Neuroscience Methods Research Articles

Promising Neuroscience Methods in Exploring the Spatiotemporal Mechanisms underlying Speech Motor Control

Speech motor control is a complex neuromotor behavior that requires the combined efforts of feedforward control and feedback control subsystems. With the advent of neuroscience, multiple lines of research have explored the spatiotemporal mechanisms underlying this process. The purpose of this review was to point out several promising neuroscience methods and their unique values in enriching the speech motor control literature. We discussed the clinical value of noninvasive brain stimulation methods, and the theoretical value of invasive brain recording methods, as well as the predictive value of brain connectivity techniques. Based on prior findings, we propose a roadmap for future research, identifying structure-function coupling that supports speech motor control.

M/EEG source localization for both subcortical and cortical sources using a convolutional neural network with a realistic head conductivity model.

While electroencephalography (EEG) and magnetoencephalography (MEG) are well-established noninvasive methods in neuroscience and clinical medicine, they suffer from low spatial resolution. Electrophysiological source imaging (ESI) addresses this by noninvasively exploring the neuronal origins of M/EEG signals. Although subcortical structures are crucial to many brain functions and neuronal diseases, accurately localizing subcortical sources of M/EEG remains particularly challenging, and the feasibility is still a subject of debate. Traditional ESIs, which depend on explicitly defined regularization priors, have struggled to set optimal priors and accurately localize brain sources. To overcome this, we introduced a data-driven, deep learning-based ESI approach without the need for these priors. We proposed a four-layered convolutional neural network (4LCNN) designed to locate both subcortical and cortical sources underlying M/EEG signals. We also employed a sophisticated realistic head conductivity model using the state-of-the-art segmentation method of ten different head tissues from individual MRI data to generate realistic training data. This is the first attempt at deep learning-based ESI targeting subcortical regions. Our method showed excellent accuracy in source localization, particularly in subcortical areas compared to other methods. This was validated through M/EEG simulations, evoked responses, and invasive recordings. The potential for accurate source localization of the 4LCNNs demonstrated in this study suggests future contributions to various research endeavors such as the clinical diagnosis, understanding of the pathophysiology of various neuronal diseases, and basic brain functions.

Clothing design factors, aesthetic experience, and preference: Additional insights from neuromarketing in civil defense clothing

ABSTRACT This study analyzed the relationships among clothing design factors, aesthetic experience, and preference and suggested ways to design civil defense clothing with better work performance. We use behavioral and electroencephalogram (EEG) experiments to identify user-preferred colors and styles and incorporate them into an improved civil defense clothing design. Through the behavioral experiment, we identified the civil defense clothing design preferred by users and explored the aesthetic experience that influenced user preference. We used the neuroscientific method of event-related potentials to further explore the neural mechanisms of users’ preferred civil defense clothing designs. In the EEG experiment, the preferred civil defense clothing contains frontal late positive potential (LPP) components involved in aesthetic experience. These results indicate that the improved civil defense clothing design evoked aesthetic experiences from users. We expect that using advanced materials and design improves the user’s aesthetic experience and preferences. This research contributes to the development of civil defense clothing that not only enhance functionality but also improve user experience and work performance.

Depressive symptoms and suicidal ideation in sexual minority adolescents: An examination of social reward responsiveness and support as moderators

Sexual minority (SM) youth are at increased risk of depression and suicidal ideation (SI), due in part to discrimination and other stressors. This raises questions about social factors that may increase risk or resilience to stressors commonly faced by SM youth. The goal of this multimethod study was to examine both neural processing of social feedback and perceived social support as potential moderators of the association between SM identity, depressive symptoms, and endorsement of SI in adolescents. For this study, 165 adolescents aged 14–17 (22.42 % identifying as SM) were oversampled for current depression. Participants self-reported social support, depressive symptoms, and SI. Electroencephalogram (EEG) was recorded while participants completed a computerized peer interaction task in which the reward positivity (RewP) component was measured in response to social acceptance vs. rejection feedback. We tested social RewP and social support as moderators of associations between SM identity, depressive symptoms, and whether SI was reported. SM youth reported lower social support and elevated depressive symptoms and were more likely to endorse SI compared to non-SM youth. Social RewP moderated the associations between SM identity, depressive symptoms, and SI such that SM youth with blunted neural responses to social acceptance had higher depression and were more likely to endorse SI. Lower social support was associated with greater depressive symptoms and SI, but social support was not a significant moderator of the association between SM identity and symptoms. This is among the first studies to use affective neuroscience methods to examine social processes in SGM youth and our findings underscore the role of social factors in SGM youth mental health.

Comparison of Studies Conducted in the Field of Neuromarketing and Artificial Intelligence Using Bibliometric Method

Abstract Neuromarketing research focuses on consumer purchase intention, decision-making processes, purchase behavior, brand awareness, brand loyalty, and repeat purchase behavior. In these studies, consumer behavior has been analyzed using neuroscientific methods and tools. The most commonly used tools include Functional Magnetic Resonance Imaging (fMRI), Eye Tracking, Electroencephalogram (EEG), Positron Emission Tomography (PET), Transcranial Magnetic Stimulation (TMS), Magnetoencephalogram (MEG), Steady State Topography (SST), Implicit Association Test (IAT), Facial Electromyography (fEMG), Automatic Face Coding (AFC), Skin Conductance Response (SCR), and other methods for measuring physiological responses. However, the use of these neuroscientific tools is not always possible due to economic constraints and lack of experimental design. Neuroscientific imaging and measurement methods are not preferred in every study due to their high costs and expertise requirements. However, when neuromarketing studies are examined, it is seen that methods such as Eye Tracking, EEG and fMRI are used more widely. These tools contribute to a deeper understanding of consumer behavior. In order to better analyze consumer behavior, it is of great importance to convey marketing stimuli and messages correctly. In the field of marketing, the effect of stimuli conveyed to consumers using the five senses is one of the focal points of neuromarketing. More than one neuroscientific method should be used together to understand consumer intentions, thoughts and purchasing behaviors. In this way, the obtained data can be analyzed more comprehensively and clearer insights can be provided about neuromarketing. The aim of this study is to present a comprehensive assessment of the use of neuroscientific tools by examining the publications in the field of neuromarketing in the Web of Science database between 2010-2024 with bibliometric analysis. The study will address the limitations of not using more than one neuroscientific tool together in neuromarketing research and the inadequacy of analyses supported by artificial intelligence. A more holistic approach will be proposed to address these shortcomings and a guiding resource for future research will be created.

A Neurophysical Hypothesis on the Role of the Intensity of the Electromagnetic Field Generated by the Cerebral Hemispheres in the Determination of Laterality, in Line with Einstein's Unified Field Theory

Abstract Objective: Traditional models of cerebral laterality, focusing primarily on anatomical and functional asymmetries, fall short of explaining the underlying physical dynamics. This study pioneers a novel perspective by hypothesizing that the intensity of the electromagnetic field generated by the cerebral hemispheres plays a crucial role in determining laterality. Inspired by Einstein's unified field theory, we explore this hypothesis through an interdisciplinary approach that merges principles of physics with neurophysiology. Material and Methods: Our research employed an innovative experimental design involving three groups of male Wistar albino rats categorized based on handedness: right-handed, left-handed, and ambidextrous. We utilized electroencephalography (EEG) to measure the electromagnetic field intensity of the cerebral hemispheres, analyzing the data through a lens that combines traditional neuroscientific methods with concepts adapted from field theory. Results: The findings reveal a significant correlation between the intensity of the electromagnetic field in the dominant hemisphere and handedness, with dominant hemispheres displaying higher field intensities. Notably, ambidextrous rats exhibited no significant difference in field intensity between hemispheres, underscoring the potential influence of electromagnetic fields on hemispheric dominance. Conclusion: This study's implications suggest a radical rethinking of how cerebral functions might be influenced by electromagnetic phenomena. The integration of Einstein's unified field theory into the study of cerebral laterality opens new pathways for research. Our findings advocate for a broader, more integrated understanding of brain functionality, highlighting the need for further interdisciplinary research in this nascent field.

The Connection between Neuroscience and Marketing

Neuroscience and marketing may seem like two separate fields, however, there is an interesting intersection between the two; the connection is called neuromarketing. Neuromarketing has emerged as a fascinating discipline that combines neuroscience principles with marketing strategies to fully understand consumer behavior. This paper explores the connection between neuroscience and marketing; it emphasizes how insights from neuroscience can drastically improve marketing strategies and consumer engagement. By collecting research findings and conclusions from many different sources, this paper thoroughly explains the ways through which neuroscience influences the field of marketing. Overall, this paper emphasizes the immense benefits for businesses who understand the neuroscience behind consumer decisions as they are able to optimize their marketing campaigns. In essence, neuromarketing is an extraordinary field that combines neuroscience with marketing to study consumers' behavior and decisions. This article will talk about how neuroscience can help improve marketing strategies in addition to consumer involvement. Not only does this paper reveal the interesting connection between marketing and neuroscience, but it also explains how marketers can use neuroscientific methods to better their campaigns.

Can late language learners acquire second language grammar? Evidence from linguistic to neuroscience methods.

Can late language learners acquire second language grammar? Evidence from linguistic to neuroscience methods.

Investigation of the Neural Basis of Social Interactions Using Hyperscanning Functional Magnetic Resonance Imaging

Hyperscanning functional magnetic resonance imaging (fMRI) was developed to gain deeper insight into the neural basis of social cognition. Simultaneous imaging of brain activity in multiple subjects facilitates analysis of the neural basis of real-time interactions and communication. This method reveals the neural basis of social interactions, including inter-individual synchronization as a phenomenon that cannot be reduced to individuals. This modality enables research into the neural mechanisms underlying social interactions that are integral to many aspects of our lives. I will outline the background, current status, and prospects of development of hyperscanning fMRI, which may be an important methodology in the shift from "first-person" neuroscience (which refers to the interaction between individuals and the environment) to "second-person" neuroscience (which refers to the application of neuroscientific methods to investigate inter-individual associations).

Development and transfer of automated methods in neuroscience: The DADTA

In the second half of the 20th century, neuroscientists across North America developed automated systems for use in their research laboratories. Their decisions to do so were complex and contingent, partly a result of global reasons, such as the need to increase efficiency and flexibility, and partly a result of local reasons, such as the need to amend perceived biases of earlier research methodologies. Automated methods were advancements but raised several challenges. Transferring a system from one location to another required that certain components of the system be standardized, such as the hardware, software, and programming language. This proved difficult as commercial manufacturers lacked incentives to create standardized products for the few neuroscientists working towards automation. Additionally, investing in automated systems required massive amounts of time, labor, funding, and computer expertise. Moreover, neuroscientists did not agree on the value of automation. My brief history investigates Karl Pribram's decisions to expand his newly created automated system by standardizing equipment, programming, and protocols. Although he was an eminent Stanford neuroscientist with strong institutional support and computer know-how, the development and transfer of his automated behavioral testing system was riddled with challenges. For Pribram and neuroscience more generally, automation was not so automatic.

A Within-Subject Multimodal NIRS-EEG Classifier for Infant Data.

Functional Near Infrared Spectroscopy (fNIRS) and Electroencephalography (EEG) are commonly employed neuroimaging methods in developmental neuroscience. Since they offer complementary strengths and their simultaneous recording is relatively easy, combining them is highly desirable. However, to date, very few infant studies have been conducted with NIRS-EEG, partly because analyzing and interpreting multimodal data is challenging. In this work, we propose a framework to carry out a multivariate pattern analysis that uses an NIRS-EEG feature matrix, obtained by selecting EEG trials presented within larger NIRS blocks, and combining the corresponding features. Importantly, this classifier is intended to be sensitive enough to apply to individual-level, and not group-level data. We tested the classifier on NIRS-EEG data acquired from five newborn infants who were listening to human speech and monkey vocalizations. We evaluated how accurately the model classified stimuli when applied to EEG data alone, NIRS data alone, or combined NIRS-EEG data. For three out of five infants, the classifier achieved high and statistically significant accuracy when using features from the NIRS data alone, but even higher accuracy when using combined EEG and NIRS data, particularly from both hemoglobin components. For the other two infants, accuracies were lower overall, but for one of them the highest accuracy was still achieved when using combined EEG and NIRS data with both hemoglobin components. We discuss how classification based on joint NIRS-EEG data could be modified to fit the needs of different experimental paradigms and needs.

Sport, social inclusion, disability and illness. Improving quality of life using new neuroscience methods

This work aims to make a contribution on how social sciences can be of support and help for people with disabilities. Social sciences can play a significant role in supporting and helping people with disabilities by identifying the environmental and social barriers that make disabilities most visible and challenging for individuals, removing them and creating more inclusive and accessible environments for them. Social sciences can also empower people with disabilities by giving them a voice and helping them build confidence and social capital. In fact, the world of physical activity, sport, disability and the path towards conquest of resilient peculiarities must merge in the awareness that they guarantee a better quality of life for disabled people is possible beyond barriers cultural, social and architectural.

Can’t ignore surrounding shapes: Neural processing mechanisms of safety sign designs

Effective safety sign design is one of the keys to accident prevention. However, the role of one design element, namely the surrounding shape, has been questioned. It may boil down to that the previous research of surrounding shapes did not reveal the net effect of shape per se. Meanwhile, the researches mostly use subjective measurement methods, such as questionnaires, which do not allow for studying the unconscious and conscious responses of people to the abstract shapes, resulting in less understanding of the role of the surrounding shape. In this study, we designed four tasks to reveal the neural processing mechanisms of pure surrounding shapes and shapes combined with pictorial symbols by using the neuroscience method (event-related potentials, ERPs). The results demonstrate that surrounding shape can convey emotional information without any context, and triangles convey negative emotion more and earlier than circles. Besides, incorporating neutral pictorial symbols into the shapes can make the cognitive processing of the combined signs earlier while not influence the degree of processing compared to pure shapes. Furthermore, the combined signs (shapes + symbols) exhibit effects on processing at two stages: early emotion perceptual processing of the surrounding shape and subsequent cognitive processing guided by neutral pictorial symbols. Therefore, the current study can deepen our understanding of surrounding shape effect and provide effective solutions for safety sign designers to facilitate the efficiency of safety signs and reduce the occurrence of hazards and accidents.

Maximizing the Effectiveness of Anti-Smoking Campaigns With Targeted Framing Strategies: Evidence From Behavioral and Neurological Studies

Background The global prevalence of smoking remains a significant public health concern, necessitating the development of effective anti-smoking campaigns to promote smoking cessation and discourage smoking initiation. Understanding the factors that influence individual responses to anti-smoking messages is critical for tailoring campaigns to different populations. Focus of the Article This study substantially exhibits the concepts of audience segmentation and targeting, informed by theory and formative research, and monitoring and evaluation research in the context of anti-smoking campaigns. Research Question The article aims to answer how smoking behavior and message framing influence individuals’ counterarguing responses to anti-smoking advertisements and the implications for ad effectiveness. Approach The research investigates the role of smoking behavior (smokers vs. non-smokers) and message framing (positive vs. negative) in shaping individuals’ counterarguing responses to anti-smoking advertisements, using two studies involving behavioral and neuroscientific methods. Methods Study 1 employed an online video task with 1920 participants, examining the effects of smoking behavior and message framing on ad effectiveness. Study 2 used electroencephalography (EEG) to record brain activity from 31 participants while they viewed anti-smoking video advertisements, focusing on the neural correlates of counterarguing and their effect on anti-smoking ad effectiveness. Results Study 1 found that smokers report lower ad effectiveness compared to non-smokers, and observed an interaction between smoking behavior and message framing. Study 2 found that smoking behavior significantly influenced brain activity in the dorsolateral prefrontal cortex (dlPFC), ventrolateral prefrontal cortex (VLPFC), and anterior cingulate cortex (ACC) regions in response to anti-smoking ads. Additionally, a significant interaction was observed between smoking behavior and ad framing on brain activity in all three regions. Recommendations for Research or Practice The findings suggest that anti-smoking campaigns should be tailored to the specific needs and attitudes of smokers and non-smokers, with separate campaigns for each group. Future research could explore the role of other individual differences in shaping counterarguing responses, the long-term effects of exposure to different types of anti-smoking messages on smoking behavior, and using more advanced neuroimaging techniques to investigate the neural processes that underlie counterarguing responses to anti-smoking messages for better flow.

A noradrenergic pathway for the induction of pain by sleep loss

An epidemic of sleep loss currently affects modern societies worldwide and is implicated in numerous physiological disorders, including pain sensitization, although few studies have explored the brain pathways affected by active sleep deprivation (ASD; e.g., due to recreation). Here, we describe a neural circuit responsible for pain sensitization in mice treated with 9-h non-stress ASD. Using a combination of advanced neuroscience methods, we found that ASD stimulates noradrenergic inputs from locus coeruleus (LCNA) to glutamatergic neurons of the hindlimb primary somatosensory cortex (S1HLGlu). Moreover, artificial inhibition of this LCNA→S1HLGlu pathway alleviates ASD-induced pain sensitization in mice, while chemogenetic activation of this pathway recapitulates the pain sensitization observed following ASD. Our study thus implicates activation of the LCNA→S1HLGlu pathway in ASD-induced pain sensitization, expanding our fundamental understanding of the multisystem interplay involved in pain processing.

Understanding Human Cognition Through Computational Modeling.

One important goal of cognitive science is to understand the mind in terms of its representational and computational capacities, where computational modeling plays an essential role in providing theoretical explanations and predictions of human behavior and mental phenomena. In my research, I have been using computational modeling, together with behavioral experiments and cognitive neuroscience methods, to investigate the information processing mechanisms underlying learning and visual cognition in terms of perceptual representation and attention strategy. In perceptual representation, I have used neural network models to understand how the split architecture in the human visual system influences visual cognition, and to examine perceptual representation development as the results of expertise. In attention strategy, I have developed the Eye Movement analysis with Hidden Markov Models method for quantifying eye movement pattern and consistency using both spatial and temporal information, which has led to novel findings across disciplines not discoverable using traditional methods. By integrating it with deep neural networks (DNN), I have developed DNN+HMM to account for eye movement strategy learning in human visual cognition. The understanding of the human mind through computational modeling also facilitates research on artificial intelligence's (AI) comparability with human cognition, which can in turn help explainable AI systems infer humans' belief on AI's operations and provide human-centered explanations to enhance human-AI interaction and mutual understanding. Together, these demonstrate the essential role of computational modeling methods in providing theoretical accounts of the human mind as well as its interaction with its environment and AI systems.

Shaping the Future of Destinations: New Clues to Smart Tourism Research from a Neuroscience Methods Approach

In the context of the technological era, the smart tourism construct serves as a bridge between human and the artificial worlds, combining social sciences and neurosciences. This study aims to explore smart tourism through neuroscientific methods in order to shape the future of tourism destinations, using a hybrid methodology combining bibliometric techniques and content analysis. The findings reveal the integration of diverse scientific domains, highlighting a transdisciplinary approach. They offer clear evidence that neuroscientific methods in smart tourism integrate multiple areas of scientific knowledge, surpassing disciplinary boundaries. “Destination” stands out alongside “emotion”, “visual attention” and eye tracking (ET). The collaboration network reveals the emergence of a new school, called neurotourism in the 21st century, formed mainly by actors and organizations from the Global North, evoking the need to include the Global South in the research scenario. The predominant methods include ET, heart rate (HR), and electroencephalography (EEG), suggesting triangulation with traditional methods for robust results. Virtual reality emerges as the primary immersive technology, promising insights when integrated with neurosciences. This study’s practical and theoretical contributions guide smart tourism strategies and enhance destination experiences through neuroscientific methods, addressing a gap in the scientific literature while advancing ontological and epistemological understanding.

A critical study on the researches about the application of neurotechnology in education

Introduction The education and pedagogy have been adopted with the development of technology in order to achieve efficient consequences and the new methods in neuroscience and neurotechnology have influenced the educational systems and the classrooms. A great number of researches have been projected in this field to demonstrate the advantages and desirable effects of neurotechnology in education and the classrooms. These researches are examinable in terms of considering both advantages and disadvantages of technology. Objects The aim of this study is to demonstrate the advantages and undesirable effects of neurotechnology in education and the classrooms. Methods This article surveys the fourteen recent researches about using neurotechnology in education and the classrooms in the framework of critical theory to discuss the adverse and undesired effects of neurotechnology as well as their neglected aspects in education and the classrooms. Findings The findings illuminate that crucial disadvantages of neurotechnology are neglected in using computerbased tools in education and the classrooms and their side effects on the participants in the process of learning. Conclusions The new methods in neuroscience and neurotechnology have influenced the educational systems and the classrooms. A considerable number of researches have been projected in this field that all try to demonstrate the advantages and desirable effects of neurotechnology in education and the classrooms, but they consciously or unconsciously neglect the immoral and unscrupulous effects of such technologies.

Modulation of neuronal dynamics by sustained and activity-dependent continuous-wave near-infrared laser stimulation.

Near-infrared laser illumination is a non-invasive alternative/complement to classical stimulation methods in neuroscience but the mechanisms underlying its action on neuronal dynamics remain unclear. Most studies deal with high-frequency pulsed protocols and stationary characterizations disregarding the dynamic modulatory effect of sustained and activity-dependent stimulation. The understanding of such modulation and its widespread dissemination can help to develop specific interventions for research applications and treatments for neural disorders. We quantified the effect of continuous-wave near-infrared (CW-NIR) laser illumination on single neuron dynamics using sustained stimulation and an open-source activity-dependent protocol to identify the biophysical mechanisms underlying this modulation and its time course. We characterized the effect by simultaneously performing long intracellular recordings of membrane potential while delivering sustained and closed-loop CW-NIR laser stimulation. We used waveform metrics and conductance-based models to assess the role of specific biophysical candidates on the modulation. We show that CW-NIR sustained illumination asymmetrically accelerates action potential dynamics and the spiking rate on single neurons, while closed-loop stimulation unveils its action at different phases of the neuron dynamics. Our model study points out the action of CW-NIR on specific ionic-channels and the key role of temperature on channel properties to explain the modulatory effect. Both sustained and activity-dependent CW-NIR stimulation effectively modulate neuronal dynamics by a combination of biophysical mechanisms. Our open-source protocols can help to disseminate this non-invasive optical stimulation in novel research and clinical applications.

Role of Intuition in Philosophical Inquiry

Purpose: This study sought to examine the role of intuition in philosophical inquiry. 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 role of intuition in philosophical inquiry. Preliminary empirical review revealed that philosophers frequently relied on intuition as a heuristic tool for generating hypotheses and evaluating arguments. The study also highlighted significant cross-cultural variations in the conceptualization and utilization of intuition in philosophical reasoning. Moreover, neuroscientific methods revealed the neural mechanisms underlying intuitive processing during philosophical tasks. Overall, the study deepened our understanding of the complexities of philosophical inquiry and identified avenues for future research to enhance the quality and rigor of philosophical research. Unique Contribution to Theory, Practice and Policy: The Reflective Equilibrium theory, Foundationalism and Coherentism may be used to anchor future studies on the role of intuition in philosophical inquiry. The study made several recommendations, contributing to theory, practice, and policy. It suggested further exploration into the nature of intuition, including its cognitive mechanisms and neural correlates, and recommended integrating empirical methods into philosophical research. Additionally, the study emphasized the importance of cultivating metacognitive awareness among philosophers and promoting ethical guidelines for the responsible use of intuition in research and dissemination. It also advocated for the integration of diverse perspectives and voices in philosophical inquiry to foster inclusivity and enrich discourse. Overall, these recommendations aimed to advance theoretical understanding, inform practical interventions, and guide policy initiatives in the field of philosophical inquiry. Keywords: Intuition, Philosophical Inquiry, Metacognitive Awareness, Ethical Guidelines, Cognitive Mechanisms, Neural Correlates, Interdisciplinary, Diversity, Inclusivity, Discourse, Responsible, Advancement