Brain Regions Of Interest Research Articles

Sex and dependence related neuroanatomical differences in regular cannabis users: findings from the ENIGMA Addiction Working Group

Males and females show different patterns of cannabis use and related psychosocial outcomes. However, the neuroanatomical substrates underlying such differences are poorly understood. The aim of this study was to map sex differences in the neurobiology (as indexed by brain volumes) of dependent and recreational cannabis use. We compared the volume of a priori regions of interest (i.e., amygdala, hippocampus, nucleus accumbens, insula, orbitofrontal cortex (OFC), anterior cingulate cortex and cerebellum) between 129 regular cannabis users (of whom 70 were recreational users and 59 cannabis dependent) and 114 controls recruited from the ENIGMA Addiction Working Group, accounting for intracranial volume, age, IQ, and alcohol and tobacco use. Dependent cannabis users, particularly females, had (marginally significant) smaller volumes of the lateral OFC and cerebellar white matter than recreational users and controls. In dependent (but not recreational) cannabis users, there was a significant association between female sex and smaller volumes of the cerebellar white matter and OFC. Volume of the OFC was also predicted by monthly standard drinks. No significant effects emerged the other brain regions of interest. Our findings warrant future multimodal studies that examine if sex and cannabis dependence are specific key drivers of neurobiological alterations in cannabis users. This, in turn, could help to identify neural pathways specifically involved in vulnerable cannabis users (e.g., females with cannabis dependence) and inform individually tailored neurobiological targets for treatment.

Evaluation of Serotonin 5‐HT 1A , 5‐HT 2A , and 5‐HT 2C Receptors and the Serotonin Transporter in an Fmr1 Knockout Mouse Model of Fragile X Syndrome

Fragile X syndrome (FXS)—caused by FMR1 gene silencing—is the leading monogenic cause of intellectual disability and autism spectrum disorder (ASD). Diminished serotonin (5-hydroxytryptamine, 5-HT) synthesis has been reported in ASD. The 5-HT transporter (SERT) and receptors (5-HTRs) have been targeted to manage ASD and FXS symptoms. Serotonergic neurons project to glutamate and GABA neurons expressing 5-HT1ARs, 5-HT2ARs, and 5-HT2CRs that modulate cellular excitation-inhibition which is altered in ASD and FXS. Here, we assessed the expression and function of these 5-HTRs and SERT in adult (P60-180) Fmr1 knockout (KO) mice, a model of FXS, compared to wild type (WT) mice. We performed autoradiography on brain sections using [3H]5-CT for 5-HT1ARs, [3H]Ketanserin for 5-HT2ARs, [3H]Mesulergine for 5-HT2CRs, [3H]Citalopram for SERT, and appropriate non-specific and off-target blocking ligands. Brain regions of interest were chosen and analyzed using ImageJ. Mean pixel intensity from the images was normalized to the mean of background intensity, and non-specific binding was subtracted from total binding to obtain normalized specific binding. Saturation binding assays, using whole brain membrane homogenates, were performed for 5-HT1ARs with [3H]5-CT and SB-269970 to block 5-HT7Rs; WAY-100635 was used to isolate 5-HT1AR specific binding. Behavioral effects of (R)-8-OH-DPAT, (±)-DOI, and lorcaserin were used to probe in vivo functional activity of 5-HT1A, 5-HT2A, and 5-HT2CRs, respectively. Responses to (R)-8-OH-DPAT (1 and 2 mg/kg), including flat body posture, head weaving, straub tail, hind limb abduction, piloerection, tremor, rearing, grooming, and head twitch responses (HTRs), were recorded by two independent observers. Locomotor effects of lorcaserin (1, 3, and 10 mg/kg) were recorded using Noldus Ethovision XT software, and HTRs elicited by (±)-DOI (1 mg/kg) were recorded using a hand-held tally counter. Sex effects were assessed in all tests. Preliminary results suggest that compared to WT males, Fmr1 KO males (N=3 per group) have higher 5-HT1AR expression in lateral septum and frontal cortex, lower 5-HT2AR expression in isocortex layer V, and lower 5-HT2CR expression in anterior olfactory nucleus and nucleus accumbens. Increased 5-HT1AR expression was confirmed by saturation binding analyses (N=6 per group). Male mice of both genotypes had lower 5-HT2CR expression in choroid plexus and caudate putamen (N=3 per group). Behavioral effects of (R)-8-OH-DPAT were significantly more pronounced in both male and female (N=5-7 per group) Fmr1 KO mice, relative to WT mice. A minor decrease in DOI-elicited HTRs was observed in Fmr1 KO males compared to WT males (14 vs. 17, N=8-9 per group). No genotype differences in locomotor activity were observed after lorcaserin administration (N=6 per group). Ongoing studies are assessing SERT expression and in vivo function via autoradiography and the tail suspension test, respectively. This study provides the first observations of perturbations in key 5-HTRs in Fmr1 KO mice, suggesting dysfunctions in the central 5-HT system in FXS.

Brain graph super-resolution using adversarial graph neural network with application to functional brain connectivity.

Brain image analysis has advanced substantially in recent years with the proliferation of neuroimaging datasets acquired at different resolutions. While research on brain image super-resolution has undergone a rapid development in the recent years, brain graph super-resolution is still poorly investigated because of the complex nature of non-Euclidean graph data. In this paper, we propose the first-ever deep graph super-resolution (GSR) framework that attempts to automatically generate high-resolution (HR) brain graphs with N' nodes (i.e., anatomical regions of interest (ROIs)) from low-resolution (LR) graphs with N nodes where N<N'. First, we formalize our GSR problem as a node feature embedding learning task. Once the HR nodes' embeddings are learned, the pairwise connectivity strength between brain ROIs can be derived through an aggregation rule based on a novel Graph U-Net architecture. While typically the Graph U-Net is a node-focused architecture where graph embedding depends mainly on node attributes, we propose a graph-focused architecture where the node feature embedding is based on the graph topology. Second, inspired by graph spectral theory, we break the symmetry of the U-Net architecture by super-resolving the low-resolution brain graph structure and node content with a GSR layer and two graph convolutional network layers to further learn the node embeddings in the HR graph. Third, to handle the domain shift between the ground-truth and the predicted HR brain graphs, we incorporate adversarial regularization to align their respective distributions. Our proposed AGSR-Net framework outperformed its variants for predicting high-resolution functional brain graphs from low-resolution ones. Our AGSR-Net code is available on GitHub at https://github.com/basiralab/AGSR-Net.

Hippocampal and Septal 5-HT1A Receptor Expression in Two Rat Models of Temporal Lobe Epilepsy

Experimental and clinical data suggest an impact of serotonergic signaling on seizure susceptibility and epilepsy-associated psychiatric comorbidities. Previous µPET studies revealed increased binding of the 5-HT1A receptor ligand [18F]MPPF in two rat models with spontaneous recurrent seizures. These findings raised the question whether these alterations are due to altered 5-HT1A receptor expression or a modification of extracellular serotonin concentrations. 5-HT1A receptor expression rates were quantitatively analyzed in rat brain tissue from an electrical and a chemical post-status epilepticus model. Based on the µPET findings, stereological analysis was focused on hippocampal subregions and the septum. Evaluation of 5-HT1A receptor expression in the electrical post-status epilepticus model revealed a decreased optical density in hippocampal CA3 region. In all other brain regions of interest, the analysis demonstrated comparable 5-HT1A receptor expression rates among all experimental groups in the brain regions evaluated. Moreover, 5-HT1A total receptor volume did not differ between groups. A model-specific correlation was demonstrated between 5-HT1A receptor expression and selected seizure and behavioral parameters. In conclusion, analysis in post-status epilepticus models in rats argued against widespread and pronounced alterations in 5-HT1A receptor expression. In view of previous µPET findings, the present data indicate that alterations in in-vivo receptor binding are due to a reduction in extracellular serotonin concentrations rather than changes in receptor density. Correlation analysis points to a possible link between 5-HT1A receptor expression and ictogenesis, seizure termination and behavioral patterns. However, as these findings proved to be model specific, the relevance needs to be further assessed in future studies focusing on other models and species.

Use of high-content imaging to quantify transduction of AAV-PHP viruses in the brain following systemic delivery.

The engineering of the AAV-PHP capsids was an important development for CNS research and the modulation of gene expression in the brain. They cross the blood brain barrier and transduce brain cells after intravenous systemic delivery, a property dependent on the genotype of Ly6a, the AAV-PHP capsid receptor. It is important to determine the transduction efficiency of a given viral preparation, as well as the comparative tropism for different brain cells; however, manual estimation of adeno-associated viral transduction efficiencies can be biased and time consuming. Therefore, we have used the Opera Phenix high-content screening system, equipped with the Harmony processing and analysis software, to reduce bias and develop an automated approach to determining transduction efficiency in the mouse brain. We used R Studio and ‘gatepoints’ to segment the data captured from coronal brain sections into brain regions of interest. C57BL/6J and CBA/Ca mice were injected with an AAV-PHP.B virus containing a green fluorescent protein reporter with a nuclear localization signal. Coronal sections at 600 μm intervals throughout the entire brain were stained with Hoechst dye, combined with immunofluorescence to NeuN and green fluorescent protein to identify all cell nuclei, neurons and transduced cells, respectively. Automated data analysis was applied to give an estimate of neuronal percentages and transduction efficiencies throughout the entire brain as well as for the cortex, striatum and hippocampus. The data from each coronal section from a given mouse were highly comparable. The percentage of neurons in the C57BL/6J and CBA/Ca brains was approximately 40% and this was higher in the cortex than striatum and hippocampus. The systemic injection of AAV-PHP.B resulted in similar transduction rates across the entire brain for C57BL/6J mice. Approximately 10–15% of all cells were transduced, with neuronal transduction efficiencies ranging from 5% to 15%, estimates that were similar across brain regions, and were in contrast to the much more localized transduction efficiencies achieved through intracerebral injection. We confirmed that the delivery of the AAV-PHP.B viruses to the brain from the vasculature resulted in widespread transduction. Our methodology allows the rapid comparison of transduction rates between brain regions producing comparable data to more time-consuming approaches. The methodology developed here can be applied to the automated quantification of any parameter of interest that can be captured as a fluorescent signal.

RADIOMICS BASED SINGLE AND MULTI-CLASS GLIOMA CLASSIFICATION USING SUPPORT VECTOR MACHINE VARIANTS

The common type of primary brain tumor is glioma. The mortality rate of glioma patients is high due to delayed diagnosis, incorrect grading and treatment planning. Traditionally, gliomas were classified into Low Grade (grade-I and grade-II) and High Grade (grade-III and grade-IV). However, World Health Organization has insisted to classify the grades into grade-I(G-I), grade II(G-II), grade III(G-III) and grade IV(G-IV) individually to aid the physicians in clinical decision-making. Although there are limited number of studies reported to differentiate individual grades, the classification accuracy was low. Consequently, in this work single-class (G-II vs. G-III, G-II vs. G-IV and G-III vs. G-IV) and multi-class (G-II vs. G-III+IV, G-III vs. G-II+IV and G-IV vs. G-II+III) analysis was performed using specific region of tumor and whole brain as Regions of Interest(ROI) by extracting radiomic features. The images for this study (N=75) were obtained from The Cancer Imaging Archive. Further, the statistically significant features were used in the classification of individual grades by implementing variants of Support Vector Machine (SVM) algorithm: SVM, Linear-SVM and Least-Squared SVM. Among these, Linear-SVM resulted in the highest classification accuracy (&gt;80%) with average sensitivity, specificity and AUC values of &gt;70%. The comparative analysis of whole brain versus tumor ROI showed that the latter yielded better classification accuracy.

Comparison of [11C]UCB-J and [18F]FDG PET in Alzheimer’s disease: A tracer kinetic modeling study

[11C]UCB-J PET for synaptic vesicle glycoprotein 2 A (SV2A) has been proposed as a suitable marker for synaptic density in Alzheimer’s disease (AD). We compared [11C]UCB-J binding for synaptic density and [18F]FDG uptake for metabolism (correlated with neuronal activity) in 14 AD and 11 cognitively normal (CN) participants. We assessed both absolute and relative outcome measures in brain regions of interest, i.e., K1 or R1 for [11C]UCB-J perfusion, VT (volume of distribution) or DVR to cerebellum for [11C]UCB-J binding to SV2A; and Ki or KiR to cerebellum for [18F]FDG metabolism. [11C]UCB-J binding and [18F]FDG metabolism showed a similar magnitude of reduction in the medial temporal lobe of AD –compared to CN participants. However, the magnitude of reduction of [11C]UCB-J binding in neocortical regions was less than that observed with [18F]FDG metabolism. Inter-tracer correlations were also higher in the medial temporal regions between synaptic density and metabolism, with lower correlations in neocortical regions. [11C]UCB-J perfusion showed a similar pattern to [18F]FDG metabolism, with high inter-tracer regional correlations. In summary, we conducted the first in vivo PET imaging of synaptic density and metabolism in the same AD participants and reported a concordant reduction in medial temporal regions but a discordant reduction in neocortical regions.

Flexible annotation atlas of the mouse brain: combining and dividing brain structures of the Allen Brain Atlas while maintaining anatomical hierarchy

A brain atlas is necessary for analyzing structure and function in neuroimaging research. Although various annotation volumes (AVs) for the mouse brain have been proposed, it is common in magnetic resonance imaging (MRI) of the mouse brain that regions-of-interest (ROIs) for brain structures (nodes) are created arbitrarily according to each researcher’s necessity, leading to inconsistent ROIs among studies. One reason for such a situation is the fact that earlier AVs were fixed, i.e. combination and division of nodes were not implemented. This report presents a pipeline for constructing a flexible annotation atlas (FAA) of the mouse brain by leveraging public resources of the Allen Institute for Brain Science on brain structure, gene expression, and axonal projection. A mere two-step procedure with user-specified, text-based information and Python codes constructs FAA with nodes which can be combined or divided objectively while maintaining anatomical hierarchy of brain structures. Four FAAs with total node count of 4, 101, 866, and 1381 were demonstrated. Unique characteristics of FAA realized analysis of resting-state functional connectivity (FC) across the anatomical hierarchy and among cortical layers, which were thin but large brain structures. FAA can improve the consistency of whole brain ROI definition among laboratories by fulfilling various requests from researchers with its flexibility and reproducibility.

Abstract P324: Your Brain May Be "HOTTER" Than You Think, Results From Phase I Check Brain Temperature Study

Background: Hypothermia is a known neuronal protecting agent and used in post cardiac arrest. However, its use for stroke and brain trauma has not made any progress due to the lack of accurate way of measuring brain temperature. Hence, hypothermic degree and duration for it to be therapeutic is unknown. The phase I Check Brain Temperature Study was to define regional brain temperatures in normal individuals via MRI thermometry. The established brain temperature map can be used as the baseline to provide therapeutic hypothermia. Method: Temperatures of 5 regions of interest (ROI) of brain (frontal lobe, thalamus, hypothalamus, occipital lobe and cerebellum) were measured in 10 healthy individuals by using proton resonance frequency MRI spectroscopy single voxel method. The scanning protocol include a whole brain anatomical images, (3DFSPGR : TR/TE=150/3.9ms, FOV=24cm,matrix=256x256, slice thickness =1 mm.) and spectroscopy PRESS (TR/TE=1500/144 ms, 8 nex, 2 x 2 x 2 cm^3) on a GE 3T scanner. Ten right handed men (18&lt;age&lt;80) were recruited and their oral and tympanic temperatures were monitored. Average whole head temperature=average of oral temp+tympanic temp and average brain temp=average of temp of 5 regions of interest. Two tails, paired t-test used to compare temps between subjects and ROIs. Results: Average temperature differences between brain (38.2 °C) and head (36.5 °C) is 1.8 °C (p&lt; 0.0000002). Thalamus has the highest temperature among all ROIs in brain. Brain temperature &gt; oral temperature &gt; tympanic temperature. Conclusion: Brain temperatures may not correlate to body temperatures and there is a regional difference. Our finding will be used as the baseline brain temperature map when hypothermia is applied in patients with hemisphere stroke in the phase II study.

Concurrent brain parcellation and connectivity estimation via co-clustering of resting state fMRI data: A novel approach.

Connectional topography mapping has been gaining widespread attention in human brain imaging studies. However, existing methods might not effectively utilize the information from neuroimaging data, thus hindering the understanding of the underlying connectional organization in the brain and uncovering the optimal clustering number from the data. In this study, we propose a novel method for the automated construction of inherent functional connectivity topography in a data‐driven manner by leveraging the power of co‐clustering‐based on resting state fMRI (rs‐fMRI) data. We propose the co‐clustering‐based method not only for concurrently parcellating two interconnected brain regions of interest (ROIs) under consideration into functionally homogenous subregions, but also for estimating the connectivity between these subregions from the two brain ROIs. In particular, we first model the connectional topography mapping as a co‐clustering‐based bipartite graph partitioning problem for constructing the inherent functional connectivity topography between the two interconnected brain ROIs. We also adopt an objective criterion, that is, silhouette width index measuring clustering quality, for determining the optimal number of clusters. The proposed method has been validated for mapping thalamocortical connectional topography based on rs‐fMRI data of 57 subjects. Validation results have demonstrated that our method identified the optimal solution with five pairs of mutually connected subregions of the thalamocortical system from the rs‐fMRI data, and could yield more meaningful, interpretable, and homogenous connectional topography than existing methods. The proposed method was further validated by the high symmetry of the mapped connectional topography between two hemispheres.

Neuroendocrine and neuroimmune responses in male and female rats: evidence for functional immaturity of the neuroimmune system during early adolescence.

Adolescence is a developmental period characterized by rapid behavioral and physiological changes, including enhanced vulnerability to stress. Recent studies using rodent models of adolescence have demonstrated age differences in neuroendocrine responses and blunted neuroimmune responding to pharmacological challenges. The present study was designed to test whether this neuroimmune insensitivity would generalize to a non-pharmacological stress challenge. Male and female adolescent (P29-33) and adult (P70-80) Sprague Dawley rats were exposed to intermittent footshock for one-, two-, or two-hours+recovery. Plasma corticosterone and progesterone levels as well as gene expression of several cytokines and c-Fos gene expression in the paraventricular nucleus of the hypothalamus (PVN), the medial amygdala (MeA), and the ventral hippocampus (vHPC) were analyzed. The results of the present study demonstrated differences in response to footshock, with these differences dependent on age, sex, and brain region of interest. Adult males and females demonstrated time-dependent increases in IL-1β and IL-1R2 in the PVN, with these changes not evident in adolescent males and substantially blunted in adolescent females. TNFα expression was decreased in all regions of interest, with adults demonstrating more suppression relative to adolescents and age differences more apparent in males than in females. IL-6 expression was affected by footshock predominantly in the vHPC of adolescent and adult males and females, with females demonstrating prolonged elevation of IL-6 gene expression. In summary, central cytokine responses to acute stressor exposure are blunted in adolescent rats, with the most pronounced immaturity evident for the brain IL-1 signaling system.

Reforming Sectarian Beliefs in Iraq: Winning the Peace

Sectarian violence continues in Iraq affecting regional and world security. Neuroscience techniques are used to assess the mentalizing process and counter-arguing in response to videos designed to prevent extremist radicalization. Measurement of neural activity in brain Regions of Interest (ROI) assists identification of messages which can promote favorable behavior. Activation of the Medial Prefrontal Cortex (MPFC) is associated with message adoption and behavior change. Public Service Announcements (PSAs) have not been effective in reducing violence in Iraq. This study demonstrates that the four PSAs investigated in this study do not activate the MPFC. The RLPFC is a brain ROI associated with counter-arguing and message resistance. This study demonstrates that reduction in activity in the Right Lateral Prefrontal Cortex (RLPFC) is associated with decreased sectarianism. Engagement was measured and is associated with activity in the frontal pole regions.We introduce Functional Near-infrared Spectroscopy (fNIRS) to measure the neural activity of highly sectarian Iraqis in response to these anti-sectarian messages. Neural activity was measured while viewing three PSAs and a fourth unpublished video. All four videos are intended to reduce sectarianism. A novel sectarianism scale is introduced to measure sectarian beliefs before and after the messages. This sectarian scale has high internal consistency as measured by Cronbach’s alpha. Measured activation of brain ROIs are correlated with changes in the sectarian scale. Twelve Sunni and twelve Shi’a Iraqis participated in the study. Subjects were shown the four videos in randomized order, while equipped with a fNIRS neural imaging device. All four videos produced significant engagement. None of the videos reduced sectarianism nor caused brain activation of adoption. This is consistent with the widely held Iraqi public perception that the PSAs are ineffective. Only one video, which was un-published, caused reduced sectarian beliefs. This un-published fourth video was associated with decreased counter-arguing. Counter-arguing is associated with message resistance.

Bi-channel image registration and deep-learning segmentation (BIRDS) for efficient, versatile 3D mapping of mouse brain.

We have developed an open-source software called bi-channel image registration and deep-learning segmentation (BIRDS) for the mapping and analysis of 3D microscopy data and applied this to the mouse brain. The BIRDS pipeline includes image preprocessing, bi-channel registration, automatic annotation, creation of a 3D digital frame, high-resolution visualization, and expandable quantitative analysis. This new bi-channel registration algorithm is adaptive to various types of whole-brain data from different microscopy platforms and shows dramatically improved registration accuracy. Additionally, as this platform combines registration with neural networks, its improved function relative to the other platforms lies in the fact that the registration procedure can readily provide training data for network construction, while the trained neural network can efficiently segment-incomplete/defective brain data that is otherwise difficult to register. Our software is thus optimized to enable either minute-timescale registration-based segmentation of cross-modality, whole-brain datasets or real-time inference-based image segmentation of various brain regions of interest. Jobs can be easily submitted and implemented via a Fiji plugin that can be adapted to most computing environments.

Intrinsic, dynamic and effective connectivity among large-scale brain networks modulated by oxytocin

The neuropeptide oxytocin is a key modulator of social-emotional behavior and its intranasal administration can influence the functional connectivity of brain networks involved in the control of attention, emotion and reward reported in humans. However, no studies have systematically investigated the effects of oxytocin on dynamic or directional aspects of functional connectivity. The present study employed a novel computational framework to investigate these latter aspects in 15 oxytocin-sensitive regions using data from randomized placebo-controlled between-subject resting state functional MRI studies incorporating 200 healthy subjects. In order to characterize the temporal dynamics, the ‘temporal state’ was defined as a temporal segment of the whole functional MRI signal which exhibited a similar functional interaction pattern among brain regions of interest. Results showed that while no significant effects of oxytocin were found on brain temporal state related characteristics (including temporal state switching frequency, probability of transitions between neighboring states, and averaged dwell time on each state) oxytocin extensively (n = 54 links) modulated effective connectivity among the 15 regions. The effects of oxytocin were primarily characterized by increased effective connectivity both between and within emotion, reward, salience, attention and social cognition processing networks and their interactions with the default mode network. Top-down control over emotional processing regions such as the amygdala was particularly affected. Oxytocin also increased effective homotopic interhemispheric connectivity in almost all these regions. Additionally, the effects of oxytocin on effective connectivity were sex-dependent, being more extensive in males. Overall, these findings suggest that modulatory effects of oxytocin on both within- and between-network interactions may underlie its functional influence on social-emotional behaviors, although in a sex-dependent manner. These findings may be of particular relevance to potential therapeutic use of oxytocin in psychiatric disorders associated with social dysfunction, such as autism spectrum disorder and schizophrenia, where directionality of treatment effects on causal interactions between networks may be of key importance .

Associations between Traumatic Brain Injury, Drug Abuse, Alcohol Use, Adverse Childhood Events, and Aggression Levels in Individuals with Foster Care History.

Nearly 50,000 Canadian children live in foster care. Compared with their peers, foster children experience greater independence and decreased guidance, predisposing them to harmful exposures such as traumatic brain injury (TBI), illicit drugs, and alcohol. Foster children also report a higher level of childhood abuse compared with the general population. This study aimed to: 1) investigate substance/alcohol use disorder, adverse childhood events (ACE), TBI, aggression levels, and the difference between normalized percentages of brain regions of interest (ROIs) in a sample of Canadian youths with and without foster care history; 2) determine the prevalence of substance/alcohol use disorder, ACE, and aggression levels within individuals with foster care history when stratified by likelihood of TBI; and 3) determine the significant correlates of elevated aggression levels within this population. Participants completed standardized questionnaires that measured the prevalence of TBI, substance and alcohol use disorder, ACE, and aggression. Magnetic resonance imaging (MRI) was used to measure differences in brain ROI. Regression and network analysis were used to study interactions between variables. Seventy-four participants (51 individuals with foster care history and 23 age-matched controls from the general population) completed standardized questionnaires. Fifty-five of these individuals (39 foster participants and 16 controls) underwent brain MRI. Foster participants had higher prevalence of substance use disorder (p < 0.001), alcohol use disorder (p = 0.003), ACE (p < 0.001), and elevated aggression levels (p < 0.001) than healthy controls. No significant difference was found among brain ROI. The prevalence of TBI in foster participants was 65%. Foster participants with moderate or high likelihood of TBI exposure had higher levels of drug use and aggression than those with no or low likelihood of exposure. Brain volumes were not associated with substance/alcohol use disorder or ACE. No significant associations were found between aggression levels and the studied variables.

Resistance exercise improves cognitive and brain health in overweight older adults

AbstractBackgroundApproximately 50% of Canadian older adults over the age of 60 are overweight or obese (based on body mass index; BMI). Individuals with high BMI (≥25) often experience cognitive and brain deficits (e.g., impaired memory, cortical atrophy, reduced neural activation), and are at high risk of dementia. One promising lifestyle intervention that may improve these deficits is exercise. For example, 6 months of aerobic training has been found to improve cognitive and brain function in overweight older adults, however studies examining whether resistance training (RT) can produce comparable results in this population is limited.MethodWe conducted a 6‐month, thrice‐weekly randomized controlled trial of RT in overweight older adults. Twenty‐four participants aged 60‐80 (sedentary; BMI ≥25) were randomized into one of two groups: 1) progressive resistance (weight) training, or 2) balance and tone (BAT; control; stretching exercises). At pre‐ and post‐intervention (0 and 6 months, respectively), we measured associative memory performance during functional MRI, and obtained high resolution T1 weighted structural images from a 3T scanner.ResultSix months of RT showed significant improvements in memory performance (6.38% reduced error rate) compared to BAT. Similarly, structural imaging showed increased hippocampal volume for RT (+0.04%) as well as increased percent signal change (neural activation) in memory‐related brain regions of interest, including the hippocampus, parahippocampal gyrus, lingual gyrus, and medial temporal gyrus, suggesting improved functional brain health overtime.ConclusionOverall, our findings offer a feasible, cost‐efficient lifestyle intervention strategy to improve cognitive and brain health in overweight older adults.

Cortical hypometabolism associated with cognitive impairment of multiple system atrophy

IntroductionCognitive impairment is not uncommon in patients with multiple system atrophy (MSA). This study investigated the cortical metabolic changes of MSA and the cortical structure associated with cognitive impairment. MethodsThe study included probable/definite MSA patients who underwent fluorodeoxyglucose positron emission tomography and cognitive evaluation based on mini-mental status examination (MMSE). Cerebral metabolism of the entire MSA patients (n = 88) was compared with healthy controls (n = 19) by voxel-wise statistical parametric mapping. Eight brain regions of interest (ROIs) were selected accordingly: the dorsolateral prefrontal, medial superior frontal, insular, posterior parietal, precuneus, lateral temporal, medial temporal, and posterior cingulate regions. Using validated population-based norms, MSA patients were divided by MMSE z-scores into MSA with cognitive dysfunction (MSA-D, n = 30) and without cognitive dysfunction (MSA-ND, n = 58). Regional metabolism of the selected ROIs was compared between the MSA-D and MSA-ND groups by logistic regression models. Correlations between the regional metabolism of the selected ROIs and MMSE z-scores were analyzed with a linear regression model. ResultsVoxel-wise analysis showed hypometabolism in the frontal, temporal, parietal, and limbic areas in MSA patients than in controls. ROI-based comparisons showed that metabolism in the posterior cingulate (P = 0.006) and medial temporal (P = 0.039) regions was significantly lower in the MSA-D than in the MSA-ND group. The degree of posterior cingulate metabolism correlated significantly with MMSE z-score (P = 0.023). ConclusionsMSA shows fronto-temporo-parietal cortical involvement. Hypometabolism of the limbic regions is associated with cognitive impairment in MSA.

Mind-body (hypnotherapy) treatment of women with urgency urinary incontinence: changes in brain attentional networks

Prior study of patients with urgency urinary incontinence by functional magnetic resonance imaging showed altered function in areas of the brain associated with interoception and salience and with attention. Our randomized controlled trial of hypnotherapy for urgency urinary incontinence demonstrated marked improvement in urgency urinary incontinence symptoms at 2 months. A subsample of these women with urgency urinary incontinence underwent functional magnetic resonance imaging before and after treatment. This study aimed to determine if hypnotherapy treatment of urgency urinary incontinence compared with pharmacotherapy was associated with altered brain activation or resting connectivity on functional magnetic resonance imaging. A subsample of women participating in a randomized controlled trial comparing hypnotherapy vs pharmacotherapy for treatment of urgency urinary incontinence was evaluated with functional magnetic resonance imaging. Scans were obtained pretreatment and 8 to 12 weeks after treatment initiation. Brain activation during bladder filling and resting functional connectivity with an empty and partially filled bladder were assessed. Brain regions of interest were derived from those previously showing differences between healthy controls and participants with untreated urgency urinary incontinence in our prior work and included regions in the interoceptive and salience, ventral attentional, and dorsal attentional networks. After treatment, participants in both groups demonstrated marked improvement in incontinence episodes (P<.001). Bladder-filling task functional magnetic resonance imaging data from the combined groups (n=64, 30 hypnotherapy, 34 pharmacotherapy) demonstrated decreased activation of the left temporoparietal junction, a component of the ventral attentional network (P<.01) compared with baseline. Resting functional connectivity differed only with the bladder partially filled (n=54). Compared with pharmacotherapy, hypnotherapy participants manifested increased functional connectivity between the anterior cingulate cortex and the left dorsolateral prefrontal cortex, a component of the dorsal attentional network (P<.001). Successful treatment of urgency urinary incontinence with both pharmacotherapy and hypnotherapy was associated with decreased activation of the ventral (bottom-up) attentional network during bladder filling. This may be attributable to decreased afferent stimuli arising from the bladder in the pharmacotherapy group. In contrast, decreased ventral attentional network activation associated with hypnotherapy may be mediated by the counterbalancing effects of the dorsal (top-down) attentional network.

Adversarial brain multiplex prediction from a single brain network with application to gender fingerprinting

Brain connectivity networks, derived from magnetic resonance imaging (MRI), non-invasively quantify the relationship in function, structure, and morphology between two brain regions of interest (ROIs) and give insights into gender-related connectional differences. However, to the best of our knowledge, studies on gender differences in brain connectivity were limited to investigating pairwise (i.e., low-order) relationships across ROIs, overlooking the complex high-order interconnectedness of the brain as a network. A few recent works on neurological disorders addressed this limitation by introducing the brain multiplex which is composed of a source network intra-layer, a target intra-layer, and a convolutional interlayer capturing the high-level relationship between both intra-layers. However, brain multiplexes are built from at least two different brain networks hindering their application to connectomic datasets with single brain networks (e.g., functional networks). To fill this gap, we propose Adversarial Brain Multiplex Translator (ABMT), the first work for predicting brain multiplexes from a source network using geometric adversarial learning to investigate gender differences in the human brain. Our framework comprises: (i) a geometric source to target network translator mimicking a U-Net architecture with skip connections, (ii) a conditional discriminator which distinguishes between predicted and ground truth target intra-layers, and finally (iii) a multi-layer perceptron (MLP) classifier which supervises the prediction of the target multiplex using the subject class label (e.g., gender). Our experiments on a large dataset demonstrated that predicted multiplexes significantly boost gender classification accuracy compared with source networks and unprecedentedly identify both low and high-order gender-specific brain multiplex connections. Our ABMT source code is available on GitHub at https://github.com/basiralab/ABMT.

Alzheimer’s disease classification using features extracted from nonsubsampled contourlet subband-based individual networks

Morphological networks constructed with structural magnetic resonance imaging (sMRI) images have been widely investigated by exploring interregional alterations of different brain regions of interest (ROI) in the spatial domain for Alzheimer’s disease (AD) classification. However, few attentions are attracted to construct a subband-based individual network with the sMRI image in the frequency domain. In order to verify the feasibility of constructing individual networks with subbands and extract features from the subband-based individual network for AD classification, in this study, we propose a novel method to capture correlations of the abnormal energy distribution patterns related to AD by constructing nonsubsampled contourlet subband-based individual networks (NCSINs) in the frequency domain. Specifically, a 2-dimensional representation of the preprocessed sMRI image is firstly reshaped by downsampling and reconstruction steps. Then, the nonsubsampled contourlet transform is performed on the 2-dimensional representation to obtain directional subbands, and each directional subband at one scale is described by a column energy feature vector (CV) regarded as a node of the NCSIN. Subsequently, edge between any two nodes is weighted with connection strength (CS). Finally, the concatenation of node and edge features of the NCSINs at different scales is used as a network feature of the sMRI image for AD classification. Meanwhile, the support vector machine (SVM) classifier with a radial basis function (RBF) kernel is applied for categorizing 680 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. Experimental results demonstrate that it is feasible to construct the subband-based individual network in the frequency domain and also show that our NCSIN method outperforms five other state-of-the-art approaches.