Welcome to Fukai Lab!
Overview
Functions of the brain emerge from computations at multiple levels, from molecular and cellular to networks. Clarifying the mechanism of complex information processing by the brain, we have to know the theoretical basis of computations by neuronal networks. In particular, it is important to reveal what and how the brain circuitry computes. The goal of our researches is to clarify the algorithms and biological mechanisms of powerful and flexible brain computations. My laboratory consists of a combination of experimental and computational neuroscientists. The people are continuously encouraged to stimulate one another. Through these interactions, we are studying a variety of up-to-date topics in computational neuroscience, for example, from the neural code that neurons and their networks use for representing information to the circuit mechanisms that underlie cognitive motor behaviors.
Current research interests
- Modeling local cortical circuits and their functions
- Neural dynamics and neural information representation
- System-level theories and network mechanisms for decision making
- Models of oscillations and synchronization in the brain
- Multiunit and juxtacellular recordings in behaving rats
- Developing new methods to analyze multiunit activities
Recent major publications
- T.Takekawa, Y.Isomura, and T.Fukai, Accurate spike-sorting for multiunit recordings, European Journal of Neuroscience 31,2(2010),263-272.
- Y.Yazaki-Sugiyama, S.Kang, H.Câteau, T.Fukai and T.K.Hensch, Bidirectional plasticity in fast-spiking GABA circuits by visual experience, Nature 462 (2009),218-221.
- Y.Isomura, R.Harukuni, T.Takekawa, H.Aizawa and T.Fukai, Microcircuitry coordination of cortical motor information in self-initiation of voluntary movements, Nature Neuroscience 12 (2009),1586-1593.
- H.Okamoto and T.Fukai, Recurrent network models for perfect temporal integration of fluctuating correlated inputs, PLoS Computational Biology,5(6): e1000404 (2009).
- J.Teramae and T.Fukai, Temporal precision of spike response to fluctuating input in pulse-coupled networks of oscillating neurons, Physical Review Letters,101.248105 (2008).
- Y.Sakai and T.Fukai, When does reward maximization lead to matching law? PLoS One,3(11): e3795 (2008).
- S.Kang, K.Kitano and T.Fukai, Structure of spontaneous UP and DOWN transitions self-organizing in a cortical network model, PLoS Computational Biology, 4(3):e1000022 (2008).
- K.Miura, Y.Tsubo, M.Okada and T.Fukai, Balanced excitatory and inhibitory inputs to cortical neurons decouple firing irregularity from rate modulations, The Journal of Neuroscience, 27:13802-13812 (2007).