DOI: 10.5061/dryad.gf1vhhmq0
title: Cortico-subcortical β burst dynamics underlying movement cancellation in humans

description: Dominant neuroanatomical models hold that humans regulate their movements
 via loop-like cortico-subcortical networks, including the subthalamic
 nucleus (STN), thalamus, and sensorimotor cortices (SMC). Inhibitory
 commands across these networks are purportedly sent via transient,
 burst-like signals in the β frequency (15-29Hz). However, since human
 depth-recording studies are typically limited to one recording site,
 direct evidence for this proposition is hitherto lacking. Here, we present
 simultaneous multi-site depth-recordings from SMC and either STN or
 thalamus in humans performing the stop-signal task. In line with their
 purported function as inhibitory signals, subcortical β-bursts were
 increased on successful stop-trials and were followed within 50ms by
 increased β-bursting over SMC. Moreover, between-site comparisons
 (including in a patient with simultaneous recordings from all three sites)
 confirmed that β-bursts in STN precede thalamic β-bursts. This provides
 first empirical evidence for the role of β-bursts in conveying inhibitory
 commands along long-proposed cortico-subcortical networks underlying
 movement regulation in humans.
description: These local field potential
 (LFP) recordings were made on a Tucker-Davis technologies (Alachua, FL)
 system, using a RA16PA 16-Channel Medusa pre-amplifier and a RA16LI
 head-stage. The sampling rate for recording was 24Hz or 2Hz, with a
 low-pass filter of 7.5 kHz on the hardware side. Stimulus onsets were
 marked in the recording using a TTL pulse from a USB Data Acquisition
 Device (USB-1208FS, Measurement Computing, Norton, MA) triggered by the
 stimulus presentation laptop. Data were collected from two four-, six-, or
 eight-contact strip electrodes placed in the subgaleal space over SMC
 (Ad-Tech, Oak Creek, WI; 10 mm spacing center-to-center, 3 mm exposed
 contact diameter) and DBS leads (3387, Medtronic, Inc, Minneapolis, MN)
 placed in either the thalamus or subthalamic nucleus. Raw data are stored
 in the folder named "data". Within this folder are two
 subfolders, "main" (containing the datasets from the main
 behavioral task) and "localizers" (containing the datasets from
 the go-only localization block used to confirm placement of subgaleal
 electrodes over hand motor regions). LFP data were preprocessed and
 analyzed using custom MATLAB scripts included with this dataset.
 Electrical line noise from the operating room environment was filtered
 from the data using EEGLAB’s (Delorme and Makeig, 2004)
 <i>cleanline</i> function after which the recordings were
 down-sampled to 1000Hz for analysis. Then, the recordings were visually
 inspected for any artifacts. Any 1s segment of the recording containing an
 artifact was removed from the data, yielding the preprocessed sets stored
 in the folder named "pp".  β burst detection was performed
 using the same procedure as in Wessel (2020) and Shin et al. (2017). Data
 from each bipolar electrode array were convolved with a complex Morlet
 wavelet. The absolute value of the resulting complex data was squared to
 yield time-frequency power estimates. The resulting time-frequency data
 were epoched around events of interest (go and stop signals) with a window
 of 500ms before stimulus onset to 1000ms after stimulus onset. β bursts
 were classified by identifying local maxima in the trial-by-trial
 time-frequency data that exceeded six times the median of the
 time-frequency power for that specific array across the recording and that
 lasted at least two β cycles. Indices of these beta bursts in the
 recordings are stored in the data structures included in the
 "beta" folder. For more information on data
 collection, preprocessing, and analysis, please see the associated
 manuscript. 
description: To run the analyses scripts included with this dataset, MATLAB
 2017a or later is needed, including the signal processing toolbox and
 EEGLab toolbox. Detailed documentation regarding the
 function of each MATLAB analysis script is provided in code
 comments.