Neural representation of information: A dynamic system approach

1. Neural representation of information: A dynamic system approach Fumihiko Taya Department of Physiology and Biosignaling, Graduate School of Medicine, Osaka University

2. The roles of neurons Neurons seem to have the following two roles. • Computational or functional role • In order to determine the activities of post-synaptic neurons, each neurons work as computational devices which convey the information necessary for calculations by means of spikes. • Mental role • Many studies on patients who have deficits of mental functions have suggested that our brains which consist of neurons support subjective conscious experiences and unconscious mental processes.

3. Neural representation by spikes There are two possible ways to represent the information by spikes. • Spike count or firing rate • PSTH • Temporal coding • Latency • Spike distribution (phasic or tonic) • ISI (Interspike Interval) • Absolute spike timing

4. Contextual modulation in V1

5. Dynamical neural activity • Neural activity changes dramatically according to the context of visual scene. • These dynamical neural activities support the both dynamical and stable aspects of the perception. • Spike count is an insufficient measure to explain the stable aspect of the perception. • Temporal coding is an alternate candidate for the way to encode the stable perception. • Neural activity at network level may have a stable structure as revealed by dynamical systems analysis, for example.

6. Dynamical and stable information • Dynamical information (intentional qualia) • Ambiguous figures, such as Necker cube, Rubin’s vase, apparent motion etc. • Stable information (sensory qualia) • Visual qualia is usually very stable, as we know well. Binocular rivalry is an exception where the visual qualia changes dynamically over time, so that we have regarded it as a good tool for studying the neural representation of the usually stable information.

7. Method Left eye Right eye Indicator Fixation point Phase difference Visual awareness

9. The Flipping effect • 左右でflipすることは、不思議なことだとここに書く。 • Unilateral neglect • Unilateral lesions of dorsolateral association cortex cause the failure to orient attention to the contralesional objects. • Neglect can move to the ipsilateral side when they rotate the attended object.

10. 円が一つだとこうなると説明

11. Spatio-temporal structure of dominance change右と左の関係は、すごい不思議だと指摘する。 Single circle Two conflict circles

12. Interpretation of the global scene • A single moving circle • The subjects are more likely to perceive the ipsilateral color in the vicinity of the moving circle (vicinity effect). This vicinity effect tends to lag behind the circle, so that we can explain it on a local basis. • Two conflict moving circles • The dominance change tends to precede the moving circles towards the edge of the screen. The interpretation of the visual scene on a global sense is prerequisite for the construction of the conscious visual perception.

13. Stable and dynamical information • Stable information is needed to keep the identities. It works as an interface used for the reliable interpretation of the external world. • Dynamic information is needed to adapt the dynamically changing external world in a flexible way. How the neural system represent these two conflict aspects of information by the same neural networks?

14. Preliminary neural network model • Our results suggested that neural activity at network level was limited by the spatial constraints of connections among units, even if the only spontaneous activity was concerned (Yanagawa, Taya and Mogi, 2002). • The spatial constraint of network may be a key factor to represent the dynamical and stable aspects of information, as a dynamical system.

15. Arieli et al (science 1999) Preferred cortical state(PCS)： あるニューロンが発火している時の周囲のニューロンの平均発火状態

16. Preferred cortical state for different levels of activation in the spontaneous state

17. Future work • Further psychophysical experiments on binocular rivalry in order to search for the neural mechanism underlying the dominance change on a global basis • Development of the neural network model to represent the dynamical and the stable information • Mathematical formalization • Global interpretation • Perceptual stability • Binding problem