Underestimation in temporal numerosity judgments computationally explained by population coding model
Abstract The ability to judge numerosity is essential to an animal’s survival. Nevertheless, the number of signals presented in a sequence is often underestimated. We attempted to elucidate the mechanism for the underestimation by means of computational modeling based on population coding. In the mo...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-09-01
|
| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-19941-8 |
| _version_ | 1798036365061914624 |
|---|---|
| author | Takahiro Kawabe Yusuke Ujitoko Takumi Yokosaka Scinob Kuroki |
| author_facet | Takahiro Kawabe Yusuke Ujitoko Takumi Yokosaka Scinob Kuroki |
| author_sort | Takahiro Kawabe |
| collection | DOAJ |
| description | Abstract The ability to judge numerosity is essential to an animal’s survival. Nevertheless, the number of signals presented in a sequence is often underestimated. We attempted to elucidate the mechanism for the underestimation by means of computational modeling based on population coding. In the model, the population of neurons which were selective to the logarithmic number of signals responded to sequential signals and the population activity was integrated by a temporal window. The total number of signals was decoded by a weighted average of the integrated activity. The model predicted well the general trends in the human data while the prediction was not fully sufficient for the novel aging effect wherein underestimation was significantly greater for the elderly than for the young in specific stimulus conditions. Barring the aging effect, we can conclude that humans judge the number of signals in sequence by temporally integrating the neural representations of numerosity. |
| first_indexed | 2024-04-11T21:11:51Z |
| format | Article |
| id | doaj.art-4da118609445486db185611ac1b39ecb |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-11T21:11:51Z |
| publishDate | 2022-09-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-4da118609445486db185611ac1b39ecb2022-12-22T04:03:00ZengNature PortfolioScientific Reports2045-23222022-09-0112111110.1038/s41598-022-19941-8Underestimation in temporal numerosity judgments computationally explained by population coding modelTakahiro Kawabe0Yusuke Ujitoko1Takumi Yokosaka2Scinob Kuroki3NTT Communication Science Laboratories, Nippon Telegraph and Telephone CorporationNTT Communication Science Laboratories, Nippon Telegraph and Telephone CorporationNTT Communication Science Laboratories, Nippon Telegraph and Telephone CorporationNTT Communication Science Laboratories, Nippon Telegraph and Telephone CorporationAbstract The ability to judge numerosity is essential to an animal’s survival. Nevertheless, the number of signals presented in a sequence is often underestimated. We attempted to elucidate the mechanism for the underestimation by means of computational modeling based on population coding. In the model, the population of neurons which were selective to the logarithmic number of signals responded to sequential signals and the population activity was integrated by a temporal window. The total number of signals was decoded by a weighted average of the integrated activity. The model predicted well the general trends in the human data while the prediction was not fully sufficient for the novel aging effect wherein underestimation was significantly greater for the elderly than for the young in specific stimulus conditions. Barring the aging effect, we can conclude that humans judge the number of signals in sequence by temporally integrating the neural representations of numerosity.https://doi.org/10.1038/s41598-022-19941-8 |
| spellingShingle | Takahiro Kawabe Yusuke Ujitoko Takumi Yokosaka Scinob Kuroki Underestimation in temporal numerosity judgments computationally explained by population coding model Scientific Reports |
| title | Underestimation in temporal numerosity judgments computationally explained by population coding model |
| title_full | Underestimation in temporal numerosity judgments computationally explained by population coding model |
| title_fullStr | Underestimation in temporal numerosity judgments computationally explained by population coding model |
| title_full_unstemmed | Underestimation in temporal numerosity judgments computationally explained by population coding model |
| title_short | Underestimation in temporal numerosity judgments computationally explained by population coding model |
| title_sort | underestimation in temporal numerosity judgments computationally explained by population coding model |
| url | https://doi.org/10.1038/s41598-022-19941-8 |
| work_keys_str_mv | AT takahirokawabe underestimationintemporalnumerosityjudgmentscomputationallyexplainedbypopulationcodingmodel AT yusukeujitoko underestimationintemporalnumerosityjudgmentscomputationallyexplainedbypopulationcodingmodel AT takumiyokosaka underestimationintemporalnumerosityjudgmentscomputationallyexplainedbypopulationcodingmodel AT scinobkuroki underestimationintemporalnumerosityjudgmentscomputationallyexplainedbypopulationcodingmodel |