Laboratory of Neuroinformatics

Head: Daniel Wójcik

Staff: Hanuma Chaitanya Chintaluri, Michał Czerwiński, Helena Głąbska, Tomasz Górski, Jakub Kowalski, Szymon Łęski, Piotr Majka, Anna Samsel

Research profile:

The main activity of the group is development of tools and models, and putting them to use to understand neural processing of sensory information. We focus on functioning of early levels of sensory systems, in particular thalamo- cortical loop, but we also study the extrageniculate pathway of the visual system and recently started to look at motor systems. Our main interests are in electrophysiology but we also analyze behavioral data. An important part of our activity is the development of a neuroinformatics infrastructure for storage and processing of histological information and the creation of histology-based 3D brain atlases from different input sources (http://www.3dbar.org/).
More information about Laboratory on the web page: https://neuroinflab.wordpress.com


Methods

• standard statistical frameworks
• nonlinear techniques and machine learning
• Matlab for most data analysis
• open software (Linux, Python, Neuron, VTK, Plone)

Current research activities

• development of methods to reconstruct Current Source Density reliably in different experimental settings from local field potentials
• information processing in the cortico-thalamic part of the rat’s somatosensory system, modeling and analysis of local field potentials
• the role of extrageniculate visual pathway in movement perception, modeling and analysis of spiking activity
• development of databases to store digital representations of histology data and tools for creation of histology-based 3D brain atlases

Selected publications

P. Majka, E. Kublik, G. Furga, D. K. Wójcik. Common Atlas Format and 3D Brain Atlas Reconstructor, the infrastructure for constructing 3D brain atlases. Neuroinformatics 10 (2012) doi: 10.1007/s12021-011-9138-6

J. Potworowski, W. Jakuczun, S. Łęski, D. K. Wójcik. Kernel Current Source Density Method. Neural Computation 24 (2012) 541-575.

A. Kiryk, G. Mochol, R. K. Filipkowski, M. Wawrzyniak, V. Lioudyno, E. Knapska, T. Gorkiewicz, M. Balcerzyk, S. Łęski, F. Van Leuven, H. P. Lipp, D. K Wójcik, L. Kaczmarek. Cognitive abilities of Alzheimer’s disease transgenic mice are modulated by social context and circadian rhythm. Current Alzheimer Research 8 (2011) 883-892

S. Łęski, K. H. Pettersen, B. Tunstall, G. T. Einevoll, J. Gigg, D. K. Wójcik. Inverse Current Source Density method in two dimensions: Inferring neural activation from multielectrode recordings. Neuroinformatics 9 (2011) 401-425

M. J. Hunt, M. Falinska, S. Łęski, D. K. Wójcik, S. Kasicki. Differential effects produced by ketamine on oscillatory activity recorded in the rat hippocampus and nucleus accumbens" Journal of Psychopharmacology 25 (2011) 808-821

S. Łęski, E. Kublik, D. A. Świejkowski, A. Wróbel, D. K. Wójcik. Extracting meaningful components of neural dynamics with ICA and iCSD. J. Comput. Neurosci. 29 (2010) 459–473

A. Sobolewski, E. Kublik, D. A. Świejkowski, S. Łęski, J. K. Kamiński, A. Wróbel Cross-trial correlation analysis of evoked potentials reveals arousal related attenuation of thalamo-cortical coupling. Journal of Computational Neuroscience, 29 (2010) 485-493

G. Mochol, D. K. Wójcik, M. Wypych, A. Wróbel, W. J. Waleszczyk. Variability of visual responses of the superior colliculus neurons corresponds to their velocity preferences. J. Neurosci. 30 (2010) 3199-3209

D. K. Wójcik, S. Łęski Current source density reconstruction from incomplete data, Neural Computation 22 (2010) 48-60

D. K. Wójcik, G. Mochol, W. Jakuczun, M. Wypych, W. Waleszczyk Direct estimation of inhomogeneous Markov interval models of spike-trains, Neural Computation 21 (2009) 2105-2113

S. Łęski, D. K. Wójcik. Inferring coupling strength from event-related dynamics. Phys. Rev. E 78 (2008) 041918

S. Łęski, D. K. Wójcik, J. Tereszczuk, D.A. Świejkowski, E. Kublik, A. Wróbel Inverse Current-Source Density Method in 3D: Reconstruction Fidelity, Boundary Effects, and Influence of Distant Sources. Neuroinformatics. 4 (2007) 205-222.