Perceptual learning may occur when multiple contrasts are practiced in a fixed, but not in a roving (random), temporal sequence. However, learning may escape roving disruption when each contrast is assigned a letter tag (i.e., A, B, C, D). Because these letter tags carry not only stimulus identity information, but also semantic sequence information, here we investigated whether the semantic seq...

Apraxia caused by left hemispheric stroke typically impairs skilled sequential movements. After stroke, apraxic patients need to reacquire motor skills by motor learning. The current study assessed for the first time incidental motor sequence learning in apraxic patients. Forty-eight human subjects (henceforth called "patients") with left hemispheric stroke affecting the middle cerebral artery ...

The capacity to learn new motor sequences is fundamental to adaptive motor behavior. The early phase of motor sequence learning relies on the ventral and anterior striatal circuitry, whereas the late phase relies on the dorsal and posterior striatal circuitry. Early Parkinson's disease (PD) is mainly characterized by dopaminergic denervation of the dorsal and posterior striatum while sparing an...

A visuo-motor sequence can be learned as a series of visuo-spatial cues or as a sequence of effector movements. Earlier imaging studies have revealed that a network of brain areas is activated in the course of motor sequence learning. However, these studies do not address the question of the type of representation being established at various stages of visuo-motor sequence learning. In an earli...

Through practice, people are able to integrate a secondary sequence (e.g., a stimulus-based sequence) into a primary sequence (e.g., a response-based sequence), but it is still controversial whether the integrated sequences lead to better learning than only the primary sequence. In the present study, we aimed to investigate the effects of a sequence that integrated space and color sequences on ...

 Sequence dependent set-up times scheduling problems (SDSTs), availability constraint and transportation times are interesting and important issues in production management, which are often addressed separately. In this paper, the SDSTs job shop scheduling problem with position-based learning effects, job-dependent transportation times and multiple preventive maintenance activities is studied. ...

Virtually all methods of learning dynamic models from data start from the same basic assumption: that the learning algorithm will be provided with a single or multiple sequences of data generated from the dynamic model. However, in quite a few modern time series modeling tasks, the collection of reliable time series data turns out to be a major challenge, due to either slow progression of the d...

of “Discriminative Methods for Label Sequence Learning” by Yasemin Altun, Ph.D., Brown University, May 2005. Discriminative learning framework is one of the very successful fields of machine learning. The methods of this paradigm, such as Boosting and Support Vector Machines, have significantly advanced the state-of-the-art for classification by improving the accuracy and by increasing the appl...