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This Article Full Text Full Text (PDF) All Versions of this Article: 98/6/3309    most recent 00440.2007v1 Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in ISI Web of Science Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Google Scholar Articles by Safran, M. N. Articles by Sompolinsky, H. PubMed PubMed Citation Articles by Safran, M. N. Articles by Sompolinsky, H.

Adaptation and Information Transmission in Fly Motion Detection

¹Institute of Life Sciences, ²Interdisciplinary Center for Neural Computation, ⁵Racah Institute of Physics, Hebrew University, Jerusalem, Israel; ³Bernstein Center for Computational Neuroscience, Munich, Germany; ⁴Department of Systems and Computational Neuroscience, Max Planck Institute of Neurobiology, Martinsried, Germany; and ⁶Center for Brain Science, Harvard University, Cambridge, Massachusetts

Submitted 18 April 2007; accepted in final form 28 September 2007

In this work, we studied the adaptation of H1, a motion-sensitive neuron in the fly visual system, to the variance of randomly fluctuating velocity stimuli. We ask two questions. 1) Which components of the motion detection system undergo genuine adaptational changes in response to the variance of the fluctuating velocity signal? 2) What are the consequences of this adaptation for the information processing capabilities of the neuron? To address these questions, we characterized the adaptation of H1 by estimating the changes in the parameters of an associated Reichardt motion detection model under various stimulus conditions. The strongest stimulus dependence was exhibited by the temporal kernel of the motion detector and was parametrized by changes in the model's high-pass time constant (_H). This time constant shortened considerably with increasing velocity fluctuations. We showed that this adaptive process contributes significantly to the shortening of the velocity response time-course but not to velocity gain control. To assess the contribution of time-constant adaptation to information transmission, we compared the information rates generated by our adaptive model motion detector with model simulations in which _H was held fixed at its unadapted value for all stimulus conditions. We found that for intermediate stimulus conditions, fixing _H at its unadapted value led to higher information rates, suggesting that time-constant adaptation does not optimize total information rates about velocity trajectories. We also found that, over the wide range of stimulus conditions tested here, H1 information rates are dependent on the amplitude of velocity fluctuations.