Monday, November 18th, 2024

Time	Event
12:47a	Visual training induced occipital fast sleep spindle clustering in humans revealed by full-night HD-EEG recordings This study investigates the impact of extensive visual procedural training on the temporal organisation of sleep spindles in healthy young adults. We selected 39 participants aged 16-20 and employed high-density electroencephalography to assess spindle characteristics during two full nights of sleep, with daytime practising in a contour integration task in between the two nights. We utilised linear mixed models to comprehensively analyse the effects of age and training on basic, clustering- and rhythmicity-related spindle parameters. Our findings indicate no significant age effects in this age-range, and no significant change between the two nights with respect to slow spindles. Fast spindles demonstrated a significant increase in density after training, and we observed significant changes in spindle clustering and rhythmicity parameters as well. Local spindle density, train density, and the ratio of clustered spindles have increased, and inter-train interval decreased by the second night. These results contribute to the growing literature on sleep-dependent memory consolidation by demonstrating that spindle reorganisation occurs not only in motor tasks but also in visual learning contexts. The absence of age-related differences further highlights the robustness of these mechanisms across developmental stages. Our study emphasises the importance of spindle dynamics in procedural learning and suggests promising possibilities for future research into the neurophysiological basis of memory consolidation. By revealing the relationship between training and sleep spindle characteristics, our findings provide valuable insights into how sleep supports learning and memory processes in young adults, potentially informing interventions aimed at enhancing memory performance through sleep-related strategies. (Comment on this)
12:47a	Regulation of Fentanyl Reward in Male and Female Mice by the Circadian Transcription Factor NPAS2 Synthetic opioids like fentanyl are highly potent and prevalent in the illicit drug market, leading to tolerance, dependence, and opioid use disorder (OUD). Chronic opioid use disrupts sleep and circadian rhythms, which persist even during treatment and abstinence, increasing the risk of relapse. The body's molecular clock, regulated by transcriptional and translational feedback loops, controls various physiological processes, including the expression of endogenous opioids and their receptors. The circadian transcription factor NPAS2, highly expressed in the nucleus accumbens, may have a crucial function in opioid-related behaviors. Our study found sex-specific roles for NPAS2-mediated reward behaviors in male and female mice, including in fentanyl seeking and craving. We also identified specific cell types and transcriptional targets in the nucleus accumbens of both mice and humans by which NPAS2 may mediate the impact of fentanyl on brain physiology and in opioid reward-related behaviors. Ultimately, our findings begin to uncover the mechanisms underlying circadian rhythm dysfunction and opioid addiction. (Comment on this)
1:17a	Individual brain activity patterns during task are predicted by distinct resting-state networks that may reflect local neurobiological features Understanding how individual cortical features shape functional brain organization offers a promising framework for examining the principles of cognitive specialization in the human brain. This study explores the relationship between various cortical characteristics--i.e resting-state functional connectivity, structural connectivity, microstructure, morphology, and geometry--and the layout of task-specific functional activations. We employ linear models to predict the functional layout of the cortex at the individual level from each of these feature modalities. Our findings demonstrate that resting-state component loadings predict individual task activations, consistently across hemispheres and independent datasets. Whereas the first few components provide a common space for functional activations across tasks, predictive higher-order component loadings demonstrated task-specificity. Cortical microstructure/morphology was notably predictive of activation strength in the occipital cortex, highlighting its relevance for cortical functional specialization. By relating resting state components to a set of reference maps of cortical organization, we identify associations that suggest possible neurobiological underpinnings of specific cognitive functions. The remaining feature modalities were only predictive of group-level functional activations. These results advance our understanding of how distinct cortical features may contribute to functional specialization, guiding future inquiry into the organization of cognitive functions on the cortex. (Comment on this)
2:30a	Biophysical network modeling of temporal and stereotyped sequence propagation of neural activity in the premotor nucleus HVC Stereotyped neural sequences are often exhibited in the brain, yet the neurophysiological mechanisms underlying their generation are not fully understood. Birdsong is a prominent model to study such behavior particularly because juvenile songbirds progressively learn from their tutors and by adulthood are able to sing stereotyped song patterns. The songbird premotor nucleus HVC coordinate motor and auditory activity responsible for learned vocalizations. The HVC comprises three neural populations that has distinct in vitro and in vivo electrophysiological responses. Typically, models that explain HVCs network either rely on intrinsic HVC circuitry to propagate sequential activity, rely on extrinsic feedback to advance the sequence or rely on both. Here, we developed a physiologically realistic neural network model incorporating the three classes of HVC neurons based on the ion channels and the synaptic currents that had been pharmacologically identified. Our model is based on a feedforward chain of microcircuits that encode for the different sub-syllabic segments (SSSs) and that interact with each other through structured feedback inhibition. The network reproduced the in vivo activity patterns of each class of HVC neurons, and unveiled key intrinsic and synaptic mechanisms that govern the sequential propagation of neural activity by highlighting important roles for the T-type Ca2+ current, Ca2+-dependent K+ current, A-type K+ current, hyperpolarization activated inward current, as well as excitatory and inhibitory synaptic currents. The result is a biophysically realistic model that suggests an improved characterization of the HVC network responsible for song production in the songbird. (Comment on this)
3:48a	Glutamate receptor-dependent cytosolic acidification in hippocampal neurons involves passive flux of protons from the extracellular space Glutamate receptor-dependent cytosolic acidification can be induced in hippocampal neurons by pharmacological or seizure-like stimulation. This acidification is thought to arise from Ca2+ and metabolism-related processes, however, the exact underlying mechanism as well as its functional role remains uncertain. To reassess the mechanism of cytosolic acidification in excitatory hippocampal neurons and address the physiological relevance of the phenomenon, we combined pH/Ca2+ biosensors to study activity-induced pH dynamics in hippocampal neurons. First, we addressed cytosolic acidification in relation to LTP at hippocampal CA3-CA1 synapses. Using hippocampal slices from adult rats of both sexes, we show that LTP-inducing stimulation at the Schaffer collaterals evokes transient cytosolic acidification in hippocampal CA1 neurons. This highlights neuronal pH shifts as a trait of general hippocampal neurotransmission rather than a marker of excitotoxicity, possibly serving as a secondary messenger. Moreover, using dissociated hippocampal neurons from rat embryos, we show that glutamate receptor agonists typically induce larger cytosolic acid shifts compared to simple depolarization or spontaneous activity, suggesting that glutamate receptor-mediated acidification involves several separate mechanisms; pyruvate-dependent dampening of neuronal acidification may reflect a direct inhibition of NMDA receptors rather than reduced glycolytic activity, questioning the previously reported involvement of metabolism in cytosolic acidification; and whereas acid shifts induced by simple depolarization show exclusive dependence on cytosolic Ca2+, AMPA-induced acidification depends both on cytosolic Ca2+ and on an inward electrochemical driving force for protons. These results suggest that glutamate receptor-induced cytosolic acidification relies both on cytosolic Ca2+ and on a passive proton influx, possibly mediated by the receptor itself. (Comment on this)
4:46p	Top-Down Effects on Translucency Perception in Relation to Shape Cues It is well established that object shape perception significantly influences the perception of translucency. However, how object shape cues such as motion and binocular disparity affect the perception of translucency in rich environments, like virtual reality or real visual environments, remains unclear. This study aims to psychophysically measure the extent to which multiple object shape cues influence the perception of translucency. Additionally, we examined whether top-down factors, such as changes in cognitive attitude caused by the sequence of experiments, affect translucency perception. The results revealed that while motion and binocular disparity enhance translucency perception, this effect is confined to situations where shape cues are poor. Moreover, the effect became particularly pronounced when the experiments began with weak specular reflection stimuli, followed by the experiments using stimuli with specular reflection. In the case of translucent objects without specular reflection, strong shape information cannot be derived solely from shading patterns. These findings thus suggest that top-down factors related to shape modulate the influence of shape cues on translucency perception. (Comment on this)
6:49p	Comparing neurocognitive mechanisms of mathematical ability and fluency in children: insights from an fNIRS study Background Early proficiency in mathematics is a strong predictor of later academic success and life achievement, considering the practical skills that mastering the subject enables students to equip. Yet, there exists a paucity of research into the neural mechanisms supporting mathematical abilities in young children. Recent research utilises resting state functional connectivity (RSFC), a measure of the coherence of brain activity among brain regions in the absence of tasks, to understand the functional roles of these regions. Methods We analysed the RSFC of 45 children to investigate the intrinsic cognitive processes underpinning arithmetic processing in three regions of interest (ROIs): middle frontal gyrus, inferior parietal lobule, and precuneus. Correlations between RSFC among these regions and mathematics or math fluency scores, derived from the Wechsler Individual Achievement Test (WIAT-III), were examined. Results RSFC between the right precuneus and both the ipsilateral middle frontal gyrus and inferior parietal region may be associated with arithmetic processing speed and accuracy, while cross-hemispheric RSFC between the right precuneus and the left inferior parietal lobule appears to be associated with problem-solving and numeracy skills. RSFC between the right precuneus and left inferior parietal lobule differed in children performing below the 10th percentile in mathematics (out of 45 participants). Conclusions The results suggest that children of the same age may follow different neural development trajectories. More targeted and differentiated interventions are essential to offer additional and early support for students struggling with mathematics. (Comment on this)
6:49p	Time affects a time-consuming, flexible component and a fast, inflexible component of sensorimotor adaptation. Prior learning can impair future learning when the requirements of the two memories conflict, in a phenomenon termed anterograde interference. In sensorimotor adaptation, the passage of time between initial and future learning can reduce such interference effects. However, we still do not fully understand how time affects learning, as some studies found no effect of time on interference. One possible explanation is that time affects distinct processes underpinning sensorimotor adaptation, and these processes may compensate for each others' effects on behaviour. Here, we used task manipulations that (1) dissociated adaptation processes driven by task errors from adaptation processes driven by sensory prediction errors, and (2) separated the task-error driven adaptation processes into a flexible component that could not be acquired under time-pressure, and a less-flexible component that could be acquired under time-pressure. The passage of time between initial and subsequent learning seemed to alter both the flexible and inflexible components of adaptation driven by task errors. Time also led to a small reduction of interference arising from sensory prediction errors. Thus, we provide evidence that multiple components of sensorimotor adaptation are sensitive to the passage of time. (Comment on this)
9:30p	Grid to Place Cell Connectivity in Eleven Different Rooms To understand the grid to place cell connectivity, we took place cell firing data from Moser lab. In MATLAB, we created grid cell firing patterns. Connection weights between the two were learned with backpropagation algorithm. The smaller place fields could be learned from grid cells with single spatial firing frequency. But bigger, multiple and irregular place fields could only be learned from grid cells with multiple spatial firing frequencies. Weights learned were normally distributed with a wider spread and multimodal distribution for rooms with uneven, larger or multiple firing fields. We conclude that each place cell is connected to single modules of grid cells with similar spatial firing frequency. Place cells connected to multi-frequency grid cells are fewer. Our results also show that grid cells resolve the space into spatial distance, orientation, and phase offset. Unique firing patterns of the place cells codify each room with this information. (Comment on this)
11:35p	Criterial Learning and Feedback Delay: Insights from Computational Models and Behavioral Experiments The notion of a response criterion is ubiquitous in psychology, yet its cognitive and neural underpinnings remain poorly understood. To address this shortcoming, three computational models that capture different hypotheses about criterial learning were developed and tested. The time-dependent drift model assumes the criterion is stored in working memory and that its value drifts over time. The delay-sensitive learning model assumes that the magnitude of criterial learning is temporally discounted by feedback delay. The reinforcement-learning model assumes that criterial learning emerges from stimulus-response association learning without an explicit representation of the criterion, with learning rate also temporally discounted by feedback delay. The performance of these models was investigated under varying feedback delay and intertrial interval (ITI) durations. The time-dependent drift model predicted that long ITIs and feedback delays both impair criterial learning. In contrast, the delay-sensitive and reinforcement-learning models predicted impairments only with feedback delays. Two behavioral experiments, which tested these predictions, showed that human criterial learning is impaired by delayed feedback but not by long ITIs. These results support the delay-sensitive and reinforcement-learning models, and suggest that even in tasks that appear to rely on explicit, rule-based reasoning, criterial learning may have strong associative underpinnings. (Comment on this)

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