Muscle activity in explicit and implicit sequence learning: Exploring additional measures of learning and certainty via tensor decomposition
Sequence learning in serial reaction time tasks (SRTTs) is usually inferred through the reaction time measured by a keyboard. However, this chronometric parameter offers no information beyond the time point of the button-press. We therefore examined whether sequence learning can be measured by muscl...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-06-01
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| Series: | Acta Psychologica |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0001691822001020 |
| _version_ | 1817990824223309824 |
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| author | Amalaswintha Leh Christine Langhanns Fang Zhao Robert Gaschler Hermann Müller |
| author_facet | Amalaswintha Leh Christine Langhanns Fang Zhao Robert Gaschler Hermann Müller |
| author_sort | Amalaswintha Leh |
| collection | DOAJ |
| description | Sequence learning in serial reaction time tasks (SRTTs) is usually inferred through the reaction time measured by a keyboard. However, this chronometric parameter offers no information beyond the time point of the button-press. We therefore examined whether sequence learning can be measured by muscle activations via electromyography (EMG) in a dual-task paradigm. The primary task was a SRTT, in which the stimuli followed a fixed sequence in some blocks, whereas the sequence was random in the control condition. The secondary task stimulus was always random. One group was informed about the fixed sequence, and the other not. We assessed three dependent variables. The chronometric parameter premotor time represents the duration between stimulus onset and the onset of EMG activity, which indicates the start of the response. The other variables describe the response itself considering the EMG activity after response start. The EMG integral was analyzed, and additionally, tensor decomposition was implemented to assess sequence dependent changes in the contribution of the obtained subcomponents. The results show explicit sequence learning in this dual-task setting. Specifically, the informed group show shorter premotor times in fixed than random sequences as well as larger EMG integral and tensor contributions. Further, increased activity seems to represent response certainty, since a decrease is found for both groups in trials following erroneous responses. Interestingly, the sensitivity to sequence and post-error effects varies between the subcomponents. The results indicate that muscle activity can be a useful indicator of response behavior in addition to chronometric parameters. |
| first_indexed | 2024-04-14T01:05:06Z |
| format | Article |
| id | doaj.art-246c2c965e5344529c27ceade3cc8e39 |
| institution | Directory Open Access Journal |
| issn | 0001-6918 |
| language | English |
| last_indexed | 2024-04-14T01:05:06Z |
| publishDate | 2022-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Acta Psychologica |
| spelling | doaj.art-246c2c965e5344529c27ceade3cc8e392022-12-22T02:21:17ZengElsevierActa Psychologica0001-69182022-06-01226103587Muscle activity in explicit and implicit sequence learning: Exploring additional measures of learning and certainty via tensor decompositionAmalaswintha Leh0Christine Langhanns1Fang Zhao2Robert Gaschler3Hermann Müller4Neuromotor Behavior Laboratory, Department of Psychology and Sport Science, Justus Liebig University Giessen, Germany; Corresponding author at: Experimental Sensomotorics, Kugelberg 62, 35394 Giessen, Germany.Neuromotor Behavior Laboratory, Department of Psychology and Sport Science, Justus Liebig University Giessen, GermanyResearch Cluster D2L2, FernUniversität in Hagen, GermanyExperimental Psychology (Learning, Motivation, Emotion), Faculty of Psychology, FernUniversität in Hagen, GermanyNeuromotor Behavior Laboratory, Department of Psychology and Sport Science, Justus Liebig University Giessen, Germany; Center for Mind, Brain and Behavior, Forschungscampus Mittelhessen, Universities Giessen and Marburg, GermanySequence learning in serial reaction time tasks (SRTTs) is usually inferred through the reaction time measured by a keyboard. However, this chronometric parameter offers no information beyond the time point of the button-press. We therefore examined whether sequence learning can be measured by muscle activations via electromyography (EMG) in a dual-task paradigm. The primary task was a SRTT, in which the stimuli followed a fixed sequence in some blocks, whereas the sequence was random in the control condition. The secondary task stimulus was always random. One group was informed about the fixed sequence, and the other not. We assessed three dependent variables. The chronometric parameter premotor time represents the duration between stimulus onset and the onset of EMG activity, which indicates the start of the response. The other variables describe the response itself considering the EMG activity after response start. The EMG integral was analyzed, and additionally, tensor decomposition was implemented to assess sequence dependent changes in the contribution of the obtained subcomponents. The results show explicit sequence learning in this dual-task setting. Specifically, the informed group show shorter premotor times in fixed than random sequences as well as larger EMG integral and tensor contributions. Further, increased activity seems to represent response certainty, since a decrease is found for both groups in trials following erroneous responses. Interestingly, the sensitivity to sequence and post-error effects varies between the subcomponents. The results indicate that muscle activity can be a useful indicator of response behavior in addition to chronometric parameters.http://www.sciencedirect.com/science/article/pii/S0001691822001020Serial reaction time taskDual-taskingEMG tensor decompositionExplicit learningImplicit learning |
| spellingShingle | Amalaswintha Leh Christine Langhanns Fang Zhao Robert Gaschler Hermann Müller Muscle activity in explicit and implicit sequence learning: Exploring additional measures of learning and certainty via tensor decomposition Acta Psychologica Serial reaction time task Dual-tasking EMG tensor decomposition Explicit learning Implicit learning |
| title | Muscle activity in explicit and implicit sequence learning: Exploring additional measures of learning and certainty via tensor decomposition |
| title_full | Muscle activity in explicit and implicit sequence learning: Exploring additional measures of learning and certainty via tensor decomposition |
| title_fullStr | Muscle activity in explicit and implicit sequence learning: Exploring additional measures of learning and certainty via tensor decomposition |
| title_full_unstemmed | Muscle activity in explicit and implicit sequence learning: Exploring additional measures of learning and certainty via tensor decomposition |
| title_short | Muscle activity in explicit and implicit sequence learning: Exploring additional measures of learning and certainty via tensor decomposition |
| title_sort | muscle activity in explicit and implicit sequence learning exploring additional measures of learning and certainty via tensor decomposition |
| topic | Serial reaction time task Dual-tasking EMG tensor decomposition Explicit learning Implicit learning |
| url | http://www.sciencedirect.com/science/article/pii/S0001691822001020 |
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