Zuzanna Piwkowska

Learn More
We review here the development of Hodgkin–Huxley (HH) type models of cerebral cortex and thalamic neurons for network simulations. The intrinsic electrophysiological properties of cortical neurons were analyzed from several preparations, and we selected the four most prominent electrophysiological classes of neurons. These four classes are “fast spiking”(More)
In neocortical neurons, network activity can activate a large number of synaptic inputs, resulting in highly irregular subthreshold membrane potential (V(m)) fluctuations, commonly called "synaptic noise." This activity contains information about the underlying network dynamics, but it is not easy to extract network properties from such complex and(More)
Intracellular recordings of neuronal membrane potential are a central tool in neurophysiology. In many situations, especially in vivo, the traditional limitation of such recordings is the high electrode resistance and capacitance, which may cause significant measurement errors during current injection. We introduce a computer-aided technique, Active(More)
The optimal patterns of synaptic conductances for spike generation in central neurons is a subject of considerable interest. Ideally such conductance time courses should be extracted from membrane potential (V(m)) activity, but this is difficult because the nonlinear contribution of conductances to the V(m) renders their estimation from the membrane(More)
Cortical neurons are subject to sustained and irregular synaptic activity which causes important fluctuations of the membrane potential (V(m)). We review here different methods to characterize this activity and its impact on spike generation. The simplified, fluctuating point-conductance model of synaptic activity provides the starting point of a variety of(More)
Cortical neurons behave similarly to stochastic processes, as a consequence of their irregularity and dense connectivity. Their firing pattern is close to a Poisson process, and their membrane potential (V(m)) is analogous to colored noise. One way to characterize this activity is to identify V(m) to a multidimensional stochastic process. We review here(More)
Cortical neurons in vivo are subjected to intense synaptic noise that has a signi2cant impact on various electrophysiological properties. Here we characterize the subthreshold activity of cortical neurons using an explicit solution of the passive membrane equation subject to independent inhibitory and excitatory conductance noise sources described by(More)
We present a new way to model the response of an electrode to an injected current. The electrode is represented by an unknown complex linear circuit, characterized by a kernel which we determine by injecting a noisy current. We show both in simulations and experiments that, when applied to a full recording setup (including acquisition board and amplifier),(More)
Cortical neurons in vivo show a highly irregular spontaneous discharge activity, characterized by a gamma statistics and coefficient of variation around unity. Modelling studies showed that this irregularity is a consequence of the high-conductance state caused by the ongoing activity in the cortical network. Here, we investigate to which extent this high(More)
In neocortical neurons, network activity is responsible for intense synaptic inputs, which maintain the membrane in a high-conductance state. Here, we propose a method for recreating specific high-conductance states intracellularly. This method makes use of the estimation of the mean and variance of excitatory and inhibitory conductances based on(More)