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Software for BMI for Vato et al (PlosCB 2012) Software for BMI for Vato et al (PlosCB 2012)

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Date added: 09/27/2013
Date modified: 02/27/2015
Filesize: 5.02 MB
Downloads: 1363

Information calculation routines Information calculation routines

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Date added: 09/30/2013
Date modified: 02/27/2015
Filesize: 186.33 kB
Downloads: 1088

FitzHugh-Nagumo data fitting software from paper "A dynamical model of  the effect of Locus Coeruleus firing on single-trial cortical state dynamics and sensory" by Safaai et al in PNAS 2015 FitzHugh-Nagumo data fitting software from paper "A dynamical model of the effect of Locus Coeruleus firing on single-trial cortical state dynamics and sensory" by Safaai et al in PNAS 2015

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Date added: 09/28/2015
Date modified: 09/29/2015
Filesize: 10.13 kB
Downloads: 441
This software is to fit FitzHugh-Nagumo (FHN) model of state dependence of neural responses was developed in paper:

[1]  H. Safaai, R. Neves, O. Eschenko, N. K. Logothetis, Stefano Panzeri, A dynamical model of  the effect of Locus Coeruleus firing on single-trial cortical state dynamics and sensory, PNAS 2015, published ahead of print September 28, 2015doi:10.1073/pnas.1516539112

Any person downloading this software accepts to acknowledge this study by citing it in every publication or report arising from the use of this material. 
The software can be downloaded as rar file from this link.
In the software, the file Test.m fits to cortical S1 multiunit activity (MUA) the FHN dynamical model with Locus Coeruleous (LC) neuromodulatory inputs to a 1.5 sec stretch of spontaneous MUA activity.
The function test.m calls the following functions contained in the package:
-       FHN_Auto.m: Function which gets the model parameters and modulatory inputs and integrates the dynamics prediction using the auto-dynamical equations defined in [1].
-       FHN_Self.m: Similar to FHN_Auto but this functions computes the self-dynamical equations defined in SAfaai et al (PNAS 2015).
-       FHN_ep_Auto.m: Computes the cost functions of the model fit error and the MUA for auto-dynamical model.
-       FHN_ep_Auto.m: Similar to FHN_ep_Auto.m but for self-dynamical model.
-       FHN_OPT.m: Optimizes the fit error and estimates the self and auto dynamical model parameters. 
-      test.m: The function calls an example dataset DATA.m that contains Matlab data with the following structure used to run a test example of the codes:

    DATA.MUA: MUA activity
    DATA.Time: Time stams
    DATA.Input1: Input 1 to the dynamical model
    DATA.Input2: Input 2 to the dynamical model
    DATA.PARAMS: Estimated model parameters of the example trial.

A Bidirectional brain-machine interface featuring a neuromorphic hardware decoder. A Bidirectional brain-machine interface featuring a neuromorphic hardware decoder.

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Date added: 10/15/2016
Date modified: 11/04/2016
Filesize: 29.2 MB
Downloads: 226
This package contains the software tools and the hardware specifications used to develop a bidirectional brain-machine interface featuring a neuromorphic hardware decoder.

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FP7-70pxeu-flag-70pxfet-70pxThe project SI-CODE acknowledges the financial support of the Future and Emerging Technologies (FET) programme within the Seventh Framework Programme for Research of the European Commission, under FET-Open grant number: FP7-284553