Recent
Publications:
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Y. Nie and M. Tatsuno, (submitted) Information-geometric measures for estimation of connection weight under correlated inputs.
Z. Navratilova, L. T. Hoang, C. D. Schwindel, M. Tatsuno and B. L. McNaughton, (submitted) Experience-dependent firing rate remapping generates directional selectivity in hippocampal place cells.
M. Tatsuno, (2010) Sleep and learning – memory consolidation and memory-trace replay during sleep -, Japanese Journal of Sleep Medicine, Vol. 4, No. 4, pp. 483-488 [Japanese].
M. Tatsuno, (2010) Multi-electrode recording from freely behaving animals and spike train analysis, Journal of Japan Neural Network Society, Vol. 17, No. 3, pp. 124-138 [Japanese].
L. A. Johnson, D. R. Euston, M. Tatsuno and B. L. McNaughton, (2010) Stored-trace reactivation in rat prefrontal cortex is correlated with down-to-up state fluctuation density, Journal of Neuroscience, Vol. 30, No. 7, pp. 2650-2661.
M. Tatsuno, (2009) Replay of behaviorally induced multi-neuronal spiking patterns during subsequent sleep, Seitai No Kagaku, Vol. 60, No. 4, pp. 285-294 [Japanese].
M. Tatsuno, JM. Fellous and S. Amari , (2009) Information geometric measures as robust estimators of connection strengths and external inputs, Neural Computation, Vol. 21, No. 8, pp. 2309-2335.
M. Tatsuno, (2007) Memory replay and memory consolidation, Seibutsu Butsuri, Vol. 47, No. 6, pp. 367 – 377 [Japanese].
D. R. Euston, M. Tatsuno and B. L. McNaughton, (2007) Fast-forward playback of recent memory sequences in prefrontal cortex during sleep, Science, Vol. 318, No. 5853, pp. 1147-1150.
M. Tatsuno, P. Lipa and B. L. McNaughton, (2006) Methodological considerations on the use of template matching to study long-lasting memory trace replay, Journal of Neuroscience, Vol. 26, No. 42, pp. 10727-10742.
M. Tatsuno and M. Okada, (2004) Investigation of possible neural architectures underlying information-geometric measures, Neural Computation , Vol. 16, No. 4, pp. 737 - 765.
M. Tatsuno and M. Okada, (2003) How does the information-geometric measure depend on underlying neural mechanisms?, Neurocomputing , Vol. 52 - 54, pp. 649 - 654.
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