Journal of Neuroscience最新文献

Anterior cingulate cortex (ACC) is a prefrontal area implicated in functions including cognitive control, attention, and prediction. Mouse ACC receives input from the visual system and uses visual information to direct behavior. While extensive work has described experience-dependent plasticity in mouse V1, less is known about how ACC itself adapts to visual experience. Our previous work demonstrated that visual sequences, presented across days, can drive plasticity in the timing of visually evoked responses in mouse ACC. However, it is not known whether this plasticity ("sequence plasticity") reflects familiarity to the first stimulus in a sequence or expectation of subsequent stimuli-a distinction that is critically important for understanding its functional significance. We recorded visually evoked responses in awake, head-fixed female and male mice trained with visual sequences across days. Visual sequences drove plasticity in ACC, expressed through a change in response timing, that reflects familiarity to the first stimulus. In addition, experience-dependent plasticity could be induced using single-orientation stimuli. Together, these findings suggest that "sequence plasticity" in ACC does not in fact require sequences, but rather reflects a broader phenomenon that we term stimulus-specific response plasticity in timing (SRPT). Our prior work demonstrated that ACC plasticity is impaired in a mouse model of Angelman syndrome (AS). Here, AS model mice showed abnormal responses to familiar visual stimuli in ACC, despite normal plasticity in V1. Together, this work demonstrates how mouse ACC adapts to familiar visual stimuli and describes impaired ACC function in a mouse model of a neurodevelopmental disorder.

Understanding how the brain transforms peripheral sensory inputs into higher-level representations, and how these contribute to perception and behavioral performance, is a central question in sensory neuroscience. However, in human olfaction, the temporal evolution of neural odor codes and their functional significance remain poorly characterized, especially at early stages. To address which odor features define early neural responses and how these relate to olfactory function, we recorded EEG from male and female participants as they inhaled diverse odors. Participants also completed standardized tests of odor detection, discrimination, and identification, along with questionnaires. Time- and frequency-resolved decoding and representational similarity analysis revealed that early theta activity encodes low-level physicochemical properties of odor molecules, with encoding peaking at 370 ms. Critically, the fidelity of this early theta coding to odor physicochemical properties selectively correlated with participants' trait-level odor discrimination ability, but not with other olfactory measures. In contrast, delta-band representations of pleasantness emerged later (peaking at 980 ms), linked only to trait-level odor affective reactivity, as measured by questionnaires. These results suggest that earlier theta-band representations reflect a distinct functional role from the later-emerging delta-band activity and are associated with olfactory performance. Extending these findings, separate EEG recordings during a task involving odor discrimination showed that early theta decoding accuracy was significantly higher on correct than incorrect trials, indicating that theta-band coding accounts for trial-by-trial performance fluctuations. Collectively, our study demonstrates that early theta-band representations of low-level odor features-prior to perceptual representations-are already functionally relevant to odor-guided behavior.

Infants preferentially process familiar social signals, but the neural mechanisms underlying continuous processing of maternal speech remain unclear. Using EEG-based neural encoding models based on temporal response functions, we investigated how 7-month-old human infants track maternal versus unfamiliar speech and whether this affects simultaneous face processing. Infants (13 boys, 12 girls) showed stronger neural tracking of their mother's voice, independent of acoustic properties, suggesting an early neural signature of voice familiarity. Furthermore, central encoding of unfamiliar faces was diminished when infants heard their mother's voice and face tracking accuracy at central electrodes increased with earlier occipital face tracking, suggesting heightened attentional engagement. However, we found no evidence for differential processing of happy versus fearful faces, contrasting previous findings on early emotion discrimination. Our results reveal interactive effects of voice familiarity on multimodal processing in infancy: while maternal speech enhances neural tracking, it may also alter how other social cues, such as faces, are processed. The findings suggest that early auditory experiences shape how infants allocate cognitive resources to social stimuli, emphasizing the need to consider cross-modal influences in early development.

Hippocampal maps and ventral prefrontal cortex (vPFC) value and goal representations support foraging in continuous spaces. How might hippocampal-vPFC interactions control the balance between behavioral exploration and exploitation? Using fMRI and reinforcement learning modeling, we investigated vPFC and hippocampal responses as humans (38 female, 34 male) explored and exploited a continuous one-dimensional space, with out-of-session and out-of-sample replication (23 female, 20 male). The spatial distribution of rewards, or value landscape, modulated activity in the hippocampus and default network vPFC subregions, but not in ventrolateral prefrontal control subregions or medial orbitofrontal limbic subregions. While prefrontal default network and hippocampus displayed higher activity in less complex, easy-to-exploit value landscapes, vPFC-hippocampal connectivity increased in uncertain landscapes requiring exploration. Further, synchronization between prefrontal default network and posterior hippocampus scaled with behavioral exploration. Considered alongside electrophysiological studies, our findings suggest that exploration targets are identified through coordinated activity binding prefrontal default network value representations to posterior hippocampal maps.

Predictive cues significantly influence perception through associative learning. However, it is unknown whether circuits are conserved across domains. We investigated how associative learning influences perceived intensity and valence of pain and hedonic taste, and whether expectancy-based modulation varies by aversiveness or modality. Sixty participants (37 females, 23 males) were randomly assigned to receive either painful heat, unpleasant liquid saline, or pleasant liquid sucrose during fMRI scanning. Following conditioning, cues initially associated with low or high intensity outcomes were intermittently followed by stimuli calibrated to elicit medium intensity ratings. Learned cues modulated expectations and subjective outcomes similarly across domains. Consistent with this, the orbitofrontal cortex exhibited domain-general anticipatory activation. Cue effects on perceived intensity and valence were mediated by the left anterior insula and thalamus, respectively - regions closely overlapping those identified in prior studies of pain expectancy (Atlas et al., 2010). Pain specificity was evident when we measured variations in stimulus intensity, whether we used univariate or multivariate approaches, but there was minimal evidence of specificity by modality or aversiveness in cue effects on medium trials. These findings suggest that shared neural circuits mediate the effects of learned expectations on perception, linking pain with other areas of affective processing and perception across domains.Significance Statement Learned expectations shape how we perceive the world, but it remains unclear whether similar brain circuits mediate expectation effects across aversive and hedonic domains. Using single-trial fMRI, we show that predictive cues alter perceived intensity and valence of pain and both aversive and appetitive tastes through shared neural mechanisms. The orbitofrontal cortex, anterior insula, and thalamus supported the domain-general modulation, while pain-specific effects emerged primarily when actual stimulus intensity varied. These findings reveal that associative learning engages overlapping neural pathways to influence perception across different sensory and affective experiences, suggesting a unified framework for understanding how the brain constructs subjective experience from expectation.

Sleep and feeding-typically mutually exclusive behaviors that are vital for survival and health-are intricately linked. Across species, chronic sleep loss or deprivation is associated with increased caloric intake, while fasting typically induces sleep suppression. Despite evidence for a dynamic relationship between these behaviors, how sleep affects eating habits and how changes in feeding behavior and nutrition alter sleep are not completely understood. Distinct neuronal manipulations in Drosophila melanogaster can dissociate sleep loss from subsequent homeostatic rebound, offering an optimal platform to examine the precise interplay between these fundamental behaviors. Here, we investigated concomitant changes in sleep and food intake in individual flies, as well as respiratory metabolic expenditure that accompany behavioral and neuronal manipulations that induce sleep loss in males. We find that sleep disruptions resulting in energy deficit through increased metabolic expenditure and manifesting as increased food intake were consistently followed by rebound sleep. In contrast, sleep loss that does not induce rebound sleep was not accompanied by increased metabolism and food intake. Our results suggest that homeostatic sleep rebound is linked to energy deficit accrued during sleep loss. Collectively, these findings support the notion that sleep functions to conserve energy and highlight the need to examine the effects of metabolic therapeutics on sleep. Our findings also stress the importance of precise measurements of sleep and the value of considering multiple indicators of energy balance, including metabolism and food intake.

Studies of cognitive flexibility suggest that switching between different tasks can entail a transient switch cost. Here, we asked whether analogous switch costs exist in the context of switching between different motor skills. We tested whether participants (23 males and 12 females) could switch between a newly learned skill associated with a novel visuomotor mapping and an existing skill associated with an intuitive mapping. Participants showed increased errors in trials immediately following a switch between mappings. These errors were attributable to persisting with the preswitch policy rather than imperfect implementation or retrieval of the postswitch policy. A subset of our participants further learned a second new skill. Switching between these two novel skills was initially very challenging but improved with further training. Our findings suggest that switching between newly learned motor skills can be challenging and that errors in the context of switching between skills are primarily attributable to perseveration with the wrong control policy.

The bed nucleus of the stria terminalis (BNST), a part of the extended amygdala, integrates emotional and arousal-related signals. While GABAergic BNST (GABA^BNST) neurons have been implicated in promoting transitions from non-rapid eye movement (NREM) sleep to wakefulness, their downstream mechanisms remain unclear. Here, we identify a neuronal circuit through which GABA^BNST neurons promote arousal via projections to a midbrain region known as the deep mesencephalic nucleus (DpMe), located within the broader mesencephalic reticular formation. In male mice, we used a combination of optogenetics, fiber photometry, neural ablation, and tracing approaches to dissect this circuit. Optogenetic stimulation of GABA^BNST terminals in the DpMe during NREM sleep elicited rapid transitions to wakefulness and increased activity of glutamatergic DpMe (GLUT^DpMe) neurons, as assessed by c-fos mRNA expression and calcium imaging. Similarly, an aversive air-puff activated GLUT^DpMe neurons, suggesting engagement by emotionally salient stimuli. Ablation of GLUT^DpMe neurons markedly attenuated arousal responses triggered by GABA^BNST stimulation, underscoring their essential role in this circuit. While monosynaptic rabies tracing revealed local input neurons to GLUT^DpMe cells, in situ hybridization identified few Vgat-positive interneurons among them. These findings suggest that GABA^BNST neurons may influence GLUT^DpMe neurons through noncanonical GABAergic mechanisms or via more complex local circuits beyond a simple disinhibition model. Together, these findings delineate a previously uncharacterized BNST-DpMe circuit that allows emotionally relevant stimuli to override sleep and promote arousal. This pathway may contribute to stress-related sleep disturbances and represents a potential target for therapeutic treatments for sleep disorders associated with emotional dysregulation.

Epilepsy constitutes a clinically manifest excitability disorder that is characterized by aberrant electrophysiological activity in the electroencephalogram (EEG). The correct identification of the seizure onset zone relies on the visual detection of pathological waveforms and the assessment of their morphology, rhythmicity, and density. Recent advances in quantitative EEG analyses indicated that aperiodic EEG background activity might provide complementary information to traditional qualitative methods. Importantly, aperiodic activity, and specifically the slope of the 1/ƒ ^χ decay function of the power spectrum, might constitute a biomarker of the underlying population excitability dynamics. Hence, in the context of epileptic activity, an altered spectral slope is often considered as a signature of pathological excitability. To date, it remained unclear if this straightforward interpretation also applies to states of manifest seizure activity. To address this question, we recorded intracranial electroencephalography (iEEG) during focal seizures from patients diagnosed with pharmacoresistant epilepsy (18 patients, 11 females). The results demonstrate that the spectral slope successfully delineates seizure activity. However, the spectral slope was sensitive to the presence and waveform shape of distinct epileptic components. By combining iEEG recordings with simulations, we demonstrate that epileptic spiking activity and associated slow-wave components differentially impact spectral slope estimates. These results offer a more parsimonious explanation for the biophysical origins of aperiodic activity as compared with the concept of an underlying balance between excitation and inhibition.