脳科学研究施設「講演会」を7月22日に開催します!

2003.07.11

日時 2003年7月22日(火曜日)
10:00~11:30 (講演者:筒井健一郎氏)
場所 玉川大学工学部第二会議室(工学部棟2階)
町田市玉川学園6-1-1(小田急線玉川学園駅南口より徒歩10分)

玉川大学学術研究所脳科学研究施設 「講演会」 演題・要旨

10:00~11:30  Angela Roberts先生

演題 Contribution of the amygdala and prefrotal cortex to positive affective behaviour in primates.
要旨 Many studies have demonstrated the importance of the amygdala and orbitofrontal cortex in the processing of reward and the use of such information in guiding behaviour. However the precise role of these structures and their differential contribution to affective behaviour is poorly understood. Recently, with greater appreciation of the range of associative learning processes that can contribute to rewarded behaviour, studies in rats have begun to dissect out the distinct contributions of nuclei within the amygdala to these different processes. These will be reviewed and then our own recent programme of research into positive affective behaviour in primates described. The latter will include a comparison of the effects of lesions to the amygdala and its projection areas in the orbital and medial prefrontal cortex in marmosets on a number of different associative learning processes. In addition, preliminary investigations will be presented that have explored the relationship between the autonomic system, the amygdala and affective behaviour by taking 'on-line' recordings of blood pressure and heart rate activity during pavlovian conditioning in amygdala lesioned monkeys.

13:00~14:00  Wolfram Schultz先生   

  • 体調不良のため来日できなくなりました。(2003.7.18付)
演題 Coding of economic decision variables by dopamine neurons
要旨 Results from lesioning and psychopharmacological studies suggest an involvement of dopamine systems in the processing of reward information. We found in formal learning paradigms that dopamine neurons detect the extent to which rewards occur differently than predicted, thus coding an 'error' in the prediction of reward. We then assessed to which extent dopamine neurons would code basic economic decision variables, namely probability and magnitude of reward, and their multiplicative combination. We found that phasic activations varied monotonically across the full range of probabilities (p=0 to 1.0). The response to the conditioned stimulus predicting reward with a specific probability increased and the response to probabilistic reward decreased with probability. In addition, we observed a separate, slower response which increased gradually until the potential time of reward. This response reflected the uncertainty of reward, as it was maximal at p = 0.5 and decreased at higher and lower probabilities. Dopamine neurons increased their activations monotonically to increasing reward magnitudes. Testing of expected reward value (probability × magnitude of reward) revealed combined coding of these variables, such that responses to magnitude could be indistinguishable from those to probability of reward. These data suggest that dopamine responses may serve as inputs to decision-making mechanisms for economic behavior.

14:00~15:00  筒井健一郎先生

  • 時間変更になりました 13:00~14:00
演題 ntegaration of disparity and texture gradient signals for the representation of 3D surface orientation in parietal area CIP
要旨 David Marr postulated that the detection of surface orientation is an important intermediate stage towards the representation of three-dimensional (3D) structure of objects, which is the main goal of visual processing. Recently we found a group of neurons that respond selectively to a 3D orientation of a flat surface in the caudal part of the lateral bank of intraparietal sulcus (area CIP). We examined the responses of these neurons with i) random-dot stereograms in which the surface orientation was defined only by disparity gradients and ii) texture patterns in which the surface orientation was defined only by texture gradients. We found three types of surface orientaion selective neurons: those which were sensitive to disparity gradients alone ('D neurons'), those which were sensitive to texture gradients alone ('T neurons'), and those which were sensitive to both disparity and texture gradients ('DT neurons'). Among three types, the most prominent in number was DT neurons. In DT neurons, preferred orientation was the same between the surface orientation defined by disparity gradients and that defined by texture gradients. The result suggests that different kinds of gradient signals are integrated in CIP in order to construct a general representation of 3D surface orientation which is independent from specific depth cues.