Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

 
Session Overview
Session
MS199, part 2: Applications of topology in neuroscience
Time:
Saturday, 13/Jul/2019:
3:00pm - 5:00pm

Location: Unitobler, F-105
53 seats, 70m^2

Presentations
3:00pm - 5:00pm

Applications of topology in neuroscience

Chair(s): Kathryn Hess Bellwald (Laboratory for topology and neuroscience, EPFL, Switzerland), Ran Levi (University of Aberdeen, UK)

Research at the interface of topology and neuroscience is growing rapidly and has produced many remarkable results in the past five years. In this minisymposium, speakers will present a wide and exciting array of current applications of topology in neuroscience, including classification and synthesis of neuron morphologies, analysis of synaptic plasticity, and diagnosis of traumatic brain injuries.

 

(25 minutes for each presentation, including questions, followed by a 5-minute break; in case of x<4 talks, the first x slots are used unless indicated otherwise)

 

Simplicial convolutional neural networks for in-painting of cochains

Gard Spreemann
Laboratory for topology and neuroscience, EPFL, Switzerland

We use the simplicial Laplacian to define convolutional neural networks over simplicial complexes in a way that naturally generalizes classical CNNs. This provides us with the tools to build networks that perform in-painting of simplicial cochains while respecting the underlying topological structure. This is joint work with Stefania Ebli and Michaël Defferrard.

 

Using topological data analysis to classify certain stimuli in the Blue Brain reconstruction

Jason Smith
University of Abedeen , UK

The Blue Brain Project's digital reconstruction of a rat's neocortical column allows us to study the effect of certain stimuli on the brain. The insertion of a stimulus into the model causes information to propagate through the column, creating activity patterns that are not well understood. Using techniques from applied topology and combinatorics we attempt to characterise the firing patterns of different stimuli. Using this characterisation we then apply the methods to an unknown sequence of stimuli of the same type and attempt a classification of those stimuli.

 

Topology and neuroscience

Daniela Egas Santander
Laboratory for topology and neuroscience, EPFL, Switzerland

I will present some of the applications of topology and topological data analysis to neuroscience through an exploration of the collaboration between the applied topology group at EPFL and the Blue Brain Project. In particular, I will describe how we are using topology to further understand learning or simulations of voltage sensitive dye experiments.

 

Application of topological data analysis to the detection of mild cognitive impairment

Alice Patania
Indiana University

Identifying subjects with cognitive deficits as early as possible is critical in pursuing treatments for Alzheimer’s Disease. However, in the mildly symptomatic stages, pathological brain atrophy can be subtle and overpowered in signal by aging. Applying persistent homology, we are able to build coarse descriptors of the overall cortical thickness of each subject and isolate atrophy features that are indicative of MCI. These 0- and 1-persistence features can be used to build integrated persistent homological kernels which retain the meaningful homological information of brain atrophy. Using a support vector machine approach, we show how building a coarse descriptor of the cortical topology improves discriminative power of whole brain atrophy biomarkers at the MCI stage and homological features prove useful in identifying individuals with early stages of cognitive impairment.