Neocortical representation of tactile primitives
ESR 1
Objectives
Any skin-object interaction will obey the laws of contact mechanics and can therefore be decomposed into many haptic input features or unique dimensions of input. These vector components are encoded in a population of skin sensors (i.e. taxels in robotic terms), and in their first central processing in the neurons of the cuneate nucleus. This project will explore the representation of the haptic input features in the neocortical neurons in vivo. A secondment at Actronika will help develop miniaturized haptic displays adaptable to different animal species that can stimulate local skin for specific haptic input features in isolation.
Expected Results
Exploration of haptic input features representation in neocortical neurons.
Placement
Host institution: Lunds Universitet
Enrolments (in Doctoral degree): Lunds Universitet
Supervisors
Henrik Jörntell, Vincent Hayward
ESR 1: Kaan Kesgin
PhD defense: October 1st 2024
Abstract of PhD Goals
The goal of the PhD thesis entails characterization of the neocortical representation of haptic input features. Sub-components for this work include exploring more naturalistic mechanical stimulators with capacity for highly dynamic modulation, followed by establishing high fidelity representations of physical skin interface under haptic interactions through high-speed imaging tools. These representations then need to be observed with population wide cortical recordings which involve exploring novel acquisition methods with high-spatial-temporal resolution. These acquired signals need to be supplemented by novel signal processing tools so ‘unmix’ the highly rich and superposed individual neuronal activities only then to be decoded with novel mathematical tools for accurate correlation of the skin-cortex relationship.
Results
Learning the multiple, parallel in vivo whole cell patch clamp recording technique in the neocortex of the rat. Exploring the representation of haptic input features in neocortical neurons. Tuning properties of neocortical neurons with respect to the haptic input features representation of haptic input features across a population of cortical neurons.
Journal Article – Upcoming
Kesgin, K.; Jörntell, H.
Singular superlet transform achieves markedly improved time-frequency super-resolution for separating complex neural signals
DOI: https://doi.org/10.1101/2023.02.27.530211
Journal Article – Upcoming
Kristensen, S.; Kesgin, K.; Jörntell, H.
High-dimensional cortical signals reveal rich bimodal and working memory-like representations among S1 neuron populations
DOI: https://doi.org/10.1101/2024.01.26.577171