eNeuro最新文献

Dopaminergic inputs to various brain regions, such as the striatum, orbitofrontal cortex, and amygdala play a critical role in processing reward acquisition information. While reward-related activity is also observed more broadly in motor, parietal, and hippocampal regions, the functional significance and potential hierarchy of reward-related representation across these latter areas remain unclear. We investigated this by quantifying neural predictive power using machine learning. Specifically, neural activity was examined in six brain areas-the primary and secondary motor cortices (M1 and M2), posterior parietal cortex (PPC), dorsal and ventral CA1 (dCA1 and vCA1), and lateral entorhinal cortex (LEC)-in male rats performing a self-initiated left-right choice task. Machine learning models classified rewarded versus non-rewarded trials based on neuronal firing properties significantly above chance for all regions. Crucially, classification revealed a clear performance gradient, forming a functional hierarchy: models using hippocampal data (dCA1 and vCA1) performed best, followed by LEC and PPC, with M1 and M2 performing lowest. Furthermore, SHapley Additive exPlanations (SHAP) analysis revealed a qualitative transformation in coding strategies along this hierarchy: while neocortical regions relied on subtle, distributed high-order statistics, the hippocampus utilized precise, categorical representations. At this apex, distinct strategies emerged: dCA1 primarily utilized temporally precise post-reward spike distributions with transient increase of response, while vCA1 integrated both spike timing and firing rate changes with suppressive response. These findings provide quantitative evidence for a functionally hierarchical and qualitative evolution of reward-related representation, highlighting distinct roles of dCA1 and vCA1 in encoding reward-related events to potentially guide future behavior.Significance Statement How the brain represents reward information across distributed networks remains unclear. We used machine learning to quantitatively compare neural representations across six brain regions (M1, M2, PPC, LEC, dCA1, vCA1) in male rats performing a choice task. We identified a robust functional hierarchy: the hippocampus provided the most accurate reward prediction, significantly outperforming the motor cortices, with intermediate performance in the parahippocampal and parietal regions. Crucially, this hierarchy reflects a qualitative transformation from graded, distributed cortical codes to precise, categorical hippocampal representations. Furthermore, distinct coding strategies emerged at the hierarchy's apex: dCA1 relied on precise spike timing, while vCA1 integrated timing with firing suppression. This study reveals how reward information evolves across neural circuits to guide goal-directed behavior.

Investigations into the neural basis of behavior frequently employ calcium imaging to measure neuronal activity. Across studies, however, seemingly reasonable but highly diverse methodological choices are typically made to assess the selectivity of individual neurons to task states. Here, we examine systematically the effect of parameter choices, along the pipeline from data acquisition through statistical testing, on the inferred encoding preferences of individual neurons. We use, as an experimental testbed, calcium imaging in the medial prefrontal cortex of freely behaving mice engaged in a classic exploration-avoidance task with animal-controlled state transitions, namely, navigation in the elevated zero maze. We report that most of the key parameters in the pipeline substantially impact the inferred selectivity of neurons and do so in distinct ways. Using novel accuracy and robustness metrics, we directly compare the quality of inference across combinations of parameter levels and discover an optimal combination. We validate its optimality using resampling methods and demonstrate its generality across the two common analytical approaches used to assess neuronal selectivity-average response rate-dependent selectivity indices and continuous time-dependent regression coefficients. Together, our results not only identify an optimal parameter setting for reliably assessing encoding preferences of cortical excitatory neurons using GCaMP6f calcium imaging but also establish a general data-driven procedure for identifying such optimal settings for other cell types, brain areas, and tasks.

The life cycle of the model nematode Caenorhabditis elegans involves a choice between two alternative developmental trajectories. Hermaphroditic larvae can either become reproductive adults or, under conditions of crowding or low food availability, enter a long-term, stress-resistant diapause known as the dauer stage. Chemical signals from a secreted larval pheromone promote the dauer trajectory in a concentration-dependent manner, and their influence can be antagonized by increased availability of a microbial food source. The decision is known to be under neuronal control, involving both sensory and interneurons. However, little is known about the dynamics of the underlying circuit, and the circuit mechanisms by which short-term fluctuations in the ratio of food and pheromone experienced by individual larvae are remembered and averaged over several hours. To investigate this, we quantitatively characterized the neuronal responses to food and pheromone inputs by measuring calcium traces from ASI and AIA neurons, each of which has previously been implicated in regulation of dauer entry. We found that calcium in ASI increases linearly in response to food and similarly decreases in response to pheromone. Notably, the ASI response persists well beyond removal of the food stimulus, thus encoding a memory of recent food exposure. In contrast, AIA reports instantaneous food availability and is unaffected by pheromone. We discuss how these findings may inform our understanding of this long-term decision-making process.

Daughterless (Da), the Drosophila melanogaster homolog of mammalian E-protein transcription factor 4 (TCF4), is well studied in fruit fly embryonic development but its functions in adult nervous system are poorly understood. Mutations in human TCF4 gene lead to intellectual disabilities such as Pitt-Hopkins syndrome and TCF4 has also been linked to schizophrenia. Here, to explore the roles of Da in the Drosophila mature brain, we map Da DNA binding sites and study the transcriptomics of the brains where Da function is inhibited by pan-neuronal Extramacrohaete (Emc) overexpression, in both male and female Drosophila Our transcriptome analyses reveal that in the adult brain Da regulates the expression of genes involved in behavior, memory, synaptic signaling, protein translation, and metabolic processes. Moreover, combining the RNA sequencing data with Da ChIP sequencing results indicates that genes associated with neuronal projection guidance, metabolism, and translation are direct targets of Da. In addition, we validate the involvement of Da in memory formation. Overall, our results provide valuable information about the functions of Da in the adult brain and aid in better understanding the mechanisms of TCF4-related disorders.

Episodic timing refers to the one-shot, automatic encoding of temporal information in the brain, in the absence of attention to time. A previous magnetoencephalography (MEG) study showed that the relative burst time of spontaneous alpha oscillations (α) during quiet wakefulness was a selective predictor of retrospective duration estimation. This observation was interpreted as α embodying the "ticks" of an internal contextual clock. Herein, we replicate and extend these findings using electroencephalography (EEG), assess robustness to time-on-task effects, and test the generalizability in virtual reality (VR) environments. In three EEG experiments, 128 participants of either sex underwent 4 min eyes-open resting-state recordings followed by an unexpected retrospective duration estimation task. Experiment 1 tested participants before any tasks, Experiment 2 after 90 min of timing tasks, and Experiment 3 in VR environments of different sizes. We successfully replicated the original MEG findings in Experiment 1 but did not in Experiment 2. We explain the lack of replication through time-on-task effects (changes in α power and topography) and contextual changes yielding a cognitive strategy based on temporal expectation (supported by a fast passage of time). In Experiment 3, we did not find the expected duration underestimation in VR and did not replicate the correlation between α bursts and retrospective time estimates. Overall, while EEG captures the α burst marker of episodic timing, its reliability depends critically on experimental context. Our findings highlight the importance of controlling experimental context when using α bursts as a neural marker of episodic timing.

Mirror invariance is the cognitive tendency to perceive mirror-image objects as identical. Mirrored letters, however, are distinct orthographic units and must be identified as different despite having the same shape. Consistent with this phenomenon, a small, localized region in the ventral visual stream, the Visual Word Form Area (VWFA), exhibits repetition suppression to both identical and mirror pairs of objects but only to identical, not mirror, pairs of letters ( Pegado et al., 2011), a phenomenon named mirror invariance "breaking". The ability of congenitally blind individuals to "break" mirror invariance for pairs of mirrored Braille letters has been demonstrated behaviorally ( de Heering et al., 2018, Korczyk et al., 2024). However, its neural underpinnings have not yet been investigated. Here, in an fMRI repetition suppression paradigm, congenitally blind individuals (8 males and 10 females) recognized pairs of everyday objects and Braille letters in identical ("p" and "p"), mirror ("p" and "q"), and different ("p" and "z") orientations. We found repetition suppression for identical and mirror pairs of everyday objects in the parietal and ventral-lateral occipital cortex, indicating that mirror-invariant object recognition engages the ventral visual stream in tactile modality as well. However, repetition suppression for identical but not mirrored pairs of Braille letters was found not in the VWFA, but in broad areas of the left parietal cortex and the lateral occipital cortex. These results suggest that reading-related orthographic processes in blind individuals depend on different neural computations than those of the sighted.

There has been a long-term need for a low-cost, highly efficient, and high-fidelity epilepsy monitoring unit (EMU) suitable for synchronized multimodal home-cage monitoring of small-animal models of epilepsy and spreading depolarization. We present an accessible, scalable, highly space- and energy-efficient EMU capable of fulfilling chronic, continuous, synchronized, multiple-animal monitoring jobs. Each rig within the EMU can provide 16-channel high-fidelity, DC-sensitive biopotential recordings, head acceleration monitoring, voltammetry applications, and synchronized video recording on one freely moving rat. We present the overall EMU architecture design and subsystem details in each recording rig. We demonstrate long-term continuous in vivo recordings of spontaneous seizure and seizure-associated spreading depolarization from freely moving rats (male, 21; female, 6) prepared under the tetanus toxin model of temporal lobe epilepsy.

The growing therapeutic promise of repeated, low-dose ketamine treatment across various psychopathologies-including depression and drug addiction-warrants clarity on its potential addictive properties and their associated mechanisms in both sexes. Accordingly, the present work examined the effects of intermittent low-dose ketamine in male and female rats on behavioral sensitization to the locomotor-activating effects of ketamine, as well as associated molecular profiles in dopamine D1- and D2-receptor-expressing medium spiny neurons (D1- and D2-MSNs) of the nucleus accumbens (NAc). Following intra-NAc infusion of a Cre-inducible RiboTag virus, locomotor activity was measured in adult Drd1a-iCre and Drd2-iCre male and female rats in either diestrus or proestrus following repeated administration of ketamine (0, 10, or 20 mg/kg, i.p.) to evaluate the development of locomotor sensitization. Female-but not male-rats developed sensitization to the locomotor-activating effects of ketamine, occurring more rapidly in proestrus than in diestrus females at the lower dose tested. To examine enduring context- and cell-type-specific changes in translating mRNAs associated with sensitization to ketamine, RNA sequencing was performed on polyribosome-bound mRNA of D1- and D2-MSNs isolated from the NAc of sensitized females in a drug-free state. A greater number of differentially expressed genes were observed selectively in D1-MSNs of ketamine-treated proestrus versus diestrus females, which were broadly related to regulation of transcription and epitranscriptional modification. These findings provide novel evidence of cell-type-specific and estrous cycle-dependent molecular profiles responsive to intermittent ketamine treatment in female rats and identify posttranscriptional mechanisms with relevance to ketamine's effects on behavioral plasticity.