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Comparative Study
. 2008 Jan;98(1):11-8.
doi: 10.1007/s00422-007-0202-0. Epub 2007 Dec 14.

Attractor models of working memory and their modulation by reward

Affiliations
Comparative Study

Attractor models of working memory and their modulation by reward

Justin R Chumbley et al. Biol Cybern. 2008 Jan.

Abstract

This work reports an empirical examination of two key issues in theoretical neuroscience: distractibility in the context of working memory (WM) and its reward dependence. While these issues have been examined fruitfully in isolation (e.g. Macoveanu et al. in Biol Cybern 96(4): 407-19, 2007), we address them here in tandem, with a focus on how distractibility and reward interact. In particular, we parameterise an observation model that embodies the nonlinear form of such interactions, as described in a recent neuronal network model (Gruber et al. in J Comput Neurosci 20:153-166, 2006). We observe that memory for a target stimulus can be corrupted by distracters in the delay period. Interestingly, in contrast to our theoretical predictions, this corruption was only partial. Distracters do not simply overwrite target; rather, a compromise is reached between target and distracter. Finally, we observed a trend towards a reduced distractibility under conditions of high reward. We discuss the implications of these findings for theoretical formulations of basal and dopamine (DA)-modulated neural bump- attractor networks of working memory.

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Figures

Fig. 1
Fig. 1
Model architecture assumed by Gruber et al. (2006)
Fig. 2
Fig. 2
The DD-curve under basal conditions
Fig. 3
Fig. 3
Modulation of the DD-curve. The inner curve has contracted under high DA
Fig. 4
Fig. 4
Dependence of the DD-curve on parameters
Fig. 5
Fig. 5
Conditional model fit, as specified by the marginal MAP estimates of the model parameters, together with data. The inner curve describes the high-reward condition
Fig. 6
Fig. 6
The marginal posterior over the slope parameter c. We see very strong evidence that the slope is greater than zero (i.e. there is a deviance-distracter effect). Interestingly we can be 89.2% certain that this slope is less than one; this is the value predicted by a winner-takes-all mechanism
Fig. 7
Fig. 7
The marginal posterior over the reward modulation parameter b. We see moderate evidence (85.5% posterior probability) that behavioural responses to distraction were contracted into a smaller range in trials with high potential reward (1 pound as opposed to 0.01 pounds)

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