Predictive brain: Addressing the level of representation by reviewing perceptual hysteresis

The computational perspective: A catalyst for research questions in cognitive neuroscience?

Where do novel research questions come from? We suggest that identifying key computational problems and comparing solutions across domains can be one source. We exemplify this by looking at perception and action and outline how findings from one domain may generate novel research avenues in the other.

Serial dependence: A matter of memory load

In serial dependence, perceptual decisions are biased towards stimuli encountered in the recent past. Here, we investigate whether and how serial dependence is affected by the availability of visual working memory (VWM) resources. In two experiments, participants reproduced the orientation of a series of stimuli. On alternating trials, we included an additional VWM task with randomly varying levels of load. Serial dependence was not only affected by the additional load task but also clearly modulated by the level of load: a high load in the previous trial reduced serial dependence while a high load in the present increased it. These results were independent of the effects of VWM load on the precision of reproduction responses. Our findings provide new insights into the mechanisms that may regulate serial dependence, revealing its intimate link with VWM resources.

Significance statement

Our perception, thoughts, and behavior are continuously influenced by recent events. For instance, the way we process and understand current visual information depends on what we have seen in the preceding seconds, a phenomenon known as serial dependence. The precise mechanisms and factors involved in serial dependence are still unclear. Here, we demonstrated that working memory resources are a crucial component. Specifically, when we are currently experiencing a heavy memory load, the influence of prior stimuli becomes stronger. Conversely, when prior stimuli were shown under a high memory load, their influence was reduced. These findings highlight the importance of working memory resources in shaping our interpretation of the present based on the recent past.

Landau model for illustrating the learning and unlearning process of nociplastic pain

Recent advancements in understanding the consolidation of nociplastic pain point to a complex, non-conscious learned process of threat perception. Neurobiological pain education is emerging as a promising approach to unlearn nociplastic pain, supported by biopsychosocial tools such as exposure to movement, mindfulness, and group sharing formats. However, this approach is still not well-known among clinicians and the society at large, creating a communication problem that unfortunately perpetuates the suffering of patients. Herein, we propose a Landau model to describe the learning and unlearning process of nociplastic pain, aiming to clarify this complex situation and facilitate communication across different sectors of the society. Nociplastic pain corresponds to a first-order transition, with attention more likely in the alert-protection state than in the trust-explore state. Two appealing results of the model are that the perception of the critical context depends on personal history regarding the symptom and that biopsychosocial loops are formed when there is alarming learned historical information about the symptom, along with confused and contradictory expert information, as seen in nocebo messages. Learning and unlearning in the model correspond to a chang in control parametrs that can weigh more on the alert-protection state, trust-explore state, uncertain state or neutral state. This description clarifies why neurobiological education is the foundational therapy from which others must be built to embody the accessible, clear, and trustworthy information.

Frequency-specific contributions to auditory perceptual priors: Testing the predictive-coding hypothesis

Perceptual priors formed by recent stimuli bias our immediate percept. These priors, expressing our implicit expectations, affect both high- and low-level processing stages. Yet, the nature of the inter-level interaction is unknown. Do priors operate top-down and bias low-level features toward recently experienced objects (predictive-coding hypothesis), or are low-level biases bottom-up driven and formed by local memory circuits? To decipher between these options in auditory perception, we used the "missing fundamental illusion", enabling the dissociation of low-level components from the high-level pitch. Surprisingly, in contrast to predictive coding, when the fundamental frequency was missing, pitch contraction across timbre categories was not found to the previously perceived high-level pitch, but to the physically present frequency. This bottom-up contribution of low-level memory components to perceptual priors, operating independently of recent high-level percepts, may stabilize the perceptual organization and underlie continuity between similar low-level features belonging to different object categories in the auditory modality.

Tuning perception and decisions to temporal context

Recent work suggests that serial dependence, where perceptual decisions are biased toward previous stimuli, arises from the prior that sensory input is temporally correlated. However, existing studies have mostly used random stimulus sequences that do not involve such temporal consistencies. Here, we manipulated the temporal statistics of visual stimuli to examine the role of true temporal correlations in serial dependence. In two experiments, observers reproduced the orientation of the last stimulus in a sequence, while we varied temporal correlations in the stimulus features at two timescales: stimulus history within the trial and decision history across trials. We found a clear dissociation: increasing temporal correlation in the stimulus history led to adaptation-like repulsive biases, whereas increasing temporal correlation in the decision history reduced attractive biases. Thus, we suggest that temporal correlation enhances the discriminative ability of the visual system, revealing the fundamental role of the broader temporal context.

Stable perceptual phenotype of the magnitude of history biases even in the face of global task complexity

According to a Bayesian framework, visual perception requires active interpretation of noisy sensory signals in light of prior information. One such mechanism, serial dependence, is thought to promote perceptual stability by assimilating current percepts with recent stimulus history. Combining a delayed orientation-adjustment paradigm with predictable (study 1) or unpredictable (study 2) task structure, we test two key predictions of this account in a novel context: first, that serial dependence should persist even in variable environments, and, second, that, within a given observer and context, this behavioral bias should be stable from one occasion to the next. Relying on data of 41 human volunteers and two separate experimental sessions, we confirm both hypotheses. Group-level, attractive serial dependence remained strong even in the face of volatile settings with multiple, unpredictable types of tasks, and, despite considerable interindividual variability, within-subject patterns of attractive and repulsive stimulus-history biases were highly stable from one experimental session to the next. In line with the hypothesized functional role of serial dependence, we propose that, together with previous work, our findings suggest the existence of a more general individual-specific fingerprint with which the past shapes current perception. Congruent with the Bayesian account, interindividual differences may then result from differential weighting of sensory evidence and prior information.

Serial dependence in visual perception: A review

How does the visual system represent continuity in the constantly changing visual input? A recent proposal is that vision is serially dependent: Stimuli seen a moment ago influence what we perceive in the present. In line with this, recent frameworks suggest that the visual system anticipates whether an object seen at one moment is the same as the one seen a moment ago, binding visual representations across consecutive perceptual episodes. A growing body of work supports this view, revealing signatures of serial dependence in many diverse visual tasks. Yet, the variety of disparate findings and interpretations calls for a more general picture. Here, we survey the main paradigms and results over the past decade. We also focus on the challenge of finding a relationship between serial dependence and the concept of "object identity," taking centuries-long history of research into account. Among the seemingly contrasting findings on serial dependence, we highlight common patterns that may elucidate the nature of this phenomenon and attempt to identify questions that are unanswered.

Flexible top-down control in the interaction between working memory and perception

Successful goal-directed behavior often requires continuous sensory processing while simultaneously maintaining task-related information in working memory (WM). Although WM and perception are known to interact, little is known about how their interactions are controlled. Here, we tested the hypothesis that WM perception interactions engage two distinct modes of control – proactive and reactive – in a manner similar to classic conflict-adaptation tasks (e.g. Stroop, flanker, and Simon). Participants performed a delayed recall-of-orientation WM task, plus a standalone visual discrimination-of-orientation task the occurred during the delay period, and with the congruity in orientation between the tasks manipulated. Proactive control was seen in the sensitivity of task performance to the previous trial's congruity (i.e. a Gratton effect). Reactive control was observed in a repulsive serial-dependence produced by incongruent discriminanda. Quantitatively, these effects were explained by parameters from a reinforcement learning-based model that tracks trial-to-trial fluctuations in control demand: reactive control by a phasic control prediction error (control PE), and proactive control by a tonic level of predicted conflict updated each trial by the control PE. Thus, WM-perception interactions may be controlled by the same mechanisms that govern conflict in other domains of cognition, such as response selection.

Recurrent processing improves occluded object recognition and gives rise to perceptual hysteresis

Over the past decades, object recognition has been predominantly studied and modelled as a feedforward process. This notion was supported by the fast response times in psychophysical and neurophysiological experiments and the recent success of deep feedforward neural networks for object recognition. Recently, however, this prevalent view has shifted and recurrent connectivity in the brain is now believed to contribute significantly to object recognition — especially under challenging conditions, including the recognition of partially occluded objects. Moreover, recurrent dynamics might be the key to understanding perceptual phenomena such as perceptual hysteresis. In this work we investigate if and how artificial neural networks can benefit from recurrent connections. We systematically compare architectures comprised of bottom-up, lateral, and top-down connections. To evaluate the impact of recurrent connections for occluded object recognition, we introduce three stereoscopic occluded object datasets, which span the range from classifying partially occluded hand-written digits to recognizing three-dimensional objects. We find that recurrent architectures perform significantly better than parameter-matched feedforward models. An analysis of the hidden representation of the models suggests that occluders are progressively discounted in later time steps of processing. We demonstrate that feedback can correct the initial misclassifications over time and that the recurrent dynamics lead to perceptual hysteresis. Overall, our results emphasize the importance of recurrent feedback for object recognition in difficult situations.

Coarse-to-Fine(r) Automatic Familiar Face Recognition in the Human Brain

At what level of spatial resolution can the human brain recognize a familiar face in a crowd of strangers? Does it depend on whether one approaches or rather moves back from the crowd? To answer these questions, 16 observers viewed different unsegmented images of unfamiliar faces alternating at 6 Hz, with spatial frequency (SF) content progressively increasing (i.e., coarse-to-fine) or decreasing (fine-to-coarse) in different sequences. Variable natural images of celebrity faces every sixth stimulus generated an objective neural index of single-glanced automatic familiar face recognition (FFR) at 1 Hz in participants' electroencephalogram (EEG). For blurry images increasing in spatial resolution, the neural FFR response over occipitotemporal regions emerged abruptly with additional cues at about 6.3-8.7 cycles/head width, immediately reaching amplitude saturation. When the same images progressively decreased in resolution, the FFR response disappeared already below 12 cycles/head width, thus providing no support for a predictive coding hypothesis. Overall, these observations indicate that rapid automatic recognition of heterogenous natural views of familiar faces is achieved from coarser visual inputs than generally thought, and support a coarse-to-fine FFR dynamics in the human brain.