The Experts below are selected from a list of 80217 Experts worldwide ranked by ideXlab platform
Tomas Knapen - One of the best experts on this subject based on the ideXlab platform.
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Implicit and Explicit Learning in reactive and voluntary saccade adaptation.
PloS one, 2019Co-Authors: Daniel Marten Van Es, Tomas KnapenAbstract:Saccades can either be elicited automatically by salient peripheral stimuli or can additionally depend on Explicit cognitive goals. Similarly, it is thought that motor adaptation is driven by the combination of a more automatic, implicit process and a more Explicit, cognitive process. However, the degree to which such implicit and Explicit Learning contribute to the adaptation of more reactive and voluntary saccades remains elusive. To study this question, we employed a global saccadic adaptation paradigm with both increasing and decreasing saccade amplitudes. We assessed the resulting adaptation using a dual state model of motor adaptation. This model decomposes Learning into a fast and slow process, which are thought to constitute Explicit and implicit Learning, respectively. Our results show that adaptation of reactive saccades is equally driven by fast and slow Learning, while fast Learning is nearly absent when adapting voluntary (i.e. scanning) saccades. This pattern of results was present both when saccade gain was increased or decreased. Our results suggest that the increased cognitive demands associated with voluntary compared to reactive saccade planning interfere specifically with Explicit Learning.
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Implicit and Explicit Learning in reactive and voluntary saccade adaptation
2018Co-Authors: Daniel Marten Van Es, Tomas KnapenAbstract:Saccades can either be elicited automatically by salient peripheral stimuli or can additionally depend on Explicit cognitive goals. Similarly, it is thought that motor adaptation is driven by the combination of a more automatic, implicit process and a more Explicit, cognitive process. However, the degree to which such implicit and Explicit Learning contribute to the adaptation of more reactive and voluntary saccades remains elusive. To study this question, we employed a global saccadic adaptation paradigm with both increasing and decreasing saccade amplitudes. We assessed the resulting adaptation using a dual state model of motor adaptation. This model decomposes Learning into a fast and slow process, which are thought to constitute the Explicit and implicit Learning, respectively. Our results show that adaptation of reactive saccades is equally driven by fast and slow Learning, while fast Learning is nearly absent when adapting voluntary (i.e. scanning) saccades. This pattern of results was present both when saccade gain was increased or decreased. Our results suggest that the increased cognitive demands associated with voluntary compared to reactive saccade planning interfere specifically with Explicit Learning.
Mark Hallett - One of the best experts on this subject based on the ideXlab platform.
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implicit and Explicit Learning in an auditory serial reaction time task
Acta Neurologica Scandinavica, 2009Co-Authors: P Zhuang, Nguyet Dang, A Warzeri, Christian Gerloff, Leonardo G Cohen, Mark HallettAbstract:Objective - To explore the role of the motor cortex during implicit and Explicit Learning. Materials and methods - EEG signals were recorded from 30 channels by measuring task-related desynchronization (TRD) when 10 right-handed naive volunteers performed a variation of the serial reaction task. Stimuli, consisting of 4 pure tones of 500, 1000, 1500, and 2000 HZ, lasting 200 ms, were presented binaurally through a pair of tubephones at 60 dB with a 2-s constant interstimulus interval. A series of 10 repetitive tones represented the test sequence; the random sequence was the control. Results - All subjects developed implicit and Explicit knowledge reflected by decreased response time, increased accuracy, and the ability to generate the sequence. Six of 10 subjects demonstrated implicit Learning without Explicit Learning during the first 3 blocks. When subjects acquired full Explicit Learning, 10 Hz TRD at C3 reached a peak amplitude, declining thereafter. Conclusions - Properties of the sensorimotor cortex change during Learning and these changes are independent of stimulus modality.
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Event-related desynchronization (ERD) in the alpha frequency during development of implicit and Explicit Learning
Electroencephalography and clinical neurophysiology, 1997Co-Authors: P Zhuang, Camilo Toro, Jordan Grafman, Paolo Manganotti, Letizia Leocani, Mark HallettAbstract:To understand the role of the motor cortex in implicit and Explicit Learning, we studied alpha event-related desynchronization (ERD) while 13 right-handed individuals performed a variation of the serial reaction time task (SRTT). EEG signals were recorded simultaneously from 29 scalp locations and the ERD was computed. During data collection, all subjects developed implicit knowledge, demonstrated by shortening of the response time, and Explicit knowledge of the test sequence. The average ERD maps of all 13 subjects demonstrated that during the initial Learning, there was a decline in alpha band power that was maximal over the contralateral central region. The ERD reached a transient peak amplitude at a point when the subjects attained full Explicit knowledge, and diminished subsequently. The transient peak in ERD was highly significant at C3. These electrophysiologic findings support previous studies which have demonstrated that motor activity changes as behavior changes over the course of Learning.
Rosemary J. Stevenson - One of the best experts on this subject based on the ideXlab platform.
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Explicit Learning of a Dynamic System with a Non-salient Pattern
The Quarterly Journal of Experimental Psychology Section A, 1997Co-Authors: Bruce W. Geddes, Rosemary J. StevensonAbstract:We examine the hypothesis that a specific goal leads to implicit Learning, whereas a nonspecific goal leads to Explicit Learning, even though the pattern to be learnt is non-salient. Subjects learned a dynamic control task (Berry & Broadbent, 1984). One group of subjects had a specific control goal, the second group had a non-specific pattern-search goal, and the third group had both goals. On measures of Learning (control performance, prediction, and general questions), the non-specific group learnt Explicitly, outperforming the other two groups on all Learning measures. The specific group performed next best on control performance and prediction questions but performed very poorly on general questions. The dual-goal group performed poorly on all measures. Non-specific subjects predicted well on both familiar and unfamiliar situations. Specific-goal subjects predicted well on familiar situations, regardless of whether their previous response had been correct or incorrect. Dual-goal subjects predicted wel...
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Explicit Learning of a DynamicSystemwith a Non-salient Pattern
1997Co-Authors: Bruce W. Geddes, Rosemary J. StevensonAbstract:We examine the hypothesis that a specie c goal leads to implicit Learning, whereas a nonspecie c goal leads to Explicit Learning, even though the pattern to be learnt is non-salient. Subjects learned a dynamic control task (Berry & Broadbent, 1984). One group of subjects had a speciec control goal, the second group had a non-speciec pattern-search goal, and the third group had both goals. On measures of Learning (control performance, prediction, and general questions), the non-speciec group learnt Explicitly, outperforming the other two groups on all Learningmeasures. The specie c group performednext best on controlperformance and predictionquestionsbut performedvery poorly on general questions. The dual-goal group performed poorly on all measures. Non-speciec subjects predicted well on both familiar and unfamiliar situations. Specie c-goal subjects predicted well on familiar situations, regardless of whether their previous response had been correct or incorrect. Dual-goal subjects predicted well only on familiar correct situations. We conclude that the non-speciec group learned through Explicit hypothesis testing, the specie c group learned through a mixture of Explicit problem solving and implicit instance Learning, and the dual-goal group learned instances.Resultsare discussed in terms of dual-space models of problemsolving and hypothesis testing and in terms of implicit instance Learning. We consider how the choice of Learning goal affects the cognitive processes used during Learning and suggest that having subjects learn the same information implicitly or Explicitly is potentially useful for drawing clearer distinctions between implicit and Explicit modes of Learning.
Daniel Marten Van Es - One of the best experts on this subject based on the ideXlab platform.
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Implicit and Explicit Learning in reactive and voluntary saccade adaptation.
PloS one, 2019Co-Authors: Daniel Marten Van Es, Tomas KnapenAbstract:Saccades can either be elicited automatically by salient peripheral stimuli or can additionally depend on Explicit cognitive goals. Similarly, it is thought that motor adaptation is driven by the combination of a more automatic, implicit process and a more Explicit, cognitive process. However, the degree to which such implicit and Explicit Learning contribute to the adaptation of more reactive and voluntary saccades remains elusive. To study this question, we employed a global saccadic adaptation paradigm with both increasing and decreasing saccade amplitudes. We assessed the resulting adaptation using a dual state model of motor adaptation. This model decomposes Learning into a fast and slow process, which are thought to constitute Explicit and implicit Learning, respectively. Our results show that adaptation of reactive saccades is equally driven by fast and slow Learning, while fast Learning is nearly absent when adapting voluntary (i.e. scanning) saccades. This pattern of results was present both when saccade gain was increased or decreased. Our results suggest that the increased cognitive demands associated with voluntary compared to reactive saccade planning interfere specifically with Explicit Learning.
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Implicit and Explicit Learning in reactive and voluntary saccade adaptation
2018Co-Authors: Daniel Marten Van Es, Tomas KnapenAbstract:Saccades can either be elicited automatically by salient peripheral stimuli or can additionally depend on Explicit cognitive goals. Similarly, it is thought that motor adaptation is driven by the combination of a more automatic, implicit process and a more Explicit, cognitive process. However, the degree to which such implicit and Explicit Learning contribute to the adaptation of more reactive and voluntary saccades remains elusive. To study this question, we employed a global saccadic adaptation paradigm with both increasing and decreasing saccade amplitudes. We assessed the resulting adaptation using a dual state model of motor adaptation. This model decomposes Learning into a fast and slow process, which are thought to constitute the Explicit and implicit Learning, respectively. Our results show that adaptation of reactive saccades is equally driven by fast and slow Learning, while fast Learning is nearly absent when adapting voluntary (i.e. scanning) saccades. This pattern of results was present both when saccade gain was increased or decreased. Our results suggest that the increased cognitive demands associated with voluntary compared to reactive saccade planning interfere specifically with Explicit Learning.
P Zhuang - One of the best experts on this subject based on the ideXlab platform.
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implicit and Explicit Learning in an auditory serial reaction time task
Acta Neurologica Scandinavica, 2009Co-Authors: P Zhuang, Nguyet Dang, A Warzeri, Christian Gerloff, Leonardo G Cohen, Mark HallettAbstract:Objective - To explore the role of the motor cortex during implicit and Explicit Learning. Materials and methods - EEG signals were recorded from 30 channels by measuring task-related desynchronization (TRD) when 10 right-handed naive volunteers performed a variation of the serial reaction task. Stimuli, consisting of 4 pure tones of 500, 1000, 1500, and 2000 HZ, lasting 200 ms, were presented binaurally through a pair of tubephones at 60 dB with a 2-s constant interstimulus interval. A series of 10 repetitive tones represented the test sequence; the random sequence was the control. Results - All subjects developed implicit and Explicit knowledge reflected by decreased response time, increased accuracy, and the ability to generate the sequence. Six of 10 subjects demonstrated implicit Learning without Explicit Learning during the first 3 blocks. When subjects acquired full Explicit Learning, 10 Hz TRD at C3 reached a peak amplitude, declining thereafter. Conclusions - Properties of the sensorimotor cortex change during Learning and these changes are independent of stimulus modality.
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Event-related desynchronization (ERD) in the alpha frequency during development of implicit and Explicit Learning
Electroencephalography and clinical neurophysiology, 1997Co-Authors: P Zhuang, Camilo Toro, Jordan Grafman, Paolo Manganotti, Letizia Leocani, Mark HallettAbstract:To understand the role of the motor cortex in implicit and Explicit Learning, we studied alpha event-related desynchronization (ERD) while 13 right-handed individuals performed a variation of the serial reaction time task (SRTT). EEG signals were recorded simultaneously from 29 scalp locations and the ERD was computed. During data collection, all subjects developed implicit knowledge, demonstrated by shortening of the response time, and Explicit knowledge of the test sequence. The average ERD maps of all 13 subjects demonstrated that during the initial Learning, there was a decline in alpha band power that was maximal over the contralateral central region. The ERD reached a transient peak amplitude at a point when the subjects attained full Explicit knowledge, and diminished subsequently. The transient peak in ERD was highly significant at C3. These electrophysiologic findings support previous studies which have demonstrated that motor activity changes as behavior changes over the course of Learning.
