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. 2010 Nov 10;30(45):15080-4.
doi: 10.1523/JNEUROSCI.5703-09.2010.

Perceptual learning increases the strength of the earliest signals in visual cortex

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Perceptual learning increases the strength of the earliest signals in visual cortex

Min Bao et al. J Neurosci. .

Abstract

Training improves performance on most visual tasks. Such perceptual learning can modify how information is read out from, and represented in, later visual areas, but effects on early visual cortex are controversial. In particular, it remains unknown whether learning can reshape neural response properties in early visual areas independent from feedback arising in later cortical areas. Here, we tested whether learning can modify feedforward signals in early visual cortex as measured by the human electroencephalogram. Fourteen subjects were trained for >24 d to detect a diagonal grating pattern in one quadrant of the visual field. Training improved performance, reducing the contrast needed for reliable detection, and also reliably increased the amplitude of the earliest component of the visual evoked potential, the C1. Control orientations and locations showed smaller effects of training. Because the C1 arises rapidly and has a source in early visual cortex, our results suggest that learning can increase early visual area response through local receptive field changes without feedback from later areas.

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Figures

Figure 1.
Figure 1.
Methods and behavioral results. A, Schematic of the RSVP task used during EEG recording. A central letter stream was presented, with letters changing at the rate of 4.17 Hz. Subjects' task was to report the presence of an “X.” Gratings were presented for 100 ms each, with a randomly varying stimulus onset asynchrony. The onsets of gratings and letters were asynchronous. Letters are not drawn to scale. B, Circles indicate the 16 possible locations for stimulus presentation. One location in each quadrant was chosen for each subject, determined by a separate C1 mapping session. C, Behavioral training curve averaged across all subjects (n = 14). Error bars are ±1 SEM. D, Percentage threshold decrease for each stimulus condition. Thresholds decreased most for the trained grating tested at the trained location.
Figure 2.
Figure 2.
Topography of the C1 component of the VEP. Cross-subject average EEG responses to the trained orientation before and after training, for subjects trained in each quadrant are shown at the mean C1 peak time [upper right visual field (VF): n = 3, upper left VF: n = 4, lower left VF: n = 4, lower right VF: n = 3]. The posterior focus of maximum amplitude (negative for upper visual field and positive for lower visual field) represents the C1 component, and shows a clear increase in amplitude following training.
Figure 3.
Figure 3.
Time course of the VEP. A, Grand average VEPs for stimuli presented in the trained quadrant [upper visual field (VF): n = 7, lower VF: n = 7]. Subjects trained in the upper and lower visual fields are presented in the upper and lower panels, respectively. Gray bars indicate the latency (70–100 ms) of the early portion of the C1 component. B, C, The effect of training on the normalized peak amplitude of the C1 for the trained orientation (TO) and untrained orientation (UO) at the trained (B) and untrained (C) locations. Error bars are ±1 SEM difference between pretraining and posttraining amplitude.

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