A New Algorithm For Automatically Detecting Epileptiform Spikes And Its Application In The Investigation Of Different Epileptic Models

Epilepsy is characterized by abnormally synchronized firing of neuronal populations,which is presented as epileptiform spikes in neural electrical signal recordings.This kind of synchronized firing would also be found in the soma layer where neuron distributed intensively(e.g.,in the hippocampus),which is also known as population spikes(PS).In order to investigate the PS caused by different mechanism quantitatively,this dissertation designed a new window-based algorithm to detect PS automatically in rat hippocampus CA1 region,then exported characteristic parameters of PS to find the relationship between PS firing patterns and the the mechanism.The main results were summarized as follows:(1)The new algorithm could recognize PS directly in wideband recording signals.This algorithm used the expanded window to eliminate the duplicate detection in traditional window-based algorithm,meanwhile used PS amplitude and PS width at half-maximum to select PS.The results showed that the new algorithm work well in epilepsy models induced by 4-aminopyridine(4-AP),a potassium channel blocker,or by picrotoxin(PTX),an antagonist of y-aminobutyric acid A-type(GABAa)receptor.Detection ratio of the new algorithm was greater than 94%and false positive ratio was below 5%,significantly lower than that of the conventional threshold method.(2)With the characteristic parameters including PS amplitude,PS width at half-maximum,PS firing rate and inter-population-spike interval(IPSI),this dissertation compared of the PS patterns between the 4-AP model and the PTX model quantitatively.The results show that the PS of the 4-AP model had wider waveforms and fired more dispersedly with intervals mainly in the range of 100?700 ms.The PS of the PTX model fired as burst with a higher firing rate and with intervals mainly in the range of 2?20 ms,resulting in a larger sum of spike amplitudes per second than the 4-AP model.Thus,the synchronous firing of neuronal populations in the PTX model was more intense than that in the 4-AP model.(3)This dissertation then used the same methods to analyze PS which were caused by orthodromic high frequency stimulation(OHFS)in input pathways of hippocampus CA1 region.During OHFS,the PS patterns changed a lot under different stimulation parameters.When stimulating frequency of continuous OHFS was 50 Hz,the synchronous firing of postsynaptic neuronal population was more intense than that in 100 or 200 Hz.After analysis of relationship between IPSI and stimulus pulses,results showed that these PS had two different mechanism.Part of these PS were driven by stimulating pulses,while others which called PS multiwave or burst may be caused by hyperexcitation of local neuronal population.What's more,neuronal population fired more PS,especially more PS multiwaves during OHFS with interval(insert interval of 100 ms after every 2 s),showed that short pause in HFS would cause more synchronous firing of postsynaptic neuronal population when compared with continuous OHFS of the same frequency.In conclusion,the new algorithm of PS detection and the design of characteristic parameters were helpful to detect PS correctly in different epilepsy models,to assess intensity of synchronous firing and to describe the characteristics of epileptic activities quantitatively.It provides a useful tool of data analysis for investigating the underlying mechanisms of seizure generation and evaluating new therapeutics of epilepsy.