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- Tatyana Sharpee, Nicole C. Rust, William Bialek
- Neural Computation
- 2004

We propose a method that allows for a rigorous statistical analysis of neural responses to natural stimuli that are nongaussian and exhibit strong correlations. We have in mind a model in which neurons are selective for a small number of stimulus dimensions out of a high-dimensional stimulus space, but within this subspace the responses can be arbitrarily… (More)

- Tatyana Sharpee, Nicole C. Rust, William Bialek
- NIPS
- 2002

We propose a method that would allow for a rigorous statistical analysis of neural responses to natural stimuli, which are non–Gaussian and exhibit strong correlations. We have in mind a model in which neurons are selective for a small number of stimulus dimensions out of the high dimensional stimulus space, but within this subspace the responses can be… (More)

- T Sharpee, H Sugihara, A V Kurgansky, S Rebrik, M P Stryker, K D Miller
- Proceedings of SPIE--the International Society…
- 2004

One way to characterize neural feature selectivity is to model the response probability as a nonlinear function of the output of a set of linear filters applied to incoming signals. Traditionally these linear filters are measured by probing neurons with correlated Gaussian noise ensembles and calculating correlation functions between incoming signals and… (More)

- Tatyana Sharpee, William Bialek
- PloS one
- 2007

We consider here how to separate multidimensional signals into two categories, such that the binary decision transmits the maximum possible information about those signals. Our motivation comes from the nervous system, where neurons process multidimensional signals into a binary sequence of responses (spikes). In a small noise limit, we derive a general… (More)

- Tatyana Sharpee
- NIPS
- 2007

This paper compares a family of methods for characterizing neural feature selectivity with natural stimuli in the framework of the linear-nonlinear model. In this model, the neural firing rate is a nonlinear function of a small number of relevant stimulus components. The relevant stimulus dimensions can be found by maximizing one of the family of objective… (More)

We show that in a magnetic field parallel to a two-dimensional ~2D! electron layer, strong electron correlations can change the rate of tunneling from the layer to the 3D continuum exponentially. It leads to a specific density dependence of the escape rate. The mechanism is a dynamical Mössbauer-type recoil, in which the Hall momentum of the tunneling… (More)

- Áine Byrne, Stephen Coombes, +30 authors Sarah Bottjer
- 2016

There is an ongoing debate about whether the cause of dyslexia is based on linguistic, auditory, or visual timing deficits. The current investigation explores the theory that a common deficit underlies all of these processing problems in dyslexia: magno-parvocellular integration causing both selective and sustained attention deficits. To investigate this… (More)

We provide a semiclassical theory of tunneling decay in a magnetic field and a three-dimensional potential of a general form. Because of broken time-reversal symmetry, the standard WKB technique has to be modified. The decay rate is found from the analysis of the Hamilton trajectories of the particle in complex phase space and time. In a magnetic field, the… (More)

- M I Dykman, T Sharpee, P M Platzman
- Physical review letters
- 2001

We consider the effect of electron correlations on tunneling from a 2D electron layer in a magnetic field parallel to the layer. A tunneling electron can exchange its momentum with other electrons, which leads to an exponential increase of the tunneling rate compared to the single-electron approximation. The effect depends on the interrelation between the… (More)

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