Frontiers in Behavioral Neuroscience最新文献

Objective: Severe traumatic brain injury (sTBI) causes permanent disability in adults worldwide. While enriched environments (EE) have been shown to improve recovery in the early post-TBI period, their efficacy during the chronic phase of sTBI remains unclear. This study evaluated neurological function recovery in mice with chronic sTBI housed in either traditional EE or supportive EE.

Methods: Adult male C57BL mice were subjected to sTBI by controlled cortical impact and maintained in standard environments (SE) for 7 months. sTBI mice were then randomized into SE (TBI-SE), traditional EE (TBI-EE-1), or supportive EE (TBI-EE-2, co-housed with sham mice). Sham controls were housed in SE (Sham-SE) or supportive EE (Sham-EE-2). EE consisted of a large stainless-steel cage with toys replaced three times weekly. Mice remained in these conditions for 10 weeks, and neurobehavioral testing was performed beginning in week 6.

Results: In the RotaRod test, TBI-SE mice displayed persistent motor coordination and learning deficits, whereas TBI-EE-2 mice showed robust motor coordination recovery and improved motor learning. Of all TBI mice, only the TBI-EE-2 mice demonstrated improved motor learning. In the Morris water maze test, both TBI-EE-1 and TBI-EE-2 groups showed enhanced spatial learning and memory compared with TBI-SE. Y-maze testing revealed impaired short-term memory in TBI-EE-1 mice but significant improvement in TBI-EE-2 mice. Anxiety-like behavior, assessed by open field and light-dark box tests, was reduced only in the TBI-EE-2 mice.

Conclusion: Supportive EE more effectively reduced anxiety and improved motor and cognitive function in chronic sTBI compared with conventional EE. These findings highlight the potential value of incorporating social integration with healthy individuals into rehabilitation programs to optimize recovery in chronic severe TBI.

Objective: Gliomas, the most aggressive type of brain tumor, are infamous for their low survival rates. Tumor grading and isocitrate dehydrogenase (IDH) status are key prognostic biomarkers for gliomas. However, obtaining these markers typically requires invasive methods such as biopsy. As an effective, noninvasive alternative, multimodal MRI can reveal tumor spatial information and the microenvironment. Low-grade and IDH-mutant gliomas often exhibit T2-FLAIR mismatch signals. Medical image foundational models can explore complex representations in medical images, and fine-tuning them may further enhance glioma diagnosis.

Methods: We propose a multi-task network, MTSAM, for simultaneous glioma IDH genotyping and grading. MTSAM first uses dilated convolutions to simulate large-field convolutions and then reviews the T2 and FLAIR images. Then, we employ convolutions to perform a detailed exploration of the T2 and FLAIR images, and we subtract the weighted T2 and FLAIR images to obtain T2-FLAIR mismatch features. T2-FLAIR mismatch features are concatenated with multimodal MRIs and input into the customized SAM-Med3D. The customized SAM-Med3D is fine-tuned by leveraging complementary information across multi-view modalities, including MRIs, handcrafted radiomics (HCR), and clinical features. Then it extracts deep features for accurate IDH genotyping and grading.

Results: MTSAM achieves AUCs of 92.38 and 94.31% for glioma IDH typing and grading on the UCSF-PDGM dataset, respectively, and AUCs of 91.56 and 93.37% on the BraTS2020 dataset, outperforming other methods. Additionally, we use Grad-CAM to visualize the attention maps of MTSAM, demonstrating its potential for non-invasive glioma diagnosis.

Conclusion: The proposed method demonstrates that we can effectively fuse multi-view, non-invasive information and fully explore the knowledge learned by medical image foundational models from large-scale medical datasets to facilitate glioma diagnosis, thereby advancing glioma research.

Introduction: Flow is characterized by complete immersion and optimal engagement in a task, striking a balance between challenge and skill. Recent neuroimaging studies suggest that flow involves dynamic interactions among large-scale brain networks, particularly the default mode network (DMN) and the executive control network (ECN). This review aims to synthesize current findings on how flow-related DMN-ECN connectivity supports creativity and emotional regulation (ER).

Methodology: Following PRISMA guidelines, we searched PubMed, PsycINFO, and Google Scholar for peer-reviewed neuroimaging studies that experimentally induced or measured flow states. Inclusion criteria encompassed task-based and resting-state fMRI, PET, or EEG designs focusing on DMN, ECN, or related networks (e.g., salience, reward), and studies explicitly reporting on creativity or ER outcomes. We extracted data on sample characteristics, flow induction methods, neuroimaging modalities, and main findings regarding DMN/ECN activation and connectivity. Risk of bias was assessed in the domains of selection, performance, detection, attrition, and reporting.

Results: Nine studies met the inclusion criteria. Across diverse tasks-ranging from video games to jazz improvisation-flow was consistently associated with (1) down-regulation of core DMN regions (e.g., medial prefrontal cortex, posterior cingulate cortex) linked to diminished self-referential thought, (2) increased activity in lateral prefrontal and parietal areas underpinning attentional control, and (3) functional connectivity between networks often considered anti-correlated (e.g., DMN and ECN). This integrated network state appears to facilitate simultaneous idea generation (DMN) and goal-directed processing (ECN), supporting creativity. Additionally, reduced amygdala activity and insula-reward network coupling during flow suggest potential benefits for emotional regulation, allowing high focus and low anxiety.

Conclusion: Flow emerges as a unique neurocognitive phenomenon marked by selective DMN suppression and enhanced ECN engagement. Such network reconfiguration fosters creativity through DMN-ECN synergy while providing emotional stability via reduced self-monitoring and negative affect. Although these findings are promising, further research should employ larger, more diverse samples, incorporate causal and longitudinal designs, and explicitly measure ER outcomes. Elucidating the neurochemical underpinnings of flow (e.g., dopamine release) and individual differences in "flow-proneness" remains an important future direction.

Machine learning is revolutionizing behavioral neuroscience by enabling the study of animal behavior with greater ecological validity while maintaining experimental rigor. Traditional manual observation methods in ethology are constrained by subjectivity, costs, and low throughput, whereas modern machine learning algorithms now provide quantitative tools to investigate natural behavior with unprecedented precision. This mini review surveys recent advances in machine learning for behavioral neuroscience, focusing on markerless pose estimation and unsupervised behavioral clustering, and discusses their roles along the typical research pipeline, from tracking and detection to classification and integration of behavioral and neural data. Open-source platforms using deep learning-based image processing have turned video cameras into high-resolution measurement devices, while unsupervised methods extend inference across large-scale behavioral recordings. In laboratory settings, machine learning enables fine-scale analysis of animal kinematics and their relationship to neural activity, while in field studies it enhances longitudinal data collection through drone and satellite imaging. These approaches expand ethological research by quantifying movement, segmenting behavior into meaningful units, detecting transient events often missed by human observers, and bridging behavior with brain activity via joint latent spaces and closed-loop paradigms. Although challenges remain in handling high-dimensional datasets, machine learning offers powerful opportunities for more comprehensive neuroscientific insights. By bridging the controlled precision of the laboratory with the complexity of real-world environments, these methods advance our understanding of animal behavior and its neural underpinnings, providing experimentalists with practical tools to design, implement, and interpret more naturalistic studies in the field of ethological neuroscience.

Background: Effective feedback in the cognitive domain is essential for surgical education but often limited by resource constraints and traditional assessment formats. Artificial Intelligence (AI) has emerged as a catalyst for innovation, enabling automated feedback, real-time cognitive diagnostics, and scalable item generation, thereby transforming how future surgeons learn and are assessed.

Methods: An item bank of 150 multiple-choice questions was developed using AI-assisted item generation and difficulty estimation. A formative Computerized Adaptive Testing (CAT), balanced across three cognitive domains (memory, analysis, and decision) and surgical topics, was delivered via QuizOne^® 3-5 days before the summative Progress Test. A total of 147 students participated, of whom 116 completed the formative CAT. Performance correlations, group comparisons, analysis of covariance (ANCOVA), and regression analyses were conducted.

Results: Students who voluntarily completed CAT showed higher Progress Test scores, though causality cannot be established due to self-selection bias (p = 0.021), with the effect persisting after adjusting for prior academic performance (ANCOVA p = 0.041). Memory skills were the strongest predictors of summative outcomes (R ² = 0.180, β = 0.425), followed by analysis (R ² = 0.080, β = 0.283); decision was not significant (R ² = 0.029, β = 0.170).

Conclusion: AI-enhanced CAT-Cognitive Diagnostic Modeling (CDM) represents a promising formative approach in undergraduate surgical education, being associated with higher summative performance and providing individualized diagnostic feedback. Refining feedback presentation and enhancing decision-making assessment could further optimize its educational impact.

Introduction: Social isolation, reduced social interaction, and social anhedonia are associated with a range of neuropsychiatric conditions. While the search for novel pharmacological agents to treat social symptoms persists, more precise social behavior measures in pre-clinical animal models are needed to make the most accurate predictions of therapeutic outcomes.

Methods: In the current study, we propose two novel behavioral tasks to measure social motivation in mouse models. We define social motivation as the willingness to exert effort to access a social partner. The first social motivation test, the weighted door task, requires a mouse to push open a one-way, weighted door that increases in weight across successive trials to access a social partner behind the door. The second social motivation test, the ladder task, requires a mouse to climb a ladder that increases in steepness across trials to access a social partner on a platform at the top of the ladder. To validate these tasks, we compared behavioral outcomes across three common inbred strains, C57BL/6J, DBA/2J, and BTBR T + Itpr3 tf /J. Social motivation outcomes were then compared to outcomes in two standard social behavior tests: the three-chamber task and the free dyadic social interaction task.

Results: Following behavioral testing, we found that each strain displayed distinct behavioral responses in social motivation tasks with BTBR mice demonstrating low social motivation, DBA mice demonstrating high social motivation, and C57 mice demonstrating conditionally high social motivation during low effort trials.

Discussion: When combined with standard social behavior testing, our measures provide more detailed social behavior phenotypes unique to each strain. In addition to allowing the creation of more complete social behavior ethograms, these tasks offer advantages as compared to existing conditioning-based behavior tasks measuring social motivation and reward such as the social conditioned place preference task and operant conditioning for social reward. The weighted door and ladder tasks leverage innate exploration behaviors that do not require prior learning which allows for more models, including those with memory, attention, and learning deficits, to be used. These pre-clinical measures of social motivation may prove useful in improving predictions of social behavior outcomes of proposed pharmacological interventions for clinical populations.

Background: Brain dysfunction is a common post-chemotherapy sequela in acute lymphoblastic leukemia (ALL) survivors and is associated with poor academic performance and reduced work ability. The prevention of brain dysfunction in ALL survivors remains a clinical challenge. In this study, we evaluated the preventive effects of probiotics on chemotherapy-induced brain development damage in a preclinical setting.

Methods: The clinical ALL chemotherapy setting was mimicked by intraperitoneally injecting doxorubicin into 4-week-old mice once every 3 days for 2 weeks. Probiotics were administered in the drinking water from the beginning of chemotherapy until adulthood. Behaviors at adulthood were assessed using open field, elevated plus maze, novel object recognition, and Barnes maze tests. Fecal microbiota composition was analyzed using 16S ribosomal RNA (rRNA) gene sequence. Hippocampal neurogenesis was assessed using EdU staining and DCX immunostaining. Synaptic protein expressions were detected using Western blotting.

Results: Early-life chemotherapy induced cognitive dysfunction in adulthood, as demonstrated by impairments in the novel object recognition and Barnes maze tests, but it did not significantly alter anxiety-like behavior in the elevated plus maze. Early-life chemotherapy also induced fecal microbiota dysbiosis both at the end of chemotherapy and in adulthood. Probiotic supplementation alleviated early-life chemotherapy-induced cognitive dysfunction and fecal microbiota dysbiosis in adulthood. In addition, probiotic supplementation also alleviated early-life chemotherapy-induced hippocampal neurogenesis impairments and synaptic protein loss.

Conclusion: Probiotic supplementation can improve early-life chemotherapy-induced brain development impairments in mice by modulating hippocampal neurogenesis.

Introduction: Neonatal hypoxic-ischemic encephalopathy (HIE) is neurological disease caused by the deprivation of oxygen and blood flow to the brain during the developmentally-critical perinatal period. Therapeutic hypothermia (TH) is the standard of care treatment for HIE, though cognitive deficits can persistent throughout life despite treatment. The nature of these deficits, and the impacts of TH and sex are not well understood, and this presents a key barrier in the development of novel therapeutics.

Methods: The goal of this study was to enhance the characterization and measurement of cognitive outcomes with tasks that measure spontaneous behaviors in a rodent models of HIE. Mild-moderate HIE was induced in term-equivalent rats by Vannucci's method and a subset of rats were treated with TH. Cognitive performance was assessed between 6-12 weeks of age.

Results: Hyperactivity and topographical disorientation were observed in HIE rats. Injured rats also spent less time investigating a novel object, suggesting HIE reduced their ability to encode or recognize a familiar object and switch attention to a new object. In a food protection test, injured rats failed to detect an approaching robber rat and protect food items, an indication of impaired attention and egocentric spatial processing. TH treatment resulted in sex-specific attenuation of deficits in attention, learning and skill acquisition, feeding, and processing self-centered spatial cues.

Discussion: These observations highlight the need for deeper understanding of the enduring social and cognitive consequences of neonatal HIE including cases where therapeutic hypothermia was administered. This can pave the way for the development of tailored interventions that enhance the ability of HIE survivors to navigate the complex social and cognitive landscape of adult life.

Introduction: Transcranial infrared laser stimulation (TILS) is a form of photobiomodulation (PBM) using a wavelength of 1064 nm shown to enhance metabolic and hemodynamic activity in the human prefrontal cortex (PFC). Prior studies have shown that when applied to the PFC in the right hemisphere, TILS improves PFC-based memory and learning and sustains attention and mood in healthy adults. However, the temporal duration of PBM mechanisms following a single administration remains poorly understood in humans. The objective of this study was to evaluate the duration of functional connectivity effects of a single administration of TILS to the right anterior PFC during both resting-state and memory-activated conditions over a 5-day period.

Methods: Hemodynamics-derived functional connectivity of the PFC in 12 healthy adults was measured using a 48-channel functional near-infrared spectroscopy (fNIRS) during 5-min resting-state and 2-back memory task activation phases, collected at six time points over a 5-day span. A sham-controlled, within-subject crossover design was employed: all participants received both sham and active TILS in counterbalanced order, with a 4-week washout period between sessions.

Results: Relative to sham, a single administration of TILS significantly modulated PFC functional connectivity during cognitively demanding memory tasks across the 5-day assessment period. No significant effects were observed during resting-state measurements. No adverse effects were reported.

Discussion: These findings suggest that a single administration of TILS can induce functional neuroplasticity in the PFC that persists for several days. The results advance understanding of PBM mechanisms and may inform future interventions aimed at promoting longer-lasting neurocognitive benefits.

The Drosophila Dif gene uses alternative messenger RNA (mRNA) processing to encode two different nuclear factor kappa Bs (NF-κBs). The DifA isoform is a canonical NF-κB transcription factor that is important for activation of the immune response. Our primary interest is the DifB isoform, which is neuron-specific and expressed in the mushroom bodies and antennal lobes of the adult brain. The DifB protein lacks a nuclear localization signal and does not enter the nucleus. Instead, it localizes to the cell body surrounding the nucleus, to axonal-dendritic projections, and to the synapse. DifB is an unusual member of the NF-κB superfamily, as it acts outside the nucleus to modulate behavior. The DifB isoform has been shown to modulate the sensitivity of the adult to sedation by alcohol. Here, we conducted a survey to determine whether the DifB NF-κB is important for other fly behaviors. We observed that a DifB-specific mutation strongly suppresses male courtship. However, despite the expression of DifB in the mushroom bodies, a DifB null allele does not interfere with learning in a learned-suppression-of-phototaxis assay. Finally, both DifA-specific and DifB-specific mutations caused flies to have a circadian long rhythm phenotype, although the circadian phenotype cannot be scored in male DifB mutants because of a sexually dimorphic locomotor defect.