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How vertical hand movements impact brain activity elicited by literally and metaphorically related words: an ERP study of embodied metaphor.

ABSTRACT: Embodied metaphor theory suggests abstract concepts are metaphorically linked to more experientially basic ones and recruit sensorimotor cortex for their comprehension. To test whether words associated with spatial attributes reactivate traces in sensorimotor cortex, we recorded EEG from the scalp of healthy adults as they read words while performing a concurrent task involving either upward- or downward- directed arm movements. ERPs were time-locked to words associated with vertical space-either literally (ascend, descend) or metaphorically (inspire, defeat)-as participants made vertical movements that were either congruent or incongruent with the words. Congruency effects emerged 200-300 ms after word onset for literal words, but not until after 500 ms post-onset for metaphorically related words. Results argue against a strong version of embodied metaphor theory, but support a role for sensorimotor simulation in concrete language.

SUBMITTER: Bardolph M

PROVIDER: S-EPMC4274969 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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How vertical hand movements impact brain activity elicited by literally and metaphorically related words: an ERP study of embodied metaphor.

Bardolph Megan M Coulson Seana S

Frontiers in human neuroscience 20141223

Embodied metaphor theory suggests abstract concepts are metaphorically linked to more experientially basic ones and recruit sensorimotor cortex for their comprehension. To test whether words associated with spatial attributes reactivate traces in sensorimotor cortex, we recorded EEG from the scalp of healthy adults as they read words while performing a concurrent task involving either upward- or downward- directed arm movements. ERPs were time-locked to words associated with vertical space-eithe ...[more]

PMID: 25566041

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Project description:Objective: Brain-machine interfaces (BMIs) are useful for inducing plastic changes in cortical representation. A BMI first decodes hand movements using cortical signals and then converts the decoded information into movements of a robotic hand. By using the BMI robotic hand, the cortical representation decoded by the BMI is modulated to improve decoding accuracy. We developed a BMI based on real-time magnetoencephalography (MEG) signals to control a robotic hand using decoded hand movements. Subjects were trained to use the BMI robotic hand freely for 10 min to evaluate plastic changes in the cortical representation due to the training. Method: We trained nine young healthy subjects with normal motor function. In open-loop conditions, they were instructed to grasp or open their right hands during MEG recording. Time-averaged MEG signals were then used to train a real decoder to control the robotic arm in real time. Then, subjects were instructed to control the BMI-controlled robotic hand by moving their right hands for 10 min while watching the robot's movement. During this closed-loop session, subjects tried to improve their ability to control the robot. Finally, subjects performed the same offline task to compare cortical activities related to the hand movements. As a control, we used a random decoder trained by the MEG signals with shuffled movement labels. We performed the same experiments with the random decoder as a crossover trial. To evaluate the cortical representation, cortical currents were estimated using a source localization technique. Hand movements were also decoded by a support vector machine using the MEG signals during the offline task. The classification accuracy of the movements was compared among offline tasks. Results: During the BMI training with the real decoder, the subjects succeeded in improving their accuracy in controlling the BMI robotic hand with correct rates of 0.28 ± 0.13 to 0.50 ± 0.11 (p = 0.017, n = 8, paired Student's t-test). Moreover, the classification accuracy of hand movements during the offline task was significantly increased after BMI training with the real decoder from 62.7 ± 6.5 to 70.0 ± 11.1% (p = 0.022, n = 8, t(7) = 2.93, paired Student's t-test), whereas accuracy did not significantly change after BMI training with the random decoder from 63.0 ± 8.8 to 66.4 ± 9.0% (p = 0.225, n = 8, t(7) = 1.33). Conclusion: BMI training is a useful tool to train the cortical activity necessary for BMI control and to induce some plastic changes in the activity.

Dataset Information

How vertical hand movements impact brain activity elicited by literally and metaphorically related words: an ERP study of embodied metaphor.

Publications

How vertical hand movements impact brain activity elicited by literally and metaphorically related words: an ERP study of embodied metaphor.

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