Appears in collection : 2022 - T1 - WS2 - Mathematical modeling and statistical analysis in neuroscience

A multi-disciplinary approach in understanding the functions mediated by synapses will reveal information at a multi-scale level from sub-cellular events to large scale network activity. This will result in better holistic understanding of the principles by which synapses orchestrate information flow in the brain, both in health and in pathological states. This is one of the greatest challenges in neuroscience which involves overcoming two key aspects: on the one hand, the heterogeneity of the brain, for example, the different receptor types, their morphological structure and on the other hand overcoming the temporal and spatial scales. Our study attempts to take these challenges to the forefront, by combining a number of techniques, including:

i) Intracellular whole-cell recording, a specialised electrophysiological technique which involves simultaneously recording two neurons that are synaptically connected, thus allowing the investigation and manipulation of the chemical or electrical communication between neurons;

ii) Biocytin and dual immunofluorescence labelling that enables the identification of the neurons recorded;

iii) Incorporation of our current understanding of the biomolecular machinery, which regulates exocytosis, the process enabling neurotransmitters to be released;

iv) Mathematical multi-scale modelling that bridges the gap between protein and electrical activity enabling the synthesis of the aforementioned empirical observations.

This multi-disciplinary approach sheds new light onto how the synaptic molecular machinery fine tunes cellular processes of neurotransmitter release. For example, we have derived a novel invariant mathematical principle, which we coined Activity Induced Transcritical Canards, which we hypothesize will lead to a better understanding of pathological cellular mechanisms of Alzheimer’s disease.

This is joint work with Serafim Rodrigues (Ikerbasque, BCAM, Bilbao, Spain).