Activate Repair In StrokE

Introduction

The brain exhibits remarkable capacities to initiate self-repair mechanisms after brain injury as a prerequisite for the recovery of lost functions. ARISE will unveil fundamental, yet not understood principles of how brain repair mechanisms are orchestrated and how they can be further enhanced.

Research Challenges

Due to technical constraints, it was previously impossible to uncover:

1. How individual neurons rewire and reconnect after CNS injury.
2. Why some surviving neurons participate in repair processes and others do not.
3. How neuronal rewiring could be further stimulated to promote the restoration of impaired functions.

Technological Advances

But now, with technological advances at hand, I am in a unique position to tackle these major questions by examining causal relationships between neuronal rewiring and behavioral outcomes.

Methodology

I have recently developed a mouse model for vascular dementia that enables the monitoring of the same neurons in the hippocampus over several weeks under healthy conditions and after the induction of multiple microstrokes in relation to the spatial memory of the animal.

Using sophisticated closed-loop experiments, I will combine:

• Chronic 2-photon imaging in-vivo
• Optogenetics
• Machine learning

I will characterize neuronal recoding in relation to the behavioral performance of the animal.

Hypothesis

I hypothesize that principles of learning are key to understanding how surviving cells are recruited to participate in new neuronal ensembles to restore lost memory engrams. Using local light stimulation, I will manipulate surviving neurons to unveil their role in rewiring network dynamics and repair processes, and to enhance their engagement in restorative operations.

Goals of ARISE

With ARISE, I will establish a novel experimental pipeline to identify the cellular mechanisms of neuronal repair that are linked to distinct behavioral outcome parameters. This approach will also allow me to train generalized linear models (GLMs) to assess the efficiency and predict the outcome of novel restorative therapies in stroke.