Updating Contextual Sensory Expectations for Adaptive Behavior

Abstract

The brain has the extraordinary capacity to construct predictive models of the environment by internalizing statistical regularities in the sensory inputs. The resulting sensory expectations shape how we perceive and react to the world; at the neural level, this relates to decreased neural responses to expected than unexpected stimuli ("expectation suppression"). Crucially, expectations may need revision as context changes. However, existing research has often neglected this issue. Further, it is unclear whether contextual revisions apply selectively to expectations relevant to the task at hand, hence serving adaptive behavior. The present fMRI study examined how contextual visual expectations spread throughout the cortical hierarchy as we update our beliefs. We created a volatile environment: two alternating contexts contained different sequences of object images, thereby producing context-dependent expectations that needed revision when the context changed. Human participants of both sexes attended a training session before scanning to learn the contextual sequences. The fMRI experiment then tested for the emergence of contextual expectation suppression in two separate tasks, respectively, with task-relevant and task-irrelevant expectations. Effects of contextual expectation emerged progressively across the cortical hierarchy as participants attuned themselves to the context: expectation suppression appeared first in the insula, inferior frontal gyrus, and posterior parietal cortex, followed by the ventral visual stream, up to early visual cortex. This applied selectively to task-relevant expectations. Together, the present results suggest that an insular and frontoparietal executive control network may guide the flexible deployment of contextual sensory expectations for adaptive behavior in our complex and dynamic world.SIGNIFICANCE STATEMENT The world is structured by statistical regularities, which we use to predict the future. This is often accompanied by suppressed neural responses to expected compared with unexpected events ("expectation suppression"). Crucially, the world is also highly volatile and context-dependent: expected events may become unexpected when the context changes, thus raising the crucial need for belief updating. However, this issue has generally been neglected. By setting up a volatile environment, we show that expectation suppression emerges first in executive control regions, followed by relevant sensory areas, only when observers use their expectations to optimize behavior. This provides surprising yet clear evidence on how the brain controls the updating of sensory expectations for adaptive behavior in our ever-changing world.

Keywords: belief updating; context; cortical hierarchy; sensory expectation; statistical learning; structure learning.

Figure 1.

General experimental design and procedure. A, Image transition matrix determining image pairs. Two leading images (L1-L2) and four trailing images (T1-T4) were randomly sampled for each participant and session. The expectation manipulation consisted of a repeated pairing of images: each leading image predicted the identity of its two paired trailing images with 40% reliability, respectively (expected condition in orange); any other trailing image occurred with 10% reliability (unexpected condition in purple). Further, we created two contexts: the set of image associations presented in Context 1 (blue) were reversed in Context 2 (green). Thus, the image pairs that were expected in one context became unexpected in the other context and vice versa. B, General run structure across tasks. The two contexts (C1 and C2) were presented over blocks of 32 trials (24 expected, 8 unexpected). Each run contained four context blocks (two per type) in alternating order. To evaluate how contextual expectation effects emerged as a function of context start, we created 8 bins for each context block. Each context bin contained 3 expected and 1 unexpected trial. In summary, collapsing across context type, the study conformed to a 2 (expectation: expected/unexpected) × 8 (bin since context start) repeated-measures design. C, General trial structure across tasks. At the beginning of a context block, a 2 s context cue (i.e., color of the fixation point) signaled context type. Within a context block, each trial presented a leading image followed by a trailing image (each image duration: 500 ms; no ISI). Within the ITI, participants provided their response, depending on the task (see Experimental procedure: fMRI).

Figure 2.

Behavioral effects of contextual expectation in the categorization task. Across participants' mean (±SEM) RTs across the three experiments: A, in the fMRI experiment; B, in the supplementary structure learning experiment; and C, in the supplementary incidental exposure experiment. Top row plots data as function of expectation (expected, orange; unexpected, purple) and bin (1-8) since the start of a context block. Bottom row plots the same data as a function of expectation and context half (first half, bins 1:4/second half, bins 5:8). After structure learning (A,B), participants responded faster in expected relative to unexpected trials in the second context half; such effect was not present during incidental exposure (C). *p < 0.05. **p < 0.01. ***p < 0.001.

Figure 3.

Neural effects of contextual expectation in the categorization task. A, Across participants' mean (±SEM) % signal change relative to baseline for each ROI as function of expectation (expected, orange; unexpected, purple) and bin (1-8) since the start of a context block. B, Same data plotted as a function of expectation and context half (first half, bins 1:4/second half, bins 5:8). C, Expectation suppression (i.e., unexpected > expected) in the second context half (bins 5:8) relative to the first context half (bins 1:4), overlaid on the MNI152 2 mm template. Colors represent the parameter estimates: red-yellow clusters represent expectation suppression; opacity represents the associated z statistics. Black contours outline statistically significant clusters (p < 0.05 cluster-corrected). Expectation suppression emerged in the second context half in three widespread networks: ventral visual stream (EVC, early visual cortex; LOC, lateral occipital complex), frontoparietal executive control network (SPL, superior parietal lobule; IFG, inferior frontal gyrus), and salience network (INS, insula; ACC, anterior cingulate cortex). a.u., Arbitrary units. *p < 0.05. **p < 0.01.

Figure 4.

Expectation suppression profile across the cortical hierarchy in the categorization task. A, Across participants' mean (±SEM) expectation suppression profile for each ROI. The regression line in black is derived from the across participants' mean linear regression parameters (i.e., slope and intercept). The estimated regression slopes (b) were significantly >0 for all ROIs, indicating an increase of expectation suppression over the course of the context block (see across participants' mean b and p value in each subplot). B, Suppression point for each expectation suppression profile (colored dot with black contour), showing that expectation suppression emerged at different moments across the cortical hierarchy: first in the insula (INS), followed by inferior frontal gyrus (IFG), superior parietal lobule (SPL), lateral occipital complex (LOC) and finally early visual cortex (EVC). C, The suppression points in INS and IFG appeared significantly earlier than the suppression points in EVC and LOC. a.u., Arbitrary units.

Figure 5.

Neural effects of contextual expectation in the oddball task. A, Across participants' mean (±SEM) % signal change relative to baseline for each ROI as function of expectation (expected, orange; unexpected, purple) and bin (1-8) since the start of a context block. B, Same data plotted as a function of expectation and context half (first half, bins 1:4/second half, bins 5:8). C, Expectation suppression (i.e., unexpected > expected) in the second context half (bins 5:8) relative to the first context half (bins 1:4), overlaid on the MNI152 2 mm template. Colors represent the parameter estimates: red-yellow clusters represent expectation suppression; opacity represents the associated z statistics. We did not observe expectation suppression in either the ROI analysis or at the whole-brain level. a.u., Arbitrary units. *p < 0.05.