As the global population ages, the number of patients with neurological and psychiatric diseases, such as Alzheimer’s disease (AD), Parkinson’s disease (PD), and mental disorders, is rapidly increasing. These conditions have an insidious onset and a progressive, irreversible clinical course, imposing an unbearable economic and social burden. Early detection and treatment can postpone disease progression, gaining more attention. Despite decades of extensive research into understanding these diseases, numerous challenges remain in both research and clinical practice.

The neurological and psychiatric diseases are accompanied by a loss of neuronal structure and function, which could be detected by non-invasive technology, such as magnetic resonance imaging (MRI), electroencephalogram (EEG), and magnetoencephalography (MEG). The large amount of data and individual variability make it difficult for clinical precision diagnosis. Additionally, due to the side effects of traditional medications, there have been numerous advancements in non-invasive neuromodulation techniques, including transcranial electric stimulation (TES), transcranial magnetic stimulation (TMS), and transcranial focused ultrasound stimulation (TFUS). However, each treatment involves different stimulation targets and strategies, and the mechanisms underlying their therapeutic effects remain unclear.

Identifying damaged neural circuitry at an early stage and developing individualized neuromodulation strategies remain crucial areas for exploration. Artificial intelligence (AI) is a valuable tool in data collection, disease diagnosis, monitoring processes, and prevention. AI can analyze vast amounts of patient information to detect subtle lesions and enhance the efficiency of neuromodulation. Consequently, further investigation is necessary to advance early diagnosis and neuromodulation in neurological and psychiatric diseases.

This research topic aims to cover studies on the early diagnosis of neurological and psychiatric diseases based on artificial intelligence and novel neuromodulation technologies.

We welcome submissions on, but not limited to, the following topics:

- Brain mechanism characterization of cognitive function or pathology

- AI applications on medical imaging data for the early detection or prediction of neurological and psychiatric diseases

- Novel algorithms in AI for improving early diagnosis and neuromodulation

- Mechanisms and applications of noninvasive neuromodulation technologies, such as TES, TMS, TFUS, and neurofeedback

- Target navigation and individualized parameter formulation

- Simulation and prediction of neuromodulation effect

This research topic is partnered with the 2024 18th International Conference on Complex Medical Engineering (CME2024) . Only papers presented at the conference are accepted for this topic and qualify for the publication fee discount. The CME2024 is set to take place in Kyoto, Japan, from November 8 to 10, 2024. Hosted by the Kyoto University and Institute of Complex Medical Engineering, the event provides a unique platform for academia and industry to exchange ideas and address challenges in optoelectronic medical instruments, brain information engineering, neurorehabilitation engineering and medicine, and communication technology.

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Frontiers in Aging Neuroscience

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