Module: Evoked Experiment

[kylemath]

Classic ERP experiment

Either auditory or visual stimuli

~700 ms apart with random jitter
2 types
red vs blue
high vs low tone

we collect 30-50 trials , 20% of which are one condition

we save a snip of data locked to the onset for each presentation
200 ms before and 1000 ms after

we append this to an array 1200 ms by number of trials, one for each condition

we subtract the 200 ms baseline average from the whole trial for each channel and trial

we average over the trials for each channel, average over hemispheres and get a single time series for each condition

plot this and save it

[kylemath]

class MovingAverageCalculator {
	constructor() {
		this.count = 0
		this._mean = 0
	}
	update(newValue) {
		this.count++
		const differential = (newValue - this._mean) / this.count
		const newMean = this._mean + differential
		this._mean = newMean
	}
	get mean() {
		this.validate()
		return this._mean
	}
	validate() {
		if (this.count == 0) {
			throw new Error('Mean is undefined')
		}
	}
}

[kylemath]

const a = [[1,2,3], [4,5,6], [7,8,9]]
math.mean(a, 1) // [4, 5, 6]

[kylemath]

const reallyImportantData = []
LOOP ME FORVER:
    reallyImportantData.push(channel.datasets[0].data)

[kylemath]

https://github.com/urish/muse-js#event-markers

[kylemath]

addressed in #110