Peter Kok

How Prediction Errors Shape Perception, Attention, and Motivation

Prediction errors (PE) are a central notion in theoretical models of reinforcement learning, perceptual inference, decision-making and cognition, and prediction error signals have been reported across a wide range of brain regions and experimental paradigms. Here, we will make an attempt to see the forest for the trees and consider the commonalities and differences of reported PE signals in light of recent suggestions that the computation of PE forms a fundamental mode of brain function. We discuss where different types of PE are encoded, how they are generated, and the different functional roles they fulfill. We suggest that while encoding of PE is a common computation across brain regions, the content and function of these error signals can be very different and are determined by the afferent and efferent connections within the neural circuitry in which they arise.

Genome-scale discovery of DNA-methylation biomarkers for blood-based detection of colorectal cancer.

Background There is an increasing demand for accurate biomarkers for early non-invasive colorectal cancer detection. We employed a genome-scale marker discovery method to identify and verify candidate DNA methylation biomarkers for blood-based detection of colorectal cancer. Methodology/Principal Findings We used DNA methylation data from 711 colorectal tumors, 53 matched adjacent-normal colonic tissue samples, 286 healthy blood samples and 4,201 tumor samples of 15 different cancer types. DNA methylation data were generated by the Illumina Infinium HumanMethylation27 and the HumanMethylation450 platforms, which determine the methylation status of 27,578 and 482,421 CpG sites respectively. We first performed a multistep marker selection to identify candidate markers with high methylation across all colorectal tumors while harboring low methylation in healthy samples and other cancer types. We then used pre-therapeutic plasma and serum samples from 107 colorectal cancer patients and 98 controls without colorectal cancer, confirmed by colonoscopy, to verify candidate markers. We selected two markers for further evaluation: methylated THBD (THBD-M) and methylated C9orf50 (C9orf50-M). When tested on clinical plasma and serum samples these markers outperformed carcinoembryonic antigen (CEA) serum measurement and resulted in a high sensitive and specific test performance for early colorectal cancer detection. Conclusions/Significance Our systematic marker discovery and verification study for blood-based DNA methylation markers resulted in two novel colorectal cancer biomarkers, THBD-M and C9orf50-M. THBD-M in particular showed promising performance in clinical samples, justifying its further optimization and clinical testing.

Selective Activation of the Deep Layers of the Human Primary Visual Cortex by Top-Down Feedback

In addition to bottom-up input, the visual cortex receives large amounts of feedback from other cortical areas [1-3]. One compelling example of feedback activation of early visual neurons in the absence of bottom-up input occurs during the famous Kanizsa illusion, where a triangular shape is perceived, even in regions of the image where there is no bottom-up visual evidence for it. This illusion increases the firing activity of neurons in the primary visual cortex with a receptive field on the illusory contour [4]. Feedback signals are largely segregated from feedforward signals within each cortical area, with feedforward signals arriving in the middle layer, while top-down feedback avoids the middle layers and predominantly targets deep and superficial layers [1, 2, 5, 6]. Therefore, the feedback-mediated activity increase in V1 during the perception of illusory shapes should lead to a specific laminar activity profile that is distinct from the activity elicited by bottom-up stimulation. Here, we used fMRI at high field (7 T) to empirically test this hypothesis, by probing the cortical response to illusory figures in human V1 at different cortical depths [7-14]. We found that, whereas bottom-up stimulation activated all cortical layers, feedback activity induced by illusory figures led to a selective activation of the deep layers of V1. These results demonstrate the potential for non-invasive recordings of neural activity with laminar specificity in humans and elucidate the role of top-down signals during perceptual processing.

Prior expectations evoke stimulus templates in the primary visual cortex

Sensory processing is strongly influenced by prior expectations. Valid expectations have been shown to lead to improvements in perception as well as in the quality of sensory representations in primary visual cortex. However, very little is known about the neural correlates of the expectations themselves. Previous studies have demonstrated increased activity in sensory cortex following the omission of an expected stimulus, yet it is unclear whether this increased activity constitutes a general surprise signal or rather has representational content. One intriguing possibility is that top–down expectation leads to the formation of a template of the expected stimulus in visual cortex, which can then be compared with subsequent bottom–up input. To test this hypothesis, we used fMRI to noninvasively measure neural activity patterns in early visual cortex of human participants during expected but omitted visual stimuli. Our results show that prior expectation of a specific visual stimulus evokes a feature-specific pattern of activity in the primary visual cortex (V1) similar to that evoked by the corresponding actual stimulus. These results are in line with the notion that prior expectation triggers the formation of specific stimulus templates to efficiently process expected sensory inputs.

Shape Perception Simultaneously Up- and Downregulates Neural Activity in the Primary Visual Cortex

An essential part of visual perception is the grouping of local elements (such as edges and lines) into coherent shapes. Previous studies have shown that this grouping process modulates neural activity in the primary visual cortex (V1) that is signaling the local elements [1-4]. However, the nature of this modulation is controversial. Some studies find that shape perception reduces neural activity in V1 [2, 5, 6], while others report increased V1 activity during shape perception [1, 3, 4, 7-10]. Neurocomputational theories that cast perception as a generative process [11-13] propose that feedback connections carry predictions (i.e., the generative model), while feedforward connections signal the mismatch between top-down predictions and bottom-up inputs. Within this framework, the effect of feedback on early visual cortex may be either enhancing or suppressive, depending on whether the feedback signal is met by congruent bottom-up input. Here, we tested this hypothesis by quantifying the spatial profile of neural activity in V1 during the perception of illusory shapes using population receptive field mapping. We find that shape perception concurrently increases neural activity in regions of V1 that have a receptive field on the shape but do not receive bottom-up input and suppresses activity in regions of V1 that receive bottom-up input that is predicted by the shape. These effects were not modulated by task requirements. Together, these findings suggest that shape perception changes lower-order sensory representations in a highly specific and automatic manner, in line with theories that cast perception in terms of hierarchical generative models.

Inflection and computational load in agrammatic speech

In this study we investigate the production of verb inflection in agrammatic aphasia. In a number of recent studies it has been argued that tense inflection is harder to produce for agrammatic individuals than agreement inflection. However, results are still inconclusive, at least for Dutch and German. Here, we report three experiments in which this matter is further investigated. Our first goal was to determine whether tense was indeed more difficult to produce than agreement. Also, we investigated whether error rates were influenced by computational load. The results for nine Dutch-speaking agrammatic participants generally indicated that tense was indeed harder to produce than agreement, but that for both types of inflection, the number of errors increased with computational load. Taking care of word order and inflection induced more errors than taking care of just inflection. These findings are discussed in relation to current processing and representational models of agrammatic production.

Serial Dependence in Perceptual Decisions Is Reflected in Activity Patterns in Primary Visual Cortex

Sensory signals are highly structured in both space and time. These regularities allow expectations about future stimulation to be formed, thereby facilitating decisions about upcoming visual features and objects. One such regularity is that the world is generally stable over short time scales. This feature of the world is exploited by the brain, leading to a bias in perception called serial dependence: previously seen stimuli bias the perception of subsequent stimuli, making them appear more similar to previous input than they really are. What are the neural processes that may underlie this bias in perceptual choice? Does serial dependence arise only in higher-level areas involved in perceptual decision-making, or does such a bias occur at the earliest levels of sensory processing? In this study, human subjects made decisions about the orientation of grating stimuli presented in the left or right visual field while activity patterns in their visual cortex were recorded using fMRI. In line with previous behavioral reports, reported orientation on the current trial was consistently biased toward the previously reported orientation. We found that the orientation signal in V1 was similarly biased toward the orientation presented on the previous trial. Both the perceptual decision and neural effects were spatially specific, such that the perceptual decision and neural representations on the current trial were only influenced by previous stimuli at the same location. These results suggest that biases in perceptual decisions induced by previous stimuli may result from neural biases in sensory cortex induced by recent perceptual history. SIGNIFICANCE STATEMENT We perceive a stable visual scene, although our visual input is constantly changing. This experience may in part be driven by a bias in visual perception that causes images to be perceived as similar to those previously seen. Here, we provide evidence for a sensory bias that may underlie this perceptual effect. We find that neural representations in early visual cortex are biased toward previous perceptual decisions. Our results suggest a direct neural correlate of serial dependencies in visual perception. These findings elucidate how our perceptual decisions are shaped by our perceptual history.

Dissociating sensory from decision processes in human perceptual decision making

A key question within systems neuroscience is how the brain translates physical stimulation into a behavioral response: perceptual decision making. To answer this question, it is important to dissociate the neural activity underlying the encoding of sensory information from the activity underlying the subsequent temporal integration into a decision variable. Here, we adopted a decoding approach to empirically assess this dissociation in human magnetoencephalography recordings. We used a functional localizer to identify the neural signature that reflects sensory-specific processes, and subsequently traced this signature while subjects were engaged in a perceptual decision making task. Our results revealed a temporal dissociation in which sensory processing was limited to an early time window and consistent with occipital areas, whereas decision-related processing became increasingly pronounced over time, and involved parietal and frontal areas. We found that the sensory processing accurately reflected the physical stimulus, irrespective of the eventual decision. Moreover, the sensory representation was stable and maintained over time when it was required for a subsequent decision, but unstable and variable over time when it was task-irrelevant. In contrast, decision-related activity displayed long-lasting sustained components. Together, our approach dissects neuro-anatomically and functionally distinct contributions to perceptual decisions.

Expectation Suppression in Early Visual Cortex Depends on Task Set

Stimulus expectation can modulate neural responses in early sensory cortical regions, with expected stimuli often leading to a reduced neural response. However, it is unclear whether this expectation suppression is an automatic phenomenon or is instead dependent on the type of task a subject is engaged in. To investigate this, human subjects were presented with visual grating stimuli in the periphery that were either predictable or non-predictable while they performed three tasks that differently engaged cognitive resources. In two of the tasks, the predictable stimulus was task-irrelevant and spatial attention was engaged at fixation, with a high load on either perceptual or working memory resources. In the third task, the predictable stimulus was task-relevant, and therefore spatially attended. We observed that expectation suppression is dependent on the cognitive resources engaged by a subjects’ current task. When the grating was task-irrelevant, expectation suppression for predictable items was visible in retinotopically specific areas of early visual cortex (V1-V3) during the perceptual task, but it was abolished when working memory was loaded. When the grating was task-relevant and spatially attended, there was no significant effect of expectation in early visual cortex. These results suggest that expectation suppression is not an automatic phenomenon, but dependent on attentional state and type of available cognitive resources.

Prior expectations induce prestimulus sensory templates

Significance The way that we perceive the world is partly shaped by what we expect to see at any given moment. However, it is unclear how this process is neurally implemented. Recently, it has been proposed that the brain generates stimulus templates in sensory cortex to preempt expected inputs. Here, we provide evidence that a representation of the expected stimulus is present in the neural signal shortly before it is presented, showing that expectations can indeed induce the preactivation of stimulus templates. Importantly, these expectation signals resembled the neural signal evoked by an actually presented stimulus, suggesting that expectations induce similar patterns of activations in visual cortex as sensory stimuli. Perception can be described as a process of inference, integrating bottom-up sensory inputs and top-down expectations. However, it is unclear how this process is neurally implemented. It has been proposed that expectations lead to prestimulus baseline increases in sensory neurons tuned to the expected stimulus, which in turn, affect the processing of subsequent stimuli. Recent fMRI studies have revealed stimulus-specific patterns of activation in sensory cortex as a result of expectation, but this method lacks the temporal resolution necessary to distinguish pre- from poststimulus processes. Here, we combined human magnetoencephalography (MEG) with multivariate decoding techniques to probe the representational content of neural signals in a time-resolved manner. We observed a representation of expected stimuli in the neural signal shortly before they were presented, showing that expectations indeed induce a preactivation of stimulus templates. The strength of these prestimulus expectation templates correlated with participants’ behavioral improvement when the expected feature was task-relevant. These results suggest a mechanism for how predictive perception can be neurally implemented.