neoconversion

neoconversion.md

Packaging data following the Neo model

General considerations

• A block corresponds to a recording session. Consequently, a full dataset will be composed of several blocks. A block should have annotations regarding the animal and all the dummy codes used in the different fields (e.g. if different trial types have specific numeric labels)
• Segments are used for trials. They should contain annotations regarding trial-specific variables, and event/epoch objects.
• Since this is a multi-area recording, channel indices correspond to a single area/bundle, and tetrode and channel information are ralegated to the annotations.

Detailed procedure

1. Construct a block corresponding to a single recording session. It contains annotations of the dummy codes used to trial parameters etc.

2. For every recording area, generate a ChannelIndex

   • The ChannelIndexes for every recording area are appended to block.channel_indexes.

3. For every recorded neuron, generate a unit object with all the relevant annotations.

   • Append unit to the corresponding ChannelIndex.units
   • Set unit.channel_index to the corresponding ChannelIndex.

4. For every behavioral trial, generate a Segment object, with the relevant annotations (trial outcome, trial type, etc.) and an Event object.

   • Append the Event to Segment.events
   • Append the segment to block.segments

5. For every unit unit_n, generate the spike train corresponding to a segment segment_m, and construct a SpikeTrain object.

   • Append the SpikeTrain so segment.spiketrains.
   • Append the SpikeTrain to unit.spiketrains.
   • Set SpikeTrain.unit=unit_n.
   • Set SpikeTrain.segment=segment_m.