional underpinnings of motor impairment and establishing general brain–behavior associations. In this study, we constructed a predictive model from the resting‐state functional data of 47 drug‐naïve patients by using a connectome‐based approach. This model was subsequently validated in 115 drug‐managed patients. The severity of motor impairment was assessed by calculating Unified Parkinson''s Disease Rating Scale Part III scores. The predictive performance of model was evaluated using the correlation coefficient (r _true) between predicted and observed scores. As a result, a connectome‐based model for predicting individual motor impairment in drug‐naïve patients was identified with significant performance (r _true = .845, p < .001, p _permu = .002). Two patterns of connection were identified according to correlations between connection strength and the severity of motor impairment. The negative motor‐impairment‐related network contained more within‐network connections in the motor, visual‐related, and default mode networks, whereas the positive motor‐impairment‐related network was constructed mostly with between‐network connections coupling the motor‐visual, motor‐limbic, and motor‐basal ganglia networks. Finally, this predictive model constructed around drug‐naïve patients was confirmed with significant predictive efficacy on drug‐managed patients (r = .209, p = .025), suggesting a generalizability in Parkinson''s disease patients under long‐term drug influence. In conclusion, this study identified a whole‐brain connectome‐based model that could predict the severity of motor impairment in Parkinson''s patients and furthers our understanding of the functional underpinnings of the disease.     

Quantitative susceptibility mapping shows lower brain iron content in children with attention‐deficit hyperactivity disorder

To investigate the feasibility of quantitative susceptibility mapping in children with attention‐deficit hyperactivity disorder (ADHD), 53 children with ADHD aged 5–16 years were prospectively selected as the study group and 49 healthy children matched with age and gender were selected as the control group. All children underwent magnetic resonance imaging conventional sequence, 3D‐T1, and enhanced T2*‐weighted magnetic resonance angiography (ESWAN) sequence scanning. The iron content of brain regions was obtained through software postprocessing, and the iron content of brain regions of children with ADHD and healthy children was compared and analyzed to find out the characteristics of the iron content of brain regions of children with ADHD. The iron content in frontal lobe, globus pallidus, caudate nucleus, substantia nigra, putamen, and hippocampus of children with ADHD was lower than that of healthy children (p < .05). There was no significant difference in the content of iron in the left and right brain regions of children with ADHD (p > .05). The volume of frontal lobe and hippocampus of children with ADHD was lower than that of healthy children (p < .05). Iron content in brain areas such as globus pallidus, caudate nucleus, hippocampus, and putamen could distinguish children with ADHD (Area under curve [AUC] > 0.5, p < .05). Quantitative susceptibility mapping showed decreased iron content in some brain regions of children with ADHD.     

Transdiagnostic time‐varying dysconnectivity across major psychiatric disorders

Dynamic functional connectivity (DFC) analysis can capture time‐varying properties of connectivity. However, studies on large samples using DFC to investigate transdiagnostic dysconnectivity across schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD) are rare. In this study, we used resting‐state functional magnetic resonance imaging and a sliding‐window method to study DFC in a total of 610 individuals (150 with SZ, 100 with BD, 150 with MDD, and 210 healthy controls [HC]) at a single site. Using k‐means clustering, DFCs were clustered into three functional connectivity states: one was a more frequent state with moderate positive and negative connectivity (State 1), and the other two were less frequent states with stronger positive and negative connectivity (State 2 and State 3). Significant 4‐group differences (SZ, BD, MDD, and HC groups; q < .05, false‐discovery rate [FDR]‐corrected) in DFC were nearly only in State 1. Post hoc analyses (q < .05, FDR‐corrected) in State 1 showed that transdiagnostic dysconnectivity patterns among SZ, BD and MDD featured consistently decreased connectivity within most networks (the visual, somatomotor, salience and frontoparietal networks), which was most obvious in both range and extent for SZ. Our findings suggest that there is more common dysconnectivity across SZ, BD and MDD than we previously expected and that such dysconnectivity is state‐dependent, which provides new insights into the pathophysiological mechanism of major psychiatric disorders.     

Effects of bariatric surgery on functional connectivity of the reward and default mode network: A pre‐registered analysis

Obesity imposes serious health risks and involves alterations in resting‐state functional connectivity of brain networks involved in eating behavior. Bariatric surgery is an effective treatment, but its effects on functional connectivity are still under debate. In this pre‐registered study, we aimed to determine the effects of bariatric surgery on major resting‐state brain networks (reward and default mode network) in a longitudinal controlled design. Thirty‐three bariatric surgery patients and 15 obese waiting‐list control patients underwent magnetic resonance imaging at baseline, after 6 and 12 months. We conducted a pre‐registered whole‐brain time‐by‐group interaction analysis, and a time‐by‐group interaction analysis on within‐network connectivity. In exploratory analyses, we investigated the effects of weight loss and head motion. Bariatric surgery compared to waiting did not significantly affect functional connectivity of the reward network and the default mode network (FWE‐corrected p > .05), neither whole‐brain nor within‐network. In exploratory analyses, surgery‐related BMI decrease (FWE‐corrected p = .041) and higher average head motion (FWE‐corrected p = .021) resulted in significantly stronger connectivity of the reward network with medial posterior frontal regions. This pre‐registered well‐controlled study did not support a strong effect of bariatric surgery, compared to waiting, on major resting‐state brain networks after 6 months. Exploratory analyses indicated that head motion might have confounded the effects. Data pooling and more rigorous control of within‐scanner head motion during data acquisition are needed to substantiate effects of bariatric surgery on brain organization.     

Disrupted brain functional networks in drug‐naïve children with attention deficit hyperactivity disorder assessed using graph theory analysis

Neuroimaging studies have revealed functional brain network abnormalities in attention deficit hyperactivity disorder (ADHD), but the results have been inconsistent, potentially related to confounding medication effects. Furthermore, specific topological alterations in functional networks and their role in behavioral inhibition dysfunction remain to be established. Resting‐state functional magnetic resonance imaging was performed on 51 drug‐naïve children with ADHD and 55 age‐matched healthy controls. Brain functional networks were constructed by thresholding the partial correlation matrices of 90 brain regions, and graph theory was used to analyze network topological properties. The Stroop test was used to assess cognitive inhibitory abilities. Nonparametric permutation tests were used to compare the topological architectures in the two groups. Compared with healthy subjects, brain networks in ADHD patients demonstrated altered topological characteristics, including lower global (FDR q = 0.01) and local efficiency (p = 0.032, uncorrected) and a longer path length (FDR q = 0.01). Lower nodal efficiencies were found in the left inferior frontal gyrus and anterior cingulate cortex in the ADHD group (FDR both q < 0.05). Altered global and nodal topological efficiencies were associated with the severity of inhibitory cognitive control deficits and hyperactivity symptoms in ADHD (p <0 .05). Alterations in network topologies in drug‐naïve ADHD patients indicate weaker small‐worldization with decreased segregation and integration of functional brain networks. Deficits in the cingulo‐fronto‐parietal attention network were associated with inhibitory control deficits.     

Abnormal brain functional network dynamics in obsessive–compulsive disorder patients and their unaffected first‐degree relatives

We utilized dynamic functional network connectivity (dFNC) analysis to compare participants with obsessive–compulsive disorder (OCD) with their unaffected first‐degree relative (UFDR) and healthy controls (HC). Resting state fMRI was performed on 46 OCD, 24 UFDR, and 49 HCs, along with clinical assessments. dFNC analyses revealed two distinct connectivity states: a less frequent, integrated state characterized by the predominance of between‐network connections (State I), and a more frequent, segregated state with strong within‐network connections (State II). OCD patients spent more time in State II and less time in State I than HC, as measured by fractional windows and mean dwell time. Time in each state for the UFDR were intermediate between OCD patients and HC. Within the OCD group, fractional windows of time spent in State I was positively correlated with OCD symptoms (as measured by the obsessive compulsive inventory‐revised [OCI‐R], r = .343, p<.05, FDR correction) and time in State II was negatively correlated with symptoms (r = −.343, p<.05, FDR correction). Within each state we also examined connectivity within and between established intrinsic connectivity networks, and found that UFDR were similar to the OCD group in State I, but more similar to the HC groups in State II. The similarities between OCD and UFDR groups in temporal properties and State I connectivity indicate that these features may reflect the endophenotype for OCD. These results indicate that the temporal dynamics of functional connectivity could be a useful biomarker to identify those at risk.     

The interaction of child abuse and rs1360780 of the FKBP5 gene is associated with amygdala resting‐state functional connectivity in young adults

Extensive research has demonstrated that rs1360780, a common single nucleotide polymorphism within the FKBP5 gene, interacts with early‐life stress in predicting psychopathology. Previous results suggest that carriers of the TT genotype of rs1360780 who were exposed to child abuse show differences in structure and functional activation of emotion‐processing brain areas belonging to the salience network. Extending these findings on intermediate phenotypes of psychopathology, we examined if the interaction between rs1360780 and child abuse predicts resting‐state functional connectivity (rsFC) between the amygdala and other areas of the salience network. We analyzed data of young European adults from the general population (N = 774; mean age = 18.76 years) who took part in the IMAGEN study. In the absence of main effects of genotype and abuse, a significant interaction effect was observed for rsFC between the right centromedial amygdala and right posterior insula (p < .025, FWE‐corrected), which was driven by stronger rsFC in TT allele carriers with a history of abuse. Our results suggest that the TT genotype of rs1360780 may render individuals with a history of abuse more vulnerable to functional changes in communication between brain areas processing emotions and bodily sensations, which could underlie or increase the risk for psychopathology.     

Mapping of whole‐cerebrum resting‐state networks using ultra‐high resolution acquisition protocols

Resting‐state functional magnetic resonance imaging (fMRI) has been used in numerous studies to map networks in the brain that employ spatially disparate regions. However, attempts to map networks with high spatial resolution have been hampered by conflicting technical demands and associated problems. Results from recent fMRI studies have shown that spatial resolution remains around 0.7 × 0.7 × 0.7 mm³, with only partial brain coverage. Therefore, this work aims to present a novel fMRI technique that was developed based on echo‐planar‐imaging with keyhole (EPIK) combined with repetition‐time‐external (TR‐external) EPI phase correction. Each technique has been previously shown to be effective in enhancing the spatial resolution of fMRI, and in this work, the combination of the two techniques into TR‐external EPIK provided a nominal spatial resolution of 0.51 × 0.51 × 1.00 mm³ (0.26 mm³ voxel) with whole‐cerebrum coverage. Here, the feasibility of using half‐millimetre in‐plane TR‐external EPIK for resting‐state fMRI was validated using 13 healthy subjects and the corresponding reproducible mapping of resting‐state networks was demonstrated. Furthermore, TR‐external EPIK enabled the identification of various resting‐state networks distributed throughout the brain from a single fMRI session, with mapping fidelity onto the grey matter at 7T. The high‐resolution functional image further revealed mesoscale anatomical structures, such as small cerebral vessels and the internal granular layer of the cortex within the postcentral gyrus.     

Eight‐week antidepressant treatment reduces functional connectivity in first‐episode drug‐naïve patients with major depressive disorder

Previous neuroimaging studies have revealed abnormal functional connectivity of brain networks in patients with major depressive disorder (MDD), but findings have been inconsistent. A recent big‐data study found abnormal intrinsic functional connectivity within the default mode network in patients with recurrent MDD but not in first‐episode drug‐naïve patients with MDD. This study also provided evidence for reduced default mode network functional connectivity in medicated MDD patients, raising the question of whether previously observed abnormalities may be attributable to antidepressant effects. The present study (ClinicalTrials.gov identifier: {"type":"clinical-trial","attrs":{"text":"NCT03294525","term_id":"NCT03294525"}}NCT03294525) aimed to disentangle the effects of antidepressant treatment from the pathophysiology of MDD and test the medication normalization hypothesis. Forty‐one first‐episode drug‐naïve MDD patients were administrated antidepressant medication (escitalopram or duloxetine) for 8 weeks, with resting‐state functional connectivity compared between posttreatment and baseline. To assess the replicability of the big‐data finding, we also conducted a cross‐sectional comparison of resting‐state functional connectivity between the MDD patients and 92 matched healthy controls. Both Network‐Based Statistic analyses and large‐scale network analyses revealed intrinsic functional connectivity decreases in extensive brain networks after treatment, indicating considerable antidepressant effects. Neither Network‐Based Statistic analyses nor large‐scale network analyses detected significant functional connectivity differences between treatment‐naïve patients and healthy controls. In short, antidepressant effects are widespread across most brain networks and need to be accounted for when considering functional connectivity abnormalities in MDD.     

Probing the role of the right inferior frontal gyrus during Pain‐Related empathy processing: Evidence from fMRI and TMS

Recent studies have suggested that the right inferior frontal gyrus (rIFG) may be involved in pain‐related empathy. To verify the role of the rIFG, we performed a functional magnetic resonance imaging (fMRI) experiment to replicate previous research and further designed a noninvasive repetitive transcranial magnetic stimulation (rTMS) experiment to probe the causal role of the rIFG in pain‐related empathy processing. We assigned 74 volunteers (37 females) to three groups. Group 1 (n = 26) performed a task in which participants were required to perceive pain in others (task of pain: TP) and we used fMRI to observe the activity of the rIFG during pain‐related empathy processing. Then, we applied online rTMS to the rIFG and the vertex site (as reference site) to observe the performance of Group 2 (n = 24; performing TP) and Group 3 (n = 24; performing a control task of identifying body parts; task of body: TB). fMRI experiment demonstrated stronger activation in the rIFG than in the vertex during the perception of pain in others (p < .0001, Bonferroni‐corrected). rTMS experiment indicated that when the rIFG was temporarily disrupted, participants perceived pain in others significantly more slowly (p < .0001, Bonferroni‐corrected) than when the vertex was disrupted. Our results provide evidence that the rIFG is involved in pain‐related empathy processing, which yields insights into how the brain perceives pain in others.     

The stage‐specifically accelerated brain aging in never‐treated first‐episode patients with depression

Depression associated with structural brain abnormalities is hypothesized to be related with accelerated brain aging. However, there is far from a unified conclusion because of clinical variations such as medication status, cumulative illness burden. To explore whether brain age is accelerated in never‐treated first‐episode patients with depression and its association with clinical characteristics, we constructed a prediction model where gray matter volumes measured by voxel‐based morphometry derived from T1‐weighted MRI scans were treated as features. The prediction model was first validated using healthy controls (HCs) in two Chinese Han datasets (Dataset 1, N = 130 for HCs and N = 195 for patients with depression; Dataset 2, N = 270 for HCs) separately or jointly, then the trained prediction model using HCs (N = 400) was applied to never‐treated first‐episode patients with depression (N = 195). The brain‐predicted age difference (brain‐PAD) scores defined as the difference between predicted brain age and chronological age, were calculated for all participants and compared between patients with age‐, gender‐, educational level‐matched HCs in Dataset 1. Overall, patients presented higher brain‐PAD scores suggesting patients with depression having an “older” brain than expected. More specially, this difference occurred at illness onset (illness duration <3 months) and following 2 years then disappeared as the illness further advanced (>2 years) in patients. This phenomenon was verified by another data‐driven method and significant correlation between brain‐PAD scores and illness duration in patients. Our results reveal that accelerated brain aging occurs at illness onset and suggest it is a stage‐dependent phenomenon in depression.     

Cortical N‐acetylaspartate concentrations are impacted in chronic stroke but do not relate to motor impairment: A magnetic resonance spectroscopy study

Magnetic resonance spectroscopy (MRS) measures cerebral metabolite concentrations, which can inform our understanding of the neurobiological processes associated with stroke recovery. Here, we investigated whether metabolite concentrations in primary motor and somatosensory cortices (sensorimotor cortex) are impacted by stroke and relate to upper‐extremity motor impairment in 45 individuals with chronic stroke. Cerebral metabolite estimates were adjusted for cerebrospinal fluid and brain tissue composition in the MRS voxel. Upper‐extremity motor impairment was indexed with the Fugl‐Meyer (FM) scale. N‐acetylaspartate (NAA) concentration was reduced bilaterally in stroke participants with right hemisphere lesions (n = 23), relative to right‐handed healthy older adults (n = 15; p = .006). Within the entire stroke sample (n = 45) NAA and glutamate/glutamine (GLX) were lower in the ipsilesional sensorimotor cortex, relative to the contralesional cortex (NAA: p < .001; GLX: p = .003). Lower ipsilesional NAA was related to greater extent of corticospinal tract (CST) injury, quantified by a weighted CST lesion load (p = .006). Cortical NAA and GLX concentrations did not relate to the severity of chronic upper‐extremity impairment (p > .05), including after a sensitivity analysis imputing missing metabolite data for individuals with large cortical lesions (n = 5). Our results suggest that NAA, a marker of neuronal integrity, is sensitive to stroke‐related cortical damage and may provide mechanistic insights into cellular processes of cortical adaptation to stroke. However, cortical MRS metabolites may have limited clinical utility as prospective biomarkers of upper‐extremity outcomes in chronic stroke.     

Mutation‐related magnetization‐transfer,not axon density,drives white matter differences in premanifest Huntington disease: Evidence from in vivo ultra‐strong gradient MRI

White matter (WM) alterations have been observed in Huntington disease (HD) but their role in the disease‐pathophysiology remains unknown. We assessed WM changes in premanifest HD by exploiting ultra‐strong‐gradient magnetic resonance imaging (MRI). This allowed to separately quantify magnetization transfer ratio (MTR) and hindered and restricted diffusion‐weighted signal fractions, and assess how they drove WM microstructure differences between patients and controls. We used tractometry to investigate region‐specific alterations across callosal segments with well‐characterized early‐ and late‐myelinating axon populations, while brain‐wise differences were explored with tract‐based cluster analysis (TBCA). Behavioral measures were included to explore disease‐associated brain‐function relationships. We detected lower MTR in patients'' callosal rostrum (tractometry: p = .03; TBCA: p = .03), but higher MTR in their splenium (tractometry: p = .02). Importantly, patients'' mutation‐size and MTR were positively correlated (all p‐values < .01), indicating that MTR alterations may directly result from the mutation. Further, MTR was higher in younger, but lower in older patients relative to controls (p = .003), suggesting that MTR increases are detrimental later in the disease. Finally, patients showed higher restricted diffusion signal fraction (FR) from the composite hindered and restricted model of diffusion (CHARMED) in the cortico‐spinal tract (p = .03), which correlated positively with MTR in the posterior callosum (p = .033), potentially reflecting compensatory mechanisms. In summary, this first comprehensive, ultra‐strong gradient MRI study in HD provides novel evidence of mutation‐driven MTR alterations at the premanifest disease stage which may reflect neurodevelopmental changes in iron, myelin, or a combination of these.     

The effect of acquisition duration on cerebral blood flow‐based resting‐state functional connectivity

Resting‐state functional connectivity (rs‐FC) is widely used to examine the functional architecture of the brain, and the blood‐oxygenation‐level‐dependent (BOLD) signal is often utilized for determining rs‐FC. However, the BOLD signal is susceptible to various factors that have less influence on the cerebral blood flow (CBF). Therefore, CBF could comprise an alternative for determining rs‐FC. Since acquisition duration is one of the essential parameters for obtaining reliable rs‐FC, we investigated the effect of acquisition duration on CBF‐based rs‐FC to examine the reliability of CBF‐based rs‐FC. Nineteen participants underwent CBF scanning for a total duration of 50 min. Variance of CBF‐based rs‐FC within the whole brain and 13 large‐scale brain networks at various acquisition durations was compared to that with a 50‐min duration using the Levene''s test. Variance of CBF‐based rs‐FC at any durations did not differ from that at a 50‐min duration (p > .05). Regarding variance of rs‐FC within each large‐scale brain network, the acquisition duration required to obtain reliable estimates of CBF‐based rs‐FC was shorter than 10 min and varied across large‐scale brain networks. Altogether, an acquisition duration of at least 10 min is required to obtain reliable CBF‐based rs‐FC. These results indicate that CBF‐based resting‐state functional magnetic resonance imaging (rs‐fMRI) with more than 10 min of total acquisition duration could be an alternative method to BOLD‐based rs‐fMRI to obtain reliable rs‐FC.     

Task‐related neural mechanisms of persecutory ideation in schizophrenia and community monozygotic twin‐pairs

Perceptions of spiteful behavior are common, distinct from rational fear, and may undergird persecutory ideation. To test this hypothesis and investigate neural mechanisms of persecutory ideation, we employed a novel economic social decision‐making task, the Minnesota Trust Game (MTG), during neuroimaging in patients with schizophrenia (n = 30) and community monozygotic (MZ) twins (n = 38; 19 pairs). We examined distinct forms of mistrust, task‐related brain activation and connectivity, and investigated relationships with persecutory ideation. We tested whether co‐twin discordance on these measurements was correlated to reflect a common source of underlying variance. Across samples persecutory ideation was associated with reduced trust only during the suspiciousness condition, which assessed spite sensitivity given partners had no monetary incentive to betray. Task‐based activation contrasts for specific forms of mistrust were limited and unrelated to persecutory ideation. However, task‐based connectivity contrasts revealed a dorsal cingulate anterior insula network sensitive to suspicious mistrust, a left frontal–parietal (lF‐P) network sensitive to rational mistrust, and a ventral medial/orbital prefrontal (vmPFC/OFC) network that was sensitive to the difference between these forms of mistrust (all p < .005). Higher persecutory ideation was predicted only by reduced connectivity between the vmPFC/OFC and lF‐P networks (p = .005), which was only observed when the intentions of the other player were relevant. Moreover, co‐twin differences in persecutory ideation predicted co‐twin differences in both spite sensitivity and in vmPFC/OFC–lF‐P connectivity. This work found that interconnectivity may be particularly important to the complex neurobiology underlying persecutory ideation, and that unique environmental variance causally linked persecutory ideation, decision‐making, and brain connectivity.     

Beware of white matter hyperintensities causing systematic errors in FreeSurfer gray matter segmentations!

Volumetric estimates of subcortical and cortical structures, extracted from T1‐weighted MRIs, are widely used in many clinical and research applications. Here, we investigate the impact of the presence of white matter hyperintensities (WMHs) on FreeSurfer gray matter (GM) structure volumes and its possible bias on functional relationships. T1‐weighted images from 1,077 participants (4,321 timepoints) from the Alzheimer''s Disease Neuroimaging Initiative were processed with FreeSurfer version 6.0.0. WMHs were segmented using a previously validated algorithm on either T2‐weighted or Fluid‐attenuated inversion recovery images. Mixed‐effects models were used to assess the relationships between overlapping WMHs and GM structure volumes and overall WMH burden, as well as to investigate whether such overlaps impact associations with age, diagnosis, and cognitive performance. Participants with higher WMH volumes had higher overlaps with GM volumes of bilateral caudate, cerebral cortex, putamen, thalamus, pallidum, and accumbens areas (p < .0001). When not corrected for WMHs, caudate volumes increased with age (p < .0001) and were not different between cognitively healthy individuals and age‐matched probable Alzheimer''s disease patients. After correcting for WMHs, caudate volumes decreased with age (p < .0001), and Alzheimer''s disease patients had lower caudate volumes than cognitively healthy individuals (p < .01). Uncorrected caudate volume was not associated with ADAS13 scores, whereas corrected lower caudate volumes were significantly associated with poorer cognitive performance (p < .0001). Presence of WMHs leads to systematic inaccuracies in GM segmentations, particularly for the caudate, which can also change clinical associations. While specifically measured for the Freesurfer toolkit, this problem likely affects other algorithms.     

The impact of COVID‐19 lockdown on brain metabolism

This study aims to evaluate the impact of French national lockdown of 55 days on brain metabolism of patients with neurological disorders. Whole‐brain voxel‐based PET analysis was used to correlate ¹⁸F‐FDG metabolism to the number of days after March 17, 2020 (in 95 patients; mean age: 54.3 years ± 15.7; 59 men), in comparison to the same period in 2019 before the SARS‐CoV‐2 outbreak (in 212 patients; mean age: 59.5 years ± 15.8; 114 men), and to the first 55 days of deconfinement (in 188 patients; mean age: 57.5 years ± 16.5; 93 men). Lockdown duration was negatively correlated to the metabolism of the sensory‐motor cortex with a prevailing effect on the left dominant pyramidal tract and on younger patients, also including the left amygdala, with only partial reversibility after 55 days of deconfinement. Weak overlap was found with the reported pattern of hypometabolism in long COVID (<9%). Restriction of physical activities, and possible related deconditioning, and social isolation may lead to functional disturbances of sensorimotor and emotional brain networks. Of note, this metabolic pattern seems distinct to those reported in long COVID. Further longitudinal studies with longer follow‐up are needed to evaluate clinical consequences and relationships on cognitive and mental health against functional deactivation hypothesis, and to extend these findings to healthy subjects in the context of lockdown.     

In vivo hippocampal subfield volumes in bipolar disorder—A mega‐analysis from The Enhancing Neuro Imaging Genetics through Meta‐Analysis Bipolar Disorder Working Group

The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder (BD). Here we, the Enhancing NeuroImaging Genetics through Meta‐Analysis Bipolar Disorder workinggroup, study hippocampal subfield volumetry in BD. T1‐weighted magnetic resonance imaging scans from 4,698 individuals (BD = 1,472, healthy controls [HC] = 3,226) from 23 sites worldwide were processed with FreeSurfer. We used linear mixed‐effects models and mega‐analysis to investigate differences in hippocampal subfield volumes between BD and HC, followed by analyses of clinical characteristics and medication use. BD showed significantly smaller volumes of the whole hippocampus (Cohen''s d = −0.20), cornu ammonis (CA)1 (d = −0.18), CA2/3 (d = −0.11), CA4 (d = −0.19), molecular layer (d = −0.21), granule cell layer of dentate gyrus (d = −0.21), hippocampal tail (d = −0.10), subiculum (d = −0.15), presubiculum (d = −0.18), and hippocampal amygdala transition area (d = −0.17) compared to HC. Lithium users did not show volume differences compared to HC, while non‐users did. Antipsychotics or antiepileptic use was associated with smaller volumes. In this largest study of hippocampal subfields in BD to date, we show widespread reductions in nine of 12 subfields studied. The associations were modulated by medication use and specifically the lack of differences between lithium users and HC supports a possible protective role of lithium in BD.     

Decoding motor expertise from fine‐tuned oscillatory network organization

Can motor expertise be robustly predicted by the organization of frequency‐specific oscillatory brain networks? To answer this question, we recorded high‐density electroencephalography (EEG) in expert Tango dancers and naïves while viewing and judging the correctness of Tango‐specific movements and during resting. We calculated task‐related and resting‐state connectivity at different frequency‐bands capturing task performance (delta [δ], 1.5–4 Hz), error monitoring (theta [θ], 4–8 Hz), and sensorimotor experience (mu [μ], 8–13 Hz), and derived topographical features using graph analysis. These features, together with canonical expertise measures (i.e., performance in action discrimination, time spent dancing Tango), were fed into a data‐driven computational learning analysis to test whether behavioral and brain signatures robustly classified individuals depending on their expertise level. Unsurprisingly, behavioral measures showed optimal classification (100%) between dancers and naïves. When considering brain models, the task‐based classification performed well (~73%), with maximal discrimination afforded by theta‐band connectivity, a hallmark signature of error processing. Interestingly, mu connectivity during rest outperformed (100%) the task‐based approach, matching the optimal classification of behavioral measures and thus emerging as a potential trait‐like marker of sensorimotor network tuning by intense training. Overall, our findings underscore the power of fine‐tuned oscillatory network signatures for capturing expertise‐related differences and their potential value in the neuroprognosis of learning outcomes.     

Specific age‐correlated activation of top hierarchical motor control areas during gait‐like plantar stimulation: An fMRI study

A better understanding of gait disorders that are associated with aging is crucial to prevent adverse outcomes. The functional study of gait remains a thorny issue due to technical constraints inherent to neuroimaging procedures, as most of them require to stay supine and motionless. Using an MRI‐compatible system of boots reproducing gait‐like plantar stimulation, we investigated the correlation between age and brain fMRI activation during simulated gait in healthy adults. Sixty‐seven right‐handed healthy volunteers aged between 20 and 77 years old (49.2 ± 18.0 years; 35 women) were recruited. Two paradigms were assessed consecutively: (a) gait‐like plantar stimulation and (b) chaotic and not gait‐related plantar stimulation. Resulting statistical parametric maps were analyzed with a multiple‐factor regression that included age and a threshold determined by Monte‐Carlo simulation to fulfill a family‐wise error rate correction of p < .05. In the first paradigm, there was an age‐correlated activation of the right pallidum, thalamus and putamen. The second paradigm showed an age‐correlated deactivation of both primary visual areas (V1). The subtraction between results of the first and second paradigms showed age‐correlated activation of the right presupplementary motor area (Brodmann Area [BA] 6) and right mid‐dorsolateral prefrontal cortex (BA9‐10). Our results show age‐correlated activity in areas that have been associated with the control of gait, highlighting the relevance of this simulation model for functional gait study. The specific progressive activation of top hierarchical control areas in simulated gait and advancing age corroborate a progressive loss of automation in healthy older adults.