Biomedical subjects

Shawn W Ell

Publications and source records attributed to Shawn W Ell.

5 recordsLinked to original sources

PubMed2006

Focal putamen lesions impair learning in rule-based, but not information-integration categorization tasks.

Previous research on the role of the basal ganglia in category learning has focused on patients with Parkinson's and Huntington's disease, neurodegenerative diseases frequently accompanied by additional cortical pathology. The goal of the present study was to extend this work to patients with basal ganglia lesions due to stroke, asking if similar changes in performance would be observed in patients with more focal pathology. Patients with basal ganglia lesions centered in the putamen (6 left side, 1 right side) were tested on rule-based and information-integration visual categorization tasks. In rule-based tasks, it is assumed that participants can learn the category structures through an explicit reasoning process. In information-integration tasks, optimal performance requires the integration of information from two or more stimulus components, and participants are typically unaware of the category rules. Consistent with previous studies involving patients with degenerative disorders of the basal ganglia, the stroke patients were impaired on the rule-based task, and quantitative, model-based analyses indicate that this deficit was due to the inefficient application of decision strategies. In contrast, the patients were unimpaired on the information-integration task. This pattern of results provides converging evidence supporting a role of the basal ganglia and, in particular, the putamen in rule-based category learning.

Analysis of Variance↗

PubMed2005

FROST: a distributed neurocomputational model of working memory maintenance.

Many studies suggest that the sustained activation underlying working memory (WM) maintenance is mediated by a distributed network that includes the prefrontal cortex and other structures (e.g., posterior parietal cortex, thalamus, globus pallidus, and the caudate nucleus). A computational model of WM, called FROST (short for FROntal-Striatal-Thalamic), is proposed in which the representation of items and spatial positions is encoded in the lateral prefrontal cortex. During delay intervals, activation in these prefrontal cells is sustained via parallel, prefrontal cortical-thalamic loops. Activation reverberates in these loops because prefrontal cortical excitation of the head of the caudate nucleus leads to disinhibition of the thalamus (via the globus pallidus). FROST successfully accounts for a wide variety of WM data, including single-cell recording data and human behavioral data.

Action Potentials↗

PubMed2004

Dynamical trajectories in category learning.

Category learning has traditionally been studied by examining how percentage correct changes with experience (i.e., in the form of learning curves). An alternative and more powerful approach is to examine dynamical learning trajectories--that is, to examine how the parameters that describe the current state of the model change with experience. We describe results from a new experimental paradigm in which empirical-learning trajectories are directly observable. In these experiments, participants learned two categories of spatial position, and they were constrained to identify and use a linear decision bound on every trial. The dependent variables of principal interest were the slope and the intercept of the bound used on each trial. Data from two experiments supported the following conclusions. (1) Gradient descent provided a poor description of the empirical trajectories. (2) The magnitude of changes in decision strategy decreased with experience at a rate that was faster than that predicted by gradient descent. (3) Learning curves suffered from substantial identifiability problems.

Cues↗

PubMed2003

Procedural learning in perceptual categorization.

In two experiments, observers learned two types of category structures: those in which perfect accuracy could be achieved via some explicit rule-based strategy and those in which perfect accuracy required integrating information from separate perceptual dimensions at some predecisional stage. At the end of training, some observers were required to switch their hands on the response keys, whereas the assignment of categories to response keys was switched for other observers. With the rule-based category structures, neither change in response instructions interfered with categorization accuracy. However, with the information-integration structures, switching response key assignments interfered with categorization performance, but switching hands did not. These results are consistent with the hypothesis that abstract category labels are learned in rule-based categorization, whereas response positions are learned in information-integration categorization. The association to response positions also supports the hypothesis of a procedural-learning-based component to information integration categorization.

Association Learning↗

PubMed2003

Category learning deficits in Parkinson's disease.

Sixteen patients with Parkinson's disease (PD), 15 older controls (OCs), and 109 younger controls (YCs) were compared in 2 category-learning tasks. Participants attempted to assign colored geometric figures to 1 of 2 categories. In rule-based tasks, category membership was defined by an explicit rule that was easy to verbalize, whereas in information-integration tasks, there was no salient verbal rule and accuracy was maximized only if information from 3 stimulus components was integrated at some predecisional stage. The YCs performed the best on both tasks. The PD patients were highly impaired compared with the OCs, in the rule-based categorization task but were not different from the OCs in the information-integration task. These results support the hypothesis that learning in these 2 tasks is mediated by functionally separate systems.

Aged↗