Transcript Population Codingにまつわる 最近の話題から

Population Codingの
最近の話題から
銅谷賢治
[email protected]
ATR 人間情報科学研究所
科学技術振興事業団 CREST
あらすじ
古典的population coding仮説
Population vector
確率的population coding仮説
Bayes/最尤推定
不確定性の表現
複数入力の統合
Population Vectors
１次運動野ニューロンの運動方向選択性
cosine tuning
fi(m) = bi + ai cos( qm-qi)
preferred direction qi は一様に分布
Population vector
v(m) = Si fi(m) vi
simplicity and robustness.
(Georgopoulos)
Probabilistic Population Codes
(Zemel, Dayan, Pouget 1998)
Encoding: underlying quantity x
noisy response: P[r|x]
Decoding
Bayesian: P[x|r]  P[r|x] P[x]
Standard Poisson model
encode single value of x
P[ri|x] = e-fi(x) (fi(x))ri/ri!
P[x|r] = P[x] Pi e-fi(x) (fi(x))ri/ri!
Extended Poisson Model
Encode the probability distribution P[x|w]
uncertainty, multiple values
<ri> = x P[x|w] fi(x) dx
Decoding for histogram representation
<ri> = Sj fj fij
logP[{fj}|{ri}] = K + logP[{fj}] + Si ri log[Sj fj fij]
Roles of the Cerebral Cortex
Representations for good generalization
modality, invariance, resolution,...
task oriented context and working memory
Combining multiple outputs
reasons for for poplulation coding?
Population Coding
(Deneve et al., 2001)
Function approximation and Cue Integration
おわりに
情報の表現から処理へ
Poisson的な発火の積極的な意味付けは？