✦ LIBER ✦

Experience-dependent and -independent neural networks for performance changes in motor sequence learning

✍ Scribed by Pierre Orban; Philippe Peigneux; Frederic Laberenne; Pierre Maquet; Habib Benali; Julien Doyon

Book ID: 116269174
Publisher: Elsevier Science
Year: 2008
Tongue: English
Weight: 41 KB
Volume: 67
Category: Article
ISSN: 0278-2626
DOI: 10.1016/j.bandc.2008.02.067

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Evidence for effector independent and de

Evidence for effector independent and dependent representations and their differential time course of acquisition during motor sequence learning

✍ Raju S. Bapi; Kenji Doya; Alexander M. Harner 📂 Article 📅 2000 🏛 Springer-Verlag 🌐 English ⚖ 406 KB

Differences in prefrontal and motor stru

Differences in prefrontal and motor structures learning dynamics depend on task complexity: A neural network model

✍ S.E. Lew; H.G. Rey; D.A. Gutnisky; B.S. Zanutto 📂 Article 📅 2008 🏛 Elsevier Science 🌐 English ⚖ 613 KB

H∞stability conditions for delayed neura

H∞stability conditions for delayed neural networks with external disturbances and norm-bounded uncertainties: Delay independent and dependent criteria

✍ Choon Ki Ahn 📂 Article 📅 2011 🏛 Science in China Press (SCP) 🌐 English ⚖ 384 KB

Time dependent neural network models for

Time dependent neural network models for detecting changes of state in complex processes: Applications in earth sciences and astronomy

✍ Julio J. Valdés; Graeme Bonham-Carter 📂 Article 📅 2006 🏛 Elsevier Science 🌐 English ⚖ 670 KB

A computational intelligence approach is used to explore the problem of detecting internal state changes in time dependent processes; described by heterogeneous, multivariate time series with imprecise data and missing values. Such processes are approximated by collections of time dependent non-line