Milad Lankarany

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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)
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)
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)
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)
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)
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)
Advanced statistical methods have enabled trial-by-trial inference of the underlying excitatory and inhibitory synaptic conductances (SCs) of membrane-potential recordings. Simultaneous inference of both excitatory and inhibitory SCs sheds light on the neural circuits underlying the neural activity and advances our understanding of neural information(More)