Unlike familiarity, recollection involves the ability to reconstruct mentally previous events that results in a strong sense of reliving. According to the reinstatement hypothesis, this specific feature emerges from the reactivation of cortical patterns involved during information exposure. Over time, the retrieval of specific details becomes more difficult, and memories become increasingly supported by familiarity judgments. The multiple trace theory (MTT) explains the gradual loss of episodic details by a transformation in the memory representation, a view that is not shared by the standard consolidation model. In this study, we tested the MTT in light of the reinstatement hypothesis. The temporal dynamics of mental imagery from long-term memory were investigated and tracked over the passage of time. Participant EEG activity was recorded during the recall of short audiovisual clips that had been watched 3 weeks, 1 day, or a few hours beforehand. The recall of the audiovisual clips was assessed using a Remember/Know/New procedure, and snapshots of clips were used as recall cues. The decoding matrices obtained from the multivariate pattern analyses revealed sustained patterns that occurred at long latencies (>500 msec poststimulus onset) that faded away over the retention intervals and that emerged from the same neural processes. Overall, our data provide further evidence toward the MTT and give new insights into the exploration of our “mind's eye.”

Earlier studies suggested that the visual system processes information at the basic level (e.g., dog) faster than at the subordinate (e.g., Dalmatian) or superordinate (e.g., animals) levels. However, the advantage of the basic category over the superordinate category in object recognition has been challenged recently, and the hierarchical nature of visual categorization is now a matter of debate. To address this issue, we used a forced-choice saccadic task in which a target and a distractor image were displayed simultaneously on each trial and participants had to saccade as fast as possible toward the image containing animal targets based on different categorization levels. This protocol enables us to investigate the first 100–120 msec, a previously unexplored temporal window, of visual object categorization. The first result is a surprising stability of the saccade latency (median RT ∼155 msec) regardless of the animal target category and the dissimilarity of target and distractor image sets. Accuracy was high (around 80% correct) for categorization tasks that can be solved at the superordinate level but dropped to almost chance levels for basic level categorization. At the basic level, the highest accuracy (62%) was obtained when distractors were restricted to another dissimilar basic category. Computational simulations based on the saliency map model showed that the results could not be predicted by pure bottom–up saliency differences between images. Our results support a model of visual recognition in which the visual system can rapidly access relatively coarse visual representations that provide information at the superordinate level of an object, but where additional visual analysis is required to allow more detailed categorization at the basic level.

We report results from two experiments in which subjects had to categorize briefly presented upright or inverted natural scenes. In the first experiment, subjects decided whether images contained animals or human faces presented at different scales. Behavioral results showed virtually identical processing speed between the two categories and very limited effects of inversion. One type of event-related potential (ERP) comparison, potentially capturing low-level physical differences, showed large effects with onsets at about 150 msec in the animal task. However, in the human face task, those differences started as early as 100 msec. In the second experiment, subjects responded to close-up views of animal faces or human faces in an attempt to limit physical differences between image sets. This manipulation almost completely eliminated small differences before 100 msec in both tasks. But again, despite very similar behavioral performances and short reaction times in both tasks, human faces were associated with earlier ERP differences compared with animal faces. Finally, in both experiments, as an alternative way to determine processing speed, we compared the ERP with the same images when seen as targets and nontargets in different tasks. Surprisingly, all task-dependent ERP differences had relatively long latencies. We conclude that task-dependent ERP differences fail to capture object processing speed, at least for some categories like faces. We discuss models of object processing that might explain our results, as well as alternative approaches.

Experiments investigating the mechanisms involved in visual processing often fail to separate low-level encoding mechanisms from higher-level behaviorally relevant ones. Using an alternating dual-task event-related potential (ERP) experimental paradigm (animals or vehicles categorization) where targets of one task are intermixed among distractors of the other, we show that visual categorization of a natural scene involves different mechanisms with different time courses: a perceptual, task-independent mechanism, followed by a task-related, category-independent process. Although average ERP responses reflect the visual category of the stimulus shortly after visual processing has begun (e.g. 75-80 msec), this difference is not correlated with the subject's behavior until 150 msec poststimulus.