International Journal of Brain Sciences

Latest articles

• Published Subscription Original Research 30 Oct 2026

  AI-Driven IoT-Based Decision-Making System for Brainwave Study: The KSK Approach

  By Kazi Kutubuddin Sayyad Liyakat, Kaustubh Subhash Mangrulkar

  Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain–computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …

  Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 · pp. 28–35 Read article →

• Published Subscription Research Article 20 Jul 2026

  Deep Learning-Based Detection and Classification of Brain Tumors Using MRI Images

  By Shubhra Chinchmalatpure, Pratiksha Chafle

  Abstract: Brain tumor detection using magnetic resonance imaging (MRI) is a critical task in the early detection and treatment of brain tumors. Manual analysis of brain tumor detection using MRI is a tedious task that requires expertise in the field. Therefore, this study proposes a deep learning-based approach for brain tumor detection and classification using Convolutional Neural Networks (CNN). The proposed approach preprocesses the MRI image using normalization, resizing, and noise …

  Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 · pp. 36–44 Read article →

• Published Subscription Original Research 20 Jul 2026

  A Review of Various Deep Learning Models for Classification of BrainTumor

  By Bhanu Bhushan Parashar, Munesh Chandra, Ashim Saha

  Abstract: Brain Tumor is most challenging and life threading decease now these days. Timely accurately detection of brain tumor is play important role for patient health improvement and it increase life survival rate. Traditional of brain tumor detection relay heavily on manual interpretation of medicalimage, it is very time consuming and chance to human error in detection of brain tumor. Now in recent advancement of Artificial intelligence (AI), Machine learning (ML) …

  Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article →

• Published Subscription Review Article 27 Jun 2026

  Deep Learning Based Detection and Classification of Brain Tumors Using MRI Images

  By Shubhra Chinchmalatpure, Pratiksha Chafle

  Abstract: Brain tumor detection using magnetic resonance imaging (MRI) is a critical task in the early detection and treatment of brain tumors. Manual analysis of brain tumor detection using MRI is a tedious task that requires expertise in the field. Therefore, this study proposes a deep learning-based approach for brain tumor detection and classification using Convolutional Neural Networks (CNN). The proposed approach preprocesses the MRI image using normalization, resizing, and noise …

  Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article →

• Published Subscription Review Article 25 Jun 2026

  Artificial Intelligence in Early Diagnosis and Personalized Treatment of Alzheimer’s Disease

  By Rohit Saroha, Chetna Chhabra, Abhishek Kumar, Gauri Mudgal

  Abstract: Artificial intelligence (AI) has become a disruptive technology in the medical care industry, with potential solutions to early diagnosis and customized treatment of Alzheimer’s disease (AD), a progressive neurodegenerative disease and the most prevalent cause of dementia globally. Conventional diagnostic techniques, such as cognitive, neuroimaging and biomarker techniques, are usually limited in the ability to detect disease at its most susceptible stage when treatment interventions are most effective. The recent …

  Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 · pp. 15–27 Read article →

• Published Subscription Review Article 30 May 2026

  AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study

  By Kazi Kutubuddin Sayyad Liyakat, Kaustubh Subhash Mangrulkar

  Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …

  Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article →

• Published Subscription Review Article 20 May 2026

  Circadian Regulation of Lipid Peroxidation in the Brain: Linking Ferroptosis to Neurodegenerative Vulnerability

  By Suraj Sen, Anit Jha, Rajeev Ratan, Neeraj Yadav, Ayush Bhardwaj

  Abstract: The human brain operates through highly coordinated physiological and biochemical processes that regulate cognition, behavior, and neural adaptability. Central to these processes are mechanisms governing brain function, neurophysiology, and neuroplasticity, which are increasingly recognized to be influenced by circadian rhythms. Recent advances in cognitive neuroscience, neuroimaging, and behavioral neuroscience have revealed that disruptions in circadian regulation can significantly impact oxidative balance within the brain, particularly through enhanced lipid peroxidation. Lipid …

  Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 · pp. 1–14 Read article →

• Published Subscription Original Research 11 Feb 2026

  Plant-Derived Psychotropic Agents Targeting Neurotransmitter Systems: Pharmacognostic Evidence, Mechanisms, and Clinical Relevance

  By Nicky Jaiswal, Kabhi Khanna, Shah Samreen, Km Priyanka Singh, Rifat Siraj

  Abstract: Psychiatric health problems are also a large burden on global health and existing psychotropic drugs may be restricted by relative effectiveness, side effects, and inadequate long-term tolerability. Plant- based psychotropic agents have subsequently been the focus of interest in the form of complementary or alternative therapies. This review outlines the pharmacognostic, mechanisms of action and therapeutic importance of plant-based psychotropic agents against central neurotransmitter systems. The traditional medicinal practices give …

  Published in International Journal of Brain Sciences · Vol. 3, Issue 1, 2026 · pp. 34–42 Read article →

All 34 articles in this journal →