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Why skill matters - PubMed

Why skill matters

Okihide Hikosaka et al. Trends Cogn Sci. 2013 Sep.

Abstract

Maximizing rewards per unit time is ideal for success and survival in humans and animals. This goal can be approached by speeding up behavior aiming at rewards and this is done most efficiently by acquiring skills. Importantly, reward-directed skills consist of two components: finding a good object (i.e., object skill) and acting on the object (i.e., action skill), which occur sequentially. Recent studies suggest that object skill is based on high-capacity memory for object-value associations. When a learned object is encountered the corresponding memory is quickly expressed as a value-based gaze bias, leading to the automatic acquisition or avoidance of the object. Object skill thus plays a crucial role in increasing rewards per unit time.

Keywords: Object–value memory; automaticity; gaze; reward delay; saccade; stable value.

Published by Elsevier Ltd.

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Figures

Figure 1
Figure 1

Two kinds of reward delay affecting reward value – hypothetical tasks. A: External delay. In front of you (as a subject) are two buttons, E and L. If you press button E, you will get a drop of juice 1 second later. If you press button L, you will get a drop of juice 5 seconds later. After you have consumed the drop of juice, you can press the button again. Shown here are two extreme cases: you continue to press button E, or continue to press button L. The amount of reward per unit time is larger in the former case. B: Internal delay. In front of you are two buttons, F and S. They are located differently so that you can reach button F in 1 second and button S in 5 seconds. Once you press either button, you will get a drop of juice 1 second later.

Figure 2
Figure 2

Internal reward delay can be shortened. A: Motivation or skill shortens internal reward delay by shortening own behavior. B: Two kinds of skill that shorten reward delay.

Figure 3
Figure 3

Fractal objects that one monkey experienced for a long time with biased rewards (n=288). In each row of eight fractals, the left four fractals were high-valued objects (consistently associated with a large reward) and the right four fractals were low-valued objects (consistently associated with a small reward). Reproduced from [65].

Figure 4
Figure 4

Object skill expressed as automatic gaze bias. A: Procedure for learning stable values of visual objects. Half of the objects were associated with a reward (high-valued objects) and the other associated with no (or a small) reward (low-valued objects). B: Free viewing procedure for testing the value-based gaze bias. On each trial, 4 fractal objects were chosen pseudo-randomly from a set of 8 learned objects (A), were presented simultaneously, and the monkey freely looked at them, but no reward was delivered. Shown here are examples of saccade trajectories. The monkey tended to look at high-valued objects (denoted as ‘H’). (C, D) The percentage of the gaze duration on each object before (C) and after (D) the long-term learning. Red and blue indicated high- and low-valued objects. Reproduced from [63].

Figure Box 1
Figure Box 1

Basal ganglia circuit that supports object skill. Neurons in the monkey CDt receives inputs from the temporal visual cortices and respond to visual objects differentially. Their responses are modulated by the stable (not flexible) values of the visual objects. Neurons in the SNr, which receive inputs from the CDt directly or indirectly, categorize visual objects into high- and low-valued objects. Their stable value signals are then sent to the SC, thereby biasing gaze toward high-valued objects. Arrows indicate excitatory connections (or effects). Lines with circular dots indicate inhibitory connections. Solid and hatched lines indicate direct and indirect connections, respectively.

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