Biology subjects

Dijkstra, N.

Publications and source records attributed to Dijkstra, N..

5 recordsLinked to original sources

bioRxiv2022

Identifying Content-Invariant Neural Signatures of Phenomenal Magnitude

Some conscious experiences are more vivid than others. Although perceptual vividness is a key component of human consciousness, how variation in this magnitude property is registered by the human brain is unknown. A striking feature of magnitudes in other psychological domains, such as number or reward, is the existence of neural magnitude codes that are independent from sensory contents. To test whether perceptual vividness similarly covaries with neural codes that are invariant to sensory content, we reanalysed existing MEG and fMRI data from two distinct studies, quantifying perceptual vividness via subjective ratings of awareness and visibility. Using representational similarity and decoding analyses, we find evidence for the existence of content-invariant neural codes for perceptual vividness distributed across visual, parietal, and frontal cortices. Our findings are consistent with a hypothesis that the subjective vividness of conscious experience is supported by neural signatures similar to magnitude codes in other cognitive domains. Significance StatementThe vividness of conscious experience varies across different stimuli and contexts. Despite being a fundamental feature of conscious awareness, exactly how perceptual vividness is encoded in the human brain remains unclear. Neural codes underpinning magnitude in reward and numerosity domains have been shown to be unchanging as stimulus identity varies. Here, we test whether components of neural activity covarying with the magnitude of perceptual vividness are similarly independent of perceptual content in analyses of MEG and fMRI data. We find dynamic, content-invariant neural signatures of vividness in visual, parietal, and frontal cortices. Our findings introduce the surprising notion that neural signatures of conscious experience might follow similar coding principles to those found for magnitude properties of entirely different cognitive domains.

neuroscience↗

bioRxiv2021

Dissociating the neural correlates of subjective visibility from those of decision confidence

A key goal of consciousness science is identifying neural signatures of being aware vs. unaware of simple stimuli. This is often investigated in the context of near-threshold detection, with reports of stimulus awareness being linked to heightened activation in a frontoparietal network. However, due to reports of stimulus presence typically being associated with higher confidence than reports of stimulus absence, these results could be explained by frontoparietal regions encoding stimulus visibility, decision confidence or both. In an exploratory analysis, we leverage fMRI data from 35 human participants (20 females) to disentangle these possibilities. We first show that, whereas stimulus identity was best decoded from the visual cortex, stimulus visibility (presence vs. absence) was best decoded from prefrontal regions. To control for effects of confidence, we then selectively sampled trials prior to decoding to equalize confidence distributions between absence and presence responses. This analysis revealed striking differences in the neural correlates of subjective visibility in prefrontal cortex regions of interest, depending on whether or not differences in confidence were controlled for. We interpret our findings as highlighting the importance of controlling for metacognitive aspects of the decision process in the search for neural correlates of visual awareness. Significance statementWhile much has been learned over the past two decades about the neural basis of visual awareness, the role of the prefrontal cortex remains a topic of debate. By applying decoding analyses to functional brain imaging data, we show that prefrontal representations of subjective visibility are contaminated by neural correlates of decision confidence. We propose a new analysis method to control for these metacognitive aspects of awareness reports, and use it to reveal confidence-independent correlates of perceptual judgments in a subset of prefrontal areas.

neuroscience↗

bioRxiv2019

Neural dynamics of perceptual inference and its reversal during imagery

After the presentation of a visual stimulus, cortical visual processing cascades from low-level sensory features in primary visual areas to increasingly abstract representations in higher-level areas. It is often hypothesized that the reverse process underpins the human ability to generate mental images. Under this hypothesis, visual information feeds back from high-level areas as abstract representations are used to construct the sensory representation in primary visual cortices. Such reversals of information flow are also hypothesized to play a central role in later stages of perception. According to predictive processing theories, ambiguous sensory information is resolved using abstract representations coming from high-level areas through oscillatory rebounds between different levels of the visual hierarchy. However, despite the elegance of these theoretical models, to this day there is no direct experimental evidence of the reversion of visual information flow during mental imagery and perception. In the first part of this paper, we provide direct evidence in humans for a reverse order of activation of the visual hierarchy during imagery. Specifically, we show that classification machine learning models trained on brain data at different time points during the early feedforward phase of perception are reactivated in reverse order during mental imagery. In the second part of the paper, we report an 11Hz oscillatory pattern of feedforward and reversed visual processing phases during perception. Together, these results are in line with the idea that during perception, the high-level cause of sensory input is inferred through recurrent hypothesis updating, whereas during imagery, this learned forward mapping is reversed to generate sensory signals given abstract representations.

neuroscience↗

bioRxiv2019

Individual differences in the influence of mental imagery on conscious perception

Mental imagery and visual perception rely on similar neural mechanisms, but the function of this overlap remains unclear. One idea is that imagery can influence perception. Previous research has shown that imagining a stimulus prior to binocular presentation of rivalling stimuli increases the chance of perceiving the imagined stimulus. In this study we investigated how this effect interacts with bottom-up sensory input by comparing psychometric response curves for congruent and incongruent imagery in humans. A Bayesian hierarchical model was used, allowing us to simultaneously study group-level effects as well as effects for individual participants. We found strong effects of both imagery as well as its interaction with sensory evidence within individual participants. However, the direction of these effects were highly variable between individuals, leading to weak effects at the group level. This highlights the heterogeneity of conscious perception and emphasizes the need for individualized investigation of such complex cognitive processes.

neuroscience↗

bioRxiv2017

Differential temporal dynamics during visual imagery and perception

Visual perception and imagery rely on similar representations in the visual cortex. During perception, visual activity is characterized by distinct processing stages, but the temporal dynamics underlying imagery remain unclear. Here, we investigated the dynamics of visual imagery in human participants using magnetoencephalography. We show that, contrary to perception, the onset of imagery is characterized by broad temporal generalization. Furthermore, there is consistent overlap between imagery and perceptual processing around 150 ms and from 300 ms after stimulus onset, presumably reflecting completion of the feedforward sweep and perceptual stabilization respectively. These results indicate that during imagery either the complete representation is activated at once and does not include low-level visual areas, or the order in which visual features are activated is less fixed and more flexible than during perception. These findings have important implications for our understanding of the neural mechanisms of visual imagery.

neuroscience↗