مقالهها، منابع و پژوهشهای تازه حوزه علوم اعصاب
Visionary philanthropy and governments worked with scientists to develop theoretical and computational neuroscience, through establishing centers with "local critical mass," training "outsiders," and fostering theory-experiment collaborations. This NeuroView traces how those bets shaped the field, helping launch AI and computational psychiatry.
Neuroscientist and neurologist Michael N. Shadlen is a world leader in the neurobiology of decision-making, a field of study he helped establish. His research explores higher brain functions-memory retrieval, reasoning, and multitasking, among others-that he theorizes share underlying mechanisms. His work suggests that a holy grail of neuroscience-the "hard problem" of consciousness, or the mechanism(s) by which physical brain operations are translated into lived experiences-could be resolved. Shadlen's Inaugural Article explains what distinguishes conscious from nonconscious thought.
Constantin von Economo was a brilliant neuroscientist whose 33 years of intense productivity are documented in over 4,200 pages of published works. He was best recognized for his notable research on encephalitis lethargica and the detailed cytoarchitectonic mapping of the human cerebral cortex. However, less widely known is that von Economo was also an aviation enthusiast, a skilled balloon and airplane pilot, who held prominent positions in aviation organizations, actively promoted international aeronautical meetings, and gained distinction as a pilot during World War I. Therefore, we aimed to revisit this remarkable but often overlooked aspect of his biography, emphasizing his love of the aeronautical arts and its impact on his medical career.
Haueis and Colaço avoid referencing "neural activity," instead of speaking "neural activities". This subtlety speaks to a strength of their framework: Their metabolically oriented account helps bypass abstractions and stimulus-response assumptions endemic to traditional neuroscience paradigms. We highlight two advantages of this pivot to "neural activities," and how they pave the way for a unified, metabolically grounded, systems neuroscience.
The present paper reexamines the contribution of Mondino de Luzzi (1275-1326) beyond his well-known association with the reintroduction of human dissection in medieval medicine. Focusing on ventricular theory, it explores how Mondino's teaching brought traditional descriptions of the brain into closer contact with the observation of the human body through public dissection. Although his work remained firmly rooted in Galenic and Avicennian traditions, the association of cerebral ventricles with identifiable bodily structures indirectly rendered established doctrines less purely speculative and more susceptible to anatomical scrutiny and criticism. From the Renaissance onward, this contributed to a broader reevaluation of inherited anatomical and physiological theories.
This brief review summarizes the most recent progress in in vivo voltage imaging in the neurosciences, as an extension to the work presented at the voltage imaging session of the 2025 FENS regional meeting in Oslo. First, we outline the latest advances in genetically encoded voltage indicators. Next, we examine technical innovations that have reshaped imaging platforms and lay the groundwork to investigate neural activity in real time across large fields of view and in deep tissue. Finally, we highlight a selection of compelling applications that have emerged over the past 5 years, illustrating how voltage imaging evolved from a proof of concept to being deployed to answer pending neuroscientific questions.
Traditional teaching materials in Anatomy, like cadavers, prosected specimens, models and illustrations have their respective issues of strengths and weaknesses, especially in dealing with complex three-dimensional spatial relationships. This quasi-experimental study was performed in the department of Anatomy, Bangladesh Medical University, Bangladesh from March 2025 to February 2026 to compared 3D Anatomy software (Complete Anatomy) against selected traditional materials (3D illustrations and 3D plastic models) for teaching Neuroanatomy and Head-Neck Anatomy. In the quasi-experimental study, 60 undergraduates from each of two medical colleges not yet exposed to Neuroanatomy or Head-Neck Anatomy were invited and divided into 'Experimental' and 'Control' groups by selecting alternate students. The 'Experimental group' was taught 10 micro-modules of Neuroanatomy or Head-Neck Anatomy using a 3D Anatomy software. The 'Control group' was taught the same using selected traditional materials- 3D illustrations or 3D plastic models. The experimental group using 3D Anatomy software obtained significantly higher overall score and scores across the 10 micro-modules compared to the group taught using 3D illustrations or 3D plastic models. The experimental group achieved significantly higher median scores (30.00 vs. 24.00, p=0.001) across 10 micro-modules, suggesting interactive 3D Anatomy software is superior for short-term knowledge acquisition in complex regions in Neuroanatomy and Head-Neck Anatomy.
OBJECTIVE: Chronic pain is a major global public health concern. Pain neuroscience education (PNE), a cognitive intervention grounded in the biopsychosocial model, has been increasingly applied to chronic pain management. However, its knowledge structure and research evolution have not been systematically delineated. This bibliometric study aimed to map the research landscape, identify hot topics and emerging trends, and provide evidence for clinical translation and research planning. METHODS: Publications on PNE in chronic pain were retrieved from the Web of Science Core Collection (2015-2026). A total of 409 articles were analyzed using Microsoft Excel, CiteSpace, VOSviewer, Bibliometrix, and SCImago Graphica to examine publication outputs, collaboration networks, keyword co-occurrence, clustering, burst detection, and citation patterns. RESULTS: Annual publications increased rapidly from 2018 to 2024, peaking in 2024. The United States, Spain, and Belgium were the most productive countries, with strong collaboration between North America and Europe, while Asian and low-and middle-income countries remained peripheral. Jo Nijs team was a central research force. Keyword analysis revealed 3 hotspots: predominant focus on chronic musculoskeletal pain; a shift from single PNE to multimodal regimens combining exercise and cognitive behavioral therapy; methodological validation of assessment tools serving as a critical hub linking research branches. Burst analysis indicated a transition from empirical accumulation to evidence synthesis with personalized interventions for older adults and adolescents as future frontiers. CONCLUSION: PNE research is advancing rapidly, shifting from efficacy validation toward implementation science and precision interventions. Current research shows a geographic imbalance; future efforts should enhance cross-regional knowledge translation. This study provides a clear knowledge map for researchers and evidence-based directions for optimizing pain management systems.
Facial expressions are considered a critical feature in affective neuroscience. Consequently, extensive research has focused on how emotional facial expressions are perceived, including investigations into which brain regions are activated during their observation and how the brain processes their social significance. To advance a more comprehensive understanding of emotion, it is essential to examine all three aspects-perception, experience and production-in a balanced manner. From an evolutionary perspective, the production of facial expressions during emotional experiences is particularly significant, as it reflects both adaptive communication and survival functions. Nevertheless, a review of existing databases reveals that research on the production of facial expressions remains scarce compared with studies on perception. This gap may stem from several methodological constraints, including the difficulty of reliably inducing emotional experiences in laboratory settings, the challenge of recording participants' full facial expressions in a magnetic resonance imaging scanner and limitations in current analytical approaches for facial expressions. In this review, we argue for the importance of studying the production of facial expressions and outline potential strategies to address these challenges. This article is part of the theme issue 'Mechanisms, development, phylogeny and functions of emotional expressions'.
As artificial intelligence (AI) elevates the economic and strategic value of data, governments are intensifying efforts to regulate the collection, use and cross-border transfer of personal information. Data are increasingly treated as national assets, subject to legal, economic and geopolitical controls. These shifts are reshaping scientific research, particularly in neuroscience and brain health, where progress depends on access to large, diverse and internationally distributed datasets. In parallel, advances in neuroimaging, neurotechnology and computational modeling are enabling population-scale neuroscience and the generation of AI-ready brain datasets. These developments further increase the strategic importance of neural data, amplifying both their scientific value and their governance complexity. The convergence of these trends exposes a fundamental tension between the need for an open science culture and data sovereignty. Without coordinated responses, these dynamics risk limiting representation, slowing innovation and reinforcing global inequities in brain health research. Here we argue that neuroscience requires an international data governance coordinating body capable of aligning research and regulatory priorities. In addition to outlining the distinct challenges posed by neural data, we propose strategies to support secure, equitable and sustainable global collaboration, as well as practical governance instruments to enable coordinated implementation across jurisdictions.
In recent years, the cognitive neuroscience literature has come under criticism for containing many low-powered studies, limiting the ability to make reliable statistical inferences. Typically, the suggestion for increasing power is to collect more data with neural signals. However, many studies in cognitive neuroscience use parameters estimated from behavioral data in order to make inferences about neural signals (such as fMRI BOLD signal). In this paper, we explore how cognitive neuroscientists can learn more about their neuroimaging signal by collecting data on behavior alone and using alternative estimators designed to leverage this information. We demonstrate through simulation and mathematical derivations that knowing more about the marginal distribution of behavior can improve inferences about the mapping between cognitive processes and neural data. We analyze the magnitude of this benefit, finding that it depends on the desired estimand and several underlying study parameters. While in many cases the absolute gains in precision can be modest, our results demonstrate that, in realistic settings, additional behavioral data can lead to the same improvement in the precision of inferences more cheaply and easily than collecting additional data from subjects in a neuroimaging study. This means that when conducting a neuroimaging study, researchers now have another knob to turn in a design analysis: the number of subjects collected in the scanner and the number of behavioral subjects collected outside the scanner (in the laboratory or online).
This study explores the historical development of neuroanatomical terms that describe coloured brain substances, particularly substantia alba (white matter) and substantia grisea (grey matter), from a terminological perspective. Through a systematic review of major anatomical sources from antiquity to the early modern period, it traces how colour descriptors entered anatomical terminology and gradually came to denote distinct brain structures. While ancient anatomy lacked colour-based distinctions in brain anatomy, Arabic and Salernitan traditions introduced the idea of the brain being white. The earliest known use of the phrase substantia alba appears in a 1502 printed version of a medieval pseudo-Galenic text De anatomia vivorum. Vesalius (1543) was the first to distinguish brain matter by colour, introducing terms corresponding to substantia alba and an early version of substantia grisea. By the late 18th century, multiple colour-based terms had been introduced to reflect distinct brain structures. Despite evolving anatomical knowledge, colour descriptors remained stable linguistic signs, often preceding or outlasting conceptual shifts.
Artificial intelligence (AI) has the potential to transform clinical neurophysiology by enabling the automated analysis of complex physiological signals and large amounts of data. While traditional clinical interpretation relies heavily on expert visual inspection, which is vulnerable to subjectivity and inter-rater variability, AI models excel at identifying patterns in complex time series. This chapter provides an overview of current and emerging clinical applications of AI across various modalities in clinical neurophysiology, including EEG, EMG, NCS, and ultrasound. In EEG, AI demonstrates value in spike and seizure detection, comprehensive interpretation for routine and long-term monitoring, and automated classification in ICU and neonatal settings. In neuromuscular medicine, machine learning and deep learning are used to classify motor unit potentials, recognize specific disease patterns in NCS, and aid in automated segmentation and quantification for nerve and muscle ultrasound. Despite these promising results, multiple barriers must be overcome to reach clinical implementation. Key challenges include data heterogeneity, label noise, limited generalizability, and the lack of explainability in "black-box" deep learning approaches. Furthermore, regulatory and legal challenges, along with ethical concerns like algorithmic bias and clinical accountability, complicate widespread adoption. The use of large international datasets combined with robust validation approaches may enable the development of AI models that reduce diagnostic subjectivity. Ultimately, AI will likely serve as an augmentation and triage tool, allowing clinical neurophysiologists to focus on clinical reasoning while also supporting the training of future residents.
One of the major challenges in neuroscience is understanding how the human brain develops into a highly organized and functionally integrated organ, because many developmental processes cannot be investigated directly in humans and are not fully recapitulated in animal models. Brain organoids derived from human pluripotent stem cells have emerged as powerful three-dimensional (3D) experimental models that recapitulate key features of human neurodevelopment, including regional patterning, cellular diversification, and neural circuit assembly. Recent advances in long-term organoid culture, organoid bioengineering, vascularization, assembloid technology, transplantation, multi-omics, and artificial intelligence have substantially expanded the applications of brain organoids to investigate human neurodevelopment, model neurological disorders, support drug discovery, and advance therapeutic development. Integration of single-cell and spatial multi-omics with computational approaches has enabled robust molecular benchmarking, assessment of developmental fidelity, and evaluation of organoid reproducibility, facilitating direct comparison with primary human fetal brain tissue. However, current organoid systems remain limited owing to incomplete cellular and tissue complexity, inter-organoid variability, limited vascularization, limited functional maturation, and incomplete physiological integration. Continued advances in tissue engineering, computational biology, and standardized differentiation protocols are expected to enhance the biological fidelity and translational utility of brain organoids for basic and translational neuroscience, as well as mechanistic and translational research.
This commentary concerns the distinction between computational modelling and computational metaphysics (i.e., the Computational Theory of Mind) in the context of consciousness studies. I argue that the ability to simulate the dynamics of a phenomenon using computational models does not entail that that phenomenon is literally performing the computations that are prescribed by the model.
This Opinion piece addresses links between functional neurological disorder, hypnosis and suggestion, and their potential modulation by virtual reality (VR) in neuroanatomical and computational terms. The cortical hierarchy provides an anatomical basis for differing neurocognitive and computational theories applied to suggested effects and functional symptoms-hierarchical predictive coding, top-down cortical feedback and signal routing, and attractor dynamics. Each theory views the brain as a graded anatomical hierarchy with bidirectional influences between levels. Each considers that representations privileged by heightened attention (whether by cognitive control or automatic processes) alter the pre-conscious 'editing' of experience to generate suggested effects and functional symptoms. This occurs through an increase in top-down signals relative to bottom-up signals across the cortical hierarchy, resulting in enhanced activation of selected neuronal populations in intermediate levels. This alters the interpretation of bottom-up signals or radically misrepresents the presence or absence of bottom-up signals to higher levels. By contrast, VR influences experience by simulating the bottom-up effects of veridical sensory input to sensory processing streams. Despite the shared framework of the cortical hierarchy, the theories differ in important respects. Implications for future research and combining suggestions and VR to treat functional symptoms are considered. This article is part of the discussion meeting issue 'Digital healthcare for the management of functional neurological disorders'.
BACKGROUND: There is a need for efficient and engaging strategies that will mitigate the effects of aging on cognitive and physical functions while keeping users motivated for long-term adherence. OBJECTIVE: This study protocol is designed to investigate, in older adults, the advantage of integrating cognitive training with aerobic exercise (AE) in fun group sessions to potentiate the effect of training on cognition while improving physical function. The protocol explores the effects of a novel intervention, the Activ4Brain program, on cognition and physical function as well as the underlying neurobiological mechanisms. METHODS: The program consists of group AE classes that include computerized games designed to train cognition during exercise, taking advantage of exercise-induced arousal. Cognitive training task difficulty is adapted throughout the intervention as users improve their performance. Importantly, the setup allows for simultaneous body movements to maintain aerobic activation. This is a 3-arm controlled trial, using a parallel design with a 1:1:1 allocation to an experimental group that is engaged in the Activ4Brain program (24 sessions, twice a week), an active control group that is engaged in AE sessions, and a passive control group. Participants are tested at baseline and after the intervention. The main study outcome is changes in cognition. Additional outcomes include changes in brain and autonomic function, levels of inflammation and neuroprotective markers, cardiovascular and physical functional fitness, and body composition. RESULTS: Data collection started in January 2024 and finished in April 2025. Seventy-three individuals (40 women and 33 men) were enrolled in the study and assigned to the 3 groups. The average age was 66 (SD 6) years. Data analyses are ongoing, with the publication of the results estimated for 2026 and 2027. CONCLUSIONS: This study will produce knowledge important for the development of efficient strategies to fight age-related decline.
In this issue of Neuron, Peng et al.1 show that introductory conversations, with either a human instructor or her AI avatar, align students' brain patterns and improve comprehension of difficult lecture content. The study both answers and raises important questions about AI in education.
Alzheimer's disease (AD) and overlapping pathologies represent a growing worldwide health concern. With the first disease-modifying treatments on the rise, it becomes increasingly important to move research in this area forward. Genetic research is excellent at discovering novel contributors to disease mechanisms, which has been demonstrated by the discovery of over 75 disease loci associated with AD. However, classical large-scale genome-wide association studies (GWAS) use cohorts of individuals that have been assigned a case or a control status based on a clinical diagnosis. For AD, this can result in bias due to the complex nature of the disease profile. More specifically, on the neuropathological level, AD is multifaceted with co-morbid pathological lesions being the norm rather than the exception. Together with the substantial preclinical phase, this can lead to the introduction of type I and type II errors. An alternative to using large-scale clinical cohorts is to shift toward studying individuals where the disease diagnosis has been neuropathologically confirmed, or cohorts where an endophenotype is used which can directly reflect ongoing pathological processes in vivo. Such endophenotypes could entail biofluid or imaging-based biomarkers, but the most undiluted signal is obtained when employing neuropathological data. These data typically represent the presence or absence of a lesion or reflects the semi-quantitative burden of pathological features. Here, we review what this shift toward more detailed phenotypes has already contributed to the field by investigating the genetic background of AD hallmark lesions as well as commonly observed co-pathologies.
The concept of causality helps distinguish neuroscience from psychoanalysis. However, it is the Real and its effects that separate them on a conceptual level. Indeed, when it comes to organic and psychic causality, the two paradigms approach the question of disorder or symptom differently. Psychoanalysis does not readily lend itself to measurable, objectifying scientific methods. It takes into account singular subjectivity within a speaking body subject to lack and desire. Conversely, neuroscience promotes a neurological causality to explain the entirety of psychic life based on neural mechanisms localized in the brain.
Despite their distinct theoretical and methodological frameworks, the two fields - psychoanalysis and cognitive neuroscience - nevertheless converge on the idea that a large part of psychological functioning eludes consciousness. While psychoanalysis conceives of the unconscious as dynamic, conflict-ridden, and meaningful, neuroscience views it as a set of non-conscious neural processes. Parallels are drawn between cognitive psychology, relational neuroscience, and psychoanalysis.
There is currently a trend toward treating many practitioners as specialists and experts who claim a monopoly on managing individuals' well-being and providing them with reassurance. The need for child and adolescent psychiatric care arises from the expression of complaints and distress. Care must go beyond the mere diagnosis to focus on addressing the needs of the individual as a whole. An integrative approach to care must not exclude any clinical approach.
The psychoanalytic unconscious is a concept with multiple meanings. Its first, positivist interpretation opens the door to a psychological debate with the neurosciences on the nature of the psyche, provided that the differences in methods and languages are respected. The second, hermeneutic interpretation views the unconscious as meaning to be interpreted or a narrative to be coconstructed. The third, which is emphasized here, offers a concrete definition of the unconscious within and through the pragmatics of psychoanalytic communication, in the here and now of the encounter. It is from this perspective that psychoanalysis's contribution to psychiatry seems most relevant today - as a tool for training in encounter and active listening within the realm of intersubjectivity, which lies at the heart of all clinical practice.
Rapid advances in neuroscience underscore the need to prepare students for a highly competitive academic and research environment. Graduates in science and biomedical disciplines require not only a solid theoretical foundation but also practical knowledge of neuroscientific techniques, analytical methods, and effective scientific communication in order to remain competitive for postgraduate opportunities and active research roles. To address this need, it is essential to enrich undergraduate neuroscience education by incorporating hands-on practical and research experiences into the curriculum. Such experiences can deepen students' understanding of theoretical concepts while equipping them with the practical skills and analytical perspectives necessary to generate and interpret new knowledge. Here, we report three specifically designed short-term research projects implemented as practical components of a third-year undergraduate neuroscience course. These projects cover cognitive-behavioral studies, neuroimaging, neuroanatomy, and anxiety disorders and their effects on cognition and are supervised by established researchers. They are aligned with the theoretical components of the course and run across the 12-wk semester. Within these projects, students review background literature, collect data, perform analyses, and present findings to address defined scientific questions. The projects also include laboratory visits and demonstrations of advanced techniques, such as immunohistochemistry, behavioral testing in rodents, and noninvasive neuroimaging. Assessments are integrated into these activities to evaluate students' knowledge and competence in conducting, documenting, and presenting neuroscience research. Overall, these practical components not only provide valuable insights into neuroscientific methods but also reinforce students' understanding of the fundamental principles of neuroscience.NEW & NOTEWORTHY Rapid advances in neuroscience underscore the need to prepare students for a highly competitive academic and research environment. We report specifically designed short-term research projects implemented as practical components of a third-year undergraduate course. Within these projects, students review background literature, collect data, perform analyses, and present findings to address defined scientific questions. These practical components not only provide valuable insights into neuroscientific methods but also reinforce students' understanding of the fundamental principles of neuroscience.
While projects in philosophy of science often focus on similar sorts of topics, there are often massive differences in how philosophers approach them. One approach that has enjoyed significant success-and that is modeled in the work of Wimsatt and others-involves taking a conceptual engineering perspective in analyzing these topics. In this paper, we outline main features of this conceptual engineering approach and use it to advance three emerging claims regarding causal explanation in biology and neuroscience. We suggest that causal explanation in these domains is non-reductive in contrast to always requiring (or improving with) lower-level details, that it is guided by precise explanatory targets in contrast to complete or multidimensional explanatory targets, and that it is pluralist in involving importantly distinct types of causal systems.
Mitochondria integrate metabolic, signalling, and quality-control pathways that are critical for neuronal and glial homeostasis. Beyond ATP production, they regulate redox balance, calcium dynamics, proteostasis, innate immune signalling, and the molecular pathways governing cell survival and death. This Closing Editorial synthesizes the main advances reported in this Collection across neurodegeneration, neurodevelopmental vulnerability, inherited mitochondrial disorders, neurotrauma, drug-induced neurotoxicity, and neuroimmune regulation. Collectively, these studies establish mitochondrial dysfunction as a heterogeneous and context-dependent process rather than a uniform or secondary consequence of neurological disease. Mitochondrial alterations are dynamically regulated across cell types, subcellular compartments, and disease stages, and are tightly coupled to inter-organelle communication and cellular stress-response pathways. The contributions highlight convergent mechanisms linking astrocytic mitochondrial DNA damage, dysregulated RNA-binding proteins, altered mitochondria-endoplasmic reticulum contacts, disrupted iron and redox homeostasis, and mitochondrial-inflammatory signalling to neuronal vulnerability and impaired circuit integrity. They also identify potential therapeutic targets while defining key unresolved questions, particularly the need to establish mechanistic causality, delineate cell- and compartment-specific mitochondrial responses, and validate findings using clinically relevant models and outcome measures. Overall, this Collection positions mitochondrial biology as a mechanistic framework connecting metabolic dysfunction, cellular stress, neuroinflammation, and neuronal degeneration, and supports its development as a therapeutic target for disease-modifying interventions in neurological disorders.
BACKGROUND: Religious and spiritual practices are among the most ancient and universal human behaviors, yet their neurobiological substrates remain incompletely characterized. Neurotheology-the scientific study of the relationship between spiritual experience and brain function-has produced growing evidence that such practices generate measurable, systematic, and neuroplastic changes in brain structure and function. However, prior reviews have been limited to single practice types, narrow evidence bases, or narrative methods, with none synthesizing the full spectrum of traditions, practices, and neuroimaging modalities in a single review. METHODS: Adhering to the PRISMA 2020 guidelines and registered on the Open Science Framework, Scopus, PubMed/MEDLINE, and ProQuest (23 sub-databases) were searched from inception to June 30, 2026. Eligible studies comprised those using objective neuroimaging or neurophysiological techniques. After multi-stage screening, 105 studies (1998-2026) were synthesized narratively using the synthesis without meta-analysis (SWiM) framework, given substantial heterogeneity. RESULTS: Studies spanned Buddhist, Christian, Islamic, Hindu, Santo Daime, Spiritist, Sant Mat, and mixed traditions, examining meditation, prayer, chanting, recitation, worship, retreat, mystical experience, mediumistic trance, and ritual altered states. Consistent engagement appeared across the prefrontal cortex, anterior cingulate, default mode network (DMN), insula, amygdala, hippocampus, temporoparietal junction, and dopaminergic/serotonergic systems. Practice-specific signatures emerged: meditation (DMN suppression, prefrontal augmentation), prayer (social-cognition networks), chanting/recitation (limbic deactivation, gamma/delta enhancement), and mystical states (most distributed profiles). Long-term practitioners showed structural neuroplasticity, and clinical-population studies linked these circuits to depression, anxiety, and stress. CONCLUSIONS: Religious and spiritual practices produce consistent, practice-specific, and neuroplastic modifications to brain systems governing attention, emotion regulation, self-referential processing, and reward-supporting a plausible mechanistic link between spiritual engagement and mental health, and positioning neurotheology as an empirically grounded dialogue between contemplative tradition and clinical neuroscience.
This article examines contested definitions of happiness, ranging from Freudian notions of unalloyed pleasure to more expansive ideas of satisfaction and contentment. More particularly, it considers how these approaches are interpreted through the specific disciplinary lenses of psychology, neurobiology, and genetics. It shows how, within each, there are disputes and areas of uncertainty, and it delineates the clinical implications of these approaches' largely siloed research agendas. By way of advancing such research agendas, it explores possibilities for how these approaches may, in combination, contribute to raising an individual's "set-point" of happiness, permitting greater life satisfaction notwithstanding trauma and disappointment. In this regard, it examines the psychological and physiological bases of resilience, as well as everyday activities that promote happiness. It highlights recent research demonstrating that happiness increases an individual's health and longevity. Finally, it looks at how psychodynamic psychiatrists can integrate an understanding of happiness into their practices, thereby increasing patients' ability to develop habits that promote happiness.
BACKGROUND: Behavior change remains challenging despite a vast body of evidence linking health behaviors with several health outcomes. Over the past few decades, various health behavioral change theories and techniques have emerged, leading to significant advances in the field. However, although some existing theories provide competent models for structuring approaches, they do not provide a unified neurobiological foundation. OBJECTIVE: To outline the connections between neuroscientific foundations in Part 1 and behavioral change theories in Part 2 and propose an overarching neuroscientific perspective. METHODS: A narrative review of the relevant history and background of the most widely adopted behavior change theories and integrates them into the proposed framework of the Behavior Change Resource Model described in Part 1. RESULTS: A structured overview of selected theories was performed. The main theories and techniques described were Social Cognitive Theory, Self-Determination Theory, Motivational Interviewing, Behavioral Activation, Transtheoretical Model, Cognitive Behavioral Therapy, Mindfulness Meditation, Positive Psychology, and Health and Lifestyle Coaching. Finally, their relation to motivation science and the Behavior Change Resource Model was detailed. CONCLUSION: By bridging the Behavior Change Resource Model (Part 1), and an array of related theories and techniques (Part 2) it was possible to provide a conceptual perspective to further support and propel the scientific understanding of human behavior, especially towards keeping and expanding health through lifespan and across society.
BACKGROUND: Behavioral change remains challenging despite a vast body of evidence linking health behaviors with several health outcomes. Over the past few decades, various health-behavior change theories and techniques have emerged, leading to significant advances in the field. However, although some existing theories provide competent models to structure behavioral-change approaches, they do not provide a unified neurobiological foundation. OBJECTIVE: To outline the connections between neuroscientific foundations and behavioral-change theories and to provide an overarching neuroscientific perspective. METHODS: We conducted a structured narrative review based on data retrieved from major biomedical databases and authoritative neuroscience textbooks to integrate neuroscience data with behavioral-change theories. RESULTS: We describe the neuroscience of behavior from neuroanatomical to neurophysiological mechanisms, emphasizing four brain systems: the hypothalamus, the amygdala, the mesocorticolimbic system, and the prefrontal cortex. Finally, we integrate these mechanisms with a neuroscience-based motivational theory called the Behavior Change Resource Model. CONCLUSION: The present work integrates established neurobiological knowledge and behavioral-change theories, providing a framework to link theory and health-behavior interventions.
BACKGROUND: Innovative modalities have been administered in educating Anatomy to medical undergraduates, specifically Neuroscience because of its clinical significance. For building strong foundation in Anatomy, focus is shifting towards adaptation of digital resources for delivery of content such as three-dimensional (3D) digital resources like 3 D Sectra Visualization Table (SVT). However, lack of dimensional details and relationship of displayed Neuroanatomy images and limited applicability of its digital dissection features necessitate an adjunct teaching strategy to complement the deficiencies in Sectra visualization table. Therefore, to bring about meaningful learning in Neuroanatomy, a model of flipped classroom was designed with existing three-dimensional digital Anatomy resource (3D SVT) and observed the comparison between two approaches on students' academic performance. OBJECTIVES: The study was designed to accomplish the following two objectives: To compare the effect of flipped classroom teaching strategy combined with a 3 D digital Anatomy resource (SVT) and 3D digital Anatomical resource (SVT) alone on students academic performance in Neuroanatomy through pre and post-test scores To assess medical students' perceptions of the flipped classroom model integrated with digital anatomy resources in the context of learning Neuroanatomy. METHODS: A Quasi- experimental study was conducted on two thirty-three medical students. Second year MBBS students were randomly divided into two groups. Group I (Experimental group) was exposed to the flipped classroom with digital anatomical resource while Group II (Control group) was taught through the 3D Sectra session. A pre and the posttest was held before and after each session. A five-point Likert scale questionnaire was administered to evaluate students' perception of the flipped classroom integrated model with Sectra (3 D digital resource). In the present study pre and post test scores of students for two groups were reported, within group comparison was made using Wilcoxon sign rank test and between group comparison was done using Mann Whitney U test. Comparison of test scores was also done with respect to gender. RESULTS: The results of the study revealed that after exposure to flipped classroom with 3D digital resource, a significant increase in the posttest score of interventional Group was observed in comparison to control Group post test score after receiving session with 3D resource alone (p < 0.001). However, with regards to gender, both male and female students give an average similar performance giving no significant difference in their performance. The reliability coefficient for perceptions of experimental group students after exposure to flipped model showed the overall Cronbach's alpha of 0.94. CONCLUSION: The study showed the flipped classroom with 3D digital resource approach significantly improved students' test scores compared to the sessions with 3D resource alone. Moreover, a general positive perception of the new teaching approach was reported by students of flipped classroom.
Neuromarketing and consumer neuroscience aim to enhance self-report and behavioral techniques by assessing neurophysiological and psychophysiological reactions that are frequently challenging to quantify. This study consolidates non-invasive tools frequently employed to examine consumer reactions to marketing stimuli, emphasizing the metrics each method assesses, the marketing inquiries it may reliably address, and the potential dangers of inference involved. We systematically compile evidence pertaining to constructs fundamental to consumer choice, including attention, affective arousal, memory encoding, and valuation, while comparing methodologies such as EEG, fMRI, TMS, Steady State Topography and MEG. The article proposes a method selection matrix that associates common research and applied inquiries (e.g., advertising attention dynamics, packaging assessment, pricing, and value indicators) with suitable measurement strategies, highlighting trade-offs concerning temporal/spatial resolution, ecological validity, cost, and interpretability. Finally, examine methodological challenges and ethical obligations. The scoping review concludes with research gaps where multimodal and more ecologically valid designs are most likely to advance the field.
OBJECTIVE: Chronic non-specific low back pain is a multifactorial condition encompassing both physical and psychosocial components, frequently characterized by maladaptive pain-related cognitions and fear-avoidance behaviours. Pain neuroscience education seeks to reconceptualize these cognitions and mitigate pain-related fear. This study evaluated the additional benefits of integrating pain neuroscience education with Flexi-Bar-based stabilization exercises on pain intensity, functional disability, and geometry of the abdominal and lumbar Multifidus muscles in individuals with chronic non-specific low back pain. METHODS: Forty-eight participants diagnosed with chronic non-specific low back pain were randomly allocated to one of two groups: (1) Pain neuroscience education followed by Flexi-Bar stabilization exercises or (2) Flexi-Bar stabilization exercises alone. Both groups underwent supervised Flexi-Bar stabilization training sessions three times a week for six weeks. The primary outcome was functional disability assessed by the Roland-Morris Questionnaire at baseline, immediately post-intervention, and at the 4-week follow-up. Secondary outcomes included pain intensity, kinesiophobia, pain catastrophizing, and fear-avoidance beliefs, all measured at the same three time points, as well as ultrasound-based geometry of abdominal and lumbar multifidus muscles, which was assessed at baseline and post-intervention in supine, seated, and standing positions. RESULT: Repeated-measures ANOVA revealed significant Time × Group interaction effects, main effects of time, and main effects of Group for both functional disability and pain intensity (p < 0.05). Ultrasound analysis demonstrated significant post-intervention increases in Transverse Abdominis and lumbar Multifidus muscle thickness across all tested positions (p < 0.05), with the pain neuroscience education plus exercise group exhibiting significantly greater increases compared to the exercise-only group. CONCLUSION: The combined PNE plus stabilization exercises yielded superior improvements in pain, disability, and muscle geometry compared with stabilization alone. However, the absence of a PNE-only group precludes isolating the educational component's unique contribution. Iranian Registry of Clinical Trials; prospectively registered (Trial number: IRCT20230505058095N1).
Obstructive sleep apnea (OSA) has a broad and clinically important effect on cognition, most often impairing attention, executive function, memory, processing speed, and visuospatial ability, while language and immediate recall are relatively preserved. A substantial proportion of adults referred to sleep clinics already meet criteria for mild cognitive impairment at initial evaluation, particularly in moderate-to-severe OSA. This cognitive burden reflects multiple interacting mechanisms. Intermittent hypoxia promotes oxidative stress, mitochondrial dysfunction, and hippocampal injury through recurrent ischemia-reperfusion cycles. Sleep fragmentation disrupts slow-wave and REM sleep, impairing memory consolidation and glymphatic clearance. Neuroinflammation, endothelial dysfunction, and structural brain changes, including hippocampal atrophy, white matter hyperintensities, and reduced frontoparietal connectivity, may further compound injury over time. REM-related hypoxemia appears especially important for cerebrovascular injury and memory impairment. Measures such as hypoxic burden and oxygen desaturation indices may better capture brain risk than the apnea-hypopnea index alone. Older age, APOE ε4 genotype, obesity, hypertension, diabetes, depression, and prior cerebrovascular disease increase vulnerability and should guide screening and treatment priorities. Cognitive assessment in OSA should be domain-sensitive rather than based only on a single global cutoff. Effective therapy, especially positive airway pressure with adequate REM-period coverage, can improve alertness and selected cognitive outcomes, although attention may remain impaired despite improved oxygenation. In children, OSA can disrupt memory consolidation and working memory, and adenotonsillectomy often leads to only partial cognitive recovery. Cognition should therefore be considered a primary treatment outcome in both clinical care and future research.
Sleep is now recognized as a vital biological process with roles beyond rest, including neurodevelopment, memory, emotional regulation, metabolism, immune function, and neuroprotection. Advances in neuroscience and technology reveal that sleep is an active, multifaceted process involving multiple brain and body systems. This chapter explores how neural networks, waste clearance, circadian rhythms, immune responses, and cognition interact to influence brain health and disease. We examine sleep's connections to neurodegeneration, mental illness, aging, and cognitive resilience. We also highlight emerging directions, including personalized sleep medicine, digital mapping of sleep networks, AI-based diagnostics, sleep biomarkers, novel therapies, wearable technologies, and circadian interventions. Integrating genetics, computational modelling, and real-time monitoring could transform both basic and clinical sleep science. Ultimately, advancing sleep neuroscience will require a unified approach that links molecular mechanisms to behavior and disease, positioning sleep as a central target for enhancing cognition, preventing brain disorders, supporting mental health, and promoting overall well-being.
INTRODUCTION: Chronic postsurgical pain (CPSP) remains a major clinical challenge following total knee arthroplasty (TKA), with psychological maladaptation and persistent neuromuscular dysfunction considered key contributors to ongoing pain and disability. Pain neuroscience education (PNE) may improve maladaptive pain cognitions, whereas blood flow restriction training (BFRT) can enhance muscle function and induce exercise-related hypoalgesia. Although both interventions have shown potential benefits in chronic pain rehabilitation, no randomized controlled trial has investigated the combined efficacy of these two interventions in patients with CPSP after TKA. This study aims to determine whether combined PNE + BFRT produces greater improvements in pain and function in this population. METHODS AND ANALYSIS: This study is a single-blind, four-arm, parallel-group randomized controlled trial. A total of 148 participants will be randomly assigned (1:1:1:1) to the Control, PNE, BFRT, or combined PNE + BFRT group. PNE will be delivered in two structured sessions. BFRT involves a 12-week supervised low-load resistance training program. The primary outcome is the group-by-time interaction effect on KOOS₄ over time. Secondary outcomes include pain intensity (NRS), global perceived effect, pain distribution, psychological measures (HADS, PCS), physical performance (40-m fast-paced walk test, stair climb test, and 30-s chair stand test), and neuromuscular strength. Assessments will be conducted at baseline, post-intervention (12 weeks), and at 12-week, 24-week, and 36-week follow-ups. Data will be analyzed using linear mixed-effects models under the intention-to-treat principle. ETHICS AND DISSEMINATION: Ethics approval has been obtained from the Ethics Committee of the Chengdu Sport University, with permission number CDSUEC2026- 177. This study has been registered with the Chinese Clinical Trial Registry (ChiCTR2600125544). Written informed consent will be obtained from all participants prior to enrollment. TRIAL REGISTRATION NUMBER: Chinese Clinical Trial Registry ChiCTR2600125544, registered on May 28, 2026.
Physical therapy has undergone substantial evolution in recent decades, extending beyond post-surgical and post-traumatic rehabilitation to encompass prevention, health promotion, differential screening, and the management of complex movement-related conditions [...].
BACKGROUND: Chronic pain affects approximately 20% of the global population. In primary care settings, chronic pain may account for up to 37.5% of weekly consultations. Most chronic pain is non-specific, complicating diagnosis and treatment. Kinesiophobia and movement avoidance may accompany chronic pain, necessitating a biopsychosocial approach to treatment. Pain neuroscience education and corrective exercise have been proposed as treatment strategies. This review aims to critically examine the relationships among kinesiophobia, movement avoidance, and chronic pain; assess the effectiveness of pain neuroscience education; and present a practical framework to guide diagnosis and treatment within integrated primary care. METHODS: Literature searches in PubMed, PsycInfo, CINAHL, and Google Scholar utilized the search terms chronic pain, kinesiophobia, fear of movement, fear of falling, backache, arthritis, neuroscience education, neuroeducation, balance, and proprioception. Inclusion criteria included English language, peer-reviewed literature published over the past 10 years. Exclusion criteria included studies not published in English and gray literature. RESULTS: Both kinesiophobia and movement avoidance were significantly correlated with non-specific chronic pain, particularly among older adults. However, the relationship between kinesiophobia and movement avoidance was not direct. Pain neuroscience education combined with strengthening exercises had a positive impact on chronic pain, movement avoidance, and kinesiophobia. DISCUSSION: Based on their findings, authors collaborated on a treatment strategy for integrated primary care settings, focusing on patient engagement, pain neuroscience education, balance assessment, and corrective exercise. More research is needed to further explain relationships between chronic pain, kinesiophobia, and movement avoidance, and the best strategies for managing these conditions in primary care.
Advances in image registration and machine learning have recently enabled volumetric analysis of postmortem brain tissue from conventional photographs of coronal slabs, which are routinely collected in brain banks and neuropathology laboratories around the world. One caveat of this methodology is the requirement of segmentation of the tissue from the background and out-of-slice tissue in photographs, which currently requires laborious manual intervention. Manual delineation is a bottleneck in this process and poses challenges in scalability, and resources, restricting adoption of these methods. In this article, we present a deep learning model to automate this process. The automatic segmentation tool relies on a U-Net architecture that was trained with a combination of 1,414 manually segmented images of both fixed and fresh tissue, from specimens with varying diagnoses, photographed at two different sites. Automated model predictions on a subset of photographs not seen in training were analyzed to estimate performance compared to manual labels, including both inter- and intra-rater variability. Our model achieved a median Dice score over 0.98, mean surface distance under 0.4 mm, and 95% Hausdorff distance under 1.60 mm, which approaches inter-/intra-rater levels. Our tool is publicly available at surfer.nmr.mgh.harvard.edu/fswiki/PhotoTools and training data is available at https://zenodo.org/records/20647553.
BACKGROUND: Bilingual education provides a natural framework for studying how experience shapes the developing and aging brain. Managing two languages engages neural networks supporting executive function and cognitive control, offering a model of experience-dependent plasticity. METHODS: This narrative review synthesizes developmental, neuroimaging, electrophysiological, and longitudinal studies published primarily between 2010 and 2025, with earlier seminal studies included to provide theoretical context. The review is based on English-language literature identified through major international databases and is not a systematic review. RESULTS: Bilingual experience induces structural and functional changes in frontoparietal and frontostriatal networks, improves white matter integrity, and enhances neural efficiency in cognitive control tasks. ERP and longitudinal studies indicate benefits for attention, working memory, and metalinguistic awareness. In older adults, lifelong bilingualism supports executive function and cognitive resilience, contributing to cognitive reserve. Behavioral effects are inconsistent, but neural adaptations are robust. CONCLUSION: Bilingual education illustrates how socially embedded, cognitively demanding learning shapes brain networks. It provides a valuable model for understanding experience-dependent neuroplasticity across the lifespan, with implications for education and cognitive health in aging.