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readNSx
readNSx
is an R package that converts
Blackrock-Microsystems
files (.nev
,
.nsx
) into commonly used formats that are compatible with
R
, Python
, Matlab
. The package is
designed for neuroscientist who study intracranial
Electroencephalography and use systems like Blackrock
,
Ripple
, etc. Support versions are 2.2
,
2.3
, 3.0
.
To install readNSx
from CRAN
,
To install development version
(Well, this package has no advanced usage.)
If you have never converted data, use the following one-time function
call to import .nev
and .nsx
data:
readNSx::import_nsp(
path = "YAB_Datafile_001.nev",
prefix = "YAB_Converted_001",
exclude_events = "spike",
partition_prefix = "/part"
)
path
: path to .nev
or any nsx
file (such as ns3, ns5
)prefix
: path prefix of imported files (where the data
will be saved)exclude_events
: events to exclude from importing;
default is “spike” (spike-sorting waveform and classes)partition_prefix
: see Section “Anatomy of imported
files”.Please check help function ?readNSx::import_nsp
(If you have never imported data before, please check previous sub-section first)
NEV
comment data packet
eventsThe following example loads the trial epoch table from
NEV
comment events. The time_in_seconds
is the
second of stimuli relative to time_origin
. Column
comment
is whatever comments sent by the task script (sent
from psychtoolbox
or related software that you use when
collecting data).
# prefix <- "YAB_Converted_001"
nev <- readNSx::get_nev(prefix)
# `time_in_seconds` is relative to time-origin
nev$header_basic$time_origin
#> Year Month DayofWeek Day Hour
#> 2022 8 5 26 15
#> Minute Second Millisecond
#> 4 10 156
readNSx::get_event(nev, "comment")
#> timestamp packet_id char_set flag data comment event time_in_seconds
#> 1 683033 65535 0 0 255 audio-ba comment 22.76777
#> 2 753242 65535 0 0 255 video-ba comment 25.10807
#> ...
# prefix <- "YAB_Converted_001"
# Gather information of channel 10
loaded <- readNSx::get_channel(prefix, channel_id = 10)
# Get NSx configurations,
loaded$nsx
#> Basic header information (NSx):
#> Internal type: NEURALCD
#> Channel count: 152
#> Sample rate: 2000 Hz
#> Time origin: 2022-08-26 15:04:10 158ms
#> Extended header information (NSx):
#> - CC (152 x 16, channels: 1-152): type, electrode_id, electrode_label, ...
#> Cache status:
#> Prefix: ...
#> Number of partitions: 1
# E.g. number of partitions (i.e. unpaused continuous recordings)
loaded$nsx$nparts
#> 1
# Get channel information
loaded$channel_info
#> type electrode_id electrode_label physical_connector connector_pin
#> 10 CC 10 RA10-010 1 10
#> min_digital_value max_digital_value min_analog_value
#> 10 -32764 32764 -8191
#> max_analog_value units high_freq_corner high_freq_order
#> 10 8191 uV 300 1
#> high_freq_type low_freq_corner low_freq_order low_freq_type
#> 10 1 7500000 3 1
#> sample_rate_signal sample_rate_timestamp which_nsp filename
#> 10 2000 30000 3 RA10-010.h5
# Get channel data
channel_signal <- loaded$channel_detail$part1$data; channel_signal
#> Class: H5D
#> Dataset: /data
#> Filename: ...
#> Access type: H5F_ACC_RDONLY
#> Datatype: H5T_IEEE_F64LE
#> Space: Type=Simple Dims=798264 Maxdims=Inf
#> Chunk: 16384
# Get the actual numbers
channel_signal[]
Please use square bracket channel_signal[]
to load the
data into the memory.
The imported file paths will start with prefix
, which is
specified by you, my dear users. In the following demonstration, I’ll
use a placeholder <prefix>
to represent your
inputs.
partition_info - Name of continuous recording within the block,
sample rates, starting time per partition per NSx
<prefix>_scans - Basic information for current block
<prefix>_channels - Electrode channel information ( ID, Label, ... )
<prefix>_events/ - NEV setting headers and data packets (events)
- DIGLABEL - Digital input setup
- NEUEVLBL - Channel labels
- NEUEVWAVE - Spike waveform settings
- ... - Other settings
- event-*** - Data packets (digital inputs, comments...)
- waveforms.h5 - Spike waveforms & cluster
<prefix>_ieeg - NSx data folder
- configurations.rds - NSx basic headers (versions, number of partitions, ...)
- partition_info - Continuous recording duration, start time, sample rates
- nsx_summary.rds - Internally used
- part1/, part2/, ...- Channel folder
- XXXX-001.h5 - Channel data file, each file correspond to a channel.
- XXXX-002.h5 The file name ALWAYS ends with channel ID.
- ... Each HDF5 file contains a "meta" and a "data" part,
"meta": JSON string of channel information
"data": numerical signal voltage data (in `uV`)
The signal data is stored at <prefix>_ieeg/part*
by default, where *
are positive integers representing the
partition number. The Blackrock
system allows users to
pause their recordings and resume later without having to start a new
block. A partition in readNSx
represents one continuous
recording within a “block”. In most of cases, when there is no pause
within a block, you will see only one partition. In some experimental
settings, there could be one or more pauses, readNSx
will
store each continuous recordings in separate folders to make sure each
partition is always continuous. The start time of the partitions will be
stored in partition_info.tsv
.
Please be aware that partition pattern
<prefix>_ieeg/part*
is not fixed. You can change the
pattern via parameter partition_prefix
when importing the
data. For example, partition_prefix="_part
will create
partition files within directory
<prefix>_ieeg_part*
.
When readNSx
stores the data, the channels are saved
individually. For example, channel 1 (LA-2)
and
2 (LA-2)
are stored in separate HDF5
files.
This arrangement is out of the file-size and computational
considerations:
HDF5
files can only have one file
pointers (file locked by some software). This could limit batch
computing algorithms that can be paralleled at channel-levelThe following file types will be generated:
.h5
(HDF5
file): common file format that
can include one or more data within a single file.
Matlab
: use h5disp
to get enclosing data
names; use h5read
to read specific dataPython
: use h5py
package to load the
filesR
: if you want to load them individually, use
raveio::h5_names
to get enclosing data names; use
raveio::load_h5
to read specific data. readNSx
also provides high-level functions to load them (see
?readNSx::get_channel
)..tsv
(tab-separated values file): plain text files that
can be easily read by many languages. You can open them in
Microsoft Office: Excel
..rds
(R object file): can only be read from R,
internally used by readNSx
to store data objects. Users do
not need to read from these files (but also do NOT delete them, or
readNSx
will break). They serve as redundant files in case
the tsv
files are altered accidentally (for example,
Excel
might alter data formats automatically). If you see
an .rds
file sharing the same name as .tsv
,
they share the same information.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.