Individual Brain Research Articles

Neural population dynamics underlying evidence accumulation in multiple rat brain regions.

Accumulating evidence to make decisions is a core cognitive function. Previous studies have tended to estimate accumulation using either neural or behavioral data alone. Here we develop a unified framework for modeling stimulus-driven behavior and multi-neuron activity simultaneously. We applied our method to choices and neural recordings from three rat brain regions - the posterior parietal cortex (PPC), the frontal orienting fields (FOF), and the anterior-dorsal striatum (ADS) - while subjects performed a pulse-based accumulation task. Each region was best described by a distinct accumulation model, which all differed from the model that best described the animal's choices. FOF activity was consistent with an accumulator where early evidence was favored while the ADS reflected near perfect accumulation. Neural responses within an accumulation framework unveiled a distinct association between each brain region and choice. Choices were better predicted from all regions using a comprehensive, accumulation-based framework and different brain regions were found to differentially reflect choice-related accumulation signals: FOF and ADS both reflected choice but ADS showed more instances of decision vacillation. Previous studies relating neural data to behaviorally-inferred accumulation dynamics have implicitly assumed that individual brain regions reflect the whole-animal level accumulator. Our results suggest that different brain regions represent accumulated evidence in dramatically different ways and that accumulation at the whole-animal level may be constructed from a variety of neural-level accumulators.

Organization of Work on Collecting an Empirical Base for Clarifying the Biological Criteria of Sanity, Limited Sanity, and Insanity (Pilot Project)

The science of criminal law and forensic psychiatry do not draw clear boundaries between the biological criteria of sanity, limited sanity, and insanity. The paper is devoted to the consideration of the prospects for using modern achievements of neuroscience to clarify the boundaries of biological criteria of sanity, limited sanity, and insanity. The paper provides information on the current state of development of neuroscience in terms of research using neuroimaging methods of the brain of individuals committing criminal offenses. The feasibility of conducting relevant research in Russia is substantiated and an option for organizing such work in the form of a pilot project is proposed. In particular, it is proposed to create a single information database, which is supposed to reflect brief information about persons who have committed criminal acts, about the acts they are accused of, and the results of neuroimaging of the brains of these persons. Several stages of organizing work on collecting an empirical base to clarify the biological criteria of sanity, limited sanity, and insanity are identified and described. Particular attention is given to the issue of the legality of compulsory neuroimaging studies in relation to persons who have committed criminal offences.

Predicting tremor improvement after MRgFUS thalamotomy in essential tremor from preoperative spontaneous brain activity: A machine learning approach

Magnetic resonance-guided focused ultrasound surgery (MRgFUS) thalamotomy is an emerging technique for medication-refractory essential tremor (ET), but with variable outcomes. This study used pattern regression analysis to identify brain signatures predictive of tremor improvements. Fifty-four ET patients (mean age = 63.06 years, standard deviation (SD) = 10.55 years, 38 males) underwent unilateral MRgFUS thalamotomy and were scanned for resting-state functional magnetic resonance imaging (rs-fMRI). Seventy-four healthy controls (mean age = 58.09 years, SD = 10.30 years, 38 males) were recruited for comparison. Tremor responses at 12 months posttreatment were evaluated by the Clinical Rating Scale for Tremor. The fractional amplitude of low-frequency fluctuations (fALFF) was calculated from rs-fMRI data. Two-sample t-test was used to generate a disease-specific mask, within which Multivariate Kernel Ridge Regression analyses were conducted. Predicted and actual clinical scores were compared using Pearson’s correlation coefficient (r) and normalized mean squared error (Norm. MSE). Permutation test and leave-one-out strategy were applied for results validation. KRR identified fALFF patterns that significantly predicted the hand tremor improvement (r = 0.23, P = 0.025; Norm. MSE = 0.05, P = 0.026) and the postural tremor improvement (r = 0.28, P = 0.025; Norm. MSE = 0.06, P = 0.023), but not action tremor improvement. Lobule VI of right cerebellum (Cerebelum_6_R), right superior occipital gyrus (Occipital_Sup_R) and lobule X of vermis (Vermis_10) contributed most for hand tremor prediction (normalized weights (NW): 2.77%, 2.40%, 2.34%) while Vermis_10, left supplementary motor area (Supp_Motor_Area_L) and right hippocampus (Hippocampus_R) for postural tremor prediction (NW: 2.69%, 2.12%, 2.05%). The low contributing NW of the individual brain regions suggested that the fALFF pattern as a whole is an overall predicting feature. Preoperative fALFF pattern predicts tremor benefits induced by MRgFUS thalamotomy. ClinicalTrials.gov number: NCT04570046.

Precision fMRI and cluster-failure in the individual brain.

Advances in neuroimaging acquisition protocols and denoising techniques, along with increasing magnetic field strengths, have dramatically improved the temporal signal-to-noise ratio (tSNR) in functional magnetic resonance imaging (fMRI). This permits spatial resolution with submillimeter voxel sizes and ultrahigh temporal resolution and opens a route toward performing precision fMRI in the brains of individuals. Yet ultrahigh spatial and temporal resolution comes at a cost: it reduces tSNR and, therefore, the sensitivity to the blood oxygen level-dependent (BOLD) effect and other functional contrasts across the brain. Here we investigate the potential of various smoothing filters to improve BOLD sensitivity while preserving the spatial accuracy of activated clusters in single-subject analysis. We introduce adaptive-weight smoothing with optimized metrics (AWSOM), which addresses this challenge extremely well. AWSOM employs a local inference approach that is as sensitive as cluster-corrected inference of data smoothed with large Gaussian kernels, but it preserves spatial details across multiple tSNR levels. This is essential for examining whole-brain fMRI data because tSNR varies across the entire brain, depending on the distance of a brain region from the receiver coil, the type of setup, acquisition protocol, preprocessing, and resolution. We found that cluster correction in single subjects results in inflated family-wise error and false positive rates. AWSOM effectively suppresses false positives while remaining sensitive even to small clusters of activated voxels. Furthermore, it preserves signal integrity, that is, the relative activation strength of significant voxels, making it a valuable asset for a wide range of fMRI applications. Here we demonstrate these features and make AWSOM freely available to the research community for download.

MAPT mutations associated with familial tauopathies lead to formation of conformationally distinct oligomers that have cross-seeding ability.

The microtubule associated protein, tau, is implicated in a multitude of neurodegenerative disorders that are collectively termed as tauopathies. These disorders are characterized by the presence of tau aggregates within the brain of afflicted individuals. Mutations within the MAPT gene that encodes the tau protein form the genetic backdrop for familial forms of tauopathies, such as frontotemporal dementia (FTD), but the molecular consequences of such alterations and their pathological effects are unclear. We sought to investigate the conformational properties of the aggregates of three tau mutants: A152T, P301L, and R406W, all implicated within FTD, and compare them to those of the native form (WT-Tau 2N4R). Our immunochemical analysis reveals that mutants and WT tau oligomers exhibit similar affinity for conformation-specific antibodies but have distinct morphology and secondary structure. Additionally, these oligomers possess different dye-binding properties and varying sensitivity to proteolytic processing. These results point to conformational variety among them. We then tested the ability of the mutant oligomers to cross-seed the aggregation of WT tau monomer. Using similar array of experiments, we found that cross-seeding with mutant aggregates leads to the formation of conformationally unique WT oligomers. The results discussed in this paper provide a novel perspective on the structural properties of oligomeric forms of WT tau 2N4R and its mutant, along with shedding some light on their cross-seeding behavior.

Novel Monoclonal Antibody Specific toward Amyloid-β Binds to a Unique Epitope within the N-Terminal Region.

Amyloid-β (Aβ) deposition throughout the neuroaxis is a classical hallmark of several neurodegenerative diseases, most notably Alzheimer's disease (AD). Aβ peptides of varied length and diverse structural conformations are deposited within the parenchyma and vasculature in the brains of individuals with AD. Neuropathologically, Aβ pathology can be assessed using antibodies to label and characterize their features, which in turn leads to a more extensive understanding of the pathological process. In the present study, we generated a novel monoclonal antibody, which we found to be specific for the N-terminal region of Aβ. This antibody reacted to amyloid precursor protein expressed in cultured cells and labels Aβ plaques and cerebral amyloid angiopathy in brain tissue from a mouse model of amyloidosis as well as post-mortem brain tissue from patients diagnosed with AD. This highly specific novel antibody will serve as a unique tool for future studies investigating Aβ deposition in novel mouse models and cross-sectional studies using post-mortem human tissue.

Proximity analysis of native proteomes reveals phenotypic modifiers in a mouse model of autism and related neurodevelopmental conditions

One of the main drivers of autism spectrum disorder is risk alleles within hundreds of genes, which may interact within shared but unknown protein complexes. Here we develop a scalable genome-editing-mediated approach to target 14 high-confidence autism risk genes within the mouse brain for proximity-based endogenous proteomics, achieving the identification of high-specificity spatial proteomes. The resulting native proximity proteomes are enriched for human genes dysregulated in the brain of autistic individuals, and reveal proximity interactions between proteins from high-confidence risk genes with those of lower-confidence that may provide new avenues to prioritize genetic risk. Importantly, the datasets are enriched for shared cellular functions and genetic interactions that may underlie the condition. We test this notion by spatial proteomics and CRISPR-based regulation of expression in two autism models, demonstrating functional interactions that modulate mechanisms of their dysregulation. Together, these results reveal native proteome networks in vivo relevant to autism, providing new inroads for understanding and manipulating the cellular drivers underpinning its etiology.

Biomarker-Based Precision Therapy for Alzheimer's Disease: Multidimensional Evidence Leading a New Breakthrough in Personalized Medicine.

(1) Background: Alzheimer's disease (AD) is a worldwide neurodegenerative disorder characterized by the buildup of abnormal proteins in the central nervous system and cognitive decline. Since no radical therapy exists, only symptomatic treatments alleviate symptoms temporarily. In this review, we will explore the latest advancements in precision medicine and biomarkers for AD, including their potential to revolutionize the way we diagnose and treat this devastating condition. (2) Methods: A literature search was performed combining the following Medical Subject Heading (MeSH) terms on PubMed: "Alzheimer's disease", "biomarkers", "APOE", "APP", "GWAS", "cerebrospinal fluid", "polygenic risk score", "Aβ42", "τP-181", " p-tau217", "ptau231", "proteomics", "total tau protein", and "precision medicine" using Boolean operators. (3) Results: Genome-wide association studies (GWAS) have identified numerous genetic variants associated with AD risk, while a transcriptomic analysis has revealed dysregulated gene expression patterns in the brains of individuals with AD. The proteomic and metabolomic profiling of biological fluids, such as blood, urine, and CSF, and neuroimaging biomarkers have also yielded potential biomarkers of AD that could be used for the early diagnosis and monitoring of disease progression. (4) Conclusion: By leveraging a combination of the above biomarkers, novel ultrasensitive immunoassays, mass spectrometry methods, and metabolomics, researchers are making significant strides towards personalized healthcare for individuals with AD.

Transcranial focused ultrasound modulates visual thalamus in a nonhuman primate model.

The thalamus plays a pivotal role as a neural hub, integrating and distributing visual information to cortical regions responsible for visual processing. Transcranial focused ultrasound (tFUS) has emerged as a promising non-invasive brain stimulation technology, enabling modulation of neural circuits with high spatial precision. This study investigates the tFUS neuromodulation at visual thalamus and characterizes the resultant effects on interconnected visual areas in a nonhuman primate model. Experiments were conducted on a rhesus macaque trained in a visual fixation task, combining tFUS stimulation with simultaneous scalp electroencephalography (EEG) and intracranial recordings from area V4, a region closely linked to the thalamus. Ultrasound was delivered through a 128-element random array ultrasound transducer operating at 700 kHz, with the focus steered onto the pulvinar of the thalamus based on neuroanatomical atlas and individual brain model. EEG source imaging revealed localized tFUS-induced activities in the thalamus, midbrain, and visual cortical regions. Critically, tFUS stimulation of the pulvinar can elicit robust neural responses in V4 without visual input, manifested as significant modulations in local field potentials, elevated alpha and gamma power, corroborating the functional thalamocortical connectivity. Furthermore, the tFUS neuromodulatory effects on visually-evoked V4 activities were region-specific within the thalamus and dependent on ultrasound pulse repetition frequency. This work provides direct electrophysiological evidence demonstrating the capability of tFUS in modulating the visual thalamus and its functional impact on interconnected cortical regions in a large mammalian model, paving the way for potential investigations for tFUS treating visual, sensory, and cognitive impairments.

FC-HGNN: A heterogeneous graph neural network based on brain functional connectivity for mental disorder identification

Rapid and accurate diagnosis of mental disorders has long been an essential challenge in clinical medicine. Due to the advantage in addressing non-Euclidean structures, graph neural networks have been increasingly used to study brain networks. Among the existing methods, the population graph models have achieved high predictive accuracy by considering intersubject relationships but weak interpretability limits its clinical applicability. The individual graph approach models functional brain networks and identifies abnormal brain regions that cause diseases but has poor accuracy. To address these issues, we propose a heterogeneous graph neural network based on brain functional connectivity (FC-HGNN), which is an end-to-end model with a two-stage process. In the first phase, the brain connectomic graph is used to extract individual brain features. An integrated intrahemispheric and interhemispheric convolutional graph layer is used to learn brain region features, and a local–global dual-channel pooling layer is used to identify biomarkers. In the second stage, a heterogeneous population graph is constructed based on sex and the fusion of imaging and non-imaging data from subjects. The feature embeddings of same-sex and opposite-sex neighbours are learned separately according to a hierarchical feature aggregation approach. Subsequently, they are adaptively fused to generate the final node embedding, which is then utilized for obtaining classification predictions. The cross-validation and transduction learning results show that FC-HGNN achieves state-of-the-art performance in classification prediction experiments using two public datasets. Moreover, FC-HGNN identifies crucial biomarker regions relevant for disease classification, aligning with existing studies and exhibiting outstanding predictive performance on actual clinical data. The code is available at https://github.com/Guuuu11/FC-HGNN_Pytorch.

Structure-function coupling in macroscale human brain networks.

Precisely how the anatomical structure of the brain gives rise to a repertoire of complex functions remains incompletely understood. A promising manifestation of this mapping from structure to function is the dependency of the functional activity of a brain region on the underlying white matter architecture. Here, we review the literature examining the macroscale coupling between structural and functional connectivity, and we establish how this structure-function coupling (SFC) can provide more information about the underlying workings of the brain than either feature alone. We begin by defining SFC and describing the computational methods used to quantify it. We then review empirical studies that examine the heterogeneous expression of SFC across different brain regions, among individuals, in the context of the cognitive task being performed, and over time, as well as its role in fostering flexible cognition. Last, we investigate how the coupling between structure and function is affected in neurological and psychiatric conditions, and we report how aberrant SFC is associated with disease duration and disease-specific cognitive impairment. By elucidating how the dynamic relationship between the structure and function of the brain is altered in the presence of neurological and psychiatric conditions, we aim to not only further our understanding of their aetiology but also establish SFC as a new and sensitive marker of disease symptomatology and cognitive performance. Overall, this Review collates the current knowledge regarding the regional interdependency between the macroscale structure and function of the human brain in both neurotypical and neuroatypical individuals.

Somatic nuclear mitochondrial DNA insertions are prevalent in the human brain and accumulate over time in fibroblasts.

The transfer of mitochondrial DNA into the nuclear genomes of eukaryotes (Numts) has been linked to lifespan in nonhuman species and recently demonstrated to occur in rare instances from one human generation to the next. Here, we investigated numtogenesis dynamics in humans in 2 ways. First, we quantified Numts in 1,187 postmortem brain and blood samples from different individuals. Compared to circulating immune cells (n = 389), postmitotic brain tissue (n = 798) contained more Numts, consistent with their potential somatic accumulation. Within brain samples, we observed a 5.5-fold enrichment of somatic Numt insertions in the dorsolateral prefrontal cortex (DLPFC) compared to cerebellum samples, suggesting that brain Numts arose spontaneously during development or across the lifespan. Moreover, an increase in the number of brain Numts was linked to earlier mortality. The brains of individuals with no cognitive impairment (NCI) who died at younger ages carried approximately 2 more Numts per decade of life lost than those who lived longer. Second, we tested the dynamic transfer of Numts using a repeated-measures whole-genome sequencing design in a human fibroblast model that recapitulates several molecular hallmarks of aging. These longitudinal experiments revealed a gradual accumulation of 1 Numt every ~13 days. Numtogenesis was independent of large-scale genomic instability and unlikely driven by cell clonality. Targeted pharmacological perturbations including chronic glucocorticoid signaling or impairing mitochondrial oxidative phosphorylation (OxPhos) only modestly increased the rate of numtogenesis, whereas patient-derived SURF1-mutant cells exhibiting mtDNA instability accumulated Numts 4.7-fold faster than healthy donors. Combined, our data document spontaneous numtogenesis in human cells and demonstrate an association between brain cortical somatic Numts and human lifespan. These findings open the possibility that mito-nuclear horizontal gene transfer among human postmitotic tissues produces functionally relevant human Numts over timescales shorter than previously assumed.

A Dramatic Case Report: Achived Remission in Metamphetamine Addiction After Changing City, Yet Ended Up in Prison

Introduction: Addiction is often viewed as a brain disease, focusing on the individual's body or brain and describing it as a disordered state. However, this perspective overlooks the significant role of social contexts and how consumption patterns evolve. Substance use disorders should be addressed with a biopsychosocial model, considering environmental impacts on addiction development and treatment. Research shows that changes in the environment can alter substance use behaviors. Additionally, substance use is linked to criminal activities, as drugs can influence thoughts and behaviors leading to crime. Case Presentation: This report details a patient with methamphetamine use disorder who was on probation for theft during his substance use p eriod. Despite multiple hospitalizations and treatments, he relapsed each time he returned to his previous environment. However, he achieved remission after moving to a stable, developed area with family support. Unfortunately, he was later imprisoned for his p rior offense during this remission period. Conclusions This case underscores the critical impact of the living environment on substance use behaviors. The patient's remission after relocating from a socially disadvantaged area highlights the importance of environmental factors in addiction treatment. While his imprisonment is unfortunate, the positive changes during his stay with his sister and his abstinence from substance use are promising for his future recovery. Effective treatment for methamphetamine addiction must consider and integrate environmental factors into treatment strategies.

Neural correlates of static and dynamic social decision-making in real-time sibling interactions.

In traditional game theory tasks, social decision-making is centered on the prediction of the intentions (i.e., mentalizing) of strangers or manipulated responses. In contrast, real-life scenarios often involve familiar individuals in dynamic environments. Further research is needed to explore neural correlates of social decision-making with changes in the available information and environmental settings. This study collected fMRI hyperscanning data (N = 100, 46 same-sex pairs were analyzed) to investigate sibling pairs engaging in an iterated Chicken Game task within a competitive context, including two decision-making phases. In the static phase, participants chose between turning (cooperate) and continuing (defect) in a fixed time window. Participants could estimate the probability of different events based on their priors (previous outcomes and representation of other's intentions) and report their decision plan. The dynamic phase mirrored real-world interactions in which information is continuously changing (replicated within a virtual environment). Individuals had to simultaneously update their beliefs, monitor the actions of the other, and adjust their decisions. Our findings revealed substantial choice consistency between the two phases and evidence for shared neural correlates in mentalizing-related brain regions, including the prefrontal cortex, temporoparietal junction (TPJ), and precuneus. Specific neural correlates were associated with each phase; increased activation of areas associated with action planning and outcome evaluation were found in the static compared with the dynamic phase. Using the opposite contrast, dynamic decision-making showed higher activation in regions related to predicting and monitoring other's actions, including the anterior cingulate cortex and insula. Cooperation (turning), compared with defection (continuing), showed increased activation in mentalizing-related regions only in the static phase, while defection, relative to cooperation, exhibited higher activation in areas associated with conflict monitoring and risk processing in the dynamic phase. Men were less cooperative and had greater TPJ activation. Sibling competitive relationship did not predict competitive behavior but showed a tendency to predict brain activity during dynamic decision-making. Only individual brain activation results are included here, and no interbrain analyses are reported. These neural correlates emphasize the significance of considering varying levels of information available and environmental settings when delving into the intricacies of mentalizing during social decision-making among familiar individuals.

Goal-directed learning is multidimensional and accompanied by diverse and widespread changes in neocortical signaling.

New tasks are often learned in stages with each stage reflecting a different learning challenge. Accordingly, each learning stage is likely mediated by distinct neuronal processes. And yet, most rodent studies of the neuronal correlates of goal-directed learning focus on individual outcome measures and individual brain regions. Here, we longitudinally studied mice from naïve to expert performance in a head-fixed, operant conditioning whisker discrimination task. In addition to tracking the primary behavioral outcome of stimulus discrimination, we tracked and compared an array of object-based and temporal-based behavioral measures. These behavioral analyses identify multiple, partially overlapping learning stages in this task, consistent with initial response implementation, early stimulus-response generalization, and late response inhibition. To begin to understand the neuronal foundations of these learning processes, we performed widefield Ca2+ imaging of dorsal neocortex throughout learning and correlated behavioral measures with neuronal activity. We found distinct and widespread correlations between neocortical activation patterns and various behavioral measures. For example, improvements in sensory discrimination correlated with target stimulus evoked activations of response-related cortices along with distractor stimulus evoked global cortical suppression. Our study reveals multidimensional learning for a simple goal-directed learning task and generates hypotheses for the neuronal modulations underlying these various learning processes.

Multiscale Functional Connectivity analysis of episodic memory reconstruction

Our ability to share memories constitutes a social foundation of our world. When exposed to another person's memory, individuals can mentally reconstruct the events described, even if they were not present during the related events. However, the extent to which the neuronal connectivity patterns elicited by the mental reconstruction of an event mirror those present in the brains of individuals who experienced the original event remains unclear. Through two independent fMRI experiments, we explore the Functional Connectivity (FC) patterns at different timescales associated with these cognitive processes using the innovative Multiscale Functional Connectivity (MFC) technique. This study aims to shed light on how our brains construct mental representations of scenes in a movie compared to the verbal transmission of the same scenes. Our results demonstrated that the Default Mode Network (DMN) plays a crucial role in these experiments and exhibits unique FC patterns across different timescales, yet remarkably consistent among participants. In addition, we found significant connectivity patterns within the temporal cortex, including significant contributions of the temporal pole and the fusiform gyrus, which exhibited a pivotal role in cooperation with the DMN in both experiments.

Longitudinal stability of individual brain plasticity patterns in blindness

The primary visual cortex (V1) in blindness is engaged in a wide spectrum of tasks and sensory modalities, including audition, touch, language, and memory. This widespread involvement raises questions regarding the constancy of its role and whether it might exhibit flexibility in its function over time, connecting to diverse network functions specific to task demands. This would suggest that reorganized V1 assumes a role like multiple-demand system regions. Alternatively, varying patterns of plasticity in blind V1 may be attributed to individual factors, with different blind individuals recruiting V1 preferentially for different functions. In support of this, we recently showed that V1 functional connectivity (FC) varies greatly across blind individuals. But do these represent stable individual patterns of plasticity, or are they driven more by instantaneous changes, like a multiple-demand system now inhabiting V1? Here, we tested whether individual FC patterns from the V1 of blind individuals are stable over time. We show that over two years, FC from the V1 is unique and highly stable in a small sample of repeatedly sampled congenitally blind individuals. Further, using multivoxel pattern analysis, we demonstrate that the unique reorganization patterns of these individuals allow decoding of participant identity. Together with recent evidence for substantial individual differences in V1 connectivity, this indicates that there may be a consistent role for V1 in blindness, which may differ for each individual. Further, it suggests that the variability in visual reorganization in blindness across individuals could be used to seek stable neuromarkers for sight rehabilitation and assistive approaches.

Design of New Aromatic Tertiary Amine-based as Butyrylcholinesterase Inhibitors Relying on Molecular Docking, ADME-Tox and Molecular Dynamics.

Butyrylcholinesterase (BChE) plays a pivotal role in the progression of Alzheimer's disease. Empirical research demonstrated a fundamental alteration in the role of BChE concerning the reduction of cholinergic neurotransmission within the brains of individuals at advanced stages of Alzheimer's. This study focuses on developing potent inhibitors for Butyrylcholinesterase (BChE) in the context of Alzheimer's disease (AD) treatment. Building upon previous research, a series of 44 aromatic tertiary amine-based compounds was investigated. Starting with ADME-Tox studies, the pharmacokinetic and pharmacodynamic properties of the compounds were analyzed to select promising candidates for BChE inhibition, which is a crucial factor in AD pathology. Molecular docking analyses identified compound M18 as the most promising candidate, and further compounds (X9 and X10) were proposed based on M18's chemical structure. These compounds displayed superior properties in terms of binding energies and hydrogen bonds in comparison to M18. The Molecular Dynamics (MD) simulations, which are over a 500 ns timeframe, confirmed the conformational stability of compounds X9 and X10, compared to M18. Overall, the stated results suggest that the proposed compounds, including X9 and X10 specifically, have a significant potential as candidates for BChE inhibition. This presents a promising avenue for therapeutic intervention in Alzheimer's disease.

Structural and functional features characterizing the brains of individuals with higher controllability of motor imagery

Motor imagery is a higher-order cognitive brain function that mentally simulates movements without performing the actual physical one. Although motor imagery has attracted the interest of many researchers, and mental practice utilizing motor imagery has been widely used in sports training and post-stroke rehabilitation, neural bases that determine individual differences in motor imagery ability are not well understood. In this study, using controllability of motor imagery (CMI) test that can objectively evaluate individual ability to manipulate one’s imaginary postures, we examined structural and functional features characterizing the brains of individuals with higher controllability of motor imagery, by analyzing T1-weighted structural MRI data obtained from 89 participants and functional MRI data obtained from 28 of 89 participants. The higher CMI test scorers had larger volume in the bilateral superior frontoparietal white matter regions. The CMI test activated the bilateral dorsal premotor cortex (PMD) and superior parietal lobule (SPL); specifically, the left PMD and/or the right SPL enhanced functional coupling with the visual body, somatosensory, and motor/kinesthetic areas in the higher scorers. Hence, controllability of motor imagery is higher for those who well-develop superior frontoparietal network, and for those whose this network accesses these sensory areas to predict the expected multisensory experiences during motor imagery. This study elucidated for the first time the structural and functional features characterizing the brains of individuals with higher controllability of motor imagery, and advanced understanding of individual differences in motor imagery ability.

Altered neural synchronization in response to 2 Hz amplitude-modulated tones in the auditory cortex of children with Autism Spectrum Disorder: An MEG study

ObjectiveSome studies have hypothesized that atypical neural synchronization at the delta frequency band in the auditory cortex is associated with phonological and language skills in children with Autism Spectrum Disorder (ASD), but it is still poorly understood. This study investigated this neural activity and addressed the relationships between auditory response and behavioral measures of children with ASD. MethodsWe used magnetoencephalography and individual brain models to investigate 2 Hz Auditory Steady-State Response (ASSR) in 20 primary-school-aged children with ASD and 20 age-matched typically developing (TD) controls. ResultsFirst, we found a between-group difference in the localization of the auditory response, so as the topology of 2 Hz ASSR was more superior and posterior in TD children when comparing to children with ASD. Second, the power of 2 Hz ASSR was reduced in the ASD group. Finally, we observed a significant association between the amplitude of neural response and language skills in children with ASD. ConclusionsThe study provided the evidence of reduced neural response in children with ASD and its relation to language skills. SignificanceThese findings may inform future interventions targeting auditory and language impairments in ASD population.