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Type 2 diabetes mellitus has a worldwide prevalence of 10.5% in the adult population (20-79 years), and by 2045, the prevalence is expected to keep rising to one in eight adults living with diabetes. Mild cognitive impairment has a global prevalence of 19.7% in adults aged 50 years. Both conditions have shown a concerning increase in prevalence rates over the past 10 years, highlighting a growing public health challenge. Future forecasts indicate that the prevalence of dementia (no estimations done for individuals with mild cognitive impairment) is expected to nearly triple by 2050. Type 2 diabetes mellitus is a risk factor for the development of cognitive impairment, and such impairment increase the likelihood of poor glycemic/metabolic control. High phytate intake has been shown to be a protective factor against the development of cognitive impairment in observational studies. Diary phytate intake might reduce the micro- and macrovascular complications of patients with type 2 diabetes mellitus through different mechanisms. We describe the protocol of the first trial (the PHYND trial) that evaluate the effect of daily phytate supplementation over 56 weeks with a two-arm double-blind placebo-controlled study on the progression of mild cognitive impairment, cerebral iron deposition, and retinal involvement in patients with type 2 diabetes mellitus. Our hypothesis proposes that phytate, by inhibiting advanced glycation end product formation and chelating transition metals, will improve cognitive function and attenuate the progression from Mild Cognitive Impairment to dementia in individuals with type 2 diabetes mellitus and mild cognitive impairment. Additionally, we predict that phytate will reduce iron accumulation in the central nervous system, mitigate neurodegenerative changes in both the central nervous system and retina, and induce alterations in biochemical markers associated with neurodegeneration., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Pujol, Sanchis, Tamayo, Nicolau, Grases, Espino, Estremera, Rigo, Amengual, Rodríguez, Ribes, Gomila, Simó-Servat and Masmiquel.)

Decision prediction based on neurophysiological signals is of great application value in many real-life situations, especially in human-AI collaboration or counteraction. Single-trial analysis of electroencephalogram (EEG) signals is a very valuable step in the development of an online decision-prediction system. However, previous EEG-based decision-prediction methods focused mainly on averaged EEG signals of all decision-making trials to predict an individual's general decision tendency (e.g., risk seeking or aversion) over a period rather than on a specific decision response in a single trial. In the present study, we used a rock-paper-scissors game, which is a common multichoice decision-making task, to explore how to predict participants' single-trial choice with EEG signals. Forty participants, comprising 20 females and 20 males, played the game with a computer player for 330 trials. Considering that the decision-making process of this game involves multiple brain regions and neural networks, we proposed a new algorithm named common spatial pattern-attractor metagene (CSP-AM) to extract CSP features from different frequency bands of EEG signals that occurred during decision making. The results showed that a multilayer perceptron classifier achieved an accuracy significantly exceeding the chance level among 88.57% (31 of 35) of participants, verifying the classification ability of CSP features in multichoice decision-making prediction. We believe that the CSP-AM algorithm could be used in the development of proactive AI systems., (© 2023 The Authors. PsyCh Journal published by Institute of Psychology, Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.)

Cerebral autoregulation (CA) refers to the control of cerebral tissue blood flow (CBF) in response to changes in perfusion pressure. Due to the challenges of measuring intracranial pressure, CA is often described as the relationship between mean arterial pressure (MAP) and CBF. Dynamic CA (dCA) can be assessed using multiple techniques, with transfer function analysis (TFA) being the most common. A 2016 white paper by members of an international Cerebrovascular Research Network (CARNet) that is focused on CA strove to improve TFA standardization by way of introducing data acquisition, analysis, and reporting guidelines. Since then, additional evidence has allowed for the improvement and refinement of the original recommendations, as well as for the inclusion of new guidelines to reflect recent advances in the field. This second edition of the white paper contains more robust, evidence-based recommendations, which have been expanded to address current streams of inquiry, including optimizing MAP variability, acquiring CBF estimates from alternative methods, estimating alternative dCA metrics, and incorporating dCA quantification into clinical trials. Implementation of these new and revised recommendations is important to improve the reliability and reproducibility of dCA studies, and to facilitate inter-institutional collaboration and the comparison of results between studies.

Magnetoencephalography, the extracranial detection of tiny magnetic fields emanating from intracranial electrical activity of neurons, and its source modeling relation, magnetic source imaging, represent a powerful functional neuroimaging technique, able to detect and localize both spontaneous and evoked activity of the brain in health and disease. Recent years have seen an increased utilization of this technique for both clinical practice and research, in the United States and worldwide. This report summarizes current thinking, presents recommendations for clinical implementation, and offers an outlook for emerging new clinical indications., (© 2022 by American Journal of Neuroradiology.)

Three-dimensional visualization of cellular and subcellular-structures in histological-tissues is essential for understanding the complexities of biological-phenomena, especially with regards structural and spatial relationships and pathologlical-diagnosis. Recent advancements in tissue-clearing technology, such as Magnified Analysis of Proteome (MAP), have significantly improved our ability to study biological-structures in three-dimensional space; however, their wide applicability to a variety of tissues is limited by long incubation-times and a need for advanced imaging-systems that are not readily available in most-laboratories. Here, we present optimized MAP-based method for paper-thin samples, Paper-MAP, which allow for rapid clearing and subsequent imaging of three-dimensional sections derived from various tissues using conventional confocal-microscopy. Paper-MAP successfully clear tissues within 1-day, compared to the original-MAP, without significant differences in achieved optical-transparency. As a proof-of-concept, we investigated the vasculature and neuronal-networks of a variety of human and rodent tissues processed via Paper-MAP, in both healthy and diseased contexts, including Alzheimer's disease and glioma., (© 2021. The Author(s).)

Background: In previous decades, large-scale research has been carried out on bacterial meningitis. In every field, citation analysis is the most significant contribution. The study's objective was to identify and analyze the 100 articles on bacterial meningitis that received the most citations between 2000 and 2023, highlighting the most significant developments in the field. Objective: The objective of this study was to find out what makes a highly influential article by identifying and analyzing the characteristics of the 100 articles in the field of bacterial meningitis that receive the most citations. The goal of this study was to find and examine the 100 articles on bacterial meningitis that received the most citations. Methodology: We identified the top 100 most-cited papers in the field of bacterial meningitis from 55 journals using the Dimensions AI database. The results of each author's analysis of 100 articles were then compared. We gathered fundamental data such as the journal's title, country of publication, and study type. Descriptive counts or percentages were used to compare the various categories. Results: Between the year 2000 and the year 2023, articles were published. The total number of citations ranged from 115 to 1176, with 42 papers receiving more than 200 citations. In 2008, 14 articles were published, followed by 10 in 2000 and 2007. One thousand one hundred and seventy-six times were given to the most-cited paper, whereas 115 times were given to the least-cited article. "Clinical Features and Prognostic Factors in Adults with Bacterial Meningitis," by Diederik van de Beek, et al. (2004) was the article that received the most citations. 1176 people have cited this article. van de Beek Diederik of the Academic Medical Center in The Netherlands is the author who has written the most articles, was mentioned in 14 of the top 100 articles. Papers were primarily published in Pediatrics (n = 9) publication with 1861 citations. The Netherlands came in second with 18 publications, followed by the United States (n = 46). Conclusion: Our study uses bibliometrics and visualization analysis of the most important articles in this field to show the current state of research in the area of bacterial meningitis, provide a history of research trends, and offer a perspective for future bacterial predicts the growth of meningitis. [ABSTRACT FROM AUTHOR]

The neuromodulatory subcortical system (NSS) nuclei are critical hubs for survival, hedonic tone, and homeostasis. Tau-associated NSS degeneration occurs early in Alzheimer's disease (AD) pathogenesis, long before the emergence of pathognomonic memory dysfunction and cortical lesions. Accumulating evidence supports the role of NSS dysfunction and degeneration in the behavioral and neuropsychiatric manifestations featured early in AD. Experimental studies even suggest that AD-associated NSS degeneration drives brain neuroinflammatory status and contributes to disease progression, including the exacerbation of cortical lesions. Given the important pathophysiologic and etiologic roles that involve the NSS in early AD stages, there is an urgent need to expand our understanding of the mechanisms underlying NSS vulnerability and more precisely detail the clinical progression of NSS changes in AD. Here, the NSS Professional Interest Area of the International Society to Advance Alzheimer's Research and Treatment highlights knowledge gaps about NSS within AD and provides recommendations for priorities specific to clinical research, biomarker development, modeling, and intervention. HIGHLIGHTS: Neuromodulatory nuclei degenerate in early Alzheimer's disease pathological stages. Alzheimer's pathophysiology is exacerbated by neuromodulatory nuclei degeneration. Neuromodulatory nuclei degeneration drives neuropsychiatric symptoms in dementia. Biomarkers of neuromodulatory integrity would be value-creating for dementia care. Neuromodulatory nuclei present strategic prospects for disease-modifying therapies.

It is a growing concern that outcomes of neuroimaging studies often cannot be replicated. To counteract this, the magnetic resonance (MR) neuroimaging community has promoted acquisition standards and created data sharing platforms, based on a consensus on how to organize and share MR neuroimaging data. Here, we take a similar approach to positron emission tomography (PET) data. To facilitate comparison of findings across studies, we first recommend publication standards for tracer characteristics, image acquisition, image preprocessing, and outcome estimation for PET neuroimaging data. The co-authors of this paper, representing more than 25 PET centers worldwide, voted to classify information as mandatory, recommended, or optional. Second, we describe a framework to facilitate data archiving and data sharing within and across centers. Because of the high cost of PET neuroimaging studies, sample sizes tend to be small and relatively few sites worldwide have the required multidisciplinary expertise to properly conduct and analyze PET studies. Data sharing will make it easier to combine datasets from different centers to achieve larger sample sizes and stronger statistical power to test hypotheses. The combining of datasets from different centers may be enhanced by adoption of a common set of best practices in data acquisition and analysis.

Rabies is a lethal zoonotic encephalomyelitis that causes an estimated 59,000 human deaths yearly worldwide. Although developing countries of Asia and Africa bear the heaviest burden, surveillance and disease detection in these countries is often hampered by the absence of local laboratories able to diagnose rabies and/or the difficulties of sample shipment from low-access areas to national reference laboratories. Filter papers offer a convenient cost-effective alternative for the sampling, shipment, and storage of biological materials for the diagnosis of many pathogens including rabies virus, yet the properties of diagnostic tests using this support have not been evaluated thoroughly. Sensitivity and specificity of molecular diagnosis of rabies infection using a reverse transcription followed by a hemi-nested polymerase chain reaction (RT-hn-PCR) either directly on brain tissue or using brain tissue dried on filter paper were assessed on 113 suspected field animal samples in comparison to the direct fluorescent antibody test (FAT) recommended by the World Health Organization as one of the reference tests for rabies diagnosis. Impact of the duration of the storage was also evaluated. The sensitivity and the specificity of RT-hn-PCR i) on brain tissue were 96.6% (95% CI: [88.1-99.6]) and 92.7% (95% CI: [82.4-98.0]) respectively and ii) on brain tissue dried on filter paper 100% (95% CI: [93.8-100.0]) and 90.9% (95% CI: [80.0-97.0]) respectively. No loss of sensitivity of RT-hn-PCR on samples of brain tissue dried on filter paper left 7 days at ambient temperature was detected indicating that this method would enable analyzing impregnated filter papers sent to the national reference laboratory at ambient temperature within a 1-week shipment time. It could therefore be an effective alternative to facilitate storage and shipment of samples from low-access areas to enhance and expand rabies surveillance., Competing Interests: The authors have declared that no competing interests exist.

Background: Neurological injuries remain the leading cause of death in comatose patients resuscitated from out-of-hospital cardiac arrest (OHCA). Adequate blood pressure is of paramount importance to optimize cerebral perfusion and to minimize secondary brain injury. Markers measuring global cerebral ischemia caused by cardiac arrest and consecutive resuscitation and reflecting the metabolic variations after successful resuscitation are needed to assist a more individualized post-resuscitation care. Currently, no technique is available for bedside evaluation of global cerebral energy state, and until now blood pressure targets have been based on limited clinical evidence. Recent experimental and clinical studies indicate that it might be possible to evaluate cerebral oxidative metabolism from measuring the lactate-to-pyruvate (LP) ratio of the draining venous blood. In this study, jugular bulb microdialysis and immediate bedside biochemical analysis are introduced as new diagnostic tools to evaluate the effect of higher mean arterial blood pressure on global cerebral metabolism and the degree of cellular damage after OHCA., Methods/design: This is a single-center, randomized, double-blinded, superiority trial. Sixty unconscious patients with sustained return of spontaneous circulation after OHCA will be randomly assigned in a one-to-one fashion to low (63 mm Hg) or high (77 mm Hg) mean arterial blood pressure target. The primary end-point will be a difference in mean LP ratio within 48 h between blood pressure groups. Secondary end-points are (1) association between LP ratio and all-cause intensive care unit (ICU) mortality and (2) association between LP ratio and survival to hospital discharge with poor neurological function., Discussion: Markers measuring cerebral ischemia caused by cardiac arrest and consecutive resuscitation and reflecting the metabolic changes after successful resuscitation are urgently needed to enable a more personalized post-resuscitation care and prognostication. Jugular bulb microdialysis may provide a reliable global estimate of cerebral metabolic state and can be implemented as an entirely new and less invasive diagnostic tool for ICU patients after OHCA and has implications for early prognosis and treatment., Trial Registration: ClinicalTrials.gov (ClinicalTrials.gov Identifier: NCT03095742 ). Registered March 30, 2017.

The toxicity of pulp and paper mill effluents (PPMEs) has been greatly decreased, yet some continue to negatively affect fish reproduction. We hypothesized that PPMEs are affecting the brain resulting in decreased reproductive performance. Our goal was to use gene expression profiling to test the hypothesis that PPMEs are having an effect on neural systems in the fathead minnow (FHM; Pimephales promelas) in vivo. Sexually mature male and female FHM were exposed to 100% final biotreated PPMEs from 5 different sources for 5 days. Using an oligo-array (15K genes) we examined the effect of PPMEs on gene expression in the hypothalamus of female fish. We validated selected genes (cholecystokinin, RevErbbeta2, and urotensin I) that were identified by microarray analysis using real-time reverse-transcriptase polymerase chain reaction (RT-PCR). We compared the FHM microarray dataset to multiple microarray datasets from experiments conducted with goldfish injected with different dopaminergic pharmaceuticals to examine whether PPMEs could be affecting the dopamine system. Exposure of FHM to PPMEs resulted in varying degrees of spawning inhibition. Microarray analysis revealed surprisingly few genes in the brain that were commonly affected by the different PPMEs. Real-time RT-PCR confirmed the changes in expression for cholecystokinin, RevErbbeta2, and urotensin I. Comparison of the FHM and goldfish microarray datasets suggest that some PPMEs may be acting on the dopamine system. We show that PPMEs are neuroactive in fish and may be acting through some of the pathways in a manner similar to dopamine., (Copyright 2010 Elsevier B.V. All rights reserved.)

Heart failure (HF) is a complex clinical syndrome with multiple interactions between the failing myocardium and cerebral (dys-)functions. Bi-directional feedback interactions between the heart and the brain are inherent in the pathophysiology of HF: (i) the impaired cardiac function affects cerebral structure and functional capacity, and (ii) neuronal signals impact on the cardiovascular continuum. These interactions contribute to the symptomatic presentation of HF patients and affect many co-morbidities of HF. Moreover, neuro-cardiac feedback signals significantly promote aggravation and further progression of HF and are causal in the poor prognosis of HF. The diversity and complexity of heart and brain interactions make it difficult to develop a comprehensive overview. In this paper a systematic approach is proposed to develop a comprehensive atlas of related conditions, signals and disease mechanisms of the interactions between the heart and the brain in HF. The proposed taxonomy is based on pathophysiological principles. Impaired perfusion of the brain may represent one major category, with acute (cardio-embolic) or chronic (haemodynamic failure) low perfusion being sub-categories with mostly different consequences (i.e. ischaemic stroke or cognitive impairment, respectively). Further categories include impairment of higher cortical function (mood, cognition), of brain stem function (sympathetic over-activation, neuro-cardiac reflexes). Treatment-related interactions could be categorized as medical, interventional and device-related interactions. Also interactions due to specific diseases are categorized. A methodical approach to categorize the interdependency of heart and brain may help to integrate individual research areas into an overall picture., (© 2017 The Authors. European Journal of Heart Failure © 2017 European Society of Cardiology.)

The group of papers on memory reactivation and consolidation during sleep included in this volume represents cutting edge work in both animals and humans. They support that the two types of sleep serve different necessary functions. The role of slow wave sleep (SWS) is reactivation of the hippocampal-neocortical circuits activated during a waking learning period, while REM sleep is responsible for the consolidation of this new learning into long-term memory. These studies provide further insights into mechanisms involved in brain plasticity. Robeiro has demonstrated the upregulation of an immediate-early gene (IEG zif 268) to waking levels, which occurs only in REM and only in connection with new learning. McNaughton and his group have identified electrical indicators that the hippocampus and neocortex are talking to each other by testing the coactivation of hippocampal sharp wave bursts in SWS and shifts from down to up states of activation in the neocortex. In human studies Smith's group reports work on individual differences such as intelligence and presleep alcohol that affect postsleep performance, and Stickgold and collaborators report that a short nap will improve performance if it contains REM sleep. Payne and Nadel suggest that the recall benefit associated with REM sleep may be due to its association with increased cortisol levels. These papers are important not only in their individual contributions but also in revitalizing the work coordinating waking and sleep. This promises to further the understanding of how our unique capacity to learn from experience and modify our behavior takes place.

We compared species mean data on the size of functionally distinct brain regions to test the relative rates at which investment in higher-order cognitive processing (mushroom body calyces) versus peripheral sensory processing (optic and antennal lobes) increased with increasing brain size. Subjects were eusocial paper wasps from queen and worker castes of 10 species from different genera. Relative investment in central processing tissue increased with brain size at a higher rate than peripheral structure investment, demonstrating that tissue devoted to higher-order cognitive processing is more constrained by brain size. This pattern held for raw data and for phylogenetically independent contrasts. These findings suggest that there is a minimum necessary investment in peripheral sensory processing brain tissue, with little to gain from additional investment. In contrast, increased brain size provides opportunities to invest in additional higher-order cognitive processing tissue. Reproductive castes differed within species in brain tissue investment, with higher central-to-peripheral brain tissue ratios in queens than in workers. Coupled with previous findings that paper wasp queen, but not worker, brain architecture corresponds to ecological and social variation, queen brain evolution appears to be most strongly shaped by cognitive demands, such as social interactions. These evolutionary patterns of neural investment echo findings in other animal lineages and have important implications, given that a greater investment in higher-order processing has been shown to increase the prevalence of complex and flexible behaviors across the animal kingdom.

Comparative sociogenomics has the potential to provide important insights into how social behaviour evolved. We examined brain gene expression profiles of the primitively eusocial wasp Polistes metricus and compared the results with a growing base of brain gene expression information for the advanced eusocial honeybee, Apis mellifera. We studied four female wasp groups that show variation in foraging/provisioning behaviour and reproductive status, using our newly developed microarray representing approximately 3248 P. metricus genes based on sequences generated from high-throughput pyrosequencing. We found differences in the expression of approximately 389 genes across the four groups. Pathways known from Drosophila melanogaster to be related to lipid metabolism, heat and stress response, and various forms of solitary behaviour were associated with behavioural differences among wasps. Forty-five per cent of differentially expressed transcripts showed significant associations with foraging/provisioning status, and 14 per cent with reproductive status. By comparing these two gene lists with lists of genes previously shown to be differentially expressed in association with honeybee division of labour, we found a significant overlap of genes associated with foraging/provisioning, but not reproduction, across the two species. These results suggest common molecular roots for foraging division of labour in two independently evolved social insect species and the possibility of more lineage-specific roots of reproductive behaviour. We explore the implications of these findings for the idea that there is a conserved 'genetic toolkit' for division of labour across multiple lineages.

The last decade has seen a considerable increase in the application of quantitative methods in the study of histological sections of brain tissue and especially in the study of neurodegenerative disease. These disorders are characterised by the deposition and aggregation of abnormal or misfolded proteins in the form of extracellular protein deposits such as senile plaques (SP) and intracellular inclusions such as neurofibrillary tangles (NFT). Quantification of brain lesions and studying the relationships between lesions and normal anatomical features of the brain, including neurons, glial cells, and blood vessels, has become an important method of elucidating disease pathogenesis. This review describes methods for quantifying the abundance of a histological feature such as density, frequency, and 'load' and the sampling methods by which quantitative measures can be obtained including plot/quadrant sampling, transect sampling, and the point-quarter method. In addition, methods for determining the spatial pattern of a histological feature, i.e., whether the feature is distributed at random, regularly, or is aggregated into clusters, are described. These methods include the use of the Poisson and binomial distributions, pattern analysis by regression, Fourier analysis, and methods based on mapped point patterns. Finally, the statistical methods available for studying the degree of spatial correlation between pathological lesions and neurons, glial cells, and blood vessels are described.

The cognitive challenges that social animals face depend on species differences in social organization and may affect mosaic brain evolution. We asked whether the relative size of functionally distinct brain regions corresponds to species differences in social behaviour among paper wasps (Hymenoptera: Vespidae). We measured the volumes of targeted brain regions in eight species of paper wasps. We found species variation in functionally distinct brain regions, which was especially strong in queens. Queens from species with open-comb nests had larger central processing regions dedicated to vision (mushroom body (MB) calyx collars) than those with enclosed nests. Queens from advanced eusocial species (swarm founders), who rely on pheromones in several contexts, had larger antennal lobes than primitively eusocial independent founders. Queens from species with morphologically distinct castes had augmented central processing regions dedicated to antennal input (MB lips) relative to caste monomorphic species. Intraspecific caste differences also varied with mode of colony founding. Independent-founding queens had larger MB collars than their workers. Conversely, workers in swarm-founding species with decentralized colony regulation had larger MB calyx collars and optic lobes than their queens. Our results suggest that brain organization is affected by evolutionary transitions in social interactions and is related to the environmental stimuli group members face.

Evans et al. and Mekel-Bobrov et al. (Reports, 9 September 2005, p. 1717 and 1720, respectively) reported that human genetic variants of Microcephalin (MCPH1) and abnormal spindle-like microcephaly associated (ASPM) are under strong positive selection. We genotyped these variants in 9000 children and find no meaningful associations with brain size and various cognitive measures, which indicates that contrary to previous speculations, ASPM and MCPH1 have not been selected for brain-related effects.

Carrying out any everyday task, be it driving in traffic, conversing with friends or playing basketball, requires rapid selection, integration and segregation of stimuli from different sensory modalities. At present, even the most advanced artificial intelligence-based systems are unable to replicate the multisensory processes that the human brain routinely performs, but how neural circuits in the brain carry out these processes is still not well understood. In this Perspective, we discuss recent findings that shed fresh light on the oscillatory neural mechanisms that mediate multisensory integration (MI), including power modulations, phase resetting, phase-amplitude coupling and dynamic functional connectivity. We then consider studies that also suggest multi-timescale dynamics in intrinsic ongoing neural activity and during stimulus-driven bottom-up and cognitive top-down neural network processing in the context of MI. We propose a new concept of MI that emphasizes the critical role of neural dynamics at multiple timescales within and across brain networks, enabling the simultaneous integration, segregation, hierarchical structuring and selection of information in different time windows. To highlight predictions from our multi-timescale concept of MI, real-world scenarios in which multi-timescale processes may coordinate MI in a flexible and adaptive manner are considered., (© 2024. Springer Nature Limited.)

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The initial study, ADNI-1, enrolled 400 subjects with early mild cognitive impairment (MCI), 200 with early AD, and 200 cognitively normal elderly controls. ADNI-1 was extended by a 2-year Grand Opportunities grant in 2009 and by a competitive renewal, ADNI-2, which enrolled an additional 550 participants and will run until 2015. This article reviews all papers published since the inception of the initiative and summarizes the results to the end of 2013. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are largely consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimer's Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers select and combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, amyloid PET, CSF biomarkers, and clinical tests; (4) the development of blood biomarkers for AD as potentially noninvasive and low-cost alternatives to CSF biomarkers for AD diagnosis and the assessment of α-syn as an additional biomarker; (5) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects and are leading candidates for the detection of AD in its preclinical stages; (6) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Multimodal methods incorporating APOE status and longitudinal MRI proved most highly predictive of future decline. Refinements of clinical tests used as outcome measures such as clinical dementia rating-sum of boxes further reduced sample sizes; (7) the pioneering of genome-wide association studies that leverage quantitative imaging and biomarker phenotypes, including longitudinal data, to confirm recently identified loci, CR1, CLU, and PICALM and to identify novel AD risk loci; (8) worldwide impact through the establishment of ADNI-like programs in Japan, Australia, Argentina, Taiwan, China, Korea, Europe, and Italy; (9) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker and clinical data to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (10) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world.

Understanding communication and information processing in nervous systems is a central goal of neuroscience. Over the past two decades, advances in connectomics and network neuroscience have opened new avenues for investigating polysynaptic communication in complex brain networks. Recent work has brought into question the mainstay assumption that connectome signalling occurs exclusively via shortest paths, resulting in a sprawling constellation of alternative network communication models. This Review surveys the latest developments in models of brain network communication. We begin by drawing a conceptual link between the mathematics of graph theory and biological aspects of neural signalling such as transmission delays and metabolic cost. We organize key network communication models and measures into a taxonomy, aimed at helping researchers navigate the growing number of concepts and methods in the literature. The taxonomy highlights the pros, cons and interpretations of different conceptualizations of connectome signalling. We showcase the utility of network communication models as a flexible, interpretable and tractable framework to study brain function by reviewing prominent applications in basic, cognitive and clinical neurosciences. Finally, we provide recommendations to guide the future development, application and validation of network communication models., (© 2023. Springer Nature Limited.)

A growing body of evidence indicates the existence of abnormal local and long-range functional connection patterns in patients with alcohol use disorder (AUD). However, it has yet to be established whether AUD is associated with abnormal interhemispheric and intrahemispheric functional connection patterns. In the present study, we analysed resting-state functional magnetic resonance imaging data from 55 individuals with AUD and 32 healthy nonalcohol users. For each subject, whole-brain functional connectivity density (FCD) was decomposed into ipsilateral and contralateral parts. Correlation analysis was performed between abnormal FCD and a range of clinical measurements in the AUD group. Compared with healthy controls, the AUD group exhibited a reduced global FCD in the anterior and middle cingulate gyri, prefrontal cortex and thalamus, along with an enhanced global FCD in the temporal, parietal and occipital cortices. Abnormal interhemispheric and intrahemispheric FCD patterns were also detected in the AUD group. Furthermore, abnormal global, contralateral and ipsilateral FCD data were correlated with the mean amount of pure alcohol and the severity of alcohol addiction in the AUD group. Collectively, our findings indicate that global, interhemispheric and intrahemispheric FCD may represent a robust method to detect abnormal functional connection patterns in AUD; this may help us to identify the neural substrates and therapeutic targets of AUD., (© 2024 The Authors. Addiction Biology published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction.)

Vascular aging influences hemodynamics, elevating risks for vascular diseases and dementia. We recently demonstrated that knockout (KO) of Dusp5 enhances cerebral and renal hemodynamics and cognitive function. This improvement correlates with elevated pPKC and pERK1/2 levels in the brain and kidneys. Additionally, we observed that Dusp5 KO modulates the passive mechanical properties of cerebral and renal arterioles, associated with increased myogenic tone at low pressure, enhanced distensibility, greater compliance, and reduced stiffness. The present study evaluates the structural and mechanical properties of the middle cerebral artery (MCA) in Dusp5 KO rats. We found that vascular smooth muscle cell layers and the collagen content in the MCA wall are comparable between Dusp5 KO and control rats. The internal elastic lamina in the MCA of Dusp5 KO rats exhibits increased thickness, higher autofluorescence intensity, smaller fenestrae areas, and fewer fenestrations. Despite an enhanced myogenic response and tone of the MCA in Dusp5 KO rats, other passive mechanical properties, such as wall thickness, cross-sectional area, wall-to-lumen ratio, distensibility, incremental elasticity, circumferential wall stress, and elastic modulus, do not significantly differ between strains. These findings suggest that while Dusp5 KO has a limited impact on altering the structural and mechanical properties of MCA, its primary role in ameliorating hemodynamics and cognitive functions is likely attributable to its enzymatic activity on cerebral arterioles. Further research is needed to elucidate the specific enzymatic mechanisms and explore potential clinical applications in the context of vascular aging., (© 2024. The Author(s), under exclusive licence to American Aging Association.)

Biomedical research on the brain has led to many discoveries and developments, such as understanding human consciousness and the mind and overcoming brain diseases. However, historical biomedical research on the brain has unique characteristics that differ from those of conventional biomedical research. For example, there are different scientific interpretations due to the high complexity of the brain and insufficient intercommunication between researchers of different disciplines owing to the limited conceptual and technical overlap of distinct backgrounds. Therefore, the development of biomedical research on the brain has been slower than that in other areas. Brain biomedical research has recently undergone a paradigm shift, and conducting patient-centered, large-scale brain biomedical research has become possible using emerging high-throughput analysis tools. Neuroimaging, multiomics, and artificial intelligence technology are the main drivers of this new approach, foreshadowing dramatic advances in translational research. In addition, emerging interdisciplinary cooperative studies provide insights into how unresolved questions in biomedicine can be addressed. This review presents the in-depth aspects of conventional biomedical research and discusses the future of biomedical research on the brain., (© 2024. The Author(s).)

To model behavioral and neural correlates of language comprehension in naturalistic environments, researchers have turned to broad-coverage tools from natural-language processing and machine learning. Where syntactic structure is explicitly modeled, prior work has relied predominantly on context-free grammars (CFGs), yet such formalisms are not sufficiently expressive for human languages. Combinatory categorial grammars (CCGs) are sufficiently expressive directly compositional models of grammar with flexible constituency that affords incremental interpretation. In this work, we evaluate whether a more expressive CCG provides a better model than a CFG for human neural signals collected with functional magnetic resonance imaging (fMRI) while participants listen to an audiobook story. We further test between variants of CCG that differ in how they handle optional adjuncts. These evaluations are carried out against a baseline that includes estimates of next-word predictability from a transformer neural network language model. Such a comparison reveals unique contributions of CCG structure-building predominantly in the left posterior temporal lobe: CCG-derived measures offer a superior fit to neural signals compared to those derived from a CFG. These effects are spatially distinct from bilateral superior temporal effects that are unique to predictability. Neural effects for structure-building are thus separable from predictability during naturalistic listening, and those effects are best characterized by a grammar whose expressive power is motivated on independent linguistic grounds., (© 2023 The Authors. Cognitive Science published by Wiley Periodicals LLC on behalf of Cognitive Science Society (CSS).)

The prediction of physical ability is a key point to understand the physical training effect of college students. This paper uses the error Back Propagation neural network algorithms to investigate the college students' physical test results, and predicts the future trends of the results. The findings indicate that, in future ten years, the physical test grades of both men and women will slip to a certain extent. It implies that the indicators of speed, power, endurance level and physical strength of college students keep going down. This phenomenon should be paid attention to. It is necessary to strength the exercise consciousness, and stimulates the enthusiasm of students' exercise.