Modality Shift Effect in Psychiatric Disorders – a New Look at an Old Paradigm

Krag, P; Licht, Rasmus W; Nielsen, René Ernst

doi:10.1016/j.eurpsy.2016.08.010

Cited by 1 publication

(1 citation statement)

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“…Attentional control may be affected in a number of populations and the MSE paradigm has been used to investigate attention across the senses, most commonly in studies of schizophrenia (see Mannuzza, 1980, for a review). This work has indicated that MSEs between visual and auditory targets are increased in the condition (Ferstl et al, 1994;Krag et al, 2017;Spring, 1980). The MSE has also been investigated in dyslexia (Harrar et al, 2014).…”

Section: Introductionmentioning

confidence: 98%

Shifting attention between modalities: Revisiting the modality-shift effect in autism

Poole

Miles

Gowen

et al. 2021

Atten Percept Psychophys

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Selective attention to a sensory modality has been observed experimentally in studies of the modality-shift effect – a relative performance benefit for targets preceded by a target in the same modality, compared to a different modality. Differences in selective attention are commonly observed in autism and we investigated whether exogenous (automatic) shift costs between modalities are increased. Autistic adults and neurotypical controls made speeded discrimination responses to simple visual, tactile and auditory targets. Shift costs were observed for each target modality in participant response times and were largest for auditory targets, reflective of fast responses on auditory repeat trials. Critically, shift costs were similar between the groups. However, integrating speed and accuracy data using drift-diffusion modelling revealed that shift costs in drift rates (reflecting the quality of information extracted from the stimulus) were reduced for autistic participants compared with neurotypicals. It may be that, unlike neurotypicals, there is little difference between attention within and between sensory modalities for autistic people. This finding also highlights the benefit of combining reaction time and accuracy data using decision models to better characterise selective attention in autism.

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