Vibrissa Oscillator (vIRt)

This model provides a computational framework to support longstanding observations of concurrent autonomous and driven rhythmic motor actions and how the interaction of the Central whisking oscillator Breathing oscillator dynamics can be studied using conductance- and rate-based modeling. The github site includes computer programs and scripts for generating figures from the article:

David Golomb, Jeffrey D. Moore, Arash Fassihi, Jun Takatoh, Vincent Prevosto, Fan Wang and David Kleinfeld, Theory of hierarchically-organized neuronal oscillator dynamics that mediate rodent rhythmic whisking. Neuron, (2022) 110:3833-3851.
Software needed: julia compiler, XMGrace LaTeX

DOI: 10.1016/j.neuron.2022.08.020


Simulation Programs


Contact: Professor David Golomb 

Mechanical Model of Whisker Bending

Samuel Andrew Hires, Lorenz Pammer, Karel Svoboda, and David Golomb, Tapered whiskers are required for active tactile sensation. Elife 2:e01350, 2013.

This is an ode script for XPPAUT that computes whisker bending in response to contact with object. The calculation is based on the quasi-static approximation, and conic whisker profile is considered.


Contact: Professor David Golomb 

Bassler_Camera_control, version of 22 Nov 2020

General software for control of Bassler camera to record animal behavior

Coded by C. Foo. Matlab-based routines to acquire video (1280x1024 frames) at high frame rates (>200Hz) for hardware-dependent periods; we currently achieve continuous acquisition of 720x720 frames at ~350 Hz.


Contact: Dr. Conrad Foo 

Analysis of neuronal spike trains, deconstructed

Coded by Prof. Johnatan Aljadeff and Dr. Benjamin J. Lansdell. Matlab-based routines for capturing relationships between spiking activities and the external stimuli. The algorithm extracts features from the input stimulus and predicts the spike rate using different models (e.g. GLM). The predicted spike rate is then used to generate the spike train by a stochastic process (e.g. Poisson process). Three example datasets are included:

  1. (Salamander) Multi-electrode array recording from retinal ganglion cells in response to white noise visual stimulus (Chichilnisky, 2001; Touryan et al., 2002; Rust et al., 2005; Pillow et al., 2008).
  2. (Rat) Single unit recordings of thalamic neurons, with simultaneous vibrissa motion (Moore et al., 2015).
  3. (Monkey) Single unit recordings of motor cortex with simultaneous recording of hand position and grip strength during joystick manipulation (Engelhard et al., 2013).

Please contact Prof. Johnatan Aljadeff for questions on the operation of this software. If you use this software in your research, please reference Aljadeff et al. (Neuron 2016) - ( )

Further: (1) commercial software from MathWorks is required, including MATLAB, the Image Processing Toolbox, the Optimization Toolbox, the Signal Processing Toolbox, the Statistics Toolbox, and the Symbolic Math Toolbox. (2) download Daniel Hill’s code (code and datasets) for the Hilbert transform (code); (3) download Partha Mitra’s Chronux Toolbox (; (4) download Jonathan Pillow’s Generalized Linear Model (GLM) implementation for spike trains (; (5) download Mark Schmidt’s L1-norm function L1GeneralGroup_Auxiliary.m (; and (6) download multidimensional histogram function histcn.m download at If you use this software in your research, please reference Aljadeff et al. (Neuron 2016)

Software and Data

Contact: Professor Johnatan (Yonatan) Aljadeff

UltraMegaSort2000, version of Feb 2012



Coded by D. N Hill and S. B. Mehta following an initial version coded by M. S. Fee. Matlab-based routines for the detection and clustering of putative single units from a multi-unit time series, along with quality metrics. Please contact Dr. Daniel N. Hill for questions on the operation and maintenance of this software after consulting the manual. If you use this software in your research, please reference Hill et al. (J Neurosci 2012) - ( ) and Fee et al. (J Neurosci Meth 1997) - ( ) & ( )

Contact: Dr. Daniel Hill

Hilbert transform


Coded by D. N. Hill, this makes use of Matlab-based routines for the extraction of amplitude, midpoint, and phase from a rhythmic signal using Black's technique. Please contact Dr. Daniel N. Hill for questions on the operation of this software. If you use this software in your research, please reference Hill et al. (Neuron 2011) - ( )

Contact: Dr. Daniel Hill

Intelligent_scanning 1.0

Algorithm and Demo Code

Coded by I. Valmianski and J. D. Driscoll. Matlab-based routines for the automatic identification of fluorescently labeled brain cells in two-photon scanning microscopy image stacks and the subsequent calculation of an optimized scan path through these cells. This program makes concurrent use of JBoost. Please contact Mr. Ilya Valmiansky for questions on the operation of this software. If you use this software in your research, please reference Valmianski et al. (J Neurophysiol 2010) - ( )

Contact: Mr. Ilya Valmiansky


Visualization and annotation tool for brains. Anatomists can view high-resolution tissue stacks and use the drawing tools to annotate and map the 3D topography of brain regions and the localization of injections via labelled cells. A groundbreaking automated system, employing cell shape parametric features and boosted decision trees, and featuring a simplified annotation process, is designed for premotor neuron detection. (in progress)

Mac Key Shortcut Reference

Front End Code (Neuroglancer fork)

Back End Code (API)

ML (feature detection)

Contact (all but feature detection): Mr. Duane Rinehart

Contact (feature detection): Mr. Kui Qian

Orofacial tracking

Deepfacetracking is a cross-platform package for automated tracking of a single head, eye, pupil, and rows of whiskers in the high-speed video. The package includes preprocessing and a graphical user interface for experimenters to modify and correct the automatic tracking outcomes.

Software (in progress)

Contact (scientific): Dr. Arash fassihiZakeri

Contact (software): Mr. Duane Rinehart

Rhythmic head and orofacial movements in foraging and rearing

The package contains codes to analyze and visualize the temporal and spectral coordination of orofacial (whisking, pad retraction, nose wiggling) and neck motor actions with respiration in the rat performing naturalistic behaviors (foraging and rearing) in an open arena.

A change in behavioral state switches the pattern of motor output that underlies rhythmic head and orofacial movements. S.-M. Liao and D. Kleinfeld, Current Biology (2023).

( )


NWB Data

Contact: Dr. Song-Mao Liao 

A brainstem circuit for the expression of defensive facial reactions in rat

Chemoreceptors in the nasal epithelium can trigger an apneic reaction and a grimace in response to airborne irritants. Callado Perez et al. find that the underlying circuit does not involve olfaction. Rather, activation of neurons in the muralis subnucleus of the spinal trigeminal complex will inhibit the Pre-Bötzinger inhalation oscillator.



Contact (scientific): Dr. Arash fassihiZakeri