<html><head><meta http-equiv="Content-Type" content="text/html charset=windows-1252"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space; ">Hello Colleagues,<div><br></div><div>My apologies for any cross postings.<br><div>I would like to draw your attention to a recent publication at NIPS. It can be found at:</div></div><div><br></div><div><a href="http://nips.cc/Conferences/2012/Program/event.php?ID=3432">http://nips.cc/Conferences/2012/Program/event.php?ID=3432</a> (the link to the full paper is at the very bottom of the page). </div><div><br></div><div>Maoz U, Ye S, Ross I, Mamelak A and Koch C (2012) Predicting Action Content On-Line and in Real Time before Action Onset – an Intracranial Human Study. <i>Advances in Neural Information Processing Systems</i> 25, MIT Press </div><div><br></div><div>Abstract</div><div>The ability to predict action content from neural signals in real time
before action onset has been long sought in the neuroscientific study of
decision-making, agency and volition. On-line real-time (ORT)
prediction is important for understanding the relation between neural
correlates of decision-making and conscious, voluntary action. Here,
epilepsy patients, implanted with intracranial depth microelectrodes or
subdural grid electrodes for clinical purposes, participated in a
“matching-pennies” game against either the experimenter or a computer.
In each trial, subjects were given a 5s countdown, after which they had
to raise their left or right hand immediately as the “go” signal
appeared on a computer screen. They won a fixed amount of money if they
raised a different hand than their opponent and lost that amount
otherwise. The working hypothesis of this experiment was that neural
precursors of the subjects’ decisions precede action onset and
potentially also the awareness of the decision to move, and that these
signals could be detected in intracranial local field potentials (LFP).
We found that low-frequency LFP signals from a combination of 10
channels, especially bilateral anterior cingulate cortex and
supplementary motor area, were predictive of the intended
left-/right-hand movements before the onset of the go signal. Our ORT
system predicted which hand the patient would raise 0.5s before the go
signal with 68±3% accuracy in two patients. Based on these results, we
constructed an ORT system that tracked up to 30 channels simultaneously,
and tested it on retrospective data from 6 patients. On average, we
could predict the correct hand choice in 80% of the trials, which rose
to 90% correct if we let the system drop about 1/3 of the trials on
which it was less confident. Our system demonstrates – for the first
time – the feasibility of accurately predicting a binary action in real
time for patients with intracranial recordings, well before the action
occurs.</div><div><br></div><div>Uri Maoz<br>Postdoctoral Scholar<br>Division of Biology, MC 216-76<br>California Institute of Technology<br>Pasadena, CA 91125<br>Tel: (626) 395-8961</div><div>Email: <a href="mailto:urim@caltech.edu">urim@caltech.edu</a> <br><a href="http://www.klab.caltech.edu/%7Eurim" target="_blank">www.klab.caltech.edu/~urim</a></div></body></html>