効果量(d)の信頼区間を計算するExcel のスプレッドシート。
日本語を表示できる。
CEM: Center for Evaluation and Monitoring http://www.cem.org/effect-size-calculator
Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models.Behavior Research Methods, 40, 879-891.
http://link.springer.com/article/10.3758%2FBRM.40.3.879
SEM（パス解析）とは異なるアイディア
SPSSで実行する
SPSS FAQ
How can I analyze multiple mediators in SPSS?
Cf.
An information integration theory of consciousness
Giulio Tononi
BMC Neuroscience 2004, 5:42 doi:10.1186/1471-2202-5-42
See, Fig.1
MATLAB functions used for calculating effective information and complexes are at webcite.
Moors, A, Ellsworth, P., Scherer, K. R., Frijda, N. H. (2013) Appraisal theories of emotion: State of the art and future development. Emotion Review 5, 119-124.
表情の感情価を条件づけによって操作し，顔表情の視覚探索における感情価と視覚的特徴の影響を評価している。
Gerritsen, C., Frischen, A., Blake, A., Smilek, D., & Eastwood, J. D. (2008). Visual search is not blind to emotion. Perception & Psychophysics, 70, 1047-1059.
GOODMAN, J., CRYDER, C., & CHEEMA, A. (2012) Data collection in a flat world: The strengths and weaknesses of Mechanical Turk samples. Journal of Behavioral Decision Making.
: Mechanical Turk (MTurk), an online labor system run by Amazon.com, provides quick, easy, and inexpensive access to online research participants.
被験者を集める一方法?
Cf.
クラウド時代の人海戦術 Amazon Mechanical Turk
http://d.hatena.ne.jp/Zellij/20110923/p1
Amazon Mechanical Turk
Samples of academic questionnaire templates
Cognitive Memory: Cellular and Network Machineries and Their Top-Down Control
Yasushi Miyashita
Science 15 October 2004:
Vol. 306 no. 5695 pp. 435-440
http://dx.doi.org/10.1126/science.1101864
基礎的な実験データをダウンロードできる。実験はいずれも教育用では代表的なもの。
“Perceptual Scotomas”
A Functional Account of Motion-Induced Blindness
Joshua J. New and
Brian J. Scholl
Psychological Science July 2008 vol. 19no. 7 653-659
http://pss.sagepub.com/content/19/7/653
MIB
Dosher, B.A.,& Lu, Z.L. (1999). Mechanisms of perceptual learning. Vision Research 1999, 39, 3197-3221.
http://dx.doi.org/10.1016/S0042-6989(99)00059-0
See Fig.2, Perceptual Template Model (PTM)
:
The PTM characterizes human performance in perceptual tasks in terms of a signal processing filter or template, an optional transducer nonlinearity, an internal additive noise source, and an internal multiplicative noise source. The stimulus consists of a signal plus external noise. The internal additive noise source is independent of the contrast of the stimulus; the internal multiplicative noise source increases directly with the contrast of the stimulus (signal plus external noise).
:
Fig.3, Three mechanisms of perceptual learning.
(1) Practice that turns up the gain on the stimulus, corresponding to stimulus enhancement.
(2) Practice that affects the amount of external noise processed through the perceptual template by narrowing the filter tuning, corresponding to external noise exclusion.
(3) Practice that reduces the gain on multiplicative internal noise, or internal multiplicative noise reduction.
:
脳科学辞典
受容野 receptive field
解説が具体的で信頼性も高い。特に，非古典的受容野の項参照。
Behrmann, M., Geng, J. J. and Shomstein, S. (2004). Parietal cortex and attention. Current Opinion in Neurobiology, 14, 212-217. (.pdf )
Jacob, S. N., & Nieder, A. (2009). Notation-independent representation of fractions in the human parietal cortex. Journal of Neuroscience, 29, 4652–4657.
アクセス
トータル
ランキング
