European Journal of Neuroscience最新文献

Despite a renewed scientific interest in lysergic acid diethylamide (LSD), its local neural effects remain underexplored. This functional magnetic resonance imaging (fMRI) study explored and compared LSD-induced changes in local activity (amplitude of low-frequency fluctuations: ALFF) and local connectivity (regional homogeneity: ReHo), assessing their relationship to regional receptor density. Imaging data of 15 healthy adults from an open dataset were analyzed. For each participant, two pairs of resting-state runs were available (rest1 and rest2), one performed under placebo and one following the intravenous administration of 75-μg LSD. Voxel-wise paired t-tests compared ALFF and ReHo in the LSD versus placebo conditions. Rest1*rest2 test–retest reliability and ALFF*ReHo cross-modal associations were assessed with conjunction maps and vertex-wise correlations. Finally, neurochemical enrichment analyses related LSD-induced ALFF and ReHo changes to cortical density maps of LSD-related neurotransmitter receptors and transporters. Both ALFF and ReHo decreased in somatosensory/visual cortices under LSD compared to placebo. Specific decreases were observed for ALFF in associative regions belonging to the default mode and frontoparietal networks, and for ReHo in subcortical regions (cluster-based corrected p < 0.05). Test–retest reliability was high for ALFF (rho = 0.80, p = 0.001) and moderate for ReHo (rho = 0.46, p = 0.001). ALFF*ReHo LSD-induced changes were moderately associated (rest1: rho = 0.36, p = 0.001; rest2: rho = 0.56, p = 0.001). Neurochemical enrichment analysis showed that LSD-induced ALFF/ReHo alterations were reliably and negatively correlated with the density of D2 and 5-HT1A receptors (FDR-corrected p < 0.05). These preliminary findings suggest that LSD may engage complex and dynamic neurochemical processes beyond its known 5-HT2A receptor target, warranting further investigation.

Mismatch negativity (MMN) is a well-established neural signature of automatic change detection in the auditory modality. Growing evidence suggests that analogous responses exist in other sensory domains, including somatosensation. This review provides an initial overview of the somatosensory MMN (sMMN), summarizing findings from both human and animal research concerning its underlying neural mechanisms and functional significance as a predictive error signal. We discuss electrophysiological and neuroimaging evidence identifying primary and secondary somatosensory cortices (S1 and S2) as key generators of the sMMN, highlighting the roles of sensory and stimulus-specific adaptation, as well as true deviance detection or surprise. Computational studies further support a hierarchical inference process, where somatosensory mismatch responses encode probabilistic structures based on transition probabilities of sequential input. We also address the clinical relevance of the sMMN in neurodevelopmental, psychiatric, and neurological disorders, as well as its role in aging and body representation. Understanding the neuronal mechanisms underlying the sMMN not only advances our knowledge of somatosensory predictive processing but also contributes to the broader study of perception and learning in the brain.

Accumulating evidence suggests that the brain continuously monitors the predictability of rapidly evolving sound sequences, even when they are not behaviorally relevant. An increasing body of empirical evidence links sustained tonic M/EEG activity to evidence accumulation and tracking the predictability, or inferred precision, of the auditory stimulus. However, it remains unclear whether, and how, this process depends on auditory contextual memory. We investigated how the history of sound sequences influences the neural representation of ongoing regularity under different structural contexts. We recorded EEG responses from naïve participants passively listening to sequences of 50-ms tone-pips across two experiments and compared these responses to predictions from ideal observer models with varying memory spans. In Experiment 1 (N = 26; both sexes), a regularly repeating sequence of 10 tones transitioned directly to a different regular sequence. In Experiment 2 (N = 28; both sexes), the same regular sequence was repeated after an intervening random segment. Results showed that in Experiment 1, neural responses were best explained by models with minimal memory. In contrast, in Experiment 2, inferred predictability of the resumed sequence was influenced by the intervening random tones, even several seconds after the interruption, indicating that the brain retains contextual memory over time. This dissociation implies that the brain can dynamically adjust its strategy based on inferred environmental structure—resetting context when interruptions signal change and preserving context when patterns are likely to resume.

Working memory (WM) is a core component of higher-order cognition, and its impairment is a common consequence of stroke. While traditional lesion-symptom mapping highlights focal damage, it often overlooks alterations in large-scale brain network dynamics. This study investigated WM deficits through functional connectivity (FC) analyses of frontoparietal networks in 34 patients with right hemisphere (RH) stroke and 35 healthy controls. Resting-state fMRI was used to examine region-of-interest and whole-brain seed-to-voxel FC in relation to WM performance on verbal and spatial N-back tasks. Compared to controls, stroke patients exhibited disrupted FC-WM associations, characterized by reduced intrahemispheric FC between anterior and posterior RH regions, which correlated with poorer WM performance. Notably, enhanced interhemispheric FC, particularly between the right middle and inferior frontal gyri and contralateral parietal cortices, was positively associated with WM accuracy, suggesting compensatory engagement of the intact hemisphere. No performance differences were observed between task modalities, supporting the involvement of domain-general WM mechanisms. These findings highlight the role of early network-level reorganization in shaping cognitive outcomes post-stroke. Specifically, WM deficits appear to result not solely from structural damage but from altered FC patterns, where reduced intrahemispheric connectivity may be mitigated by adaptive interhemispheric recruitment.

Mounting evidence challenges the view that antibodies reach the brain solely via vascular leaks. Neurons, astrocytes and microglia appear able to assemble restricted and context-dependent immunoglobulin repertoires via cryptic V(D)J recombination, splice-and-link RNA editing and retroelement-assisted rearrangements. These endogenous antibodies have been associated with complement-mediated pruning, receptor trafficking and astrocyte–neuron metabolic coupling and may change after injury. However, causal evidence from in vivo, cell-type–specific gain- or loss-of-function models remains sparse. Accordingly, we synthesise current evidence and outline testable, conservative hypotheses about when and how neural immunoglobulins might influence CNS function and disease.

The lateral habenula (LHb) integrates aversive information to regulate motivated behaviors. Despite recent advances in identifying neuronal diversity at the molecular level, in vivo electrophysiological diversity of LHb neurons remains poorly understood. Understanding this diversity is essential for deciphering how information is processed in the LHb. To address this gap, we conducted in vivo juxtacellular recording and labeling of single LHb neurons in mice. Morphological analysis revealed a direct axonal projection of LHb neurons to the mediodorsal thalamus. To analyze in vivo LHb firing patterns, we applied an unsupervised clustering algorithm. This analysis identified four distinct spontaneous firing patterns of LHb neurons, which were consistent across both anesthetized and awake states. To determine whether these firing patterns correlate with function, we recorded neuronal responses to foot shock stimulation in anesthetized mice and monitored spontaneous behavior in awake mice. We found that low-firing, bursting neurons were preferentially modulated by foot shocks in anesthetized mice and also tracked behavioral states in awake mice. Collectively, our findings indicate significant electrophysiological diversity among LHb neurons, which is associated with their modulation by aversive stimuli and behavioral state.

Multiple sclerosis (MS) is the most common inflammatory and demyelinating disease affecting the central nervous system (CNS). While immune-modulating drugs can prevent new lesions by targeting lymphocyte activity, treating relapse-independent disease progression remains challenging. Persisting CNS inflammation, leading to axonal and neuronal injury along with failure of compensatory mechanisms, such as brain plasticity and remyelination, drives disease progression. Thus, identifying neuroprotective and/or remyelination-promoting compounds is urgently needed.

We developed an in vitro platform utilizing human-induced pluripotent stem cell (iPSC)-derived neurons and oligodendrocytes to assess neuroprotective and potentially promyelinating effects of selected compounds. We established assays mimicking MS pathophysiologies, such as neuronal loss and axonal injury. Proteomic analysis revealed modulation of molecular mechanisms. Findings were validated in an acute cuprizone (CPZ) mouse model.

We demonstrated that pioglitazone and minocycline protected against glutamate-induced axonal injury, rotenone-induced neuronal death and promoted oligodendrocyte differentiation. Proteomic analyses suggest that pioglitazone's neuroprotective effect may involve reducing mitochondrial reactive oxygen species (ROS) production via PGC-1α and stabilizing axonal transport through GSK3β phosphorylation. Minocycline mainly impacted glutathione metabolism. In the cuprizone model, both compounds displayed neuroprotective effects but did not reduce demyelination or oligodendroglial loss. In summary, our findings demonstrate that human preclinical IPSC platforms can be used to characterize the neuroprotective properties of compounds and thus may aid the selection of drugs for clinical trials. Moreover, the platform's flexibility allows for the easy incorporation of additional disease-specific phenotypic assays.