Evidence of Serial Dependence from Decoding of Visual Evoked Potentials

Interpersonal prior information informs ensemble coding through the co-representation process

Humans have the ability to rapidly extract summary statistics from object groupings through a specific capability known as ensemble coding. Previous literature has reported that this ability can become biased by prior perceptual experiences at the individual level. However, it remains unknown whether interpersonal prior information could also bias ensemble perception through a co-representation process. Experiment 1 found that participants' summary estimations were biased toward their co-actor's stimuli. Experiment 2 confirmed a causal relationship between the bias effect and the co-representation process by showing a reduction in biased estimation after pairing participants with an out-group partner. These findings extend the sources of prior information exploited by humans during perceptual average from individual-level information (i.e., self-tasks) to interpersonal-level information (i.e., co-actor's tasks). More specifically, interpersonal prior information is shown to act in a top-down and implicit manner, biasing ensemble perception.

Serial Dependence in Perception

Much evidence has shown that perception is biased towards previously presented similar stimuli, an effect recently termed serial dependence. Serial dependence affects nearly every aspect of perception, often causing gross perceptual distortions, especially for weak and ambiguous stimuli. Despite unwanted side-effects, empirical evidence and Bayesian modeling show that serial dependence acts to improve efficiency and is generally beneficial to the system. Consistent with models of predictive coding, the Bayesian priors of serial dependence are generated at high levels of cortical analysis, incorporating much perceptual experience, but feed back to lower sensory areas. These feedback loops may drive oscillations in the alpha range, linked strongly with serial dependence. The discovery of top-down predictive perceptual processes is not new, but the new, more quantitative approach characterizing serial dependence promises to lead to a deeper understanding of predictive perceptual processes and their underlying neural mechanisms.

Neural mechanisms of sequential dependence in time perception: the impact of prior task and memory processing

Our perception and decision-making are susceptible to prior context. Such sequential dependence has been extensively studied in the visual domain, but less is known about its impact on time perception. Moreover, there are ongoing debates about whether these sequential biases occur at the perceptual stage or during subsequent post-perceptual processing. Using functional magnetic resonance imaging, we investigated neural mechanisms underlying temporal sequential dependence and the role of action in time judgments across trials. Participants performed a timing task where they had to remember the duration of green coherent motion and were cued to either actively reproduce its duration or simply view it passively. We found that sequential biases in time perception were only evident when the preceding task involved active duration reproduction. Merely encoding a prior duration without reproduction failed to induce such biases. Neurally, we observed activation in networks associated with timing, such as striato-thalamo-cortical circuits, and performance monitoring networks, particularly when a "Response" trial was anticipated. Importantly, the hippocampus showed sensitivity to these sequential biases, and its activation negatively correlated with the individual's sequential bias following active reproduction trials. These findings highlight the significant role of memory networks in shaping time-related sequential biases at the post-perceptual stages.

Spatial correspondence in relative space regulates serial dependence

Our perception is often attracted to what we have seen before, a phenomenon called 'serial dependence.' Serial dependence can help maintain a stable perception of the world, given the statistical regularity in the environment. If serial dependence serves this presumed utility, it should be pronounced when consecutive elements share the same identity when multiple elements spatially shift across successive views. However, such preferential serial dependence between identity-matching elements in dynamic situations has never been empirically tested. Here, we hypothesized that serial dependence between consecutive elements is modulated more effectively by the spatial correspondence in relative space than by that in absolute space because spatial correspondence in relative coordinates can warrant identity matching invariantly to changes in absolute coordinates. To test this hypothesis, we developed a task where two targets change positions in unison between successive views. We found that serial dependence was substantially modulated by the correspondence in relative coordinates, but not by that in absolute coordinates. Moreover, such selective modulation by the correspondence in relative space was also observed even for the serial dependence defined by previous non-target elements. Our findings are consistent with the view that serial dependence subserves object-based perceptual stabilization over time in dynamic situations.

Subspace partitioning in the human prefrontal cortex resolves cognitive interference

The human prefrontal cortex (PFC) constitutes the structural basis underlying flexible cognitive control, where mixed-selective neural populations encode multiple task features to guide subsequent behavior. The mechanisms by which the brain simultaneously encodes multiple task-relevant variables while minimizing interference from task-irrelevant features remain unknown. Leveraging intracranial recordings from the human PFC, we first demonstrate that competition between coexisting representations of past and present task variables incurs a behavioral switch cost. Our results reveal that this interference between past and present states in the PFC is resolved through coding partitioning into distinct low-dimensional neural states; thereby strongly attenuating behavioral switch costs. In sum, these findings uncover a fundamental coding mechanism that constitutes a central building block of flexible cognitive control.