European Journal of Neuroscience最新文献

This study aims to investigate the value of basal ganglia and limbic/paralimbic networks alteration in identifying preschool children with ASD and normal controls using diffusion basis spectrum imaging (DBSI). DBSI data from 31 patients with ASD and 30 NC were collected in Hunan Children's Hospital. All data were imported into the post-processing server. The most discriminative features were extracted from the connection, global and nodal metrics separately using the two-sample t-test. To effectively integrate the multimodal information, we employed the multi-kernel learning support vector machine (MKL-SVM). In ASD group, the value of global efficiency, local efficiency, clustering coefficient and synchronization were lower than NC group, while modularity score, hierarchy, normalized clustering coefficient, normalized characteristic path length, small-world, characteristic path length and assortativity were higher. Significant weaker connections are mainly distributed in the limbic/paralimbic networks. The model combining consensus connection, global and nodal graph metrics features can achieve the best performance in identifying ASD patients, with an accuracy of 96.72%.The most specific brain regions connection weakening associated with preschool ASD are predominantly located in limbic/paralimbic networks, suggesting their involvement in abnormal brain development processes. The effective combination of connection, global and nodal metrics information by MKL-SVM can effectively distinguish patients with ASD.

The adaptation to the daily 24-h light-dark cycle is ubiquitous across animal species and is crucial for maintaining fitness. This free-running cycle occurs innately within multiple bodily systems, such as endogenous circadian rhythms in clock-gene expression and synaptic plasticity. These phenomena are well studied; however, it is unknown if and how the 24-h clock affects electrophysiologic network function in vivo. The hippocampus is a region of interest for long timescale (>8 h) studies because it is critical for cognitive function and exhibits time-of-day effects in learning. We recorded single cell spiking activity and local field potentials (LFPs) in mouse hippocampus across the 24-h (12:12-h light/dark) cycle to quantify how electrophysiological network function is modulated across the 24-h day. We found that while inhibitory population firing rates and LFP oscillations exhibit modulation across the day, average excitatory population firing is static. This excitatory stability, despite inhibitory dynamism, may enable consistent around-the-clock function of neural circuits.

Approximately 15%-20% of school-aged children suffer from mathematics learning difficulties (MLD). Most children with developmental dyscalculia (DD) or MLD also have comorbid cognitive deficits. Recent literature suggests that research should focus on uncovering the neural underpinnings of MLD across more inclusive samples, rather than limiting studies to pure cases of DD or MLD with highly stringent inclusion criteria. Therefore, this study aims to identify neural aberrancies that may be common across multiple MLD cases with different deficit profiles. Nine MLD cases and 45 typically developing (TD) children, all around 7 years old (27 boys), were recruited. Using functional near-infrared spectroscopy (fNIRS), brain data were collected during an approximate resting state and a mathematical computation task (addition). Graph theory was then applied to assess global and nodal network indicators of brain function. When comparing the network indicators and brain activation of the MLD cases to those of TD children, no unified neural aberrancy was found across all cases. However, three MLD cases did show distinct neural aberrancies compared to TD children. The study discusses the implications of these findings, considering both the neural aberrancies in the three MLD cases and the neural similarities found in the other six cases, which were comparable to those of the TD children. This raises important questions about the presence and nature of aberrant neural indicators in MLD across large cohorts and highlights the need for further research in this area.

The nature of explanation is an important area of inquiry in philosophy of science. Consensus has been that explanation in the cognitive and brain sciences is typically a special case of causal explanation, specifically, mechanistic explanation. But recently there has been increased attention to computational explanation in the brain sciences and to whether that can be understood as a variety of mechanistic explanation. After laying out the stakes for a proper understanding of scientific explanation, we consider the status of computational explanation in the brain sciences by comparing the mechanistic proposal to computational accounts advanced by Piccinini, Milkowski, Cao, Chirimuuta and Ross. We argue that many of these accounts of computational explanation in neuroscience can satisfy the same explanatory criteria as causal explanations, but not all. This has implications for interpretation of those computational explanations that satisfy different criteria.

Good brain health plays a significant role in an individual's well-being and profoundly impacts the collective economy and society. Brain development does not stop at birth, and some aspects continue throughout childhood and adolescence, allowing the full development of cognitive functions. Different determinants related to physical health, healthy environments, safety and security, life-long learning and social connection as well as access to quality services influence the way our brains develop, adapt and respond to stress and adversity. Ongoing progress in neurobiology and cognitive neuroscience allows the design of better prevention and intervention strategies to help avoid brain deficits and/or limit their impact and maintain brain health. The European Brain Council (EBC) convened an expert meeting during the Federation of European Neuroscience Societies (FENS) Forum 2024 to address youth brain health challenges. In recent years, the importance of brain health has garnered significant attention across scientific, medical and policy-making communities. Although much focus has traditionally been on neurodegenerative conditions affecting the elderly, a paradigm shift towards prioritizing brain health in youth is both timely and necessary. This shift can profoundly impact individual lives and society, necessitating an interdisciplinary approach that brings neuroscience to the forefront of public health and informs evidence-based policy. The topic is of utmost importance as EBC launched this year a new campaign on No Health Without Brain Health rallying support with its member organizations and the wider brain community for the increased prioritization of brain health on EU health and research agendas.

Within the reductionist framework, researchers in the special sciences formulate key terms and concepts and try to explain them with lower-level science terms and concepts. For example, behavioural vision scientists describe contrast perception with a psychometric function, in which the perceived brightness increases logarithmically with the physical contrast of a light patch (the Weber-Fechner law). Visual neuroscientists describe the output of neural circuits with neurometric functions. Intuitively, the key terms from two adjacent scientific domains should map onto each other; for instance, psychometric and neurometric functions may map onto each other. Identifying such mappings has been the very goal of neuroscience for nearly two centuries. Yet mapping behaviour to brain measures has turned out to be difficult. Here, we provide various arguments as to why the conspicuous lack of robust brain-behaviour mappings is rather a rule than an exception. First, we provide an overview of methodological and conceptual issues that may stand in the way of successful brain-behaviour mapping. Second, extending previous theoretical work (Herzog, Doerig and Sachse, 2023), we show that brain-behaviour mapping may be limited by complexity barriers. In this case, reduction may be impossible.

Combination of structural and functional brain connectivity methods provides a more complete and effective avenue into the investigation of cortical network responses to traumatic brain injury (TBI) and subtle alterations in brain connectivity associated with TBI. Structural connectivity (SC) can be measured using diffusion tensor imaging to evaluate white matter integrity, whereas functional connectivity (FC) can be studied by examining functional correlations within or between functional networks. In this study, the alterations of SC and FC were assessed for TBI patients, with and without chronic symptoms (TBIcs/TBIncs), compared with a healthy control group (CG). The correlation between global SC and FC was significantly increased for both TBI groups compared with CG. SC was significantly lower in the TBIcs group compared with CG, and FC changes were seen in the TBIncs group compared with CG. When comparing TBI groups, FC differences were observed in the TBIcs group compared with the TBIncs group. These observations show that the presence of chronic symptoms is associated with a distinct pattern of SC and FC changes including the atrophy of the SC and a mixture of functional hypoconnectivity and hyperconnectivity, as well as loss of segregation of functional networks.

Parkinson's disease (PD) is a neurodegenerative disease involving multiple factors. We explored the connection between intestinal microbiome levels and PD by examining inflammatory cytokines, peripheral immune cell counts and plasma metabolomics as potential factors. By obtaining the Genome-Wide Association Study (GWAS) data needed for this study from GWAS Catalog, including summary data for 473 intestinal microbiota traits (N = 5959), 91 inflammatory cytokine traits (N = 14,824), 118 peripheral immune cell count traits (N = 3757), 1400 plasma metabolite traits (N = 8299) and PD traits (N = 482,730). We used two-step Mendelian randomization (MR) mediated analysis to investigate possible pathways from intestinal microbiota to PD mediated by inflammatory cytokines, peripheral immune cells and plasma metabolites. MR has revealed the causal effects of 19 intestinal microbiota, 1 inflammatory cytokine and 12 plasma metabolites on PD, whereas there is no significant causal relationship between immune cell count characteristics and the occurrence of PD. Mediation analysis showed that the associations between the genus Demequina and PD were mediated by tryptophan with mediated proportions of 17.51% (p = 0.0393). Our study demonstrates that genus Demequina may promote the occurrence of PD by reducing the levels of tryptophan.

This study aimed to investigate the topological properties of brain functional networks in patients with tinnitus of varying durations. A total of 51 tinnitus patients (divided into recent-onset tinnitus (ROT) and persistent tinnitus (PT) groups) and 27 healthy controls (HC) were recruited. All participants underwent resting-state functional MRI and audiological assessments. Graph theory was used to examine brain network topology. The results showed that the ROT group exhibited lower clustering coefficient, gamma, sigma and local efficiency compared to both the HC and PT groups (all P < 0.05). Significant reductions in nodal clustering coefficient and local efficiency were found in the left caudate nucleus and left olfactory cortex, while increased nodal centralities were observed in the left orbital middle frontal gyrus and left postcentral gyrus in ROT patients (all P < 0.05). Furthermore, the ROT group had decreased nodal clustering in the right lenticular putamen and reduced nodal efficiency in the left olfactory cortex compared to both PT patients and HCs (all P < 0.05). Additionally, PT patients showed weaker functional connectivity between the subcortical and occipital lobe modules, as well as between the prefrontal and intra-frontal modules, compared to ROT patients. However, intra-module connectivity in the subcortical module was stronger in PT patients than in HCs. These findings suggest that recent-onset tinnitus is associated with alterations in brain network topology, but many of these changes are restored with the persistence of tinnitus.