Research and Reviews: A Journal of Neuroscience

Latest articles

• Published Subscription Review Article 31 Aug 2026

  Artificial Intelligence for Tracking Cognitive Deviation in Aging Populations: A Comprehensive Review of Techniques, Challenges, and Ethical Concerns

  By Dipali Prakash Patil

  Abstract: Population aging is accelerating worldwide, and with it the burden of cognitive health conditions such as mild cognitive impairment (MCI), Alzheimer’s disease (AD), and dementia. Detecting and monitoring cognitive change early is central to timely intervention, yet conventional diagnostic tools often miss the subtle signals that appear before overt symptoms. Artificial intelligence (AI) has emerged as a promising complement to clinical assessment because it can work through high-dimensional data and …

  Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 · pp. 27–37 Read article →

• Published Subscription Original Research 31 Aug 2026

  Machine Learning Approach to Detect and Analyze Attention-Deficit/Hyperactivity Disorder

  By Amit Gaikwad, Abhaykumar Vasanta Adole

  Abstract: Attention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder characterized by difficulties with attention, impulse control, behavioral regulation, and daily functioning that persist across childhood and adulthood. Clinical diagnosis is predominantly based on behavioral assessments and expert interpretation, which may result in subjectivity and delayed clinical decisions. To reduce reliance on subjective evaluation, this study introduces an automated ADHD identification framework that integrates resting-state functional Magnetic Resonance Imaging (rs-fMRI) with advanced machine …

  Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 · pp. 22–26 Read article →

• Published Subscription Original Research 31 Aug 2026

  Comparative Study of Handwriting in Sitting as Well as Standing Position

  By Aatika Mansoori, Abhaya Bhople, Samruddhi Patha, Aaifaz Pappuwale

  Abstract: Handwriting is a complex motor activity influenced by posture, muscle coordination, balance, and environmental conditions. Handwriting analysis is very important in forensic science to determine authenticity of documents in various criminal cases. This comparative study examines the characteristics of handwriting produced in sitting and standing positions to determine the effect of body posture on writing performance and handwriting quality. The study focuses on parameters such as letter formation, alignment, spacing, …

  Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 · pp. 15–21 Read article →

• Published Subscription Original Research 31 Aug 2026

  Brain Stroke Detection Using Deep Learning and Grad-CAM Explainability Framework

  By Vibhav Dadhich, Shruti Mathur, Dimpal Sharma

  Abstract: Seconds matter when a brain stroke occurs; it is a race against time where rapid, precise intervention is the only way to preserve a patient’s quality of life. This research introduces a deep learning framework designed to act as a vital ally for clinicians, providing automated, high-speed stroke detection through brain MRI analysis. At the heart of our approach is EfficientNetB0, a sophisticated neural network chosen for its ability to …

  Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 · pp. 8–14 Read article →

• Published Subscription Review Article 4 May 2026

  The Early Brain Hemorrhage Prediction System Using Machine Learning

  By Rohan Srivastava, Swapnil Srivastava, Ram Bhushan, Archana Dwivedi

  Abstract: Brain hemorrhage is a critical medical emergency that requires immediate attention, as delays in diagnosis can result in severe neurological damage or death. The condition involves bleeding within or around brain tissues, leading to increased intracranial pressure and disruption of normal brain function. Although imaging techniques such as CT scans and MRI provide accurate diagnosis, their availability is limited in emergency and rural settings. In recent years, machine learning has …

  Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 Read article →

• Published Subscription Review Article 15 Apr 2026

  Nutrient–Xenobiotic Crosstalk in Dairy Cattle: Implications for Metabolism, Immunity, Health, and Productivity in Resilient Dairy Development

  By Md. Emran Hossain

  Abstract: Dairy cattle are routinely exposed to a wide range of xenobiotics, including mycotoxins, heavy metals, pesticides, residues from veterinary drugs, and plant secondary metabolites, through feed, water, and environmental sources. These xenobiotics, being foreign to biological systems, can interfere with the absorption, metabolism, and utilization of essential nutrients, while also compromising immune function, organ health, and overall physiological performance. Chronic or subclinical exposure can reduce feed efficiency, disrupt energy and …

  Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 37–46 Read article →

• Published Subscription Review Article 19 Mar 2026

  Neural Implants & Brain–Computer Interfaces: Enhancing Human Intelligence or Violating Free Will?

  By Shreeya Sampada Nayak, Vansh, Tushar, Yogesh Pilwan, Jyoti Kumari

  Abstract: The integration of neural implants with artificial intelligence creates opportunities to develop new implants and enhance current nanotechnologies. Although these advances hold significant potential for restoring neurological functions, they also introduce important ethical concerns. The rapid advancements in neural implants and brain–computer interfaces [BCIs] are revolutionizing human cognition, enabling enhanced intelligence, communication, and even thought-driven control of external devices. Although these technologies offer great promise in enhancing human abilities, they …

  Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 13–18 Read article →

• Published Subscription Review Article 19 Mar 2026

  Early Alzheimer’s Disease Prediction Using Vision Transformers and Attention-Guided MRI Analysis

  By Altaf O. Mulani

  Abstract: Alzheimer’s Disease (AD) continues to be a major global health concern, with early detection being crucial for effective intervention. While conventional machine learning and convolutional neural network (CNN) approaches have made notable progress in automated AD diagnosis using MRI data, they often struggle with capturing long-range dependencies and maintaining spatial contextual awareness. In this research, we propose a novel framework using Vision Transformers (ViTs) for early Alzheimer’s prediction from 3D …

  Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 30–40 Read article →

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