A specific implicit sequence learning deficit as an underlying cause of dyslexia? Investigating the role of attention in implicit learning tasks.

2017 ◽  
Vol 31 (4) ◽  
pp. 371-382 ◽  
Author(s):  
Eva Staels ◽  
Wim Van den Broeck
Keyword(s):  
Implicit Learning ◽  
Sequence Learning ◽  
Implicit Sequence Learning ◽  
Learning Deficit ◽  
Learning Tasks

Evidence of Developmental Differences in Implicit Sequence Learning: An fMRI Study of Children and Adults

2004 ◽  
Vol 16 (8) ◽  
pp. 1339-1351 ◽  
Author(s):  
Kathleen M. Thomas ◽  
Ruskin H. Hunt ◽  
Nathalie Vizueta ◽  
Tobias Sommer ◽  
Sarah Durston ◽  
...  
Keyword(s):  
Implicit Learning ◽  
Sequence Learning ◽  
Premotor Cortex ◽  
Age Groups ◽  
Reaction Time Task ◽  
Memory Systems ◽  
Brain Regions ◽  
Developmental Differences ◽  
Implicit Sequence Learning ◽  
Age Related

Prevailing theories of implicit or unaware learning propose a developmental invariance model, with implicit function maturing early in infancy or childhood despite prolonged improvements in explicit or intentional learning and memory systems across childhood. Neuroimaging studies of adult visuomotor sequence learning have associated fronto-striatal brain regions with implicit learning of spatial sequences. Given evidence of continued development in these brain regions during childhood, we compare implicit sequence learning in adults and 7- to 11-year-old children to examine potential developmental differences in the recruitment of fronto-striatal circuitry during implicit learning. Participants performed a standard serial reaction time task. Stimuli alternately followed a fixed 10-step sequence of locations or were presented in a pseudorandom order of locations. Adults outperformed children, achieving a significantly larger sequence learning effect and showing learning more quickly than children. Age-related differences in activity were observed in the premotor cortex, putamen, hippocampus, inferotemporal cortex, and parietal cortex. We observed differential recruitment of cortical and subcortical motor systems between groups, presumably reflecting age differences in motor response execution. Adults showed greater hippocampal activity for sequence trials, whereas children demonstrated greater signal during random trials. Activity in the right caudate correlated significantly with behavioral measures of implicit learning for both age groups, although adults showed greater signal change than children overall, as would be expected given developmental differences in sequence learning magnitude. These results challenge the idea of developmental invariance in implicit learning and instead support a view of parallel developments in implicit and explicit learning systems.

The Effect of Within Stimulus Presentation in Implicit Sequence Learning

2005 ◽  
Vol 49 (21) ◽  
pp. 1836-1840
Author(s):  
Timothy A. Nichols ◽  
Arthur D. Fisk ◽  
Wendy A. Rogers
Keyword(s):  
Implicit Learning ◽  
Dual Task ◽  
Sequence Learning ◽  
Traffic Control ◽  
Single Stimulus ◽  
Implicit Sequence Learning ◽  
Multiple Control ◽  
Task Interference ◽  
Dual Task Condition ◽  
Dual Task Interference

The tacit and incidental acquisition of sequential information can occur in tasks from air-traffic control to crossing the streets in a crowded metropolis. The present study investigated how implicit sequence learning occurs when attention is divided amongst tasks. Our conceptualization of implicit sequence learning is that dual task interference arises from multiple control processes in the secondary task. This fits with findings that implicit learning remains intact when a within stimulus dual task is employed, where the stimulus for both tasks is incorporated within a single stimulus. However, a direct comparison with the standard dual task condition has not been presented. This comparison revealed another possible explanation for dual task interference in implicit sequence learning, that longer inter-trial intervals, a function of the within stimulus methodology, result in better performance and implicit learning. The data suggest that implicit learning and overall performance in a task that contains an incidental, consistent structure is optimized when stimuli are contained within a single stimulus.

Implicit sequence learning despite multitasking: the role of across-task predictability

2017 ◽  
Vol 83 (3) ◽  
pp. 526-543 ◽  
Author(s):  
Eva Röttger ◽  
Hilde Haider ◽  
Fang Zhao ◽  
Robert Gaschler
Keyword(s):  
Sequence Learning ◽  
Implicit Sequence Learning

Re-examining the role of context in implicit sequence learning

2014 ◽  
Vol 27 ◽  
pp. 172-193 ◽  
Author(s):  
Maria C. D’Angelo ◽  
Bruce Milliken ◽  
Luis Jiménez ◽  
Juan Lupiáñez
Keyword(s):  
Sequence Learning ◽  
Implicit Sequence Learning

scholarly journals The ecological validity of MET was favourable in sitting implicit sequence learning consciousness by eyes closed and eyes open resting states fMRI

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jianxin Zhang ◽  
Xiangpeng Wang ◽  
Didi Zhang ◽  
Antao Chen ◽  
Dianzhi Liu
Keyword(s):  
Implicit Learning ◽  
Sequence Learning ◽  
Resting State ◽  
Ecological Validity ◽  
Implicit Sequence Learning ◽  
Brain Areas ◽  
Learning Network ◽  
Eyes Closed ◽  
Motor Network ◽  
Eyes Open

AbstractThe current study made participants sit to complete both the implicit sequence learning and the inclusion/exclusion tasks with the latter just after the former, and used eyes-closed and eyes-open resting states fMRI and their difference to test the ecological validity of the mutually exclusive theory (MET) in implicit-sequence-learning consciousness. (1) The behavioral and neuroimaging data did not support the process dissociation procedure, but did fit well with the MET. The correct inclusion-task response and the incorrect exclusion-task response were mutually exclusive with each other. The relevant brain areas of the two responses were either different or opposite in the eyes-closed and eyes-open resting-states and their difference. (2) ALFFs in eyes-closed and eyes-open resting-states and their difference were diversely related to the four MET knowledge in implicit sequence learning. The relevant brain areas of the four MET knowledge in the eyes-closed and eyes-open resting-state were the cerebral cortex responsible for vision, attention, cognitive control and consciousness, which could be called the upper consciousness network, and there were more relevant brain areas in the eyes-open resting-state than in the eye-closed resting-state.The relevant brain areas in ALFFs-difference were the subcortical nucleus responsible for sensory awareness, memory and implicit sequence learning, which could be called the lower consciousness network. ALFFs-difference could predict the four MET knowledge as a quantitative transition sensitivity index from internal feeling to external stimulus. (3) The relevant resting-state brain areas of the four MET knowledge were either different (for most brain areas, if some brain areas were related to one MET knowledge, they were not related to the other three MET knowledge) or opposite (for some brain areas, if some brain areas were positively related to one MET knowledge, they were negatively related to other MET knowledge). With the participants' control/consciousness level increasing from no-acquisition to controllable knowledge step by step, the positively relevant resting-state brain areas of the four MET knowledge changed from some consciousness network and the motor network, to some consciousness network and the implicit learning network, and then to some consciousness network; and the negatively relevant resting-state brain areas of the four MET knowledge changed from some consciousness network and visual perception network, to some consciousness network, then to some consciousness network and the motor network, and then to some consciousness network, the implicit learning network, and the motor network. In conclusion, the current study found the ecological validity of the MET was good in sitting posture and eyes-closed and eyes-open resting-states, ALFFs in eyes-closed and eyes-open resting-states and their difference could predict the four MET knowledge diversely, and the four MET knowledge had different or opposite relevant resting-state brain areas.

scholarly journals Implicit Learning of True and False Belief Sequences

2021 ◽  
Vol 12 ◽  
Author(s):  
Qianying Ma ◽  
Elien Heleven ◽  
Giulia Funghi ◽  
Min Pu ◽  
Kris Baetens ◽  
...  
Keyword(s):  
Implicit Learning ◽  
Sequence Learning ◽  
Reaction Times ◽  
Social Conditions ◽  
False Belief ◽  
Three Dimensions ◽  
Implicit Sequence Learning ◽  
Related Sequence ◽  
Motor Responses ◽  
True False

To investigate whether people can implicitly learn regularities in a social context, we developed a new implicit sequence learning task combining elements from classic false belief and serial reaction time tasks. Participants learned that protagonists were offered flowers at four locations. The protagonists' beliefs concerning the flowers were true or false, depending on their orientation, respectively, toward the scene (so that the flowers could be seen) or away from it. Unbeknown to the participants, there was a fixed belief-related sequence involving three dimensions (identity of the two protagonists, true-false belief orientation held by the protagonists, and flower location as believed by the protagonists). Participants had to indicate as fast as possible where the flowers were located (Experiment 1), or how many flowers were given (Experiment 2) according to the protagonists. Experiment 1 combined perceptual and motor processes (as both the belief-related sequence and motor responses referred to location), whereas Experiment 2 unconfounded the sequence and motor responses, allowing to investigate pure perceptual implicit learning. For reasons of comparison, two non-social conditions were created in Experiment 2 by replacing the protagonists with two non-social objects—colored cameras or shapes. Results revealed significant implicit sequence learning of all belief-related dimensions in Experiment 1, and of true-false belief orientation in Experiment 2, even without a motor confound. Importantly, there were faster reaction times and stronger sequence learning effects in the social than in the non-social conditions. The present findings demonstrate for the first time that people are able to implicitly learn belief-related sequences.

On the Role of Fragmentary Knowledge in a Sequence Learning Task

1998 ◽  
Vol 51 (2) ◽  
pp. 251-281 ◽  
Author(s):  
Axel Buchner ◽  
Melanie C. Steffens ◽  
Rainer Rothkegel
Keyword(s):  
Sequence Learning ◽  
Explicit Knowledge ◽  
Reaction Times ◽  
Measurement Model ◽  
Learning Task ◽  
Memory Processes ◽  
Learning Tasks ◽  
Considerable Debate ◽  
Adapted Process

There has been considerable debate about whether or not we need to distinguish between the acquisition of implicit—and, independently thereof, the acquisition of explicit—knowledge in sequence learning tasks. Proponents of the view that a unitary knowledge base is formed assume (a) that the knowledge acquired is explicitly available, and (b) that information about sequence fragments forms the core of this explicit knowledge. Both of these issues are addressed empirically in the present article. In two experiments, an adapted process dissociation procedure and a suitable measurement model were used to separate recollective (explicit) and fluency-based (implicit) memory processes in a sequence learning task. Experiment 1 demonstrated that fluency-based processes came into play much later than recollective processes. Such recollective processes have been conceptualized as being based on simple knowledge about sequence fragments or chunks. Indeed, Experiment 2 showed that recollective processes are more likely to contribute to sequence judgements if chunks are readily available at test than if they are not. Together, these results are in line with the view that the learning of an event systematicity can be conceived of as the memorization of chunks of events that support both the speeding up of reaction times to systematic events and explicit, recollective memory processes even after relatively little training.

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