Temporal differences and commonalities between hand and tool neural processing
Abstract Object recognition is a complex cognitive process that relies on how the brain organizes object-related information. While spatial principles have been extensively studied, less studied temporal dynamics may also offer valuable insights into this process, particularly when neural processing...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-12-01
|
| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-48180-8 |
| _version_ | 1797388429958316032 |
|---|---|
| author | L. Amaral G. Besson E. Caparelli-Dáquer F. Bergström J. Almeida |
| author_facet | L. Amaral G. Besson E. Caparelli-Dáquer F. Bergström J. Almeida |
| author_sort | L. Amaral |
| collection | DOAJ |
| description | Abstract Object recognition is a complex cognitive process that relies on how the brain organizes object-related information. While spatial principles have been extensively studied, less studied temporal dynamics may also offer valuable insights into this process, particularly when neural processing overlaps for different categories, as it is the case of the categories of hands and tools. Here we focus on the differences and/or similarities between the time-courses of hand and tool processing under electroencephalography (EEG). Using multivariate pattern analysis, we compared, for different time points, classification accuracy for images of hands or tools when compared to images of animals. We show that for particular time intervals (~ 136–156 ms and ~ 252–328 ms), classification accuracy for hands and for tools differs. Furthermore, we show that classifiers trained to differentiate between tools and animals generalize their learning to classification of hand stimuli between ~ 260–320 ms and ~ 376–500 ms after stimulus onset. Classifiers trained to distinguish between hands and animals, on the other hand, were able to extend their learning to the classification of tools at ~ 150 ms. These findings suggest variations in semantic features and domain-specific differences between the two categories, with later-stage similarities potentially related to shared action processing for hands and tools. |
| first_indexed | 2024-03-08T22:39:44Z |
| format | Article |
| id | doaj.art-c24771befcf04b19a3f00639d997f263 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-08T22:39:44Z |
| publishDate | 2023-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-c24771befcf04b19a3f00639d997f2632023-12-17T12:14:23ZengNature PortfolioScientific Reports2045-23222023-12-0113111110.1038/s41598-023-48180-8Temporal differences and commonalities between hand and tool neural processingL. Amaral0G. Besson1E. Caparelli-Dáquer2F. Bergström3J. Almeida4Proaction Laboratory, Faculty of Psychology and Educational Sciences, University of CoimbraProaction Laboratory, Faculty of Psychology and Educational Sciences, University of CoimbraLaboratory of Electrical Stimulation of the Nervous System (LabEEL), Rio de Janeiro State UniversityProaction Laboratory, Faculty of Psychology and Educational Sciences, University of CoimbraProaction Laboratory, Faculty of Psychology and Educational Sciences, University of CoimbraAbstract Object recognition is a complex cognitive process that relies on how the brain organizes object-related information. While spatial principles have been extensively studied, less studied temporal dynamics may also offer valuable insights into this process, particularly when neural processing overlaps for different categories, as it is the case of the categories of hands and tools. Here we focus on the differences and/or similarities between the time-courses of hand and tool processing under electroencephalography (EEG). Using multivariate pattern analysis, we compared, for different time points, classification accuracy for images of hands or tools when compared to images of animals. We show that for particular time intervals (~ 136–156 ms and ~ 252–328 ms), classification accuracy for hands and for tools differs. Furthermore, we show that classifiers trained to differentiate between tools and animals generalize their learning to classification of hand stimuli between ~ 260–320 ms and ~ 376–500 ms after stimulus onset. Classifiers trained to distinguish between hands and animals, on the other hand, were able to extend their learning to the classification of tools at ~ 150 ms. These findings suggest variations in semantic features and domain-specific differences between the two categories, with later-stage similarities potentially related to shared action processing for hands and tools.https://doi.org/10.1038/s41598-023-48180-8 |
| spellingShingle | L. Amaral G. Besson E. Caparelli-Dáquer F. Bergström J. Almeida Temporal differences and commonalities between hand and tool neural processing Scientific Reports |
| title | Temporal differences and commonalities between hand and tool neural processing |
| title_full | Temporal differences and commonalities between hand and tool neural processing |
| title_fullStr | Temporal differences and commonalities between hand and tool neural processing |
| title_full_unstemmed | Temporal differences and commonalities between hand and tool neural processing |
| title_short | Temporal differences and commonalities between hand and tool neural processing |
| title_sort | temporal differences and commonalities between hand and tool neural processing |
| url | https://doi.org/10.1038/s41598-023-48180-8 |
| work_keys_str_mv | AT lamaral temporaldifferencesandcommonalitiesbetweenhandandtoolneuralprocessing AT gbesson temporaldifferencesandcommonalitiesbetweenhandandtoolneuralprocessing AT ecaparellidaquer temporaldifferencesandcommonalitiesbetweenhandandtoolneuralprocessing AT fbergstrom temporaldifferencesandcommonalitiesbetweenhandandtoolneuralprocessing AT jalmeida temporaldifferencesandcommonalitiesbetweenhandandtoolneuralprocessing |