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Controlling epileptic brain networks with computationally optimized weak electric fields

Periodic Reporting for period 3 - GALVANI (Controlling epileptic brain networks with computationally optimized weak electric fields)

Reporting period: 2023-06-01 to 2024-11-30

Epilepsy is a major brain disorder characterized by recurring and, most often, unpredictable seizures. In non-operable drug-resistant epilepsy (DRE), therapeutic procedures alternative to surgery are urgently needed. The Galvani project aims at developing, testing and validating innovative models and unconventional electrical stimulation methods (Figure 1). Reaching this ambitious goal requires a synergetic approach that brings together biomathematics (computational neurosciences), biophysics (bioelectromagnetism) and medicine (epileptology), uniting the passion and background of three experts and their teams (Rennes, Marseille and Barcelona).
A unique research strategy has been designed to address four major challenges:
1) Unravel the intricate relationship between neuromodulatory low-magnitude electric fields (E-fields) induced by transcranial current stimulation (tCS) and the resulting neurophysiological effects induced at the level of neurons, neuronal assemblies and larger scale networks;
2) Maximize the therapeutic effects of tCS-induced weak E-fields by targeting patient-specific epileptogenic networks (ENs) in order to reduce seizure occurrence;
3) Develop optimized personalized therapeutic protocols for novel repetitive non-invasive multichannel tCS devices;
4) Assess and validate optimized protocols in a cohort of patients in order to stratify patients and objectively define potential responders.
To achieve Galvani’s objectives, the research program consists of three research tracks (RTs). RT1 aims at understanding the impact of weak, persistent E-fields on brain activity and connectivity through the development of a novel class of hybrid brain models (HBMs) They are personalized in RT2 from patient data to investigate the therapeutic effects of optimized protocols. RT3 is devoted to clinical translation: 1) development of comprehensive advanced signal processing procedures to determine patient-specific ENs and 2) clinical assessment of personalized neuromodulation protocols.
RT1:
Developing, at the microscopic level (cellular), a novel realistic model of the human neocortical tissue and reproducing epileptiform events similar to those recorded in patients;
Developing, at the mesoscopic level (neural mass), a novel layered model for the human neocortex, reproducing and explaining the variety of interictal epileptic events;
Developing a mesoscale layered model, reproducing autonomous and realistic transitions from interictal to ictal state;
Quantifying the magnitude and spatial distribution of E-fields induced by intracranial stimulation.
RT2:
Generating a personalized stimulation montages for the two pilot studies PS-1 and PS-2;
Improving the biophysical modeling pipeline: development of a neural network for T1 processing, study of stereo electroencephalography (SEEG) burr-holes in head models;
Developing a laminar neural mass model (NMM) framework and integrating a physical model for the generation of physiological measurements;
Developing a software pipeline to create personalized models of seizure spread from SEEG, diffusion magnetic resonance imaging (dMRI) and clinical data, including a dMRI processing pipeline;
Studying single parcel stimulation in the personalized whole-brain models.
Developing a pipeline to optimize stimulation protocols;
Preparing the multicentric crossover general study GS-3: production of stimulation devices and accessories, protocol writing.
RT3:
Applying independent component analysis (ICA) on spikes and high-frequency oscillations (SEEG) to improve the definition of the epileptogenic zone (EZ) and surgical outcomes for epileptic patients;
Applying ICA and source localization to SEEG recordings, in cases of suboptimal electrode implantation, to improve diagnostic outcomes for epilepsy surgery;
Building PS-1 and PS-2 protocols, approvals, patient inclusions, data collection, monitoring and statistical analyses;
Extending PS-1 protocol for tDCS responders. One patient was included;
Studying functional connectivity (FC) changes in MEG in patients having tDCS (PS-1) and correlating with the prognosis;
Studying the influence of extent and depth of EZ on the effect of tDCS in PS-1 patients;
Evaluating changes in FC, spectral density and spike rate after applying tDCS or tACS during SEEG recording (PS-2);
Preparation of GS-3: the clinical investigation plan was written in collaboration with other partners, definition of data flow and patient follow-up. Approvals are still pending.
tCS is a rapidly developing technique of non-invasive brain stimulation. Its effects result from persistent, weak E-fields at low frequencies acting on neurons and neuronal circuitry. tCS is recognized for its applicability and safety in epileptic patients. However, it is not yet indicated as a standard treatment for non-surgical epilepsies. This situation results from the absence of a science-based strategy for defining target networks and protocols. Currently, stimulation parameters are empirically chosen based on safety considerations or clinical experience, without a strong rationale about how cortical excitability is altered by induced E-fields, network effects, and how these effects result in plastic changes.
Our ambition is to combine science, engineering and clinical research to disentangle the mechanisms of interaction of weak E-fields with brain networks and to develop novel non-invasive patient-specific therapeutic procedures.
Galvani's main objective is to improve the care of incurable epileptic patients, providing a personalized therapeutic solution based on non-invasive brain electrical neuromodulation. The inflection point is to achieve optimal control of seizures from a bottom-up, model-based, mechanistic understanding of dynamic weak E-fields effects on target large-scale brain networks.
Until the end of the project, expected results are two-fold. First, from a clinical viewpoint, we will better identify patients who are potential responders or non-responders to tDCS. Second, from a methodological viewpoint, we will show that the critical features of pathological epileptic networks can effectively be captured in personalized HBMs, developed to optimize non-invasively delivered E-fields of clinical value.
Figure illustrating the ERC project Galvani-Legend embedded in the figure
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