It’s not always about me: The effects of prior beliefs and stimulus prevalence on self–other prioritisation

Although self-relevance is widely acknowledged to enhance stimulus processing, the exclusivity of this effect remains open to question. In particular, in commonly adopted experimental paradigms, the prioritisation of self-relevant (vs. other-relevant) material may reflect the operation of a task-specific strategy rather than an obligatory facet of social-cognitive functioning. By changing basic aspects of the decisional context, it may therefore be possible to generate stimulus-prioritisation effects for targets other than the self. Based on the demonstration that ownership facilitates object categorisation (i.e., self-ownership effect), here we showed that stimulus prioritisation is sensitive to prior expectations about the prevalence of forthcoming objects (owned-by-self vs. owned-by-friend) and whether these beliefs are supported during the task. Under conditions of stimulus uncertainty (i.e., no prior beliefs), replicating previous research, objects were classified more rapidly when owned-by-self compared with owned-by-friend (Experiment 1). When, however, the frequency of stimulus presentation either confirmed (Experiment 2) or disconfirmed (Experiment 3) prior expectations, stimulus prioritisation was observed for the most prevalent objects regardless of their owner. A hierarchical drift diffusion model (HDDM) analysis further revealed that decisional bias was underpinned by differences in the evidential requirements of response generation. These findings underscore the flexibility of ownership effects (i.e., stimulus prioritisation) during object processing.

Representation of uncertainty in macaque visual cortex

Uncertainty is intrinsic to perception. Neural circuits which process sensory information must therefore also represent the reliability of this information. How they do so is a topic of debate. We propose a view of visual cortex in which average neural response strength encodes stimulus features, while cross-neuron variability in response gain encodes the uncertainty of these features. To test our theory, we studied spiking activity of neurons in macaque V1 and V2 elicited by repeated presentations of stimuli whose uncertainty was manipulated in distinct ways. We show that gain variability of individual neurons is tuned to stimulus uncertainty, that this tuning is invariant to the source of uncertainty, and that it is specific to the features encoded by these neurons. We demonstrate that this behavior naturally arises from known gain-control mechanisms, and derive how downstream circuits can jointly decode stimulus features and their uncertainty from sensory population activity.

Neural basis of somatosensory target detection independent of uncertainty, relevance, and reports

Research on somatosensory awareness has yielded highly diverse findings with putative neural correlates ranging from activity within somatosensory cortex to activation of widely distributed frontoparietal networks. Divergent results from previous studies may reside in cognitive processes that often coincide with stimulus awareness in experimental settings. To scrutinise the specific relevance of regions implied in the target detection network, we used functional magnetic resonance imaging (n = 27) on a novel somatosensory detection task that explicitly controls for stimulus uncertainty, behavioural relevance, overt reports, and motor responses. Using Bayesian Model Selection, we show that responses reflecting target detection are restricted to secondary somatosensory cortex, whereas activity in insular, cingulate, and motor regions is best explained in terms of stimulus uncertainty and overt reports. Our results emphasise the role of sensory-specific cortex for the emergence of perceptual awareness and dissect the contribution of the frontoparietal network to classical detection tasks.

On the Summation of Visual Noise

What information is used by the visual system to detect patterns? A standard modelhypothesizes that both spatial frequency and orientation information are processed byindependent channels, meaning there is no summation among channels. Despite the consensus among researchers on how the visual system sums spatial frequency and orientation information, there are data in the literature (Kersten, 1987) that ostensibly contradict the standard model. To resolve this conflict, we measured the e?ciency of spatial frequency and orientation of ?ltered noise. To learn what information the visual system uses when detecting ?ltered noise, we applied a technique that can determine the information used to detect and discriminate ?ltered visual noise. In Chapter 2 the detection of spatial frequency ?ltered noise is not only e?cient but remains so with stimulus uncertainty and extremely brief (10ms) stimulus duration. When the spatial frequency channel used wasmeasured, we found a fi?xed bandwidth channel as the spatial frequency of the pattern was increased. To test the standard model, we implemented simulations of the standard model and contrary to the interpretation, the standard model could predict detection of spatial frequency ?ltered noise. Chapter 3 used spatial frequency filtered noise to relate the detection and discrimination of ?ltered visual noise. A simple rule relates what information observers use to detect and discriminate spatial frequency ?ltered noise. Chapter 4 extends the work of Chapter 2 to orientation information and found that orientation fi?ltered noise is detected efficiently. We again measured what information observers used and found that unlike SF ?filtered noise, observers use orientation in a flexible or adjustablemanner.