An empirical analysis of structural neuroimaging profiles in a staging model of depression.

We examine structural brain characteristics across three diagnostic categories: at risk for serious mental illness; first-presenting episode and recurrent major depressive disorder (MDD). We investigate whether the three diagnostic groups display a stepwise pattern of brain changes in the cortico-limbic regions. Integrated clinical and neuroimaging data from three large Canadian studies were pooled (total n = 622 participants, aged 12-66 years). Four clinical profiles were used in the classification of a clinical staging model: healthy comparison individuals with no history of depression (HC, n = 240), individuals at high risk for serious mental illness due to the presence of subclinical symptoms (SC, n = 80), first-episode depression (FD, n = 82), and participants with recurrent MDD in a current major depressive episode (RD, n = 220). Whole-brain volumetric measurements were extracted with FreeSurfer 7.1 and examined using three different types of analyses. Hippocampal volume decrease and cortico-limbic thinning were the most informative features for the RD vs HC comparisons. FD vs HC revealed that FD participants were characterized by a focal decrease in cortical thickness and global enlargement in amygdala volumes. Greater total amygdala volumes were significantly associated with earlier onset of illness in the FD but not the RD group. We did not confirm the construct validity of a tested clinical staging model, as a differential pattern of brain alterations was identified across the three diagnostic groups that did not parallel a stepwise clinical staging approach. The pathological processes during early stages of the illness may fundamentally differ from those that occur at later stages with clinical progression.

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.

Cerebello-limbic functional connectivity patterns in youth at clinical high risk for psychosis.

Youth at clinical high risk (CHR) for psychosis can present not only with characteristic attenuated psychotic symptoms but also may have other comorbid conditions, including anxiety and depression. These undifferentiated mood symptoms can overlap with the clinical presentation of youth with Distress syndromes. Increased resting-state functional connectivity within cerebello-thalamo-cortical (CTC) pathways has been proposed as a trait-specific biomarker for CHR. However, it is unclear whether this functional neural signature remains specific when compared to a different risk group: youth with Distress syndromes. The purpose of the present work was to describe CTC alterations that distinguish between CHR and Distressed individuals. Using machine learning algorithms, we analyzed CTC connectivity features of CHR (n = 51), Distressed (n = 41), and healthy control (n = 36) participants. We found four cerebellar (lobes VII and left Crus II anterior/posterior) and two basal ganglia (right putamen and right thalamus) nodes containing a set of specific connectivity features that distinguished between CHR, Distressed and healthy control groups. Hyperconnectivity between medial lobule VIIb, somatomotor network and middle temporal gyrus was associated with CHR status and more severe symptoms. Detailed atlas parcellation suggested that CHR individuals may have dysfunction mainly within the associative (cognitive) pathways, particularly, between those brain areas responsible for the multi-sensory signal integration.

Effects of virtual reality-based motor rehabilitation: a systematic review of fMRI studies.

Background.The use of virtual reality (VR) as a rehabilitation tool has been shown to induce motor and cognitive improvements in different populations. Functional magnetic resonance imaging (fMRI) has been used to investigate neuroplasticity resulting from these treatments. We hypothesize that VR rehabilitation induces functional improvement and brain changes that can be detected by fMRI.Objective.To systematically review the effects of VR intervention on the cortical reorganization measured by fMRI and associated with functional improvement.Approach.We performed a systematic review of studies published between 2005 and 2021. Papers were retrieved from six databases using the following keywords: 'motor rehabilitation', 'fMRI' and 'virtual reality'. Case studies, pre-post studies, cross-sectional studies, and randomized controlled trials published were included. Manuscripts were assessed by The National Institutes of Health study quality assessment tools to determine their quality.Main results.Twenty-three articles met our eligibility criteria: 18 about VR rehabilitation in stroke and five on other clinical conditions (older adults, cerebral palsy, and Parkinson's disease). Changes in neural patterns of activation and reorganization were revealed in both the ipsilesional and the contralesional hemispheres. Results were located mainly in the primary motor cortex, sensorimotor cortex and supplementary motor area in post-stroke patients in the acute, subacute, and chronic rehabilitation phases, and were associated with functional improvement after VR intervention. Similar effects were observed in older adults and in patients with other neurological diseases with improved performance.Significance.Most stroke-related studies showed either restoration to normal or increase of activation patterns or relateralization at/to the ipsilesional hemisphere, with some also reporting a decrease in activity or extent of activation after VR therapy. In general, VR intervention demonstrated evidence of efficacy both in neurological rehabilitation and in performance improvement of older adults, accompanied by fMRI evidence of brain reorganization.

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.

Brain Damage and Gene Expression Across Hereditary Spastic Paraplegia Subtypes.

BACKGROUND: Spinal cord has been considered the main target of damage in hereditary spastic paraplegias (HSPs), but mounting evidence indicates that the brain is also affected. Despite this, little is known about the brain signature of HSPs, in particular regarding stratification for specific genetic subtypes. OBJECTIVE: We aimed to characterize cerebral and cerebellar damage in five HSP subtypes (9 SPG3A, 27 SPG4, 10 SPG7, 9 SPG8, and 29 SPG11) and to uncover the clinical and gene expression correlates. METHODS: We obtained high-resolution brain T1 and diffusion tensor image (DTI) datasets in this cross-sectional case-control study (n = 84). The MRICloud, FreeSurfer, and CERES-SUIT pipelines were employed to assess cerebral gray (GM) and white matter (WM) as well as the cerebellum. RESULTS: Brain abnormalities were found in all but one HSP group (SPG3A), but the patterns were gene-specific: basal ganglia, thalamic, and posterior WM involvement in SPG4; diffuse WM and cerebellar involvement in SPG7; cortical thinning at the motor cortices and pallidal atrophy in SPG8; and widespread GM, WM, and deep cerebellar nuclei damage in SPG11. Abnormal regions in SPG4 and SPG8 matched those with higher SPAST and WASHC5 expression, whereas in SPG7 and SPG11 this concordance was only noticed in the cerebellum. CONCLUSIONS: Brain damage is a conspicuous feature of HSPs (even for pure subtypes), but the pattern of abnormalities is genotype-specific. Correlation between brain structural damage and gene expression maps is different for autosomal dominant and recessive HSPs, pointing to distinct pathophysiological mechanisms underlying brain damage in these subgroups of the disease. © 2021 International Parkinson and Movement Disorder Society.

Alzheimer's Disease Detection Through Whole-Brain 3D-CNN MRI.

The projected burden of dementia by Alzheimer's disease (AD) represents a looming healthcare crisis as the population of most countries grows older. Although there is currently no cure, it is possible to treat symptoms of dementia. Early diagnosis is paramount to the development and success of interventions, and neuroimaging represents one of the most promising areas for early detection of AD. We aimed to deploy advanced deep learning methods to determine whether they can extract useful AD biomarkers from structural magnetic resonance imaging (sMRI) and classify brain images into AD, mild cognitive impairment (MCI), and cognitively normal (CN) groups. We tailored and trained Convolutional Neural Networks (CNNs) on sMRIs of the brain from datasets available in online databases. Our proposed method, ADNet, was evaluated on the CADDementia challenge and outperformed several approaches in the prior art. The method's configuration with machine-learning domain adaptation, ADNet-DA, reached 52.3% accuracy. Contributions of our study include devising a deep learning system that is entirely automatic and comparatively fast, presenting competitive results without using any patient's domain-specific knowledge about the disease. We were able to implement an end-to-end CNN system to classify subjects into AD, MCI, or CN groups, reflecting the identification of distinctive elements in brain images. In this context, our system represents a promising tool in finding biomarkers to help with the diagnosis of AD and, eventually, many other diseases.

Interactions between in vivo neuronal-glial markers, side of hippocampal sclerosis, and pharmacoresponse in temporal lobe epilepsy.

OBJECTIVE: To evaluate the interactions of metabolic neuronal-glial changes with the presence and hemispheric-side of hippocampal sclerosis (HS) and its potential role in predicting pharmacoresistance in temporal lobe epilepsy (TLE). METHODS: We included structural magnetic resonance imaging (MRI) and proton magnetic resonance spectroscopy (1 H-MRS) metabolic data for 91 patients with unilateral TLE and 50 healthy controls. We measured the values of total N-acetyl aspartate/total creatine (tNAA/tCr), glutamate/tCr (Glu/tCr), and myo-inositol/tCr (mIns/tCr). To assess the influence of the pharmacoresponse and hemispheric-side of HS on metabolic data, the relationship between clinical and MRI data, and the predictive value of NAA/Cr, we used analysis of variance/covariance and built a logistic regression model. We used bootstrap simulations to evaluate reproducibility. RESULTS: Bilateral tNAA/tCr reduction was associated with pharmacoresistance and with left HS, a decrease of Glu/tCr ipsilateral to the seizure focus was associated with pharmacoresistance, and ipsilateral mIns/tCr increase was related to pharmacoresistance and the presence of left HS. The logistic regression model containing clinical and 1 H-MRS data discriminated pharmacoresistance (area under the curve [AUC] = 0.78). However, the reduction of tNAA/tCr was the main predictor, with the odds 2.48 greater for pharmacoresistance. SIGNIFICANCE: Our study revealed a spectrum of neuronal-glial changes in TLE, which was associated with pharmacoresistance, being more severe in left-sided HS and less severe in MRI-negative TLE. These noninvasive, in vivo biomarkers provide valuable additional information about the interhemispheric differences in metabolic dysfunction, seizure burden, and HS, and may help to predict pharmacoresistance.

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.

Sensory neuronopathy heralding human T cell lymphotropic virus type I myelopathy.

Neurological phenotypes of human T cell lymphotropic virus type I (HTLV-1) are numerous and rarely may not manifest the classic HTLV-associated myelopathy/tropical spastic paraparesis (HAM/TSP). We report a case of HTLV-1-related sensory neuronopathy heralding the classic HAM/TSP.

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.

Derek Denny-Brown: the man behind the ganglia.

The authors present an historical review about the main contributions of Professor Derek Denny-Brown to neurology. Some of his achievements include the first description of sensory neuronopathies, and some of the essential textbooks on the function and anatomy of the basal ganglia. In 2016, on the 35th anniversary of his death, modern neurologists are still strongly influenced by his legacy.

Derek Denny-Brown: the man behind the ganglia / Derek Denny-Brown: o homem por detrás dos gânglios

ABSTRACT The authors present an historical review about the main contributions of Professor Derek Denny-Brown to neurology. Some of his achievements include the first description of sensory neuronopathies, and some of the essential textbooks on the function and anatomy of the basal ganglia. In 2016, on the 35th anniversary of his death, modern neurologists are still strongly influenced by his legacy.

RESUMO Os autores apresentam uma revisão histórica sobre as principais contribuições do Professor Derek Denny-Brown à neurologia. Suas realizações incluem a primeira descrição da neuronopatia sensitiva e alguns dos livros fundamentais acerca da função e anatomia dos núcleos da base. Em 2016, ano do seu 35o aniversário de falecimento, os neurologistas atuais ainda são fortemente influenciados pelo seu legado.

Transcultural validation of the ALS-CBS Cognitive Section for the Brazilian population.

Cognitive decline (CD) is common but often under-recognized in ALS due to the scarcity of adequate cognitive screening methods. In this scenario, the Amyotrophic Lateral Sclerosis Cognitive Behavioural Screen (ALS-CBS) is the most investigated instrument and presents high sensitivity to identify CD. Currently, there are no validated cognitive screening tools for ALS patients in the Brazilian population and little is known about the frequency of ALS related CD in the country. We assessed the accuracy of the Brazilian Portuguese version of ALS-CBS Cognitive Section (ALS-CBS-Br) for classifying the cognitive status of Brazilian patients compared to a standard neuropsychological battery, and estimated the prevalence of CD in the Brazilian ALS population. Among 73 initially recruited ALS patients, 49 were included. Twenty-four patients were excluded due to severe motor disability, FTD diagnosis or non-acceptance. Ten healthy controls were also included. Ten ALS patients (20%) were diagnosed with executive dysfunction (ALSci) based on the battery results. ALS-CBS-Br scores were significantly lower in the ALSci group (p < 0.001). The scale accuracy in detecting executive dysfunction was 0.906. Optimal cut-off score was 10/20 (specificity 0.872 and sensitivity 0.900). In conclusion, the ALS-CBS-Br may facilitate the recognition of CD in routine clinical care and complement future studies in our population.

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.

Multimodal MRI-based study in patients with SPG4 mutations.

Mutations in the SPG4 gene (SPG4-HSP) are the most frequent cause of hereditary spastic paraplegia, but the extent of the neurodegeneration related to the disease is not yet known. Therefore, our objective is to identify regions of the central nervous system damaged in patients with SPG4-HSP using a multi-modal neuroimaging approach. In addition, we aimed to identify possible clinical correlates of such damage. Eleven patients (mean age 46.0 ± 15.0 years, 8 men) with molecular confirmation of hereditary spastic paraplegia, and 23 matched healthy controls (mean age 51.4 ± 14.1years, 17 men) underwent MRI scans in a 3T scanner. We used 3D T1 images to perform volumetric measurements of the brain and spinal cord. We then performed tract-based spatial statistics and tractography analyses of diffusion tensor images to assess microstructural integrity of white matter tracts. Disease severity was quantified with the Spastic Paraplegia Rating Scale. Correlations were then carried out between MRI metrics and clinical data. Volumetric analyses did not identify macroscopic abnormalities in the brain of hereditary spastic paraplegia patients. In contrast, we found extensive fractional anisotropy reduction in the corticospinal tracts, cingulate gyri and splenium of the corpus callosum. Spinal cord morphometry identified atrophy without flattening in the group of patients with hereditary spastic paraplegia. Fractional anisotropy of the corpus callosum and pyramidal tracts did correlate with disease severity. Hereditary spastic paraplegia is characterized by relative sparing of the cortical mantle and remarkable damage to the distal portions of the corticospinal tracts, extending into the spinal cord.