Hasil untuk "Neurophysiology and neuropsychology"

Anna Blasi Ribera, Borja Blanco Maniega, Samantha McCann et al.

As infants and young children learn from and respond to their environment, their development is driven by their ability to filter out irrelevant stimuli and respond to salient stimuli. While sources and types of stimuli vary across cultural contexts, research to understand the neural mechanisms of these behaviors have largely focused on relatively homogeneous populations in high income settings. To address this lack of diverse representation the Brain Imaging for Global health project (BRIGHT) collected longitudinal data in The Gambia (N = 204) and the UK (N = 61). Here we present results of the Habituation and Novelty Detection (HaND) fNIRS neuroimaging task. Gambian infants showed persistent response suppression (Habituation) at all visits (from 5mo to 60mo) while Novelty Detection was only observed once infants reached 18 and 24mo. In the UK, infants only showed persistent habituation from 5 to 12mo, while the response was not evident at 18 and 24mo. Furthermore, in contrast to The Gambia, alongside the habituation patterns observed Uk infants showed novelty detection from 5 to 12mo. This is the first longitudinal description of the HaND response in individuals from different contextual backgrounds across such a broad age range and number of time points, revealing different patterns of specialization in The Gambia and UK.

Yu Liu, Songjun Peng, Xinran Wu et al.

Adolescence is a critical period for brain development, yet the impact of peer environments on brain structure, cognition, and psychopathology remains poorly understood. Here, we capitalized on data from 7806 adolescents (age = 12.02 ± 0.67) from the Adolescent Brain Cognitive Development (ABCD) study, to determine associations between two distinct peer environments (proportion of prosocial or delinquent friends) and the structural and functional architecture of the brain, cognition, as well as behavioral and emotional dysregulation. A higher proportion of prosocial friends was associated with fewer behavioral problems and larger fronto-cingulate and striatal regions. In contrast, a higher proportion of delinquent friends was linked to increased behavioral problems, lower neurocognitive performance, and decreased functional connectivity in the default-mode and fronto-striato-limbic circuits, which spatially overlapped with external dopamine density maps. Moreover, the associations between prosocial friends and behaviors were mediated by brain volumes (e.g., pallidum), while the associations between delinquent friends and behaviors were primarily mediated by fronto-striato-limbic connectivity. Prosocial friends also attenuated the development of internalizing problems, whereas delinquent friends promoted externalizing symptoms. These findings underscore the profound influence of peer environments on adolescent brain development and mental health, highlighting the need for early interventions to promote resilience and healthy neuro-maturation.

David Koplow, Tomaso Poggio, Liu Ziyin

Hebbian and anti-Hebbian plasticity are widely observed in the biological brain, yet their theoretical understanding remains limited. In this work, we find that when a learning method is regularized with L2 weight decay, its learning signal will gradually align with the direction of the Hebbian learning signal as it approaches stationarity. This Hebbian-like behavior is not unique to SGD: almost any learning rule, including random ones, can exhibit the same signature long before learning has ceased. We also provide a theoretical explanation for anti-Hebbian plasticity in regression tasks, demonstrating how it can arise naturally from gradient or input noise, and offering a potential reason for the observed anti-Hebbian effects in the brain. Certainly, our proposed mechanisms do not rule out any conventionally established forms of Hebbian plasticity and could coexist with them extensively in the brain. A key insight for neurophysiology is the need to develop ways to experimentally distinguish these two types of Hebbian observations.

Moshe Unger, Alexander Tuzhilin, Michel Wedel

The present work proposes a Deep Learning architecture for the prediction of various consumer choice behaviors from time series of raw gaze or eye fixations on images of the decision environment, for which currently no foundational models are available. The architecture, called STARE (Spatio-Temporal Attention Representation for Eye Tracking), uses a new tokenization strategy, which involves mapping the x- and y- pixel coordinates of eye-movement time series on predefined, contiguous Regions of Interest. That tokenization makes the spatio-temporal eye-movement data available to the Chronos, a time-series foundation model based on the T5 architecture, to which co-attention and/or cross-attention is added to capture directional and/or interocular influences of eye movements. We compare STARE with several state-of-the art alternatives on multiple datasets with the purpose of predicting consumer choice behaviors from eye movements. We thus make a first step towards developing and testing DL architectures that represent visual attention dynamics rooted in the neurophysiology of eye movements.

Zhang D, She Y, Sun J et al.

Di Zhang,1,2 Yichong She,1,2 Jinbo Sun,1,2 Yapeng Cui,1,2 Xuejuan Yang,1,2 Xiao Zeng,1,2 Wei Qin1,2 1Engineering Research Center of Molecular and Neuro Imaging of the Ministry of Education, School of Life Science and Technology, Xidian University, Xi’an, Shaanxi, 710126, People’s Republic of China; 2Intelligent Non-Invasive Neuromodulation Technology and Transformation Joint Laboratory, Xidian University, Xi’an, People’s Republic of ChinaCorrespondence: Xiao Zeng, Xidian University, 266 Xifeng Road, Xinglong, Xi’an, Shaanxi, People’s Republic of China, 710126, Email xiaozeng1024@gmail.comPurpose: This study aims to improve brain age estimation by developing a novel deep learning model utilizing overnight electroencephalography (EEG) data.Methods: We address limitations in current brain age prediction methods by proposing a model trained and evaluated on multiple cohort data, covering a broad age range. The model employs a one-dimensional Swin Transformer to efficiently extract complex patterns from sleep EEG signals and a convolutional neural network with attentional mechanisms to summarize sleep structural features. A multi-flow learning-based framework attentively merges these two features, employing sleep structural information to direct and augment the EEG features. A post-prediction model is designed to integrate the age-related features throughout the night. Furthermore, we propose a DecadeCE loss function to address the problem of an uneven age distribution.Results: We utilized 18,767 polysomnograms (PSGs) from 13,616 subjects to develop and evaluate the proposed model. The model achieves a mean absolute error (MAE) of 4.19 and a correlation of 0.97 on the mixed-cohort test set, and an MAE of 6.18 years and a correlation of 0.78 on an independent test set. Our brain age estimation work reduced the error by more than 1 year compared to other studies that also used EEG, achieving the level of neuroimaging. The estimated brain age index demonstrated longitudinal sensitivity and exhibited a significant increase of 1.27 years in individuals with psychiatric or neurological disorders relative to healthy individuals.Conclusion: The multi-flow deep learning model proposed in this study, based on overnight EEG, represents a more accurate approach for estimating brain age. The utilization of overnight sleep EEG for the prediction of brain age is both cost-effective and adept at capturing dynamic changes. These findings demonstrate the potential of EEG in predicting brain age, presenting a noninvasive and accessible method for assessing brain aging.Keywords: brain age, sleep polysomnography, electroencephalography, deep learning, swin transformer

Helen Close, Sharon Vincent, Hayley Alderson et al.

Objectives and methods Anecdotal evidence suggests a high prevalence of hoarding behaviours among care-experienced children (those in foster, residential, adoptive, or kinship care). This systematic review, aimed to examine the prevalence of hoarding among care-experienced children, their lived experience, and the effectiveness of any hoarding interventions for this population. Primary research articles were included on hoarding behaviours in care-experienced children, published in English in indexed journals from ever to September 2024.Results Three eligible uncontrolled, observational studies, including 374 children and 23 carers, were identified. While hoarding was not clearly defined, there were high levels of hoarding behaviours specific to storing food (26%), associated with confirmed maltreatment in care (Odds Ratio = 17.4). Empirical lived experience perspectives were few and polarised between views that food hoarding was punishment towards caregivers or a trauma-survival mechanism. We identified no interventions involving assessment or management of hoarding behaviours in this population.Conclusions There is a paucity of evidence about hoarding behaviours among care-experienced children and a small amount of poor-quality evidence suggesting a high prevalence of food-related hoarding. In contrast, stakeholder consultation suggests hoarding may be common, long-lasting, and involve not just food but many other objects. Further research is required to understand the extent and type of hoarding behaviours, and effective interventions. Care-experienced children experience health, educational, and well-being outcomes across the life course, which are much poorer than their non-care peers, and this research offers a new avenue of enquiry to understand and improve their experiences and lives.

M. Ram Murty, A. Narayan Prasad

Current concepts of neural networks have emerged over two centuries of progress beginning with the neural doctrine to the idea of neural cell assemblies. Presently the model of neural networks involves distributed neural circuits of nodes, hubs, and connections that are dynamic in different states of brain function. Advances in neurophysiology, neuroimaging and the field of connectomics have given impetus to the application of mathematical concepts of graph theory. Current approaches do carry limitations and inconsistency in results achieved. We model the neural network of the brain as a directed graph and attach a matrix (called the Markov matrix) of transition probabilities (determined by the synaptic strengths) to every pair of distinct nodes giving rise to a (continuous) Markov process. We postulate that the network hubs are the nodes with the highest probabilities given by the stationary distribution of Markov theory. We also derive a new upper bound for the diameter of a graph in terms of the eigenvalues of the Markov matrix.

Laurent Goffart

At the turn of the 20th century, Henri Poincar{é} explained that geometry is a convention and that the properties of space and time are the properties of our measuring instruments. Intriguingly, numerous contemporary authors argue that space, time and even number are ''encoded'' within the brain, as a consequence of evolution, adaptation and natural selection. In the neuroscientific study of movement generation, the activity of neurons would ''encode'' kinematic parameters: when they emit action potentials, neurons would ''speak'' a language carrying notions of classical mechanics. In this article, we shall explain that the movement of a body segment is the ultimate product of a measurement, a filtered numerical outcome of multiple processes taking place in parallel in the central nervous system and converging on the groups of neurons responsible for muscle contractions. The fact that notions of classical mechanics efficiently describe movements does not imply their implementation in the inner workings of the brain. Their relevance to the question how the brain activity enables one to produce accurate movements is questioned within the framework of the neurophysiology of orienting gaze movements toward a visual target.

Vitória Piai, Dilys Eikelboom

AbstractLesion-symptom mapping (LSM) studies have revealed brain areas critical for naming, typically finding significant associations between damage to left temporal, inferior parietal, and inferior fontal regions and impoverished naming performance. However, specific subregions found in the available literature vary. Hence, the aim of this study was to perform a systematic review and meta-analysis of published lesion-based findings, obtained from studies with unique cohorts investigating brain areas critical for accuracy in naming in stroke patients at least 1 month post-onset. An anatomic likelihood estimation (ALE) meta-analysis of these LSM studies was performed. Ten papers entered the ALE meta-analysis, with similar lesion coverage over left temporal and left inferior frontal areas. This small number is a major limitation of the present study. Clusters were found in left anterior temporal lobe, posterior temporal lobe extending into inferior parietal areas, in line with the arcuate fasciculus, and in pre- and postcentral gyri and middle frontal gyrus. No clusters were found in left inferior frontal gyrus. These results were further substantiated by examining five naming studies that investigated performance beyond global accuracy, corroborating the ALE meta-analysis results. The present review and meta-analysis highlight the involvement of left temporal and inferior parietal cortices in naming, and of mid to posterior portions of the temporal lobe in particular in conceptual-lexical retrieval for speaking.

Attila Kolonics, Zoltán Bori, Ferenc Torma et al.

Abstract Background It has been suggested that exercise training and postbiotic supplement could decelerate the progress of functional and biochemical deterioration in double transgenic mice overexpresses mutated forms of the genes for human amyloid precursor protein (APPsw) and presenilin 1 (m146L) (APP/PS1TG). Our earlier published data indicated that the mice performed better than controls on the Morris Maze Test parallel with decreased occurrence of amyloid-β plaques in the hippocampus. We investigated the neuroprotective and therapeutic effects of high-intensity training and postbiotic supplementation. Methods Thirty-two adult APP/PS1TG mice were randomly divided into four groups: (1) control, (2) high-intensity training (3) postbiotic, (4) combined (training and postbiotic) treatment for 20 weeks. In this study, the whole hemibrain without hippocampus was used to find molecular traits explaining improved brain function. We applied qualitative RT-PCR for gene expression, Western blot for protein level, and Zymography for LONP1 activity. Disaggregation analysis of Aβ-40 was performed in the presence of Lactobacillus acidophilus and Bifidobacterium longum lysate. Results We found that exercise training decreased Alzheimer’s Disease (AD)-related gene expression (NF-kB) that was not affected by postbiotic treatment. The preparation used for postbiotic treatment is composed of tyndallized Bifidobacterium longum and Lactobacillus acidophilus. Both of the postbiotics effectively disaggregated amyloid-β/Aβ-40 aggregates by chelating Zn2+ and Cu2+ ions. The postbiotic treatment decreased endogenous human APPTG protein expression and mouse APP gene expression in the hemibrains. In addition, the postbiotic treatment elevated mitochondrial LONP1 activity as well. Conclusion Our findings revealed distinct mechanisms behind improved memory performance in the whole brain: while exercise training modulates NF-kB signaling pathway regulating immune response until postbiotic diminishes APP gene expression, disaggregates pre-existing amyloid-β plaques and activates mitochondrial protein quality control in the region of brain out of hippocampus. Using the above treatments complements and efficiently slows down the development of AD.

Yi Pan, Christopher Laohathai, Daniel J. Weber

EEG monitoring in the ICU is essential for diagnosing seizures in critically ill patients. Neurology residents are the frontline for rapid diagnosis of seizures. Residents received EEG training through didactic lectures and their epilepsy rotations. We hypothesized that seizure recognition was dependent on epilepsy rotation, not the seniority of the residency. Residents were taught ACNS Standardized Critical Care EEG Terminology, unified EEG terminology and criteria for non-convulsive status epilepticus. EEG segments were given to residents for seizure recognition, and explanations provided to residents after each test. Anonymous results with the postgraduate training year (PGY) and time spent in epilepsy rotation were collected. These tests were conducted 3 times, with total of 48 EEG segments, between October, 2017 and May, 2019. There were 43 participates, including 4 PGY-1 (9.3%), 20 PGY-2 (46.5%), 12 PGY-3 (27.9%), and 7 PGY-4 (16.3%) residents. The mean rate of seizure recognition was 57.1% in PGY-1, 63.8% in PGY-2, 58.4% in PGY-3, and 70.1% in PGY-4. Comparing the duration of epilepsy rotations, the mean correct scores of seizure recognition were 58.6%, 64.6%, 64.4%, and 67.3% for duration at 0, 0.5, 1, and 2 months respectively. There was no significant difference regarding the PGY or the time of epilepsy rotation statistically by ANOVA (p = 0.37). Seizure recognition in the EEG of a critically ill patient is not solely dependent time spent in epilepsy rotation or stage of residency training. EEG interpretation skill may require an alternate approach, and continuous training.

Nadia Chernyak, Bertilia Y. Trieu, Tamar Kushnir

Mohammad Ali Ameri, Ayatolla Fathi, Saeid Sharifi Rahnmo et al.

Aim and Background: Women, as half of human resources in societies, are an effective factor in advancing the goals of society and the family. Studies show that women are more vulnerable to poverty and discrimination than men. Now, Unattended women are exposed to all kinds of social harms due to excessive responsibility, lack of familiarity with some social skills, lack of access to resources and consequently poor quality of life, as well as loss of network of relationships and responsibilities of dependents. Therefore, the present study was conducted to identify the effectiveness of acceptance and commitment therapy on psychosocial security, happiness and mental health of unattended women. Methods and Materials: The research design was a quasi-experimental pretest-posttest with a control group. The statistical population of unattended women is covered by the Imam Khomeini Relief Committee in Kalibar city in 1399. From this population, 40 people were selected by purposive sampling and studied. So that 40 women were randomly divided into 2 groups: experimental (20) and control (20). The Maslow (1992) Psychosocial Security Questionnaire, Arhil & Lou (1990) Happiness and Goldberg (2008) Mental Health Questionnaire were used to collect data. Data were analyzed by analysis of covariance. Findings: The results showed; Acceptance and commitment therapy has an effect on psychosocial security, happiness and mental health of Unattended women and increases psychosocial security and happiness and decreases mental health in Unattended women (lower score indicates higher mental health). Conclusions: Therefore, according to the research findings, it can be said; Institutions provide the conditions for free psychological interventions, including acceptance and commitment treatment, along with appropriate economic, educational, and cultural support for these families so that Unattended women can have a positive assessment of their social status and have favorable conditions.

Mary A. O'Neal, Barbara A. Dworetzky, Gaston Baslet

Patients with a functional neurological disorder can be difficult to engage in treatment. The reasons for this are complex and may be related to physician, patient and health care system issues. Providers contribute to difficulties in treatment engagement by giving confusing explanations for the patient symptoms, stigmatizing patients, and not allowing patients time to voice their questions and concerns. Patient factors include a lack of engagement after an explanation of the diagnosis, resistance to treatment, family/work dynamics and prior negative experiences with the health care system. The scarcity of providers skilled in the treatment of functional neurological disorder is yet another hurdle. This article will define these barriers and discuss good clinical practices to help improve outcomes by tackling those challenges and discuss why for many patients an integrated care team approach is needed.

Pascal Fries, Eric Maris

The field of in-vivo neurophysiology currently uses statistical standards that are based on tradition rather than formal analysis. Typically, data from two (or few) animals are pooled for one statistical test, or a significant test in a first animal is replicated in one (or few) further animals. The use of more than one animal is widely believed to allow an inference on the population. Here, we explain that a useful inference on the population would require larger numbers and a different statistical approach. The field should consider to perform studies at that standard, potentially through coordinated multi-center efforts, for selected questions of exceptional importance. Yet, for many questions, this is ethically and/or economically not justifiable. We explain why in those studies with two (or few) animals, any useful inference is limited to the sample of investigated animals, irrespective of whether it is based on few animals, two animals or a single animal.

Nicholas Pestell, Thom Griffith, Nathan F. Lepora

For robot touch to converge with the human sense of touch, artificial transduction should involve biologically-plausible population codes analogous to those of natural afferents. Using a biomimetic tactile sensor with 3d-printed skin based on the dermal-epidermal boundary, we propose two novel feature sets to mimic slowly-adapting and rapidly-adapting type-I tactile mechanoreceptor function. Their plausibility is tested with three classic experiments from the study of natural touch: impingement on a flat plate to probe adaptation and spatial modulation; stimulation by spatially-complex ridged stimuli to probe single afferent responses; and perception of grating orientation to probe the population response. Our results show a match between artificial and natural afferent responses in their sensitivity to edges and gaps; likewise, the human and robot psychometric functions match for grating orientation. These findings could benefit robot manipulation, prosthetics and the neurophysiology of touch.

Corinna Laube, Robert Lorenz, Wouter van den Bos

Recent self-report and behavioral studies have demonstrated that pubertal testosterone is related to an increase in risky and impulsive behavior. Yet, the mechanisms underlying such a relationship are poorly understood. Findings from both human and rodent studies point towards distinct striatal pathways including the ventral and dorsal striatum as key target regions for pubertal hormones. In this study we investigated task-related impatience of boys between 10 and 15 years of age (N = 75), using an intertemporal choice task combined with measures of functional magnetic resonance imaging and hormonal assessment. Increased levels of testosterone were associated with a greater response bias towards choosing the smaller sooner option. Furthermore, our results show that testosterone specifically modulates the dorsal, not ventral, striatal pathway. These results provide novel insights into our understanding of adolescent impulsive and risky behaviors and how pubertal hormones are related to neural processes.

Allison Woodruff, Yasmin Asare Anderson, Katherine Jameson Armstrong et al.

Algorithmic systems are increasingly deployed to make decisions in many areas of people's lives. The shift from human to algorithmic decision-making has been accompanied by concern about potentially opaque decisions that are not aligned with social values, as well as proposed remedies such as explainability. We present results of a qualitative study of algorithmic decision-making, comprised of five workshops conducted with a total of 60 participants in Finland, Germany, the United Kingdom, and the United States. We invited participants to reason about decision-making qualities such as explainability and accuracy in a variety of domains. Participants viewed AI as a decision-maker that follows rigid criteria and performs mechanical tasks well, but is largely incapable of subjective or morally complex judgments. We discuss participants' consideration of humanity in decision-making, and introduce the concept of 'negotiability,' the ability to go beyond formal criteria and work flexibly around the system.

Sanket S. Kalamkar, Fuad M. Abinader, François Baccelli et al.

Beam management is central in the operation of dense 5G cellular networks. Focusing the energy radiated to mobile terminals (MTs) by increasing the number of beams per cell increases signal power and decreases interference, and has hence the potential to bring major improvements on area spectral efficiency (ASE). This benefit, however, comes with unavoidable overheads that increase with the number of beams and the MT speed. This paper proposes a first system-level stochastic geometry model encompassing major aspects of the beam management problem: frequencies, antennas, and propagation; physical layer, wireless links, and coding; network geometry, interference, and resource sharing; sensing, signaling, and mobility management. This model leads to a simple analytical expression for the effective ASE that the typical user gets in this context. This in turn allows one to find, for a wide variety of 5G network scenarios including millimeter wave (mmWave) and sub-6 GHz, the number of beams per cell that offers the best global trade-off between these benefits and costs. We finally provide numerical results that discuss the effects of different systemic trade-offs and performances of mmWave and sub-6 GHz 5G deployments.

Walter L. Arias Gallegos, Renzo Rivera, Mariela Laura Colque

En el presente trabajo se analizaron las diferencias en el desarrollo neuropsicológico según la lateralidad manual, pedal y ocular. Para ello se evaluó a 140 niños con una media de 76 meses de edad, de ambos sexos, equilibrados según sean monolingües y bilingües y su lugar de procedencia, de zonas rurales y urbanas de Arequipa. Se aplicó el Cuestionario de Madurez Neuropsicológica Infantil (CUMANIN) de Portellano et al. (2000). Los resultados indican que no existen diferencias significativas en el desarrollo neuropsicológico de los menores evaluados según la lateralidad manual y pedal, pero sí en cuanto a la lateralidad ocular en la función del lenguaje articulado.