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Compositional symbol grounding for motor patterns.

Greco A, Caneva C - Front Neurorobot (2010)

Bottom Line: In this experiment, the compositional group achieved better results in naming motor patterns especially for patterns where hand postures discrimination was relevant.In order to ascertain the differential effect, upon this result, of memory load and of systematic grounding, neural network simulations were also made.All results are discussed in connection to the possible support of the hypothesis of a compositional motor representation and toward a more precise explanation of the factors that make compositional representations working.

View Article: PubMed Central - PubMed

Affiliation: Laboratory of Psychology and Cognitive Sciences, Department of Anthropological Sciences, University of Genova Genova, Italy.

ABSTRACT
We developed a new experimental and simulative paradigm to study the establishing of compositional grounded representations for motor patterns. Participants learned to associate non-sense arm motor patterns, performed in three different hand postures, with non-sense words. There were two group conditions: in the first (compositional), each pattern was associated with a two-word (verb-adverb) sentence; in the second (holistic), each same pattern was associated with a unique word. Two experiments were performed. In the first, motor pattern recognition and naming were tested in the two conditions. Results showed that verbal compositionality had no role in recognition and that the main source of confusability in this task came from discriminating hand postures. As the naming task resulted too difficult, some changes in the learning procedure were implemented in the second experiment. In this experiment, the compositional group achieved better results in naming motor patterns especially for patterns where hand postures discrimination was relevant. In order to ascertain the differential effect, upon this result, of memory load and of systematic grounding, neural network simulations were also made. After a basic simulation that worked as a good model of subjects performance, in following simulations the number of stimuli (motor patterns and words) was increased and the systematic association between words and patterns was disrupted, while keeping the same number of words and syntax. Results showed that in both conditions the advantage for the compositional condition significantly increased. These simulations showed that the advantage for this condition may be more related to the systematicity rather than to the mere informational gain. All results are discussed in connection to the possible support of the hypothesis of a compositional motor representation and toward a more precise explanation of the factors that make compositional representations working.

No MeSH data available.


Learning curve in Experiment 2.
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Figure 2: Learning curve in Experiment 2.

Mentions: We first analyzed learning progress in different experimental stages. Figure 2 shows the learning curve (mean proportion of correct responses) from the first to the final phase. At the first TPT there were no significant differences between the two groups (A = 0.47, SD = 0.50; B = 0.41, SD = 0.49; t = 0.82, p = 0.41). This shows that there were no differences between subjects at the start and, importantly, that stimuli used for the two groups were equivalent. Mean values of correct responses at the final test (FT), instead, were significantly different (A = 0.60, SD = 0.49; B = 0.46, SD = 0.50; t = 2.51, p = 0.01).


Compositional symbol grounding for motor patterns.

Greco A, Caneva C - Front Neurorobot (2010)

Learning curve in Experiment 2.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2991125&req=5

Figure 2: Learning curve in Experiment 2.
Mentions: We first analyzed learning progress in different experimental stages. Figure 2 shows the learning curve (mean proportion of correct responses) from the first to the final phase. At the first TPT there were no significant differences between the two groups (A = 0.47, SD = 0.50; B = 0.41, SD = 0.49; t = 0.82, p = 0.41). This shows that there were no differences between subjects at the start and, importantly, that stimuli used for the two groups were equivalent. Mean values of correct responses at the final test (FT), instead, were significantly different (A = 0.60, SD = 0.49; B = 0.46, SD = 0.50; t = 2.51, p = 0.01).

Bottom Line: In this experiment, the compositional group achieved better results in naming motor patterns especially for patterns where hand postures discrimination was relevant.In order to ascertain the differential effect, upon this result, of memory load and of systematic grounding, neural network simulations were also made.All results are discussed in connection to the possible support of the hypothesis of a compositional motor representation and toward a more precise explanation of the factors that make compositional representations working.

View Article: PubMed Central - PubMed

Affiliation: Laboratory of Psychology and Cognitive Sciences, Department of Anthropological Sciences, University of Genova Genova, Italy.

ABSTRACT
We developed a new experimental and simulative paradigm to study the establishing of compositional grounded representations for motor patterns. Participants learned to associate non-sense arm motor patterns, performed in three different hand postures, with non-sense words. There were two group conditions: in the first (compositional), each pattern was associated with a two-word (verb-adverb) sentence; in the second (holistic), each same pattern was associated with a unique word. Two experiments were performed. In the first, motor pattern recognition and naming were tested in the two conditions. Results showed that verbal compositionality had no role in recognition and that the main source of confusability in this task came from discriminating hand postures. As the naming task resulted too difficult, some changes in the learning procedure were implemented in the second experiment. In this experiment, the compositional group achieved better results in naming motor patterns especially for patterns where hand postures discrimination was relevant. In order to ascertain the differential effect, upon this result, of memory load and of systematic grounding, neural network simulations were also made. After a basic simulation that worked as a good model of subjects performance, in following simulations the number of stimuli (motor patterns and words) was increased and the systematic association between words and patterns was disrupted, while keeping the same number of words and syntax. Results showed that in both conditions the advantage for the compositional condition significantly increased. These simulations showed that the advantage for this condition may be more related to the systematicity rather than to the mere informational gain. All results are discussed in connection to the possible support of the hypothesis of a compositional motor representation and toward a more precise explanation of the factors that make compositional representations working.

No MeSH data available.