Patterns Of Neural Activity Research Articles

Decoding multi-limb movements from two-photon calcium imaging of neuronal activity using deep learning

Objective.Brain-machine interfaces (BMIs) aim to restore sensorimotor function to individuals suffering from neural injury and disease. A critical step in implementing a BMI is to decode movement intention from recorded neural activity patterns in sensorimotor areas. Optical imaging, including two-photon (2p) calcium imaging, is an attractive approach for recording large-scale neural activity with high spatial resolution using a minimally-invasive technique. However, relating slow two-photon calcium imaging data to fast behaviors is challenging due to the relatively low optical imaging sampling rates. Nevertheless, neural activity recorded with 2p calcium imaging has been used to decode information about stereotyped single-limb movements and to control BMIs. Here, we expand upon prior work by applying deep learning to decode multi-limb movements of running mice from 2p calcium imaging data.Approach.We developed a recurrent encoder-decoder network (LSTM-encdec) in which the output is longer than the input.Main results.LSTM-encdec could accurately decode information about all four limbs (contralateral and ipsilateral front and hind limbs) from calcium imaging data recorded in a single cortical hemisphere.Significance.Our approach provides interpretability measures to validate decoding accuracy and expands the utility of BMIs by establishing the groundwork for control of multiple limbs. Our work contributes to the advancement of neural decoding techniques and the development of next-generation optical BMIs.

Maternal care is associated with neural and behavioral effects of oxytocin administration during empathic accuracy in schizophrenia and controls

Empathic accuracy, the ability to accurately understand other people’s emotions, is a complex social cognitive skill that is often impaired in schizophrenia and this impairment is associated with poor functional outcomes. Intranasally administered oxytocin, a neuropeptide implicated in social behavior, is thought to improve empathic accuracy for individuals with schizophrenia. However, early experiences related to caregiving may shape the oxytocinergic system and influence individual responses to oxytocin administration. Using a cross-over, double-blind, placebo-controlled design coupled with fMRI, the current study investigated whether administration of oxytocin improves empathic accuracy in schizophrenia compared to a matched placebo, and the moderating role of early maternal care. Results revealed that, compared to controls, individuals with schizophrenia had lower empathic accuracy and recruited a sparser pattern of neural activation to achieve empathic accuracy. Oxytocin administration was not associated with improved empathic accuracy for either group. However, in both groups, individuals reporting higher maternal care demonstrated the greatest improvements in empathic accuracy with oxytocin administration, accompanied by decreased activity in the right dorsolateral prefrontal cortex, a region implicated in selective attention to socioemotional stimuli. Findings highlight the importance of examining individual differences in responses to oxytocin administration and suggest that early social experiences influence later responses to oxytocin administration.

Enhancing prediction of human traits and behaviors through ensemble learning of traditional and novel resting-state fMRI connectivity analyses

Recent advances in cognitive neuroscience have focused on using resting-state functional connectivity (RSFC) data from fMRI scans to more accurately predict human traits and behaviors. Traditional approaches generally analyze RSFC by correlating averaged time-series data across regions of interest (ROIs) or networks, which may overlook important spatial signal patterns. To address this limitation, we introduced a novel linear regression technique that estimates RSFC by predicting spatial brain activity patterns in a target ROI from those in a seed ROI. We applied both traditional and our novel RSFC estimation methods to a large-scale dataset from the Human Connectome Project and the Brain Genomics Superstruct Project, analyzing resting-state fMRI data to predict sex, age, personality traits, and psychological task performance. To enhance prediction accuracy, we developed an ensemble learner that combines these qualitatively different methods using a weighted average approach. Our findings revealed that hierarchical clustering of RSFC patterns using our novel method displays distinct whole-brain grouping patterns compared to the traditional approach. Importantly, the ensemble model, integrating these diverse weak learners, outperformed the traditional RSFC method in predicting human traits and behaviors. Notably, the predictions from the traditional and novel methods showed relatively low similarity, indicating that our novel approach captures unique and previously undetected information about human traits and behaviors through fine-grained local spatial patterns of neural activation. These results highlight the potential of combining traditional and innovative RSFC analysis techniques to enrich our understanding of the neural basis of human traits and behaviors.

Effects of robot-assisted hand function therapy on brain functional mechanisms: a synchronized study using fNIRS and sEMG.

Robot-assisted hand function therapy is pivotal in the rehabilitation of patients with stroke; however, its therapeutic mechanism remains elusive. Currently, research examining the impact of robot-assisted hand function therapy on brain function in patients with stroke is scarce, and there is a lack of studies investigating the correlation between muscle activity and alterations in brain function. This study aimed to investigate the correlation between forearm muscle movement and brain functional activation by employing the synchronized use of functional near-infrared spectroscopy and surface electromyography methods. Moreover, it sought to compare neural activity patterns during different rehabilitation tasks and refine the mechanism of robot-assisted hand function therapy for post-stroke hand function impairments. Stroke patients with hand dysfunction underwent three sessions of robot-assisted hand function therapy within 2 weeks to 3 months of onset. The fNIRS-sEMG synchronous technique was used to observe brain function and forearm muscle activation. Ten participants were randomly assigned to receive mirror, resistance, or passive rehabilitation training. During the intervention, cortical and muscle activation information was obtained using fNIRS and electromyographic signals. The primary outcomes included changes in oxyhemoglobin concentration and root mean square of surface electromyography. Compared to the resting state, the Oxy-Hb concentration in the brain regions involved in three rehabilitation tasks with robot-assisted hand function therapy significantly increased (p < 0.05). Mirror therapy significantly enhanced the prefrontal cortex and the superior frontal cortex activation levels. In contrast, resistance therapy significantly promoted the activation of the supplementary motor area and the premotor cortex. Passive rehabilitation tasks showed some activation in the target brain area premotor cortex region. Robot-assisted hand function therapy has shown that forearm muscle movement is closely related to oxygenated hemoglobin concentration activity in specific brain regions during different rehabilitation tasks. The simultaneous sEMG-fNIRS study found a significant correlation between muscle movement and brain activity after stroke, which provides an important basis for understanding the treatment mechanism of hand function impairment.

The role of mirror neurons in empathy, with a focus on their relevance in autism spectrum disorder and other clinical implications

Introduction Mirror neurons are brain cells that engage when an individual performs an action and then observes another person completing the same action. These neurons are supposed to help us grasp others' emotions and intentions by mimicking their experiences. This has led to the theory that mirror neurons influence empathy, or the ability to share and understand the experiences of others. The article investigates the role of mirror neurons in empathy, specifically their potential contribution to emotional resonance, perspective-taking, their relevance in autism spectrum disorder and other clinical implications. Aim of the study The aim of this comprehensive review is to provide an overview of how mirror neurones contribute to the development and expression of empathy in humans, with a focus on their role in autism spectrum disorder. The objective of this research is to clarify the role of mirror neurons in social cognition and gain a better understanding of the neurological foundation for empathy. Materials and methods Scientific articles from the Pubmed, Google Scholar, and Web of Science databases were analysed. The goal of this study was to choose recent articles that most adequately encompassed the problems under consideration. The search was conducted out using the following keylords: mirror neurones, empathy and autism spectrum disorder. Summary Mirror neurones appear to play an important part in empathy, as evidenced by neural activity patterns during emotion identification. While they are not the single source of empathy or the only trigger, they are definitely present. Conflicting evidence limits our understanding of their exact impact, and more credible studies need to be conducted. However, current research reveals that mirror neurones have a measurable, although limited, impact on empathy.

Application of Multi-Input Multi-Output Brain-Computer Interface in Cognitive Assessment for Alzheimer’s Disease

This research aims to augment human cognitive abilities, particularly memory function, through the development of innovative prosthetics. The hippocampus, a crucial brain region involved in memory encoding and recall, has been the focal point of numerous studies seeking to develop prosthetics that can restore or enhance memory function in individuals with impairments such as Alzheimer’s disease. This review examines two studies that delve into the development and application of hippocampal neural prosthetics, highlighting the potential of these prosthetics to revolutionize the treatment of memory impairments. One study utilized static neural stimulation patterns to enhance memory for specific information content, while another developed a nonlinear Multiple Input Multiple Output (MIMO) dynamic model to predict and stimulate neural activity patterns during memory encoding. Both studies demonstrated significant improvements in memory performance. Additionally, this paper discusses the clinical significance and application prospects of hippocampal neural prosthetics, including the potential for implantable prosthetics and the widespread applicability of MIMO stimulation. Furthermore, the paper explores advanced modeling and classification techniques for neural ensembles and visual memory decoding, including Volterra-type hierarchical modeling, optimal multi-unit stimulation patterns, and a sparse classification model for decoding visual memories. Finally, the paper presents the implementation and evaluation of neural prosthesis systems, including an application-specific integrated circuit (ASIC) design for a hippocampal prosthesis and a high-performance, scalable system architecture for real-time estimation of neural activity. These advancements hold promise for future research and applications in neural prosthetics for memory enhancement.

A common neural response to perceiving but not implicitly regulating infant and adult affect in postpartum mothers

ABSTRACT The transition to parenthood requires parents develop caregiving behaviors, such as the ability to identify their infant’s emotions and regulate their own emotional response. Research has identified patterns of neural activation in parenting contexts that are interpreted as socioemotional processing. However, no prior research has directly tested whether mothers’ neural responses to their infant’s affect are the same as those involved in emotion perception/experience and regulation in other contexts. We employed conjunction analyses to clarify which components of mothers’ neural response to viewing their infant’s affect are shared with passively viewing and labeling adult affective faces (emotion perception/experience and implicit emotion regulation, respectively) in 24 mothers three months postpartum. Our results support a common neural response to viewing infant and adult affect in regions associated with emotion perception/experience (bilateral hippocampi, amygdalae, thalami, orbitofrontal cortex, and ventrolateral prefrontal cortex), but no areas of common response to viewing negative infant affect and implicitly regulating negative adult affect outside of the occipital lobe and cerebellum. This study provides corroborating evidence for shared neural patterns being involved in perceiving/experiencing infant and adult affect but not implicit regulation of infant and adult negative affect.

Altered neural activities during emotion regulation in depression: a meta-analysis.

Deficient neural activities during emotion regulation have been reported in depression. We sought to conduct a meta-analysis to provide a comprehensive description of these neural alterations during use of emotion regulation strategies among patients with depression, including major depressive disorder (MDD) and bipolar disorder (BD). We identified neuroimaging studies of abnormal neural activities during emotion regulation in depression. We extracted the peak coordinates and effect sizes of differences in brain activity between patients and healthy controls. Using seed-based d mapping, we conducted voxel-wise meta-analyses of the neural activation pattern differences between the 2 groups across conditions involving emotion regulation and those where emotion regulation was not needed. We included 33 studies reporting 34 data sets, including 23 involving MDD (571 people with MDD and 578 matched controls) and 11 involving BD (358 people with BD and 369 matched controls). Overall, compared with controls, patients with depression showed hyperactivity in the insula and postcentral gyrus, and hypoactivity in the prefrontal part of the inferior, middle, and superior frontal gyrus, the middle temporal gyrus, and the supplementary motor area. In subgroup analyses, data from patients with MDD and studies focused on decreasing negative emotions or using the emotional strategy of reappraisal reported specific hypoactivity in the middle cerebellar peduncles. Given limited studies involving patients with BD, we were unable to detect the common and distinct abnormalities in neural activation between MDD and BD. We did not conduct any meta-regression analyses because of limited information. In this meta-analysis, we identified hyperactivity in brain regions associated with emotional experience and hypoactivity in brain regions associated with cognitive control during emotion regulation among patients with depression, relative to healthy controls. These findings could help indicate a target for future interventions aimed at increasing emotion regulation capacity for patients with depression.

40 Hz sensory stimulation enhances CA3-CA1 coordination and prospective coding during navigation in a mouse model of Alzheimer's disease.

Brain stimulation has emerged as a new potential therapeutic approach to potentially correct or improve altered neural activity in Alzheimer's disease. One such approach, 40 Hz sensory stimulation, or flicker, has been shown to improve cognition in disease models. However, it is not clear how 40 Hz flicker affects neural activity underlying memory processes. Here, we investigate how 40 Hz flicker exposure affects neural activity patterns that are crucial for memory. We find 40Hz flicker increases neural coordination in memory circuits, indicating better communication. Furthermore, 40Hz flicker increased neural representations of future positions, patterns theorized to support memory-based planning. These results indicate that 40 Hz flicker increases key neural activity that is important for memory.

Intrinsic dynamics of randomly clustered networks generate place fields and preplay of novel environments.

During both sleep and awake immobility, hippocampal place cells reactivate time-compressed versions of sequences representing recently experienced trajectories in a phenomenon known as replay. Intriguingly, spontaneous sequences can also correspond to forthcoming trajectories in novel environments experienced later, in a phenomenon known as preplay. Here, we present a model showing that sequences of spikes correlated with the place fields underlying spatial trajectories in both previously experienced and future novel environments can arise spontaneously in neural circuits with random, clustered connectivity rather than pre-configured spatial maps. Moreover, the realistic place fields themselves arise in the circuit from minimal, landmark-based inputs. We find that preplay quality depends on the network's balance of cluster isolation and overlap, with optimal preplay occurring in small-world regimes of high clustering yet short path lengths. We validate the results of our model by applying the same place field and preplay analyses to previously published rat hippocampal place cell data. Our results show that clustered recurrent connectivity can generate spontaneous preplay and immediate replay of novel environments. These findings support a framework whereby novel sensory experiences become associated with preexisting "pluripotent" internal neural activity patterns.

Intrinsic dynamics of randomly clustered networks generate place fields and preplay of novel environments

During both sleep and awake immobility, hippocampal place cells reactivate time-compressed versions of sequences representing recently experienced trajectories in a phenomenon known as replay. Intriguingly, spontaneous sequences can also correspond to forthcoming trajectories in novel environments experienced later, in a phenomenon known as preplay. Here, we present a model showing that sequences of spikes correlated with the place fields underlying spatial trajectories in both previously experienced and future novel environments can arise spontaneously in neural circuits with random, clustered connectivity rather than pre-configured spatial maps. Moreover, the realistic place fields themselves arise in the circuit from minimal, landmark-based inputs. We find that preplay quality depends on the network’s balance of cluster isolation and overlap, with optimal preplay occurring in small-world regimes of high clustering yet short path lengths. We validate the results of our model by applying the same place field and preplay analyses to previously published rat hippocampal place cell data. Our results show that clustered recurrent connectivity can generate spontaneous preplay and immediate replay of novel environments. These findings support a framework whereby novel sensory experiences become associated with preexisting “pluripotent” internal neural activity patterns.

Evaluation of the influence of athlete neural activity patterns on the dynamic index of leaping ability using data mining techniques

There are many dynamic indicators of jumping ability, and the athlete’s neural activity pattern is an important factor in regulating limb activities. This article uses data mining technology to collect, preprocess, data modeling and analysis, and data visualization of dynamic index data of athletes’ neural activity patterns of jumping ability. The results show that the jumping ability of athletes with higher neural activity intensity increased significantly after training to around 40 cm–50 cm, while athletes with lower neural activity intensity did not change significantly and remained around 30 cm–35 cm. The overall learning ability of athletes with higher levels of neural activity improved by about 10 cm, and the base of neural activity also increased significantly. It shows that there is a significant correlation between the intensity of neural activity and dynamic indicators of jumping ability, which is the main driving force for athletes’ jumping explosive power. The research results can help formulate reasonable and scientific training methods to improve athletes’ jumping ability and overall sports level.

Disrupted Hippocampal-Prefrontal Networks in a Rat Model of Fragile X Syndrome: A Study Linking Neural Dynamics to Autism-Like Behavioral Impairments.

FMR-KO and control rats underwent a battery of behavioral tests assessing sociability, memory, and anxiety. Single-unit electrophysiology recordings were then conducted to measure patterns of neural activity in H-PFC circuit. Advanced mathematical models were used to characterize the patterns that were then compared between groups using generalized linear mixed models. FMR-KO rats demonstrated significant behavioral deficits in sociability, spatial learning, and anxiety, aligning with symptoms of ASD. At the neural level, these rats exhibited abnormal firing patterns in the H-PFC circuit that is critical for learning, memory, and social behavior. The neural networks in FMR-KO rats were also less densely connected and more fragmented, particularly in hippocampal-PFC correlated firing. These findings suggest that disruptions in neural network dynamics underlie the observed behavioral impairments in FMR-KO rats. FMR-KO significantly disrupts several characteristics of action potential firing in the H-PFC network, leading to deficits in social behavior, memory, and anxiety, as seen in FXS. This disruption is characterized by less organized and less resilient hippocampal-PFC networks. These findings suggest that therapeutic strategies aimed at normalizing neural dynamics, such as with brain stimulation, could potentially improve behavior and cognitive functions in autistic individuals. Fragile X Syndrome is associated with autism, cognitive challenges and anxietyThe loss of Fmr1 protein disrupts processes involved in building neural networksThe consequence is abnormal neural dynamics in hippocampal-prefrontal cortex networksNormalization of dynamics could improve outcomes in FXS and ASD.

Neural Mechanisms of Social Interaction Perception: Observing Interpersonal Synchrony Modulates Action Observation Network Activation and Is Spared in Autism.

How the temporal dynamics of social interactions are perceived arguably plays an important role in how one engages in social interactions and how difficulties in establishing smooth social interactions may occur. One aspect of temporal dynamics in social interactions is the mutual coordination of individuals' behaviors during social interaction, otherwise known as behavioral interpersonal synchrony (IPS). Behavioral IPS has been studied increasingly in various contexts, such as a feature of the social interaction difficulties inherent to autism. To fully understand the temporal dynamics of social interactions, or reductions thereof in autism, the neural basis of IPS perception needs to be established. Thus, the current study's aim was twofold: to establish the basic neuro-perceptual processing of IPS in social interactions for typical observers and to test whether it might differ for autistic individuals. In a task-based fMRI paradigm, participants viewed short, silent video vignettes of humans during social interactions featuring a variation of behavioral IPS. The results show that observing behavioral IPS modulates the Action Observation Network (AON). Interestingly, autistic participants showed similar neural activation patterns as non-autistic participants which were modulated by the behavioral IPS they observed in the videos, suggesting that the perception oftemporal dynamics of social interactions is spared and may not underly reduced behavioral IPS often observed in autism. Nevertheless, a general difference in processing social interactions was found in autistic observers, characterized by decreased neural activation in the right middle frontal gyrus, angular gyrus, and superior temporal areas. These findings demonstrate that although the autistic and non-autistic groups indeed differed in the neural processing of social interaction perception, the temporal dynamics of these social interactions were not the reason for these differences in social interaction perception in autism. Hence, spared recruitment of the AON for processing temporal dynamics of social interactions in autism does not account for the widely reported attenuation of IPS in autism and for the widely reported and presently observed differences in social interaction perception in autism.

State of the Art of Brain Function Detection Technologies in Robot-Assisted Lower Limb Rehabilitation.

Background: With an aging population, the prevalence of neurological disorders is increasing, leading to a rise in lower limb movement disorders and, in turn, a growing need for rehabilitation training. Previous neuroimaging studies have shown a growing scientific interest in the study of brain mechanisms in robot-assisted lower limb rehabilitation (RALLR). Objective: This review aimed to determine differences in neural activity patterns during different RALLR tasks and the impact on neurofunctional plasticity. Methods: Sixty-five articles in the field of RALLR were selected and tested using three brain function detection technologies. Results: Most studies have focused on changes in activity in various regions of the cerebral cortex during different lower limb rehabilitation tasks but have also increasingly focused on functional changes in other cortical and deep subcortical structures. Our analysis also revealed a neglect of certain task types. Conclusion: We identify and discuss future research directions that may contribute to a clear understanding of neural functional plasticity under different RALLR tasks. Impact Statement The evaluation of robot-assisted lower limb rehabilitation based on brain function detection technology can assess the neurological changes of patients in the rehabilitation process by monitoring brain activities and can also provide more accurate guidance for robot-assisted lower limb rehabilitation. By monitoring the patient's brain activity, the robot can adjust according to the real-time status of the patient to achieve more effective rehabilitation training. This has potential impact on improving the rehabilitation effect and speeding up the rehabilitation process of patients.

Dynamics of Saccade Trajectory Modulation by Distractors: Neural Activity Patterns in the Frontal Eye Field.

The sudden appearance of a visual distractor shortly before saccade initiation can capture spatial attention and modulate the saccade trajectory in spite of the ongoing execution of the initial plan to shift gaze straight to the saccade target. To elucidate the neural correlates underlying these curved saccades, we recorded from single neurons in the frontal eye field (FEF) of two male rhesus monkeys shifting gaze to a target while a distractor with the same eccentricity appeared either left or right of the target at various delays after target presentation. We found that the population level of pre-saccadic activity of neurons representing the distractor location encoded the direction of the saccade trajectory. Stronger activity occurred when saccades curved toward the distractor, and weaker when saccades curved away. This relationship held whether the distractor was ipsilateral or contralateral to the recorded neurons. Meanwhile, visually responsive neurons showed asymmetrical patterns of excitatory responses that varied with the location of the distractor and the duration of distractor processing relating to attentional capture and distractor inhibition. During earlier distractor processing, neurons encoded curvature towards the distractor. During later distractor processing, neurons encoded curvature away from the distractor. This was observed when saccades curved away from distractors contralateral to the recording site and when saccades curved towards distractors ipsilateral to the recording site. These findings indicate that saccadic motor planning involves dynamic push-pull hemispheric interactions producing attraction or repulsion for potential but unselected saccade targets.Significant Statement This study not only advances our understanding of oculomotor function in dynamic environments but also has potential clinical relevance for diagnosing and understanding disorders characterized by abnormal saccade trajectories. Our research elucidates the neural mechanisms behind saccade trajectories that are not always linear due to the brain's integration of multiple visual cues and/or motor plans. By analyzing the frontal eye field (FEF) activity in rhesus monkeys, we found that saccade directionality and timing are influenced by the interaction between FEF visual neurons representing target and distractor stimuli. The FEF's role extends beyond a winner-takes-all approach, incorporating saccade vector averaging computations that produce curved saccades. Furthermore, ipsilateral visual neurons encode distractor suppression that drives curvature away from the distractor.

Abnormal beta bursts of depression in the orbitofrontal cortex and its relationship with clinical symptoms

BackgroundRecent researches have reported that frequency-specific patterns of neural activity contain not only rhythmically sustained oscillations but also transient-bursts of isolated events. The aim of this study was to investigated the correlation between beta burst and depression in order to explore depressive disease and the neurological underpinnings of disease-related symptoms. MethodsWe collected resting-state MEG recordings from 30 depressive patients and a matched 40 healthy controls. A Hidden Markov Model (HMM) was applied on source-space time courses for 78 cortical regions of the AAL atlas and the temporal characteristics of beta burst from the matched HMM states were captured. Group differences were evaluated on these beta burst characteristics after permutation tests and, for the depressive group, associations between burst characteristics and clinical symptom severity were determined using Spearman correlation coefficients. ResultsAt a threshold of p=0.05corrected, burst characteristics revealed significant differences between depression patients and controls at the group level, including increased burst amplitude in frontal lobe, decreased burst duration in occipital regions, increased burst rate and decreased burst interval time in some brain regions. Furthermore, burst amplitude in the orbitofrontal cortex (OFC) was positively related to the severity of sleep disturbance and burst rate in the OFC was negatively related to the severity of anxiety in depression patients. ConclusionsThe findings highlight OFC may be a targeted area responsible for the anxiety and sleep disturbance symptom by abnormal beta burst in depressive patients and beta burst characteristics of OFC might serve as a neuro-marker for the depression.

Neural mechanisms associated with sleep-dependent enhancement of motor learning after brain injury.

This study aimed to examine the improvement in performance and functional magnetic resonance imaging correlates of motor learning after a daytime nap versus a period of resting wakefulness among individuals with traumatic brain injury. A sample of 32 individuals with traumatic brain injury was randomly assigned to a Sleep (N = 17) or Wake (N = 15) group after a period of training on a motor sequential learning task. A 45-min nap opportunity was provided for the Sleep group, while the Wake group watched a documentary for 45 min. Performance at the end of training was compared with their performance after the nap or wake intervention. Before and after the intervention, the motor sequential learning task was completed in the magnetic resonance imaging scanner to examine the relationship between change in performance and neural activation. Participants in the Sleep group showed significant gains from the end of training to after the intervention, whereas the Wake group did not. The functional magnetic resonance imaging results showed that relative to the Wake group, the Sleep group showed significantly decreased activation post-intervention in the anterior cingulate/paracingulate, cerebellum, cuneus/precuneus, and inferior parietal lobule including angular and supramarginal gyri. Importantly, across both groups, increased task performance at post-intervention was associated with decreased activation in the anterior cingulate/paracingulate and cerebellum. This study demonstrated the enhancing effect of a nap on motor learning performance in a sample of individuals with traumatic brain injury, with patterns of neural activation suggesting that the sequence was more automatized in the Sleep group. Strategic placement of a nap after an intense period of motor learning in the medical rehabilitation setting may have important implications for maximizing recovery after traumatic brain injury.

Cortically Disparate Visual Features Evoke Content-Independent Load Signals during Storage in Working Memory.

It is well established that holding information in working memory (WM) elicits sustained stimulus-specific patterns of neural activity. Nevertheless, here we provide evidence for a distinct class of neural activity that tracks the number of individuated items in working memory, independent of the type of visual features stored. We present two EEG studies of young adults of both sexes that provide robust evidence for a signal tracking the number of individuated representations in working memory, regardless of the specific feature values stored. In Study 1, subjects maintained either colors or orientations across separate blocks in a single session. We found near-perfect generalization of the load signal between these two conditions, despite being able to simultaneously decode which feature had been voluntarily stored. In Study 2, participants attended to two features with very distinct cortical representations: color and motion coherence. We again found evidence for a neural load signal that robustly generalized across these distinct visual features, even though cortically disparate regions process color and motion coherence. Moreover, representational similarity analysis provided converging evidence for a content-independent load signal, while simultaneously showing that unique variance in EEG activity tracked the specific features that were stored. We posit that this load signal reflects a content-independent "pointer" operation that binds objects to the current context while parallel but distinct neural signals represent the features that are stored for each item in memory.

Pairing tones with vagus nerve stimulation improves brain stem responses to speech in the valproic acid model of autism.

Receptive language deficits and aberrant auditory processing are often observed in individuals with autism spectrum disorders (ASD). Symptoms associated with ASD are observed in rodents prenatally exposed to valproic acid (VPA), including deficits in speech sound discrimination ability. These perceptual difficulties are accompanied by changes in neural activity patterns. In both cortical and subcortical levels of the auditory pathway, VPA-exposed rats have impaired responses to speech sounds. Developing a method to improve these neural deficits throughout the auditory pathway is necessary. The purpose of this study was to investigate the ability of vagus nerve stimulation (VNS) paired with sounds to restore degraded inferior colliculus (IC) responses in VPA-exposed rats. VNS paired with the speech sound "dad" was presented to a group of VPA-exposed rats 300 times per day for 20 days. Another group of VPA-exposed rats were presented with VNS paired with multiple tone frequencies for 20 days. The IC responses were recorded from 19 saline-exposed control rats and 18 VPA-exposed with no VNS, 8 VNS-speech paired VPA-exposed, and 7 VNS-tone paired VPA-exposed female and male rats. Pairing VNS with tones increased the IC response strength to speech sounds by 44% compared to VPA-exposed rats alone. Contrarily, VNS-speech pairing significantly decreased the IC response to speech compared with VPA-exposed rats by 5%. The present research indicates that pairing VNS with tones improved sound processing in rats exposed to VPA and suggests that auditory processing can be improved through targeted plasticity.NEW & NOTEWORTHY Pairing vagus nerve stimulation (VNS) with sounds has improved auditory processing in the auditory cortex of normal-hearing rats and autism models of rats. This study tests the ability of VNS-sound pairing to restore auditory processing in the inferior colliculus (IC) of valproic acid (VPA)-exposed rats. Pairing VNS with tones significantly reversed the degraded sound processing in the IC in VPA-exposed rats. The findings provide evidence that auditory processing in autism rat models can be improved through VNS.