2017
DOI: 10.1007/978-3-319-68600-4_46
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Multicompartment Simulations of NMDA Receptor Based Facilitation in an Insect Target Tracking Neuron

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Cited by 4 publications
(12 citation statements)
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“…Applications range from imaging neurons revealed via optogenetic techniques, to in-situ neuronal tracing in order to establish circuit level interactions between neurons (Dunbier et al, 2012;Keles and Frye, 2017). As an example, our lab has been applying biophysically realistic computational models for dendritic integration by neurons (Shoemaker, 2011;Bekkouche et al, 2017). Such models rely on high resolution 3D reconstruction of individual neuron morphologies within the brain, to establish the biophysical compartments through which neuronal signals travel.…”
Section: Introductionmentioning
confidence: 99%
“…Applications range from imaging neurons revealed via optogenetic techniques, to in-situ neuronal tracing in order to establish circuit level interactions between neurons (Dunbier et al, 2012;Keles and Frye, 2017). As an example, our lab has been applying biophysically realistic computational models for dendritic integration by neurons (Shoemaker, 2011;Bekkouche et al, 2017). Such models rely on high resolution 3D reconstruction of individual neuron morphologies within the brain, to establish the biophysical compartments through which neuronal signals travel.…”
Section: Introductionmentioning
confidence: 99%
“…We have reported here analysis of NMDA-mediated response facilitation using an elaborated version of a model for which we previously reported the modelling framework (Bekkouche et al, 2017). It should be noted that our preliminary version of this model suffered from mapping inaccuracies between the ESTMD inputs and the BSTMD1 model.…”
Section: Discussionmentioning
confidence: 99%
“…A low-pass temporal filter delays the signals from each partially rectified detector so that a non-linear (multiplicative) correlator within the ESTMD compares each delayed signal with the undelayed signal of opposite sign. Combination of this ‘feature template’ with fast adaptation (to reject background texture) and center-surround antagonism provides a sharp selectivity for small, moving targets within the input images (Wiederman et al, 2008; Bekkouche et al, 2017). The output of this model stage was then mapped onto the presumed input dendrites of the neurons, as projected into a 2-dimensional image ( Figure 1B ) assumed to be a retinotopic projection of the space in the visual field.…”
Section: Methodsmentioning
confidence: 99%
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“…Applications range from imaging neurons revealed via optogenetic techniques, to in-situ neuronal tracing in order to establish circuit level interactions between neurons (Dunbier et al, 2012; Keles and Frye, 2017). In our own lab, for example, we are interested in applying biophysically realistic computational models to improve our understanding and test hypotheses regarding how the brain works (Shoemaker, 2011; Bekkouche et al, 2017). Such models rely on high resolution microscopy, enabling 3D reconstruction of individual neuron morphologies within the brain, to establish the likely biophysical compartments through which neuronal signals travel.…”
Section: Introductionmentioning
confidence: 99%