- About our group
- How to contact us
- People
- Projects
- Computational Neuroscience Projects
- Complex Systems Projects
- Past projects
- EURESIST - Project
- ICEA - Modelling goal-directed navigation of the rat
- Hippocampal oscillations
- Study of sensory systems
- Software package for complex network analysis
- Dynamics of evolving networks
- A populational model of hippocampus CA3 region slices
- Development of hippocampal place fields
- Hippocampal coding and dynamics
- Location dependent differences between somatic and dendritic IPSPs
- Olfaction and its underlying stochastic phenomena
- The role of self-excitation in the development of topographic order
- Publications
- Events
- CNS '15 Host Proposal
- IJCNN 11 Workshop
- Past events
- Minisymposium on Computational Aspects of Neurological and Psychatric Diseases
- Workshop on large scale random graphs
- Workshop on Cortico- Hippocampal dynamics: Navigation and Neuromodulation
- Joint Workshop on Neural Autonomous Robots
- Workshop on System Neuroscience
- Neuronhálózatok strukturális kérdései
- 7th Tamagawa Dynamic Brain Forum 2002
- Minisymposium on Computational Neuroscience
- Számítógepes neurológia konferencia, Problemák - Adatok - Modellek
- Budapest - Tampere Minisymposium on Computational Neurolgy
- Education / Oktatás
- Lectures and News
- Positions
- Intranet
Probabilistic computation in dendritic trees
Dendritic trees possess a plethora of voltage-dependent conductances that render them sophisticated computational devices well beyond the realm of traditional cable theory. Previous functional approaches to active dendritic processing were limited because they studied dendritic computations at the single neuron-level, or, at best, in purely feed-forward neural networks. However, many computations in the nervous system, especially those underlying learning and memory, are carried out by the dynamics of recurrently-coupled neural circuits, and thus it becomes pressing to identify the computational benefits active dendritic trees bring to such network-level computations.
People
This is a collaborative project between Balázs Ujfalussy (Budapest CNS Group) and Máté Lengyel (University of Cambridge).
Publications
B. Ujfalussy, T Kiss, P. Érdi: Parallel Computational Subunits in Dentate Granule Cells Generate Multiple Place Fields PLoS Comput Biol (2009) 5(9):e1000500.