Deep brain stimulation (DBS), which usually utilizes high frequency stimulation (HFS) of electrical pulses, is effective for treating many brain disorders in clinic. Studying the dynamic response of downstream neurons to HFS and its time relationship with stimulus pulses can reveal important mechanisms of DBS and advance the development of new stimulation modes (e.g., closed-loop DBS). To exhibit the dynamic neuronal firing and its relationship with stimuli, we designed a two-dimensional raster plot to visualize neuronal activity during HFS (especially in the initial stage of HFS). Additionally, the influence of plot resolution on the visualization effect was investigated. The method was then validated by investigating the neuronal responses to the axonal HFS in the hippocampal CA1 region of rats. Results show that the new design of raster plot is able to illustrate the dynamics of indexes (such as phase-locked relationship and latency) of single unit activity (i.e., spikes) during periodic pulse stimulations. Furthermore, the plots can intuitively show changes of neuronal firing from the baseline before stimulation to the onset dynamics during stimulation, as well as other information including the silent period of spikes immediately following the end of HFS. In addition, by adjusting resolution, the raster plot can be adapted to a large range of firing rates for clear illustration of neuronal activity. The new raster plot can illustrate more information with a clearer image than a regular raster plot, and thereby provides a useful tool for studying neuronal behaviors during high-frequency stimulations in brain.
Currently, commercial devices for electrical neural stimulations can only provide fixed stimulation paradigms with preset constant parameters, while the development of new stimulation paradigms with time-varying parameters has emerged as one of the important research directions for expanding clinical applications. To facilitate the performance of electrical stimulation paradigms with time-varying parameters in animal experiments, the present study developed a well-integrated stimulation system to output various pulse sequences by designing a LabVIEW software to control a general data acquisition card and an electrical stimulus isolator. The system was able to generate pulse sequences with inter-pulse-intervals (IPI) randomly varying in real time with specific distributions such as uniform distribution, normal distribution, gamma distribution and Poisson distribution. It was also able to generate pulse sequences with arbitrary time-varying IPIs. In addition, the pulse parameters, including pulse amplitude, pulse width, interphase delay of biphasic pulse and duration of pulse sequence, were adjustable. The results of performance tests of the stimulation system showed that the errors of the parameters of pulse sequences output by the system were all less than 1%. By utilizing the stimulation system, pulse sequences with IPI randomly varying in the range of 5~10 ms were generated and applied in rat hippocampal regions for animal experiments. The experimental results showed that, even with a same mean pulse frequency of ~130 Hz, for neuronal populations, the excitatory effect of stimulations with randomly varying IPIs was significantly greater than the effect of stimulations with fixed IPIs. In conclusion, the stimulation system designed here may provide a useful tool for the researches and the development of new paradigms of neural electrical stimulations.
Epilepsy is characterized by abnormally synchronized firing of neuronal populations, which is presented as epileptiform spikes in neural electrical signal recordings. In order to investigate the epileptiform spikes quantitatively, we designed a new window-based algorithm to automatically detect population spikes (PS) in acute epilepsy models in rat hippocampus CA1 region, and to calculate characteristic parameters of PS. Results show that the algorithm could recognize PS waveforms directly in wideband recording signals in epilepsy models induced by 4-aminopyridine (4-AP), a potassium channel blocker, or by picrotoxin (PTX), an antagonist of γ-aminobutyric acid A-type receptor. The PS detection ratios of the two epilepsy models were 94.2%±1.6% (n=11) and 95.9%±1.9% (n=12), respectively. The false positive ratios were 3.5%±2.3% (n=11) and 4.8%±2.3% (n=12), which were significantly lower than those of the conventional threshold method. Comparisons of the PS patterns between the 4-AP model and the PTX model showed 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. In conclusion, the new algorithm of PS detection can correctly detect and analyze epileptiform population spikes. It provides a useful tool of data analysis for investigating the underlying mechanism of seizure generation and for evaluating new therapeutics of epilepsy.
Deep brain stimulation (DBS) has been successfully used to treat a variety of brain diseases in clinic. Recent investigations have suggested that high frequency stimulation (HFS) of electrical pulses used by DBS might change pathological rhythms in action potential firing of neurons, which may be one of the important mechanisms of DBS therapy. However, experimental data are required to confirm the hypothesis. In the present study, 1 min of 100 Hz HFS was applied to the Schaffer collaterals of hippocampal CA1 region in anaesthetized rats. The changes of the rhythmic firing of action potentials from pyramidal cells and interneurons were investigated in the downstream CA1 region. The results showed that obvious θ rhythms were present in the field potential of CA1 region of the anesthetized rats. The θ rhythms were especially pronounced in the stratum radiatum. In addition, there was a phase-locking relationship between neuronal spikes and the θ rhythms. However, HFS trains significantly decreased the phase-locking values between the spikes of pyramidal cells and the θ rhythms in stratum radiatum from 0.36 ± 0.12 to 0.06 ± 0.04 (P < 0.001, paired t-test, N = 8). The phase-locking values of interneuron spikes were also decreased significantly from 0.27 ± 0.08 to 0.09 ± 0.05 (P < 0.01, paired t-test, N = 8). Similar changes were obtained in the phase-locking values between neuronal spikes and the θ rhythms in the pyramidal layer. These results suggested that axonal HFS could eliminate the phase-locking relationship between action potentials of neurons and θ rhythms thereby changing the rhythmic firing of downstream neurons. HFS induced conduction block in the axons might be one of the underlying mechanisms. The finding is important for further understanding the mechanisms of DBS.