Poisson Model of Spike Generation

نویسنده

  • David Heeger
چکیده

In the cortex, the timing of successive action potentials is highly irregular. The interpretation of this irregularity has led to two divergent views of cortical organization. On the one hand, the irregularity might arise from stochastic forces. If so, the irregular interspike interval reflects a random process and implies that an instantaneous estimate of the spike rate can be obtained by averaging the pooled responses of many individual neurons. In keeping with this theory, one would expect that the precise timing of individual spikes conveys little information. Alternatively, the irregular ISI may result from precise coincidences of presynaptic events. In this scenario, it is postulated that the timing of spikes, their intervals and patterns can convey information. According to this view, the irregularity of the ISI reflects a rich bandwidth for information transfer.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Information transmission with spiking Bayesian neurons

Spike trains of cortical neurons resulting from repeated presentations of a stimulus are variable and exhibit Poisson-like statistics. Many models of neural coding therefore assumed that sensory information is contained in instantaneous firing rates, not spike times. Here, we ask how much information about time-varying stimuli can be transmitted by spiking neurons with such input and output var...

متن کامل

Towards a Unified Model for the Retina - Static vs Dynamic Integrate and Fire Models

Many models have been proposed to describe the visual processing mechanisms in the retina. The spike generation mechanism of the models is typically performed by a Poisson process. Alternatively, a more realistic approach can be used by implementing an integrate and fire mechanism. In this paper we show that the Stochastic Leaky Integrate and Fire (SLIF) model is equivalent to a non-linear Pois...

متن کامل

Biases in white noise analysis due to non-Poisson spike generation

White noise analysis methods for receptive field characterization typically ignore the dynamics of neural spike generation (i.e., they assume Poisson spike generation). We show that a linear integrate-and-fire spike generation model can induce significant bias in the estimation of the linear kernel, and leads to reverse correlation estimates that depend on stimulus amplitude, as has been observ...

متن کامل

Predicting Spiking Activities in DLS Neurons with Linear-Nonlinear-Poisson Model

Spike train generation in primary motor cortex (M1) and somatosensory cortex (S1) has been studied extensively and is relatively well understood. On the contrary, the functionality and physiology of the dorsolateral striatum (DLS), the immediate downstream region of M1 and S1 and a critical link in the motor circuit, still requires intensive investigation. In the current study, spike trains of ...

متن کامل

Serial Spike Time Correlations Affect Probability Distribution of Joint Spike Events

Detecting the existence of temporally coordinated spiking activity, and its role in information processing in the cortex, has remained a major challenge for neuroscience research. Different methods and approaches have been suggested to test whether the observed synchronized events are significantly different from those expected by chance. To analyze the simultaneous spike trains for precise spi...

متن کامل

Technique(s) for Spike - Sorting

Spike-sorting techniques attempt to classify a series of noisy electrical waveforms according to the identity of the neurons that generated them. Existing techniques perform this classification ignoring several properties of actual neurons that can ultimately improve classification performance. In this chapter, after illustrating the spike-sorting problem with real data, we propose a more reali...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2000