Alterations In Brain Function Research Articles

Effects of Alcohol on EEG Activity: A Systematic Review Focused on Sex-Related Differences in Youth.

Most electroencephalographic (EEG) investigations on alcohol have focused on adults, and scarce data is available about the potential of EEG measurements to detect young people at high-risk, as well as, to understand possible sex differences in alcohol impact on the brain. This systematic review aimed to explore sex-related differences in EEG among young people with alcohol misuse, alcohol use disorder (AUD), and offspring of families with AUD. A systematic review of the literature was conducted following PRISMA guidelines. Review protocol was registered in Prospero (ID: CRD42024511471). After article selection process and quality assessment, 25 studies were included in our review. The search included participants between 12 and 30 years old with problematic alcohol consumption, as defined by DSM, AUDIT, or specific alcohol misuse questionnaires. It seems that beta was generally higher in young males with AUD, and they usually exhibited greater interhemispheric connectivity (interHC), whereas young females with AUD tended towards enhanced intraHC. P3 appears to be particularly sensitive to alcohol misuse, with males typically exhibiting a lower amplitude than young females. Other event related potentials (ERPs) such as N415, P640, and the error-related negativity (ERN) lacked sufficient methodological support to draw conclusions regarding sex differences, N340 and P540 suggested avenues for expanding research on memory processing, indicating differences in amplitude between males and females. Considering sex variables in clinical research will enhance our understanding of alterations in brain function and structure with the goal of tailoring treatment strategies for AUD.

Hypercomplex Graph Neural Network: Towards Deep Intersection of Multi-modal Brain Networks.

The multi-modal neuroimage study has provided insights into understanding the heteromodal relationships between brain network organization and behavioral phenotypes. Integrating data from various modalities facilitates the characterization of the interplay among anatomical, functional, and physiological brain alterations or developments. Graph Neural Networks (GNNs) have recently become popular in analyzing and fusing multi-modal, graph-structured brain networks. However, effectively learning complementary representations from other modalities remains a significant challenge due to the sophisticated and heterogeneous inter-modal dependencies. Furthermore, most existing studies often focus on specific modalities (e.g., only fMRI and DTI), which limits their scalability to other types of brain networks. To overcome these limitations, we propose a HyperComplex Graph Neural Network (HC-GNN) that models multi-modal networks as hypercomplex tensor graphs. In our approach, HC-GNN is conceptualized as a dynamic spatial graph, where the attentively learned inter-modal associations are represented as the adjacency matrix. HC-GNN leverages hypercomplex operations for inter-modal intersections through cross-embedding and cross-aggregation, enriching the deep coupling of multi-modal representations. We conduct a statistical analysis on the saliency maps to associate disease biomarkers. Extensive experiments on three datasets demonstrate the superior classification performance of our method and its strong scalability to various types of modalities. Our work presents a powerful paradigm for the study of multi-modal brain networks.

Alterations of regional homogeneity and functional connectivity in different hoehn and yahr stages of Parkinson's disease

PurposeUsing regional homogeneity (ReHo) and functional connectivity (FC) to assess alterations in brain function and their potential relation to different Hoehn and Yahr (H&Y) stages in Parkinson's disease (PD). Materials and methods66 patients with PD and 57 age- and sex-matched healthy control (HC) participants were recruited. All subjects underwent clinical assessments and resting-state functional magnetic resonance imaging (rs-fMRI) scanning. We analyzed alterations in regional brain activity using ReHo analyses in all subjects and further explored their relationship to disease severity. Finally, the brain region significantly associated with disease severity was used as a seed point to analyze the FC changes between it and other brain regions in the whole brain. ResultsCompared with HC participants, PD patients showed a significant decrease ReHo in the sensorimotor network (bilateral precentral and postcentral gyrus). The ReHo value of the left precentral gyrus in PD patients decreased with increasing H&Y stage and correlated negatively with Unified Parkinson’s Disease Rating Scale (UPDRS) III scores. Further, FC analysis of the left precentral gyrus as a region of interest showed that functional activity between the left precentral gyrus and sensorimotor network, default network, and visual network was decreased. ConclusionThe left precentral gyrus plays an important role in the pathophysiological mechanisms of PD patients, and this finding further highlights the potential of the primary motor cortex (M1) as a non-invasive therapeutic target for neuromodulation in PD patients.

Functional and connectivity correlates associated with Parkinson's disease psychosis: a systematic review.

Neural underpinnings of Parkinson's disease psychosis remain unclear to this day with relatively few studies and reviews available. Using a systematic review approach, here, we aimed to qualitatively synthesize evidence from studies investigating Parkinson's psychosis-specific alterations in brain structure, function or chemistry using different neuroimaging modalities. PubMed, Web of Science and Embase databases were searched for functional MRI (task-based and resting state), diffusion tensor imaging, PET and single-photon emission computed tomography studies comparing Parkinson's disease psychosis patients with Parkinson's patients without psychosis. We report findings from 29 studies (514 Parkinson's psychosis patients, mean age ± SD = 67.92 ± 4.37 years; 51.36% males; 853 Parkinson's patients, mean age ± SD = 66.75 ± 4.19 years; 55.81% males). Qualitative synthesis revealed widespread patterns of altered brain function across task-based and resting-state functional MRI studies in Parkinson's psychosis patients compared with Parkinson's patients without psychosis. Similarly, white matter abnormalities were reported in parietal, temporal and occipital regions. Hypo-metabolism and reduced dopamine transporter binding were also reported whole brain and in sub-cortical areas. This suggests extensive alterations affecting regions involved in high-order visual processing and attentional networks.

Topological organization of the brain network in thyroid-associated ophthalmopathy using graph theoretical analysis.

Mounting neuroimaging evidence indicates that patients with thyroid-associated ophthalmopathy (TAO) demonstrate altered brain function and structure. Nonetheless, the alterations in the topological properties of the functional brain connectome in TAO patients are not yet fully understood. This study aimed to investigate the topological organization of the functional brain connectome in TAO patients using graph-theoretic methods. Twenty-five TAO patients (10 males and 15 females) and 25 age-, sex-, and education-matched healthy controls (HCs) (10 males and 15 females) (the TAO and HC data are from the same dataset in previous studies) underwent resting-state MRI scans. Graph-theoretic analysis was used to study the global, nodal, and edge topological properties of the brain's functional connectome. Both the TAO and HC groups exhibited high-efficiency small-world networks in their brain functional networks. However, there were no significant differences in small-world properties (Cp, γ, λ, Lp, and σ) and network efficiency [global and local efficiencies (Eloc)] between the two groups. In addition, the TAO group demonstrated reduced betweenness centrality in the right fusiform and increased nodal Eloc in the right intraparietal sulcus (P < 0.05, Bonferroni-corrected). Furthermore, the TAO group displayed altered functional connections among the default-mode network (DMN), visual network (VN), sensorimotor network (SMN), and cingulo-opercular network (CON). Patients with TAO exhibited abnormal topological organization of the human brain connectome, including decreased betweenness centrality and increased nodal Eloc. Moreover, the TAO group displayed altered functional connections primarily within the DMN, VN, SMN, and CON. These findings provide crucial insights into the neural mechanisms underlying visual loss, abnormal emotion regulation, and cognitive deficits in TAO patients.

Neuronal alterations in AKT isotype expression in schizophrenia.

Schizophrenia is characterized by substantial alterations in brain function, and previous studies suggest insulin signaling pathways, particularly involving AKT, are implicated in the pathophysiology of the disorder. This study demonstrates elevated mRNA expression of AKT1-3 in neurons from schizophrenia subjects, contrary to unchanged or diminished total AKT protein expression reported in previous postmortem studies, suggesting a potential decoupling of transcript and protein levels. Sex-specific differential AKT activity was observed, indicating divergent roles in males and females with schizophrenia. Alongside AKT, upregulation of PDPK1, a critical component of the insulin signaling pathway, and several protein phosphatases known to regulate AKT were detected. Moreover, enhanced expression of the transcription factor FOXO1, a regulator of glucose metabolism, hints at possible compensatory mechanisms related to insulin signaling dysregulation. Findings were largely independent of antipsychotic medication use, suggesting inherent alterations in schizophrenia. These results highlight the significance of AKT and related signaling pathways in schizophrenia, proposing that these changes might represent a compensatory response to a primary defect of canonical insulin signaling pathways. This research underscores the need for a detailed understanding of these signaling pathways for the development of effective therapeutic strategies.

Dorsolateral prefrontal cortex to ipsilateral primary motor cortex intercortical interactions during inhibitory control enhance response inhibition in open-skill athletes

Numerous studies have reported that long-term sports training can affect inhibitory control and induce brain functional alterations. However, the influence of environmental dynamics in sports training on inter-cortical connectivity has not been well studied. In the current study, we used twin-coil transcranial magnetic stimulation to investigate the functional connectivity between dorsolateral prefrontal cortex (DLPFC) and ipsilateral primary motor cortex (M1) during proactive and reactive inhibition in participants with sports skills in dynamic environment (open-skill experts), stable environment (closed-skill experts), and no sports skills (controls). Using a modified stop signal task, proactive inhibition was measured by the response delay effect (RDE), and reactive inhibition was measured by the stop-signal reaction time (SSRT). Intra-hemispheric DLPFC-M1 interactions and single pulse motor-evoked potentials (MEPs) were measured during the task. A stronger inhibitory effect of the DLPFC over M1 was observed during early reactive control stages compared to baseline levels. In addition, this inhibitory effect was pronounced when comparing open-skill experts to non-athlete controls, a relationship that was significantly correlated with superior reactive control performance. Furthermore, DLPFC to M1 influencing direction shifted from late proactive control to reactive control. Behavioral results also demonstrated enhanced proactive control abilities in open-skill experts relative to controls. Such enhancement may be due to the combination of environmental complexity and physical fitness in long-term skill training.

Brain functional alteration and cognitive performance in cardiovascular diseases: a systematic review of fMRI studies.

Functional magnetic resonance imaging (fMRI) is a useful tool to evaluate brain inefficiencies secondary to cardiovascular diseases (CVDs); nevertheless, limited fMRI studies have been conducted to investigate the effect of CVDs on brain functional changes and cognitive function. This systematic review aims to explore, synthesise, and report fMRI outcomes (resting state and task-based) and cognitive performance in patients with CVDs. Two reviewers independently searched published literature until April 2024 on ScienceDirect, PubMed, Web of Science, and ClinicalTrials.gov adhering to the PRISMA protocol. A total of 26 eligible studies were considered for full-text screening, of which 10 were included in this review. The methodological quality was assessed by mixed methods appraisal tool and was reported as empirically fair. Among 336 subjects with CVDs, aged between 49.90 ± 6.10 to 72.20 ± 5.70 years, the majority had coronary artery diseases (n = 177, 52.68%) and hypertension (n = 200, 59.52%), and approximately half of them were females (n = 169, 50.30%). Based on the qualitative synthesis, subjects with CVDs demonstrated an increased cognitive decline (reduced Mini-Mental State Examination/Montreal Cognitive Assessment mean values) and attenuated task performance (lower mean 2-back task scores and slower reaction time). Results also indicated impaired brain activity at the supplementary motor area associated with poor ejection fraction; reduced default mode network suppression linked to high low-density lipoprotein cholesterol; lower regional homogeneity and amplitude of low-frequency fluctuation values; and reduced functional connectivity. In summary, alterations in brain networks connectivity may have contributed to an impaired cognitive performance in patients with cardiovascular diseases. It can be extrapolated that CVDs tend to alter the brain network connectivity and result in cognitive impairment and poorer task performance. However, for future imaging studies, more stringent and homogenous demographic data are highly recommended.

Developmental Syngap1 haploinsufficiency in medial ganglionic eminence-derived interneurons impairs auditory cortex activity, social behavior and extinction of fear memory.

Mutations in SYNGAP1, a protein enriched at glutamatergic synapses, cause intellectual disability associated with epilepsy, autism spectrum disorder and sensory dysfunctions. Several studies showed that Syngap1 regulates the time course of forebrain glutamatergic synapse maturation; however, the developmental role of Syngap1 in inhibitory GABAergic neurons is less clear. GABAergic neurons can be classified into different subtypes based on their morphology, connectivity and physiological properties. Whether Syngap1 expression specifically in Parvalbumin (PV) and Somatostatin (SST)-expressing interneurons, which are derived from the medial ganglionic eminence, plays a role in the emergence of distinct brain functions remains largely unknown. We used genetic strategies to generate Syngap1 haploinsufficiency in a) prenatal interneurons derived from the medial ganglionic eminence, b) in postnatal PV cells and c) in prenatal SST interneurons. We further performed in vivo recordings and behavioral assays to test whether and how these different genetic manipulations alter brain function and behavior in mice of either sex.Mice with prenatal-onset Syngap1 haploinsufficiency restricted to Nkx2.1-expressing neurons show abnormal cortical oscillations and increased entrainment induced by 40Hz auditory stimulation, but lack of stimulus-specific adaptation. This latter phenotype was reproduced in mice with Syngap1 haploinsufficiency restricted to PV, but not SST, interneurons. Prenatal-onset Syngap1 haploinsufficiency in Nkx2.1-expressing neurons led to impaired social behavior and inability to extinguish fear memories; however, neither postnatal PV- nor prenatal SST-specific mutant mice show these phenotypes. We speculate that Syngap1 haploinsufficiency in prenatal/perinatal PV interneurons may contribute to cortical activity and cognitive alterations associated with Syngap1 mutations.Significance statement Mutations in the human gene cause a form of developmental epileptic encephalopathy associated with intellectual disability, autism and sensory dysfunctions. Several studies have shown that in addition to playing a major role in the synaptic maturation and plasticity of forebrain excitatory neurons, Syngap1 affects GABAergic circuit function as well. Forebrain GABAergic neurons can be divided into different subtypes. Whether Syngap1 expression specifically in distinct interneuron populations and during specific developmental time windows plays a role in the emergence of distinct brain functions remains largely unknown. Here, we report that early, pre or perinatal Syngap1 expression in developing GABAergic neurons derived from the medial ganglionic eminence promotes the development of auditory cortex function, social behavior and ability to extinguish fear memories.

How Can Near‐Infrared Spectroscopy (NIRS) Help Understanding of the Psychotherapy Process? A Scoping Review of Therapeutic Interactions

AbstractIn recent years, near‐infrared spectroscopy (NIRS) has garnered significant attention for its potential clinical applications as a non‐invasive and straightforward method for measuring brain functions. While NIRS has become useful in psychiatric contexts by aiding in the differential diagnosis of depression, its application in clinical psychology is still developing. Due to its ecological validity, which allows for measurements in natural settings, NIRS shows promise in revealing the dynamic elements of the psychotherapy process. In this study, we conducted a scoping literature review of the use of NIRS in psychotherapeutic interactions, exploring its potential to unveil the complexities of psychotherapy settings involving interpersonal interactions. Employing a scoping review approach, we systematically searched the PubMed, PsycINFO, and Web of Science databases for articles published through October 19, 2023 about studies using NIRS as a measurement instrument: This yielded various therapeutic interactions. Of the 155 retrieved results that remained after the initial screening, seven met the inclusion criteria. Of these, six studies examined the synchronization of brain functions through the simultaneous brain activity measurements (hyperscanning) of two participants. The review revealed that, despite the anticipated potential of NIRS, it has become evident there is a dearth of research focusing on interactions during psychotherapy. Furthermore, the few available studies have not explored changes in line with the progression of psychotherapeutic interactions. Consequently, future studies should address whether NIRS can effectively assess alterations in brain function resulting from micro‐level events, such as the therapeutic interaction between therapists and clients during psychotherapy.

Atypical gut microbiota composition in a mouse model of developmental stuttering.

Developmental stuttering is a complex neurodevelopmental disorder characterized by disfluent speech. It has been associated with mutations in genes involved in lysosomal enzyme trafficking. Mice with mutations in one such gene, Gnptab, exhibit atypical vocalizations analogous to stuttering in humans. This mouse model has enabled the study of various molecular mechanisms related to the disorder. Simultaneously, an increasing number of reports have suggested the role of gut microbiota in altered brain function and development in neurological disorders. In this study, we compared gut microbiota profiles from Gnptab mutant mice to wildtype control mice. Microbiome analysis demonstrated a distinct microbiota profile in Gnptab mutant mice. The most significant alteration was an increased relative abundance of Akkermansia, a genus of mucin degrading bacteria, which has previously been associated with multiple neurological disorders. Moreover, the altered microbiota profile of these mice was predicted to result in differences in abundance of several metabolic pathways, including short chain fatty acid and lipopolysaccharide synthesis. These pathways may play a role in the onset, progression and persistence of developmental stuttering. This is the first study to show a potential link between developmental stuttering and changes in the gut microbiota, laying the groundwork for a new research direction.

A-102 Clinical Evaluation of Novel Markers in Brain Injury

Abstract Background Traumatic brain injury (TBI) is a significant health concern affecting individuals of all ages, demanding precise diagnostic methodologies to guide effective clinical management. According to the 2010 definition, a TBI results from an external force causing an alteration in brain function or other evidence of brain pathology. Current diagnostic tools, i.e. CT scans and the Glasgow Coma Scale (GCS), are inefficient because they are time and labor intensive. The need for rapid diagnostic tools is underscored by the drawbacks of existing methods, such as CT scans, which are expensive, expose patients to large amounts of radiation, and lead to delayed treatment. Recent advances in TBI diagnosis involve novel biomarkers, such as Glial Fibrillary Acidic Protein (GFAP) and Ubiquitin C-Terminal Hydrolase L1 (UCH-L1), which have shown promise in revolutionizing the assessment of head traumas. GFAP, a glial-specific protein, is elevated in circulation after a TBI, distinguishing it from multi-trauma patients without brain injuries. UCH-L1, found in neurons, is significantly elevated in TBI patients compared to uninjured controls. A 2021 study further supports the clinical effectiveness of these biomarkers, demonstrating their capacity to exclude CT-positive injury in acute TBI cases. The primary aim of this study is to explore the clinical utility of the Abbott Alinity TBI assay, specifically biomarkers GFAP and UCH-L1, in emergency department patients with a history of head trauma. Methods A retrospective study involving 238 emergency department patients with a history of head trauma and noncontrast CT scans was conducted using the Abbott Alinity TBI assay. Serum samples were collected, and biomarker values were established and compared to CT scan results. The study was comprised of 94 females and 144 males spanning various age groups. The GFAP and UCH-L1 cutoffs used were FDA approved, at 35.0 ng/L and 400.0 ng/L, respectively. If either marker was above the cutoff the patient ruled at risk for TBI. Results Results demonstrated the assay correctly identified all CT-positive cases (100% sensitivity), placing them in the rule-in group, while identifying 44 patients with a 0 chance of TBI. The negative predictive value for the TBI overall was 100% (95% CI: 91.96%-100%). The GFAP assay alone identified 30/31 positive CT scans, reporting a 98.77% (95% CI: 92.03%-99.82%) negative predictive value. The UCH-L1 assay reported 26/31 positive CT scans with a negative predictive value of 94.68% (95% CI: 88.71-97.58%). Analyzing the data revealed the TBI assay would have reduced CT scans by 18.5%. Conclusions The results of this study did show a potential reduction in the number of patients sent to CT making it a valuable tool for triaging patients presenting with head trauma; however, the complexity of neurological problems may lead to increased false positives, reducing assay specificity. Despite this limitation, this study concludes that the GFAP and UCH-L1 markers could be used to triage patients into CT rule-out and rule-in groups, thereby streamlining clinical management. In conclusion, this assay, incorporating GFAP and UCH-L1 biomarkers, presents as a promising diagnostic tool for emergency departments.

448 - Brain functional alterations in patients with schizophrenia with comorbid metabolic syndrome treated with risperidone or clozapine: A resting-state functional magnetic resonance imaging study of regional homogeneity

448 - Brain functional alterations in patients with schizophrenia with comorbid metabolic syndrome treated with risperidone or clozapine: A resting-state functional magnetic resonance imaging study of regional homogeneity

Urine Albumin-to-Creatinine Ratio as an Indicator of Brain Activity Changes in Chronic Kidney Disease: A Resting-State fMRI Study.

Chronic kidney disease (CKD) is increasingly recognized as a risk factor for alterations in brain function. However, detecting early-stage symptoms and structural changes remains challenging, potentially leading to delayed treatment. In our study, we aimed to investigate spontaneous brain activity changes in CKD patients using resting-state functional magnetic resonance imaging (fMRI). Additionally, we explored the correlation between common biomarkers reflecting CKD severity and brain activity. We recruited a cohort of 22 non-dialysis-dependent CKD patients and 22 controls for resting-state fMRI scans. Amplitude of low-frequency fluctuations (ALFFs) and regional homogeneity (ReHo) were calculated to evaluate brain activity. Regression analysis was conducted to explore the correlations between biomarkers reflecting the severity of CKD and brain activity. CKD patients exhibited reduced z-scored ALFF (zALFF) and mean ALFF (mALFF) in the bilateral putamen, right caudate nucleus, left anterior cingulate, and right precuneus. Changes in bilateral putamen were also found in smCohe-ReHo and szCohe-ReHo analyses. Urine albumin-to-creatinine ratio (UACR), urine protein-to-creatinine ratio (UPCR), and serum albumin levels were associated with attenuated putamen activity. Non-dialysis-dependent CKD patients had changes in zALFF, mALFF, smCohe-ReHo, and szCohe-ReHo values in specific brain regions, especially bilateral putamen. UACR, UPCR, and serum albumin levels are associated with putamen activity attenuation in rs-fMRI.

Prefrontal oxygenation during experimental pain in adolescents engaging in non-suicidal self-injury

BackgroundThe intricate role of pain in non-suicidal self-injury (NSSI) makes the investigation of alterations in brain function during pain processing a critical yet underexplored topic. The aim of this study was to investigate fNIRS correlates of experimental pain and how these differed between adolescent patients engaging in NSSI and healthy controls. Methods154 adolescent patients with NSSI and 48 healthy controls underwent a heat pain stimulation with linearly increasing temperature from 32 °C to max. 50 °C, during which fNIRS activity was recorded. Associations between fNIRS activity and pain perception (i.e. pain threshold, pain tolerance and pain intensity) were examined using linear mixed models and linear regression analyses. ResultsAcross groups, we found a decrease in prefrontal oxygenation during increasing pain stimulation: Oxygenated hemoglobin was higher during baseline than during pain threshold (b = −0.36, p < .001) and higher during pain threshold than during pain tolerance (b = −0.10, p < .001). We did not find differential patterns of prefrontal oxygenation across the pain assessment between patients and healthy controls. Also, no association between pain intensity and fNIRS activity was found. LimitationsfNIRS was only recorded in prefrontal regions and our design did not include a non-painful stimulation as a control condition. ConclusionWhile our study adds to the understanding of prefrontal hemodynamic changes associated with pain processing, it did not contribute further evidence to the few existing findings regarding altered neural processing of pain in adolescents engaging in NSSI.

Aging, brain plasticity, and motor learning.

Motor skill learning, the process of acquiring new motor skills, is critically important across the lifespan, from early development through adulthood and into older age, as well as in pathological conditions (i.e., rehabilitation). Extensive research has demonstrated that motor skill acquisition in young adults is accompanied by significant neuroplastic changes, including alterations in brain structure (gray and white matter), function (i.e., activity and connectivity), and neurochemistry (i.e., levels of neurotransmitters). In the aging population, motor performance typically declines, characterized by slower and less accurate movements. However, despite these age-related changes, older adults maintain the capacity for skill improvement through training. In this review, we explore the extent to which the aging brain retains the ability to adapt in response to motor learning, specifically whether skill acquisition is accompanied by neural changes. Furthermore, we discuss the associations between inter-individual variability in brain structure and function and the potential for future learning in older adults. Finally, we consider the use of non-invasive brain stimulation techniques aimed at optimizing motor learning in this population. Our review provides insights into the neurobiological underpinnings of motor learning in older adults and emphasizes strategies to enhance their motor skill acquisition.

Effects of serotonergic manipulation in the brainstem and hypothalamus of overnourished rats during lactation

Previous studies suggest that being overweight and obese is capable of altering brain function during critical periods due to the higher plasticity of the brain during development. However, more literature still needs to be on the immediate effect of overnutrition and serotonin modulation in brain areas. In this study, we aimed to evaluate the effects of serotoninergic manipulation on oxidative stress and pro-inflammatory markers in the brainstem and hypothalamus of overnourished rats. The fluoxetine treatment was performed from postnatal day 3 (PND3) to postnatal day 21 (PND21) to evaluate mitochondrial function, oxidative balance, and the mRNA levels of monoaminergic molecules such as serotonin and dopamine, pro-inflammatory cytokines, and BDNF. Neonatal overnutrition induces molecular and biochemical changes in the brainstem and hypothalamus. These nutritional disturbances during lactation dysregulate energy balance and cellular redox, inducing oxidative stress. Conversely, modulation of the serotoninergic system through pharmacological use of fluoxetine was able to reverse the deleterious effects of overnutrition during lactation, enabling better brain development and delaying the development of pathologies and oxidative stress.

Evolution of aberrant brain-wide spatiotemporal dynamics of resting-state networks in a Huntington's disease mouse model.

Huntington's disease (HD) is marked by irreversible loss of neuronal function for which currently no availability for disease-modifying treatment exists. Advances in the understanding of disease progression can aid biomarker development, which in turn can accelerate therapeutic discovery. We characterised the progression of altered dynamics of whole-brain network states in the zQ175DN mouse model of HD using a dynamic functional connectivity (FC) approach to resting-state fMRI and identified quasi-periodic patterns (QPPs) of brain activity constituting the most prominent resting-state networks. The occurrence of the normative QPPs, as observed in healthy controls, was reduced in the HD model as the phenotype progressed. This uncovered progressive cessation of synchronous brain activity with phenotypic progression, which is not observed with the conventional static FC approaches. To better understand the potential underlying cause of the observed changes in these brain states, we further assessed how mutant huntingtin (mHTT) protein deposition affects astrocytes and pericytes - one of the most important effectors of neurovascular coupling, along phenotypic progression. Increased cell-type dependent mHTT deposition was observed at the age of onset of motor anomalies, in the caudate putamen, somatosensory and motor cortex, regions that are prominently involved in HD pathology as seen in humans. Our findings provide meaningful insights into the development and progression of altered functional brain dynamics in this HD model and open new avenues in assessing the dynamics of whole brain states, through QPPs, in clinical HD research. Hyperactivity in the LCN-linked regions within short QPPs observed before motor impairment onset. DMLN QPP presents a progressive decrease in DMLN activity and occurrence along HD-like phenotype development. Breakdown of the LCN DMLN state flux at motor onset leads to a subsequent absence of the LCN DMLN QPP at an advanced HD-like stage.

Functional brain alterations in COVID-19 patients using resting-state fMRI: a systematic review.

This study systematically reviews the available evidence on resting-state functional magnetic resonance imaging (rs-fMRI) related to neurological symptoms and cognitive declines in COVID-19 patients. We followed PRISMA guidelines and looked up the PubMed, and Scopus databases for articles search on COVID-19 patients with neurological impairments, and functional connectivity alteration using rs-fMRI technique. Articles published between January 1, 2020, and May 31, 2024, are included in this study. The Quality Assessment Tool for Observational Prospective and Cross-Sectional Studies from the National Heart, Lung, and Blood Institute (NHLBI) was used to assess the quality of papers. A total of 15 articles met the inclusion criteria. The result reveals that the most prevalent neurological impairment associated with COVID-19 was cognitive decline, encompassing issues in attention, memory, processing speed, executive functions, language, and visuospatial ability. The brain connectivity results reveal that two brain areas were functionally altered; the prefrontal cortex and parahippocampus. The functional connectivity mainly increased in the frontal, temporal, and anterior piriform cortex, and reduced in the cerebellum, superior orbitofrontal cortex, and middle temporal gyrus, which also correlated with cognitive decline. The findings of neurological symptoms indicate one study reported a Disorder of Consciousness (DoC), and four studies reported COVID-19 patients with olfactory dysfunction. The present study concludes that COVID-19 can alter brain functional connectivity and offers significant insight into how COVID-19 affects the neuronal foundation of cognitive decline and other neurological impairments.

Classification of mindfulness experiences from gamma-band effective connectivity: Application of machine-learning algorithms on resting, breathing, and body scan

Background and ObjectivePracticing mindfulness is a mental process toward interoceptive awareness, achieving stress reduction and emotion regulation through brain-function alteration. Literature has shown that electroencephalography (EEG)-derived connectivity possesses the potential to differentiate brain functions between mindfulness naïve and mindfulness experienced, where such quantitative differentiation could benefit telediagnosis for mental health. However, there is no prior guidance in model selection targeting on the mindfulness-experience prediction. Here we hypothesized that the EEG effective connectivity could reach a good prediction performance in mindfulness experiences with brain interpretability. MethodsWe aimed at probing direct Directed Transfer Function (dDTF) to classify the participants’ history of mindfulness-based stress reduction (MBSR), and aimed at optimizing the prediction accuracy by comparing multiple machine learning (ML) algorithms. Targeting the gamma-band effective connectivity, we evaluated the EEG-based prediction of the mindfulness experiences across 7 machine learning (ML) algorithms and 3 sessions (i.e., resting, focus-breathing, and body-scan). ResultsThe support vector machine and naïve Bayes classifiers exhibited significant accuracies above the chance level across all three sessions, and the decision tree algorithm reached the highest prediction accuracy of 91.7 % with the resting state, compared to the classification accuracies with the other two mindful states. We further conducted the analysis on essential EEG channels to preserve the classification accuracy, revealing that preserving just four channels (F7, F8, T7, and P7) out of 19 yielded the accuracy of 83.3 %. Delving into the contribution of connectivity features, specific connectivity features predominantly located in the frontal lobe contributed more to classifier construction, which aligned well with the existing mindfulness literature. ConclusionIn the present study, we initiated a milestone of developing an EEG-based classifier to detect a person's mindfulness experience objectively. The prediction accuracy of the decision tree was optimal to differentiate the mindfulness experiences using the local resting-state EEG data. The suggested algorithm and key channels on the mindfulness-experience prediction may provide guidance for predicting mindfulness experiences using the EEG-based classification embedded in future wearable neurofeedback systems or plausible digital therapeutics.