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2201 Motion perception for composite sine-wave grating patterns in rhesus monkeys: Motion from feature and luminance
$234
22. Cognitive and computational neuroscience, Others
2201
blOTION PERCEPTION FOR COblPOS1TE SINE-WAVE GRATING PATTERNS IN RHESUS blONKEYS: blOTION FRObl FEATURE AND LUMINANCE. AKITOSHI HANAZAWA, Dept. o f B e h a v i o r a l a n d
B r a i n Sciences, P r i m a t e Res. Inst.. Kyoto U n i v e r s i t y . K a n r i n , I n u v a m a . Aich 484. l a p a n . Existence o f two motion p e r c e p t i o n m e c h a n i s m s was e x a m i n e d in r h e s u s m o n k e y s u s i n g composite s i n e - w a v e g r a t i n g p a t t e r n s . The e m p l o y e d stimuli h a d p e r i o d i c c o n t r a s t m o d u l a t i o n o f f r e q u e n c y f a n d s i n u s o i d a l c o m p o n e n t s o f f r e q u e n c i e s 3t, 2 f a n d / o r 4f. The), w e r e s t e p p e d o n e q u a r t e r - c y c l e (90 °) o f t h e c o n t r a s t m o d u l a t i o n t h a t r e s u l t e d i n -90 ° p h a s e s h i f t o f 3f c o m p o n e n t . C h a n g i n g s p a t i o - t e m p o r a l p a r a m e t e r s o f t h e stimuli, d e t e c t i o n o f t h e d i r e c t i o n o f motion was m e a s u r e d u s i n g r e s p o n s e s o f m o n k e y s t r a i n e d to d i s c r i m i n a t e motion d i r e c t i o n . F o r s h o r t s t i m u l u s o n s e t a s y n c h r o n y a n d i n t e r - s t i m u l u s i n t e r v a l (ISI) p e r f o r m a n c e c o r r e s p o n d e d to s p a t i o - t e m p o r a l F o u r i e r p o w e r s p e c t r u m , w h e r e a s
f o r l o n g ISI
p e r f o r m a n c e c o r r e s p o n d e d to motion d i r e c t i o n o f t h e f e a t u r e s o f t h e w a v e f o r m . Contrasts o f c o m p o n e n t s a f f e c t e d p e r f o r m a n c e . These r e s u l t s s u g g e s t t h a t t h e r h e s u s m o n k e y h a s m o t i o n detectors based on f e a t u r e a n d l u m i n a n c e j u s t like as p r o p o s e d i n t h e h u m a n v i s u a l system.
2202
CAUSALITY ANALYSIS BASED ON AN ENTROPY FUNCTION AND ITS APPLICATION
.TETSUYA TAKAHA~HI, Lab for Neural Networks, The Institute of Physical and Chemical Research (RIKEN), WakQ-shL Saitama, 351-01, Japan Based on PCA (principal component analysis), an entropy function is defined to reflect changes in the selectivity of multiple neurons towards a set of multiple stimuli. Since "learning" in nervous systems is considered to be a process of changes in selectK, ity, it c'an be quantitatively characterized by the function. Moreover, the quantity can describe the strength of the causal relationship between two events such as the onset of a stimulus and the onset of a response. In order to demonstrate this, the responses of neurons in A1 of anesthetized monkeys obtained by single unit recordings .were analyzed using the function together with a time-slice analysis utilizing 2-way ANOVA. The results show that the strength of the causal relationship between the stimuli (pure tones with different frequencies and intensities) and the responses varies in the time course of a response and that the presence of a large number of spikes at some time point does not necessarily mean that the set of neurons has a strong causal relationship with the set of stimuli at the time point.
22. Cognitive and computational neuroscience, Others
2201
blOTION PERCEPTION FOR COblPOS1TE SINE-WAVE GRATING PATTERNS IN RHESUS blONKEYS: blOTION FRObl FEATURE AND LUMINANCE. AKITOSHI HANAZAWA, Dept. o f B e h a v i o r a l a n d
B r a i n Sciences, P r i m a t e Res. Inst.. Kyoto U n i v e r s i t y . K a n r i n , I n u v a m a . Aich 484. l a p a n . Existence o f two motion p e r c e p t i o n m e c h a n i s m s was e x a m i n e d in r h e s u s m o n k e y s u s i n g composite s i n e - w a v e g r a t i n g p a t t e r n s . The e m p l o y e d stimuli h a d p e r i o d i c c o n t r a s t m o d u l a t i o n o f f r e q u e n c y f a n d s i n u s o i d a l c o m p o n e n t s o f f r e q u e n c i e s 3t, 2 f a n d / o r 4f. The), w e r e s t e p p e d o n e q u a r t e r - c y c l e (90 °) o f t h e c o n t r a s t m o d u l a t i o n t h a t r e s u l t e d i n -90 ° p h a s e s h i f t o f 3f c o m p o n e n t . C h a n g i n g s p a t i o - t e m p o r a l p a r a m e t e r s o f t h e stimuli, d e t e c t i o n o f t h e d i r e c t i o n o f motion was m e a s u r e d u s i n g r e s p o n s e s o f m o n k e y s t r a i n e d to d i s c r i m i n a t e motion d i r e c t i o n . F o r s h o r t s t i m u l u s o n s e t a s y n c h r o n y a n d i n t e r - s t i m u l u s i n t e r v a l (ISI) p e r f o r m a n c e c o r r e s p o n d e d to s p a t i o - t e m p o r a l F o u r i e r p o w e r s p e c t r u m , w h e r e a s
f o r l o n g ISI
p e r f o r m a n c e c o r r e s p o n d e d to motion d i r e c t i o n o f t h e f e a t u r e s o f t h e w a v e f o r m . Contrasts o f c o m p o n e n t s a f f e c t e d p e r f o r m a n c e . These r e s u l t s s u g g e s t t h a t t h e r h e s u s m o n k e y h a s m o t i o n detectors based on f e a t u r e a n d l u m i n a n c e j u s t like as p r o p o s e d i n t h e h u m a n v i s u a l system.
2202
CAUSALITY ANALYSIS BASED ON AN ENTROPY FUNCTION AND ITS APPLICATION
.TETSUYA TAKAHA~HI, Lab for Neural Networks, The Institute of Physical and Chemical Research (RIKEN), WakQ-shL Saitama, 351-01, Japan Based on PCA (principal component analysis), an entropy function is defined to reflect changes in the selectivity of multiple neurons towards a set of multiple stimuli. Since "learning" in nervous systems is considered to be a process of changes in selectK, ity, it c'an be quantitatively characterized by the function. Moreover, the quantity can describe the strength of the causal relationship between two events such as the onset of a stimulus and the onset of a response. In order to demonstrate this, the responses of neurons in A1 of anesthetized monkeys obtained by single unit recordings .were analyzed using the function together with a time-slice analysis utilizing 2-way ANOVA. The results show that the strength of the causal relationship between the stimuli (pure tones with different frequencies and intensities) and the responses varies in the time course of a response and that the presence of a large number of spikes at some time point does not necessarily mean that the set of neurons has a strong causal relationship with the set of stimuli at the time point.