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Sparse coding and challenges for Bayesian models of the brain
Thomas Trappenberg, Paul Hollensen
Journal:

Behavioral and Brain Sciences / Volume 36 / Issue 3 / June 2013

Published online by Cambridge University Press:

10 May 2013, pp. 232-233
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While the target article provides a glowing account for the excitement in the field, we stress that hierarchical predictive learning in the brain requires sparseness of the representation. We also question the relation between Bayesian cognitive processes and hierarchical generative models as discussed by the target article.

12 - Cognitive neuroscience
from Part III - Research programs
- By Dominic Standage, Thomas Trappenberg
Edited by Keith Frankish, The Open University, Milton Keynes, William Ramsey, University of Nevada, Las Vegas
Book:

The Cambridge Handbook of Cognitive Science

Published online:

05 August 2012

Print publication:

19 July 2012, pp -
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Summary

This chapter surveys some recent philosophical and empirical work on the nature and structure of action, on conscious agency, and on our knowledge of actions. By reuniting the causal approach with the rational approach, the causalists opened the way for a naturalistic stance in action theory and thus for an integration of philosophical and scientific enquiries. Many philosophers introduce a conception of intentions as distinctive, sui generis, mental states. Intentions are responsible for triggering or initiating the intended action (initiating function) and for guiding its course until completion. Dual-intention theories provide a partial answer to the problem of causal deviance. The chapter concentrates on the functional architecture of motor cognition, introducing some of the theoretical concepts, models, and hypotheses that play a central role in current thinking in the motor domain and are of particular relevance for philosophical theorizing on action.

Generating oculomotor and neuronal behavior in a neural field model of the superior colliculus
Thomas P. Trappenberg, Raymond M. Klein
Journal:

Behavioral and Brain Sciences / Volume 22 / Issue 4 / August 1999

Published online by Cambridge University Press:

01 August 1999, pp. 700-701
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The functional schema in the Findlay & Walker target article presents an understanding of oculomotor behavior primarily at an algorithmic level of analysis. Although such an analysis is an important first step, present knowledge of the neuroscientific substrate for oculomotor behavior is sufficiently advanced to support, if not warrant, computationally explicit models explaining how oculomotor behavior is implemented by this substrate. The literature contains a growing number of examples of this strategy, which we illustrate using our work.

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