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phys[protocol_id].mat

phys*

.study_id

link to study in database

; 0 before saving

* saved as "-struct", so individual variables loaded with phys = load(...)

.name

name

.start_time

(optional)

date-time: precise start time of recording

• • Either to nearest second, or to nearest ms - this is relevant for physiology linked to slice times, for example.

  • MySQL needs to be running 5.6.4 or later to record ms: http://dev.mysql.com/doc/refman/5.6/en/fractional-seconds.html

Optional because for some fMRI physiology we don't have this, or it's not synced with scanner.

.num_chans

.chan{1:N}

cell array of channels

.id

unique identifier

added 2022 - needed to link created channels

.name

channel name

.type

"rec" (recorded) or "calc" (calculated)

.filename

mat file of timeseries object; variable has channel name. File is located in phys folder). The channels are synchronized such that the time is equivalent (this is critical for events). The time should start at 0.

Time is in seconds.

.ts (memory only)

the timeseries when loaded; this is not saved in the file, and is only loaded when needed. It slows things down a lot if it gets loaded every time.

.sample_rate

empty for asynchronous

.offset

time offset (relative to phys.start_time if present)

.calc_sourcechans

for calculated channels; cell array of "rec" channel names used to calculate "calc" channel

.descr

description (optional)

.units

units (optional)

.num_features

number of features (types of markers, eg. resp peaks/troughs, ECG Q/R/S

.feature{1:N}

cell array of features (optional)

.type

feature type (peak/trough, ECG)

.descr

description (optional)

.num_markers

.marker_list

.marker

cell array or markers

.name

.x

.y

.shortname

.color

.num_events

this includes states (events with non-zero duration)

.event{1:N}

Cell array of events or states; note that these are all events, not only those in the database. For analysis, we will use the database events and select segments of the timeseries.

For this reason, the names don't matter too much, as we can select events for analysis and classify them at the same time we incorporate them into the database.

.

time

time in seconds, relative to phys.start_time

.event_id

event_id from database

.duration

empty or 0 for event, time for "state"

.type (optional?)