Evidence map›Paper›PMID 42145878›Full record

ArticleProceedings of the ... American Control Conference. American Control Conference2025

Proportional-Integral Controller-Based Deep Brain Stimulation Strategy for Controlling Excitatory-Inhibitory Network Synchronization.

Aanuoluwapo V Olumuyiwa, Gautam Kumar

Abstract read
In one paragraph

Article in Proceedings of the ... American Control Conference. American Control Conference, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Aanuoluwapo V OlumuyiwaDepartment of Chemical and Materials Engineering, San Jose State University, CA 95192, U.S.A.
Gautam KumarDepartment of Chemical and Materials Engineering, San Jose State University, CA 95192, U.S.A.

Funding

Closed-Loop Deep Brain Stimulation for Controlling Abnormal Neural Synchronization and OscillationsR16NS140310 · NINDS · SAN JOSE STATE UNIVERSITY · PI Gautam Kumar · 2024 to 2026
$440k
NINDS NIH HHS R16 NS140310
6 · The paper itself

Abstract

Deep brain stimulation (DBS) has emerged as a potential therapy for disrupting pathological synchronous firing patterns of neurons and restoring healthy oscillations in many brain disorders when pharmacological interventions fail. However, existing DBS devices require extensive clinical interventions in tuning stimulation parameters over the treatment period. In our previous works, we developed a novel neurostimulation motif, referred to as "Forced Temporal Spike-Time Stimulation" (FTSTS), which can reliably and robustly desynchronize the excessively synchronized excitatory-inhibitory (E-I) networks by harnessing E-to-I synaptic plasticity. However, our FTSTS protocol was an open loop and required us to manually titrate the FTSTS parameters, such as amplitude, frequency, and pulse width. In this work, we close the DBS loop by developing a proportional-integral (PI) controller-based FTSTS strategy to tune the stimulation amplitude. Using an E-I network model, we perform the spectral analysis of spiking data to determine the correlation between the network synchrony and the mean population firing rate of E and I neurons. We systematically investigate the stimulation parameter space to investigate the effects of amplitude and frequency on the mean firing rate of E and I neurons. We design a PI controller to tune the stimulation amplitude using the mean firing rate of I neurons as a feedback signal. We demonstrate the feasibility of our approach in controlling the neuronal synchronization in the E-I network consisting of 400 E and 100 I neurons through various case studies.

Identifiers

PMID42145878
PMCPMC13179481

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.