A. Babolhavaeji, S. Karimi, A. Ghaffari, A. Hamidinekoo, B. Vosoughi-Vahdat
{"title":"Optimal temporal resolution for decoding of visual stimuli in inferior temporal cortex","authors":"A. Babolhavaeji, S. Karimi, A. Ghaffari, A. Hamidinekoo, B. Vosoughi-Vahdat","doi":"10.1109/ICBME.2014.7043903","DOIUrl":null,"url":null,"abstract":"Inferior temporal (IT) cortex is the most important part of the brain and plays an important role in response to visual stimuli. In this study, object decoding has been performed using neuron spikes in IT cortex region. Single Unit Activity (SUA) was recorded from 123 neurons in IT cortex. Pseudo-population firing rate vectors were created, then dimension reduction was done and an Artificial Neural Network (ANN) was used for object decoding. Object decoding accuracy was calculated for various window lengths from 50 ms to 200 ms and various window steps from 25 ms to 100 ms. The results show that 150 ms length and 50 ms window step size gives an optimum performance in average accuracy.","PeriodicalId":434822,"journal":{"name":"2014 21th Iranian Conference on Biomedical Engineering (ICBME)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 21th Iranian Conference on Biomedical Engineering (ICBME)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICBME.2014.7043903","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Inferior temporal (IT) cortex is the most important part of the brain and plays an important role in response to visual stimuli. In this study, object decoding has been performed using neuron spikes in IT cortex region. Single Unit Activity (SUA) was recorded from 123 neurons in IT cortex. Pseudo-population firing rate vectors were created, then dimension reduction was done and an Artificial Neural Network (ANN) was used for object decoding. Object decoding accuracy was calculated for various window lengths from 50 ms to 200 ms and various window steps from 25 ms to 100 ms. The results show that 150 ms length and 50 ms window step size gives an optimum performance in average accuracy.