916 research outputs found
Correction to: When terminology hinders research: the colloquialisms of transitions of control in automated driving (Cognition, Technology & Work, (2022), 10.1007/s10111-022-00705-3)
No full textIn the original article, author affiliation published with error. The correct affiliations are: Davide Maggi—Institute for Transport Studies, Leeds, UK. Richard Romano—Institute for Transport Studies, Leeds, UK. Oliver Carsten—Institute for Transport Studies, Leeds, UK. Joost C. F. De Winter—Faculty of Mechanical, Maritime and Materials Engineering, Delft University of Technology, Delft, The Netherlands. The original article has been corrected.Human-Robot Interactio
Factors underlying the (heterogeneous) benefits from transcranial direct current stimulation in age-related cognitive decline
No full textEvidence for the contribution of pre-established semantic networks to stimulus-classification associations
No full textWatching clumsy robots : correlates of high-level error recognition in the human EEG
No full textSignatur: 2016-01 Welk
On the measurement and analysis of neuronal subpopulation activity
No full textOn a fine scale, the brain tissue is not composed of a homogeneous neuron assembly. Rather, it comprises a large number of diverse neuron types, which can express diverse functional properties. The goal of this work is to study the function of neuronal subpopulations in local microcircuits. Depending on the question at hand, several properties can be utilized to define neuronal subpopulations. Recently, motivated by the development of exciting experimental techniques, neural subtypes based on genetic markers have been intensely studied. Furthermore, subpopulations defined by their spatial distribution or based on morphological features are likely to be of relevance for neural computation. In order to understand the function of different subtypes, two tasks have to be accomplished: In the first step, the activity of the individual populations needs to be reliably measured. The second step is to analyze the activity in order to disentangle and understand the often complex and unintuitive interactions. In the first part of this thesis, we investigate the function of the layered populations in primary visual cortex. Our approach combines the physiologically based network model of Potjans and Diesmann (2014) with an informative input as proposed by Sadeh et al. (2014). Without any fine tuning of parameters, the model results in a realistic distribution of orientation selectivity over populations. By developing sophisticated mathematical analysis tools, we could directly relate this distribution to the underlying connectivity. Furthermore, our theory can be applied to the design of optogenetic stimulations for targeted manipulation of individual subpopulations.The second part of the thesis then tackles the question of how more detailed information about individual neurons can be extracted from modern multi-electrode array recordings. We developed two different approaches. The first method aims at reconstructing the full three-dimensional current source density from the two-dimensional extracellular action potential recording. Using compressed sensing techniques, we were able to recover the approximate current source distribution, thus also obtaining information about the location and--via the shape of the dentritic component--about the neuron type. The second method then focuses on neuronal localization and classification. Here, we took a novel approach which combines deep learning techniques with highly detailed compartmental simulations. We obtain accurate predictions for soma position and neuron class that outperform all existing methods. Furthermore, we validate the performance on a number of different datasets, including experimental ground truth data.In summary, by tackling the problem of data analysis of neuronal subtypes in combination with the analysis of their interactions, this work provides progress towards understanding the function of neuronal subpopulations
Analysis of calcium levels in brain tumour stem cells and characterisation of calcium role in ZBTB18 protein cleavage by calpain 2
No full textClassifying discriminative connections of whole brain effective connectivity inferred from autism brain imaging data
No full text
- …
