Job ID: 119162

PhD Student: Classification of epileptic signals and its relation to navigational behavior in a virtual environment

Position: Ph.D. Student

Deadline: 30 June 2024

Employment Start Date: 1 October 2024

Contract Length: 3 years

City: Paris

Country: France

Institution: Sorbonne Université

Department: Neuroscience Paris Seine - IBPS

Description:

The objective of this thesis project is to assess the potential link between epileptic activity observed in intracerebral EEG and a navigation task performed in a virtual environment.

Epileptic patients with focal epilepsy starting in the hippocampus have memory problems, including difficulties in forming new memories [1]. In addition, studies have revealed a close relationship between the hippocampus, spatial representation, and navigation strategy, highlighting the importance of this brain region in navigation and spatial orientation [2, 3]. This project aims to investigate how epileptic activity (ictal discharges and interictal activity) affects or is modulated by navigation processes in order to better understand the links between epilepsy, memory and navigation.

First, the work will consist in analyzing intracranial electrophysiological recordings (sEEG) in patients implanted as part of a pre-surgical diagnosis in order to classify and quantify the different epileptic activities. In addition, microelectrodes implanted in the hippocampus allow to record action potentials and to isolate the activity of individual neurons by subsequent spike sorting. Thus, a first part of the work will be to characterize epileptic activity not only at the level of local field potentials, but also at the level of unit activity, using various algorithms, including machine learning methods (see [4]).

Second, we will investigate the relationship between epileptic activity and oculomotor and spatial orientation behavior recorded during a navigation task in a virtual environment. In each patient, we aim to correlate the occurrence of these different types of epileptic activity with specific trial-level behaviors (success, strategy choice) or on a finer time scale (e.g., changes in oculomotor activity, changes in speed in the virtual environment during a trial).

We will also seek to determine, at the patient group level, whether there are reproducible patterns linking specific types of epileptic activity (identified in terms of localization, frequency, power, duration, etc.) to specific types of behaviors or deficits. Given that a recent study has demonstrated an impact of sex on theta rhythm and spatial performance has been demonstrated in a recent study [5], we will specifically test the effect of sex on potential vulnerability to spatial orientation and navigation deficits in epilepsy.

Ultimately, this project aims to automatically identify different types of epileptic activity and behaviors associated with them. This could lead to the characterization of new behavioral indicators of the pathology and its evolution. Conversely, the detection of specific epileptic activities could help to predict certain deficits and improve patient care management.