Question:Open Does anyone know why extracellular waveshapes (looking like sources and not sinks) might look overlapping without actually being two different units?Or alternatively do extracellular waveshapes summate very nonlinearly? I've seen some spikes with drastically unusual shapes that are throwing me off... [more]Or alternatively do extracellular waveshapes summate very nonlinearly? I've seen some spikes with drastically unusual shapes that are throwing me off: extra wide valley with a peak in the middle of the valley, but in feature space and by cross-correlation, it comes up as only a single unit when compared to the more usual-looking spike shape that i can also sort out. I know synchrony can cause something like that, but there's no other spike around that's nearly the same size, so if it were only a "sinkward-deflection" (that peak), that would make sense, but the anomaly has a variable amplitude and shape. I can post a picture if you're that interested, but i'm just wondering about names of phenomena that i might look-up...Following
Answer added to:10 Spikes convolved with a kernel functionIf I understood correctly your problem, you are not interested in spectral features which are connected to the specific shape of the spike, but only i... [more]If I understood correctly your problem, you are not interested in spectral features which are connected to the specific shape of the spike, but only in searching for periodic behavior on a time scale much larger than the typical separation between spikes. In other words, you should ignore spectral features at frequencies greater than the inverse of the sampling time. If this is true the convolution kernel is largely arbitrary, the only basic requirement is that its width is 1/(2 tau), where tau is the sampling time (this is basically the uncertainty principle). In order to obtain a significant result for your spectrogram you should - fix a time scale T which typically contains several spikes - for a given t, select all the spikes in the interval [t-T/2,t+T/2] - work as suggested in the matlab example of https://www.researchgate.net/profile/Julius_Barzdziukas/ using the selected spikes (note that it is important to take into account the phase factor) and a kernel of you choice which satisfy the uncertainty constraint - discard all the frequencies larger than 1/tau - take the square module of the result - repeat for t+Dt, where Dt is less or equal than T (the chunks of your spectrogram could overlap)Following
Answer added to:17 Is it possible to distinguish type of neuron (e.g. GABAergic, dopaminergic etc.) from any features derived from extracellular action potentials?I am quite confident that at least in the SNC, by examining spike shape and firing properties, is quite certain you are recording extracellularly from... [more]I am quite confident that at least in the SNC, by examining spike shape and firing properties, is quite certain you are recording extracellularly from dopaminergic cells. Moreover, if you add pharmacological characterizations then, the same confidence could be extrapolated to VTA dopaminergic neurons.Following
About Spike Sorting
Spike sorting is a class of techniques used in the analysis of electrophysiological data. Spike sorting algorithms use the shape(s) of waveforms collected with one or more electrodes in the brain to distinguish the activity of one or more neurons from background electrical noise.