Top-down attention switches coupling between low-level and high-level areas of human visual cortex

Abstract

Top-down attention is an essential cognitive ability, allowing our finite brains to process complex natural environments by prioritizing information relevant to our goals. Previous evidence suggests that top-down attention operates by modulating stimulus-evoked neural activity within visual areas specialized for processing goal-relevant information. We show that top-down attention also has a separate influence on the background coupling between visual areas: adopting different attentional goals resulted in specific patterns of noise correlations in the visual system, whereby intrinsic activity in the same set of low-level areas was shared with only those high-level areas relevant to the current goal. These changes occurred independently of evoked activity, persisted without visual stimulation, and predicted behavioral success in deploying attention better than the modulation of evoked activity. This attentional switching of background connectivity suggests that attention may help synchronize different levels of the visual processing hierarchy, forming state-dependent functional pathways in human visual cortex to prioritize goal-relevant information.

Fig. 1.

Study overview. (A) We hypothesize that top-down attention to an object category enhances interactions between retinotopic areas in occipital cortex selective for low-level features and the area of ventral temporal cortex selective for the attended category. (B) Attention was directed to the face or scene component of composite stimuli. Time series for each attentional state were extracted from all ROIs (example subject, dark green). Stimulus-evoked responses (gray) were projected from the time series, isolating spontaneous fluctuations (light green). We analyze whether correlations of these fluctuations between occipital and temporal ROIs depend on attentional state.

Fig. 2.

Background connectivity. (A) Background connectivity between V4 and ventral temporal ROIs was state dependent: V4 correlated more strongly with FFA under face attention and with PPA under scene attention. (B) The magnitude of this interaction [modulation = ([FFA_face − FFA_scene] + [PPA_scene − PPA_face])/2] was an excellent predictor of behavioral accuracy. (C) The interaction also occurred to varying degrees in other retinotopic areas of occipital cortex. Error bars in all figures are within-subject SEMs (25).

Fig. 3.

FFA/PPA evoked-responses vs. connectivity with V4. We observed a double dissociation between evoked responses and attentional modulation of background connectivity (i.e., correlations after removing evoked responses). First, modulation of background connectivity was robust during nonstimulated volumes between blocks when there were no evoked responses. Second, FFA/PPA showed evoked responses when they were goal-irrelevant (FFA during scene attention, PPA during face attention) but no increase in connectivity relative to rest.

Fig. 4.

Analysis stages. (A) Each stage shown in a row, with analyses to the right performed on residuals from that stage. (B) Sources of variance in the residuals of current stage. (C) Mean evoked responses across blocks, with proportions of variance explained by average block response. (D) V4-FFA/PPA correlations. Despite the large reduction in the variance explained by evoked responses across analysis stages, there are negligible changes in the attentional modulation of V4 connectivity (main effect of reduced correlations, but no change in the ROI × state interaction; see text). This suggests that attentional modulation of connectivity does not depend on stimulus responses but rather on spontaneous activity commonly used to measure intrinsic brain networks at rest.