Reliability of amplitude propagation--论文代写范文

另一个选择是内部时序结构的破裂,这可能包含多个峰值。单一时间破裂无法衡量实验结果,关键变量的进程可以使用我们的实验系统。原则上,每一斜率比振幅有不同的信息。下面的论文代写范文对此进行论述。

Abstract
  The population bursts commence locally, stimulated either spontaneously or by glutamate application (Feinerman et al., 2005), and then spread to the whole culture. In analogy, we may associate the local group of neurons in which bursting commenced to sensory neurons, whose activity carries information about an “external stimulus.” As the population burst propagates, this information is conveyed to more distal parts of the culture. This process involves a deterioration of the signal, so that distant groups of neurons receive an inaccurate account of the “sensory” activity. A quantitative comparison between the firing levels in distal groups of neurons was performed by use of information theory.

  To check whether a coding scheme can reliably transmit information through the experimental system, we need first to identify the specific critical parameters that carry information along the channel (such as millisecond interspike intervals for temporal coding). We can then ask whether these succeed to progress through the system without an accumulation of errors. A few possible choices for such parameters were considered for our experimental measurements and analysis. One such parameter is the interburst interval (IBI), the time interval between two consecutive population bursts, but this is typically on the order of ten of seconds (Feinerman et al., 2005). 

  Such long timescales do not seem to be relevant for the coding of any realistic information. Another option is the internal temporal structure of the burst, which may contain several spikes. However, the shorter timescales between the spikes in a single burst cannot be measured in our experiment because of the long decay times of the calcium-sensitive dye as well as the 20 ms time resolution of video imaging. What is practically accessible are the event amplitudes as measured by the concurrent increase in fluorescence, as well as the initial slope for each event. These are a critical variable whose progression can be tracked using our experimental system, and we therefore chose to concentrate on this measurement. As mentioned above, it is linearly related to a rate code. 

  In principle, the slope of each burst could hold different information than the amplitude, for example, on the timing between initial spikes. However, a close examination showed that the relationship of initial slopes of the fluorescence signal of bursts to their amplitude, as measured in 18 different cultures and 180 ROIs, is linear. On average, the amplitude of a signal is just 0.2 0.004 s times its initial slope. This strict relationship actually identifies spike number (amplitude) with spike rate (slope), connecting these two related modes of coding in the activity of the one-dimensional cultures. We therefore concentrate our discussion on amplitude measurements. We define the area in which activity commenced as the input of an information channel and another, distal area as the output. The reliability of the channel is obtained by measuring the mutual information between a given activity parameter in these two areas. To get ideally good estimates on channel performance, no limitations should be imposed by the stimuli chosen; they should be randomly chosen over a wide dynamical range (Werner and Mountcastle, 1965; Rieke et al., 1997). 

  Our experimental design supplies us with a reasonably wide range of amplitudes, as much as a factor of 2 between the maxi mum and the minimum of a random Gaussian signal. These fluctuations in event amplitude are inherent to the system and are common to a variety of neuronal culture preparations (Murphy et al., 1992; Maeda et al., 1998; Bacci et al., 1999; Tscherter et al., 2001; Tabak and Latham, 2003; van Pelt et al., 2005). Interestingly, such variations were not observed by Pinto et al. (2005), perhaps because of the fact that, in this slice preparation, inhibition was blocked to achieve propagating waves. Propagating waves in slice preparations usually require special treatment such as the removal of inhibition (Golomb and Amitai, 1997; Wu et al., 1999; Stoop and Pralong, 2000; Harris and Stewart, 2001; Pinto et al., 2005). 

  As shown by Houweling et al. (2005), this may be attributed to the fact that neurons in cortical slice preparations develop in vivo and experience constant synaptic bombardment that may tune them to low responsiveness. Culture preparations allow for neurons to be studied in the same environment in which they have developed. As stated above, no special treatment is required for propagating waves to be generated. The amplitude variations obtained while stimulating the culture at constant time intervals are similar to those in the spontaneous case (see below). It is possible that the variations in response to a constant stimulus are because the stimulation causes large-scale population response only indirectly. The initial response is local and may be specific to the stimulation, but it gets amplified by recurrent activity before developing into the large-scale event (Feinerman et al., 2005; Pinto et al., 2005). 

  Event amplitudes depend only weakly on the preceding quiescent period. Because the average fluorescence amplitude of events in a specific area depends on local parameters, such as local neuron density, it carries no information (Litvak et al., 2003), and we must normalize each list by its mean. We end up with a list of normalized deviations from the average that do carry information and typically range between 0.7 and 1.3 times the mean. This normalized data are proportional to the spike count, averaged over the neurons in a given ROI, regardless of their total number. We quantify the efficiency of the rate-code communication by estimating the mutual information of normalized amplitude lists recorded in different ROIs. 

 Discussion 
  The linear neural network is very efficient in passing population waves of activity, as demonstrated by the very high percentage that travel to excite the full 17 mm of the culture. Such stability was suggested previously in a theoretical network with similar converging/diverging connections (Abeles, 1991). There is no rounding off of the signal: it keeps its characteristic form and propagates along the line. This is similar to in vivo measurements in cortex (Bair and Koch, 1996) as well as measurement in slice preparations (Wu et al., 1999). The one-dimensional structure and anatomy (Feinerman et al., 2005) of the culture induces causality in the propagation of the signal as each area excites its neighbor. The physical distance along the line is easily measured and can be identified with the temporal evolution of the activity, which is much harder to quantify. (论文代写)

  This is beautifully manifested by the way in which the measured values of mutual information fall unto a curve once plotted versus distance in Figure 3. One dimensionality also allows the accurate comparison of this curve with one obtained from a simple theoretical model of linear information transport. This comparison suggests that the main obstacle for information propagation, at the natural dynamic range exhibited by both spontaneous and evoked activity, is synaptic transmission noise (Koch, 1999). This noise is even greater for transmission through thin parts of the culture because of the reduced synaptic connectivity (Feinerman et al., 2005). We can conclude that the integration of postsynaptic potentials from a large group of presynaptic neurons serves to decrease the noise of the channel. The linearity of the noise term in the Gaussian chain ensures that the parameters for the theoretical curve do not rely on our choice of ROIs.(论文代写)

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