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Brain Imaging

Brain Imaging

Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans), magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...

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Updated: May 5, 2026

Microdialysis of Excitatory Amino Acids During EEG Recordings in Freely Moving Rats

Microdialysis of Excitatory Amino Acids During EEG Recordings in Freely Moving Rats

Published on: November 8, 2018

Bioelectronic interface for real-time brain biomarker analysis.

Ankur Singh¹, Rashmita Priyadarshini Swain¹, Shubhranshu Shekhar Chaturvedi¹

¹Laboratory of Bio-Physio Sensors and Nano bioengineering, School of Biochemical Engineering, Indian Institute of Technology (BHU), Varanasi, Uttar Pradesh 221005, India.

Bioelectrochemistry (Amsterdam, Netherlands)

|February 21, 2026

Summary

This summary is machine-generated.

Advanced biosensing technologies enable real-time brain biomarker mapping to monitor neurological conditions. Integrating artificial intelligence/machine learning (AI/ML) with these biosensors promises precision neuromonitoring and intelligent neurotherapeutics for brain disorders.

Keywords:

Bioelectronic Interfaces Brain Biomarkers Neurochemical Sensing Real-Time In Vivo Biosensing, Point of care diagnosis, AI/ML in brain biomarker mapping

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Last Updated: May 5, 2026

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Area of Science:

Neuroscience
Biochemistry
Biomedical Engineering

Background:

The brain's dynamic chemical environment is vital for neural communication and coordination.
Fluctuations in brain chemistry are linked to neurological disorders like Parkinson's, Alzheimer's, epilepsy, and neuroinflammation.
Real-time monitoring of these biochemical changes is essential for understanding and managing brain conditions.

Purpose of the Study:

To review integrated biosensing technologies for brain biomarker mapping.
To discuss the role of biomarkers in diagnosing neurological diseases.
To explore the integration of AI/ML for advanced neuromonitoring and neurotherapeutics.

Main Methods:

Discussion of brain biochemistry fundamentals and their link to neuropathology.
Analysis of various biomarkers including neurotransmitters, protein-based markers, and immune markers.
Review of biosensor design, signal transduction, and in vivo system integration.

Main Results:

Integrated biosensing technologies offer promising solutions for real-time brain biomarker mapping.
AI/ML integration can enhance precision neuromonitoring and enable intelligent neurotherapeutics.
These advancements bridge molecular neurochemistry with digital health for improved brain disorder management.

Conclusions:

Integrated biosensing technologies are crucial for real-time monitoring of brain chemistry.
The synergy of biosensors and AI/ML holds potential for revolutionizing the diagnosis and treatment of brain disorders.
This approach redefines the landscape of digital health for complex neurological conditions.