Abstract: This discussion of the spike train data applies the approach of Hadjipantelis et al. developed for Linguistic data to jointly model both the phase and amplitude functions via a mixed effects model. The approach shows that care needs to be taken when assessing amplitude and phase functions, particularly if separate analysis is undertaken, as there can be high levels of correlation betw...

Spike synchronization is thought to have a constructive role for feature integration, attention, associative learning, and the formation of bidirectionally connected Hebbian cell assemblies. By contrast, theoretical studies on spike-timing-dependent plasticity (STDP) report an inherently decoupling influence of spike synchronization on synaptic connections of coactivated neurons. For example, b...

dependent reset partially resolves this issue. One might expect that the problem of spike timing is overcome completely when considering biophysically more detailed models, such as Hodgkin–Huxley or compartment models; but even for arbitrarily refined, high-dimensional differential equation models, any reasonable time scale described must be much larger than intrinsic time scales characterizing...

Feedforward models of visual cortex appear to be inconsistent with a well-known property of cortical cells: contrast invariance of orientation tuning. The models' fixed threshold broadens orientation tuning as contrast increases, whereas in real cells tuning width is invariant with contrast. We have compared the orientation tuning of spike and membrane potential responses in single cells. Both ...

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BACKGROUND The nature of spike count distributions is of great practical concern for the analysis of neural data. These distributions often have a tendency for 'failures' and a long tail of large counts, and may show a strong dependence of variance on the mean. Furthermore, spike count distributions often show multiplicative rather than additive effects of covariates. We analyzed the responses ...

Ahmadian Y, Packer AM, Yuste R, Paninski L. Designing optimal stimuli to control neuronal spike timing. J Neurophysiol 106: 1038–1053, 2011. First published April 20, 2011; doi:10.1152/jn.00427.2010.—Recent advances in experimental stimulation methods have raised the following important computational question: how can we choose a stimulus that will drive a neuron to output a target spike train ...

Object recognition is a task of fundamental importance for sensory systems. Although this problem has been intensively investigated in the visual system, relatively little is known about the recognition of complex auditory objects. Recent work has shown that spike trains from individual sensory neurons can be used to discriminate between and recognize stimuli. Multiple groups have developed spi...

We assess, both numerically and theoretically, how positively correlated Poisson inputs affect the output of the integrate-and-fire and Hodgkin-Huxley models. For the integrate-and-fire model the variability of efferent spike trains is an increasing function of input correlation, and of the ratio between inhibitory and excitatory inputs. Interestingly for the Hodgkin-Huxley model the variabilit...

In this paper we review some of our recent results on discrete-state spiking neuron models. The discrete-state spiking neuron model is a wired system of shift registers and can generate various spike-trains by adjusting the pattern of the wirings. In this paper we show basic relations between the wiring pattern and characteristics of the spike-train. We also show a learning algorithm which util...