Pascal Helson
About me
I am currently a post doctoral researcher at KTH Royal Institute of Technology in Stockholm within the NeuroLogic group of Arvind Kumar.
My academic career were guided by the ambition to do research in mathematics applied to biology. First, I had the opportunity to go to a Maths and Physics preparatory school at Lycée Masséna in Nice, France. Then, I went to the engineering school of Mines de Saint Etienne where I could learn more about Biology, Mathematics and Computational languages. Finally, I went to École des Ponts et Chaussées where I did the Master ANEDP of University Paris 6 (UPMC).
I did my PhD at Inria Sophia-Antipolis in the TOSCA and MathNeuro teams under the supervision of Etienne Tanré and Romain Veltz. My PhD focuses on modelling and analysing (mathematically and numerically) neural networks in which neurons interact through plastic synaptic weights. Analysing rigorously the coupled dynamics (of neurons and synapses) is a non trivial task. In order to overcome this difficulty, I use probabilistic tools to simplify such complex models : at the mesoscopic scale, I make a time-scale separation when there is some biological time-scale differences (synaptic plasticity much slower than the neurons dynamics for example) and at the macroscopic scale, I did a mean field analysis when the network considered possesses a large number of neurons.
My post doctoral research project is part of the dBRAIN project and under the supervision of Arvind Kumar. I am interested in Parkinson’s disease and in particular how brain imaging/activity can give us new insights in PD by analysing them with a modelling perspective.
Mail : pashel@kth.se
Thesis : Plasticity in networks of spiking neurons in interaction, defended (slides in French) on March 29th, 2021.
4. Structural constraints on the emergence of oscillations in multi-population neural networks (with Jie Zang and Arvind Kumar)
eLife (March 2024). arXiv
3. Cortex-wide topography of 1/f-exponent in Parkinson’s disease (with Per Svenningsson, Daniel Lundqvist, Mikkel Vinding and Arvind Kumar)
npj Parkinson's Disease (July 2023). arXiv
2. A Mathematical Analysis of Memory Lifetime in a Simple Network Model of Memory
Neural Computation (July 2020). arXiv, HAL
1. A new STDP Rule in a neural Network Model (with Etienne Tanré and Romain Veltz)
Talks
INRIA Sophia-Antipolis PhD Seminar (2017) : Spike-Timing Dependent Plasticity (STDP) models or how to understand memory
CNOD 2017 : A simple spiking neuron model based on stochastic STDP
Second year PhD Colloquium EDSFA (2018) : A Mathematical approach on memory capacity of simple synapses models
Neuromod Seminar (2020) : A Mathematical approach on memory capacity of simple synapses models
CCNSv2 (2021) : A new stochastic STDP Rule in a neural Network Model
ICMNS (2021) : Slow-fast and long time behaviour analysis of a neural network with stochastic STDP
GdR ISIS meeting (2022) : Estimating the brain-wide distribution of excitation-inhibition balance in Parkinson's disease
Dive deep - Digital Futures (2023): Cortex-wide topography of 1/f-exponent in Parkinson’s disease
WINQ workshop (2024) : Graph signal processing to get insights into Parkinson’s disease
MEG Nord (2024) : Graph signal processing on MEG for Parkinson’s disease (NATMEG) + Aperiodic activity in MEG-DBS from PD patients (CFIN)
ICTP Workshop (2024, Simons foundation travel grant): Mean Field Analysis of a Stochastic STDP model
ICMNS (2024) : Mean Field Analysis of a Stochastic STDP model
Posters
ICMNS 2017 : A simple spiking neuron model based on stochastic STDP
ICMNS 2018 : A mathematical approach on memory capacity of a simple synapses model
ICMNS 2019 : A Mathematical Analysis of Memory Lifetime in a simple Network model of Memory
MEG Nord 2023 : Cortex-wide excitation/inhibition topography in Parkinson’s disease
Neural Traces 2024 : Integration and segregation analysis of resting-state MEG in Parkinson’s Disease
MEG Nord 2024 : On the neural dynamics role of excitation-inhibition (EI) balance in Parkinson's disease
Workshops (organiser)
BrainNet 2023: video recordings on youtube !
Interpretable Brain Data (IBD) 2023: video recordings on youtube!
BrainNet+ 2024: video recordings on youtube !
Collaborations
MEG-DBS and LFP-DBS: Andreas Højlund (CFIN, Aarhus University, Denmark) and Erik Johnsen (Aarhus University Hospital). Two projects started thanks to respectively the Nordic MEG Hub Mobility Grant and Parkinson Fonden Travel Grant. The first project is on the DBS effects on MEG aperiodic activity in Parkinson’s disease, and the second on the aperiodic activity in LFPs recorded during STN-DBS surgery.
Mean field for networks with STDP: Quentin Cormier (Inria de Saclay) and Milica Tomasevic (École polytechnique). We study the mathematical foundations for proposing a mean field approximation of models of neuronal network with STDP. More info here.