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Kosilo M, Martinovic J, Haenschel C. Luminance Contrast Drives Interactions between Perception and Working Memory. J Cogn Neurosci 2022; 34:1128-1147. [PMID: 35468214 DOI: 10.1162/jocn_a_01852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Visual working memory (WM) enables the use of past sensory experience in guiding behavior. Yet, laboratory tasks commonly evaluate WM in a way that separates it from its sensory bottleneck. To understand how perception interacts with visual memory, we used a delayed shape recognition task to probe how WM may differ for stimuli that bias processing toward different visual pathways. Luminance compared with chromatic signals are more efficient in driving the processing of shapes and may thus also lead to better WM encoding, maintenance, and memory recognition. To evaluate this prediction, we conducted two experiments. In the first psychophysical experiment, we measured contrast thresholds for different WM loads. Luminance contrast was encoded into WM more efficiently than chromatic contrast, even when both sets of stimuli were equated for discriminability. In the second experiment, which also equated stimuli for discriminability, early sensory responses in the EEG that are specific to luminance pathways were modulated by WM load and thus likely reflect the neural substrate of the increased efficiency. Our results cannot be accounted for by simple saliency differences between luminance and color. Rather, they provide evidence for a direct connection between low-level perceptual mechanisms and WM by showing a crucial role of luminance for forming WM representations of shape.
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Affiliation(s)
- Maciej Kosilo
- University of London, United Kingdom.,University of Lisbon, Portugal
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Poiroux E, Cavaro-Ménard C, Leruez S, Lemée JM, Richard I, Dinomais M. What Do Eye Gaze Metrics Tell Us about Motor Imagery? PLoS One 2015; 10:e0143831. [PMID: 26605915 PMCID: PMC4659676 DOI: 10.1371/journal.pone.0143831] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2015] [Accepted: 11/10/2015] [Indexed: 11/18/2022] Open
Abstract
Many of the brain structures involved in performing real movements also have increased activity during imagined movements or during motor observation, and this could be the neural substrate underlying the effects of motor imagery in motor learning or motor rehabilitation. In the absence of any objective physiological method of measurement, it is currently impossible to be sure that the patient is indeed performing the task as instructed. Eye gaze recording during a motor imagery task could be a possible way to "spy" on the activity an individual is really engaged in. The aim of the present study was to compare the pattern of eye movement metrics during motor observation, visual and kinesthetic motor imagery (VI, KI), target fixation, and mental calculation. Twenty-two healthy subjects (16 females and 6 males), were required to perform tests in five conditions using imagery in the Box and Block Test tasks following the procedure described by Liepert et al. Eye movements were analysed by a non-invasive oculometric measure (SMI RED250 system). Two parameters describing gaze pattern were calculated: the index of ocular mobility (saccade duration over saccade + fixation duration) and the number of midline crossings (i.e. the number of times the subjects gaze crossed the midline of the screen when performing the different tasks). Both parameters were significantly different between visual imagery and kinesthesic imagery, visual imagery and mental calculation, and visual imagery and target fixation. For the first time we were able to show that eye movement patterns are different during VI and KI tasks. Our results suggest gaze metric parameters could be used as an objective unobtrusive approach to assess engagement in a motor imagery task. Further studies should define how oculomotor parameters could be used as an indicator of the rehabilitation task a patient is engaged in.
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Affiliation(s)
- Elodie Poiroux
- LUNAM, Université d’Angers, Laboratoire Angevin de Recherche en Ingénierie des Systèmes (LARIS), EA 7315 F-49000, Angers, France
- LUNAM, Université d’Angers, Département de Médecine Physique et de Réadaptation, CHU d’Angers, 4 rue Larrey, 49933, Angers, Cedex 9, France
| | - Christine Cavaro-Ménard
- LUNAM, Université d’Angers, Laboratoire Angevin de Recherche en Ingénierie des Systèmes (LARIS), EA 7315 F-49000, Angers, France
| | - Stéphanie Leruez
- LUNAM, Université d’Angers, Laboratoire Angevin de Recherche en Ingénierie des Systèmes (LARIS), EA 7315 F-49000, Angers, France
- LUNAM, Université d’Angers, Département d’Ophtalmologie, CHU d’Angers, 4 rue Larrey, 49933, Angers, Cedex 9, France
| | - Jean Michel Lemée
- LUNAM, Université d’Angers, Département de Neurochirurgie, CHU d’Angers, 4 rue Larrey, 49933, Angers, Cedex 9, France
- LUNAM, Université d’Angers, INSERM U1066 « Micro- et nano-médecines biomimétiques », bâtiment IRIS 3e étage, CHU d’Angers, 4 rue Larrey, 49933, Angers, Cedex 9, France
| | - Isabelle Richard
- LUNAM, Université d’Angers, Département de Médecine Physique et de Réadaptation, CHU d’Angers, 4 rue Larrey, 49933, Angers, Cedex 9, France
- LUNAM, Université d’Angers, Laboratoire d’épidémiologie, ergonomie et santé au travail, EA 4626 F-49000, Angers, France
| | - Mickael Dinomais
- LUNAM, Université d’Angers, Laboratoire Angevin de Recherche en Ingénierie des Systèmes (LARIS), EA 7315 F-49000, Angers, France
- LUNAM, Université d’Angers, Département de Médecine Physique et de Réadaptation, CHU d’Angers, 4 rue Larrey, 49933, Angers, Cedex 9, France
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