Classification of human chronotype based on fMRI network-based statistics.

Chronotype-the relationship between the internal circadian physiology of an individual and the external 24-h light-dark cycle-is increasingly implicated in mental health and cognition. Individuals presenting with a late chronotype have an increased likelihood of developing depression, and can display reduced cognitive performance during the societal 9-5 day. However, the interplay between physiological rhythms and the brain networks that underpin cognition and mental health is not well-understood. To address this issue, we use rs-fMRI collected from 16 people with an early chronotype and 22 people with a late chronotype over three scanning sessions. We develop a classification framework utilizing the Network Based-Statistic methodology, to understand if differentiable information about chronotype is embedded in functional brain networks and how this changes throughout the day. We find evidence of subnetworks throughout the day that differ between extreme chronotypes such that high accuracy can occur, describe rigorous threshold criteria for achieving 97.3% accuracy in the Evening and investigate how the same conditions hinder accuracy for other scanning sessions. Revealing differences in functional brain networks based on extreme chronotype suggests future avenues of research that may ultimately better characterize the relationship between internal physiology, external perturbations, brain networks, and disease.

Evaluating denoising strategies in resting-state functional magnetic resonance in traumatic brain injury (EpiBioS4Rx).

Resting-state functional MRI is increasingly used in the clinical setting and is now included in some diagnostic guidelines for severe brain injury patients. However, to ensure high-quality data, one should mitigate fMRI-related noise typical of this population. Therefore, we aimed to evaluate the ability of different preprocessing strategies to mitigate noise-related signal (i.e., in-scanner movement and physiological noise) in functional connectivity (FC) of traumatic brain injury (TBI) patients. We applied nine commonly used denoising strategies, combined into 17 pipelines, to 88 TBI patients from the Epilepsy Bioinformatics Study for Anti-epileptogenic Therapy clinical trial. Pipelines were evaluated by three quality control (QC) metrics across three exclusion regimes based on the participant's head movement profile. While no pipeline eliminated noise effects on FC, some pipelines exhibited relatively high effectiveness depending on the exclusion regime. Once high-motion participants were excluded, the choice of denoising pipeline becomes secondary - although this strategy leads to substantial data loss. Pipelines combining spike regression with physiological regressors were the best performers, whereas pipelines that used automated data-driven methods performed comparatively worse. In this study, we report the first large-scale evaluation of denoising pipelines aimed at reducing noise-related FC in a clinical population known to be highly susceptible to in-scanner motion and significant anatomical abnormalities. If resting-state functional magnetic resonance is to be a successful clinical technique, it is crucial that procedures mitigating the effect of noise be systematically evaluated in the most challenging populations, such as TBI datasets.

ResectVol: A tool to automatically segment and characterize lacunas in brain images.

OBJECTIVE: To assess and validate the performance of a new tool developed for segmenting and characterizing lacunas in postoperative MR images of epilepsy patients. METHODS: A MATLAB-based pipeline was implemented using SPM12 to produce the 3D mask of the surgical lacuna and estimate its volume. To validate its performance, we compared the manual and automatic lacuna segmentations obtained from 51 MRI scans of epilepsy patients who underwent temporal lobe resections. RESULTS: The code is consolidated as a tool named ResectVol, which can be run via a graphical user interface or command line. The automatic and manual segmentation comparison resulted in a median Dice similarity coefficient of 0.77 (interquartile range: 0.71-0.81). SIGNIFICANCE: Epilepsy surgery is the treatment of choice for pharmacoresistant focal epilepsies, and despite the extensive literature on the subject, we still cannot predict surgical outcomes accurately. As the volume and location of the resected tissue are fundamentally relevant to this prediction, researchers commonly perform a manual segmentation of the lacuna, which presents human bias and does not provide detailed information about the structures removed. In this study, we introduce ResectVol, a user-friendly, fully automatic tool to accomplish these tasks. This capability enables more advanced analytical techniques applied to surgical outcomes prediction, such as machine-learning algorithms, by facilitating coregistration of the resected area and preoperative findings with other imaging modalities such as PET, SPECT, and functional MRI ResectVol is freely available at https://www.lniunicamp.com/resectvol.

EEG Signal Connectivity for Characterizing Interictal Activity in Patients With Mesial Temporal Lobe Epilepsy.

Over the last decade, several methods for analysis of epileptiform signals in electroencephalography (EEG) have been proposed. These methods mainly use EEG signal features in either the time or the frequency domain to separate regular, interictal, and ictal brain activity. The aim of this work was to evaluate the feasibility of using functional connectivity (FC) based feature extraction methods for the analysis of epileptiform discharges in EEG signals. These signals were obtained from EEG-fMRI sessions of 10 patients with mesial temporal lobe epilepsy (MTLE) with unilateral hippocampal atrophy. The connectivity functions investigated were motif synchronization, imaginary coherence, and magnitude squared coherence in the alpha, beta, and gamma bands of the EEG. EEG signals were sectioned into 1-s epochs and classified according to (using neurologist markers): activity far from interictal epileptiform discharges (IED), activity immediately before an IED and, finally, mid-IED activity. Connectivity matrices for each epoch for each FC function were built, and graph theory was used to obtain the following metrics: strength, cluster coefficient, betweenness centrality, eigenvector centrality (both local and global), and global efficiency. The statistical distributions of these metrics were compared among the three classes, using ANOVA, for each FC function. We found significant differences in all global (p < 0.001) and local (p < 0.00002) graph metrics of the far class compared with before and mid for motif synchronization on the beta band; local betweenness centrality also pointed to a degree of lateralization on the frontotemporal structures. This analysis demonstrates the potential of FC measures, computed using motif synchronization, for the characterization of epileptiform activity of MTLE patients. This methodology may be helpful in the analysis of EEG-fMRI data applied to epileptic foci localization. Nonetheless, the methods must be tested with a larger sample and with other epileptic phenotypes.

Cerebral Structure and Function in Stroke-free Patients with Atrial Fibrillation.

OBJECTIVES: Atrial fibrillation (AF) is associated with high risk of dementia and brain atrophy in stroke-free patients, but the mechanisms underlying this association remain unclear. We aimed to examine the brain volume and connectivity of paramount cognitive brain networks in stroke-free patients with AF without dementia. MATERIALS AND METHODS: Twenty-six stroke-free patients with AF and 26 age and sex-matched subjects without AF were submitted to a 3-tesla brain structural and functional MRI. An extensive clinical evaluation excluded stroke, dementia, low cardiac output, carotid stenosis and metabolic diseases without optimal therapy. We used CHA2DS2-VASc score to classify the cardiovascular risk factor burden and a broad neuropsychological battery to assess the cognitive performance. Voxel based morphometry analysis of. structural MRI defined whole-brain gray and white matter volumes. Finally, we used eco-plannar MRI images to compare the differences of functional connectivity of 7 large-scale resting-state networks between AF patients and controls. RESULTS: Taking into account the history of hypertension and heart failure, AF was associated to volume decrease of the right basal frontal lobe and right inferior cerebellum. Decreased connectivity of the ventral Default Mode Network (vDMN) was observed in the AF group. No disruption of connectivity was observed in the executive, visuospatial and salience networks. CONCLUSION: Individuals with AF without stroke or dementia have subtle reduction of gray and white matter, restricted to frontal areas and cerebellum. These patients show decreased vDMN connectivity, without other large-scale brain network disruption.

Temporal organisation of the brain's intrinsic motor network: The relationship with circadian phenotype and motor performance.

BACKGROUND: Functional connectivity (FC) of the motor network (MN) is often used to investigate how intrinsic properties of the brain are associated with motor abilities and performance. In addition, the MN is a key feature in clinical work to map the recovery after stroke and aid the understanding of neurodegenerative disorders. Time of day variation and individual differences in circadian timing, however, have not yet been considered collectively when looking at FC. METHODS: A total of 33 healthy, right handed individuals (13 male, 23.1 ± 4.2 years) took part in the study. Actigraphy, sleep diaries and circadian phase markers (dim light melatonin onset and cortisol awakening response) were used to determine early (ECP, n = 13) and late (LCP, n = 20) circadian phenotype groups. Resting state functional MRI testing sessions were conducted at 14:00 h, 20:00 h and 08:00 h and preceded by a maximum voluntary contraction test for isometric grip strength to measure motor performance. RESULTS: Significant differences in FC of the MN between ECPs and LCPs were found, as well as significant variations between different times of day. A higher amplitude in diurnal variation of FC and performance was observed in LCPs compared to ECPs, with the morning being most significantly affected. Overall, lower FC was significantly associated with poorer motor performance. DISCUSSION: Our findings uncover intrinsic differences between times of day and circadian phenotype groups. This suggests that central mechanisms contribute to diurnal variation in motor performance and the functional integrity of the MN at rest influences the ability to perform in a motor task.

Selective sensory deafferentation induces structural and functional brain plasticity.

Sensory-motor integration models have been proposed aiming to explain how the brain uses sensory information to guide and check the planning and execution of movements. Sensory neuronopathy (SN) is a peculiar disease characterized by exclusive, severe and widespread sensory loss. It is a valuable condition to investigate how sensory deafferentation impacts brain organization. We thus recruited patients with clinical and electrophysiological criteria for SN to perform structural and functional MRI analyses. We investigated volumetric changes in gray matter (GM) using anatomical images; the microstructure of WM within segmented regions of interest (ROI), via diffusion images; and brain activation related to a finger tapping task. All significant results were related to the long disease duration subgroup of patients. Structural analysis showed hypertrophy of the caudate nucleus, whereas the diffusion study identified reduction of fractional anisotropy values in ROIs located around the thalamus and the striatum. We also found differences regarding finger-tapping activation in the posterior parietal regions and in the medial areas of the cerebellum. Our results stress the role of the caudate nucleus over the other basal ganglia in the sensory-motor integration models, and suggest an inhibitory function of a recently discovered tract between the thalamus and the striatum. Overall, our findings confirm plasticity in the adult brain and open new avenues to design neurorehabilitation strategies.

Default Mode Network Disruption in Stroke-Free Patients with Atrial Fibrillation.

BACKGROUND: Atrial fibrillation (AF) is a widely accepted risk for causing stroke. However, recent studies show AF as a risk factor for dementia, even without causing stroke. The mechanisms by which dementia develops in stroke-free patients with AF are still poorly understood and the association of AF with abnormal function of brain networks activities, such as the default mode network (DMN), has not been previously studied. We aimed to determine whether, in the absence of stroke and dementia, patients with AF have abnormal resting-state brain networks compared to controls without AF. METHODS: Twenty-one stroke-free patients with AF and 21 age- and sex-matched controls without AF underwent brain functional magnetic resonance imaging acquired at a 3.0 Tesla scanner. During the exam, the subjects were instructed to lie still with eyes closed. At first-level analysis, connectivity of the DMN was obtained for all subjects. Second-level analysis compared the DMN connectivity between AF patients and controls with a general linear model (two-sample t test, p < 0.05, False Discovery Rate corrected, minimum of 50 contiguous voxels). RESULTS: Patients with AF compared with controls showed decreased connectivity in regions of the DMN including the frontal lobe (left medial frontal gyrus, left superior frontal gyrus and anterior cingulate), left angular gyrus, and bilateral precuneus. CONCLUSIONS: Stroke-free patients with AF have evidence of abnormal DMN connectivity. This study adds evidence to the occurrence of cerebral dysfunction in patients with AF.

Brain signature of mild stages of cognitive and behavioral impairment in amyotrophic lateral sclerosis.

We aimed to assess the brain signature of cognitive and behavioral impairment in C9orf72-negative non-demented ALS patients. The study included 50 amyotrophic lateral sclerosis (ALS) patients (out of 75 initially recruited) and 38 healthy controls. High-resolution T1-weighted and spin-echo diffusion tensor images were acquired in a 3T MRI scanner. The multi atlas-based analysis protocol and the FreeSurfer tool were employed for gray matter assessment, and fiber tractography for white matter evaluation. Cognitively impaired ALS patients (n = 12) had bilateral amygdalae and left thalamic volumetric reduction compared to non-impaired ALS patients. Behaviorally impaired ALS patients (n = 14) had lower fractional anisotropy (FA) at the fornix in comparison with healthy subjects. These parameters did correlate with cognitive/behavioral scores, but not with motor-functional parameters in the ALS cohort. We believe that basal ganglia and fornix damage might be related to cognitive and behavioral impairment across ALS-frontotemporal dementia continuum. Also, distinct anatomical areas seem to influence the behavioral and cognitive status of these individuals.

Brain Connectivity and Functional Recovery in Patients With Ischemic Stroke.

BACKGROUND: Brain mapping studies have demonstrated that functional poststroke brain reorganization is associated with recovery of motor function. Nonetheless, the specific mechanisms associated with functional reorganization leading to motor recovery are still partly unknown. In this study, we performed a cross-sectional evaluation of poststroke subjects with the following goals: (1) To assess intra- and interhemispheric functional brain activation patterns associated with motor function in poststroke patients with variable degrees of recovery; (2) to investigate the involvement of other nonmotor functional networks in relationship with recovery. METHODS: We studied 59 individuals: 13 patients with function Rankin > 1 and Barthel < 100; 19 patients with preserved function with Rankin 0-1 and Barthel = 100; and 27 healthy controls. All subjects underwent structural and functional magnetic resonance imaging (3T Philips Achieva, Holland) using the same protocol (TR = 2 seconds, TE = 30 ms, FOV = 240 × 240 × 117, slice = 39). Resting state functional connectivity was used by in-house software, based on SPM12. Among patients with and without preserved function, the functional connectivity between the primary motor region (M1) and the contralateral hemisphere was increased compared with controls. Nonetheless, only patients with decreased function exhibited decreased functional connectivity between executive control, sensorimotor and visuospatial networks. CONCLUSION: Functional recovery after stroke is associated with preserved functional connectivity of motor to nonmotor networks.

Modified Anterior Temporal Lobectomy: Anatomical Landmarks and Operative Technique.

There is great controversy about which surgical approach is the most selective and efficient for resection of mesial structures of the temporal lobe for treatment of mesial temporal lobe epilepsy. Selective approaches have been described in an attempt to preserve the neocortex and the temporal stem. Nonselective approaches, such as anterior temporal lobectomy (ATL), result in injuries in these structures. We describe a modified selective technique for resection of the amygdala and hippocampus with resection of the temporal pole performed through the Sylvian fissure based on anatomical landmarks and diligent microsurgical techniques. Briefly, after opening the Sylvian fissure, the temporal pole is resected and the temporal horn is directly accessed through the uncus, in an anteroposterior direction, preserving the temporal stem and the neocortex of the temporal lobe. The surgical technique used by our group is described in detail with illustrations. Precise microsurgical techniques associated with knowledge of microsurgical anatomy are of paramount importance for temporal lobe epilepsy surgery. According to our analysis, the modified ATL approach to the temporal mesial structures is a feasible selective technique that can be used as an alternative to traditional surgical procedures.

Diffuse decreased gray matter in patients with idiopathic craniocervical dystonia: a voxel-based morphometry study.

BACKGROUND: Recent studies have addressed the role of structures other than the basal ganglia in the pathophysiology of craniocervical dystonia (CCD). Neuroimaging studies have attempted to identify structural abnormalities in CCD but a clear pattern of alteration has not been established. We performed whole-brain evaluation using voxel-based morphometry (VBM) to identify patterns of gray matter (GM) changes in CCD. METHODS: We compared 27 patients with CCD matched in age and gender to 54 healthy controls. VBM was used to compare GM volumes. We created a two-sample t-test corrected for subjects' age, and we tested with a level of significance of p < 0.001 and false discovery rate (FDR) correction (p < 0.05). RESULTS: Voxel-based morphometry demonstrated significant reductions of GM using p < 0.001 in the cerebellar vermis IV/V, bilaterally in the superior frontal gyrus, precuneus, anterior cingulate and paracingulate, insular cortex, lingual gyrus, and calcarine fissure; in the left hemisphere in the supplementary motor area, inferior frontal gyrus, inferior parietal gyrus, temporal pole, supramarginal gyrus, rolandic operculum, hippocampus, middle occipital gyrus, cerebellar lobules IV/V, superior, and middle temporal gyri; in the right hemisphere, the middle cingulate and precentral gyrus. Our study did not report any significant result using the FDR correction. We also detected correlations between GM volume and age, disease duration, duration of botulinum toxin treatment, and the Marsden-Fahn dystonia scale scores. CONCLUSION: We detected large clusters of GM changes chiefly in structures primarily involved in sensorimotor integration, motor planning, visuospatial function, and emotional processing.