Journal of Neuroscience最新文献

Social creatures can infer the mental states of others. This cognitive ability, called mentalizing, can be considered a process of inferring others' hidden states behind their actions from partially observable sensory information. The purpose of this review is to propose the computational mechanisms of mentalizing and review the neural substrates that might underlie each computational process. In fact, inference about hidden states is a ubiquitous task in many sensory systems, and this can be achieved under the predictive coding framework in which the brain probabilistically estimates a latent state that most likely causes the observed sensory events by minimizing errors between the actual and predicted sensory signals. We argue that what might be unique to mentalizing is not merely the representation of others' internal states in an arbitrary latent space but also the capacity to represent them in a mental space that one can experience subjectively. This function can solve the so-called symbol grounding problem. Further, the use of symbol grounding makes the inference system efficient and reliable by reducing the cost to learn de novo the latent representations of others' mental states. On the basis of a preliminary simulation, we demonstrate that an artificial mentalizing system with a symbol grounding function performs better in predicting the actions of virtual agents than a pure Bayesian observer without the symbol grounding function. Emerging novel paradigms integrating artificial and biological neural networks will enable a better understanding of the neural algorithms and computational processes for complex social cognition including mentalizing.

Magnetic Resonance Spectroscopy (MRS)-derived excitation/inhibition (E/I) ratio is recognized as a valuable index of attentional modulation, the plasticity and stability of learning states, and disordered functioning. Inferring the E/I ratio from electroencephalography (EEG), however, offers greater accessibility and superior temporal resolution, and therefore holds strong potential for advancing research on dynamic neural processes. Yet, the underlying neurochemical mechanisms contributing to changes in EEG-based E/I ratio remain unclear. In this study we used concurrent EEG and magnetic resonance spectroscopy (MRS) to examine how the EEG-based E/I ratio correlates with the MRS-based E/I ratio in sleeping humans of both sexes (n = 15). The MRS-based E/I ratio was calculated as the ratio of Glx (glutamate + glutamine) to GABA+ (GABA + co-edited macromolecules) concentrations in early visual areas. We estimated 10 candidate EEG-based E/I indices using four algorithms across multiple spontaneous frequency bands from the occipital region. Uniquely, we quantified the associations between EEG- and MRS-based E/I ratios by separately analyzing between-subject and within-subject variations. We found that each EEG-based E/I algorithm showed reliable and positive associations with MRS-based E/I, particularly in the alpha band, which is known to play a key role in attentional modulation and in the plasticity and stability of learning states. These results highlight the potential of EEG-based E/I measures to serve as practical indices of neurochemical dynamics in early visual cortex.Significance Statement Although a balance between cortical excitation and inhibition is important for many functions, measurement of this balance has remained a challenge. Candidate methods to efficiently measure excitation/inhibition balance via electroencephalography (EEG) have been proposed, but validation of these methods using concurrent measurement of neurochemistry (i.e., using magnetic resonance spectroscopy) has been lacking. The results reported here show that several candidate EEG-based measures of excitation/inhibition balance are reliably and positively associated with the ratio of excitatory to inhibitory neurotransmitters. Such results provide a necessary foundation for advancing methods, basic research, and applied research using efficient EEG measures of excitation/inhibition balance to understand brain states.

N-methyl-D-aspartate receptors (NMDARs) are ionotropic glutamate receptors essential for excitatory neurotransmission. Previous studies proposed the existence of four disulfide bonds in the GluN1 subunit; however, their role in NMDAR trafficking remains unclear. Our study first confirmed the existence of four disulfide bonds in the GluN1 subunit using biochemistry in human embryonic kidney 293T (HEK293T) cells. Disrupting the individual disulfide bonds by serine replacements produced the following surface expression trend for GluN1/GluN2A, GluN1/GluN2B, and GluN1/GluN3A receptors: wild-type (WT) > GluN1-C744S-C798S > GluN1-C79S-C308S > GluN1-C420S-C454S > GluN1-C436S-C455S subunits. Electrophysiology revealed altered functional properties of NMDARs with disrupted disulfide bonds, specifically an increased probability of opening (Po) at the GluN1-C744S-C798S/GluN2 receptors. Synchronized release from the endoplasmic reticulum confirmed that disruption of disulfide bonds impaired early trafficking of NMDARs in HEK293T cells and primary hippocampal neurons prepared from Wistar rats of both sexes (embryonic day 18). The pathogenic GluN1-C744Y variant, associated with neurodevelopmental disorder and seizures, caused reduced surface expression and increased Po at GluN1/GluN2 receptors, consistent with findings for the GluN1-C744S-C798S subunit. The FDA-approved memantine inhibited GluN1-C744Y/GluN2 receptors more potently and with distinct kinetics compared to WT GluN1/GluN2 receptors. We also observed enhanced NMDA-induced excitotoxicity in hippocampal neurons expressing the GluN1-C744Y subunit, which memantine reduced more effectively compared to the WT GluN1 subunit. Lastly, we demonstrated that the presence of the hGluN1-1a-C744Y subunit counteracted the effect of the hGluN3A subunit on decreasing dendritic spine maturation, consistent with the reduced surface delivery of the NMDARs carrying this variant.Significance statement Our findings highlight the critical role of disulfide bonds in the GluN1 subunit in regulating trafficking and function of major conventional (GluN1/GluN2A, GluN1/GluN2B) and unconventional (GluN1/GluN3A) diheteromeric N-methyl-D-aspartate receptors (NMDARs) subtypes in the postnatal forebrain. We further demonstrated that the pathogenic GluN1-C744Y variant reduces surface expression of all studied NMDARs, as well as increases the probability of opening (Po) of the GluN1/GluN2 receptors, leading to heightened NMDA-induced excitotoxicity in hippocampal neurons. Additionally, we introduced an ARIAD-based system for the synchronized release of NMDARs from the endoplasmic reticulum (ER) in hippocampal neurons. This system provides a powerful tool for studying pathogenic variants of NMDARs and addresses the current lack of molecular methods for analyzing their early trafficking.

People often make decisions in contexts where rewards and punishments co-occur, yet most human research still examines reward and punishment learning as independent processes. Here, across three studies, we address this gap by demonstrating that punishments amplify reward learning and its neural correlates in healthy human participants. In Study 1 (N = 102, 69 females and 33 males), participants performed a probabilistic learning task involving monetary rewards and punishments presented in either intermixed or separated contexts. In intermixed contexts, punishments enhanced reward learning accompanied by changes in computational parameters, including higher learning rates from reward prediction errors. In Study 2 (N = 26, 18 females and 8 males), fMRI revealed that punishments amplified reward prediction errors signals in the caudate. Study 3, an fMRI meta-analysis, confirmed that striatal reward responses are consistently stronger when punishments are present. Across studies, we found no reciprocal enhancement of punishment learning by rewards. Together, these findings demonstrate that punishments sharpen reward learning through striatal modulation and underscore the extent to which reward learning is influenced by its broader outcome context.Significance Statement A central question in cognitive neuroscience is how people learn to pursue rewards and avoid punishments. In everyday life, these processes rarely operate in isolation; they often co-occur and interact. For example, a win often feels more rewarding after a loss. Yet, human research has largely examined rewards and punishments separately, overlooking their interplay. Across three studies, we find that punishments enhance reward learning and its underlying striatal prediction-error signals, whereas rewards do not exert a comparable influence on punishment learning. This directional modulation shows that reward learning depends on its broader outcome context, with punishments acting as a key contextual factor. This work offers a theoretical framework for understanding punishment-reward interactions and a new benchmark for future research.

Weakening of synaptic inhibition in the spinal dorsal horn contributes to mechanical allodynia after peripheral nerve pathology. Restoring inhibition can alleviate allodynia whereas weakening it is sufficient to induce allodynia and spontaneous pain in uninjured conditions. Disinhibition is known to un-gate nociceptive polysynaptic spinal circuits, but why allodynia is predominantly evoked by certain touch stimuli remains unclear. To address this, we incorporated receptive fields (RFs) into a computational model of the spinal dorsal horn to study the processing of stimuli with different spatiotemporal features. Our model reveals that broad stimuli normally suppress spinal output by engaging inhibition from the RF's inhibitory surround, but previously subliminal excitation can be engaged when inhibition is compromised, fundamentally altering E-I balance. The efficacy of spinal inhibition also depends on the input's temporal pattern, especially since excitatory and inhibitory spinal neurons are preferentially sensitive to synchronous and asynchronous input, respectively. Furthermore, spikes driven by synchronous input are resistant to feedforward inhibition. This combination of effects may explain why broad dynamic touch (e.g. brush) evokes more allodynia than punctate static touch. On the other hand, asynchronous and spatially disordered input like that evoked by kilohertz-frequency spinal cord stimulation was found to preferentially activate inhibitory neurons, thus reducing allodynia. Overall, our results suggest how spatial and temporal stimulus features impact the flow of sensory input through disinhibited spinal circuits. Our results show how quantitative computational models can connect injury-induced molecular changes to clinically relevant sensory effects by revealing nonintuitive processes occurring at the cellular and circuit levels.Significance Statement Following peripheral nerve injury, light touch can become mistakenly perceived as painful. This so-called mechanical allodynia can be reproduced experimentally by reducing synaptic inhibition in the dorsal horn of the spinal cord. Furthermore, spinal inhibition is diminished by nerve injury. But it remains unclear why certain tactile stimuli, like brushing or vibration, are particularly painful. To address this knowledge gap, we built a computational model of the spinal dorsal horn to investigate how different types of tactile input are processed. Our results reveal that the spatiotemporal features of tactile stimuli dramatically influence sensory processing. Our results are explained by considering how synaptic excitation and inhibition interact over space and time.

Inhibitory control is essential for adaptive behaviour and declines with age, yet the underlying neural dynamics remain poorly understood. The β-rhythm (15-29 Hz) is associated with inhibitory signalling within the fronto-basal ganglia network. Recent evidence suggests that transient β-bursts support inhibitory performance but are often masked by conventional trial-averaged β-power analyses. A recently developed analysis approach, combining linear mixed-effects modelling and threshold-free cluster enhancement (LMM-TFCE), was applied to examine trial-by-trial β-bursting activity associated with response inhibition and initiation in older adults. Twenty healthy older adults (9 female) performed a bimanual anticipatory response inhibition task, while electroencephalography and electromyography were recorded to capture β-activity (β-burst rate/volume; averaged β-power) and muscle bursting dynamics, respectively. Our analysis revealed distinct β-bursting signatures absent in averaged β-power data. During bimanual response inhibition, parieto-occipital β-bursting preceded bilateral fronto-central β-bursting, consistent with initial attentional processes prior to broader inhibitory network engagement. Moreover, a link was established between right sensorimotor β-bursting and muscle bursts during stopping, indicating rapid cortical suppression of initiated motor output. β-burst volume proved uniquely sensitive to response withholding, with early left frontal activity supporting preparatory suppression mechanisms. A further link between increased parieto-occipital β-burst volume and muscle bursts aligned with top-down inhibitory signalling to support visuomotor stabilisation and prevent premature response release. These results underscore the sensitivity of β-bursting to both the timing and context of inhibitory demands in healthy ageing. Future research will help establish the potential of β-bursting, combined with LMM-TFCE analysis, as a clinically relevant marker of impulse control dysfunction.Significance statement: Our novel application of an advanced statistical framework revealed distinct spatiotemporal β-bursting patterns during response inhibition and response withholding in healthy older adults, which were not captured by averaged β-power. Identifying a further link between cortical β-bursting and muscle-level suppression, the findings offer a mechanistic account of how the brain halts action in real time in older adults. This work provides a sensitive, trial-level framework for studying β-burst measures in general, as well as inhibitory control across aging and clinical populations.

Microglia, the main immune cells of the central nervous system, are crucial for maintaining brain homeostasis by modulating immune processes and neurovascular function. However, the mechanisms by which microglia regulate neuronal networks and local microcircuits remain incompletely understood. Here, we identify microglia as important modulators of neuronal network activity at the single-cell level and brain-wide functional connectivity in male mice. We show that in the absence of microglia or microglial P2Y12 receptor (P2Y12R), the baseline firing rate of putative interneurons was increased, while whisker-stimulation-induced sensory responses remained unchanged in microglia-depleted and P2Y12R KO animals. Increase in cortical delta oscillations in both models and increased single neuron phase coupling to delta-band rhythms in microglia-depleted mice revealed cortical hypersynchrony. Microglia depletion led to a significant reduction in connectivity between the contralateral barrel cortex and the anatomically connected ventral posteromedial nucleus of the thalamus (VPMb) during somatosensory stimulation, while resting-state functional connectivity remained unchanged. Similarly, genetic blockade of P2Y12R resulted in diminished functional connectivity within this thalamocortical network. Our findings suggest that cortical interneuron hyperexcitability due to dysfunction of microglia could be a key cause for local hypersynchrony relevant to sensory processing.Significance statement Microglia have been shown to modulate neuronal activity, but the underlying mechanisms are insufficiently defined. In particular, it is not well understood how microglia could shape excitatory / inhibitory balance in the cerebral cortex and whether such modulatory processes could alter sensory processing. Here, we studied single cell-level effects in the barrel cortex by using two established models of microglia dysfunction. We show that the absence of microglia or the purinergic microglial receptor, P2Y12R, have both large-scale effects on thalamocortical networks and cortical slow oscillations, while specifically shape the firing rate of interneurons in cortical microcircuits. Such neuroglial interactions could have broad impact on sensory processing in health and under different disease states.

Neuroplasticity is a defining property of the brain. Structural and functional brain changes arise soon after learning and are particularly evident following years of practice that underpin expert performance. Much existing evidence comes from work on individual measures of learning rather than interrelated processes. However, the relationship between structural remodeling, functional tuning and processing domain-specific stimuli is central to how the brain and behavior adapt with experience. Here, we provide a multimodal view of cortical reorganization in a domain for which high-level perception, attention, and memory are shaped through extensive practice: bird identification expertise. In both skilled bird ID experts (n = 29; ages 24-75, 15 female) and matched novices (n = 29; ages 22-79, 14 female) cortical structure was assessed with diffusion-weighted MRI. Functional and behavioral measures were obtained during a delayed matching task requiring identification of local and nonlocal species. Compared to novices, experts showed lower mean diffusivity in frontoparietal (SFG, IPS) and posterior cortical (AG, precuneus, LOC, fusiform) areas, along with a trend for more gradual increases in age-related MD. This suggests a regionally-specific increase in structural complexity and potential attenuation of age-related decline. Across these regions, lower MD predicted higher identification accuracy in experts. Task-related BOLD timecourses revealed that these same frontoparietal regions were selectively engaged when experts judged less-familiar nonlocal (vs. local) birds, and the magnitude of this nonlocal > local response tracked performance. Together, these results suggest convergent structural remodeling and functional tuning in service of expert performance across the lifespan.Significance statement The extensive training required to achieve domain-specific expertise modifies the brain. Changes in brain structure have been found in domains including music, athletics and navigation. Training also alters brain activity. To connect these different components of neuroplasticity, and extend them to conceptual expertise, we explored bird identification in experts and matched novices, assessing changes in brain structure, brain activity, and identification performance. Regions involved in attention and perception showed structural modification in experts, and these same regions were selectively engaged to support identification in challenging circumstances. Results also suggest that knowledge acquisition might mitigate age-related decline in circumscribed brain regions supporting expert performance.

Sequential movements rely on two information sources: external sensory cues and internal memory representations. Although often both sources jointly drive sequential behavior, previous research has primarily examined them in isolation. To address this, we trained participants (n = 26, 15F) to perform sequences of rapid finger presses in response to numerical cues. Sensory influence was measured by varying the number of visible cues, and memory influence was determined by comparing repeating and random sequences. Early in learning, participants integrated sensory and memory information: repeating sequences were performed more quickly when more cues were visible. After learning, when repeating sequences were predictable with certainty, participants relied solely on memory and ignored sensory cues. However, when this certainty was manipulated by introducing occasional violations within repeating sequences, participants reverted to integrating memory with sensory cues. We propose a computational model that successfully predicted both speed and accuracy of individual presses. Critically, this model relied on the assumption that multiple movements are planned independently of each other. This independence assumption was then validated by examining response patterns to isolated violations in repeating sequences. Finally, we provide evidence into how sequence memories can be flexibly deactivated and reactivated in response to these violations. Together, these results reveal how brain dynamically integrates sensory and memory information to produce sequences of movements.Significance Statement How the brain coordinates sequential movements is fundamental in understanding human motor control. Previous research has studied sensory-driven and memory-driven modes of sequence production in isolation, characterizing learning as a switch from one to the other. In this study, using a sequential finger-pressing task, we show that memory and sensory information jointly drive sequence production. We found that unless sequences were fully predictable, participants integrated sensory information with their memory to achieve faster and more accurate performance. These findings highlight the importance of understanding the mechanisms that underlie sensory and memory integration in sequence production.

During sleep, the human brain transitions to a 'sentinel processing mode', enabling the continued processing of environmental stimuli despite the absence of consciousness. We employed advanced information-theoretic analyses, including mutual information (MI) and co-information (co-I), alongside event-related potential (ERP) and temporal generalization analyses (TGA), to characterize auditory prediction error processing across wakefulness and sleep. We hypothesized that a shared neural code would be present across sleep stages, with deeper sleep being associated with reduced information content and increased information redundancy. Twenty-nine participants (15 women) underwent an auditory 'local-global' oddball paradigm during wakefulness and an 8-hour sleep opportunity monitored via polysomnography. We focused on 'local' mismatch responses to a deviating fifth tone after four standards. ERP analyses showed that prediction error processing continued throughout all sleep stages (N1-N3, REM). Mutual information analyses revealed a substantial reduction in encoded prediction error information particularly during N3 and REM, although ERP amplitudes increased with deeper NREM sleep. We also observed delayed information encoding during sleep, and co-information analyses showed neural dynamics became increasingly redundant with increasing sleep depth. Temporal generalisation analyses revealed a largely shared neural code between N2 and N3 sleep, though it differed between wakefulness and sleep. We demonstrate how the neural code of the 'sentinel processing mode' changes from wake to light to deep sleep and REM, characterised by delayed processing, more redundant and less rich neural information in the human cortex as consciousness wanes. This altered stimulus processing reveals how neural information evolves with variations in consciousness across the night.Statement of Significance Even during sleep, the human brain remains responsive to its surroundings. Using an auditory stimulation paradigm, the study reveals how the neural code underlying this 'sentinel processing mode' changes from wakefulness to sleep and with increasing sleep depth. Using computational methods to precisely characterise information processing in the brain, we show that as sleep deepens, the brain encodes less information at increasing redundancy. These findings provide new insights that may help understand why we lose consciousness when falling asleep.