Disentangling presentation and processing times in the brain

Caplette, Laurent; Ince, Robin A. A.; Jerbi, Karim; Gosselin, Frédéric

doi:10.1016/j.neuroimage.2020.116994

Cited by 9 publications

(16 citation statements)

References 46 publications

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“…On each Bubbles trial, random areas of a randomly selected exemplar face were gradually revealed at random moments across a total duration of 200 ms (Caplette et al, 2020; Vinette et al, 2004). In other words, different random parts of a face were revealed on different frames of the stimulus, and the revealed areas were gradually appearing and disappearing (Figure 1c; Videos S1-S2).…”

Section: Methodsmentioning

confidence: 99%

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Rhythmic information sampling in the brain during visual recognition

Caplette

Jerbi

Gosselin

2022

Preprint

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Several studies observed behavioral oscillations in perceptual sensitivity across stimulus presentation time, and these fluctuations have been linked to oscillatory processing in the brain. However, whether specific brain areas show oscillations across stimulus time (i.e., oscillatory sampling) has not been investigated. Here, we randomly revealed features of face images across time and recorded participants' brain activity using magnetoencephalography (MEG) while they performed two recognition tasks. This allowed us to quantify how each snapshot of visual information coming from the stimulus is processed across time and across the brain. Oscillatory sampling was mostly visible in early visual areas, at theta and low beta frequencies. Furthermore, it explained a larger part of brain activity than oscillatory processing. Other parts of the brain showed distinct sampling patterns. These results advance our understanding of the oscillatory neural dynamics associated with visual processing and show the importance of considering the temporal dimension of stimuli when studying visual recognition.

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Section: Methodsmentioning

confidence: 99%

“…Trials with a response time +/-3 standard deviations away from the mean response time, below 100 ms or above 2000 ms were excluded from further analyses (1.37% of trials) (Caplette et al, 2020). Accuracies were transformed in z-scores across trials for each session.…”

Section: Methodsmentioning

confidence: 99%

Rhythmic information sampling in the brain during visual recognition

Caplette

Jerbi

Gosselin

2022

Preprint

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“…Readers skip over text that inspires or demands little cognitive effort but pause at or return to points of novelty, importance or surprise (Joseph et al, 2014: 241; Østergaard, 2003: 80; Taylor and Perfetti, 2016: 1097). As reading continues, cascading microcognitive perturbations may involve attention to and subsequent processing of incoming information even ‘at different moments within a fixation’ (Caplette et al, 2020: 2), selective attention activity that ‘focuses visual processing on relevant stimuli… despite an abundance of distracting information’ (Antonov et al, 2020: 1), salience detection ‘to filter a stream of sensory stimuli into pertinent and non-pertinent information’ (Hegarty et al, 2020: 1), changing predictions (Clark, 2016; Hohwy, 2020) that are ‘usually pre-conscious’ (Kukkonen, 2020: 2), retrieval of associative memories (Derner et al, 2020: 1), ‘flexible’ or selective retrieval of specific features of a concept or memory (Zhang et al, 2021: 14) and rapid processing of positive or negative response ‘at 224-304 ms after fixation onset’ (Pfeiffer et al, 2020: 13). The seething microcognitive processes and interactions that are masked or eclipsed at consciously experienced timescales are indispensable; without them, reading and interpretation do not occur.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…A key term in this paper, microcognition refers to rapid subconscious cognitive interactions at very small scales operating over times measured in milliseconds. For example, visual recognition of a familiar object such as a printed word seems to happen instantaneously, but processing occurs for around 170 milliseconds before visual recognition is achieved (Caplette et al, 2020: 9), with semantic processing taking longer, to around 585 milliseconds (Giari et al, 2020: 6). This processing is so fast that it is not consciously experienced.…”

Section: Introductionmentioning

confidence: 99%

Literary dynamics in The.PowerBook by Jeanette Winterson and Oryx and Crake by Margaret Atwood

O’Leary

2021

Language and Literature: International Journal of Stylistics

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Interaction between text and reader is a prominent concern in stylistics. This paper focusses on interactions among stylistic processes and subconscious microcognitive processes that generate changes to narrative and interpretation during reading. Drawing on process philosophy and recent neuroscientific research, I articulate this dynamism through analysis of a brief narrative moment from each of The.PowerBook by Jeanette Winterson and Oryx and Crake by Margaret Atwood. I argue that high densities of stylistic and microcognitive perturbations lead to frequent narrative and interpretive changes in the two moments. The analyses reinforce portrayals of reading as intensely complex, dynamic and changeable. Complexity, dynamism and mutability also characterise the stylistic changes in the two narrative moments. This paper advocates greater attention to the role of volatile stylistic and cognitive microdynamics in shaping the reading of prose fiction.

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“…These similarities could also be used for other purposes. For example, we have used a similar procedure to better separate electroencephalographic (EEG) data in true correct and true incorrect responses (Caplette et al, 2020). A cross-validation procedure could also be used in this case to reduce or eliminate doubledipping.…”

Section: Other Reclassification Evidencesmentioning

confidence: 99%

Reclassifying guesses to increase signal-to-noise ratio in psychological experiments

Gosselin¹,

Caplette²,

Daigneault³

et al. 2020

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Researchers studying the mind often rely on behavioral tasks and differences, either in stimuli or in brain activity, between correct and incorrect trials. However, subjects often guess when they don't know the answer, leading to correct responses that result from the same causes as the incorrect responses: this is a source of noise that remains no matter the number of trials performed by the subjects. This paper presents a response reclassification procedure to reduce the noise caused by “false” correct responses using an independent source of reclassification evidence. We illustrate the procedure on data from Faghel-Soubeyrand et al. (2019) with response times as reclassification evidence. The reclassification procedure increased signal-to-noise ratio by about 13.5% with little bias. Matlab and Python implementations of the reclassification procedure are freely available.

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Disentangling presentation and processing times in the brain

Cited by 9 publications

References 46 publications

Rhythmic information sampling in the brain during visual recognition

Rhythmic information sampling in the brain during visual recognition

Literary dynamics in The.PowerBook by Jeanette Winterson and Oryx and Crake by Margaret Atwood

Reclassifying guesses to increase signal-to-noise ratio in psychological experiments

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