# PREDICTIVE MODELING OF BIOELECTRIC ACTIVITY ON MAMMALIAN MULTILAYERED NEURONAL STRUCTURES IN THE PRESENCE OF SUPRAPHYSIOLOGICAL ELECTRIC FIELDS

> **NIH NIH U01** · UNIVERSITY OF SOUTHERN CALIFORNIA · 2021 · $637,210

## Abstract

Project Abstract
The end goal of this multiscale modeling research is to bridge the gap existing between three-dimensional, full-
wave, macro-modeling of electrical and magnetic biointeractions (global modeling) and cellular-level modeling
strategies. Our research team is composed of engineers and neuroscientists that are experts in all
computational and experimental aspects necessary to fill the existing gaps in multi-scale modeling.
This multi-university effort to predict spatio-temporal distributions of active neurons based on current densities
created by multi-electrode electrical stimulation depends on having a set of "core models" of molecular
(receptor-channel kinetics), synaptic, neuron, and multi-neuron activity. These models and their inputs and
outputs must be integrated into a global model of the extracellular media/matrix including relevant multi-
electrode arrays. Successful modeling at these levels will allow hypotheses about space-time patterns of
electrical stimulation to produce predictions about the number and distribution of activated inputs (based on
known spatial distributions of afferent axons). The linked molecular, synaptic, neuron, multi-neuron, and global
model will provide the basis for emerging predictions of the spatio-temporal distribution of active neurons and
thus, the spatio-temporal distributions of spike train activity that encode all information in the nervous system.
Further, we believe the proposed multiscale modeling framework constitutes an ideal platform capable of
generating novel insights into the pathogenic mechanisms precipitating abnormal hippocampal function.
Although the proposed research is focused on the hippocampal system, our effort will capitalize on our
multiscale modeling accomplishments during the performance period of our original multiscale modeling U01
grant, in the realm of both retinal and cortical prostheses.

## Key facts

- **NIH application ID:** 10242065
- **Project number:** 5U01EB025830-09
- **Recipient organization:** UNIVERSITY OF SOUTHERN CALIFORNIA
- **Principal Investigator:** THEODORE W. BERGER
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $637,210
- **Award type:** 5
- **Project period:** 2012-09-15 → 2024-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10242065

## Citation

> US National Institutes of Health, RePORTER application 10242065, PREDICTIVE MODELING OF BIOELECTRIC ACTIVITY ON MAMMALIAN MULTILAYERED NEURONAL STRUCTURES IN THE PRESENCE OF SUPRAPHYSIOLOGICAL ELECTRIC FIELDS (5U01EB025830-09). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10242065. Licensed CC0.

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