Milad Lankarany

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Time-varying excitatory and inhibitory synaptic inputs govern activity of neurons and process information in the brain. The importance of trial-to-trial fluctuations of synaptic inputs has recently been investigated in neuroscience. Such fluctuations are ignored in the most conventional techniques because they are removed when trials are averaged during(More)
Fitting biophysical models to real noisy data jointly with extracting fundamental biophysical parameters has recently stimulated tremendous studies in computational neuroscience. Hodgkin–Huxley (HH) neuronal model has been considered as the most detailed biophysical model for representing the dynamical behavior of the spiking neurons. The unscented Kalman(More)
In this paper we present a novel method for identification of linear time invariant, non-minimum phase (NMP), FIR systems when only output data are available and the order of system exceeds four. We generally model a non-minimum phase FIR system as an MA model of known order. To estimate the model parameters, we exploit the 1-D diagonal slice of the third(More)
Neurons rely on action potentials, or spikes, to encode information. But spikes can encode different stimulus features in different neurons. We show here through simulations and experiments how neurons encode the integral or derivative of their input based on the distinct tuning properties conferred upon them by subthreshold currents. Slow-activating(More)
Fitting biophysical models to real noisy data jointly with extracting fundamental biophysical parameters has recently stimulated tremendous studies in computational neuroscience. Hodgkin-Huxley (HH) neuronal model has been considered as the most detailed biophysical model for representing the dynamical behavior of the spiking neurons. In this paper, we(More)
Neuron transforms information via a complex interaction between its previous states, its intrinsic properties, and the synaptic input it receives from other neurons. Inferring synaptic input of a neuron only from its membrane potential (output) that contains both sub-threshold and action potentials can effectively elucidate the information processing(More)
The cortex encodes a broad range of inputs. This breadth of operation requires sensitivity to weak inputs yet non-saturating responses to strong inputs. If individual pyramidal neurons were to have a narrow dynamic range, as previously claimed, then staggered all-or-none recruitment of those neurons would be necessary for the population to achieve a broad(More)
We address, in this paper, the problem of estimating the input sequence of a known, non-minimum phase, FIR system, when a large number of its roots are located near or on the unit circle. This issue cannot be solved by conventional methods known to date. Recently, algorithms based on spectral factorization are considered as possible solutions of inversing(More)
This paper proposed a new method to obtain an optimum arrangement of the second-order sections in digital IIR filters in order to reduce the steady-state output noise variance when the model of filter is considered as the cascade connections of second-order sections. The proposed method is based on minimizing the external normalization coefficients in each(More)