Home Research Project Details A3 - Optophysiological studies of the firing rate dynamics of cortical neurons
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A3 - Optophysiological studies of the firing rate dynamics of cortical neurons

Walter Stühmer and Fred Wolf

Cortical pyramidal neurons in vivo operate in a fluctuation driven regime, in which the mean synaptic input current is below threshold but temporal current fluctuations due to “synaptic bombardment” drive the neuron to fire in a temporally irregular fashion [La Camera et al. 2008, Giugliano et al. 2008]. Theoretical studies have started to examine the dynamical response of simple neuron models in this regime [La Camera et al. 2008, Giugliano et al. 2008, Fourcaud-Trocmé et al. 2003, Naundorf et al. 2005]. These studies show that the firing rate dynamics, as described by linear response functions mapping changes in the mean input current or in the strength of its fluctuations to the instantaneous firing rate, are very sensitive to fine details of the action potential (AP) generation [Naundorf et al. 2005, Silberberg et al. 2004]. Precise knowledge of these response functions would thus reveal essential information about the nature of the AP encoding machinery of cortical neurons. For this reason, recent experiments have started to examine the firing rate dynamics of cortical neurons in vitro [Silberberg et al. 2004, Köndgen et al. 2008, Boucsein et al. 2009] using dynamic current injection in the whole-cell patch clamp configuration. This approach, however, limits measurement time to at most one hour, a time during which only on the order of 10.000 APs can be recorded. Because this number of APs is not sufficient to precisely determine of the entire dynamical response function of an individual cell, studies so far only reported noisy cell-averaged data and targeted high firing rates [Silberberg et al. 2004, Köndgen et al. 2008, Boucsein et al. 2009].

In this project, we will combine our expertise in single neuron dynamics and electrophysiology to explore whether non-invasive neurostimulation using light-gated conductances (see e.g. [Zhang et al. 2007]) can provide a way to determine the dynamical response of cortical neurons with high precision. We will first characterize by whole-cell patch clamp measurements the temporal characteristics of photocurrents in cortical neurons expressing Channelrhodopsin 2 or tandem molecules of Channelrhodopsin (Chop2) and Halorhodopsin (NpHR) when stimulated by fluctuating light of different temporal statistics. Since green light stimulation can shut down Chop2 currents on a sub-millisecond timescale [Bamann et al. 2008], we will in particular explore stimulation by a combination of fluctuating blue and green light sources to achieve rapidly fluctuating photocurrents. We will use these measurements to constrain a biophysical model of the photocurrents that can aid to engineer the temporal correlations of a fluctuating light-source in order to induce a prescribed temporal statistics of fluctuating currents in the stimulated cell. We will then perform long-term recordings under dynamic photo-stimulation of pharmacologically-isolated neurons, cultured on multi electrode arrays (MEAs). To effectively modulate the mean potential of the cells AP generator at high frequency we will combine dynamic photostimulation with extra-cellular electrical stimulation with bath electrodes. We expect that using long-term recordings in this configuration will increase the amount of data recorded from an individual neuron up to 2 orders of magnitude, enabling to characterize dynamical firing responses with much higher precision. We will then use recording protocols to assess dynamical response properties of neurons with modified molecular AP generator components. This characterization of cortical neuron dynamics is expected to be very informative about key features of cortical AP encoding and the functional cutoffs of cortical population codes.

Belongs to Group(s):
Theoretical Neurophysics, Molecular Biology of Neuronal Signals

Is part of  Section A 

Members working within this Project:
Merino, Ricardo M. 
Keith, Tureiti 
Schottdorf, Manuel 
Lazarov, Elinor 
Wolf, Fred 
Stühmer, Walter  

Selected Publication(s):

Wolf, F, Engelken, R, Puelma-Touzel, M, Flórez Weidinger, JD, and Neef, A (2014).
Dynamical models of cortical circuits
Current Opinion in Neurobiology 25:228-236.

Huang, M, Volgushev, M, and Wolf, F (2012).
A Small Fraction of Strongly Cooperative Sodium Channels Boosts Neuronal Encoding of High Frequencies
Plos One 7(5):e37629.

Tchumatchenko, T, and Wolf, F (2011).
Representation of Dynamical Stimuli in Populations of Threshold Neurons
Plos Computational Biology 7(10):e1002239.

Tchumatchenko, T, Geisel, T, Volgushev, M, and Wolf, F (2011).
Spike correlations - what can they tell about synchrony?
Frontiers in Neuroscience 5:68.

Tchumatchenko, T, Malyshev, A, Wolf, F, and Volgushev, M (2011).
Ultrafast population encoding by cortical neurons
The Journal of neuroscience 31(34):12171-12179.

Wei, W, and Wolf, F (2011).
Spike Onset Dynamics and Response Speed in Neuronal Populations
Physical Review Letters 106(8):088102.

Tchumatchenko, T, Geisel, T, Volgushev, M, and Wolf, F (2010).
Signatures of synchrony in pairwise count correlations
Frontiers in Computational Neuroscience 4:1.

Tchumatchenko, T, Malyshev, A, Geisel, T, Volgushev, M, and Wolf, F (2010).
Correlations and Synchrony in Threshold Neuron Models
Physical Review Letters 104(5):058102.