Note that a forward prediction generates a sensory expectation, or in the terminology of the attentional literature, a selective attentional gain applied to the expected sensory features (and/or suppression of irrelevant features). Thus, forward predictions generated via motor commands can function as a top-down attentional modulation of sensory systems. Such attentional modulation may be important for sensory feedback control because it

sharpens the perceptual acuity of the sensory system to the relevant range of expected inputs (see below). This “attentional” mechanism might then be easily co-opted for motor-directed modulation of the perception of others’ speech, which Bortezomib cell line would be especially useful

under noisy listening conditions, thus explaining the motor speech-induced effects of perception as summarized above. On the face of it, there seems to be a tension between error correction and selective attention. One the one hand, selective attention increases perceptual detectability to attended features and decreases detectability to unattended features. On the other hand, for error correction the system needs to be able to detect deviations from the expected (attended) pattern. However, these two computational effects are not OSI-906 supplier mutually exclusive. Suppose selective attention in this context both increases the gain of the response in networks tuned to the attended units and sharpens the tuning selectivity for the relevant features (Figure 5). The increased Rutecarpine gain will result in facilitation of detection of the presence of expected (attended) features, whereas the sharpened tuning curve may make deviations from the expectation more salient.

The idea that attention can modulate gain is well established (Boynton, 2005, McAdams and Maunsell, 1999, Moran and Desimone, 1985, Reynolds et al., 1999, Reynolds and Heeger, 2009, Treue and Martínez Trujillo, 1999 and Treue and Maunsell, 1999). Whether attention can sharpen the tuning properties of neurons is less well established although limited evidence exists (Murray and Wojciulik, 2004 and Spitzer et al., 1988). An alternative approach to explaining how selective attention could both enhance detection of deviation from an expected target and enhance detection of the presence of the expected target comes from recent work on the nature of the gain modulation induced by selective attention. The traditional view is that attention to a given feature increases the gain of neurons that are selective for that feature, and this model works well for detecting the presence of a stimulus or for making coarse discriminations.