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Neuro-technology and counselling
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Neurobiological aspects of violent and criminal behaviour: Deficits in frontal lobe function and neurotransmitters
Many neurobiological abnormalities have been reported in patients with violent and criminal behaviour. Strong associations exist between aggressive/violent behaviour and brain dysfunction. Also, many studies support an association between frontal lobe dysfunction and increased aggressive or antisocial behaviour. The focal orbitofrontal brain injury is specifically associated with increased aggression. Deficits in frontal lobe executive functions may increase the likelihood of future aggression, but as of now, studies have reliably demonstrated a characteristic pattern of frontal network dysfunction predictive of violent crime. The evidence is strongest for an association between focal prefrontal damage and an impulsive subtype of aggressive behaviour. This paper covers dysfunctions in these regions contributing to severe aggressive and violent behaviour, as well as neurotransmitters implicated in the same. 2018 International Journal of Criminal Justice Sciences (IJCJS). -
Neurocognitive aspects of mathematical achievement in children
Neurocognitive factors, including information integration and executive functioning, contribute significantly to a child's early success in math achievement, even though the significance of home and school environments cannot be ignored. There are only a few studies that have systematically examined how information integration and executive function skills impact different aspects of learning math and math achievement. Using a comprehensive tool such as the brain-Based Intelligence Test (BBIT), a brain-based comprehensive approach to the understanding of cognition, for the assessment of information integration and executive function skills can have significant implications for mathematical education and remediation (brain plasticity). The Author(s), under exclusive license to Springer Nature Switzerland AG 2021. All rights reserved. -
Neurocognitive modeling of emotional states using EEG and hidden markov models: A multidisciplinary approach
This interdisciplinary research cuts computational modeling and cognitive neuroscience approaches with the intention of studying dynamic emotional involvement with multimedia stimuli via HMM analysis of EEG data. In particular, the paper deals with advertisements that target excitement and love-type emotions, setting forth new paradigms for understanding the building and modulation of emotional experience across time in the human brain. EEG parameters such as amplitude, arousal, and frontal activation were studied as markers of neural reactions to emotionally arousing content. The neural markers are tracked over time to record the changes in emotional engagement. The HMMs use identifies hidden neural states and their probabilistic transitions, making the temporal description of neural dynamics during emotional processing rich and nuanced. The analytical approach provides identifiable neural patterns for excitement and love stimuli distinguished in terms of arousal, spectral amplitude, and hemispheric asymmetry in frontal activation. Due to these distinctions, we ascertain that the brain processes different affective tones distinctly, shedding light on the intricacies of emotion perception and its immediate brain counterpart. Using the results, a predictive HMM model is presented to model emotional changes when individuals are subjected to effective multimedia stimuli. The model serves as a bridge to further real-time developments in human-computer interaction, adaptive e-learning, immersive media conception, and affective UX (user experience) optimization. In other words, this enables the system to detect shifts in the user's emotions automatically and adapt content accordingly, representing truly affect-sensitive technologies. Amalgamating computational modeling with neurophysiological measurement, this study contributes to the birth of emotion-aware technology that can be dynamically responsive to the users' current affective state, thus harnessing engagement, personalization, and user satisfaction as opportunities. It builds on the interdisciplinary discourse between cognitive neuroscience, affective computing, and computational psychology to serve as a methodological guideline for future investigations into emotional dynamics and brain-computer interfaces (BCIs), as well as neuroadaptive technology. It makes a case for the relevance of temporal modeling in decoding emotional cognition and therefore advocates the continued employment of machine-learning approaches in brain activity and human affective behaviour studies. Copyright (c) 2025 The Authors. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. -
Neurodiversity at the Workplace: The new paradigm of talent acquisition and retention
The importance of neurodiversity in the workplace has gained popularity in recent years. Companies can access a pool of distinctive skills and viewpoints that can stimulate innovation, creativity, and productivity by embracing neurodiversity in the workplace. This chapter examines the idea of neurodiversity in relation to hiring and retaining talent, emphasizing the advantages for both companies and workers. It covers methods for establishing welcoming environments at work that support neurodiverse workers and help them reach their full potential. It also looks at how corporate culture, HR regulations, and leadership all contribute to creating a welcoming workplace for individuals who are neurodiverse. Companies can promote diversity, equity, and inclusion at the workplace in addition to attracting and retaining neurodiverse employees (NDEs). A conceptual framework has been proposed to demonstrate the influence of various factors like awareness, perceived benefits, accommodation, organizational policy, stigma, and unconscious bias on retention of NDEs. 2024, IGI Global. -
Neurofeedback Therapy Meets Transformers: Rewiring Sleep Disorders Through AI-Driven EEG Modulation
Sleep disorders such as insomnia, sleep Apnea, and hypersomnia significantly impair neurophysiological functioning, yet conventional treatments like Cognitive Behavioral Therapy for Insomnia (CBT-I) remain resource-intensive and difficult to personalize. This study introduces a novel AI-powered neurofeedback simulation framework designed to detect dysregulated EEG frequency band activity across sleep stages and simulate targeted interventions. A Transformer-based model serves as the core component, offering a unique capability to model cross-epoch temporal dynamics and frequency-specific spectral patterns. Unlike traditional architectures that treat EEG epochs in isolation, the Transformer captures how EEG band activity evolves across the night, critical for identifying persistent dysregulation patterns and planning stage-specific interventions. Through its multi-head attention mechanism, the model can simultaneously monitor delta, theta, alpha, beta, and gamma fluctuations while preserving sleep architecture transitions using positional encoding. Dysregulated epochs are classified with 92% accuracy, and intervention simulations-such as beta suppression in N2 or delta enhancement in REM-led to measurable improvements: average WASO decreased by 23%, and Sleep Efficiency improved by 13%. This framework not only demonstrates the efficacy of Transformer-based temporal-spectral modelling in EEG but also lays the foundation for closed-loop, wearable-compatible, personalized neurofeedback systems for remote sleep therapy. 2026 A l A KA d V idh hi V -
Neuroinflammation and cognitive function in infectious diseases
Inflammation of the central nervous system (CNS), which various infectious diseases can induce and significantly affect cognitive functions. The review enriches the current understanding of neuroinflammation pathology and suggests novel diagnostic/therapeutic strategies for cognitive impairments. Pathogens cause disruption of the blood-brain barrier (BBB), which could be due to a repertoire of mechanism viz. the interplay of inflammatory cytokines and reactive oxygen species. The influence of neuroinflammation on cognitive function is immense and multifactorial. Neuroinflammatory responses in the acute phase can result in cognitive impairments, like memory deficits, attention span being reduced, and executive dysfunction. However, in cases of persistent neuroinflammation lead to long-term cognitive decline and neurodegenerative processes. The mechanisms underlying these cognitive changes are diverse, including disruptions in synaptic plasticity, alterations in neurotransmitter systems, and neuronal cell death. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Neuroleadership strategies: Elevating motivation and engagement among employees
In the ever-evolving landscape of the modern era, organizations face the ongoing challenge of maintaining motivated and engaged employees. Despite the substantial body of research on this topic, many organizations still struggle to effectively promote engagement and motivation among their employees. This research aims to investigate the application of neuroleadership strategies in addressing this issue. The SCARF model, based on neuroscience principles, provides a valuable framework for understanding neuroleadership strategies which address social and emotional triggers that impact engagement and motivation. It can be effectively used to drive motivation and engagement in the workplace by addressing the fundamental social and emotional needs of employees. This study employs a quantitative approach which assesses the 321 employees from different organizations in India. The results of the study would provide leaders with practical insights to boost motivation and engagement in organizations and thereby improve the effectiveness of the organization. 2024, IGI Global. All rights reserved. -
Neuromarketing: The new science of advertising /
Universal Journal Of Management, Vol.3, Issue 12, pp.524 - 531, ISSN No: 2331-950X. -
Neuropalliative Care Needs Checklist for Motor Neuron Disease and Parkinson's Disease: A Biopsychosocial Approach
Objectives: Neurodegenerative disorders necessitate comprehensive palliative care due to their progressive and irreversible nature. Limited studies have explored the comprehensive assessment needs of this population. This present study is designed to develop a checklist for evaluating the palliative care needs of individuals with motor neuron disease (MND) and Parkinson's disease (PD). Materials and Methods: The checklist was created through an extensive literature review and discussions with stakeholders in neuropalliative. Feedback from six field experts led to the finalisation of the checklist, which comprised 53 items addressing the unique biopsychosocial needs of MND and PD. Sixty patient-caregiver dyads receiving treatment in a tertiary referral care centre for neurology in south India completed the checklist. Results: People with MND had more identified needs with speech, swallowing, and communication, while people with PD reported needs in managing tremors, reduced movements, and subjective feelings of stiffness. People denying the severity of the illness was found to be a major psychosocial issue. The checklist addresses the dearth of specific tools for assessing palliative care needs in neurodegenerative disorders, particularly MND and PD. By incorporating disease-specific and generic items, the checklist offers a broad assessment of patients' multidimensional needs. Conclusion: This study contributes to the area of neuropalliative care by developing the neuropalliative care needs checklist (NPCNC) as a valuable tool for assessing the needs of individuals with neurodegenerative diseases. Future research should focus on refining and validating the NPCNC with larger and more diverse groups, applicability in different contexts, and investigating its sensitivity to changes over time. 2024 Published by Scientific Scholar on behalf of Indian Journal of Palliative Care. -
NEUROPLASTICITY UNLEASHED: Receiving the Brain for Recovery
Neuroplasticity, the brains dynamic ability to reorganize and adapt across the lifespan, underpins contemporary approaches to neurorehabilitation. This chapter critically examines the clinical, neuroimaging, and neurophysiological evidence for plasticity-driven recovery. Drawing on longitudinal studies and case-based analyses, we illuminate how recovery can occur even in late stages, challenging the traditional notion of static chronic phases. The chapter highlights the role of task-specific practice, intensity, and timing in shaping neural reorganization, emphasizing that plasticity is not merely a spontaneous biological process but one that can be modulated through structured intervention. We further explore how electroencephalography (EEG)-based markers offer temporally precise insights into reorganization across cognitive, sensory, and affective domains. Neuroimaging findings reveal compensatory activation, network shifts, and bilateral engagement as hallmarks of adaptive plasticity. Affect, motivation, and goal-directed behavior are positioned as central to driving experience-dependent changes, especially when integrated into patient-centered therapy. In addition, we examine the intersection of individual difference factorsincluding personality and cognitive reservewith neuroplastic potential and propose frameworks for personalized rehabilitation. Finally, the chapter outlines emerging directions in tech-enabled plasticity interventions and translational models of care. Together, the evidence underscores neuroplasticity not only as a recovery mechanism but also as a target for strategic, evidence-based rehabilitation. The interdisciplinary approach adopted here aims to bridge neuroscience, clinical practice, and lived patient experiences to inform future research and therapeutic innovation. 2026 selection and editorial matter, K. Jayasankara Reddy; individual chapters, the contributors. All rights reserved. -
Neuroplasticity, Stress, and Resilience in the Mordern Workplace
Workplace stress profoundly impacts well- being, leading to burnout and low productivity despite traditional interventions. This chapter explores how neuroplasticity offers a solution for enhanced resilience. Chronic stress alters brain regions like the amygdala and prefrontal cortex, impairing decision- making and memory. Fortunately, processes like synaptic reorganization and neurogenesis enable brain recovery. Evidence- based interventions mindfulness, exercise, social support, and sleep hygienestrengthen stress tolerance. Workplace- level changes, including resilient leadership and ergonomics, also foster adaptability. Integrating neuroscience, psychology, and organizational behavior, this framework highlights neuroplasticity's role in building individual and organizational resilience, creating more adaptive and humane workplaces. 2026 by IGI Global Scientific Publishing. -
Neuropsychological functions and optimism levels in stroke patients: A cross-sectional study
Neuropsychological abnormalities, as well as behavioural and psychological characteristics, are being examined in patients in order to determine the prevalence of cognitive impairment and other neurovascular riskfactors, including prior strokes. The green light has been given by the institution's human ethics committee for this investigation. In order to conduct the study, the researchers used experimental clinical research techniques. Seventy-five stroke patients ranging in age from 20-70 were the focus of this study. All patients in the hospital had daily clinical examinations and were able to identify the underlying causes of their strokes. The NIMHANS Neuropsychological Battery was administered to all patients between one and six months after the onset of their stroke symptoms. 2023, IGI Global. All rights reserved. -
Neuroscience of social understanding
Comprehending human behavior and interactions requires an understanding of the social mind. Social cognitive neuroscience provides a lens to understand these complexities. This chapter explores the core brain mechanisms that control social conduct by exploring the field of social cognitive neuroscience. It examines aspects of social cognition, like the theory of mind, social perception, empathy, and decisionmaking. It explains how the brain helps navigate complex social contexts by looking at complex interactions between neurological processes and social behaviors. Important subjects include the function of the mirror neuron system, temporoparietal junction and prefrontal cortex in mediating social cognition. It discusses the implications of social cognitive neuroscience for understanding diseases such as schizophrenia and autism spectrum disorder, which are characterized by social deficiencies. Through this research, we learn about the social mind and its brain foundations, and it opens the door to novel interventions that improve interpersonal relationships and social well-being. 2024 by IGI Global. All rights reserved. -
NEUROSCIENTIFIC METHODS IN PRACTICE: Applications in Clinical Neuropsychology and Neuro-Forensic Psychology
This book presents an in-depth exploration of the convergence of neuroscience with clinical psychology, clinical neuropsychology, and forensic psychology, examining advanced methodologies, practical applications, and real-world case studies. K. Jayasankara Reddy provides a thorough examination of state-of-the-art neuroscientific methods and the revolutionary effects on both diagnosis and forensic inquiry. Reddy highlights the transformative impact of neuroimaging, neurophysiology, neuroelectrophysiology, and genetic analysis on our comprehension of brain function and behavior, using compelling case examples and empirical evidence. This book not only discusses methods but also critically examines ethical difficulties, merits, and challenges of the techniques, as well as the legal ramifications that may arise from the use of neuroscientific evidence in clinical and forensic settings. This book also highlights the need for a sophisticated comprehension of privacy issues, patient self-governance, and the use of neurobiological information within legal structures. Overall, it provides readers with the tools to negotiate complicated ethical landscapes while responsibly utilizing neuroscientific discoveries, advocating for a balanced approach that combines scientific rigor and ethical responsibility. This volume is an important resource for students, researchers, and practitioners of clinical neuropsychology, forensic psychology, and neuroscience. 2026 K. Jayasankara Reddy. -
NEUROSTIMULATION IN LONG COVID: Advancing Neurocognitive Rehabilitation and Recovery
Neurostimulation techniques are emerging as promising interventions for addressing neurocognitive impairments associated with Long COVID, including brain fog, fatigue, memory deficits and executive dysfunction. Non-invasive modalities such as transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) have demonstrated potential in modulating neural activity, enhancing cognitive recovery and alleviating neuroinflammatory processes linked to post-viral syndromes. Vagus nerve stimulation (VNS) and transcutaneous auricular VNS (taVNS) offer additional therapeutic avenues by targeting autonomic dysfunction, which is often implicated in Long COVID-related dysautonomia and cognitive fatigue. Neuromodulation approaches combined with neurofeedback and cognitive rehabilitation may optimise neuroplasticity and functional outcomes in affected individuals. Wearable neurostimulation devices and home-based therapies further improve accessibility, offering scalable solutions for post-COVID neurorehabilitation. However, challenges such as variability in patient response, optimal stimulation parameters and long-term efficacy require further investigation. Integrating neurostimulation into multidisciplinary rehabilitation frameworks that include cognitive training, exercise therapy and pharmacological support may enhance recovery trajectories. Future research should prioritise personalised stimulation protocols, biomarker-driven treatment strategies and longitudinal studies to establish evidence-based guidelines for neurostimulation in Long COVID. 2026 selection and editorial matter, K. Jayasankara Reddy; individual chapters, the contributors. All rights reserved. -
NEUROSYMBOLIC AI FOR CONTEXT-AWARE RESOURCE MANAGEMENT IN 5G SMART HEALTHCARE NETWORKS
Context-aware resource management in 5G Utilising neurosymbolic AI has growing impacts in the next-generation healthcare systems as smart healthcare networks to overcome the crucial issues of optimal service delivery and dynamic resource allocation. The 5G technology is adopted in healthcare networks for real-time processing, low latency, and high reliability that supports a vital application as telemedicine and remote patient monitoring. The resource management process of existing model rapidly fails in complicated, context-dependent situation with dynamic demands. To overcome these limitations, we proposed improved framework that combines a deep learning (DL) models for context extraction and symbolic reasoning process for decision-making. To determine the contextual patterns, the DL component analyses the multi-source data, as patient vitals, network conditions, and device status by utilising Transformer and Graph Neural Networks (GNNs). These data fed into symbolic reasoning module employ a knowledge graph and a rule-based system to dynamically allocate and distribute the resources based on the predetermined healthcare policies and requirements. Experimental results of this study showcase the improvements by attaining a reduction in latency, enhances in resource utilisation efficiency, and improved Quality of Service (QoS) for essential healthcare applications. In 5G-enabled smart healthcare systems, the results ensure a proposed model potential to transforms a resource management and ensure context-aware, versatile, and dependable service delivery for enhanced patient outcomes. 2025, Scibulcom Ltd.. All rights reserved. -
Neutron Polarization Observables in d(Formula Presented.)p at Low Energies of Interest to Astrophysics
A model-independent theoretical analysis of neutron polarization observables in (Formula Presented.) using circularly polarized photons at the range of energies of interest to Big Bang Nucleosynthesis is presented. An investigation of various spin dependent observables is carried out including the isoscalar multipole amplitudes M1s and E2s. It is suggested that the measurement of neutron polarization in the final state at near threshold energies will be very useful to assess the contribution of isoscalar amplitudes at range of energies of interest to BigBang Nucleosynthesis. 2022, The Author(s). -
New biomarkers for the detection of fetal death derived from large-scale proteomic analysis of maternal plasma
Background Normal pregnancy involves the modulation of thousands of maternal plasma proteins, and protein values not within the normal range may indicate the development of adverse pregnancy outcomes. A decrease in placental growth factor and an increase in soluble fms-like tyrosine kinase 1 in maternal plasma were shown to be associated with fetal death at the time of diagnosis and to predict this devastating pregnancy outcome at 24 to 28 weeks of gestation. However, these proteomic dysregulations are also present in other obstetrical syndromes, and more specific and sensitive biomarkers are needed to implement preventive strategies. Objective This study aimed to identify candidate protein biomarkers that can improve the prediction of fetal death relative to placental growth factor and soluble fms-like tyrosine kinase 1. Study Design This retrospective case-control study included 38 patients who experienced fetal death (cases) and 23 patients with uncomplicated pregnancies (controls). Plasma samples were collected at the time of diagnosis (2041 weeks of gestation) from cases and during routine care from gestational agematched controls. An aptamer-based multiplex assay was used to measure the abundance of >7000 protein analytes. Differential protein abundance was assessed using linear models with adjustment for gestational age at sample collection. Significance was inferred using a moderated t test adjusted P value of <.1 and a fold change of >1.25. Hypergeometric tests were performed to identify gene ontology biological processes enriched among proteins with significant changes in abundance. Random forest models were trained and evaluated via cross-validation to distinguish between fetal death cases and controls and to pinpoint the most salient predictors. Results Among the 7146 protein assays tested, 97 assays (1.4%) corresponding to 87 unique proteins differed significantly in abundance between fetal death cases and controls: 63 of 87 proteins (72%) were less abundant in fetal death cases, and 24 of 87 proteins (26%) were more abundant in fetal death cases. Dysregulated proteins were involved in pregnancy-related processes, such as angiogenesis and lactation. Random forest models effectively differentiated fetal death cases from controls, achieving an area under the receiver operating characteristic curve of 72% for the combination of placental growth factor and soluble fms-like tyrosine kinase 1, which increased to 86% when up to 50 additional proteins were included in the models (Delong test: P =.004). In addition, the point estimate of sensitivity increased from 53% to 74% (false-positive rate of approximately 10% for both). Glycoprotein hormones alpha chain (CGA), DnaJ homolog subfamily B member 9 (DNAJB9), and DNA-directed RNA polymerase III subunit RPC10 (POLR3K) emerged as the top 3 candidates to improve discrimination relative to placental growth factor and soluble fms-like tyrosine kinase 1. The significant proteomic changes in a subset of fetal death cases diagnosed first with preeclampsia relative to controls were highly correlated ( r =0.78; P <.001) with those reported in late preeclampsia cases leading to live births. On average, for each 2-fold change in protein abundance in late preeclampsia leading to live birth, there was an 8.6-fold change in preeclampsia leading to fetal death. Despite this overall correlation, transcobalamin 2, glucose-6-phosphate 1-dehydrogenase, and hepcidin, among others, demonstrated dysregulation only in preeclampsia leading to fetal death, suggesting both shared and distinct pathways perturbed in the 2 syndromes. Conclusion Our findings suggest that new maternal plasma proteins improve the discrimination of fetal death from controls relative to known biomarkers and that, although the signatures of fetal death and of preeclampsia are correlated, fetal death not only represents a much heightened disease state but also involves distinct perturbed pathways. Future studies are needed to determine whether the biomarkers can predict fetal death. 2026 Elsevier Inc.