Neuroscientific Findings Research Articles

A scalable platform for acquisition of high-fidelity human intracranial EEG with minimal clinical burden.

Human neuroscience research has been significantly advanced by neuroelectrophysiological studies from people with refractory epilepsy-the only routine clinical intervention that acquires multi-day, multi-electrode human intracranial electroencephalography (iEEG). While a sampling rate below 2 kHz is sufficient for manual iEEG review by epileptologists, computational methods and research studies may benefit from higher resolution, which requires significant technical development. At adult and pediatric Stanford hospitals, research ports of commercial clinical acquisition systems were configured to collect 10 kHz iEEG of up to 256 electrodes simultaneously with the clinical data. The research digital stream was designed to be acquired post-digitization, resulting in no loss in clinical signal quality. This novel framework implements a near-invisible research platform to facilitate the secure, routine collection of high-resolution iEEG that minimizes research hardware footprint and clinical workflow interference. The addition of a pocket-sized router in the patient room enabled an encrypted tunnel to securely transmit research-quality iEEG across hospital networks to a research computer within the hospital server room, where data was coded, de-identified, and uploaded to cloud storage. Every eligible patient undergoing iEEG clinical evaluation at both hospitals since September 2017 has been recruited; participant recruitment is ongoing. Over 350+ terabytes (representing 1000+ days) of neuroelectrophysiology were recorded across 200+ participants of diverse demographics. To our knowledge, this is the first report of such a research integration within a hospital setting. It is a promising approach to promoting equitable participant enrollment and building comprehensive data repositories with consistent, high-fidelity specifications towards new discoveries in human neuroscience.

High‐density implantable neural electrodes and chips for massive neural recordings

AbstractHigh‐density neural recordings with superior spatiotemporal resolution powerfully unveil cellular‐scale neural communication, showing great promise in neural science, translational medicine, and clinical applications. To achieve such, many design and fabrication innovations enhanced the electrode, chip, or both for biocompatibility improvement, electrical performance upgrade, and size miniaturization, offering several thousands of recording sites. However, an enormous gap exists along the trajectory toward billions of recording sites for brain scale resolution, posing many more design challenges. This review tries to find possible insight into mitigating the gap by discussing the latest progress in high‐density electrodes and chips for neural recordings. It emphasizes the design, fabrication, bonding techniques, and in vivo performance optimization of high‐density electrodes. It discusses the promising opportunities for circuit‐level and architecture‐level multi‐channel chip design innovations. We expect that joint effort and close collaboration between high‐density electrodes and chips will pave the way to high‐resolution neural recording tools supporting cutting‐edge neuroscience discoveries and applications.

Prior-Guided Adversarial Learning With Hypergraph for Predicting Abnormal Connections in Alzheimer's Disease.

Alzheimer's disease (AD) is characterized by alterations of the brain's structural and functional connectivity during its progressive degenerative processes. Existing auxiliary diagnostic methods have accomplished the classification task, but few of them can accurately evaluate the changing characteristics of brain connectivity. In this work, a prior-guided adversarial learning with hypergraph (PALH) model is proposed to predict abnormal brain connections using triple-modality medical images. Concretely, a prior distribution from anatomical knowledge is estimated to guide multimodal representation learning using an adversarial strategy. Also, the pairwise collaborative discriminator structure is further utilized to narrow the difference in representation distribution. Moreover, the hypergraph perceptual network is developed to effectively fuse the learned representations while establishing high-order relations within and between multimodal images. Experimental results demonstrate that the proposed model outperforms other related methods in analyzing and predicting AD progression. More importantly, the identified abnormal connections are partly consistent with previous neuroscience discoveries. The proposed model can evaluate the characteristics of abnormal brain connections at different stages of AD, which is helpful for cognitive disease study and early treatment.

Attention-guided graph structure learning network for EEG-enabled auditory attention detection

Objective: Decoding auditory attention from brain signals is essential for the development of neuro-steered hearing aids. This study aims to overcome the challenges of extracting discriminative feature representations from electroencephalography (EEG) signals for auditory attention detection (AAD) tasks, particularly focusing on the intrinsic relationships between different EEG channels. Approach: We propose a novel attention-guided graph structure learning network, AGSLnet, which leverages potential relationships between EEG channels to improve AAD performance. Specifically, AGSLnet is designed to dynamically capture latent relationships between channels and construct a graph structure of EEG signals. Main result: We evaluated AGSLnet on two publicly available AAD datasets and demonstrated its superiority and robustness over state-of-the-art models. Visualization of the graph structure trained by AGSLnet supports previous neuroscience findings, enhancing our understanding of the underlying neural mechanisms. Significance: This study presents a novel approach for examining brain functional connections, improving AAD performance in low-latency settings, and supporting the development of neuro-steered hearing aids.

The Philosophical Implications of Neuroscience Research on Free Will and Moral Responsibility

Purpose: This study sought to analyze the philosophical implications of neuroscience research on free will and moral responsibility. 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 the philosophical implications of neuroscience research on free will and moral responsibility. Preliminary empirical review recognized that the compatibility between neuroscientific determinism and philosophical concepts of free will. It highlighted the need for interdisciplinary collaboration to address the ethical considerations and societal implications of using neuroscientific evidence in legal and ethical contexts. The study emphasized the importance of public engagement to foster informed discourse on the ethical and philosophical implications of neuroscience research. Overall, the findings underscored the complexity of navigating the intersection of neuroscience and philosophy, calling for continued interdisciplinary dialogue to address the multifaceted implications of neuroscience research on free will and moral responsibility. Unique Contribution to Theory, Practice and Policy: Compatibilism, Libertarianism and Determinism may be used to anchor future studies on philosophical implications of neuroscience research on free will and moral responsibility. The study provided valuable insights and recommendations across theory, practice, and policy. It contributed to theoretical advancements by synthesizing neuroscientific findings with philosophical theories, fostering interdisciplinary collaboration. In practice, the study emphasized ethical considerations in research conduct and interpretation, aiming to enhance the reliability and validity of neuroscientific evidence. Policy recommendations focused on developing evidence-based policies governing the use of neuroscientific evidence and promoting public engagement and education. Additionally, the study identified areas for further research, such as longitudinal and cross-cultural studies, to advance understanding in the field. Overall, the study highlighted the importance of ethical considerations and responsible innovation in the development and application of neuroscience research. Keywords: Philosophical Implications, Neuroscience Research, Free Will, Moral Responsibility, Ethics, Interdisciplinary Collaboration, Neuroscientific Findings, Public Engagement, Education, Ethical Considerations, Responsible Innovation

It Depends

While Comic-Con is a celebration of popular culture, it is also a launching pad for new properties in film and television. In recent years, the conventional thought about how to approach this has changed from handing out free memorabilia such as tee shirts and posters to providing an actual experience in the properties world. This type of advertising is the immersive activation. The goal of the activation is an analogous relationship between the live experience and the mediated, neither serving as the precedent to the other. In embracing this analogous relationship, mediatized and live performances move forward, establishing new entanglements with their audience. The clearest example of this analogous relationship exists in activations. An immersive activation is a live-action event where the spectator is tasked with the moniker of both audience and participant. The shift from “viewer” to “collaborator” is, as Clair Bishop (2012) and so many others have noted, manifested in fascinating and new creations. I take an approach following neuroscientific discoveries, which support this shift through different means joining the brain’s function with philosophy, as I explore the immersive activation.

Disentangling periodic and aperiodic resting EEG correlates of personality

Previous studies of resting electroencephalography (EEG) correlates of personality traits have conflated periodic and aperiodic sources of EEG signals. Because these are associated with different underlying neural dynamics, disentangling them can avoid measurement confounds and clarify findings. In a large sample (n = 300), we investigated how disentangling these activities impacts findings related to two research programs within personality neuroscience. In Study 1 we examined associations between Extraversion and two putative markers of reward sensitivity—Left Frontal Alpha asymmetry (LFA) and Frontal-Posterior Theta (FPT). In Study 2 we used machine learning to predict personality trait scores from resting EEG. In both studies, power within each EEG frequency bin was quantified as both total power and separate contributions of periodic and aperiodic activity. In Study 1, total power LFA and FPT correlated negatively with Extraversion (r ∼ -0.14), but there was no relation when LFA and FPT were derived only from periodic activity. In Study 2, all Big Five traits could be decoded from periodic power (r ∼ 0.20), and Agreeableness could also be decoded from total power and from aperiodic indices. Taken together, these results show how separation of periodic and aperiodic activity in resting EEG may clarify findings in personality neuroscience. Disentangling these signals allows for more reliable findings relating to periodic EEG markers of personality, and highlights novel aperiodic markers to be explored in future research.

Exploring Neuro Management: Bridging Science and Leadership – An Overview

Purpose: To develop a comprehensive overview of Neuro Management, by bridging the gap between scientific insights and effective leadership within organizational contexts based on exploring Neuro Management concepts, applications, and their implications for managerial practices. Procedure: The overview begins by delineating the fundamental concepts and applications of Neuro Management, elucidating its relevance in leveraging neuroscience principles for enhancing leadership effectiveness. It then provides an extensive overview of key themes and contributions within the field, identifying foundational works and highlighting significant research directions. A critical analysis of the evolution of Neuro Management concepts is presented, identifying existing research gaps and tracing the evolutionary trajectory of the field. Furthermore, a conceptual framework is developed, integrating neuroscience principles with leadership practices, and delineating a structured approach for applying neuroscience insights in leadership contexts. Analysis: The paper discusses the neural mechanisms underlying various aspects related to Neuro Management, exploring decision-making processes, emotional intelligence, and their neural correlates. Subsequently, it analyzes how Neuro Management concepts bridge the gap between scientific insights and effective leadership, highlighting the translation of neuroscience findings into practical leadership strategies. Moreover, the implications of Neuro Management for organizational practices, decision-making, team dynamics, and productivity are expounded upon, emphasizing its transformative impact on enhancing organizational performance. The study assesses the connection between human productivity and Neuro Management, focusing on how Neuro Management strategies affect organizational effectiveness. The study also critically analyzes leadership and neuro management from a managerial perspective, evaluating their effects on organizational outcomes and their roles in decision-making. Additionally, it explores how different Neuro Management models that are helpful in decision science might be applied to create efficient decision-making processes. Furthermore, the paper adopts an ABCD listing framework, analyzing Neuro Management from Managers' Points of View, evaluating its Advantages, Benefits, Constraints, and Disadvantages. Finally, it suggests postulates for future research and practical applications in Neuro Management, emphasizing areas warranting further exploration and implementation. Originality/Value: This comprehensive overview aims to serve as a foundational resource in the expanding field of Neuro Management, offering insights, analyses, and frameworks for advancing leadership practices informed by neuroscience principles. Type of Paper: Conceptual exploratory research.

Neuro-Robotics: Bridging Neuroscience and Robotics

The field of neurorobotics represents the combination of neuroscience and robotics, aiming to elucidate neural functional principles and use them to create intelligent robots. This article considers the symbiotic relationship between the two fields and explores how insights from neuroscience can inform the design and control of robots; Robotic platforms offer a unique opportunity to learn and validate insights from neuroscience. For example, this article focuses on the core concepts of neuroscience and robotics and highlights key advances that support the integration of these fields, including brain-computer interfaces, neurorobotic simulations, and bionic design. It examines how discoveries in neuroscience, such as the understanding of sensorimotor control, learning processes, and cognitive processes, are supporting the creation of biomimetic robots that can address behavioural challenges and interact with their environments.

Neuromarketing Insights Enhanced by Artificial Intelligence

The intersection of neuromarketing and artificial intelligence is examined in this research, along with the significant implications for transforming marketing tactics. By using neuroscience methods to identify subconscious reactions to marketing stimuli, neuromarketing sheds light on consumer behaviour. The integration of AI enhances neuromarketing research by effectively analysing neurodata and detecting significant patterns. When combined, they allow for marketing initiatives that are emotionally compelling, targeted, and personalised. However, ethical issues pertaining to bias in AI algorithms, customer privacy, and societal ramifications need to be taken into account. Businesses must adopt this multidisciplinary strategy if they want to stay ahead in the increasingly competitive market. This study advocates for responsible and ethical use in marketing practices while highlighting the transformational potential of utilising AI technologies with neuroscience findings.

Telling the Stories of Neuroscientific Discovery to Schoolchildren and the Public Can Make an Impact.

Telling the Stories of Neuroscientific Discovery to Schoolchildren and the Public Can Make an Impact.

Stability and variation of brain-behavior correlation patterns across measures of social support

Abstract The social environment has a critical influence on human development, cognition, and health. Research in health psychology and social neuroscience indicate an urgent need to understand how social relationships are associated with brain function and organization. To address this, we apply multilayer modeling and modularity maximization—both established tools in network neuroscience—to jointly cluster patterns of brain-behavior associations for seven social support measures. By using network approaches to map and analyze the connectivity between all pairs of brain regions simultaneously, we can clarify how relationships between brain regions (e.g. connectivity) change as a function of social relationships. This multilayer approach enables direct comparison of brain-behavior associations across social contexts for all brain regions and builds on both ecological and developmental neuroscientific findings and network neuroscientific approaches. In particular, we find that subcortical and control systems are especially sensitive to different constructs of perceived social support. Network nodes in these systems are highly flexible; their community affiliations, which reflect groups of nodes with similar patterns of brain-behavior associations, differ across social support measures. Additionally, our application of multilayer modeling to patterns of brain-behavior correlations, as opposed to just functional connectivity, represents and innovation in how multilayer models are used in human neuroscience. More than that, it offers a generalizable technique for studying the stability and variation of brain-behavior associations.

Peculiarities of Translating an Oral Text in the Field of Neuro-Legal and its Transformation into Written Text

Due to the practical usage of neuro-technologies in all areas of our life, lawyers make attempts to provide a legal definition of such a philosophical category as mind, which expresses the highest type of thinking activity, and to develop legal norms and standards in this field. The area of law that deals with the impact of neuroscience discoveries on the regulation of social relations is referred to as neurolaw. This branch of law is considered to be interdisciplinary establishing close connections with a spectrum of sciences such as neuropsychology, neurogenetics, neurobiology, neurosociology and many other neurosciences and links a brain with law. As a result this area of law often employs categories and concepts of those sciences. This is a reason for legal terminology in this field of law to be constantly broadened. New legal terms are of great interest to translators who create and analyze conceptual fields in the area of “neuro-law”. For translators it is a real challenge to deal with specialized legal texts when they can apply not only their translation skills, techniques and methods but also their knowledge in a particular field of neuro-technology application in the real sector of economy. The author of the article makes an attempt to reveal the peculiarities and features of translation of the texts which deal with human body enhancement technologies and legal issues related to their application. New legal terms and concepts are of great interest to understand a developing area of law.

Numerosity estimation of virtual humans as a digital-robotic marker for hallucinations in Parkinson’s disease

Hallucinations are frequent non-motor symptoms in Parkinson’s disease (PD) associated with dementia and higher mortality. Despite their high clinical relevance, current assessments of hallucinations are based on verbal self-reports and interviews that are limited by important biases. Here, we used virtual reality (VR), robotics, and digital online technology to quantify presence hallucination (vivid sensations that another person is nearby when no one is actually present and can neither be seen nor heard) in laboratory and home-based settings. We establish that elevated numerosity estimation of virtual human agents in VR is a digital marker for experimentally induced presence hallucinations in healthy participants, as confirmed across several control conditions and analyses. We translated the digital marker (numerosity estimation) to an online procedure that 170 PD patients carried out remotely at their homes, revealing that PD patients with disease-related presence hallucinations (but not control PD patients) showed higher numerosity estimation. Numerosity estimation enables quantitative monitoring of hallucinations, is an easy-to-use unobtrusive online method, reaching people far away from medical centers, translating neuroscientific findings using robotics and VR, to patients’ homes without specific equipment or trained staff.

Multimode fiber endoscopes for computational brain imaging.

Advances in imaging tools have always been a pivotal driver for new discoveries in neuroscience. An ability to visualize neurons and subcellular structures deep within the brain of a freely behaving animal is integral to our understanding of the relationship between neural activity and higher cognitive functions. However, fast high-resolution imaging is limited to sub-surface brain regions and generally requires head fixation of the animal under the microscope. Developing new approaches to address these challenges is critical. The last decades have seen rapid progress in minimally invasive endo-microscopy techniques based on bare optical fibers. A single multimode fiber can be used to penetrate deep into the brain without causing significant damage to the overlying structures and provide high-resolution imaging. Here, we discuss how the full potential of high-speed super-resolution fiber endoscopy can be realized by a holistic approach that combines fiber optics, light shaping, and advanced computational algorithms. The recent progress opens up new avenues for minimally invasive deep brain studies in freely behaving mice.

The HERVAT Method as a Neurolearning Strategy in Education

The pedagogical methodology has evolved in recent years, moving towards approaches that integrate advances in neuroscience with educational practices. In this context, the HERVAT method emerges, aiming to consolidate these advances and apply them in the educational sphere to enhance the learning experience. The main objective of this research was to implement the HERVAT method in various educational institutions in Ecuador. For this, a qualitative methodology was adopted, with an analysis based on the systematization of experiences and grounded in the profound interpretation of a specific phenomenon. Through a rigorous data collection and analysis process, which incorporated techniques such as observations and documentary analysis, the HERVAT method was applied to students in seven renowned educational institutions in the country. The findings of the study highlight those contemporary pedagogical interventions, supported by this method, emphasize the holistic development of the student. By integrating innovative techniques, such as gamification and multisensory stimulation, the aim is to align pedagogical practices with key discoveries in neuroscience. This alignment enhances brain plasticity, facilitating adaptability and depth in learning processes. The personalization of strategies and adherence to empirical evidence emerge as fundamental components to elevate educational quality in the contemporary era. It is concluded that the HERVAT method, rooted in neuroscientific principles, revitalizes learning by activating crucial neural circuits, optimizing aspects such as student attention and concentration. Strategies based on neurodidactics, backed by empirical evidence, highlight the relevance of natural environments and varied stimuli, enhancing sensory perception and the active commitment of the student in their educational process. This approach promotes comprehensive education, aiming to maximize each student's neurocognitive potential.
 
 Received: 22 September 2023 / Accepted: 27 January 2024 / Published: 5 March 2024

Cerebral asymmetry representation learning-based deep subdomain adaptation network for electroencephalogram-based emotion recognition.

Objective.Extracting discriminative spatial information from multiple electrodes is a crucial and challenging problem for electroencephalogram (EEG)-based emotion recognition. Additionally, the domain shift caused by the individual differences degrades the performance of cross-subject EEG classification.Approach.To deal with the above problems, we propose the cerebral asymmetry representation learning-based deep subdomain adaptation network (CARL-DSAN) to enhance cross-subject EEG-based emotion recognition. Specifically, the CARL module is inspired by the neuroscience findings that asymmetrical activations of the left and right brain hemispheres occur during cognitive and affective processes. In the CARL module, we introduce a novel two-step strategy for extracting discriminative features through intra-hemisphere spatial learning and asymmetry representation learning. Moreover, the transformer encoders within the CARL module can emphasize the contributive electrodes and electrode pairs. Subsequently, the DSAN module, known for its superior performance over global domain adaptation, is adopted to mitigate domain shift and further improve the cross-subject performance by aligning relevant subdomains that share the same class samples.Main Results.To validate the effectiveness of the CARL-DSAN, we conduct subject-independent experiments on the DEAP database, achieving accuracies of 68.67% and 67.11% for arousal and valence classification, respectively, and corresponding accuracies of 67.70% and 67.18% on the MAHNOB-HCI database.Significance.The results demonstrate that CARL-DSAN can achieve an outstanding cross-subject performance in both arousal and valence classification.

The Neuromyth of learning styles

In recent years, neuroscience has gained prominence in the field of education. However, those who seek to learn about neuroscience on their own may encounter inaccurate information or misconceptions about neuroscientific findings, known as neuromyths. One of the most widespread myths among educators is the one about Learning Styles (LS), which suggests that students learn best when information is presented according to their preferred style. This study aimed to investigate the perception of Biological Sciences students at the University of Brasília (UnB) regarding this neuromyth. To achieve this, an online questionnaire was administered to the participants. The results indicated that students have a positive view of Learning Styles. Therefore, it is necessary to debunk this neuromyth in the academic environment by integrating the study of neuroscience and educational neuromyths into initial teacher education through courses, research projects, and extension activities.

Cognitive neuroscience and music education: Relationships and interactions

This article examines the relationship between cognitive neuroscience and music education, evaluating the impact of cognitive neuroscience on musical learning, performance, and teaching strategies. The first section establishes the purpose and scope of the article, followed by an emphasis on the foundations of cognitive neuroscience in the second section. Cognitive neuroscience is explored in terms of music perception, mental processes, and fundamental concepts related to learning and memory. The third section, focusing on cognitive processes in music education, delves into the cognitive foundations of musical knowledge, addressing topics such as melody and rhythm perception and cognitive development in instrumental education. The fourth section discusses the neuroscientific analysis of musical performance, stage fright, brain activity, creativity, and mental processes. The fifth section discusses cognitive neuroscience-based teaching models, the neuroscientific foundations of student-centred approaches, and the role of technology in music education. The sixth section highlights future perspectives and research directions, recommendations for future studies, contributions of new cognitive neuroscience findings to music education, current developments in the intersection of music and cognitive neuroscience, and suggestions for future research. In the concluding section, the summarised article's significant findings and contributions are emphasised, drawing attention to potential areas for future examination and application. This article aims to serve as a comprehensive resource for readers interested in understanding the connections between cognitive neuroscience and music education, providing a foundation for further research in this field.

Evolutionary origin of the nervous system from Ctenophora prospective.

Nervous system is one of the key adaptations underlying the evolutionary success of the majority of animal groups. Ctenophores (or comb jellies) are gelatinous marine invertebrates that were probably the first lineage to diverge from the rest of animals. Due to the key phylogenetic position and multiple unique adaptations, the noncentralized nervous system of comb jellies has been in the center of the debate around the origin of the nervous system in the animal kingdom and whether it happened only once or twice. Here, we discuss the latest findings in ctenophore neuroscience and multiple challenges on the way to build a clear evolutionary picture of the origin of the nervous system.