One Thing Leads to Another: Anticipating Visual Object Identity Based on Associative-Memory Templates

Neural Mechanisms Determining the Duration of Task-free, Self-paced Visual Perception

Humans spend hours each day spontaneously engaging with visual content, free from specific tasks and at their own pace. Currently, the brain mechanisms determining the duration of self-paced perceptual behavior remain largely unknown. Here, participants viewed naturalistic images under task-free settings and self-paced each image's viewing duration while undergoing EEG and pupillometry recordings. Across two independent data sets, we observed large inter- and intra-individual variability in viewing duration. However, beyond an image's presentation order and category, specific image content had no consistent effects on spontaneous viewing duration across participants. Overall, longer viewing durations were associated with sustained enhanced posterior positivity and anterior negativity in the ERPs. Individual-specific variations in the spontaneous viewing duration were consistently correlated with evoked EEG activity amplitudes and pupil size changes. By contrast, presentation order was selectively correlated with baseline alpha power and baseline pupil size. Critically, spontaneous viewing duration was strongly predicted by the temporal stability in neural activity patterns starting as early as 350 msec after image onset, suggesting that early neural stability is a key predictor for sustained perceptual engagement. Interestingly, neither bottom-up nor top-down predictions about image category influenced spontaneous viewing duration. Overall, these results suggest that individual-specific factors can influence perceptual processing at a surprisingly early time point and influence the multifaceted ebb and flow of spontaneous human perceptual behavior in naturalistic settings.

Learned associations serve as target proxies during difficult but not easy visual search

The target template contains information in memory that is used to guide attention during visual search and is typically thought of as containing features of the actual target object. However, when targets are hard to find, it is advantageous to use other information in the visual environment that is predictive of the target's location to help guide attention. The purpose of these studies was to test if newly learned associations between face and scene category images lead observers to use scene information as a proxy for the face target. Our results showed that scene information was used as a proxy for the target to guide attention but only when the target face was difficult to discriminate from the distractor face; when the faces were easy to distinguish, attention was no longer guided by the scene unless the scene was presented earlier. The results suggest that attention is flexibly guided by both target features as well as features of objects that are predictive of the target location. The degree to which each contributes to guiding attention depends on the efficiency with which that information can be used to decode the location of the target in the current moment. The results contribute to the view that attentional guidance is highly flexible in its use of information to rapidly locate the target.

Cue predictiveness and uncertainty determine cue representation during visual statistical learning

This study investigated how humans process probabilistic-associated information when encountering varying levels of uncertainty during implicit visual statistical learning. A novel probabilistic cueing validation paradigm was developed to probe the representation of cues with high (75% probability), medium (50%), low (25%), or zero levels of predictiveness in response to preceding targets that appeared with high (75%), medium (50%), or low (25%) transitional probabilities (TPs). Experiments 1 and 2 demonstrated a significant negative association between cue probe identification accuracy and cue predictiveness when these cues appeared after high-TP but not medium-TP or low-TP targets, establishing exploration-like cue processing triggered by lower-uncertainty rather than high-uncertainty inputs. Experiment 3 ruled out the confounding factor of probe repetition and extended this finding by demonstrating (1) enhanced representation of low-predictive and zero-predictive but not high-predictive cues across blocks after high-TP targets and (2) enhanced representation of high-predictive but not low-predictive and zero-predictive cues across blocks after low-TP targets for learners who exhibited above-chance awareness of cue-target transition. These results suggest that during implicit statistical learning, input characteristics alter cue-processing mechanisms, such that exploration-like and exploitation-like mechanisms are triggered by lower-uncertainty and higher-uncertainty cue-target sequences, respectively.

The relation between implicit statistical learning and proactivity as revealed by EEG

Environmental events often occur on a probabilistic basis but can sometimes be predicted based on specific cues and thus approached proactively. Incidental statistical learning enables the acquisition of knowledge about probabilistic cue-target contingencies. However, the neural mechanisms of statistical learning about contingencies (SLC), the required conditions for successful learning, and the role of implicit processes in the resultant proactive behavior are still debated. We examined changes in behavior and cortical activity during an SLC task in which subjects responded to visual targets. Unbeknown to them, there were three types of target cues associated with high-, low-, and zero target probabilities. About half of the subjects spontaneously gained explicit knowledge about the contingencies (contingency-aware group), and only they showed evidence of proactivity: shortened response times to predictable targets and enhanced event-related brain responses (cue-evoked P300 and contingent negative variation, CNV) to high probability cues. The behavioral and brain responses were strictly associated on a single-trial basis. Source reconstruction of the brain responses revealed activation of fronto-parietal brain regions associated with cognitive control, particularly the anterior cingulate cortex and precuneus. We also found neural correlates of SLC in the contingency-unaware group, but these were restricted to post-target latencies and visual association areas. Our results document a qualitative difference between explicit and implicit learning processes and suggest that in certain conditions, proactivity may require explicit knowledge about contingencies.

Tuning to non-veridical features in attention and perceptual decision-making: An EEG study

When searching for a lost item, we tune attention to the known properties of the object. Previously, it was believed that attention is tuned to the veridical attributes of the search target (e.g., orange), or an attribute that is slightly shifted away from irrelevant features towards a value that can more optimally distinguish the target from the distractors (e.g., red-orange; optimal tuning). However, recent studies showed that attention is often tuned to the relative feature of the search target (e.g., redder), so that all items that match the relative features of the target equally attract attention (e.g., all redder items; relational account). Optimal tuning was shown to occur only at a later stage of identifying the target. However, the evidence for this division mainly relied on eye tracking studies that assessed the first eye movements. The present study tested whether this division can also be observed when the task is completed with covert attention and without moving the eyes. We used the N2pc in the EEG of participants to assess covert attention, and found comparable results: Attention was initially tuned to the relative colour of the target, as shown by a significantly larger N2pc to relatively matching distractors than a target-coloured distractor. However, in the response accuracies, a slightly shifted, "optimal" distractor interfered most strongly with target identification. These results confirm that early (covert) attention is tuned to the relative properties of an item, in line with the relational account, while later decision-making processes may be biased to optimal features.

Humans predict the forest, not the trees: statistical learning of spatiotemporal structure in visual scenes

The human brain is capable of using statistical regularities to predict future inputs. In the real world, such inputs typically comprise a collection of objects (e.g. a forest constitutes numerous trees). The present study aimed to investigate whether perceptual anticipation relies on lower-level or higher-level information. Specifically, we examined whether the human brain anticipates each object in a scene individually or anticipates the scene as a whole. To explore this issue, we first trained participants to associate co-occurring objects within fixed spatial arrangements. Meanwhile, participants implicitly learned temporal regularities between these displays. We then tested how spatial and temporal violations of the structure modulated behavior and neural activity in the visual system using fMRI. We found that participants only showed a behavioral advantage of temporal regularities when the displays conformed to their previously learned spatial structure, demonstrating that humans form configuration-specific temporal expectations instead of predicting individual objects. Similarly, we found suppression of neural responses for temporally expected compared with temporally unexpected objects in lateral occipital cortex only when the objects were embedded within expected configurations. Overall, our findings indicate that humans form expectations about object configurations, demonstrating the prioritization of higher-level over lower-level information in temporal expectation.

Be there on time: Spatial-temporal regularities guide young children's attention in dynamic environments

Children's ability to benefit from spatiotemporal regularities to detect goal-relevant targets was tested in a dynamic, extended context. Young adults and children (from a low-deprivation area school in the United Kingdom; N = 80; 5-6 years; 39 female; ethics approval did not permit individual-level race/ethnicity surveying) completed a dynamic visual-search task. Targets and distractors faded in and out of a display over seconds. Half of the targets appeared at predictable times and locations. Search performance in children was poorer overall. Nevertheless, they benefitted equivalently from spatiotemporal regularities, detecting more predictable than unpredictable targets. Children's benefits from predictions correlated positively with their attention. The study brings ecological validity to the study of attentional guidance in children, revealing striking behavioral benefits of dynamic experience-based predictions.

High-pass filtering artifacts in multivariate classification of neural time series data

BACKGROUND

Traditionally, EEG/MEG data are high-pass filtered and baseline-corrected to remove slow drifts. Minor deleterious effects of high-pass filtering in traditional time-series analysis have been well-documented, including temporal displacements. However, its effects on time-resolved multivariate pattern classification analyses (MVPA) are largely unknown.

NEW METHOD

To prevent potential displacement effects, we extend an alternative method of removing slow drift noise - robust detrending - with a procedure in which we mask out all cortical events from each trial. We refer to this method as trial-masked robust detrending.

RESULTS

In both real and simulated EEG data of a working memory experiment, we show that both high-pass filtering and standard robust detrending create artifacts that result in the displacement of multivariate patterns into activity silent periods, particularly apparent in temporal generalization analyses, and especially in combination with baseline correction. We show that trial-masked robust detrending is free from such displacements.

COMPARISON WITH EXISTING METHOD(S)

Temporal displacement may emerge even with modest filter cut-off settings such as 0.05 Hz, and even in regular robust detrending. However, trial-masked robust detrending results in artifact-free decoding without displacements. Baseline correction may unwittingly obfuscate spurious decoding effects and displace them to the rest of the trial.

CONCLUSIONS

Decoding analyses benefit from trial-masked robust detrending, without the unwanted side effects introduced by filtering or regular robust detrending. However, for sufficiently clean data sets and sufficiently strong signals, no filtering or detrending at all may work adequately. Implications for other types of data are discussed, followed by a number of recommendations.

Dissociable neural indices for time and space estimates during virtual distance reproduction

The perception and measurement of spatial and temporal dimensions have been widely studied. Yet, whether these two dimensions are processed independently is still being debated. Additionally, whether EEG components are uniquely associated with time or space, or whether they reflect a more general measure of magnitude quantity remains unknown. While undergoing EEG, subjects performed a virtual distance reproduction task, in which they were required to first walk forward for an unknown distance or time, and then reproduce that distance or time. Walking speed was varied between estimation and reproduction phases, to prevent interference between distance or time in each estimate. Behaviorally, subject performance was more variable when reproducing time than when reproducing distance, but with similar patterns of accuracy. During estimation, EEG data revealed the contingent negative variation (CNV), a measure previously associated with timing and expectation, tracked the probability of the upcoming interval, for both time and distance. However, during reproduction, the CNV exclusively oriented to the upcoming temporal interval at the start of reproduction, with no change across spatial distances. Our findings indicate that time and space are neurally separable dimensions, with the CNV both serving a supramodal role in temporal and spatial expectation, yet an exclusive role in preparing duration reproduction.

Functional biases in attentional templates from associative memory

In everyday life, attentional templates—which facilitate the perception of task-relevant sensory inputs—are often based on associations in long-term memory. We ask whether templates retrieved from memory are necessarily faithful reproductions of the encoded information or if associative-memory templates can be functionally adapted after retrieval in service of current task demands. Participants learned associations between four shapes and four colored gratings, each with a characteristic combination of color (green or pink) and orientation (left or right tilt). On each trial, observers saw one shape followed by a grating and indicated whether the pair matched the learned shape-grating association. Across experimental blocks, we manipulated the types of nonmatch (lure) gratings most often presented. In some blocks the lures were most likely to differ in color but not tilt, whereas in other blocks this was reversed. If participants functionally adapt the retrieved template such that the distinguishing information between lures and targets is prioritized, then they should overemphasize the most commonly diagnostic feature dimension within the template. We found evidence for this in the behavioral responses to the lures: participants were more accurate and faster when responding to common versus rare lures, as predicted by the functional—but not the strictly veridical—template hypothesis. This shows that templates retrieved from memory can be functionally biased to optimize task performance in a flexible, context-dependent, manner.

Temporal Expectations Prepare Visual Working Memory for Behavior

Working memory enables us to retain past sensations in service of anticipated task demands. How we prepare for anticipated task demands during working memory retention remains poorly understood. Here, we focused on the role of time—asking how temporal expectations help prepare for ensuing memory-guided behavior. We manipulated the expected probe time in a delayed change-detection task and report that temporal expectation can have a profound influence on memory-guided behavioral performance. EEG measurements corroborated the utilization of temporal expectations: demonstrating the involvement of a classic EEG signature of temporal expectation—the contingent negative variation—in the context of working memory. We also report the influence of temporal expectations on 2 EEG signatures associated with visual working memory—the lateralization of 8- to 12-Hz alpha activity, and the contralateral delay activity. We observed a dissociation between these signatures, whereby alpha lateralization (but not the contralateral delay activity) adapted to the time of expected memory utilization. These data show how temporal expectations prepare visual working memory for behavior and shed new light on the electrophysiological markers of both temporal expectation and working memory.