Neuroscience Techniques Research Articles

The neuropolitical imaginaries of cognitive warfare

The concept of cognitive warfare is currently gaining ground in the policy discussion and in academic research as a way of conceptualizing the ‘weaponization of the neurosciences’. Introducing the Science and Technology Studies-inspired concept of ‘neuropolitical imaginaries’ and assessing discussions on cognitive warfare launched by the NATO Innovation Hub in 2017, this article explores how the contemporary turn to the brain sciences in defense and security reimagines politics. The article argues that seeing the human mind as increasingly vulnerable to external interference redefines the nature of human agency by giving precedence to the skilful ‘cartographer’ employing neuroscientific techniques and methods for persuasion. This emerging vulnerability of the human mind reshapes security into a zero-sum game for ‘cognitive superiority’, making brain science scholars authorities in security. Finally, speaking to the literature on security expertise and science in security, the article argues that the envisaged arms race for cognitive superiority gives rise to a neurosecurity dilemma: as the neurosciences becomes entangled with security, neuroscientific practices simultaneously arise as a core vulnerability, making their work conditional upon compliance with security practices.

Enhancing Learning Abilities in Students Using a Cognitive Neuroscience Model Based on Brain-Computer Interface Signal Analysis

Computational intelligence is used to create artificially intelligent systems with the ability to learn, adapt, and solve problems. Learners’ computational abilities can be improved with the help of Cognitive Neuroscience techniques. Computational intelligence refers to the ability of a learner based on the complex operations of the brain in the four relevant dimensions: Visual (V), Aural (A), Kinematic (K), and Reading/Writing (R/W). Our proposed framework consists of electroencephalogram (EEG) data acquisition, signal extraction, and EEG signal categorization to assess students’ cognitive learning abilities. Our proposed approach uses an EEG device equipped with a microprocessor, a Think Gear (TGAM) EEG sensor, and a PCB of 16 dry electrodes. The EEG device and the remote processing device are connected by Bluetooth. The EEG signal provides the students with neurofeedback on their cognitive learning capability. The feedback obtained through the learning process will be endowing to improvise computational intelligence. The statistical derivative, Pearson Co-efficient, is used to find the correlation among the derived attributes. The attributes considered are the learner’s gender, stream, age, and geographical region. The results obtained highlight that gender, stream, and age have no correlation with the detectable learning index, and the most accurate learners are kinesthetic ones. Bi-modal learners, who can maintain focus while reading and using their kinematic abilities, had the second highest learning capacity.

TAG-SPARK: Empowering High-Speed Volumetric Imaging With Deep Learning and Spatial Redundancy.

Two-photon high-speed fluorescence calcium imaging stands as a mainstream technique in neuroscience for capturing neural activities with high spatiotemporal resolution. However, challenges arise from the inherent tradeoff between acquisition speed and image quality, grappling with a low signal-to-noise ratio (SNR) due to limited signal photon flux. Here, a contrast-enhanced video-rate volumetric system, integrating a tunable acoustic gradient (TAG) lens-based high-speed microscopy with a TAG-SPARK denoising algorithm is demonstrated. The former facilitates high-speed dense z-sampling at sub-micrometer-scale intervals, allowing the latter to exploit the spatial redundancy of z-slices for self-supervised model training. This spatial redundancy-based approach, tailored for 4D (xyzt) dataset, not only achieves >700% SNR enhancement but also retains fast-spiking functional profiles of neuronal activities. High-speed plus high-quality images are exemplified by in vivo Purkinje cells calcium observation, revealing intriguing dendritic-to-somatic signal convolution, i.e., similar dendritic signals lead to reverse somatic responses. This tailored technique allows for capturing neuronal activities with high SNR, thus advancing the fundamental comprehension of neuronal transduction pathways within 3D neuronal architecture.

Brain activities in the auditory area and insula represent stimuli evoking emotional response

Cinema, a modern titan of entertainment, holds power to move people with the artful manipulation of auditory and visual stimuli. Despite this, the mechanisms behind how sensory stimuli elicit emotional responses are unknown. Thus, this study evaluated which brain regions were involved when sensory stimuli evoke auditory- or visual-driven emotions during film viewing. Using functional magnetic resonance imaging (fMRI) decoding techniques, we found that brain activities in the auditory area and insula represent the stimuli that evoke emotional response. The observation of brain activities in these regions could provide further insights to these mechanisms for the improvement of film-making, as well as the development of novel neural techniques in neuroscience. In near feature, such a “neuro-designed” products/ applications might gain in popularity.

Influence Of Neuromarketing On Consumer Purchase Levels: Ambato Case Study - Ecuado

This work has been done with the purpose of determining the influence of neuromarketing in the levels of consumer purchase of the Paseo Shopping Ambato Mall, neuromarketing has applied neuroscience techniques focused on marketing in order to study different brain areas that are activated in the consumer when choosing a product as well as it is based on the consumer, since its objective is the identification of the impact generated by a product or brand, the understanding of the consumer when making a purchase or acquisition and the identification and satisfaction of customer needs, along with the characteristics measured by neuromarketing, which are attention, emotion and memory. The objective of the research is focused on analyzing the influence of neuromarketing in the purchase process, relating the importance that requires broadening knowledge in the understanding of the levels and stimuli that are emitted by the brands of the different products that are offered in a shopping center. The present investigation determines the neuromarketing actions to better understand the expressions and non-verbal reactions that consumers develop, associated with the advertising practices that are used in the Paseo Shopping Ambato Shopping Center; where commercial sales transactions become the result of the emotions shown by consumers towards a certain product or service. The analysis is obtained by applying a conceptual investigation on the fundamentals of neuromarketing in the purchase decision process and its influence towards a specific decision. Neuromarketing has positively influenced the purchase of a certain product by the consumer.

Memphis NeuroSTART Program: Promoting Student Success and Increasing the Diversity of Applicants to Neuroscience Graduate Programs.

With grant support from the Research Experience for Undergraduates (REU) program funded by the National Science Foundation (NSF) and the Awards to Stimulate and Support Undergraduate Research Experiences (ASSURE) program funded by the Department of Defense (DoD) Air Force Office of Scientific Research (AFOSR), we established a program intended to increase the number of underrepresented racial and ethnic minority (URM) and first-generation undergraduate students successfully applying to neuroscience and other STEM-related graduate programs. The Neuroscience Techniques and Research Training (NeuroSTART) Program aimed to increase the number of undergraduate students from the Memphis area involved in behavioral neuroscience research. In this two-semester program, students completed an empirical research project in a neuroscience lab, received individual mentoring from neuroscience faculty, became part of a STEM network, presented at research conferences, and attended specialized professional development seminars. In two cohorts of 15 students, 4 are PhD students in neuroscience-related programs or in medical school (27%), 4 are employed in neuroscience-related research facilities (27%), 3 are employed as clinical assistants (20%), and 1 is employed in the IT field (7%). The remaining three recently graduated and are planning a gap year prior to applying for admission to graduate/medical school. The Memphis NeuroSTART program has provided valuable training to participants, making them competitive applicants for jobs in the health sciences and for admittance into graduate neuroscience programs. By providing this training to first-generation and URM students, the broader impact of this program was an increase in the diversity of the health sciences workforce, particularly those specializing in neuroscience-related research and treatment.

Emotional Artificial Intelligence and Brand Association: A Neuro-Bibliometric Study

This study conducts a comprehensive bibliometric analysis to explore the research landscape in neuromarketing and brand association. With a growing interest in the neural mechanisms influencing consumer behavior, neuromarketing leverages neuroscientific techniques like fMRI, EEG, and eye tracking to uncover subconscious decision-making processes. The study aims to map research trends, identify key themes, and highlight influential works within this field. Using data from Scopus and Web of Science, the methodology includes examining publication growth, geographic distribution, co-authorship networks, and keyword co-occurrence over the past two decades. The data collection process employed effective keywords such as "neuromarketing," "brand association," "EEG," "fMRI," and "consumer behavior," ensuring a comprehensive dataset of peer-reviewed articles. The findings reveal significant growth in publications, with notable contributions from North America and Europe, and increasing input from Asia. Key insights highlight the central role of emotional engagement, sensory marketing, and the integration of advanced technologies like AI and deep learning in neuromarketing research. The study emphasizes the need for more longitudinal studies to understand the long-term impacts of neuromarketing strategies and calls for cross-cultural comparisons to enhance the global applicability of the findings. Concluding, the research identifies literature gaps and offers practical recommendations for marketers to leverage neuromarketing techniques to boost consumer engagement.

Neural Network Mechanisms Underlying General Anesthesia: Cortical and Subcortical Nuclei.

General anesthesia plays a significant role in modern medicine. However, the precise mechanism of general anesthesia remains unclear, posing a key scientific challenge in anesthesiology. Advances in neuroscience techniques have enabled targeted manipulation of specific neural circuits and the capture of brain-wide neural activity at high resolution. These advances hold promise for elucidating the intricate mechanisms of action of general anesthetics. This review aims to summarize our current understanding of the role of cortical and subcortical nuclei in modulating general anesthesia, providing new evidence of cortico-cortical and thalamocortical networks in relation to anesthesia and consciousness. These insights contribute to a comprehensive understanding of the neural network mechanisms underlying general anesthesia.

Preliminary Validation of Stereotaxic Injection Coordinates via Cryosectioning.

Stereotaxic injection of a specific brain region constitutes a fundamental experimental technique in basic neuroscience. Researchers commonly base their choice of stereotaxic injection parameters on mouse brain atlases or published materials that employed various populations/ages of mice and different stereotaxic equipment, necessitating further validation of the stereotaxic coordinate parameters. The efficacy of calcium imaging, chemogenetic, and optogenetic manipulations relies on the precise expression of reporter genes within the region of interest, often requiring several weeks of effort. Thus, it is a time-consuming task if the coordinates of the target brain region are not verified in advance. Using an appropriate dye instead of a virus and implementing cryosectioning, researchers can observe the injection site immediately following dye administration. This facilitates timely adjustments to coordinate parameters in cases where discrepancies exist between the actual injection site and the theoretical position. Such adjustments significantly enhance the accuracy of viral expression within the target region in subsequent experiments.

From E-Commerce to the Metaverse: A Neuroscientific Analysis of Digital Consumer Behavior.

The growing interest in consumer behavior in the digital environment is leading scholars and companies to focus on consumer behavior and choices on digital platforms, such as the metaverse. On this immersive digital shopping platform, consumer neuroscience provides an optimal opportunity to explore consumers' emotions and cognitions. In this study, neuroscience techniques (EEG, SC, BVP) were used to compare emotional and cognitive aspects of shopping between metaverse and traditional e-commerce platforms. Participants were asked to purchase the same product once on a metaverse platform (Second Life, SL) and once via an e-commerce website (EC). After each task, questionnaires were administered to measure perceived enjoyment, informativeness, ease of use, cognitive effort, and flow. Statistical analyses were conducted to examine differences between SL and EC at the neurophysiological and self-report levels, as well as between different stages of the purchase process. The results show that SL elicits greater cognitive engagement than EC, but it is also more mentally demanding, with a higher workload and more memorization, and fails to elicit a strong positive emotional response, leading to a poorer shopping experience. These findings provide insights not only for digital-related consumer research but also for companies to improve their metaverse shopping experience. Before investing in the platform or creating a digital retail space, companies should thoroughly analyze it, focusing on how to enhance users' cognition and emotions, ultimately promoting a better consumer experience. Despite its limitations, this pilot study sheds light on the emotional and cognitive aspects of metaverse shopping and suggests potential for further research with a consumer neuroscience approach in the metaverse field.

Towards a Paradigm Shift with Neuro-Entrepreneurship Education: a Lesson for the Developing Asian Nations

The field of neuro-entrepreneurship explores the specific characteristics that drive entrepreneurs' decisions and contribute to their success. Recent advancements in neuroscience offer a new way to understand how entrepreneurs think and behave. This understanding has led to a shift in entrepreneurial education, with a focus on integrating neuroscientific techniques. However, research in neuro-entrepreneurship is still fragmented, and there is a lack of comprehensive literature reviews. We are presenting a thorough review to address this gap and emphasize the urgent need for developing countries in South and South East Asia to incorporate neuroscientific techniques into entrepreneurial education, starting from the school level. The current entrepreneurial education in Sri Lanka suppresses the innovation and creativity of aspiring entrepreneurs, leading to a high demand for traditional practices. Integrating neuroscientific techniques into entrepreneurial education at all levels can help foster successful and productive entrepreneurs. This also emphasizes how experiments and neuroscientific techniques can improve entrepreneurial theories. This calls for a significant change in entrepreneurship education, aiming to cultivate a comprehensive entrepreneurial mindset in developing Asian nations.

Unveiling wearables: exploring the global landscape of biometric applications and vital signs and behavioral impact

The development of neuroscientific techniques enabling the recording of brain and peripheral nervous system activity has fueled research in cognitive science. Recent technological advancements offer new possibilities for inducing behavioral change, particularly through cost-effective Internet-based interventions. However, limitations in laboratory equipment volume have hindered the generalization of results to real-life contexts. The advent of Internet of Things (IoT) devices, such as wearables, equipped with sensors and microchips, has ushered in a new era in behavior change techniques. Wearables, including smartwatches, electronic tattoos, and more, are poised for massive adoption, with an expected annual growth rate of 55% over the next five years. These devices enable personalized instructions, leading to increased productivity and efficiency, particularly in industrial production. Additionally, the healthcare sector has seen a significant demand for wearables, with over 80% of global consumers willing to use them for health monitoring. This research explores the primary biometric applications of wearables and their impact on users’ well-being, focusing on the integration of behavior change techniques facilitated by IoT devices. Wearables have revolutionized health monitoring by providing real-time feedback, personalized interventions, and gamification. They encourage positive behavior changes by delivering immediate feedback, tailored recommendations, and gamified experiences, leading to sustained improvements in health. Furthermore, wearables seamlessly integrate with digital platforms, enhancing their impact through social support and connectivity. However, privacy and data security concerns must be addressed to maintain users’ trust. As technology continues to advance, the refinement of IoT devices’ design and functionality is crucial for promoting behavior change and improving health outcomes. This study aims to investigate the effects of behavior change techniques facilitated by wearables on individuals’ health outcomes and the role of wearables in promoting a healthier lifestyle.

Getting closer to social interactions using electroencephalography in developmental cognitive neuroscience

The field of developmental cognitive neuroscience is advancing rapidly, with large-scale, population-wide, longitudinal studies emerging as a key means of unraveling the complexity of the developing brain and cognitive processes in children. While numerous neuroscientific techniques like functional magnetic resonance imaging (fMRI), functional near-infrared spectroscopy (fNIRS), magnetoencephalography (MEG), and transcranial magnetic stimulation (TMS) have proved advantageous in such investigations, this perspective proposes a renewed focus on electroencephalography (EEG), leveraging underexplored possibilities of EEG. In addition to its temporal precision, low costs, and ease of application, EEG distinguishes itself with its ability to capture neural activity linked to social interactions in increasingly ecologically valid settings. Specifically, EEG can be measured during social interactions in the lab, hyperscanning can be used to study brain activity in two (or more) people simultaneously, and mobile EEG can be used to measure brain activity in real-life settings. This perspective paper summarizes research in these three areas, making a persuasive argument for the renewed inclusion of EEG into the toolkit of developmental cognitive and social neuroscientists.

Overcoming boundaries: Interdisciplinary challenges and opportunities in cognitive neuroscience

Cognitive neuroscience has considerable untapped potential to translate our understanding of brain function into applications that maintain, restore, or enhance human cognition. Complex, real-world phenomena encountered in daily life, professional contexts, and in the arts, can also be a rich source of information for better understanding cognition, which in turn can lead to advances in knowledge and health outcomes. Interdisciplinary work is needed for these bi-directional benefits to be realized. Our cognitive neuroscience team has been collaborating on several interdisciplinary projects: hardware and software development for brain stimulation, measuring human operator state in safety-critical robotics environments, and exploring emotional regulation in actors who perform traumatic narratives. Our approach is to study research questions of mutual interest in the contexts of domain-specific applications, using (and sometimes improving) the experimental tools and techniques of cognitive neuroscience. These interdisciplinary attempts are described as case studies in the present work to illustrate non-trivial challenges that come from working across traditional disciplinary boundaries. We reflect on how obstacles to interdisciplinary work can be overcome, with the goals of enriching our understanding of human cognition and amplifying the positive effects cognitive neuroscientists have on society and innovation.

FiPhA: an open-source platform for fiber photometry analysis.

Fiber photometry (FP) is a widely used technique in modern behavioral neuroscience, employing genetically encoded fluorescent sensors to monitor neural activity and neurotransmitter release in awake-behaving animals. However, analyzing photometry data can be both laborious and time-consuming. We propose the fiber photometry analysis (FiPhA) app, which is a general-purpose FP analysis application. The goal is to develop a pipeline suitable for a wide range of photometry approaches, including spectrally resolved, camera-based, and lock-in demodulation. FiPhA was developed using the R Shiny framework and offers interactive visualization, quality control, and batch processing functionalities in a user-friendly interface. This application simplifies and streamlines the analysis process, thereby reducing labor and time requirements. It offers interactive visualizations, event-triggered average processing, powerful tools for filtering behavioral events, and quality control features. FiPhA is a valuable tool for behavioral neuroscientists working with discrete, event-based FP data. It addresses the challenges associated with analyzing and investigating such data, offering a robust and user-friendly solution without the complexity of having to hand-design custom analysis pipelines. This application thus helps standardize an approach to FP analysis.

Application of robust regression in translational neuroscience studies with non-Gaussian outcome data.

Linear regression is one of the most used statistical techniques in neuroscience, including the study of the neuropathology of Alzheimer's disease (AD) dementia. However, the practical utility of this approach is often limited because dependent variables are often highly skewed and fail to meet the assumption of normality. Applying linear regression analyses to highly skewed datasets can generate imprecise results, which lead to erroneous estimates derived from statistical models. Furthermore, the presence of outliers can introduce unwanted bias, which affect estimates derived from linear regression models. Although a variety of data transformations can be utilized to mitigate these problems, these approaches are also associated with various caveats. By contrast, a robust regression approach does not impose distributional assumptions on data allowing for results to be interpreted in a similar manner to that derived using a linear regression analysis. Here, we demonstrate the utility of applying robust regression to the analysis of data derived from studies of human brain neurodegeneration where the error distribution of a dependent variable does not meet the assumption of normality. We show that the application of a robust regression approach to two independent published human clinical neuropathologic data sets provides reliable estimates of associations. We also demonstrate that results from a linear regression analysis can be biased if the dependent variable is significantly skewed, further indicating robust regression as a suitable alternate approach.

Neuroscientific Evidence in Italian Criminal Proceedings

The author asks whether and to what extent neuroscientific evidentiary techniques can be considered admissible in Italian criminal procedure to assess the mental state of the accused or to verify the truthfulness of a statement, analyzing the national jurisprudence on the subject. First, the author asks whether neuroscientific techniques can be used to determine whether the defendant was totally or partially insane at the time of the crime charged and to determine whether the defendant is a socially dangerous person. The answer is yes, although great caution must be exercised. The main risk is to theorize the existence of a real biological basis for antisocial behavior, which could even justify the adoption of restrictive measures praeter delictum against the biologically vulnerable person. Secondly, the author asks whether the techniques called A-IAT (Autobiographical Implicit Association Test) and TARA (Temporal Antagonistic Response Aletiometer), used in Italy in some criminal proceedings to verify the truthfulness of a statement, are compatible with the Italian law of evidence, which prohibits the use, even with the consent of the person concerned, of methods and techniques that are likely to impair his freedom of self-determination and his ability to recall and evaluate facts. The answer is certainly no if it is believed that these techniques can function as "memory detection" techniques, i.e. they are capable of detecting in the mind of the person concerned even memories that he or she has erased. More controversial is whether a-IAT and TARA are to be considered admissible if they are believed to be simple “lie-detection” techniques, aimed at revealing whether or not the declarant is truthful in reporting his or her memories.

Low-Power Fully Integrated 256-Channel Nanowire Electrode-on-Chip Neural Interface for Intracellular Electrophysiology.

Intracellular electrophysiology, a vital and versatile technique in cellular neuroscience, is typically conducted using the patch-clamp method. Despite its effectiveness, this method poses challenges due to its complexity and low throughput. The pursuit of multi-channel parallel neural intracellular recording has been a long-standing goal, yet achieving reliable and consistent scaling has been elusive because of several technological barriers. In this work, we introduce a micropower integrated circuit, optimized for scalable, high-throughput in vitro intrinsically intracellular electrophysiology. This system is capable of simultaneous recording and stimulation, implementing all essential functions such as signal amplification, acquisition, and control, with a direct interface to electrodes integrated on the chip. The electrophysiology system-on-chip (eSoC), fabricated in 180nm CMOS, measures 2.236 mm × 2.236 mm. It contains four 8 × 8 arrays of nanowire electrodes, each with a 50 μm pitch, placed over the top-metal layer on the chip surface, totaling 256 channels. Each channel has a power consumption of 0.47 μW, suitable for current stimulation and voltage recording, and covers 80 dB adjustable range at a sampling rate of 25 kHz. Experimental recordings with the eSoC from cultured neurons in vitro validate its functionality in accurately resolving chemically induced multi-unit intracellular electrical activity.

The Role of Prefrontal Ensembles in Memory Across Time: Time-Dependent Transformations of Prefrontal Memory Ensembles.

The medial prefrontal cortex (mPFC) plays a critical role in recalling recent and remote fearful memories. Modern neuroscience techniques, such as projection-specific circuit manipulation and activity-dependent labeling, have illuminated how mPFC memory ensembles are reorganized over time. This chapter discusses the implications of new findings for traditional theories of memory, such as the systems consolidation theory and theories of memory engrams. It also examines the specific contributions of mPFC subregions, like the prelimbic and infralimbic cortices, in fear memory, highlighting how their distinct connections influence memory recall. Further, it elaborates on the cellular and molecular changes within the mPFC that support memory persistence and how these are influenced by interactions with the hippocampus. Ultimately, this chapter provides insights into how lasting memories are dynamically encoded in prefrontal circuits, arguing for a key role of memory ensembles that extend beyond strict definitions of the engram.

CATCHU: A NOVEL VISUAL-SOMATOSENSORY INTEGRATION TOOL FOR PREDICTING FALLS

Abstract Ability to integrate information across sensory systems is a vital aspect of human functioning in the real world. While multisensory integration effects are measured across a wide array of populations using various sensory pairings and different neuroscience techniques, a gold standard for quantifying multisensory integration was seemingly lacking. We recently established a standardized protocol for administering and calculating behavioral multisensory integration effects across diverse clinical populations and age-ranges. Our previous work has linked the magnitude of visual-somatosensory integration (measured behaviorally using simple reaction time tasks) to important cognitive (attention) and motor (balance, gait, and falls) outcomes in healthy and cognitively impaired older adults. Given the paucity of extant translational multisensory integration tools in clinical settings, we recently developed a novel digital health app grounded in over 15 years of multisensory research. CatchU® (Before You Fall…) quantitatively measures visual-somatosensory integration performance, while considering medical comorbidities, to detect one’s fall propensity. Our goal is to facilitate the identification of patients who are at increased risk of falls and promote physician-initiated falls counseling in routine practice (e.g., annual wellness, sick, or follow-up visits). This will thereby raise awareness of falls and foster physician efforts to alleviate disability, promote independence, and improve the well-being of older adults, all while aiming to reduce the significant societal cost of falls in older adults and others at high risk.