Internal state of monkey primary visual cortex (V1) predicts figure-ground perception

Abstract

When stimulus information enters the visual cortex, it is rapidly processed for identification. However, sometimes the processing of the stimulus is inadequate and the subject fails to notice the stimulus. Human psychophysical studies show that this occurs during states of inattention or absent-mindedness. At a neurophysiological level, it remains unclear what these states are. To study the role of cortical state in perception, we analyzed neural activity in the monkey primary visual cortex before the appearance of a stimulus. We show that, before the appearance of a reported stimulus, neural activity was stronger and more correlated than for a not-reported stimulus. This indicates that the strength of neural activity and the functional connectivity between neurons in the primary visual cortex participate in the perceptual processing of stimulus information. Thus, to detect a stimulus, the visual cortex needs to be in an appropriate state.

Fig. 1.

Illustration of the prestimulus screen and figure–ground display (stimulus screen) and sequence of visual stimulation. A, The prestimulus screen consisted of randomly orientated line segments. In the stimulus screen, a 90^o difference in orientation of the line segments results in a figure–ground percept. The figure could appear in one of three possible locations. Illustrations are not at scale.B, Animals started to fixate 300 msec before onset of the stimulus screen and identified the presence or absence of a figure after stimulus onset by making an eye movement toward it or maintaining fixation, respectively.

Fig. 2.

Example of a normalized average neural response obtained at a typical recording site. Time 0 equals stimulus onset. The animal started to fixate 300 msec before stimulus onset, causing an initial decrease and subsequent increase of activity. The thick line represents the average response for hits (reported figure-present trials), and the thin line represents the average response for the misses (not-reported figure-present trials). Dots represent the SEM of the reported trials response.

Fig. 3.

Prestimulus activity for reported and not-reported trials of all of the figure-present trials. A,B, Mean strength of activity during the 200 msec period after fixation (A) and during the interval of 100 msec before stimulus onset (B) for each electrode, plotted for reported trials against not-reported trials. Different symbols represent different animals.

Fig. 4.

Prestimulus activity for figure-present and figure-absent (catch) trials. A, Average activity during the epoch between −100 and 0 msec relative to stimulus onset for reported figure trials versus reported ground trials. B, Average activity during the epoch between −100 and 0 msec relative to stimulus onset for correct catch trials against incorrect catch trials. Different symbols represent different animals. C, Population data for correct and incorrect figure (Fg), ground (Gr), and catch (Ct) trials.

Fig. 5.

Quantitative relationship between prestimulus activity and detection performance. Trial-to-trial prestimulus activity was binned into eight different levels of strength, and detection performance (d′) was calculated for each of the bins. Data shown represent the average of two animals. Line is the linear regression.

Fig. 6.

Relationship between different epochs of neural responses during stimulus detection. Shown are the strengths of correlation between the mean responses levels during three periods relative to stimulus onset: −100 to 0 msec (Pre), 0 to 100 msec (Post1), and 100–200 msec (Post2).

Fig. 7.

Performance and prestimulus responses throughout the recording session. A, Each recording session was divided into 20 time slices, and percentage reported figure-present trials was calculated for each slice. A linear regression line is plotted through the data points. B, Differences in the average prestimulus activity (−100 to 0 msec) between reported figure-present trials and not-reported figure-present trials, for the first, middle, and final periods of the recording session. Error bars are SEM.

Fig. 8.

Correlated activity and behavioral response. Example of correlated firing of two neurons over time. Each pixel of the color-coded matrices depicts the normalized correlation coefficient at a particular correlation lag and time delay relative to stimulus onset. Left matrix shows data from hits (reported trials), and right matrix shows data from misses (not-reported trials). Color scale (as shown in the middle bar) is from blue (minimum) to red (maximum). The prestimulus and poststimulus neural responses are shown as PSTHs (see Fig. 2) and are plotted for comparison in black along thex-axis and y-axis. The white squares indicate the windows for the calculations of the average cross-correlograms (see Fig. 9).

Fig. 9.

Average cross-correlograms for all electrode pairs. A, The cross-correlogram for the electrode pair in Figure 8. Thick lines represent hits (reported trials), and thin lines represent the misses (not-reported trials). Dots represent SEM of the reported trials. B, Scatter plot showing the average cross-correlation coefficients (Corr. Coeff.) during the 100 msec preceding stimulus onset for incorrect trials versus correct trials for all electrode pairs. Different symbols represent different animals.