Neuroscience Research Research Articles

Comparative analysis of six adeno-associated viral vector serotypes in mouse inferior colliculus and cerebellum.

Adeno-associated viral vector (AAV) serotypes vary in how effectively they express genes across different cell types and brain regions. Here we report a systematic comparison of the AAV serotypes 1, 2, 5, 8, 9, and the directed evolution derived AAVrg, in the inferior colliculus and cerebellum. The AAVs were identical apart from their different serotypes, each having a synapsin promotor and expressing GFP (AAV-hSyn-GFP). Identical titers and volumes were injected into the inferior colliculus and cerebellum of adult male and female mice and brains were sectioned and imaged 2 weeks later. Transduction efficacy, anterograde labeling of axonal projections, and retrograde labeling of somata, were characterized and compared across serotypes. Cell-type tropism was assessed by analyzing the morphology of the GFP-labeled neurons in the cerebellar cortex. In both the cerebellum and inferior colliculus, AAV1 expressed GFP in more cells, labeled a larger volume, and produced significantly brighter labeling than all other serotypes, indicating superior transgene expression. AAV1 labeled more Purkinje cells, unipolar brush cells, and molecular layer interneurons than the other serotypes, while AAV2 labeled a greater number of granule cells. These results provide guidelines for the use of AAVs as gene delivery tools in these regions.Significance statement AAVs have become ubiquitous gene expression tools in neuroscience research and are becoming more common in clinical settings. Naturally occurring and engineered serotypes have varying abilities to infect neurons and cause them to produce proteins of interest. The efficacy of AAV transduction in specific cell types depends on many factors and remains difficult to predict, so an empirical approach is often required to determine the best performing serotype in each population of cells. In the present study we show that AAV1 produces the highest expression in these two regions, labels the most axonal projections, and labels Purkinje cells and unipolar brush cells better than the other serotypes tested, while AAV2 labels granule cells most effectively.

Development of a Marmoset Apparatus for Automated Pulling to study cooperative behaviors

In recent years, the field of neuroscience has increasingly recognized the importance of studying animal behaviors in naturalistic environments to gain deeper insights into ethologically relevant behavioral processes and neural mechanisms. The common marmoset (Callithrix jacchus), due to its small size, prosocial nature, and genetic proximity to humans, has emerged as a pivotal model toward this effort. However, traditional research methodologies often fail to fully capture the nuances of marmoset social interactions and cooperative behaviors. To address this critical gap, we developed the Marmoset Apparatus for Automated Pulling (MarmoAAP), a novel behavioral apparatus designed for studying cooperative behaviors in common marmosets. MarmoAAP addresses the limitations of traditional behavioral research methods by enabling high-throughput, detailed behavior outputs that can be integrated with video and audio recordings, allowing for more nuanced and comprehensive analyses even in a naturalistic setting. We also highlight the flexibility of MarmoAAP in task parameter manipulation which accommodates a wide range of behaviors and individual animal capabilities. Furthermore, MarmoAAP provides a platform to perform investigations of neural activity underlying naturalistic social behaviors. MarmoAAP is a versatile and robust tool for advancing our understanding of primate behavior and related cognitive processes. This new apparatus bridges the gap between ethologically relevant animal behavior studies and neural investigations, paving the way for future research in cognitive and social neuroscience using marmosets as a model organism.

Development of a Marmoset Apparatus for Automated Pulling to study cooperative behaviors.

In recent years, the field of neuroscience has increasingly recognized the importance of studying animal behaviors in naturalistic environments to gain deeper insights into ethologically relevant behavioral processes and neural mechanisms. The common marmoset (Callithrix jacchus), due to its small size, prosocial nature, and genetic proximity to humans, has emerged as a pivotal model toward this effort. However, traditional research methodologies often fail to fully capture the nuances of marmoset social interactions and cooperative behaviors. To address this critical gap, we developed the Marmoset Apparatus for Automated Pulling (MarmoAAP), a novel behavioral apparatus designed for studying cooperative behaviors in common marmosets. MarmoAAP addresses the limitations of traditional behavioral research methods by enabling high-throughput, detailed behavior outputs that can be integrated with video and audio recordings, allowing for more nuanced and comprehensive analyses even in a naturalistic setting. We also highlight the flexibility of MarmoAAP in task parameter manipulation which accommodates a wide range of behaviors and individual animal capabilities. Furthermore, MarmoAAP provides a platform to perform investigations of neural activity underlying naturalistic social behaviors. MarmoAAP is a versatile and robust tool for advancing our understanding of primate behavior and related cognitive processes. This new apparatus bridges the gap between ethologically relevant animal behavior studies and neural investigations, paving the way for future research in cognitive and social neuroscience using marmosets as a model organism.

Cross-species translational paradigms for assessing positive valence system as defined by the RDoC matrix.

Functions associated with processing reward-related information are fundamental drivers of motivation, learning, and goal-directed behavior. Such functions have been classified as the positive valence system under the Research Domain and Criteria (RDoC) criteria and are negatively impacted across a range of psychiatric disorders and mental illnesses. The positive valence system is composed of three comprehensive categories containing related but dissociable functions that are organized into either Reward Responsiveness, Reward Learning, or Reward Valuation. The presence of overlapping behavioral dysfunction across diagnostic mental disorders is in-part what motivated the RDoC initiative, which emphasized that the study of mental illness focus on investigating relevant behavior and cognitive functions and their underlying mechanisms, rather than separating efforts on diagnostic categories (i.e., transdiagnostic). Moreover, the RDoC approach is well-suited for preclinical neuroscience research, as the rise in genetic toolboxes and associated neurotechnologies enables researchers to probe specific cellular targets with high specificity. Thus, there is an opportunity to dissect whether behaviors and cognitive functions are supported by shared or distinct neural mechanisms. For preclinical research to effectively inform our understandings of human behavior however, the cognitive and behavioral paradigms should have predictive, neurobiological, and pharmacological predictive validity to the human test. Touchscreen-based testing systems provide a further advantage for this endeavor enabling tasks to be presented to animals using the same media and task design as in humans. Here, we outline the primary categories of the positive valence system and review the work that has been done cross-species to investigate the neurobiology and neurochemistry underlying reward-related functioning. Additionally, we provide clinical tasks outlined by RDoC, along with validity and/or need for further validation for analogous rodent paradigms with a focus on implementing the touchscreen-based cognitive testing systems.

The Impact of Sports Participation on College Students' Learning Outcomes: A Mixed Methods Study based on Multiple Campuses

Plato said: In order for humans to have a successful life, God provides two channels-education and sports. We are increasingly seeing that these two channels are complementary and indispensable. Modern neuroscience research shows that sports can have beneficial effects on brain structure and function, epigenetic regulation of brain tissue, cerebral cortex activity patterns and learning-related psychological factors, thereby improving students' cognitive abilities and academic performance. This study aims to explore the multifaceted effects of sports participation on college students' learning outcomes. A mixed research method was used to collect data in three different types of universities, including a questionnaire survey of 500 students and in-depth interviews with 20 students and 10 faculty members. Quantitative analysis showed that moderate sports participation was significantly related to better academic performance, higher mental health and stronger time management skills. However, excessive participation in physical activities may have a negative impact on study time. Qualitative data further revealed how sport participation enhanced students' self-confidence, teamwork and stress management skills. The study also found that the impact of sports participation varies depending on students' personal backgrounds and the characteristics of their universities. Based on the research results, this article puts forward practical suggestions to promote the balanced development of college students, providing a basis for higher education institutions to formulate relevant policies.

An Evidence-Based Comprehensive Review of Laughter Therapy in Depression Management

Abstract: Depression is a widespread mental health challenge, necessitating diverse therapeutic approaches. Emerging research suggests that laughter may offer a valuable adjunctive intervention for individuals grappling with depressive symptoms. This review systematically investigates the multifaceted relationship between laughter and depression, elucidating the underlying mechanisms and potential therapeutic benefits. A comprehensive literature search was conducted across multiple electronic databases, including PubMed, PsycINFO, Scopus, and Google Scholar. Keywords used in the search included “laughter therapy,” “humor,” “depression,” “mental health,” and “psychological well-being.” The search was limited to articles published in English and included both peer-reviewed journal articles and relevant gray literature. Relevant data were extracted from each study, including the study design, sample size, participant characteristics, type of laughter intervention, duration and frequency of the intervention, outcome measures, and key findings. The extracted data were organized into tables to facilitate comparison across studies. By synthesizing findings from clinical studies, neuroscience research, and anecdotal evidence, this review examines the physiological, psychological, and social dimensions of laughter's impact on depression. Special attention is given to neurochemical pathways, stress modulation, cognitive restructuring, and social dynamics. The physiological effects of laughter on depression encompass neurochemical regulation (endorphins, serotonin, dopamine), stress reduction, and immune system modulation. Psychologically, laughter contributes to cognitive reframing, enhanced coping mechanisms, and mood regulation. Socially, it strengthens social bonds, mitigates social isolation, and fosters a positive social environment. In conclusion, this review synthesizes current knowledge on the healing potential of laughter in mitigating depression, providing a holistic understanding of its multifaceted impact. The findings underscore the importance of integrating laughter-based interventions into mental health care practices and highlight avenues for future research and clinical applications in the realm of depression treatment.

A trainee-informed model for undergraduate neuroscience research programs serving marginalized students.

A trainee-informed model for undergraduate neuroscience research programs serving marginalized students.

Study While You Sleep: Using Targeted Memory Reactivation as an Independent Research Project for Undergraduates.

Newly acquired information is stabilized into long-term memory through the process of consolidation. Memories are not static; rather, they are constantly updated via reactivation, and this reactivation occurs preferentially during Slow-Wave Sleep (SWS, also referred to as N3 in humans). Here we present a scalable neuroscience research investigation of memory reactivation using low-cost electroencephalogram (EEG) recording hardware and open-source software, for students and educators across the K-12 and higher education spectrum. The investigation uses a method called targeted memory reactivation (TMR), whereby auditory cues that were previously associated with learning are re-presented during sleep, triggering the recall of stored memories and (through this) strengthening these memories. We demonstrated the efficacy of this technique on seven healthy human subjects (ages 19-35). The subjects learned to play a spatial memory game on an app where they associated pictures (e.g., a clock) with locations on a grid while they listened to picture-appropriate sounds (e.g., "tic-toc"); next, they took a nap while undergoing EEG recordings. During SWS, half of the sounds from the game were replayed by the app, while half were substituted with non-learned sounds. Subjects then played the memory game again after waking. Results showed that spatial recall was improved more for cued than uncued memories, demonstrating the benefits of memory replay during sleep and suggesting that one may intervene in this process to boost recall of specific memories. This research investigation takes advantage of the importance of sleep for memory consolidation and demonstrates improved memory performance by cueing sounds during SWS.

Ultrasound Neuromodulation for Sleep and Neurological Disorder Therapy: A Path to Clinical Translation.

Ultrasound neuromodulation is a promising noninvasive technique capable of penetrating the skull and precisely targeting deep brain regions with millimeter accuracy. Recent studies have demonstrated that transcranial ultrasound stimulation (TUS) of sleep-related brain areas can induce sleep in mice and even trigger a reversible, hibernation-like state without causing damage. Beyond its utility in preclinical models of central nervous system diseases, such as epilepsy, tremors, Alzheimer's disease, and depression, TUS holds significant potential for clinical translation. Given that many neurological disorders, including Alzheimer's and Parkinson's disease, are associated with sleep abnormalities, leveraging clinical TUS applications for these diseases also creates a pathway for translating this technology to sleep modulation in human use. These findings highlight the potential for ultrasound neuromodulation to advance neuroscience research and clinical applications in sleep control.

How Bud Craig's Insights Reshape the Research on Pain and Mind-Body Therapies.

With his elegant studies, Bud Craig determined the structural neural basis for interoception and critically expanded our conceptual understanding of it. Importantly, he placed pain in the framework of interoception and redefined pain as a homeostatic emotion. Craig understood emotions and pain as experiences based on inferential brain processes within the theoretical model of prediction processing. This chapter aims to give a brief overview of relevant research. Mind-body therapies, such as meditation, mindfulness, yoga, Tai Chi, and others, are included as first-line non-pharmacological approaches in clinical guidelines for the management of chronic pain. Craig's groundbreaking work provided the background for our contemporary understanding of mind-body therapies and for the key role that interoceptive processes play in these therapies as they apply to a wide range of clinical conditions, including pain. This chapter reviews the tremendous influence that Craig's work had on the current state of research on mind-body therapies for managing chronic pain and how it led to new directions for cutting-edge clinical and neuroscientific research.

A Wireless Bi-Directional Brain–Computer Interface Supporting Both Bluetooth and Wi-Fi Transmission

Wireless neural signal transmission is essential for both neuroscience research and neural disorder therapies. However, conventional wireless systems are often constrained by low sampling rates, limited channel counts, and their support of only a single transmission mode. Here, we developed a wireless bi-directional brain–computer interface system featuring dual transmission modes. This system supports both low-power Bluetooth transmission and high-sampling-rate Wi-Fi transmission, providing flexibility for various application scenarios. The Bluetooth mode, with a maximum sampling rate of 14.4 kS/s, is well suited for detecting low-frequency signals, as demonstrated by both in vitro recordings of signals from 10 to 50 Hz and in vivo recordings of 16-channel local field potentials in mice. More importantly, the Wi-Fi mode, offering a maximum sampling rate of 56.8 kS/s, is optimized for recording high-frequency signals. This capability was validated through in vitro recordings of signals from 500 to 2000 Hz and in vivo recordings of single-neuron spike firings with amplitudes reaching hundreds of microvolts and high signal-to-noise ratios. Additionally, the system incorporates a wireless stimulation function capable of delivering current pulses up to 2.55 mA, with adjustable pulse width and polarity. Overall, this dual-mode system provides an efficient and flexible solution for both neural recording and stimulation applications.

Diffusion MRI with Machine Learning

Abstract Diffusion-weighted magnetic resonance imaging (dMRI) of the brain offers unique capabilities including noninvasive probing of tissue microstructure and structural connectivity. It is widely used for clinical assessment of disease and injury, and for neuroscience research. Analyzing the dMRI data to extract useful information for medical and scientific purposes can be challenging. The dMRI measurements may suffer from strong noise and artifacts, and may exhibit high inter-session and inter-scanner variability in the data, as well as inter-subject heterogeneity in brain structure. Moreover, the relationship between measurements and the phenomena of interest can be highly complex. Recent years have witnessed increasing use of machine learning methods for dMRI analysis. This manuscript aims to assess these efforts, with a focus on methods that have addressed data preprocessing and harmonization, microstructure mapping, tractography, and white matter tract analysis. We study the main findings, strengths, and weaknesses of the existing methods and suggest topics for future research. We find that machine learning may be exceptionally suited to tackle some of the difficult tasks in dMRI analysis. However, for this to happen, several shortcomings of existing methods and critical unresolved issues need to be addressed. There is a pressing need to improve evaluation practices, to increase the availability of rich training datasets and validation benchmarks, as well as model generalizability, reliability, and explainability concerns.

Analyses of Rodent Grooming and its Behavioral Microstructure in Modern Neurobiological Studies

Grooming is a complex innate animal behavior used as an indicator of the physiological state of rodents under stress. Here, we analyze the impact of various experimental factors, including genetic, pharmacological and physiological, on self-grooming behavior of laboratory mice and rats. Analysis of grooming microstructure assesses not only the amount, but also the frequency, sequence, localization and consistency of this behavior, and can serve as a sensitive marker of changes in the brain, its response to stress, and predisposition to pathological conditions that model human mental illnesses, such as obsessive-compulsive disorder, autism and depression. Studying rodent self-grooming microstructure can provide valuable information about the mechanisms of brain pathogenesis and has multiple important translational implications for neuroscience research.

Extending insights from LeDoux: using movies to study subjective, clinically meaningful experiences in neuroscience.

Neuroscience research with public health relevance to emotional disorders examines brain-behavior relations. Joe LeDoux's legacy advances these efforts in ways that remain truly unique. While recognized for his basic science research, he also inspires applied researchers, guiding an agenda for clinical scientists: understanding the pathophysiology of altered subjective experiences in emotional disorders. For brain imaging, movie-watching approaches help clinicians realize this agenda due to movies' relative strength in evoking rich, meaningful subjective experiences. Here, we describe methodological advances in movie-watching paradigms that might sustain LeDoux's impact by facilitating the discovery of neural mechanisms generating complex emotional responses. Of note, while linking subjective emotion to pathophysiology is a first step, innovations in movie-watching designs, especially involving therapeutic techniques for emotional disorders, can boost clinical application. Leveraging research on pathophysiology to generate novel therapy reflects the clinical legacy sustained through Joe LeDoux's rousing career.

Cannabis and Cannabinoid Signaling: Research Gaps and Opportunities.

Cannabis and its products have been used for centuries for both medicinal and recreational purposes. The recent widespread legalization of cannabis has vastly expanded its use in the United States across all demographics except for adolescents. Meanwhile, decades of research have advanced our knowledge of cannabis pharmacology and particularly of the endocannabinoid system with which the components of cannabis interact. This research has revealed multiple targets and approaches for manipulating the system for therapeutic use and to ameliorate cannabis toxicity or cannabis use disorder. Research has also led to new questions that underscore the potential risks of its widespread use, particularly the enduring consequences of exposure during critical windows of brain development or for consumption of large daily doses of cannabis with high content Δ 9-tetrahydrocannabinol. This article highlights current neuroscience research on cannabis that has shed light on therapeutic opportunities and potential adverse consequences of misuse and points to gaps in knowledge that can guide future research. SIGNIFICANCE STATEMENT: Cannabis use has escalated with its increased availability. Here, the authors highlight the challenges of cannabis research and the gaps in our knowledge of cannabis pharmacology and of the endocannabinoid system that it targets. Future research that addresses these gaps is needed so that the endocannabinoid system can be leveraged for safe and effective use.

T1- and T2-weighted MRI signal and histology findings in suboptimally fixed human brains

Neuroscientific research that requires brain tissue depends on brain banks that provide very small tissue samples fixed by immersion in neutral-buffered formalin (NBF), while anatomy laboratories could provide full brain specimens. However, these brains are generally fixed by perfusion of the full body with solutions other than NBF generally used by brain banks, such as an alcohol-formaldehyde solution (AFS) that is typically used for dissection and teaching. Therefore, fixation quality of these brains needs to be assessed to determine their usefulness in post-mortem investigations through magnetic resonance imaging (MRI) and histology, two common neuroimaging modalities. Here, we report the characteristics of five brains fixed by full body perfusion of an AFS from our Anatomy Laboratory suspected of being poorly fixed, given the altered signal seen on T1w MRI scans in situ. We describe 1- the characteristics of the donors; 2- the fixation procedures applied for each case; 3- the tissue contrast characteristics of the T1w and T2w images; 4- the macroscopic tissue quality after extraction of the brains; 5- the macroscopic arterial characteristics and presence or absence of blood clots; and 6- four histological stains of the areas that we suspected were poorly fixed. We conclude that multiple factors can affect the fixation quality of the brain. Nevertheless, cases in which brain fixation is suboptimal, consequently altering the T1w signal, still have T2w of adequate gray-matter to white-matter contrast and may also be used for histology stains with sufficient quality.

Scale matters: Large language models with billions (rather than millions) of parameters better match neural representations of natural language.

Recent research has used large language models (LLMs) to study the neural basis of naturalistic language processing in the human brain. LLMs have rapidly grown in complexity, leading to improved language processing capabilities. However, neuroscience researchers haven't kept up with the quick progress in LLM development. Here, we utilized several families of transformer-based LLMs to investigate the relationship between model size and their ability to capture linguistic information in the human brain. Crucially, a subset of LLMs were trained on a fixed training set, enabling us to dissociate model size from architecture and training set size. We used electrocorticography (ECoG) to measure neural activity in epilepsy patients while they listened to a 30-minute naturalistic audio story. We fit electrode-wise encoding models using contextual embeddings extracted from each hidden layer of the LLMs to predict word-level neural signals. In line with prior work, we found that larger LLMs better capture the structure of natural language and better predict neural activity. We also found a log-linear relationship where the encoding performance peaks in relatively earlier layers as model size increases. We also observed variations in the best-performing layer across different brain regions, corresponding to an organized language processing hierarchy.

Zebrafish as a Model for Multiple Sclerosis.

Background: Zebrafish have become a key model organism in neuroscience research because of their unique advantages. Their genetic, anatomical, and physiological similarities to humans, coupled with their rapid development and transparent embryos, make them an excellent tool for investigating various aspects of neurobiology. They have specifically emerged as a valuable and versatile model organism in biomedical research, including the study of neurological disorders such as multiple sclerosis. Multiple sclerosis is a chronic autoimmune disease known to cause damage to the myelin sheath that protects the nerves in the brain and spinal cord. Objective: This review emphasizes the importance of continued research in both in vitro and in vivo models to advance our understanding of MS and develop effective treatments, ultimately improving the quality of life for those affected by this debilitating disease. Conclusions: Recent studies show the significance of zebrafish as a model organism for investigating demyelination and remyelination processes, providing new insights into MS pathology and potential therapies.

Violations of Musical Expectations and Emotion

This study investigates the possibility of a relationship between types of violations of musical expectations and perceived emotions. A natural consequence of listening to music is the development of musical expectations, or rhythmic, harmonic, and structural anticipations of what the listener expects to hear. Existing research in psychology and neuroscience demonstrates that violation of these musical expectations has significant physiological and emotional effects on the listener. Through a survey format, participants were asked to evaluate their experience listening to twelve excerpts by providing written responses and completing two rating scales. This allowed for a qualitative and quantitative evaluation of emotion in contrast to physiological measures used in other studies. Nonparametric tests showed statistically significant differences between ranked mean ratings according to type of violation. Thus, this study provides evidence supporting the existence of a relationship between types of violations of musical expectation and perceived emotions in listeners. Further research is suggested for clarification of this relationship and its possible applications in musical compositions.

The alterations of repetitive transcranial magnetic stimulation on the energy landscape of resting-state networks differ across the human cortex.

Repetitive transcranial magnetic stimulation (rTMS) is a promising intervention tool for the noninvasive modulation of brain activity and behavior in neuroscience research and clinical settings. However, the resting-state dynamic evolution of large-scale functional brain networks following rTMS has rarely been investigated. Here, using resting-state fMRI images collected from 23 healthy individuals before (baseline) and after 1 Hz rTMS of the left frontal (FRO) and occipital (OCC) lobes, we examined the different effects of rTMS on brain dynamics across the human cortex. By fitting a pairwise maximum entropy model (pMEM), we constructed an energy landscape for the baseline and poststimulus conditions by fitting a pMEM. We defined dominant brain states (local minima) in the energy landscape with synergistic activation and deactivation patterns of large-scale functional networks. We calculated state dynamics including appearance probability, transitions and duration. The results showed that 1 Hz rTMS induced increased and decreased state probability, transitions and duration when delivered to the FRO and OCC targets, respectively. Most importantly, the shortest path and minimum cost between dominant brain states were altered after stimulation. The absolute sum of the costs from the source states to the destinations was lower after OCC stimulation than after FRO stimulation. In conclusion, our study characterized the dynamic trajectory of state transitions in the energy landscape and suggested that local rTMS can induce significant dynamic perturbation involving stimulated and distant functional networks, which aligns with the modern view of the dynamic and complex brain. Our results suggest low-dimensional mapping of rTMS-induced brain adaption, which will contribute to a broader and more effective application of rTMS in clinical settings.