Electrophysiological correlates of learning-induced modulation of visual motion processing in humans

Abstract

Training on a visual task leads to increased perceptual and neural responses to visual features that were attended during training as well as decreased responses to neglected distractor features. However, the time course of these attention-based modulations of neural sensitivity for visual features has not been investigated before. Here we measured event related potentials (ERP) in response to motion stimuli with different coherence levels before and after training on a speed discrimination task requiring object-based attentional selection of one of the two competing motion stimuli. We found that two peaks on the ERP waveform were modulated by the strength of the coherent motion signal; the response amplitude associated with motion directions that were neglected during training was smaller than the response amplitude associated with motion directions that were attended during training. The first peak of motion coherence-dependent modulation of the ERP responses was at 300 ms after stimulus onset and it was most pronounced over the occipitotemporal cortex. The second peak was around 500 ms and was focused over the parietal cortex. A control experiment suggests that the earlier motion coherence-related response modulation reflects the extraction of the coherent motion signal whereas the later peak might index accumulation and readout of motion signals by parietal decision mechanisms. These findings suggest that attention-based learning affects neural responses both at the sensory and decision processing stages.

Keywords: event related potentials (ERP); parietal cortex; perceptual decision making; perceptual learning; visual attention.

Figure 1

Schematic representation of the stimuli during training and the experimental procedure. (A) Transparent random dot motion display used during the training sessions. One of the motion directions was task-relevant and the other direction was task-irrelevant throughout training. The different length of the arrows indicate that dot speed was different in the two intervals both, in the case of task-relevant and task-irrelavant direction. (B) The experimental protocol consisted of a training phase and two testing phases, one before and another after training. During training (six 1-h sessions), subjects performed a speed discrimination task. Before and after training, the test phase included an ERP recording session.

Figure 2

(A) Motion direction discrimination performance during the ERP recording sessions. Before training. (solid line), there was no difference between the performance in the case of task-relevant (red) and task-irrelevant (blue) directions. After training (dashed line), subjects more often reported seeing the task-relevant than the task-irrelevant direction. Data were modeled by Weibull psychometric functions. (B) Reaction times in the motion direction discrimination task. Learning led to overall reduction of reaction times after training (bars with solid outlines). There was no difference in subjects’ reaction times between task-relevant (light shaded bars) and task-irrelevant direction (dark shaded bars) neither before nor after training. Error bars indicate the SEM.

Figure 3

Grand average ERP responses shown for the PO8 (A–D) and Pz (E–H) electrodes. There was no difference between the ERP responses to the task-relevant (A,E) and task-irrelevant (B,F) directions before training. After training, the magnitude of motion signal strength dependent modulation of the ERP responses in the 300–550 ms time interval is reduced in the case of task-irrelevant direction (D,H) compared to that in the case of task-relevant direction (C,G). Different colors represent different motion coherence levels. Grey shaded bars indicate the time-windows where motion signal strength dependent modulations are most pronounced.

Figure 4

Spatial distribution of motion strength dependent modulation of the ERP responses: scalp maps of beta values related to task-relevant motion before training (the scalp map was similar to the map obtained in response to task-irrelevant motion. ). The temporal evolution of the distribution shows an early (320–360 ms) bilateral occipital and a late (480–520 ms) parietal peak.

Figure 5

Learning effects on the motion strength dependent modulation of the ERP responses. Time courses of the beta values for the task-relevant (red) and the task-irrelevant (blue) direction are shown; computed within a cluster of occipito-temporal (A) and parietal (B) electrodes. Black filled dots at the bottom of the figure indicate the intervals where beta values averaged across the two conditions are significantly different from zero (Student t-tests, corrected for multiple comparison, FDR = 0.05). Data from the time interval indicated by the vertical grey shaded bars placed at the peaks of the beta values were used for ANOVA. Red and blue shaded bands around the time courses indicate the SEM.

Figure 6

Control experiment grand average ERP waveforms during the color discrimination task (A) and the motion direction discrimination task (B) shown for the PO8 and Pz electrodes. In the case of color discrimination task (A), ERP responses differed between the 10% (grey line) and 45% (black line) motion coherence stimuli only in an early temporal interval (330 ms after stimulus onset, grey shaded bar). During the direction discrimination task (B) ERP responses to the low and high motion coherence stimuli differed in two time intervals (indicated by grey shaded bars) which closely corresponded to the two peaks of motion coherence-related modulation of the ERP responses observed in the main experiment.