Intersection Of Neuroscience Research Articles

The Intersection of Neuroscience and Criminology: Role of Brain Mapping in Addressing Criminal Behavior by Nepal Police

Neuroscience is being integrated into criminal investigations, offering new opportunities for understanding, predicting, and potentially preventing criminal behavior. In Nepal, brain-mapping techniques like P300 wave tests and Brain Electrical Oscillation Signature profiling were used in a murder investigation in 2024. However, ethical concerns include privacy concerns, false positives, and the potential for false positives. Consent regarding neurobiological evidence in criminal cases is crucial, as intrusive procedures may require individuals to be informed. The legal implications of using neurobiological evidence could be severe if it serves to wrongfully accuse or convict an individual. Therefore, the use of neuroscience in criminology must be carefully balanced to ensure ethical considerations. This viewpoint interprets the potential of neuroscience in criminal investigations, addressing ethical, privacy, consent, and legal issues within the Nepal Police and criminal justice system.

Electromagnetic field enhanced flow state: Insights from electrophysiological measures, self-reported experiences, and gameplay

The intersection of neuroscience and technology hinges on the development of wearable devices and electrodes that can augment brain networks to improve cognitive capabilities such as learning and concentration. The capacity to enhance networks associated with these functions above baseline capabilities, holds the potential to benefit numerous individuals. The purpose of this study was to determine if electromagnetic field exposure modeled from physiological data would increase instances of flow in participants playing a computer game. The flow state refers to a subjective state of optimal performance experienced by individuals during a variety of tasks. For this study, participants (n = 39, 18–65 years, nfemale = 20) played the arcade game Snake for two ten-minute periods (each with a ten-minute rest period immediately following). For one of the trials, an electromagnetic field was applied bilaterally to the temporal lobes, with the other serving as the control. Brain activity was measured using quantitative electroencephalography, flow experience was measured using the Flow Short Scale and game play scores were also recorded. Results showed deceased beta 1 (12–16 Hz) activity in the left cuneus [t = 4.650, p < 0.01] and left precuneus [t = 4.603, p < 0.01], left posterior cingulate [t = 4.521, p < 0.05], insula [t = 4.234, p < 0.05], and parahippocampal gyrus [t = 4.113, p < 0.05] for trials when the field was active, compared to controls during rest periods. Results from the Flow Short Scale showed a statistically significant difference in mean “concentration ease” scores across electromagnetic field conditions, irrespective of difficulty [t = 2.131, p < 0.05]. In the EMF exposure trials, there was no discernible experience effect; participants with prior experience in the game Snake did not exhibit significantly better performance compared to those without prior experience. This anticipated effect was observed in control conditions. The comparable performance observed between novices and experienced players in the EMF condition indicate a noteworthy learning curve for novices. In all, these results provide evidence supporting the ability of EMF patterned from amygdaloid firing (6–20 Hz) to elicit neurological correlates of flow in brain regions previously reported in the literature, facilitate concentration, and subtly improve game scores. The possibility for wearable devices to support learning, concentration, and focus are discussed.

Neurogenomics contribution to neurodegenerative Diseases

Introduction: Neurodegenerative diseases are a group of complex disorders that progressively impair the structure and function of the nervous system, resulting in debilitating symptoms and reduced quality of life for affected individuals. Over the past few decades, advances in the field of genomics have revolutionized our understanding of the underlying molecular mechanisms driving these disorders. Neurogenomics, the intersection of neuroscience and genomics, has emerged as a crucial discipline in unraveling the genetic and molecular underpinnings of neurodegenerative diseases. Neurogenomics focuses on deciphering the genetic variations that contribute to the susceptibility and progression of neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis (ALS), and Huntington's disease. Advances in DNA sequencing technologies have enabled researchers to identify specific genetic mutations and variations that are associated with increased disease risk. By studying the genetic mutations involved in neurodegenerative diseases, neurogenomics has provided valuable insights into the underlying disease mechanisms. These insights have led to a deeper understanding of protein aggregation, mitochondrial dysfunction, inflammation, and other cellular processes implicated in disease progression. By harnessing the power of neurogenomics through further studies, researchers and clinicians are moving closer to the goal of effectively preventing, diagnosing, and treating neurodegenerative diseases, thus offering hope to millions of individuals affected by these challenging conditions. Conclusion: Neurogenomics has emerged as a pivotal field in unraveling the complex interplay between genetics and neurobiology in neurodegenerative diseases. By dissecting the genetic architecture, elucidating molecular mechanisms, and paving the way for targeted therapies, neurogenomics offers new avenues for understanding, diagnosing, and ultimately treating these disorders.

Artificial Intelligence’s Novel “Mind-Reading” Capabilities through Neuroscience: A Challenge for Mind-Body Dualism?

This paper explores a philosophical problem at the intersection of neuroscience and artificial intelligence (AI), and the potential impact of these novel AI “mind-reading” technologies on various forms of mind–body dualism, including substance, interaction, property, predicate, and emergent dualisms. It critically examines how AI’s ability to interpret and predict mental states from neural patterns challenges traditional dualistic theories, which have historically posited distinct relationships between the mind and body. The paper analyzes each dualistic theory in the context of AI advancements. Substance and interaction dualisms are scrutinized for their claims of mind–body independence and causal interaction, respectively, in light of AI’s capabilities to correlate mental and physical states. Property dualism’s assertion of unique mental properties emerging from physical processes is tested against AI’s potential to map mental phenomena to brain activity. Predicate dualism’s linguistic and conceptual distinction between mental and physical realms is challenged by AI’s ability to bridge these domains. Similarly, emergent dualism, which views mental states as novel phenomena, confronts the possibility of their reduction to physical brain processes. Despite these challenges, the paper argues for the adaptability of dualistic theories to integrate AI insights, suggesting a re-evaluation rather than a negation of dualism. It highlights the enduring relevance of philosophical inquiry into the nature of consciousness and mind–body relationships in the age of AI, suggesting that such technological advancements invigorate rather than terminate the philosophical debate.

Integrating Modern Neuroscience with Traditional Philosophical Theories

Purpose: The general objective of the study was to examine how changes or advancements in modern neuroscience may impact or influence traditional philosophical theories. Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library. Findings: The findings reveal that there exists a contextual and methodological gap relating to modern neuroscience with traditional philosophical theories. Preliminary empirical review revealed that interdisciplinary collaboration between these fields holds significant potential. Through a comprehensive review of existing literature, it was found that while challenges existed, there were also considerable opportunities for integration. The study emphasized the importance of theoretical integration and methodological innovation in advancing understanding at the intersection of neuroscience and philosophy. Practical implications were highlighted for stakeholders, including researchers, educators, policymakers, and the public, with the conclusion suggesting that embracing interdisciplinary perspectives could lead to deeper insights into the nature of the human mind and its philosophical implications. Unique Contribution to Theory, Practice and Policy: The Dual-Aspect Monism, Embodied Cognition and Enactivism theory may be used to anchor future studies on modern neuroscience with traditional philosophical theories. The study provided recommendations aimed at advancing theory, practice, and policy. Interdisciplinary dialogue and collaboration between neuroscientists and philosophers were fostered to enrich theoretical discussions. Insights from the integration of neuroscience and philosophy were incorporated into educational curricula and training programs, promoting critical thinking skills. Ethical considerations were integrated into neuroscience research through the development of guidelines and regulations. Interdisciplinary research teams were formed to design innovative methodologies, bridging terminological and conceptual differences. Furthermore, international collaboration was encouraged to leverage diverse perspectives and resources. Keywords: Integrating, Modern Neuroscience, Traditional Philosophical Theories, Interdisciplinary, Dialogue, Collaboration, Ethical Considerations, Education, Terminological Differences, International Collaboration, Critical Thinking

The coming decade of digital brain research: A vision for neuroscience at the intersection of technology and computing

Abstract In recent years, brain research has indisputably entered a new epoch, driven by substantial methodological advances and digitally enabled data integration and modelling at multiple scales—from molecules to the whole brain. Major advances are emerging at the intersection of neuroscience with technology and computing. This new science of the brain combines high-quality research, data integration across multiple scales, a new culture of multidisciplinary large-scale collaboration, and translation into applications. As pioneered in Europe’s Human Brain Project (HBP), a systematic approach will be essential for meeting the coming decade’s pressing medical and technological challenges. The aims of this paper are to: develop a concept for the coming decade of digital brain research, discuss this new concept with the research community at large, identify points of convergence, and derive therefrom scientific common goals; provide a scientific framework for the current and future development of EBRAINS, a research infrastructure resulting from the HBP’s work; inform and engage stakeholders, funding organisations and research institutions regarding future digital brain research; identify and address the transformational potential of comprehensive brain models for artificial intelligence, including machine learning and deep learning; outline a collaborative approach that integrates reflection, dialogues, and societal engagement on ethical and societal opportunities and challenges as part of future neuroscience research.

Mini review: Challenges in EEG emotion recognition.

Electroencephalography (EEG) stands as a pioneering tool at the intersection of neuroscience and technology, offering unprecedented insights into human emotions. Through this comprehensive review, we explore the challenges and opportunities associated with EEG-based emotion recognition. While recent literature suggests promising high accuracy rates, these claims necessitate critical scrutiny for their authenticity and applicability. The article highlights the significant challenges in generalizing findings from a multitude of EEG devices and data sources, as well as the difficulties in data collection. Furthermore, the disparity between controlled laboratory settings and genuine emotional experiences presents a paradox within the paradigm of emotion research. We advocate for a balanced approach, emphasizing the importance of critical evaluation, methodological standardization, and acknowledging the dynamism of emotions for a more holistic understanding of the human emotional landscape.

Current Trends in the Development of Neuroscientific Research in Education

Modern neuroscience is making significant progress in the study of brain functions, which can be of great importance for the education. However, there is a gap between current neuroscientific evidence on how the brain learns and its direct application in classrooms. What can neuroscientists, psychologists, and educators do to improve the interaction between neuroscience and education? In this article, we attempt to answer this question by examining the essentials of educational neuroscience as an interdisciplinary field of research at the intersection of neuroscience, pedagogy, and cognitive science, which seeks to translate research on the neural mechanisms of learning into educational practice and understand the impact of education on the learner's brain. In the first part of the article we describe the origins and current progress of neuroscience in education, discuss terminological uncertainty in the Russian scientific literature on the relationship between neuroscience and education, as well as possible and, in our opinion, most promising ways of interaction between psychology, pedagogy and neuroscience. In the second part of the article we analyze the main directions of contemporary research in the field of neuroscience, based on the Scopus database of scientific information.

Advances in neuroproteomics for neurotrauma: unraveling insights for personalized medicine and future prospects

Neuroproteomics, an emerging field at the intersection of neuroscience and proteomics, has garnered significant attention in the context of neurotrauma research. Neuroproteomics involves the quantitative and qualitative analysis of nervous system components, essential for understanding the dynamic events involved in the vast areas of neuroscience, including, but not limited to, neuropsychiatric disorders, neurodegenerative disorders, mental illness, traumatic brain injury, chronic traumatic encephalopathy, and other neurodegenerative diseases. With advancements in mass spectrometry coupled with bioinformatics and systems biology, neuroproteomics has led to the development of innovative techniques such as microproteomics, single-cell proteomics, and imaging mass spectrometry, which have significantly impacted neuronal biomarker research. By analyzing the complex protein interactions and alterations that occur in the injured brain, neuroproteomics provides valuable insights into the pathophysiological mechanisms underlying neurotrauma. This review explores how such insights can be harnessed to advance personalized medicine (PM) approaches, tailoring treatments based on individual patient profiles. Additionally, we highlight the potential future prospects of neuroproteomics, such as identifying novel biomarkers and developing targeted therapies by employing artificial intelligence (AI) and machine learning (ML). By shedding light on neurotrauma’s current state and future directions, this review aims to stimulate further research and collaboration in this promising and transformative field.

Demystifying neurotourism: An interdisciplinary approach and research agenda

The academic discourse surrounding tourism's interdisciplinary approach has long piqued the interest of the scholarly community. More recently, attention has pivoted towards the intersection of neuroscience and neuromarketing within the realm of tourism, giving rise to the concept of “neurotourism”. This emergence requires a comprehensive elucidation of the relevance of neuromarketing and neuroscience to the field of tourism, thereby addressing the imperative to bridge existing knowledge gaps. In light of this, the present paper endeavours to fulfil this objective by synthesizing global research in this domain. The study adopts an interdisciplinary approach, employing a hybrid systematic review methodology that encompasses a literature review encompassing nine key indicators and a bibliometric analysis through co-word analysis of author keywords. In total, our investigation unearthed 45 papers from Scopus, each exploring the application of neuroscience and neuromarketing theories and methods within the context of tourism. Among these, three papers delve into the concept of neurotourism. In this paper, we underscore the deep connection between neuroscience, neuroscientific methodologies, and neuromarketing within the realm of tourism research. The outcomes of this research significantly enhance our comprehension of the current state of neurotourism research, revealing both existing voids and emerging areas of interest. Furthermore, this study introduces a pioneering methodological approach, fusing Scival topic prominence and hybrid systematic review techniques into bibliometric analysis. Ultimately, our findings illuminate a notable research lacuna, presenting a fertile terrain for prospective investigations. Additionally, we deliberate on current trends and propose directions for future research within the neurotourism landscape.

Current status, challenges and future prospects in computational psychiatry: a narrative review.

Computational psychiatry is an area of scientific knowledge which lies at the intersection of neuroscience, psychiatry, and computer science. It employs mathematical models and computational simulations to shed light on the complexities inherent to mental disorders. The aim of this narrative review is to offer insight into the current landscape of computational psychiatry, to discuss its significant challenges, as well as the potential opportunities for the fields growth. The authors have carried out a narrative review of the scientific literature published on the topic of computational psychiatry. The literature search was performed in the PubMed, eLibrary, PsycINFO, and Google Scholar databases. A descriptive analysis was used to summarize the published information on the theoretical and practical aspects of computational psychiatry. The article relates the development of the scientific approach in computational psychiatry since the mid-1980s. The data on the practical application of computational psychiatry in modeling psychiatric disorders and explaining the mechanisms of how psychopathological symptomatology develops (in schizophrenia, attention-deficit/hyperactivity disorder, autism spectrum disorder, anxiety disorders, obsessive-compulsive disorder, substance use disorders) are summarized. Challenges, limitations, and the prospects of computational psychiatry are discussed. The capacity of current computational technologies in psychiatry has reached a stage where its integration into psychiatric practice is not just feasible but urgently needed. The hurdles that now need to be addressed are no longer rooted in technological advancement, but in ethics, education, and understanding.

From Brain Models to Robotic Embodied Cognition: How Does Biological Plausibility Inform Neuromorphic Systems?

We examine the challenging "marriage" between computational efficiency and biological plausibility-A crucial node in the domain of spiking neural networks at the intersection of neuroscience, artificial intelligence, and robotics. Through a transdisciplinary review, we retrace the historical and most recent constraining influences that these parallel fields have exerted on descriptive analysis of the brain, construction of predictive brain models, and ultimately, the embodiment of neural networks in an enacted robotic agent. We study models of Spiking Neural Networks (SNN) as the central means enabling autonomous and intelligent behaviors in biological systems. We then provide a critical comparison of the available hardware and software to emulate SNNs for investigating biological entities and their application on artificial systems. Neuromorphics is identified as a promising tool to embody SNNs in real physical systems and different neuromorphic chips are compared. The concepts required for describing SNNs are dissected and contextualized in the new no man's land between cognitive neuroscience and artificial intelligence. Although there are recent reviews on the application of neuromorphic computing in various modules of the guidance, navigation, and control of robotic systems, the focus of this paper is more on closing the cognition loop in SNN-embodied robotics. We argue that biologically viable spiking neuronal models used for electroencephalogram signals are excellent candidates for furthering our knowledge of the explainability of SNNs. We complete our survey by reviewing different robotic modules that can benefit from neuromorphic hardware, e.g., perception (with a focus on vision), localization, and cognition. We conclude that the tradeoff between symbolic computational power and biological plausibility of hardware can be best addressed by neuromorphics, whose presence in neurorobotics provides an accountable empirical testbench for investigating synthetic and natural embodied cognition. We argue this is where both theoretical and empirical future work should converge in multidisciplinary efforts involving neuroscience, artificial intelligence, and robotics.

Identifying customer preferences through the eye-tracking in travel websites focusing on neuromarketing

ABSTRACT The psychology of people and behavior associated with decision-making can be analyzed by examining their visual attention to products based on the introduction of neuromarketing at the intersection of neuroscience and marketing. This study aims to identify factors affecting consumers’ decision-making on travel products by investigating their preferences and areas of interest via online vacation booking sites. In this experimental study, eye-tracking was measured on 30 male participants in the age of forties, and data on their gazes in response to stimuli were extracted and compared with their choices in the questionnaire survey. The study addresses the following research question: “On what areas of customer preference can visual attention be deemed an influence?” Whether changes to the visual information about spatial products influence product preferences and decision-making was investigated. As a result of analyzing the region of interest in the eye-tracking according to the order of space preference, the preference rate for image 3 (M = 782.65) containing the outdoor space was the highest, followed by furniture and web information. Regarding the initial concentration, among the flow of time, the fastest concentration started at stimuli 2 (4.21s), but the time when concentration increased was at stimuli 3 (16.28s). Visual perception data were analyzed as a verification process for determining the time difference in the concentration of gaze movements according to personal preference. The correlation between the questionnaire survey, reflecting consumers’ conscious preferences, and the data of gaze movements, showing unconscious decision-making, was analyzed.

On Demon Time

Click to increase image sizeClick to decrease image size Additional informationNotes on contributorsPhilip ButlerPhilip Butler is an Assistant Professor of Theology and Posthuman Artificial Intelligence Systems at Iliff School of Theology. He is also the founder of the Seekr Project, a distinctly Black conversational artificial intelligence with mental health capacities. His work primarily focuses on the intersection of neuroscience, technology, spirituality, and race. He is the author of Black Transhuman Liberation Theology: Spirituality and Technology (Bloomsbury, 2019) and most recently the editor of Critical Black Futures: Speculative Theories and Explorations (Palgrave Macmillan, 2021).

Modeling Driver’s Visual Fixation Behavior Using White-Box Representations

Driving is a highly dynamic task requiring extensive and fast processing of visuospatial information in brief time intervals, while experienced drivers can efficiently perform this task. Therefore, investigating the human-like visual fixation behavior shows much potential in developing the advanced driving assistance systems and efficient autonomous vehicles. Literature shows that driver’s visual fixation behavior is guided by a combination of top-down and bottom-up mechanisms. Currently, existing excellent computational frameworks rely heavily on the deep neural network’s strong feature extraction ability, which is inherently task-unaware. These black-box models are limited in strengthening the guidance of task-aware top-down factors in governing the fixation behavior. Furthermore, using the black-box model to fit the training data directly decreases its interpretability. In this paper, we encourage to adopt the white-box method. By researching the findings in the intersection of neuroscience and psychology, we propose to identify two white-box representations for driving separately: the information selection representation including salience, effort, expectancy, and value, and the driving task-aware representation highlighting sub-task and speed. We present a novel computational framework to incorporate all the above factors to predict driver’s visual fixation systematically. On the BDDA dataset, we have conducted the extensive quantitative evaluation and qualitative analysis to validate the effectiveness. Its performance surpasses the previous state-of-the-art by +11.3% in the Pearson’s Correlation Coefficient, especially by a large margin of +24.5% and +28.8% in the turning operations. The ablation study further demonstrates the influence of each component in our framework. Moreover, the trained model has been deployed on the DR(eye)VE dataset to verify the generalization ability, demonstrating the potential of domain adaptation.

A COMMON GROUND BETWEEN NEUROSCIENCES AND ARCHITECTURAL DESIGN: EMPATHY, EMBODIMENT, EMOTION

In the last decade, the increasing popularity of neuroscience has involved architecture. Both neuroscientists and architects have endeavoured to understand how the experience of architecture works from the standpoint of cognitive functioning. This has been possible thanks to the neuroimaging techniques such as fMRI and discoveries like mirror neurons. These researches, despite their outstanding quality, are difficult to implement for what concerns the practice of architectural design. However, there is a common ground where architectural theory, phenomenology and neuroscience intersect, represented by empathy, embodiment, and emotion. They are the frame of the awareness of space and the counterpart of the visual perception. The main goal of design is to make the living space but to take a meaning, it has to be the “negative” of the human body. This process comes into existence through “old” tools, i.e. the mentioned empathy, embodiment, and emotion. Still, they can get a new meaning if their traditional hermeneutic is blended with the latest knowledge provided by neurosciences.

Design Meets Neuroscience: A Preliminary Review of Design Research Using Neuroscience Tools

The past decade has witnessed a burgeoning interest in the intersection of neuroscience and design. Recent advancements in tools for measuring brain activity enable design researchers to investigate how brain function supports mental processes, complementing self–report and behavioral measures in exploring design cognition. With the aim of providing a preliminary understanding of how design researchers have approached neuroscience to date, we examined (1) previously explored neural research topics, (2) available tools and their contributions and limitations, and (3) the challenges of conducting design research using neuroscience tools. We start with a brief overview of major neuroscience tools measuring brain activation including electroencephalography (EEG), magnetic resonance imaging (MRI), near–infrared spectroscopy (NIRS), and positron emission tomography (PET). We then present a review of design research specifically on neural processes involved in design thinking and creativity. Consistencies of brain activity across studies are identified. Distinct patterns of brain activation associated with specific comparisons (e.g., design thinking vs. problem–solving) observed in previous studies are also summarized. An introductory review of design research using neuroscience tools on design evaluation and aesthetics is then provided. In addition to the promises of the fast–growing interdisciplinary collaboration of design and neuroscience, we outline technical, practical, and experimental difficulties caused by the limits of neuroscience tools for design research studies.

Linking Brain Structure, Activity, and Cognitive Function through Computation.

Understanding the human brain is a "Grand Challenge" for 21st century research. Computational approaches enable large and complex datasets to be addressed efficiently, supported by artificial neural networks, modeling and simulation. Dynamic generative multiscale models, which enable the investigation of causation across scales and are guided by principles and theories of brain function, are instrumental for linking brain structure and function. An example of a resource enabling such an integrated approach to neuroscientific discovery is the BigBrain, which spatially anchors tissue models and data across different scales and ensures that multiscale models are supported by the data, making the bridge to both basic neuroscience and medicine. Research at the intersection of neuroscience, computing and robotics has the potential to advance neuro-inspired technologies by taking advantage of a growing body of insights into perception, plasticity and learning. To render data, tools and methods, theories, basic principles and concepts interoperable, the Human Brain Project (HBP) has launched EBRAINS, a digital neuroscience research infrastructure, which brings together a transdisciplinary community of researchers united by the quest to understand the brain, with fascinating insights and perspectives for societal benefits.

Forms of explanation and understanding for neuroscience and artificial intelligence.

Much of the controversy evoked by the use of deep neural networks as models of biological neural systems amount to debates over what constitutes scientific progress in neuroscience. To discuss what constitutes scientific progress, one must have a goal in mind (progress toward what?). One such long-term goal is to produce scientific explanations of intelligent capacities (e.g., object recognition, relational reasoning). I argue that the most pressing philosophical questions at the intersection of neuroscience and artificial intelligence are ultimately concerned with defining the phenomena to be explained and with what constitute valid explanations of such phenomena. I propose that a foundation in the philosophy of scientific explanation and understanding can scaffold future discussions about how an integrated science of intelligence might progress. Toward this vision, I review relevant theories of scientific explanation and discuss strategies for unifying the scientific goals of neuroscience and AI.

A scientometric analysis and review of spatial cognition studies within the framework of neuroscience and architecture

Although there is a large potential overlap between neuroscience and architecture, the studies bridging these fields are rare and newly emerging. Moreover, a gap is observed between the constructs, terminologies and research methods of architecture and neuroscience. In order to alleviate these problems, this study investigates main research themes and developments in spatial cognition research over the past two decades on the basis of the author keywords of published articles. Vosviewer© bibliometric analysis software was utilized to conduct keyword co-occurrence analysis, keyword clustering, and timeline analysis of keywords and current research on spatial cognition is discussed accordingly. The paper also reviews existing research at the intersection of neuroscience and architecture and comments on how this nexus could evolve in the future. It is concluded that embodied spatial cognition and affordances of architectural design provide a robust framework to guide further studies in this track.