Decoding perceptual awareness across the brain with a no-report fMRI masking paradigm

Hatamimajoumerd, Elaheh; Murty, N. Apurva Ratan; Pitts, Michael; Cohen, Michael A.

doi:10.1016/j.cub.2022.07.068

Cited by 37 publications

(26 citation statements)

References 75 publications

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“…As our neuroimaging results were obtained in the absence of reports, they provide evidence in favour of an architecture in which awareness prediction errors are automatically elicited even under passive viewing conditions. Our results are also consistent with other studies observing prefrontal correlates of awareness in the absence of overt report (Hatamimajoumerd et al, 2022), and argue against interpretations in which prefrontal correlates of consciousness are merely correlates of reports, rather than awareness itself (Bartels, 2021;Storm et al, 2017;Tsuchiya et al, 2015). A natural next step is to seek to causally intervene on regions (such as vmPFC) exhibiting signatures of awareness prediction error (for instance, using multivariate neurofeedback; Taschereau-Dumouchel et al, 2021), and ask how such interventions alter conscious experience.…”

Section: Discussionsupporting

confidence: 88%

Distinguishing neural correlates of prediction errors on perceptual content and detection of content

Dijkstra¹,

Warrington²,

Kok³

et al. 2023

Preprint

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Accounting for why sensitivity to perceptual input (as assayed by discrimination judgments) is not always accompanied by conscious awareness (as assayed by detection judgments) remains a challenge for theories of perception. Here we test a hypothesis that awareness is supported by higher-order inferences within generative models of perceptual content. We develop a novel visual perception paradigm that probes such inferences by orthogonally manipulating expectations about stimulus content (discrimination) and awareness of content (detection). In line with model simulations we show that both detection and discrimination expectations influence reaction times on a categorisation task. By combining a no-report version of our task with functional neuroimaging we reveal a neural dissociation between prediction errors (PEs) on content (discrimination) and awareness of content (detection): content PEs are tracked in posterior sensory cortex while awareness PEs are tracked in prefrontal cortex. Together, our results reveal a hierarchical structure supporting visual detection and discrimination, consistent with a proposal that awareness reflects a higher-order inference within perceptual generative models.

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Section: Discussionsupporting

confidence: 88%

Distinguishing neural correlates of prediction errors on perceptual content and detection of content

Dijkstra¹,

Warrington²,

Kok³

et al. 2023

Preprint

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“…Despite overlapping clusters being obtained in the superior and inferior lateral occipital cortex (see Table S2 for full list of individual and overlapping clusters), a clear anatomical distinction in occipital regions can be seen between representations of stimulus content and abstract representations of visibility, with the former being decoded from more lateral regions of the occipital 31 cortex, while the latter was decoded closer to the medial surface (Figure 5C, Table S2). As expected, stimulus content was less well decoded from frontal regions, whereas here content-invariant representations of visibility were more abundant (Hatamimajoumerd et al, 2022). Distinct decoding patterns for content and visibility representations further strengthens the notion that content-invariant representations of visibility exist independently of perceptual content, even in regions typically associated with the encoding of stimulus content such as the visual cortex (Kamitani & Tong, 2005;Kriegeskorte et al, 2008;Mazor et al, 2022).…”

Section: Stimulus Content and Visibility Are Encoded In Dissociable B...supporting

confidence: 77%

“…However, under the assumption that such processes are minimised or reduced in such conditions, comparing the within-subject neural profile of phenomenal magnitudes in report and no-report blocks could shed light on the relative contribution of such signals to reporting requirements. Notably, a recent study employing such an approach found that graded changes in perceptual visibility could be reliably decoded from the prefrontal cortex in the absence of report, consistent with a contribution of this region to phenomenal magnitude (Hatamimajoumerd et al, 2022).…”

Section: Discussionmentioning

confidence: 78%

Identifying content-invariant neural signatures of perceptual vividness

Barnett

Andersen

Fleming

et al. 2022

Preprint

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Some experiences are stronger than others: they have greater phenomenal magnitude. Although the phenomenal magnitude of experience is a familiar component of human consciousness, the computational scheme underpinning its encoding in the brain is unknown. In particular, it is unknown whether phenomenal magnitude is encoded in a "rich" manner, via the strengthening or broadcast of content-specific perceptual representations, or a "sparse" scheme, in which a content-invariant signal monitors the reliability or precision of first-order contents. In a reanalysis of existing MEG and fMRI data from two distinct studies, we operationalise phenomenal magnitude as subjective ratings of awareness and visibility to address this question. We find that phenomenal magnitude is associated with content-invariant neural signatures distributed across visual, parietal, and frontal cortices. Moreover, we show that these neural signatures exhibit similarities with other analogue magnitude codes such as number, with each rating being represented as being more similar to its neighbours, and less similar to more distant ratings. Our findings suggest a role for a content-invariant analogue magnitude code in determining the strength of perceptual experience.

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“…From there, one can gradually approach states and conditions in which we have reason to doubt subjective reports. Although the field is still in its infancy, there have been several advances in this regard, for example decoding dreams ( Horikawa et al, 2013 ; Smith, 2013 ; Horikawa and Kamitani, 2017 ), movie watching ( Huth et al, 2016 ; Nishida and Nishimoto, 2018 ), speech ( Wang et al, 2021 ), and other sensory modalities ( Hatamimajoumerd et al, 2022 ). This approach is similar to solving the “real” problem of consciousness ( Seth, 2016 ).…”

Section: Possible Solutionsmentioning

confidence: 99%

Are we really unconscious in “unconscious” states? Common assumptions revisited

Nilsen

Juel

Thürer

et al. 2022

Front. Hum. Neurosci.

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In the field of consciousness science, there is a tradition to categorize certain states such as slow-wave non-REM sleep and deep general anesthesia as “unconscious”. While this categorization seems reasonable at first glance, careful investigations have revealed that it is not so simple. Given that (1) behavioral signs of (un-)consciousness can be unreliable, (2) subjective reports of (un-)consciousness can be unreliable, and, (3) states presumed to be unconscious are not always devoid of reported experience, there are reasons to reexamine our traditional assumptions about “states of unconsciousness”. While these issues are not novel, and may be partly semantic, they have implications both for scientific progress and clinical practice. We suggest that focusing on approaches that provide a more pragmatic and nuanced characterization of different experimental conditions may promote clarity in the field going forward, and help us build stronger foundations for future studies.

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Decoding perceptual awareness across the brain with a no-report fMRI masking paradigm

Cited by 37 publications

References 75 publications

Distinguishing neural correlates of prediction errors on perceptual content and detection of content

Distinguishing neural correlates of prediction errors on perceptual content and detection of content

Identifying content-invariant neural signatures of perceptual vividness

Are we really unconscious in “unconscious” states? Common assumptions revisited

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