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Real-time position reconstruction with hippocampal place cells

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dc.contributor.author Guger, Christoph
dc.contributor.author Gener, Thomas
dc.contributor.author Pennartz, Cyriel
dc.contributor.author Brotons-Mas, Jorge
dc.contributor.author Edlinger, Günter
dc.contributor.author Bermúdez i Badia, Sergi
dc.contributor.author Verschure, Paul F. M. J.
dc.contributor.author Schaffelhofer, Stefan
dc.contributor.author Sanchez-Vives, Maria V.
dc.date.accessioned 2016-02-11T19:07:15Z
dc.date.available 2016-02-11T19:07:15Z
dc.date.issued 2011
dc.identifier.citation Guger C, Gener T, Pennartz C, Brotons-Mas JR, Edlinger G, Bermúdez S, Verschure P, Schaffelhofer S, Sanchez-Vives MV. Real-time position reconstruction with hippocampal place cells. Front. Neurosci. 2011;86(5):1-10. DOI: 10.3389/fnins.2011.00085.
dc.identifier.issn 1662-4548
dc.identifier.uri http://hdl.handle.net/10230/25799
dc.description.abstract Brain–computer interfaces (BCI) are using the electroencephalogram, the electrocorticogram and trains of action potentials as inputs to analyze brain activity for communication purposes and/or the control of external devices. Thus far it is not known whether a BCI system can be developed that utilizes the states of brain structures that are situated well below the cortical surface, such as the hippocampus. In order to address this question we used the activity of hippocampal place cells (PCs) to predict the position of an rodent in real-time. First, spike activity was recorded from the hippocampus during foraging and analyzed off-line to optimize the spike sorting and position reconstruction algorithm of rats. Then the spike activity was recorded and analyzed in real-time. The rat was running in a box of 80 cm × 80 cm and its locomotor movement was captured with a video tracking system. Data were acquired to calculate the rat’s trajectories and to identify place fields. Then a Bayesian classifier was trained to predict the position of the rat given its neural activity. This information was used in subsequent trials to predict the rat’s position in real-time. The real-time experiments were successfully performed and yielded an error between 12.2 and 17.4% using 5–6 neurons. It must be noted here that the encoding step was done with data recorded before the real-time experiment and comparable accuracies between off-line (mean error of 15.9% for three rats) and real-time experiments (mean error of 14.7%) were achieved. The experiment shows proof of principle that position reconstruction can be done in real-time, that PCs were stable and spike sorting was robust enough to generalize from the training run to the real-time reconstruction phase of the experiment. Real-time reconstruction may be used for a variety of purposes, including creating behavioral–neuronal feedback loops or for implementing neuroprosthetic control.
dc.description.sponsorship This work was supported by the FFG, EU-IST (FP6-027731) project Presenccia, and Renachip.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Frontiers Media
dc.relation.ispartof Frontiers in neuroscience. 2011;86(5):1-10
dc.rights © 2011 Guger, Gener, Pennartz, Brotons-Mas, Edlinger, Bermúdez i Badia, Verschure, Schaffelhofer and Sanchez-Vives. This is an open-access article subject to a non-exclusive license between the authors and Frontiers Media SA, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and other Frontiers conditions are complied with.
dc.rights.uri http://creativecommons.org/licenses/by/3.0/
dc.title Real-time position reconstruction with hippocampal place cells
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.3389/fnins.2011.00085
dc.subject.keyword Real-time position reconstruction
dc.subject.keyword Place cells
dc.subject.keyword Firing fields
dc.subject.keyword Spatial navigation
dc.subject.keyword Hippocampus
dc.subject.keyword Brain–computer interface
dc.subject.keyword BCI
dc.subject.keyword Spikes
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP6/027731
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion


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