DOI: 10.5061/dryad.n2z34tn5s
title: Data from: Measuring instability in chronic human intracortical neural recordings towards stable, long-term brain-computer interfaces

description: Intracortical brain-computer interfaces (iBCIs) enable people with
 tetraplegia to gain intuitive cursor control from movement intentions. To
 translate to practical use, iBCIs should provide reliable performance for
 extended periods of time. However, performance begins to degrade as the
 relationship between kinematic intention and recorded neural activity
 shifts compared to when the decoder was initially trained. In addition to
 developing decoders to better handle long-term instability, identifying
 when to recalibrate will also optimize performance. We propose a method,
 “MINDFUL”, to measure instabilities in neural data for useful long-term
 iBCI, without needing labels of user intentions. Longitudinal
 data were analyzed from two BrainGate2 participants with tetraplegia as
 they used fixed decoders to control a computer cursor spanning 142 days
 and 28 days, respectively. We demonstrate a measure of instability that
 correlates with changes in closed-loop cursor performance solely based on
 the recorded neural activity (Pearson r = 0.93 and 0.72,
 respectively). This result suggests a strategy to infer online iBCI
 performance from neural data alone and to determine when recalibration
 should take place for practical long-term use.
description: Longitudinal iBCI Cursor Control using a Fixed
 Decoder These data are released with the manuscript -
 by <em>Pun, T. K. et al. Measuring instability in chronic human
 intracortical neural recordings towards stable, long-term brain-computer
 interfaces. Nature Communications Biology <strong>7</strong>,
 1363 (2024).</em> Written by Tsam Kiu Pun, 2024.
 Brown University. Dataset Description
 This dataset comprises intracortical neural signals recorded from
 two participants enrolled in the BrainGate2 pilot clinical trial
 (NCT00912041): 
 <strong>T5</strong>: A 65-year-old right-handed male with a C4
 AIS-C SCI incurred approximately 9 years prior to enrollment.
 <strong>T11</strong>: A 37-year-old right-handed
 male with a C4 AIS-B spinal cord injury (SCI) incurred approximately 11
 years prior to enrollment. This research
 was conducted under an Investigational Device Exemption (IDE) granted by
 the US Food and Drug Administration (IDE #G090003; CAUTION:
 Investigational device. Limited by Federal law to investigational
 use).  All sessions took place at the
 participants' residences. Intracortical neural
 recordings and neural features Each participant had
 two 96-channel microelectrode arrays (Blackrock Neurotech, Salt Lake City,
 UT) placed in the dominant (left) hand/arm knob area of the precentral
 gyrus 2. The following neural features are included in this
 dataset: <strong>T5:</strong>
 Multi-unit threshold-crossing spike rates (RMS &lt; -3.5) per
 electrode. <strong>T11</strong>:
 Multi-unit threshold-crossing spike rates (RMS &lt; -3.5) and power in
 the spike band (250-5000 Hz) per electrode. 
 BCI behavioral tasks 
 <strong>T5: </strong>Performed a closed-loop 2D random target
 selection task across 6 sessions spanning 28 days (trial days 2121-2149),
 using a fixed linear decoder. Each session included two to four 4-minute
 closed-loop blocks. Total task time: 84 minutes, 1200 trials.
 <strong>T11</strong>: Performed a closed-loop 2D
 point-and-click center-out-and-back task across 15 sessions spanning 4
 months (trial days 658-800), using a fixed RNN-based decoder. Each session
 included two 5-minute task blocks, except for trial day 751 with one
 block. Total task time: 145 minutes, 1840 trials. In
 addition for T11, approximately 16 minutes of personal use (i.e. active
 web browsing) on trial day 658 and 10 minutes of random target tasks on
 trial day 665 were included to assess the robustness of MINDFUL using
 different task as the reference dataset. This data is stored in separate
 subfolder within the folder named "T11(additional)/". The same
 RNN decoder was used online.
description: ## Data Organization This dataset contains data from two participants.
 Data of each participants is organized into respective folders, namely
 "T5/" and "T11/", with subfolders categorizing data by
 trial day and block number. Additional T11 (personal use and random target
 tasks) is in the "T11(additional)/" folder. Each block contains
 three files: "data.mat", "task.mat", and
 "info.mat". Only selected blocks from each session were
 included. \&gt;&gt; T5/      &gt;&gt; day k/           &gt;&gt; block_01/
                &gt;&gt; data.mat                &gt;&gt; task.mat        
        &gt;&gt; info.mat           &gt;&gt; block_02/       &gt;&gt; day
 n/           &gt;&gt; ... \&gt;&gt; T11/      &gt;&gt; day k/          
 &gt;&gt; block_01/                &gt;&gt; data.mat              
  &gt;&gt; task.mat                &gt;&gt; info.mat      &gt;&gt; ...
 \&gt;&gt; T11(additional)/      &gt;&gt; day k/           &gt;&gt;
 block_01/      &gt;&gt; ... # Field description of each .mat
 "data.mat" contains neural features, and inferred and decoded
 velocity vectors; "task.mat" contains task related per trial
 information and "info.mat" contains additional information such
 as cursor performance metrics. Below is the description of each field of
 each .mat file within each block. nStep: number of 20 ms steps (bins)
 nChan: number of channels of both arrays nTrial: number of trials where a
 trial spans target cue to target acquisition ### data.mat nctx : [nStep x
 nChan] Raw concatenated neural features - non-causal threshold crossings
 (RMS &lt; -3.5) spikePower : [nStep x nChan] Raw concatenated neural
 features - spike band power (250 – 5000 Hz) labels : [nStep x 2] Inferred
 2-d cursor-to-target vector [x, y] cursorVel : [nStep x 2] Decoded 2-d
 velocity vector output from the decoder [x, y] ### task.mat name : [str]
 Task name for this block - ['Fitts', 'circle',
 'personal use'] nPointsPerBlock : [1 x 1] Number of time steps
 in this block startStops : [nTrial x 2] trial [start, stop] time indices
 in chronological order excludeTrials : [nTrial x 1] Boolean; True if trial
 is excluded due to mean noise exceeding 5% during trial useClick : [nTrial
 x 1] Boolean; True if click was used to select target in task moveDirVect
 : [nTrial x 2] Movement direction vector [x, y] ### info.mat This contains
 task related performance info, as well as outlier details. targetPos :
 [nStep x 2] Target position [x, y] cursorPos : [nStep x 2] Cursor position
 [x, y] magEst : [nStep x 1] Adjusted decoded cursor-to-target magnitude
 from the decoder percentCorrect : [1 x 1] Success rate of the block in
 percentage pathEfficiency : [nTrial x 1] Path efficiency per trial
 trialSuccess : [nTrial x 1] Boolean; True if trial success orthChanges :
 [nTrial x 1] Number of orthogonal directional changes per trial
 timeToTarget : [nTrial x 1] Time to target per trial in second
 angleErrorPerTrial : [nTrial x 1] Median angular error per trial
 angleError : [nSteps x 1] Instantaneous angular error in degree
 (additional field, if available) prctOutliers : [nStep x Ch - sparsed
 matrix] Percent of ns5 outliers per channel per time step avgOutliers :
 [nStep x 1] Maximum average outlier across all channels between arrays per
 time step