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Neural Application of Artificial Intelligence in Clinical Neuroscience
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Neural Application of Artificial Intelligence in Clinical Neuroscience

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Clinical Neurology".

Deadline for manuscript submissions: 30 May 2025 | Viewed by 542

Special Issue Editor

Dr. Saurabh J. Singhal

E-Mail Website
Guest Editor
Department of Neurology, WellSmart Health Neurology Clinic, Opelousas, LA 70570, USA
Interests: artificial intelligence (AI) and clinical neurology; chronic inflammatory demyelinating polyneuropathy (CIDP) and variants; stroke; endovascular; medically refractory epilepsy

Special Issue Information

Dear Colleagues,

Artificial Intelligence ( AI) is revolutionizing clinical neuroscience, enhancing diagnosis, treatment, and patient management.

* In neuroimaging, AI detects early signs of conditions like strokes, Alzheimer’s, and brain tumors by analyzing MRI, CT, and PET scans. AI also predicts outcomes for stroke recovery, seizures, and Parkinson’s progression, helping personalize treatment plans.

* Brain–computer interfaces (BCIs) powered by AI enable neuroprosthetics and communication devices for patients with severe motor impairments.

* In electroencephalogram ( EEG) and electromyography (EMG) analysis, AI automates the detection of abnormalities, improving diagnostic efficiency.

* Robotic surgery driven by AI assists in precision neurosurgery, including tumor resection and deep brain stimulation (DBS).

* AI also accelerates drug discovery for neurological conditions and enhances telemedicine by integrating with wearable devices for remote monitoring.

* In rehabilitation, AI adjusts therapies for stroke and cognitive recovery.

* Lastly, natural language processing (NLP) tools reduce administrative burdens by automating clinical documentation, allowing neurologists to focus more on patient care.

These applications of AI are rapidly transforming the field, leading to better diagnosis, personalized treatments, and improved patient outcomes.

With this Special Issue, we aim to encourage research submissions that further explore the current applications of AI in clinical neuroscience, as well as highlighting future research opportunities and emerging developments in the field.

Dr. Saurabh J. Singhal
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Clinical Medicine is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • artificial intelligence (AI)
  • clinical neuroscience
  • neuroimaging
  • brain–computer interfaces (BCIs)
  • neuroprosthetics
  • EEG/EMG analysis
  • robotic surgery
  • deep brain stimulation (DBS)
  • drug discovery
  • telemedicine
  • neurorehabilitation
  • stroke detection
  • Alzheimer’s disease
  • brain tumors
  • seizure prediction

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (1 paper)

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Research

11 pages, 4992 KiB  
Article
Deep Brain Stimulation Combined with NMDA Antagonist Therapy in the Treatment of Alzheimer’s Disease: In Silico Trials
by Dariusz Świetlik
J. Clin. Med. 2024, 13(24), 7759; https://doi.org/10.3390/jcm13247759 - 19 Dec 2024
Viewed by 292
Abstract
Background: Deep brain stimulation (DBS) is employed to adjust the activity of impaired brain circuits. The variability in clinical trial outcomes for treating Alzheimer’s disease with memantine is not yet fully understood. We conducted a randomized in silico study comparing virtual DBS [...] Read more.
Background: Deep brain stimulation (DBS) is employed to adjust the activity of impaired brain circuits. The variability in clinical trial outcomes for treating Alzheimer’s disease with memantine is not yet fully understood. We conducted a randomized in silico study comparing virtual DBS therapies with treatment involving an NMDA antagonist combined with DBS in patients with Alzheimer’s disease. Methods: Neural network models representing Alzheimer’s disease (AD) patients were randomly assigned to four groups: AD, memantine treatment, DBS, and DBS and memantine. Out of 100 unique neural networks created to model moderate and severe AD with varying hippocampal synaptic loss, 20 were randomly selected to represent AD patients. Virtual treatments—memantine, DBS, and DBS and memantine—were applied, resulting in a total of 80 simulations. Results: The normalized mean number of spikes in the CA1 region among the virtual AD hippocampi treated with memantine, DBS therapy, and DBS and memantine differed significantly (p < 0.0001). The normalized mean number of spikes in the virtual AD hippocampi was 0.33 (95% CI, 0.29–0.36) and was significantly lower compared to the number of spikes in the virtual AD hippocampi treated with memantine, which was 0.53 (95% CI, 0.48–0.59) (p = 0.0162), and in the DBS and memantine group, which was 0.67 (95% CI, 0.57–0.78) (p = 0.0001). Conclusions: Our simulation results indicate the effectiveness of virtual memantine and DBS therapy compared to memantine monotherapy for Alzheimer’s disease. Full article
(This article belongs to the Special Issue Neural Application of Artificial Intelligence in Clinical Neuroscience)
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Figure 1

Figure 1
<p>The DG-CA3-CA1 microcircuit of the hippocampal formation, involving the dentate gyrus (DG) region (<b>A</b>), CA3 (<b>B</b>), CA1 (<b>C</b>), and schematic of hippocampal structures including DG, CA3, and CA1: the modeling DBS therapy involved simulating oscillations in the perforant pathway from EC2 to the dentate gyrus and CA3 region, at a frequency of 40 Hz (<b>D</b>). Major cell types and their connections include the following: granule cells (G1–G8), Flow of information in the hippocampus from DG through CA3 to CA1, pyramidal cells (CA3 of P1–P16) and (CA1 of P1–P8), basket cells (B1–B6), O-LM1 and O-LM2 cells, mossy cells (MCs), and GABAergic cells (T1–T9) located in the medial septum-diagonal band (MS-DB). These GABAergic cells deliver disinhibitory inputs to hippocampal interneurons operating at theta rhythm. The dentate gyrus and CA3 region receive layer II (EC2) inputs from both the medial and lateral entorhinal cortex, which are radially organized. Meanwhile, principal neurons in the entorhinal cortex layer 3 (EC3) send direct projections to the CA1 field, synapsing with pyramidal neurons in the CA1 region. (<b>E</b>) Connections from EC2 to granule cells are shown at Ex1-Ex9, and for Ex1-Ex7, there are bursts of five action potentials (100 Hz) with inter-burst theta frequency at 8 Hz, shifted in phase between particular lines. On lines E × 8 and 9, there were no spikes or silent synapses. For experiments, DBS was added at 40 Hz.</p> Full article ">Figure 2
<p>Diagram illustrating the simulation of the hippocampal network. The AD group was randomized to one of three subgroups, where one received virtual memantine therapy, DBS therapy, and memantine and DBS therapy.</p> Full article ">Figure 3
<p>Analysis of simulations of normalized spikes CA1 (<b>A</b>), CA3 (<b>B</b>), and DG (<b>C</b>) (* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01). In the box-and-whisker plot, the top and bottom sides of the box are ±1.96 times the variable standard error. The horizontal line that splits the box in two is the mean. The box covers the mean ± 1.96 times the variable standard error.</p> Full article ">
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