@inproceedings{9288c30f616940ae8477df6c16f24363,
title = "Prediction of a Go/No-go decision from single-trial activities of multiple neurons in monkey superior colliculus",
abstract = "The purpose of this study was to develop an algorithm capable of transforming neural activity to correctly report behavioral outcome during a cognitive task. We recorded from small groups of 2-5 neurons in the superior colliculus (SC) while monkeys performed a go/no-go task. Depending upon the color of a peripheral stimulus, the monkey was required to either make a saccade to the stimulus (go) or maintain fixation (no-go). In order to replicate the progress of the decision-making process and generate a virtual decision function (VDF), we performed a multiple regression analysis, with 1 msec resolution, on neuron activity during individual trials. Post hoc analyses by VDF predicted the monkey's choice with nearly 90% accuracy. These results suggest that monitoring of a limited number of SC neurons has sufficient capacity to predict go/no-go decisions on a trial-by-trial basis, and serves as an ideal candidate for a cognitive brain-machine interface (BMI).",
keywords = "Brain-machine interface, Decision-making, Go/no-go, Prediction, Saccade, Superior colliculus",
author = "Hasegawa, {Ryohei P.} and Hasegawa, {Yukako T.} and Segraves, {Mark A.}",
year = "2008",
month = oct,
day = "23",
doi = "10.1007/978-3-540-69162-4_104",
language = "English (US)",
isbn = "3540691596",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
number = "PART 2",
pages = "997--1006",
booktitle = "Neural Information Processing - 14th International Conference, ICONIP 2007, Revised Selected Papers",
edition = "PART 2",
note = "14th International Conference on Neural Information Processing, ICONIP 2007 ; Conference date: 13-11-2007 Through 16-11-2007",
}