Neuronal Data Analyzer Lab v0.6.0

Added

• Laser speckle flowmetry (launcher → Blood flow → Laser speckle,
  apps/LSCIAnalysisApp.m, core/LaserSpeckle.m): blood-flow maps from
  laser speckle images. Loads raw speckle images from the camera, speckle
  contrast images, or the perfusion / flux images a commercial system
  exports (.mat, multi-frame TIFF or video; the type is judged from the
  images when the file does not say). Spatial (N × N window) or temporal
  (N frames) speckle contrast after the camera dark level, a flow index
  (1/K², or 1/τc from the exposure model with β), the flow of each ROI
  over time (K² averaged over the ROI before conversion), trials around
  each stimulus (from the stimulus trace in the file or a regular
  protocol) as % change from each trial's baseline, the average response
  (mean ± SD, with the mean change in a response window) and a response
  map. A Checks tab says in plain words what to look at: saturated
  pixels, a missing dark level, a small window, an unusual contrast,
  trials left out, too few trials. Export as .csv / .mat; Save trials
  writes the LDF trial format, so LDF Average and Response features open
  it. Sessions, report and methods text (citing Briers & Webster 1996,
  Boas & Dunn 2010, Bandyopadhyay et al. 2005, Cheng et al. 2003) as in
  every window. New demo demo_lsci.mat (core/demo/demoLSCI.m): raw
  speckle with known contrast in cortex, a vessel and static tissue, and
  a +25% flow response of an activated area after four stimuli; new Help
  topic Laser Speckle with the answers.
• Blood-flow recordings from the common acquisition systems
  (core/io/SignalSource.m, readSignalText.m, readBiopacACQ.m,
  writeBiopacACQ.m): LabChart .mat exports with several blocks, channel
  rates, units and comments; LabChart and AcqKnowledge text exports;
  BIOPAC AcqKnowledge .acq files (3.x to 5.x, Windows and Mac, compressed
  or not, with event markers; checked against the 32 sample files of the
  bioread project); AcqKnowledge and Spike2 .mat exports; any delimited
  table (PeriSoft, moorVMS-PC, spreadsheets: decimal comma, clock times,
  units rows). The flow and stimulus channels are found from their names,
  and comments / markers can be the stimulus. New demo files
  (core/demo/demoLDFFormats.m): the LDF demo as a LabChart text export,
  an AcqKnowledge .acq, a PeriSoft-style table, a Spike2 export and a table
  without a time column.
• core/io/readImageStack.m: one reader for image stacks over time
  (.mat, multi-page TIFF with the ImageJ frame interval, channels and
  pixel size, and video).
• Perimed PeriCam PSI recordings (core/io/readPerimedDat.m,
  perimedPerfusion.m, writePerimedDat.m): PIMSoft .dat files (file
  versions 1 to 3) open in the Laser speckle window as speckle contrast
  images (β · SD / intensity from the variance and intensity images),
  with the frame rate and pixel size of the header; PIMSoft's perfusion
  (gain × (1/C − 1), 0–3000 PU) is available as well. Other laser speckle
  systems (moorFLPI, RWD, SIM, Omegawave) keep their undocumented files:
  open their TIFF, video or MATLAB exports.
• TIFF metadata (core/io/tiffMeta.m, unitScale.m): one reading of
  what microscope and slide software writes into TIFFs, used by Histology,
  ROI analysis and Laser speckle: ImageJ hyperstacks (channels, slices,
  frames, frame interval, z spacing), OME-TIFF (DimensionOrder, sizes,
  physical pixel size with units, time increment, plane times, channel
  names), ScanImage (saved channels, frame rate, field of view in µm,
  slices with flyback frames, frame timestamps) and Aperio .svs (MPP,
  magnification). Multi-channel TIFFs open on one channel and the first
  slice.
• Imaging files from microscope software (core/io/readImagingFolder.m,
  writeImagingFormat.m), in ROI analysis and every reader of image
  stacks: Inscopix .isxd movies (uint16, float32, uint8; frame rate and
  pixel size from the JSON footer), ThorImageLS folders (Experiment.xml +
  .raw, channels, averaging, fast z), Bruker Prairie View T-series and
  Z-series (PVScan .xml, one TIFF per frame, frame times, microns per
  pixel) and UCLA Miniscope folders (numbered videos, timeStamps.csv /
  timestamp.dat, metaData.json). ROI analysis now also reads the frame
  interval of TIFFs.
• Histology: Import regions (core/io/readRegions.m,
  writeImageJRoi.m): regions drawn in ImageJ / Fiji (.roi and the ROI
  Manager's RoiSet.zip: polygon, freehand, traced, rectangle and oval, with
  their names) or QuPath (GeoJSON annotations, Polygon and MultiPolygon,
  names or classifications) become Histology regions.
• Electrophysiology recordings from eight more systems (Extract Ephys
  → Source; core/io/readSpikeGLX.m, readBlackrock.m,
  readNeuralynx.m, readPlexon.m, readMCS.m, readIntanRHS.m,
  readOpenEphysLegacy.m, readABF.m): SpikeGLX (Neuropixels 1.0 / 2.0
  imec and nidq, sync and digital bits), Blackrock NSx 2.1-3.0 with the
  NEV digital input, Neuralynx .ncs folders with Events.nev TTLs, Plexon
  .plx (continuous channels placed by time stamp, AI and event channels,
  sorted spike times), Multi Channel Systems HDF5 (electrode, auxiliary
  and digital streams, events; MATLAB only), Intan .rhs (digital and
  analog inputs, stimulation current), Open Ephys legacy .continuous
  folders and Axon ABF 2 (gap-free or episodic). The format is also
  recognized from the file's extension, folder contents or first bytes;
  Try demo data writes the demo in each one, and the methods text names
  it. Each reader was checked during development against python-neo (and
  pyABF) on files from its synthetic writer (write*.m, used by the tests
  and the demo); for Multi Channel Systems, the file layout was checked
  with McsPyDataTools.
• EDF, EDF+ and BDF files (core/io/readEDF.m, writeEDF.m): the
  European Data Format that LabChart, clinical systems and many others
  export, with EDF+ annotations (onset, duration, text), discontinuous
  EDF+D recordings (records placed at their times) and BioSemi's 24-bit
  BDF with its Status trigger word. Extract LDF opens them again (the
  annotations can be the stimulus), and EEG analysis reads them as
  continuous EEG (the channels in volts, annotations and BioSemi trigger
  codes as events); the LDF demo and the rodent EEG demo are also written
  as EDF+ (and BDF).
• EGI .mff (core/io/readMFF.m, writeMFF.m): Net Station
  recordings (the .mff folder or its info.xml): float32 blocks,
  channel gains, pauses placed at their times, events, sensor positions
  and the vertex reference. mffpy and MNE-Python read the files written
  here with the same values, gains, pause and events, and readMFF reads
  mffpy's files. The rodent EEG demo is also written as .mff.
• XDF (core/io/readXDF.m, writeXDF.m): LabRecorder files (Lab
  Streaming Layer): every stream with its time stamps (full or deduced)
  and clock offsets; EEG analysis reads the EEG stream and takes the
  marker streams as events. pyxdf reads the files written here with the
  same values, time stamps and markers. The rodent EEG demo is also
  written as XDF.
• EEG-BIDS (core/io/readEEGBIDS.m, writeEEGBIDS.m): EEG analysis
  opens the sub-…_eeg file of a BIDS dataset (OpenNeuro) with its
  sidecar files: only the EEG channels of channels.tsv (bad channels
  noted), the events of events.tsv, the positions of electrodes.tsv
  with coordsystem.json, and the reference and line frequency of
  eeg.json. The rodent demo is also written as a BIDS dataset. Checked
  during development both ways with MNE-BIDS.
  Values and annotations were checked during development against pyedflib
  and MNE-Python.

Changed

• Extract LDF opens every recording above, not only the LabChart .mat
  export. Step 1 now has LDF, Stimulus and Block choices, guessed from
  the channel names (the old convention, stimulus on channel 6 and LDF on
  channel 8, stays for LabChart files with 8 or more unnamed channels);
  the stimulus can also be the comments / event markers of the file, or
  none. The plots are titled with the channel names, the file label shows
  the format, rate, duration and channels, and a table without a time
  column asks for its sampling rate. The cropped .mat also keeps
  flowName, flowUnits and stimName; sessions store the format and
  the channel choice (older sessions still open), and the methods text
  names the acquisition software and the channels.
• Launcher: Laser speckle joins LDF under Blood flow, so the tiles
  now take four rows at the default width (Blood flow and EEG, then
  Electrophysiology, Imaging and Across techniques).

Fixed

• README: the version badge said 0.5.1 in the 0.5.2 release.
• Histology: the pixel size of ImageJ TIFFs saved with the unit µm was not
  read (ImageJ writes it as \u00B5m); the Greek mu is accepted too, and
  an unknown unit falls back to the TIFF resolution tags.

Install: download the source ZIP below, unzip it, open MATLAB in that folder and run NeuroAnalyzerLab. See the README for details.

Neuronal Data Analyzer Lab v0.5.2

Changed

• Launcher: Course and Virtual lab keep their tiles under Learn with
  a greyed-out Coming soon button; they no longer point to website pages,
  which are offline until the Course and the Virtual lab are ready.

Install: download the source ZIP below, unzip it, open MATLAB in that folder and run NeuroAnalyzerLab. See the README for details.

Neuronal Data Analyzer Lab v0.5.1

Changed

• Name: Neuronal Data Analyzer Lab everywhere you read it: the website,
  the Help, the window titles and footers, reports, methods texts and the
  link previews (it was "NeuroAnalyzer" in most places). The command that
  opens it is now NeuroAnalyzerLab (was NeuroAnalyzer); sessions saved
  before open as before.
• Licence: PolyForm Noncommercial 1.0.0 with a citation condition (was
  "All rights reserved"). Free for noncommercial use (universities, public
  research, hospitals, charities, personal study): use it, change it and
  share it for these purposes. Commercial use needs a separate licence from
  the author. If you publish or present work that used it, cite it
  (CITATION.cff). LICENSE.txt, README, CITATION.cff and the window
  footers say so.
• Course and Virtual lab: coming soon. They are not in this release. In
  the launcher their tiles under Learn show a greyed-out Coming soon
  button; on the website their pages say what they will offer. Everything
  needed to learn the tool stays free: the in-app Help, Try with demo
  data and the website's guide and walkthroughs.
• Launcher: Help and demo data in one place. The Learn area keeps only
  the Course and Virtual lab. ? Help (top right) opens the Help, where
  every window's topic has Try it with demo data; each tile's ? opens
  its topic directly.
• The website is kept apart from this repository. It stays online
  (Help → Learn more opens it); its source is no longer in the toolbox.

Removed

• The Course and Virtual lab windows (CourseApp, VirtualLabApp), their
  Help topics, tests and website lesson pages.

Install: download the source ZIP below, unzip it, open MATLAB in that folder and run NeuroAnalyzerLab. See the README for details.