Computational protocol: Enhanced Burst-Suppression and Disruption of Local Field Potential Synchrony in a Mouse Model of Focal Cortical Dysplasia Exhibiting Spike-Wave Seizures

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Protocol publication

[…] All extracellular signal files recorded using linear micro-arrays were exported to NeuroExplorer (Nex Technologies, Madison, AL, USA) for data analysis and visual inspection. In each case, no significant effects were contributed to the sex of the animal so data for males and females were combined. Quantitative analysis of discrete extracellular recording samples (2 s duration) were analyzed for changes in the spectral profile including power spectral density (PSD) and LFP synchrony (i.e., cross-correlation between signals). PSD values were computed across a frequency range of 1–20 Hz with a single taper Hann FFT using a bin size of 0.0012 Hz and 50% overlap between bins to mitigate data loss at the spectral edge of each bin. Correlation analysis was used to compute the cross-correlation between simultaneously recorded signals from a single linear microarray recording using standard correlograms across a −0.3 to +0.3 s offset (bin size of 0.05 ms based on the A/D sampling rate). Signals with similar waveform patterns exhibit high correlation values (ranging from 0 to 1) with negative values representing a reversal in phase of the recorded signals. For comparison, the cross-correlation values of all channels were compared to the cortical recording from channel 5 (approximate level of the granular layer, i.e., see Figure ).Following analysis, raw data was exported to Microsoft Excel for tabulation of statistical averages and standard error values or Sigmaplot (ver. 11.0, SYSTAT software Inc., San Jose, CA, USA) for graphical display and statistical analysis between groups. Group averages are presented mean ± SEM. Student t-tests were used to evaluate significant differences between two groups. A multifactorial analysis of variance (ANOVA) was used to evaluate main effects and interactions when multiple independent variables were present including electrode depth, anesthetic state, treatment group (e.g., control vs. FL), or animal sex, followed by a Holm-Sidak post hoc analysis to evaluate significant differences between individual groups. Three main variables were evaluated: incidence of burst suppression, PSD values, and signal synchrony. A Kaplan-Meier Log-Rank analysis was used to evaluate the incidence of burst/suppression in control and FL animals across anesthesia level. Pearson’s correlation was used to determine the relationship between cortical vs. subcortical signal cross-correlation values and the distance to the microgyrus. A P value of <0.05 was considered significant.Intracranial EEG signals were visually inspected offline for the presence of epileptiform activity. The following seizure parameters were examined across the 24 h recording period: total number of seizure spike-train events, total seizure duration, average number of spikes per seizure event. The timing of epileptiform activity was plotted against specific sleep stages (REM, NREM, Wake, and Active Awake) using methods previously described (Sun et al., ). Briefly, sleep-stage detection was based on a Fast Fourier Transform of the EEG signal from 1 Hz to 20 Hz, yielding power in δ, θ, α, σ and β bands plus integrated floor sensor activity across 2-s epochs. REM sleep was identified by an increased θ power and concomitant low δ and σ power in association with a lack of movement. Changes in δ power were used to distinguish NREM sleep from quiet waking epochs (without movement) or active awake epochs (with movement). […]

Pipeline specifications

Software tools NeuroExplorer, SigmaPlot
Applications Miscellaneous, Neurophysiology analysis
Organisms Mus musculus, Homo sapiens
Chemicals Isoflurane