The underlying neuropsychological and neural correlates of the impaired Chinese reading skills in children with attention deficit hyperactivity disorder.

Impaired basic academic skills (e.g., word recognition) are common in children with Attention Deficit Hyperactivity Disorder (ADHD). The underlying neuropsychological and neural correlates of impaired Chinese reading skills in children with ADHD have not been substantially explored. Three hundred and two children with ADHD (all medication-naïve) and 105 healthy controls underwent the Chinese language skill assessment, and 175 also underwent fMRI scans (84 ADHD and 91 controls). Between-group and mediation analyses were applied to explore the interrelationships of the diagnosis of ADHD, cognitive dysfunction, and impaired reading skills. Five ADHD-related brain functional networks, including the default mode network (DMN) and the dorsal attention network (DAN), were built using predefined regions of interest. Voxel-based group-wise comparisons were performed. The ADHD group performed worse than the control group in word-level reading ability tests, with lower scores in Chinese character recognition (CR) and word chains (WS) (all P < 0.05). With full-scale IQ and sustained attention in the mediation model, the direct effect of ADHD status on the CR score became insignificant (P = 0.066). The underlying neural correlates for the orthographic knowledge (OT) and CR differed between the ADHD and the control group. The ADHD group tended to recruit more DMN regions to maintain their reading performance, while the control group seemed to utilize more DAN regions. Children with ADHD generally presented impaired word-level reading skills, which might be caused by impaired sustained attention and lower IQ. According to the brain functional results, we infer that ADHD children might utilize a different strategy to maintain their orthographic knowledge and character recognition performance.

Online and offline effects of parietal 10 Hz repetitive transcranial magnetic stimulation on working memory in healthy controls.

Parietal alpha activity shows a specific pattern of phasic changes during working memory. It decreases during the encoding and recall phases but increases during the maintenance phase. This study tested whether online rTMS delivered to the parietal cortex during the maintenance phase of a working memory task would increase alpha activity and hence improve working memory. Then, 46 healthy volunteers were randomly assigned to two groups to receive 3-day parietal 10 Hz online rTMS (either real or sham, 3600 pulses in total) that were time-locked to the maintenance phase of a spatial span task (180 trials in total). Behavioral performance on another spatial span task and EEG signals during a change detection task were recorded on the day before the first rTMS (pretest) and the day after the last rTMS (posttest). We found that rTMS improved performance on both online and offline spatial span tasks. For the offline change detection task, rTMS enhanced alpha activity within the maintenance phase and improved interference control of working memory at both behavioral (K score) and neural (contralateral delay activity) levels. These results suggested that rTMS with alpha frequency time-locked to the maintenance phase is a promising way to boost working memory.

The power of many brains: Catalyzing neuropsychiatric discovery through open neuroimaging data and large-scale collaboration.

Recent advances in open neuroimaging data are enhancing our comprehension of neuropsychiatric disorders. By pooling images from various cohorts, statistical power has increased, enabling the detection of subtle abnormalities and robust associations, and fostering new research methods. Global collaborations in imaging have furthered our knowledge of the neurobiological foundations of brain disorders and aided in imaging-based prediction for more targeted treatment. Large-scale magnetic resonance imaging initiatives are driving innovation in analytics and supporting generalizable psychiatric studies. We also emphasize the significant role of big data in understanding neural mechanisms and in the early identification and precise treatment of neuropsychiatric disorders. However, challenges such as data harmonization across different sites, privacy protection, and effective data sharing must be addressed. With proper governance and open science practices, we conclude with a projection of how large-scale imaging resources and collaborations could revolutionize diagnosis, treatment selection, and outcome prediction, contributing to optimal brain health.

Abnormal functional connectivity of the reward network is associated with social communication impairments in autism spectrum disorder: A large-scale multi-site resting-state fMRI study.

BACKGROUND: The social motivation hypothesis proposes that the social deficits of autism spectrum disorder (ASD) are related to reward system dysfunction. However, functional connectivity (FC) patterns of the reward network in ASD have not been systematically explored yet. METHODS: The reward network was defined as eight regions of interest (ROIs) per hemisphere, including the nucleus accumbens (NAc), caudate, putamen, anterior cingulate cortex (ACC), ventromedial prefrontal cortex (vmPFC), orbitofrontal cortex (OFC), amygdala, and insula. We computed both the ROI-wise resting-state FC and seed-based whole-brain FC in 298 ASD participants and 348 typically developing (TD) controls from the Autism Brain Imaging Data Exchange I dataset. Two-sample t-tests were applied to obtain the aberrant FCs. Then, the association between aberrant FCs and clinical symptoms was assessed with Pearson's correlation or Spearman's correlation. In addition, Neurosynth Image Decoder was used to generate word clouds verifying the cognitive functions of the aberrant pathways. Furthermore, a three-way multivariate analysis of variance (MANOVA) was conducted to examine the effects of gender, subtype and age on the atypical FCs. RESULTS: For the within network analysis, the left ACC showed weaker FCs with both the right amygdala and left NAc in ASD compared with TD, which were negatively correlated with the Autism Diagnostic Observation Schedule (ADOS) total scores and Social Responsiveness Scale (SRS) total scores respectively. For the whole-brain analysis, weaker FC (i.e., FC between the left vmPFC and left calcarine gyrus, and between the right vmPFC and left precuneus) accompanied by stronger FC (i.e., FC between the left caudate and right insula) were exhibited in ASD relative to TD, which were positively associated with the SRS motivation scores. Additionally, we detected the main effect of age on FC between the left vmPFC and left calcarine gyrus, of subtype on FC between the right vmPFC and left precuneus, of age and age-by-gender interaction on FC between the left caudate and right insula. CONCLUSIONS: Our findings highlight the crucial role of abnormal FC patterns of the reward network in the core social deficits of ASD, which have the potential to reveal new biomarkers for ASD.

Impaired segregation of the attention deficit hyperactivity disorder related pattern in children.

BACKGROUND: Inattention is a key characteristic of attention deficit hyperactivity disorder (ADHD). Specific brain abnormalities associated with this symptom form a discernible pattern related with ADHD in children (i.e., ADHD related pattern) in our earlier research. The developmental processes of segregation and integration may be crucial to ADHD. However, how brains reconfigure these processes of the ADHD related pattern in different subtypes of ADHD and across sexes remain unclear. METHODS: Nested-spectral partition method was applied to identify effects of subtype and sex on segregation and integration of the ADHD related pattern, using 145 ADHD patients and 135 typically developing controls (TDC) aged 7-14. Relationships between the measures and inattention symptoms were also investigated. RESULTS: Children with ADHD exhibited lower segregation of the ADHD related pattern (p = 1.17 × 10-8) than TDCs. Only the main effect of subtype was significant (p = 1.14 × 10-5). Both ADHD-C (p = 2.16 × 10-6) and ADHD-I (p = 2.87 × 10-6) patients had lower segregation components relative to the TDC. Moreover, segregation components were negatively correlated with inattention scores. CONCLUSIONS: This study identified impaired segregation in the ADHD related pattern of children with ADHD and found shared neural bases among different subtypes and sexes.

Short-term effect of coil handle orientations on fMRI-guided rTMS on insomnia: A case report.

Introduction: The coil handle orientation plays a pivotal role in the therapeutic efficacy of repetitive transcranial magnetic stimulation (rTMS). However, there is currently no consensus on the optimal individualized coil handle orientation, especially for non-motor areas. Case presentation: The present case reported a short-term effect of functional connectivity (FC)-guided rTMS with coil handle posterior-anterior 45° (PA45°) and posterior-anterior 135° (PA135°) on a patient with insomnia. Notably, in this case, the PA45° orientation was nearly perpendicular to the adjacent sulcus, while the PA135° orientation was almost parallel to it. Local brain activity and functional connectivity were assessed using resting-state functional magnetic resonance imaging (RS-fMRI). Additionally, motor evoked potentials (MEPs) were captured both pre and post-rTMS sessions. Findings: The coil handle orientation PA45° outperformed the PA135° in both RS-fMRI and MEP outcomes. Moreover, a 9-day rTMS treatment led to discernible improvements in symptoms of depression and anxiety, complemented by a modest enhancement in sleep quality.

Abnormal individualized peak functional connectivity toward potential repetitive transcranial magnetic stimulation treatment of autism spectrum disorder.

Functional connectivity (FC) derived from resting-state functional magnetic resonance imaging has been widely applied to guide precise repetitive transcranial magnetic stimulation (rTMS). The left, right, and bilateral dorsolateral prefrontal cortices (DLPFC) have been used as rTMS treatment target regions for autism spectrum disorder (ASD), albeit with moderate efficacy. Thus, we aimed to develop an individualized localization method for rTMS treatment of ASD. We included 266 male ASDs and 297 male typically-developed controls (TDCs) from the Autism Brain Imaging Data Exchange Dataset. The nucleus accumbens (NAc) was regarded as a promising effective region, which was used as a seed and individualized peak FC strength in the DLPFC was compared between ASD and TDC. Correlation analysis was conducted between individualized peak FC strength and symptoms in ASD. We also investigated the spatial distribution of individualized peak FC locations in the DLPFC and conducted voxel-wise analysis to compare NAc-based FC between the two groups. ASD showed stronger peak FC in the right DLPFC related to TDC (Cohen's d = -.19, 95% CI: -0.36 to -0.03, t = -2.30, p = .02). Moreover, negative correlation was found between the peak FC strength in the right DLPFC and Autism Diagnostic Observation Schedule (ADOS) scores, which assessed both the social communication and interaction (r = -.147, p = .04, uncorrected significant), and stereotyped behaviors and restricted interests (r = -.198, p = .02, corrected significant). Peak FC locations varied substantially across participants. No significant differences in NAc-based FC in the DLPFC were found in the voxel-wise comparison. Our study supports the use of individualized peak FC-guided precise rTMS treatment of male ASD. Moreover, stimulating the right DLPFC might alleviate core symptoms of ASD.

Network analysis of comorbid insomnia and depressive symptoms among psychiatric practitioners during the COVID-19 pandemic.

STUDY OBJECTIVES: Insomnia and depression are common mental health problems reported by mental health professionals during the COVID-19 pandemic. Network analysis is a fine-grained approach used to examine associations between psychiatric syndromes at a symptom level. This study was designed to elucidate central symptoms and bridge symptoms of a depression-insomnia network among psychiatric practitioners in China. The identification of particularly important symptoms via network analysis provides an empirical foundation for targeting specific symptoms when developing treatments for comorbid insomnia and depression within this population. METHODS: A total of 10,516 psychiatric practitioners were included in this study. The Insomnia Severity Index (ISI) and 9-item Patient Health Questionnaire (PHQ-9) were used to estimate prevalence rates of insomnia and depressive symptoms, respectively. Analyses also generated a network model of insomnia and depression symptoms in the sample. RESULTS: Prevalence rates of insomnia (ISI total score ≥8), depression (PHQ-9 total score ≥5) and comorbid insomnia and depression were 22.2% (95% confidence interval: 21.4-22.9%), 28.5% (95% confidence interval: 27.6-29.4%), and 16.0% (95% confidence interval: 15.3-16.7%), respectively. Network analysis revealed that "Distress caused by sleep difficulties" (ISI7) and "Sleep maintenance" (ISI2) had the highest strength centrality, followed by "Motor dysfunction" (PHQ8) and "Sad mood" (PHQ2). Furthermore, the nodes "Sleep dissatisfaction" (ISI4), "Fatigue" (PHQ4), and "Motor dysfunction" (PHQ8) had the highest bridge strengths in linking depression and insomnia communities. CONCLUSIONS: Both central and bridge symptoms (ie, Distress caused by sleep difficulties, Sleep maintenance, Motor dysfunction, Sad mood, Sleep dissatisfaction, and Fatigue) should be prioritized when testing preventive measures and specific treatments to address comorbid insomnia and depression among psychiatric practitioners during the COVID-19 pandemic. CITATION: Zhao N, Zhao Y-J, An F, et al. Network analysis of comorbid insomnia and depressive symptoms among psychiatric practitioners during the COVID-19 pandemic. J Clin Sleep Med. 2023;19(7):1271-1279.

Higher reliability and validity of Wavelet-ALFF of resting-state fMRI: From multicenter database and application to rTMS modulation.

Amplitude of low-frequency fluctuation (ALFF) has been widely used for localization of abnormal activity at the single-voxel level in resting-state fMRI (RS-fMRI) studies. However, previous ALFF studies were based on fast Fourier transform (FFT-ALFF). Our recent study found that ALFF based on wavelet transform (Wavelet-ALFF) showed better sensitivity and reproducibility than FFT-ALFF. The current study aimed to test the reliability and validity of Wavelet-ALFF, and apply Wavelet-ALFF to investigate the modulation effect of repetitive transcranial magnetic stimulation (rTMS). The reliability and validity were assessed on multicenter RS-fMRI datasets under eyes closed (EC) and eyes open (EO) conditions (248 healthy participants in total). We then detected the sensitivity of Wavelet-ALFF using a rTMS modulation dataset (24 healthy participants). For each dataset, Wavelet-ALFF based on five mother wavelets (i.e., db2, bior4.4, morl, meyr and sym3) and FFT-ALFF were calculated in the conventional band and five frequency sub-bands. The results showed that the reliability of both inter-scanner and intra-scanner was higher with Wavelet-ALFF than with FFT-ALFF across multiple frequency bands, especially db2-ALFF in the higher frequency band slow-2 (0.1992-0.25 Hz). In terms of validity, the multicenter ECEO datasets showed that the effect sizes of Wavelet-ALFF with all mother wavelets (especially for db2-ALFF) were larger than those of FFT-ALFF across multiple frequency bands. Furthermore, Wavelet-ALFF detected a larger modulation effect than FFT-ALFF. Collectively, Wavelet db2-ALFF showed the best reliability and validity, suggesting that db2-ALFF may offer a powerful metric for inspecting regional spontaneous brain activities in future studies.

The neural correlates of amplitude of low-frequency fluctuation: a multimodal resting-state MEG and fMRI-EEG study.

The amplitude of low-frequency fluctuation (ALFF) describes the regional intensity of spontaneous blood-oxygen-level-dependent signal in resting-state functional magnetic resonance imaging (fMRI). How the fMRI-ALFF relates to the amplitude in electrophysiological signals remains unclear. We here aimed to investigate the neural correlates of fMRI-ALFF by comparing the spatial difference of amplitude between the eyes-closed (EC) and eyes-open (EO) states from fMRI and magnetoencephalography (MEG), respectively. By synthesizing MEG signal into amplitude-based envelope time course, we first investigated 2 types of amplitude in MEG, meaning the amplitude of neural activities from delta to gamma (i.e. MEG-amplitude) and the amplitude of their low-frequency modulation at the fMRI range (i.e. MEG-ALFF). We observed that the MEG-ALFF in EC was increased at parietal sensors, ranging from alpha to beta; whereas the MEG-amplitude in EC was increased at the occipital sensors in alpha. Source-level analysis revealed that the increased MEG-ALFF in the sensorimotor cortex overlapped with the most reliable EC-EO differences observed in fMRI at slow-3 (0.073-0.198 Hz), and these differences were more significant after global mean standardization. Taken together, our results support that (i) the amplitude at 2 timescales in MEG reflect distinct physiological information and that (ii) the fMRI-ALFF may relate to the ALFF in neural activity.

Test-retest reliability of peak location in the sensorimotor network of resting state fMRI for potential rTMS targets.

Most stroke repetitive transcranial magnetic stimulation (rTMS) studies have used hand motor hotspots as rTMS stimulation targets; in addition, recent studies demonstrated that functional magnetic resonance imaging (fMRI) task activation could be used to determine suitable targets due to its ability to reveal individualized precise and stronger functional connectivity with motor-related brain regions. However, rTMS is unlikely to elicit motor evoked potentials in the affected hemisphere, nor would activity be detected when stroke patients with severe hemiplegia perform an fMRI motor task using the affected limbs. The current study proposed that the peak voxel in the resting-state fMRI (RS-fMRI) motor network determined by independent component analysis (ICA) could be a potential stimulation target. Twenty-one healthy young subjects underwent RS-fMRI at three visits (V1 and V2 on a GE MR750 scanner and V3 on a Siemens Prisma) under eyes-open (EO) and eyes-closed (EC) conditions. Single-subject ICA with different total number of components (20, 30, and 40) were evaluated, and then the locations of peak voxels on the left and right sides of the sensorimotor network (SMN) were identified. While most ICA RS-fMRI studies have been carried out on the group level, that is, Group-ICA, the current study performed individual ICA because only the individual analysis could guide the individual target of rTMS. The intra- (test-retest) and inter-scanner reliabilities of the peak location were calculated. The use of 40 components resulted in the highest test-retest reliability of the peak location in both the left and right SMN compared with that determined when 20 and 30 components were used for both EC and EO conditions. ICA with 40 components might be another way to define a potential target in the SMN for poststroke rTMS treatment.

Default mode network mediates low-frequency fluctuations in brain activity and behavior during sustained attention.

The low-frequency (<0.1 Hz) fluctuation in sustained attention attracts enormous interest in cognitive neuroscience and clinical research since it always leads to cognitive and behavioral lapses. What is the source of the spontaneous fluctuation in sustained attention in neural activity, and how does the neural fluctuation relate to behavioral fluctuation? Here, we address these questions by collecting and analyzing two independent fMRI and behavior datasets. We show that the neural (fMRI) fluctuation in a key brain network, the default-mode network (DMN), mediate behavioral (reaction time) fluctuation during sustained attention. DMN shows the increased amplitude of fluctuation, which correlates with the behavioral fluctuation in a similar frequency range (0.01-0.1 Hz) but not in the lower (<0.01 Hz) or higher (>0.1 Hz) frequency range. This was observed during both auditory and visual sustained attention and was replicable across independent datasets. These results provide a novel insight into the neural source of attention-fluctuation and extend the former concept that DMN was deactivated in cognitive tasks. More generally, our findings highlight the temporal dynamic of the brain-behavior relationship.

Lifespan associations of resting-state brain functional networks with ADHD symptoms.

Attention-deficit/hyperactivity disorder (ADHD) is increasingly being diagnosed in both children and adults, but the neural mechanisms that underlie its distinct symptoms and whether children and adults share the same mechanism remain poorly understood. Here, we used a nested-spectral partition approach to study resting-state brain networks of ADHD patients (n = 97) and healthy controls (HCs, n = 97) across the lifespan (7-50 years). Compared to the linear lifespan associations of brain segregation and integration with age in HCs, ADHD patients have a quadratic association in the whole-brain and in most functional systems, whereas the limbic system dominantly affected by ADHD has a linear association. Furthermore, the limbic system better predicts hyperactivity, and the salient attention system better predicts inattention. These predictions are shared in children and adults with ADHD. Our findings reveal a lifespan association of brain networks with ADHD and provide potential shared neural bases of distinct ADHD symptoms in children and adults.

Aberrant visual-related networks in familial cortical myoclonic tremor with epilepsy.

INTRODUCTION: In familial cortical myoclonic tremor with epilepsy, photic stimulation can trigger visual symptoms and induce a photoparoxysmal response, or photosensitivity, on electroencephalography. However, the mechanism is poorly understood. In this study, we aimed to explore the neuroimaging changes related to visual symptoms and photosensitivity in genetically confirmed familial cortical myoclonic tremor with epilepsy type 1. METHODS: Resting-state functional magnetic resonance imaging and electroencephalography data were collected from 31 patients carrying the heterozygous pathogenic intronic pentanucleotide (TTTCA)n insertion in the sterile alpha motif domain-containing 12 gene and from 52 age- and sex-matched healthy controls. RESULTS: (1) Both regional homogeneity and degree centrality values in the bilateral calcarine sulcus were significantly increased in patients compared with healthy controls. (2) When the calcarine sulcus area with increased regional homogeneity was taken as a seed, increased functional connectivity values were observed in the right precentral gyrus, while decreased functional connectivity values were observed in the right superior frontal gyrus and right inferior parietal lobule. (3) Independent component analysis showed increased connectivity in the left calcarine sulcus inside the medial visual network. (4) Correlation analysis revealed a significant positive correlation between regional homogeneity values and frequency of seizure, and photoparoxysmal response grades were positively correlated with the severity of cortical tremor and duration of epilepsy. CONCLUSION: These findings provide strong evidence for the interpretation of visual symptoms and photosensitivity in familial cortical myoclonic tremor with epilepsy. We speculate that functional changes in the primary visual cortex may be an imaging biomarker for the disease.

Toward Precise Localization of Abnormal Brain Activity: 1D CNN on Single Voxel fMRI Time-Series.

Functional magnetic resonance imaging (fMRI) is one of the best techniques for precise localization of abnormal brain activity non-invasively. Machine-learning approaches have been widely used in neuroimaging studies; however, few studies have investigated the single-voxel modeling of fMRI data under cognitive tasks. We proposed a hybrid one-dimensional (1D) convolutional neural network (1D-CNN) based on the temporal dynamics of single-voxel fMRI time-series and successfully differentiated two continuous task states, namely, self-initiated (SI) and visually guided (VG) motor tasks. First, 25 activation peaks were identified from the contrast maps of SI and VG tasks in a blocked design. Then, the fMRI time-series of each peak voxel was transformed into a temporal-frequency domain by using continuous wavelet transform across a broader frequency range (0.003-0.313 Hz, with a step of 0.01 Hz). The transformed time-series was inputted into a 1D-CNN model for the binary classification of SI and VG continuous tasks. Compared with the univariate analysis, e.g., amplitude of low-frequency fluctuation (ALFF) at each frequency band, including, wavelet-ALFF, the 1D-CNN model highly outperformed wavelet-ALFF, with more efficient decoding models [46% of 800 models showing area under the curve (AUC) > 0.61] and higher decoding accuracies (94% of the efficient models), especially on the high-frequency bands (>0.1 Hz). Moreover, our results also demonstrated the advantages of wavelet decompositions over the original fMRI series by showing higher decoding performance on all peak voxels. Overall, this study suggests a great potential of single-voxel analysis using 1D-CNN and wavelet transformation of fMRI series with continuous, naturalistic, steady-state task design or resting-state design. It opens new avenues to precise localization of abnormal brain activity and fMRI-guided precision brain stimulation therapy.

The Location Reliability of the Resting-State fMRI FC of Emotional Regions Towards rTMS Therapy.

Resting-state magnetic resonance imaging (RS-fMRI) studies indicated that the repetitive transcranial magnetic stimulation (rTMS) exerts antidepression effect through the functional connectivity (FC) of the DLPFC with the subgenual anterior cingulate cortex (sgACC), pregneual ACC (pgACC), or nucleus accumbens (NAc). It is proposed that the FC-guided individualized precise stimulation on the DLPFC would be more effective. The current study systematically investigated the reliability of the RS-fMRI FC location as well as the FC strength with multiple potential factors. We aimed to provide a stable stimulation target for future FC-guided TMS therapy for affective related disorders. Twenty-one subjects under RS-fMRI conditions with the first two times (V1, V2) scanned on a GE 3 T scanner and the third visit (V3) on a Siemens 3 T scanner. Then the FC strength and location reliability were assessed by using intra-class correlation (ICC) and intra-individual distance, respectively. The factors included deep seed ROIs (midline (mid-) sgACC, left pgACC, mid-pgACC, and left NAc), eyes closed (EC) vs eyes open (EO), frequency bands, FC algorithm (Pearson vs Spearman), scanning length (half a session vs whole session), and location method (FC peak vs center of gravity (COG)). The reliability of the voxel-wise FC strength was low to moderate. The intra-individual distances of the COG were 3.8-7.3 mm across all factors, much smaller than that of FC peak (approximately 30 mm). The COG of seed-based FC might be a potential rTMS stimulation target. Anyway, all potential stimulation targets should be tested in future rTMS treatment studies.

Toward Coordinate-based Cognition Dictionaries: A BrainMap and Neurosynth Demo.

Characterizing the functional involvement of specific brain regions has long been a central challenge in cognitive neuroscience. Functional magnetic resonance imaging (fMRI) techniques have offered solutions for mapping functional neural networks. The complex nature of structure-function correspondence makes an elaborate task design difficult to fully capture higher-order cognitive function. Other research practices, such as brain-behavior association or between-group comparisons, are thus widely used to explore cognitive correlations with specific brain regions. However, interpreting the results derived from a specific brain region with their underlying cognitive functions has been too general in publications. Here, we use two examples, i.e., a brain-intelligence correlation study and a depression-control comparison meta-study, to demonstrate use of two neuroimaging online databases, BrainMap and Neurosynth. One key utility of the two databases is collecting results from massive cognitive task-based fMRI (tb-fMRI) studies, i.e., coordinates in standard brain space. Just like looking up a "coordinate-based cognition dictionary", researchers can receive a plethora of related tb-fMRI activation information characterized by cognitive domains, specific cognitive functions, cognitive task paradigms, and related publications. Surprisingly, we found that only less than 1% of brain-behavior association or between-group comparison studies have utilized this dictionary approach. We encourage the community to further engage with the existing databases for specific and comprehensive interpretation of neuroimaging as well as guidance of future experimental tb-fMRI design.

White matter alterations in familial cortical myoclonic tremor with epilepsy type 1.

OBJECTIVE: Although previous imaging studies have reported cerebellar gray matter loss in patients with familial cortical myoclonic tremor with epilepsy (FCMTE), the corresponding white matter alterations remain unknown. We investigated white matter structural changes in FCMTE1 and compared them with clinical and electrophysiological features. METHODS: We enrolled 36 patients carrying heterozygous pathogenic intronic pentanucleotide insertions in the SAMD12 gene and 52 age- and sex-matched healthy controls. Diffusion tensor imaging-derived metrics, including fractional anisotropy, mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD), were calculated along with white matter voxel-based morphometry (VBM) analysis. We also examined correlations between magnetic resonance metrics and clinical and electrophysiological features. RESULTS: We detected widespread white matter reductions in MD, RD, and AD values in FCMTE1 patients, including in the commissural, projection, and association fibers. VBM analysis revealed that increases in white matter volume predominantly occurred in the right cerebellum and sagittal stratum. MD, RD, AD, and VBM analysis clearly indicated changes in the sagittal stratum. We found a positive correlation between VBM values in the right cerebellum and somatosensory-evoked potential P25-N33 amplitude. Decreased MD and AD values in the right sagittal stratum were detected in patients with versus without photophobia. SIGNIFICANCE: FCMTE is a network disorder involving a wide range of cortical and subcortical structures, including the cerebellum, thalamus, thalamocortical connections, and corticocortical connections. The right sagittal stratum is closely related with visual symptoms, especially photophobia. Our findings indicate that cerebellum and cortical hyperexcitability are closely linked, and emphasize the important role of the cerebellum in the pathophysiological mechanisms of cortical tremor.