Bayes-Like Integration of a New Sensory Skill with Vision

Negen, James; Wen, Lisa; Thaler, Lore; Nardini, Marko

doi:10.1038/s41598-018-35046-7

Cited by 24 publications

(46 citation statements)

References 48 publications

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“…Examples of such experiences can be infrared (IR) vision conveyed through sound or ultrasound perception through touch. Initial evidence confirms that NSEs can be induced in humans via SSDs (Kaspar et al, 2014;König et al, 2016;Negen et al, 2018).…”

Section: Does the Concept Of Reversible Plasticity Gradient Extend Almentioning

confidence: 76%

Are critical periods reversible in the adult brain? Insights on cortical specializations based on sensory deprivation studies

Heimler

Amedi

2020

Neuroscience & Biobehavioral Reviews

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We review here studies with visual and auditory deprived/recovery populations to argue for the need of a redefinition of the crucial role of unisensory-specific experiences during critical periods (CPs) on the emergence of sensory specializations. Specifically, we highlight that these studies, with emphasis on results with congenitally blind adults using visual sensory-substitution devices, consistently document that typical specializations (e.g., in visual cortex) could arise also in adulthood via other sensory modalities (e.g., audition), even after relatively short (tailored) trainings. Altogether, these studies suggest that 1) brain specializations are driven by sensory-independent computations rather than by unisensory-specific inputs and that 2) specific computationoriented trainings, even if executed during adulthood, can guide the sensory brain to display/recover, core properties of brain specializations. We thus introduce here the concept of a reversible plasticity gradient, namely that brain plasticity spontaneously decreases with age in line with CPs theory, but it nonetheless can be reignited across the lifespan, even without any exposure to unisensory (e.g., visual) experiences during childhood, thus diverging dramatically from CPs assumptions.

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Section: Does the Concept Of Reversible Plasticity Gradient Extend Almentioning

confidence: 76%

Are critical periods reversible in the adult brain? Insights on cortical specializations based on sensory deprivation studies

Heimler

Amedi

2020

Neuroscience & Biobehavioral Reviews

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“…A recent study with adults also fits with this type of explanation (Negen, Wen, Thaler, & Nardini, 2018). Adults were asked to learn new depth cues -based either on sound delay or wrist vibration -and combine these with a noisy visual cue.…”

Section: The Hard Limit At 10-11 Hypothesismentioning

confidence: 85%

Sensory Cue Combination in Children Under 10 Years of Age

Negen

Chere

Bird

et al. 2018

Preprint

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Cue combination occurs when two independent noisy perceptual estimates are merged together as a weighted average, creating a unified estimate that is more precise than either single estimate alone. Surprisingly, this effect has not been demonstrated compellingly in children under the age of 10 years, in contrast with the array of other multisensory skills that children show even in infancy. Instead, across a wide variety of studies, precision with both cues is no better than the best single cue – and sometimes worse. Here we provide the first consistent evidence of cue combination in children from 7–10 years old. Across three experiments, participants showed evidence of a bimodal precision advantage (Experiments 1a and 1b) and the majority were best-fit by a combining model (Experiment 2). The task was to localize a target horizontally with a binaural audio cue and a noisy visual cue in immersive virtual reality. Feedback was given as well, which could both (a) help participants judge how reliable each cue is and (b) help correct between-cue biases that might prevent cue combination. A feedback effect was found in Experiment 2, with children who were given single-cue feedback showing the highest rate of cue combination. Given this, we suggest that children at 7–10 years old are capable of cue combination in principle, but must have sufficient representations of reliabilities and biases in their own perceptual estimates as relevant to the task, which can be facilitated through task-specific feedback.

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“…Indeed, a recent tutorial detailing how to test for optimal cue integration has proposed a visual taxonomy by which one can judge the fit of a set of data to MWF by visual inspection of the data, associated error bars and model predictions (Rohde et al, 2016). This taxonomy has started to be used researchers to assess the adherence to MWF (Negen et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

“…Indeed, a recent review has suggested that the adherence to optimal cue integration (without comparison to alternative models) can be assessed visually and has provided a visual taxonomy of "optimal", "sub-optimal", "ambiguous", "near optimal" and "supra-optimal" performance (Rohde et al, 2016, p. 23). This visual taxonomy, of judging the fit to the predictions of optimal cue integration based upon visual inspection of (1) the data, (2) the error bars around the data, and (3) the predictions of optimal cue integration, has started to be used by researchers to assess "optimality" of experimental data through adherence to MWF (Negen, Wen, Thaler, & Nardini, 2018).…”

Section: Alternative Models To Mwfmentioning

confidence: 99%

Experimentally disambiguating models of sensory cue integration

Scarfe

2020

Preprint

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Sensory cue integration is one of the primary areas in which a normative mathematical framework has been used to (1) define the “optimal” way in which to make decisions based upon ambiguous sensory information and (2) compare these predictions to an organism’s behaviour. The conclusion from such studies is that sensory cues are integrated in a statistically optimal fashion. Problematically, numerous alternative computational frameworks exist by which sensory cues could be integrated, many of which could be described as “optimal” base on different optimising criteria. Existing studies rarely assess the evidence relative to different candidate models, resulting in an inability to conclude that sensory cues are integrated according to the experimenters preferred framework. The aims of the present paper are to summarise and highlight the implicit assumptions rarely acknowledged in testing models of sensory cue integration, as well as to introduce an unbiased and principled method by which to distinguish the probability with which experimental data is consistent with a set of candidate models.

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Bayes-Like Integration of a New Sensory Skill with Vision

Cited by 24 publications

References 48 publications

Are critical periods reversible in the adult brain? Insights on cortical specializations based on sensory deprivation studies

Are critical periods reversible in the adult brain? Insights on cortical specializations based on sensory deprivation studies

Sensory Cue Combination in Children Under 10 Years of Age

Experimentally disambiguating models of sensory cue integration

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