The Structure And Its Age-ralative Changes Of Spike Trains Of Neurons In Different Visual Areas In Cats

In neocortical slices, the vast majority of neurons fire rather regularly in response to constant current injections. But neurons in the intact animal fire irregularly in response to constant stimuli, For instance, to the same visual stimuli in visual system. Similarly, The spike trains of neurons presented in a rather complex structure. For example, there is trial-to-trial variability and the irregularity in the trial. Now, The studies suggest that the main source of neuronal variability and irregularity is noise, which exists in multiple nervous subsystems such as sensory systems, central nervous system and motor systems. The noise that is present at multiple levels of the nervous system such as thermodynamic noise in molecules, channel noise in membranes, biochemical noise at synapses, response noise at neurons, and so on. The neural network is intrinsically noisy, so that the variability is an unavoidable concomitant of neural activity in nervous system. From the evolutionary point of view, The neural network is in the noisy environment that leads to the brain’s structure and function changes, which affects the structure of spike train of neurons. Therefore, The structure of spike trains can reflect physiological information of neurons in a certain degree, and also it is essential for us to reveal the physiological information of the nervous system.It is well known that vision system plays an irreplaceable role to precept the outer world. There are80%of the external information going into the human brain through vision system.There are many different information-processing stages in vision sub-system. The research of structure of spike trains is of great importance for us to comprehend nervous system. In previous study, The Fano factor has been a common measure of variability in general, but it is so simple that ignores temporal structure and higher-order statistics of spike trains. We use firing rate vector to characterize information, and then introduces higher-order statistics such as mean of the coefficient of variation of firing rate vectors(Cv, Cv2), Euclidean Distance (ED) of firing rate vectors and mean of signal-to-noise ratio (mSNR) to analyse the structure of spike trains.During normal aging, visual abilities are impaired with response characteristics of the visual cortex changing as a result. This has been demonstrated in several studies in which the change of response characteristics was considered to be the source of the degradation of visual functions. In this paper, we used the above statistics to study the effect on the structure and higher-order statistics of spike trains of the visual cortex with normal aging, and then we explored whether Sample Entropy(SampEn) of Interspike Intervals(ISI) of neurons reflects a certain amount of physiological information. Experimental studies are as follows:1. Aging Affects Response Irregularity of Cells in Different Visual Areas in CatsThe visual neuron responses for LGN, A18and PMLS in old and young cats were compared by extracellular single-neuron recording techniques. We used firing rate vector to characterize information. In this research, we use response irregularity of cells to evaluate the degeneration of visual characters. Response irregularity is characterized by mean of the coefficient of variation of firing rate vectors:Cv and Cv2. We found that there is no significant change of the response irregularity in LGN areas between old and young cats. But in the other two areas, neurons in old cats exhibited significantly larger response irregularity than those in young cats. The result indicated that the information processing function of advanced visual cortex is impaired by aging, this research provided a reference for the research of the other neuronal system changes during aging.2. Aging affects response variability and mean of signal-to-noise ratio of cells in different visual areas in catsVisual function declines with aging. It was hypothesized that such declines are likely due to the degradation of visual pathway. To test the hypothesis, we compared response variability and signal-to-noise ratio of cells in lateral geniculate nucleus (LGN), V1, V2and posteromedial lateral suprasylvian area (PMLS) between young and old cats using extracellular single-unit in vivo recording. Spike trains were converted to firing rate vectors. Euclidean Distance (ED) was calculated from such vectors and taken as an index of trial-by-trial response variability. No significant changes of ED and mean of signal-to-noise ratio (mSNR) in LGN were observed between old and young cats. However, in other three visual areas, old cats exhibited significantly larger ED and lower mSNR than young cats. Higher variability and lower signal-to-noise ratio will decrease the ability of decoding of sensory system. The neural changes described here could contribute to declines in visual function during senescence.3. The analysis of Interspike Intervals based on Sample EntropyInterspike Intervals(ISI) of neurons contain a store of spatiotemporal coding information, but the implication of physiological information in the spatiotemporal coding information was not revealed very well. In this research, physiological information was quantified and analysed in the ISI series by Sample Entropy(SampEn) method. Using extracellular multi-unit in vivo recording, response action potential for sinusoidal gratings stimulus in cat primary visual cortex was recorded in this paper. And the jitter method was proposed to create many new ISI series that would be equivalent to original ones in different time scales. Physiological information in ISI series is analyzed based on SampEn. This paper analyzed the correlation between SampEn and firing rate, the relationship between SampEn and direction selectivity, and the change of the SampEn with time scales. SampEn of neurons has significantly negative correlation with firing rate, and has some remarkably reverse correlation with direction selectivity on six of eight neurons. Finally it was not affected appreciably by different time scales and has weakly correlation with time scales. This research indicated that SampEn can reflect physiological information of neurons in a certain degree, and provided a reference for the research of physiological information of ISI series in the other neuronal system.