By Murat Saglam, Yuki Hayashida, Nobuki Murayama (auth.), Masumi Ishikawa, Kenji Doya, Hiroyuki Miyamoto, Takeshi Yamakawa (eds.)
The quantity set LNCS 4984 and LNCS 4985 constitutes the completely refereed post-conference court cases of the 14th foreign convention on Neural details Processing, ICONIP 2007, held in Kitakyushu, Japan, in November 2007, together with BRAINIT 2007, the 4th foreign convention on Brain-Inspired info Technology.
The 228 revised complete papers awarded have been conscientiously reviewed and chosen from various traditional paper submissions and 15 particular prepared classes. The 116 papers of the 1st quantity are geared up in topical sections on computational neuroscience, studying and reminiscence, neural community versions, supervised/unsupervised/reinforcement studying, statistical studying algorithms, optimization algorithms, novel algorithms, in addition to motor keep an eye on and imaginative and prescient. the second one quantity comprises 112 contributions relating to statistical and trend acceptance algorithms, neuromorphic and implementations, robotics, info mining and data discovery, actual global purposes, cognitive and hybrid clever structures, bioinformatics, neuroinformatics, brain-conputer interfaces, and novel approaches.
Read or Download Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I PDF
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Extra info for Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I
On the other hand, when monkeys exhibit the irrelevant behavior for the task and then receive no reward, the attractor associated with the irrelevant behavior is destabilized, and then eliminated in the PFC network. As a result, the PFC retains only the object information relevant to the categorization task, as working memory. The feedback from PFC to IT and PP makes the responses of IT and PP neurons strengthened, thereby enabling the visual system to rapidly and accurately discriminate between object features belonging to diﬀerent categories.
Spatial Organization and Magnitude of Orientation Contrast Interaction in Primate V1. Journal of Neurophysiology 88, 2796–2808 (2002) 8. edu/Research/ Projects/CS/vision/grouping/segbench/ 9. : Dynamic predictions: oscillations and synchrony in topdown processing. Nature Reviews Neuroscience 2, 704–716 (2001) Neural Mechanism for Extracting Object Features Critical for Visual Categorization Task Mitsuya Soga1 and Yoshiki Kashimori1,2 Dept. of Information Network Science, Graduate school of Information Systems, Univ.
1 Neural Mechanism for Extracting Diagnostic Features in Visual Categorization Task Categorization Task We used the line drawings of faces used by Sigala and Logothetis  to investigate the neural mechanism of categorization task. The face images consist of four varying features, eye height, eye separation, nose length, and mouse height. The monkeys were trained to categorize the face stimuli depending on two diagnostic features, eye height and eye separation. 2b. The face stimuli were not linearly separable by using the other two, non-diagnostic features, or nose length and mouth height.