Laboratory for Neural Circuit Theory

High-level functions of the brain, such as perception, learning and memory, decision making, etc., emerge from computations by neuronal networks. My lab uses theoretical and electrophysiological approaches to better understand the fundamental properties of neural networks.
Uncovering the circuit mechanism is particularly important as I consider that most of the advantages of brain's computation reside in the way the brain implements it by neural circuits. The brain is believed to utilize noise for modeling the external world for performing robust and flexible computations in sensory perception, decision making, and so on. The low energy consumption of the brain (~a few tens of watts) also suggests that the powerful computations performed by the brain do not require a code with a clear separation between signals and noise. The goal of our research is to uncover the principles of the brain's stochastic computation and to provide the theoretical basis for creating brain-style computing machines.

Research Subjects

• Stochastic computation by the brain and its circuit mechanism
• Neural dynamics and information representations
• Theoretical/experimental studies of cortical microcircuit functions
• Information analysis of neural ensemble data

Publications

1. Jun-nosuke Teramae, Yasuhiro Tsubo and Tomoki Fukai,:
   "Optimal spike-based communication in excitable networks with strong-sparse and weak-dense links."
   Scientific Reports 2: 485. doi: 10.1038/srep00485 (2012).
2. Yasuhiro Tsubo, Yoshikazu Isomura, and Tomoki Fukai,:
   "Power-Law Inter-Spike Interval Distributions Infer a Conditional Maximization of Entropy in Cortical Neurons."
   PLoS Comput Biol 8(4): e1002461. doi:10.1371/journal.pcbi.1002461 (2012)
3. Matthieu Gilson and Tomoki Fukai,:
   "Stability versus Neuronal Specialization for STDP: Long-Tail Weight Distributions Solve the Dilemma."
   PLoS one 6(10): e25339 (2011).
4. Nobuhiko Wagatsuma, Tobias C. Potjans, Markus Diesmann, and Tomoki Fukai,:
   "Layer-dependent attentional processing by top-down signals in a visual cortical microcircuit model."
   Frontiers in Computational Neuroscience 5: doi: 10.3389/fncom.2011.00031 (2011).
5. Takashi Takekawa, Yoshikazu Isomura, and Tomoki Fukai,:
   "Accurate spike-sorting for multiunit recordings."
   European Journal of Neuroscience 31(2): 263-272 (2010).
6. Yoko Yazaki-Sugiyama, Siu Kang, Hideyuki Cateau, Tomoki Fukai, and Takao K. Hensch,:
   "Bidirectional plasticity in fast-spiking GABA circuits by visual experience."
   Nature 462: 218-221 (2009).
7. Yoshikazu Isomura, Rie Harukuni, Takashi Takekawa, Hidenori Aizawa, and Tomoki Fukai,:
   "Microcircuitry coordination of cortical motor information in self-initiation of voluntary movements."
   Nature Neuroscience 12: 1586-1593 (2009).
8. Hiroshi Okamoto and Tomoki Fukai,:
   "Recurrent network models for perfect temporal integration of fluctuating correlated inputs."
   PLoS Computational Biology 5(6): e1000404 (2009).
9. Jun-nosuke Teramae and Tomoki Fukai,:
   "Temporal precision of spike response to fluctuating input in pulse-coupled networks of oscillating neurons."
   Physical Review Letters 101: 248105 (2008).
10. Keiji Miura, Yasuhiro Tsubo, Masato Okada and Tomoki Fukai,:
    "Balanced excitatory and inhibitory inputs to cortical neurons decouple firing irregularity from rate modulations."
    The Journal of Neuroscience 27:13802-13812 (2007).