Frontiers in Integrative Neuroscience

Purely discovery-driven biological research \"...performed without thought of practical ends...\" establishes fundamental conceptual frameworks for technological and medical breakthroughs that often occur many years later. Despite the critical importance of discovery-driven research for scientific progress, there is increasing concern that it is increasingly less favored by funding agencies than research with explicit goals of application and innovation, resulting in a decline in discovery-driven research output. This in turn appears to promote the use of genetically modified organisms (those with advanced molecular toolkits for gene manipulation and visualization) for which genetic models of human disease can be studied at molecular and cellular resolution using state of the art methodology, and to discourage use of other experimental organisms that provide necessary evolutionary context. This field of neuroscience encompasses both applied and discovery-driven research, providing an opportunity to empirically determine whether funding and publication rates for the latter have indeed declined. Additionally, the diversity of experimental organisms traditionally employed in neuroscience research provides a means to quantify changes in use of study organisms that lack genetic tools over time. In particular, the basic research field of neuroethology is characterized by its distinct approach to selection of study organisms based on their adaptive behaviors, evolutionary history, and suitability for answering the question of interest, providing a stronger basis for the assumption that findings reflect fundamental concepts of nervous system function and behavior. A 30-year analysis of National Science Foundation (NSF) funding of neuroethology research finds that the agency has funded progressively fewer researchers with smaller average award amounts, with a decline in awards for research on non-genetically modified organisms. Neuroscience funding by the National Institutes of Health (NIH) shows the same trend but also increasing support for genetically modified organisms. The same pattern is observed in the neuroscience literature but occurs prior to changes in funding, suggesting that the shift to genetically modified organisms was likely initiated by researchers but may potentially have been later reinforced by funding agency and journal publisher preferences.

Cumulative effects of repetitive head impact have been highly associated with short and long term neurological conditions. Despite high rates of head injuries, many people in the U.S. and around the world continue to participate in collision sports. As one approach to address this concern, 2nd Skull has developed supplemental protective headgears including a skull cap, scrum cap and headband that can be utilized in both helmet and non-helmet sports. To test the effectiveness of 2nd Skull products as an adjunctive tool to reduce the severity of head impact, data were extracted from a series of tests completed at four sites under laboratory conditions using linear, projectile and rotational impactor to simulate blows to the head in sports. The majority of test cases showed the same pattern of reduced impact severity with the addition of 2nd Skull padding. It remains to be seen if these laboratory results will translate to the field.

The use of robots to help teachers to engage students in STEM subjects has been increasing in recent years, and much progress has been made in K12 schools to incorporate robots in the pedagogy. Recent studies indicate that robots can play a significant role to engage students in neuroscience subjects, but little is known about teachers perceptions of using robots to teach neuroscience. In this paper, we present a study based on a survey questionnaire conducted with 84 teachers across multiple high schools in the United States to understand their perceptions about the usefulness of using robots to teach neuroscience. To situate teachers with an example of how robots can be used in neuroscience classrooms, we describe an educational tool called the SpikerBot. Our preliminary results indicate that there is an opportunity for neuroscience-oriented robots in secondary education, provided sufficient on-boarding and training videos.

Understanding the skill sets required for career paths is a prerequisite for preparing students for those careers. Neuroscience career paths are rapidly changing as the field expands and increasingly overlaps with computational and data-heavy job sectors. With the steady growth in neuroscience trainees and the diversification of jobs for those trainees, it is important to assess whether or not our training is matching the skill sets required in the workforce. Here, we surveyed hundreds of neuroscience professionals and graduate students to assess their use and valuation of a range of skills, from bench skills to communication and management. We find that professionals with neuroscience degrees can be clustered into three main groups based on their skill sets: academic research, industry research and technical work, and non-research. Further, we find that while graduate students do not use or highly value management and communication skills, almost all neuroscience professionals report strongly needing those skills. Finally, coding and data analysis skills are widely used in academic and industry research and predict higher salaries. Our findings can help trainees assess their own skill sets as well as encourage educational leaders to offer training in management and communication-skills which may help catapult trainees into the next stages of their careers.

Preclinical research in traumatic brain injury (TBI) continues to significantly increase knowledge and yield a large number of peer-reviewed studies, but translation of these results to the clinical setting has been minimal. Rigor and transparency factors such as concealment of group allocation (e.g., "blinding) or ensuring that reagents are identifiable are critical in ensuring that scientific studies are replicable and translatable. Yet, nearly all efforts aimed at measuring these factors have concluded that reporting practices are problematic and incomplete. One way to improve transparency of reporting practices is to require that authors address a set of transparency related items in some way, such as a checklist or a paper section. Recently, Journal of Neurotrauma, a leading publisher of preclinical TBI research, instituted a required rigor-related section, which is explained to authors via a set of transparency, rigor, and reproducibility (TRR) instructions (one example for each manuscript type). These documents include specific transparency sections explaining blinding, power calculations, protocols, code, and data deposition. Experimental Neurology is a journal that is similar in size, impact and topic but the journal does not have explicit instructions to authors about transparency items. The purpose of this study was to assess the degree to which transparency reporting items were included in published manuscripts comparing reporting practices in the Journal of Neurotrauma and Experimental Neurology. We used a commercial software, SciScore, which is an AI tool tuned to detect rigor/transparency sentences in published manuscripts and count the number found (roughly dividing by the number expected) to obtain a score. Overall, SciScore found that in 6 of 8 items that were explicitly asked for, such as power calculations, investigator blinding, inclusion criteria, attrition, and data were significantly greater (more than 10%) compared to Experimental Neurology. However in Journal of Neurotrauma papers with the extra rigor section, 3 of 4 rigor items that were not explicitly asked for in the template rigor documents, such as subject demographics or transparent antibody reporting were not different from Experimental Neurology. One item, reporting of the sex of subjects was significantly better in Experimental Neurology. This shows that the Journal of Neurotrauma required rigor section is effective in improving reporting, but it would be far better if sex as a biological variable and transparent reporting of reagents (items present on major checklists including NIH rigor criteria) would be included.

Infancy is a time of elevated neuroplasticity supporting rapid brain and sensory development. The gut microbiome, also undergoing extensive developmental changes in early life, may influence brain development through metabolism of neuroactive compounds. Here, we leverage longitudinal data from 194 infants across the first 18 months of life to show that microbial genes encoding enzymes that metabolize molecules playing a key role in modulating early neuroplasticity are associated with visual cortical neurodevelopment, measured by the Visual-Evoked Potential (VEP). Neuroactive compounds included neurotransmitters GABA and glutamate, the amino acid tryptophan, and short-chain fatty acids involved in myelination, including acetate and butyrate. Microbial gene sets around 4 months of age were strongly associated with the VEP from around 9 to 14 months of age and showed more associations than concurrently measured gene sets, suggesting microbial metabolism in early life may affect subsequent neural plasticity and development.

We present a deep neural network for data-driven analyses of infant rat behavior in an open field task. The network was applied to study the effect of maternal nicotine exposure prior to conception on offspring motor development. The neural network outperformed human expert designed animal locomotion measures in distinguishing rat pups born to nicotine exposed dams versus control dams. Notably, the network discovered novel movement alterations in posture, movement initiation and a stereotypy in "warm-up" behavior (the initiation of movement along specific dimensions) that were predictive of nicotine exposure. The results suggest that maternal preconception nicotine exposure delays and alters offspring motor development. In summary, we demonstrated that a deep neural network can automatically assess animal behavior with high accuracy, and that it offers a data-driven approach to investigating pharmacological effects on brain development. SignificanceRelating neuronal activity to behavior is crucial to understand brain function. Despite the staggering progress in monitoring brain activity, behavioral analyses still do not differ much from methods developed 30-50 years ago. The reason for that is the difficulty for automated video analyses to detect small differences in complex movements. Here we show that applying deep neuronal networks for automated video analyses can help to solve this problem. More importantly, knowledge extracted from the network allowed to identify subtle changes in multiple behavioral components, which were caused by maternal preconception nicotine exposure in rat pups. Thus, the examples presented here show how neuronal networks can guide the development of more accurate behavioral tests to assess symptoms of neurological disorders.

Early-life stress is known to impair neurodevelopment. Prior work from our group showed that prolonged physical and emotional separation necessitated by the medical needs of preterm infants (born <37 weeks) is associated with lower electroencephalogram (EEG) power in frontal areas, and that trend can be reversed by an intervention that enhances the physical and emotional contact between preterm infant and mother. Here we sought to model the changes in preterm infant frontal EEG power in a rodent model. We examined effects of daily maternal separation (MS) on frontal cortex electrophysiological (electrocorticography [EcoG]) activity in neonatal rats. We also explored the effects of dam-pup behavioral interactions on EcoG activity. From postnatal days (P) 2-10, rat pups were separated daily from their dam and isolated from their littermates for 3 hours. Control rats were normally reared. On P10, pups were implanted with telemetry devices and an electrode placed on the left frontal dura. EcoG activity was recorded during daily sessions over the next four days while pups remained in the home cage, as well as in response to a pup-dam isolation-reunion paradigm at P12. EcoG power was computed in 1 Hz frequency bins between 1-100 Hz. Dam and pup behavioral interactions during recording sessions were coded and synchronized to EcoG data. MS pups showed lower EcoG power during dam-pup interactions. These data parallel human and provide evidence of lower fronto-cortical activity as an early marker of early-life stress and possible mechanism for long-term effects of maternal separation on neurobehavioral development.

A study based on a survey questionnaire was conducted with 55 teachers across multiple high schools in the United States to understand their perceptions about their attitudes and confidence towards using research-based classroom exercises, which models they use to develop such exercises and their availability and preferences for an intensive summer professional development course. Our preliminary results indicate that while teachers are comfortable teaching research-based classroom activities, they are none-the-less very interested in paid professional development courses on teaching research practices to students (79%), more than two-thirds (69%) would be willing to devote at least one hour a week during the school year and three-quarters (75%) would be willing to spend 2-3 hours a week or more during the summer.

Objective: To evaluate long-term neurological, mental, and menstrual health outcomes using a mixed-methods approach among women approximately 2 years after concussion compared with non-head-injured controls. Setting: Participants were recruited from [University X] sites, including the Concussion Clinic, Emergency Departments, Student Health Clinic, and [University X] + Me registry (April 2023 to September 2025). Follow-up occurred October to November 2025. Participants: Eligible participants were assigned female at birth, aged 18 to 45 years, not using hormonal birth control, and, for the concussion group, diagnosed within 7 days of injury. Of 45 concussion patients and 29 controls recruited, 11 concussion patients (mean age 30.4 +/- 8.4 years) and 16 controls (31.3 +/- 7.4 years) completed follow-up. Main Measures: Post-concussion symptoms were assessed using the Rivermead Post-Concussion Symptoms Questionnaire (RPQ), depression using the Patient Health Questionnaire-9 (PHQ-9), and anxiety using the Generalized Anxiety Disorder-7 (GAD-7). Menstrual health was assessed using study-specific measures. Qualitative data captured perceived impacts on daily life, with recurring themes summarized using word clouds. Results: At follow-up, concussion patients reported significantly greater symptom burden (RPQ: 31.6 +/- 13.5 vs 9.4 +/- 9.8; p=0.0002; Hedges g=1.90), depression (PHQ-9: 9.5 +/- 6.5 vs 2.3 +/- 2.2; p=0.0005; g=1.60), and anxiety (GAD-7: 9.8 +/- 6.8 vs 2.8 +/- 3.0; p=0.0057; g=1.42). Qualitative findings highlighted persistent headaches, sleep difficulties, reduced interest, and effects on relationships and daily functioning. Conclusions: This study demonstrates significant long-term differences in symptom burden among women with concussions compared to controls. Findings highlight the importance of understanding real-world impacts to improve long-term care.

Crayfish are well known to many but not often newsworthy, so cases where crayfish are covered in international news provide an example of how science journalism covers a news story about basic research. Headlines have a disproportionately large influence on peoples factual knowledge and perceptions of stories covered in media. I tracked online media coverage of one scientific paper involving marbled crayfish and analyzed the headlines used by the articles. Articles were framed as "news," but almost no headlines contained "new" facts that first appeared in the target scientific paper. The fact that appeared in the most headlines (that marbled crayfish reproduce by cloning) was over a decade old. Headlines misled readers into thinking a "breakthrough" was made by one team, rather than showing incremental advances by many teams of researchers over years.

Yips is an involuntary movement disorder seen in some professional golfers. The diagnostic challenge in yips is to distinguish symptoms of task-specific dystonia from psychological choking. We evaluated 15 professional golfers with mild symptomatic yips via anxiety tests, motion-capture and surface electromyography during a putting task. Movement instabilities were analyzed via temporal statistical methodologies (one-dimensional statistical parametric mapping). In a subset of golfers, we found significant differences in angular velocities of the putter-club rotation and altered synergy neural coefficients during the downswing phase. Our results showed that golfers with mild yips require sensitive motion-capture evaluations wherein movement instabilities become evident. Particularly the downswing is affected, and the ensuing perturbations in phasic muscle activity share dystonic features that are consistently identified as abnormal muscle synergy patterns. Despite a strong subjective feeling of yips that golfers complain of, movement analysis can reliably exclude those with choking from those with task-specific dystonias.

This study is a retrospective chart review of 200 clients who participated in a non-verbal restorative Cognitive Remediation Training (rCRT) program. The program was applied to effect proper neural functional remodeling needed to support resilient, flexible and adaptable behaviors after encountering a mild to medium closed head traumatic brain injury (mTBI). The r CRT training program focused on improving functional performance in executive cognitive control networks as defined by fMRI studies. All rCRT training activities were delivered in a semi-game-like manner, incorporating a Brain Computer Interface (BCI) that provided in-the-moment neural network performance integrity metrics (nPIMs) used to adjust the level of play required to properly engage long-term potentiation (LTP) and long term depreciation (LTD) network learning rules. This study reports on t-test and Reliable Change Index (RCI) changes found within cognitive abilities performance metrics derived from the Woodcock Johnson Cognitive Abilities III Test. We compared pre and post scores from seven cognitive abilities considered dependent on executive cognitive control networks against seven non-executive control abilities. We observed significant improvements (p values 10 to 10-22) with large Cohens d effect sizes (0.78-1.20) across thirteen cognitive ability domains with a medium effect size (.49) on the remaining. The mean percent change for pooled trained domain was double that observed for pooled untrained domain, at 17.2% versus 8.3%, respectively. To further adjust for practice effects, practice effect RCI values were computed and further supported the effectiveness of the rCRT training (RCI-trained 1.4 - 4.8; untrained RCI 0.08-0.75).

In birds, like in mammals, the hippocampus critically mediates spatial navigation through the formation of a spatial map. This study investigates the impact of active exploration of a novel environment on the hippocampus of young domestic chicks, during formation of a new spatial map. Chicks that were free to actively explore the novel environment exhibited a significantly higher neural activation (measured by c-Fos expression), compared to those that passively observed the novel environment from a restricted area. The difference was limited to the anterior and the dorsolateral parts of the intermediate hippocampus. Furthermore, the nucleus taeniae of the amygdala showed a higher c-Fos expression in the active exploration group than the passive observation group. In both brain regions, brain activation correlated with the number of locations that chicks visited during the test. This suggest that the increase of c-Fos expression in the hippocampus is related to increased firing rates of spatially coding neurons. Furthermore, our study indicates a functional linkage of the hippocampus and nucleus taeniae of the amygdala in processing spatial information. Overall, with the present study, we confirm that, in birds like in mammals, exploration of novel environments activates hippocampus, which is likely related to the formation of new spatial representations. Summary statementActive exploration of a novel environment induces stronger activation of hippocampus and taeniae of domestic chicks than pure visual, passive exploration from a restricted area.

Neurodevelopmental disorders like ADHD can affect rhythm perception and production, impacting the performance in attention and sensorimotor tasks. Improving rhythmic abilities through targeted training might compensate for these cognitive functions. We introduce a novel protocol for training rhythmic skills via a tablet-based serious game called Rhythm Workers (RW). This proof-of-concept study tested the feasibility of using RW in children with ADHD. We administered an at-home longitudinal protocol across Canada. A total of 27 children (7-13 years) were randomly assigned to either a finger-tapping rhythmic game (RW) or a control game with comparable auditory-motor demands but without beat-synchronization (active control condition). Participants played the game for 300 minutes over two weeks. We collected data (self-reported and logged onto the device) on game compliance and acceptance. Further, we measured rhythmic abilities using the Battery for the Assessment of Auditory Sensorimotor and Timing Abilities (BAASTA). The current findings show that both games were equally played in duration, rated similarly for overall enjoyment, and relied on similar motor activity (finger taps). The children who played RW showed improved general rhythmic abilities compared to controls; these improvements were also positively related to the playing duration. We also present preliminary evidence that executive functioning improved in those who played RW but not controls. These findings indicate that both games are well-matched. RW demonstrates efficacy in enhancing sensorimotor skills in children with ADHD, potentially benefiting executive functioning. A future RCT with extended training and sample size could further validate these skill transfer effects.

Autism spectrum disorder is a group of developmental disorders whose clinical characteristics include socialization impairment, language disability, and unusual behavior. This review aimed to analyze how the Brazilian community researches autism, seeking answers surrounding its treatment, etiology, and diagnosis. The search for publications was based in Elseviers Scopus Database in June 2019 and was focused on the study of autism in Brazil or with Brazilian data. We categorized publications on diagnosis, treatment, and etiology. The majority of the publications found after inclusion/exclusion criteria sought to validate and adapt pre-existing scales to the Brazilian Portuguese. Instead, the groups performing these studies have had little background in the biochemical, genetic, or environmental aspects of the disease in the country.

As the relevance of neuroscience in education grows, effective methods for teaching this complex subject in high school classrooms remain elusive. Integrating classroom experiments with brain-based robots offers a promising solution. This paper presents a structured curriculum designed around the use of camera-equipped mobile robots which enables students to construct and explore artificial neural networks. Through this hands-on approach, students engage directly with core concepts in neuroscience, learning to model spiking neural networks, decision-making processes in the basal ganglia, and principles of learning and memory. The curriculum not only makes challenging neuroscience concepts accessible and engaging but also demonstrates significant improvements in students understanding and self-efficacy. By detailing the curriculums development, implementation, and educational outcomes, this study outlines a scalable model for incorporating advanced scientific topics into secondary education, paving the way for a deeper student understanding of both theoretical neuroscience and its practical applications.

Interactive neurorobotics is a subfield which characterizes brain responses evoked during interaction with a robot, and their relationship with the behavioral responses. Gathering rich neural and behavioral data from humans or animals responding to agents can act as a scaffold for the design process of future social robots. The goals of this research can be broadly broken down into two categories. The first, seeks to directly study how organisms respond to artificial agents in contrast to biological or inanimate ones. The second, uses the novel affordances of the robotic platforms to investigate complex phenomena, such as responses to multisensory stimuli during minimally structured interactions, that would be difficult to capture with classical experimental setups. Here we argue that to realize the full potential of the approach, both goals must be integrated through methodological design that is informed by a deep understanding of the model system, as well as engineering and analytical considerations. We then propose a general framework for such experiments that emphasizes naturalistic interactions combined with multimodal observations and complementary analysis pipelines that are necessary to render a holistic picture of the data for the purpose of informing robotic design principles. Finally, we demonstrate this approach with an exemplar rat-robot social interaction task which included simultaneous multi-agent tracking and neural recordings.

The canonical framework for testing pain and mechanical sensitivity in rodents is manual delivery of stimuli to the paw. However, this approach is time consuming, produces variability in results, requires significant training, and is ergonomically unfavorable to the experimenter. To circumvent limitations in manual delivery of stimuli, we have created a device called the ARM (Automated Reproducible Mechano-stimulator). Built using a series of linear stages, cameras, and stimulus holders, the ARM is more accurate at hitting the desired target, delivers stimuli faster, and decreases variability in delivery of von Frey hair filaments. We demonstrate that the ARM can be combined with traditional measurements of pain behavior and automated machine-learning based pipelines. Importantly, the ARM enables remote testing of mice with experimenters outside the testing room. Using remote testing, we found that mice habituated more quickly when an experimenter was not present and experimenter presence leads to significant sex-dependent differences in paw withdrawal and pain associated behaviors. Lastly, to demonstrate the utility of the ARM for neural circuit dissection of pain mechanisms, we combined the ARM with cellular-resolved microendoscopy in the amygdala, linking stimulus, behavior, and brain activity of amygdala neurons that encode negative pain states. Taken together, the ARM improves speed, accuracy, and robustness of mechanical pain assays and can be combined with automated pain detection systems and brain recordings to map central control of pain.

High-density electrophysiological recording using Neuropixels probes enables single-unit resolution of human neural activity. However, integrating these systems into clinical environments remains challenging. Reported human recordings have been limited to a few centres in the United States utilising variable regulatory, sterilisation and operative techniques. Here, we present human Neuropixels recordings under a nationally managed ethical and regulatory framework in the United Kingdom. We provide a reproducible roadmap to overcome regulatory and equipment constraints. Guided by the IDEAL Stage 2a (Development) framework, we established a frameless intraoperative workflow utilising manufacturer-sterilised probes and a commercially available, clinical-grade setup for Neuropixels insertion including micromanipulator and endoscope holder. We prospectively evaluated this workflow across six participants (mean age 62.5 years) undergoing elective ventriculoperitoneal shunt surgery. Iterative failure-mitigation cycles successfully resolved key technical barriers, including neuronavigation interference and hardware instability. Assessed across three predefined endpoints (clinical safety, procedural timing, and neural data yield), the workflow achieved zero research-related adverse events and maintained a strict 30-minute procedural extension. Progressive technical refinements increased single-unit yield from 25 units during early development to 146 manually curated units. This approach provides a scalable, clinically integrated workflow to safely perform high-density electrophysiology in routine neurosurgical environments.