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2022 ◽  
Vol 57 ◽  
pp. 1-14
Lucia Carboni ◽  
Aram El Khoury ◽  
Daniela I. Beiderbeck ◽  
Inga D. Neumann ◽  
Aleksander A. Mathé

2022 ◽  
Vol 12 (3) ◽  
pp. 564-568
Ming Lei ◽  
Junjian Zhang ◽  
Dongmei Wu

<sec> <title>Objective:</title> By using amplitude of low-frequency fluctuations (ALFF) we have analyzed activationsin brain regions at different phases in migraineurs. </sec> <sec> <title>Methods:</title> Participants included 41 patients with migraine, 19 in episode and 22 in interictal phase, and 22 controls in the healthy condition. To analyze the brain function of patients and controls, ALFF was used for performing the post-processing in the resting state by scores of Montreal Cognitive Assessment (MoCA) scale, Mini-Mental State Examination (MMSE), Hamilton Anxiety Rating Scale (HAM-A) and Hamilton Depression Rating Scale (HAM-D). </sec> <sec> <title>Results:</title> The comparison between groups of patients with migraine in the episode or interictal phases, and healthy controls showed that both episode and interictal migraine groups had the similar HAM-A and HAM-D scores (P > 0.05), but higher than that in controls (P < 0.01). For ALFF values of Episode and Interictal groups, the Montreal Neurological Institute (MNI) coordinates of the decreased ALFF were (−9, 42, 9), the voxel size = 215, including the bilateral anterior cingulate cortex (ACC), T =−4.15, without significant differences. Patients in Interictal group were with a stronger activation at MNI coordinates (12, 51, 12), in the bilateral ACC, voxel size = 90, T =3.87. </sec> <sec> <title>Conclusion:</title> ACC plays an adaptive, regulatory role in migraine and is related to multiple brain regions, which may mediate activation through descending anti-nociceptive pathways. ACC is related to opioid receptor and glutamate excitatory regulation. </sec>

2022 ◽  
Vol 15 ◽  
Meghan L. Donovan ◽  
Eileen K. Chun ◽  
Yan Liu ◽  
Zuoxin Wang

The socially monogamous prairie vole (Microtus ochrogaster) offers a unique opportunity to examine the impacts of adolescent social isolation on the brain, immune system, and behavior. In the current study, male and female prairie voles were randomly assigned to be housed alone or with a same-sex cagemate after weaning (i.e., on postnatal day 21–22) for a 6-week period. Thereafter, subjects were tested for anxiety-like and depressive-like behaviors using the elevated plus maze (EPM) and Forced Swim Test (FST), respectively. Blood was collected to measure peripheral cytokine levels, and brain tissue was processed for microglial density in various brain regions, including the Nucleus Accumbens (NAcc), Medial Amygdala (MeA), Central Amygdala (CeA), Bed Nucleus of the Stria Terminalis (BNST), and Paraventricular Nucleus of the Hypothalamus (PVN). Sex differences were found in EPM and FST behaviors, where male voles had significantly lower total arm entries in the EPM as well as lower latency to immobility in the FST compared to females. A sex by treatment effect was found in peripheral IL-1β levels, where isolated males had a lower level of IL-1β compared to cohoused females. Post-weaning social isolation also altered microglial density in a brain region-specific manner. Isolated voles had higher microglial density in the NAcc, MeA, and CeA, but lower microglial density in the dorsal BNST. Cohoused male voles also had higher microglial density in the PVN compared to cohoused females. Taken together, these data suggest that post-weaning social housing environments can alter peripheral and central immune systems in prairie voles, highlighting a potential role for the immune system in shaping isolation-induced alterations to the brain and behavior.

Inês Carreira Figueiredo ◽  
Faith Borgan ◽  
Ofer Pasternak ◽  
Federico E. Turkheimer ◽  
Oliver D. Howes

AbstractWhite-matter abnormalities, including increases in extracellular free-water, are implicated in the pathophysiology of schizophrenia. Recent advances in diffusion magnetic resonance imaging (MRI) enable free-water levels to be indexed. However, the brain levels in patients with schizophrenia have not yet been systematically investigated. We aimed to meta-analyse white-matter free-water levels in patients with schizophrenia compared to healthy volunteers. We performed a literature search in EMBASE, MEDLINE, and PsycINFO databases. Diffusion MRI studies reporting free-water in patients with schizophrenia compared to healthy controls were included. We investigated the effect of demographic variables, illness duration, chlorpromazine equivalents of antipsychotic medication, type of scanner, and clinical symptoms severity on free-water measures. Ten studies, including five of first episode of psychosis have investigated free-water levels in schizophrenia, with significantly higher levels reported in whole-brain and specific brain regions (including corona radiata, internal capsule, superior and inferior longitudinal fasciculus, cingulum bundle, and corpus callosum). Six studies, including a total of 614 participants met the inclusion criteria for quantitative analysis. Whole-brain free-water levels were significantly higher in patients relative to healthy volunteers (Hedge’s g = 0.38, 95% confidence interval (CI) 0.07–0.69, p = 0.02). Sex moderated this effect, such that smaller effects were seen in samples with more females (z = −2.54, p < 0.05), but antipsychotic dose, illness duration and symptom severity did not. Patients with schizophrenia have increased free-water compared to healthy volunteers. Future studies are necessary to determine the pathological sources of increased free-water, and its relationship with illness duration and severity.

2022 ◽  
Vol 12 ◽  
Qiong Ma ◽  
Xiudong Shi ◽  
Guochao Chen ◽  
Fengxiang Song ◽  
Fengjun Liu ◽  

Purpose:Neuroimaging elucidations have shown structural and functional brain alterations in HIV-infected (HIV+) individuals when compared to HIV-negative (HIV–) controls. However, HIV− groups used in previous studies were not specifically considered for sexual orientation, which also affects the brain structures and functions. The current study aimed to characterize the brain alterations associated with HIV infection while controlling for sexual orientation.Methods:Forty-three HIV+ and 40 HIV– homosexual men (HoM) were recruited and underwent resting-state MRI scanning. Group differences in gray matter volume (GMV) were assessed using a voxel-based morphometry analysis. Brain regions with the altered GMV in the HIV+ HoM group were then taken as regions of interest in a seed-based analysis to identify altered functional connectivity. Furthermore, the amplitude of low-frequency fluctuation (ALFF) and regional homogeneity values were compared between the two groups to evaluate the HIV-associated functional abnormalities in local brain regions.Results:HIV+ HoM showed significantly increased GMV in the bilateral parahippocampal gyrus and amygdala, and decreased GMV in the right inferior cerebellum, compared with the HIV– HoM. The brain regions with increased GMV were hyper-connected with the left superior cerebellum, right lingual gyrus, and left precuneus in the HIV+ HoM. Moreover, the ALFF values of the right fusiform gyrus, and left parahippocampal gyrus were increased in the HIV+ HoM. The regional homogeneity values of the right anterior cingulate and paracingulate gyri, and left superior cerebellum were decreased in the HIV+ HoM.Conclusion:When the study population was restricted to HoM, HIV+ individuals exhibited structural alterations in the limbic system and cerebellum, and functional abnormalities in the limbic, cerebellum, and visual network. These findings complement the existing knowledge on the HIV-associated neurocognitive impairment from the previous neuroimaging studies by controlling for the potential confounding factor, sexual orientation. Future studies on brain alternations with the exclusion of related factors like sexual orientation are needed to understand the impact of HIV infection on neurocognitive function more accurately.

2022 ◽  
Vol 12 ◽  
Michaela Schuermann ◽  
Yvonne Dzierma ◽  
Frank Nuesken ◽  
Joachim Oertel ◽  
Christian Rübe ◽  

BackgroundNavigated transcranial magnetic stimulation (nTMS) of the motor cortex has been successfully implemented into radiotherapy planning by a number of studies. Furthermore, the hippocampus has been identified as a radiation-sensitive structure meriting particular sparing in radiotherapy. This study assesses the joint protection of these two eloquent brain regions for the treatment of glioblastoma (GBM), with particular emphasis on the use of automatic planning.Patients and MethodsPatients with motor-eloquent brain glioblastoma who underwent surgical resection after nTMS mapping of the motor cortex and adjuvant radiotherapy were retrospectively evaluated. The radiotherapy treatment plans were retrieved, and the nTMS-defined motor cortex and hippocampus contours were added. Four additional treatment plans were created for each patient: two manual plans aimed to reduce the dose to the motor cortex and hippocampus by manual inverse planning. The second pair of re-optimized plans was created by the Auto-Planning algorithm. The optimized plans were compared with the “Original” plan regarding plan quality, planning target volume (PTV) coverage, and sparing of organs at risk (OAR).ResultsA total of 50 plans were analyzed. All plans were clinically acceptable with no differences in the PTV coverage and plan quality metrics. The OARs were preserved in all plans; however, overall the sparing was significantly improved by Auto-Planning. Motor cortex protection was feasible and significant, amounting to a reduction in the mean dose by &gt;6 Gy. The dose to the motor cortex outside the PTV was reduced by &gt;12 Gy (mean dose) and &gt;5 Gy (maximum dose). The hippocampi were significantly improved (reduction in mean dose: ipsilateral &gt;6 Gy, contralateral &gt;4.6 Gy; reduction in maximum dose: ipsilateral &gt;5 Gy, contralateral &gt;5 Gy). While the dose reduction using Auto-Planning was generally better than by manual optimization, the radiated total monitor units were significantly increased.ConclusionConsiderable dose sparing of the nTMS-motor cortex and hippocampus could be achieved with no disadvantages in plan quality. Auto-Planning could further contribute to better protection of OAR. Whether the improved dosimetric protection of functional areas can translate into improved quality of life and motor or cognitive performance of the patients can only be decided by future studies.

2022 ◽  
Vol 15 ◽  
Lavinia Floreani ◽  
Federico Ansaloni ◽  
Damiano Mangoni ◽  
Elena Agostoni ◽  
Remo Sanges ◽  

Transposable elements (TEs) are mobile genetic elements that made up about half the human genome. Among them, the autonomous non-LTR retrotransposon long interspersed nuclear element-1 (L1) is the only currently active TE in mammals and covers about 17% of the mammalian genome. L1s exert their function as structural elements in the genome, as transcribed RNAs to influence chromatin structure and as retrotransposed elements to shape genomic variation in somatic cells. L1s activity has been shown altered in several diseases of the nervous system. Huntington disease (HD) is a dominantly inherited neurodegenerative disorder caused by an expansion of a CAG repeat in the HTT gene which leads to a gradual loss of neurons most prominently in the striatum and, to a lesser extent, in cortical brain regions. The length of the expanded CAG tract is related to age at disease onset, with longer repeats leading to earlier onset. Here we carried out bioinformatic analysis of public RNA-seq data of a panel of HD mouse models showing that a decrease of L1 RNA expression recapitulates two hallmarks of the disease: it correlates to CAG repeat length and it occurs in the striatum, the site of neurodegeneration. Results were then experimentally validated in HttQ111 knock-in mice. The expression of L1-encoded proteins was independent from L1 RNA levels and differentially regulated in time and tissues. The pattern of expression L1 RNAs in human HD post-mortem brains showed similarity to mouse models of the disease. This work suggests the need for further study of L1s in HD and adds support to the current hypothesis that dysregulation of TEs may be involved in neurodegenerative diseases.

2022 ◽  
Vol 9 (1) ◽  
Jan Cimbalnik ◽  
Jaromir Dolezal ◽  
Çağdaş Topçu ◽  
Michal Lech ◽  
Victoria S. Marks ◽  

AbstractData comprise intracranial EEG (iEEG) brain activity represented by stereo EEG (sEEG) signals, recorded from over 100 electrode channels implanted in any one patient across various brain regions. The iEEG signals were recorded in epilepsy patients (N = 10) undergoing invasive monitoring and localization of seizures when they were performing a battery of four memory tasks lasting approx. 1 hour in total. Gaze tracking on the task computer screen with estimating the pupil size was also recorded together with behavioral performance. Each dataset comes from one patient with anatomical localization of each electrode contact. Metadata contains labels for the recording channels with behavioral events marked from all tasks, including timing of correct and incorrect vocalization of the remembered stimuli. The iEEG and the pupillometric signals are saved in BIDS data structure to facilitate efficient data sharing and analysis.

2022 ◽  
Vol 12 ◽  
Auriana Irannejad ◽  
Ganne Chaitanya ◽  
Emilia Toth ◽  
Diana Pizarro ◽  
Sandipan Pati

Accurate mapping of the seizure onset zone (SOZ) is critical to the success of epilepsy surgery outcomes. Epileptogenicity index (EI) is a statistical method that delineates hyperexcitable brain regions involved in the generation and early propagation of seizures. However, EI can overestimate the SOZ for particular electrographic seizure onset patterns. Therefore, using direct cortical stimulation (DCS) as a probing tool to identify seizure generators, we systematically evaluated the causality of the high EI nodes (&gt;0.3) in replicating the patient's habitual seizures. Specifically, we assessed the diagnostic yield of high EI nodes, i.e., the proportion of high EI nodes that evoked habitual seizures. A retrospective single-center study that included post-stereo encephalography (SEEG) confirmed TLE patients (n = 37) that had all high EI nodes stimulated, intending to induce a seizure. We evaluated the nodal responses (true and false responder rate) to stimulation and correlated with electrographic seizure onset patterns (hypersynchronous-HYP and low amplitude fast activity patterns-LAFA) and clinically defined SOZ. The ictogenicity (i.e., the propensity to induce the patient's habitual seizure) of a high EI node was only 44.5%. The LAFA onset pattern had a significantly higher response rate to DCS (i.e., higher evoked seizures). The concordance of an evoked habitual seizure with a clinically defined SOZ with good outcomes was over 50% (p = 0.0025). These results support targeted mapping of SOZ in LAFA onset patterns by performing DCS in high EI nodes to distinguish seizure generators (true responders) from hyperexcitable nodes that may be involved in early propagation.

2022 ◽  
pp. 1-49
Tiberiu Teşileanu ◽  
Siavash Golkar ◽  
Samaneh Nasiri ◽  
Anirvan M. Sengupta ◽  
Dmitri B. Chklovskii

Abstract The brain must extract behaviorally relevant latent variables from the signals streamed by the sensory organs. Such latent variables are often encoded in the dynamics that generated the signal rather than in the specific realization of the waveform. Therefore, one problem faced by the brain is to segment time series based on underlying dynamics. We present two algorithms for performing this segmentation task that are biologically plausible, which we define as acting in a streaming setting and all learning rules being local. One algorithm is model based and can be derived from an optimization problem involving a mixture of autoregressive processes. This algorithm relies on feedback in the form of a prediction error and can also be used for forecasting future samples. In some brain regions, such as the retina, the feedback connections necessary to use the prediction error for learning are absent. For this case, we propose a second, model-free algorithm that uses a running estimate of the autocorrelation structure of the signal to perform the segmentation. We show that both algorithms do well when tasked with segmenting signals drawn from autoregressive models with piecewise-constant parameters. In particular, the segmentation accuracy is similar to that obtained from oracle-like methods in which the ground-truth parameters of the autoregressive models are known. We also test our methods on data sets generated by alternating snippets of voice recordings. We provide implementations of our algorithms at

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