Predictive activation of sensory representations as a source of evidence in perceptual decision-making

Viewed touch influences tactile detection by altering decision criterion

Our tactile perception is shaped not only by somatosensory input but also by visual information. Prior research on the effect of viewing touch on tactile processing has found higher tactile detection rates when paired with viewed touch versus a control visual stimulus. Therefore, some have proposed a vicarious tactile system that activates somatosensory areas when viewing touch, resulting in enhanced tactile perception. However, we propose an alternative explanation: Viewing touch makes the observer more liberal in their decision to report a tactile stimulus relative to not viewing touch, also resulting in higher tactile detection rates. To disambiguate between the two explanations, we examined the effect of viewed touch on tactile sensitivity and decision criterion using signal detection theory. In three experiments, participants engaged in a tactile detection task while viewing a hand being touched or approached by a finger, a red dot, or no stimulus. We found that viewing touch led to a consistent, liberal criterion shift but inconsistent enhancement in tactile sensitivity relative to not viewing touch. Moreover, observing a finger approach the hand was sufficient to bias the criterion. These findings suggest that viewing touch influences tactile performance by altering tactile decision mechanisms rather than the tactile perceptual signal.

Prior probability cues bias sensory encoding with increasing task exposure

When observers have prior knowledge about the likely outcome of their perceptual decisions, they exhibit robust behavioural biases in reaction time and choice accuracy. Computational modelling typically attributes these effects to strategic adjustments in the criterion amount of evidence required to commit to a choice alternative - usually implemented by a starting point shift - but recent work suggests that expectations may also fundamentally bias the encoding of the sensory evidence itself. Here, we recorded neural activity with EEG while participants performed a contrast discrimination task with valid, invalid, or neutral probabilistic cues across multiple testing sessions. We measured sensory evidence encoding via contrast-dependent steady-state visual-evoked potentials (SSVEP), while a read-out of criterion adjustments was provided by effector-selective mu-beta band activity over motor cortex. In keeping with prior modelling and neural recording studies, cues evoked substantial biases in motor preparation consistent with criterion adjustments, but we additionally found that the cues produced a significant modulation of the SSVEP during evidence presentation. While motor preparation adjustments were observed in the earliest trials, the sensory-level effects only emerged with extended task exposure. Our results suggest that, in addition to strategic adjustments to the decision process, probabilistic information can also induce subtle biases in the encoding of the evidence itself.

Stimulus expectations do not modulate visual event-related potentials in probabilistic cueing designs

Humans and other animals can learn and exploit repeating patterns that occur within their environments. These learned patterns can be used to form expectations about future sensory events. Several influential predictive coding models have been proposed to explain how learned expectations influence the activity of stimulus-selective neurons in the visual system. These models specify reductions in neural response measures when expectations are fulfilled (termed expectation suppression) and increases following surprising sensory events. However, there is currently scant evidence for expectation suppression in the visual system when confounding factors are taken into account. Effects of surprise have been observed in blood oxygen level dependent (BOLD) signals, but not when using electrophysiological measures. To provide a strong test for expectation suppression and surprise effects we performed a predictive cueing experiment while recording electroencephalographic (EEG) data. Participants (n=48) learned cue-face associations during a training session and were then exposed to these cue-face pairs in a subsequent experiment. Using univariate analyses of face-evoked event-related potentials (ERPs) we did not observe any differences across expected (90% probability), neutral (50%) and surprising (10%) face conditions. Across these comparisons, Bayes factors consistently favoured the null hypothesis throughout the time-course of the stimulus-evoked response. When using multivariate pattern analysis we did not observe above-chance classification of expected and surprising face-evoked ERPs. By contrast, we found robust within- and across-trial stimulus repetition effects. Our findings do not support predictive coding-based accounts that specify reduced prediction error signalling when perceptual expectations are fulfilled. They instead highlight the utility of other types of predictive processing models that describe expectation-related phenomena in the visual system without recourse to prediction error signalling.

Updating perceptual expectations as certainty diminishes

Forming expectations about what we are likely to perceive often facilitates perception. We forge such expectations on the basis of strong statistical relationships between events in our environment. However, due to our ever-changing world these relationships often subsequently degrade or even disappear, yet it is unclear how these altered statistics influence perceptual expectations. We examined this question across two studies by training participants in perfect relationships between actions (index or little finger abductions) and outcomes (clockwise or counter-clockwise gratings), before degrading the predictive relationship in a test phase - such that 'expected' events followed actions on 50-75% of trials and 'unexpected' events ensued on the remainder. Perceptual decisions about outcomes were faster and less error prone on expected than unexpected trials when predictive relationships remained high and reduced as the relationship diminished. Drift diffusion modelling indicated that these effects are explained by shifting the starting point in the evidence accumulation process as well as biasing the rate of evidence accumulation - with the former reflecting biases from statistics within the training session and the latter those of the test session. These findings demonstrate how perceptual expectations are updated as statistical certainty diminishes, with interacting influences speculatively dependent upon learning consolidation. We discuss how underlying mechanisms optimise the interaction between learning and perception - allowing our experiences to reflect a nuanced, ever-changing environment.

Blurred Lines: Memory, Perceptions, and Consciousness: Commentary on "Consciousness as a Memory System" by Budson et al (2022)

In the previous issue, Budson, Richman, and Kensinger (2022) put forth the intriguing proposal that consciousness may have evolved from the episodic memory system. In addition to providing a possible evolutionary trajectory for consciousness, I believe that viewing consciousness as an extension of memory in this way is particularly useful for understanding some of the puzzling temporal complexities that are inherent to consciousness. For example, due to neural transmission delays, our conscious experience must necessarily lag the outside world, which creates a paradox for both conscious perception (Do we see the past, rather than the present?) and action (How can we make rapid decisions if it takes so long to become conscious of something?). These paradoxes can be elegantly solved by treating consciousness as a memory system. Finally, the proposal put forth by Budson and colleagues (2022) aligns with the emerging perspective that consciousness, like memory, represents a narrative time line of events rather than any single instant. However, I believe that this conceptualization can be further extended to include not only the past, but also the future. In this way, consciousness can be provocatively viewed as the remembered past, present, and future.

Imagery adds stimulus-specific sensory evidence to perceptual detection

Internally generated imagery and externally triggered perception rely on overlapping sensory processes. This overlap poses a challenge for perceptual reality monitoring: determining whether sensory signals reflect reality or imagination. In this study, we used psychophysics to investigate how imagery and perception interact to determine visual experience. Participants were instructed to detect oriented gratings that gradually appeared in noise while simultaneously either imagining the same grating, a grating perpendicular to the to-be-detected grating, or nothing. We found that, compared to both incongruent imagery and no imagery, congruent imagery caused a leftward shift of the psychometric function relating stimulus contrast to perceptual threshold. We discuss how this effect can best be explained by a model in which imagery adds sensory signal to the perceptual input, thereby increasing the visibility of perceived stimuli. These results suggest that, in contrast to changes in sensory signals caused by self-generated movement, the brain does not discount the influence of self-generated sensory signals on perception.

Perception in real-time: predicting the present, reconstructing the past

We feel that we perceive events in the environment as they unfold in real-time. However, this intuitive view of perception is impossible to implement in the nervous system due to biological constraints such as neural transmission delays. I propose a new way of thinking about real-time perception: at any given moment, instead of representing a single timepoint, perceptual mechanisms represent an entire timeline. On this timeline, predictive mechanisms predict ahead to compensate for delays in incoming sensory input, and reconstruction mechanisms retroactively revise perception when those predictions do not come true. This proposal integrates and extends previous work to address a crucial gap in our understanding of a fundamental aspect of our everyday life: the experience of perceiving the present.