Measures of complexity in neural spike-trains of the slowly adapting stretch receptor organs.
نویسندگان
چکیده
Discrete sequence analysis methods were applied to study spike-trains generated by the isolated neuron of the slowly adapting stretch receptor organ. Calculation of the algorithmic complexity and block entropies of digitized individual spike-train forms allowed us to distinguish different classes of neural behavior. While some spike-trains exhibited significant structure, others displayed diverse degrees of randomness. The sequences recorded during the stimulated portions of the intermittent and walk-through forms, differed considerably from their randomly shuffled surrogates. Informational and grammar complexity measures (in two, four and eight-letter alphabets), tell us things about the structure of spike-trains that are not obtained with conventional spike analysis. Comparison of the conditional entropies for the digitized signals showed that the method distinguishes between different stimulated conditions. Additionally, comparison of the different stimulated conditions with their corresponding surrogates showed that, both, conditional entropies and complexities were significantly different for the two groups. Although the original and the randomly shuffled sequences had the same distribution and average firing rate, their complexity values were different. The results obtained with both measures of sequence structure were quite consistent.
منابع مشابه
Pulmonary stretch receptor spike time precision increases with lung inflation amplitude and airway smooth muscle tension.
Slowly adapting pulmonary stretch receptors (SARs) respond to different lung inflation volumes with distinct spike counts and patterns, conveying information regarding the rate and depth of breathing to the cardiovascular and respiratory control systems. Previous studies demonstrated that SARs respond to repetitions of the same lung inflation faithfully, suggesting the possibility of modeling a...
متن کاملJoint probability-based neuronal spike train classification
Neuronal spike trains are used by the nervous system to encode and transmit information. Euclidean distance-basedmethods (EDBMs) have been applied to quantify the similarity between temporally-discretized spike trains and model responses. In this study, using the same discretization procedure, we developed and applied a joint probability-based method (JPBM) to classify individual spike trains o...
متن کاملRepetitive firing: quantitative analysis of encoder behavior of slowly adapting stretch receptor of crayfish and eccentric cell of Limulus
Techniques developed for determining summed encoder feedback in conjunction with the leaky integrator and variable-gamma models for repetitive firing are applied to spike train data obtained from the slowly adapting crustacean stretch receptor and the eccentric cell of Limulus. Input stimuli were intracellularly applied currents. Analysis of data from cells stringently selected by reproducibili...
متن کاملThe algorithmic complexity of neural spike trains increases during focal seizures.
The interspike interval spike trains of spontaneously active cortical neurons can display nonrandom internal structure. The degree of nonrandom structure can be quantified and was found to decrease during focal epileptic seizures. Greater statistical discrimination between the two physiological conditions (normal vs seizure) was obtained with measurements of context-free grammar complexity than...
متن کاملEffects of Lithium on Different Membrane Components of Crayfish Stretch Receptor Neurons
Unlike several other varieties of input membrane, that of the crayfish stretch receptor develops a generator potential in response to stretch when all the Na of the medium is replaced with Li. However, Li depolarizes the receptor neuron, the soma membrane becoming more depolarized than that of the axon. During exposure to Li the cell usually fires spontaneously for a period, and when it becomes...
متن کاملذخیره 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 ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Bio Systems
دوره 58 1-3 شماره
صفحات -
تاریخ انتشار 2000