Mobile Brain-Body Imaging (MoBI) dual-tasking datasets (response inhibition while walking): Older adults
Data files
Feb 12, 2024 version files 226.23 GB
Abstract
Combining walking with a demanding cognitive task is traditionally expected to elicit decrements in gait and/or cognitive task performance. However, it was recently shown that, in a cohort of young adults, most participants improved performance when walking was added to performance of a Go/NoGo response inhibition task. The present study aims to extend these previous findings to an older adult cohort, to investigate whether this improvement when dual-tasking is observed in healthy older adults. Mobile Brain/Body Imaging (MoBI) was used to record electroencephalographic (EEG) activity, three-dimensional (3D) gait kinematics and behavioral responses in the Go/NoGo task, during sitting or walking on a treadmill, in 34 young adults and 37 older adults. Increased response accuracy during walking, independent of age, was found to correlate with slower responses to stimuli (r = 0.44) and with walking-related EEG amplitude modulations over frontocentral regions (r = 0.47) during the sensory gating (N1) and conflict monitoring (N2) stages of inhibition, and over left-lateralized prefrontal regions (r = 0.47) during the stage of inhibitory control implementation (P3). These neural activity changes are related to the cognitive component of inhibition, and they were interpreted as signatures of behavioral improvement during walking. On the other hand, aging, independent of response accuracy during walking, was found to correlate with slower treadmill walking speeds (r = -0.68) and attenuation in walking-related EEG amplitude modulations over left-dominant frontal (r = -0.44) and parietooccipital regions (r = 0.48) during the N2 stage, and over centroparietal regions (r = 0.48) during the P3 stage. These neural activity changes are related to the motor component of inhibition, and they were interpreted as signatures of aging. Older adults whose response accuracy ‘paradoxically’ improved during walking manifested neural signatures of both behavioral improvement and aging, suggesting that their flexibility in reallocating neural resources while walking might be maintained for the cognitive but not for the motor inhibitory component. These distinct neural signatures of aging and behavior can potentially be used to identify ‘super-agers’, or individuals at risk for cognitive decline due to aging or neurodegenerative disease.
README: Title of Dataset
Mobile Brain-Body Imaging (MoBI) dual-tasking datasets (response inhibition while walking): Older adults
Description of the data and file structure
This Drayd dataset contains multimodal MoBI data, collected from older adults while performing the 1-back Go/NoGo response inhibition task and concurrently walking on a treadmill.
The data is organized as follows:
|-- 010705027
| |-- LSLData
| | |-- 010705027_1.mat
| | |-- 010705027_2.mat
| |-- Logfiles_Raw
| | |-- GoNoGo_010705027_1.txt
| | |-- GoNoGo_noTraining_010705027_2.txt
| | |-- mainExperScript_010705027_1.log
| | |-- mainExperScript_noTraining_010705027_2.log
| | |-- motion_state_010705027_1.txt
| | |-- motion_state_010705027_2.txt
| | |-- Training_GoNoGo_010705027.txt
| |-- Logfiles_Processed
| | |-- GoNoGo_010705027_processed.txt
| | |-- mainExperScript_010705027_processed.txt
| |-- EEGstruct_Raw
| | |-- 010705027.set
| | |-- 010705027.fdt
|-- 010705028
| |-- LSLData
| | |-- 010705028.mat
| |-- Logfiles_Raw
| | |-- GoNoGo_010705028.txt
| | |-- mainExperScript_010705028.log
| | |-- motion_state_010705028.txt
| | |-- Training_GoNoGo_010705028.txt
| |-- Logfiles_Processed
| | |-- GoNoGo_010705028_processed.txt
| | |-- mainExperScript_010705028_processed.txt
| |-- EEGstruct_Raw
| | |-- 010705028.set
| | |-- 010705028.fdt
|-- ...
|-- ...
|-- ...
|-- metadata.xlsx
Notes:
About the LSLData folder:
The .mat
file in this folder contains a cell array with the 3 synchronized datastreams (EEG, motion capture, behavioral responses) along with metadata. Each cell of the array contains a different datastream.
In case the Presentation scenario had to be terminated before its completion (e.g. the participant wanted to take a restroom break), then a new scenario was launched after the break to complete the required number of task blocks. In those cases, two separate .mat
files occurred: one containing the recording before the break (e.g. 010705027_1.mat
, 010705082_1.mat
) and another containing the recording after the break (eg. 010705027_2.mat
, 010705082_2.mat
).
About the Logfiles_Raw folder:
The
GoNoGo_{participantID}.txt
is a manually created logfile containing the following information about the images presented during the Go/NoGo task (each row corresponds to one image):- Column Block: contains the block number during which the image was presented
- Column Trial: contains the trial number during which the imagee was presented
- Column Image: contains the IAPS code of the presented image
- Column RespTime: contains the response time to the presented image
- Column MotState: contains
sitting
if the block was a sitting block, andwalking
if the block was a walking block - Column Button: contains
1
if a valid button press was recorded in response to the image, and0
if no valid button press was recorded.
The
Training_GoNoGo_{participantID}.txt
is a manually created logfile containing the same information as theGoNoGo_{participantID}.txt
, but only for the training block. Note that this data was not analyzed the in the paper--it only serves to assess how well the participant understands the task, before they start with the actual experiment.The
motion_state_{participantID}.txt
is a manually created logfile containing the order in which sitting and walking blocks were performed. IMPORTANT: this is the final/correct sequence of walking/sitting -- if the walking/sitting sequence in theGoNoGo_{participantID}.txt
is different, then it must change to align with this one. The reason why those two sequences are different for some participants between the two logfiles is because the walking/sitting sequence that had initially been planned for them (GoNoGo_{participantID}.txt
) had to change on the fly, for example because they were tired and requested to do more sitting and leave walking for later.The
mainExperScript_{participantID}.log
is an logfile automatically generated by Presentation after the completion of each experimental scenario run. The information is organized in the following columns:- Column Trial: incremental trial number
- Column Event Type: it can take one the following values
-
Picture
: this is the most common event. ThePicture
event is on throughout runtime of the experimental scenario (even when a the black screen with the white centered cross is dispayed on the projection screen--that is a picture too) -
Response
: button press from the Nintendo switch -
Text Input
: it occurs at the end of some experimental blocks. The experimenter has coded the scenario to pause and wait until text input from is provided -
Pause
: it occurs at the end of some experimental blocks. It indicates that the scenario has been paused manually. -
Resume
: it almost always occurs after pause events, at the end of some experimental blocks. It indicates that the scenario has been resumed manually. -
Quit
: the scenario has been ternimated manually before its completion
-
- Column Code:
- For the Picture event type, it can take one of the following values:
-
countdown_3
: Part of the countdown at the beginning of each experimental block. Displays a white '3' with a black background on the projection screen in front of the participant. -
countdown_2
: Part of the countdown at the beginning of each experimental block. Displays a white '2' with a black background on the projection screen in front of the participant. -
countdown_1
: Part of the countdown at the beginning of each experimental block. Displays a white '1' with a black background on the projection screen in front of the participant. -
countdown_go
: Part of the countdown at the beginning of each experimental block. Displays a white 'Go' with a black background on the projection screen in front of the participant. -
pic_display
: Displays an IAPS image on the projection screen in front of the participant. -
fixation_cross_no_resp
: Displays a white '+' with a black background on the projection screen in front of the participant. No button presses are accepted during this event code, since they are considered as delayed responses to the previous trial. -
fixation_cross_resp
: Displays a white '+' with a black background on the projection screen in front of the participant. Button presses are accepted during this event code.
-
- For the Response event type, it can take either of the following values:
-
1
For button presses provided by the participant during task performance. -
2
: For keyboard presses provided by the experimenter at the end of each block, to enable continuing to the next block.
-
- For all the rest of the event types (Text Input, Pause, Resume, Quit), the event code value is empty.
- For the Picture event type, it can take one of the following values:
Column Time: time of occurrence of each event relative to the start of the scenario.
Column TTime: time of occurrence of each event relative to the start of the trial the event is in.
Column Uncertainty (Time): temporal uncertainty for each event. For details, see here
Column Duration: For picture stimuli, this is the duration of the picture presentation. For pause events, this is the duration of the pause. Presentation does not monitor the durations of other events.
Column Uncertainty (Duration): uncertainty in the duration of a picture stimulus. For details, see here
Column ReqTime: Requested time of presentation given in the scenario file. Note that actual presentation times for picture stimuli are constrained by the monitor refresh and therefore should differ from requested times.
Column ReqDur: For picture stimuli, this is the requested duration of presentation given in the scenario file. Note that picture stimuli durations are constrained by the monitor refresh.
Column Stim Type: Its value is
other
, except for pictures with codefixation_cross_resp
during which button presses are accepted. For these picture events, the value is eitherhit
(button press was detected) or miss (no button press was detected).
All times written in the logfile are in tenths of milliseconds (0.1 milliseconds resolution). The uncertainties provide the upper limit so that an uncertainty of 0.2 milliseconds means the uncertainty is between 0.1 and 0.2 milliseconds.
To view the logfile data properly aligned with respect to the columns defined above, it is suggested to use the following command in MATLAB:
S = importdata({full_path_to_logfile},'\t')
where S is a structure, and the field S.textdata is a cell array containing the aligned data.
For more details about its structure, check the Presentation documentation.
The event code of every image is the same, i.e. pic_display
, which functions as a placeholder. To obtain behaviorally meaningful information, i.e. whether a specific trial was a correct or incorrect Go or NoGo, we need to know which exact IAPS image code each pic_display
event corresponds to. To this end, information from the mainExperScript_{participantID}.log
has to be fused with information from the GoNoGo_{participantID}.txt
(after ensuring that the walking/sitting sequence of the latter is corrected according to the motion_state_{participantID}.txt
).
In case the Presentation scenario had to be terminated before its completion (e.g. the participant wanted to take a restroom break), then a new scenario was launched after the break to complete the required number of task blocks. As such, two separate sets of logfiles occurred, for all logfiles described above. Any logfile recorded as part of the first session, before the break, is denoted by an additional _1
at the end of the logfile name, for example: mainExperScript_010705082_1.log
, GoNoGo_010705082_1.txt
, motion_state_010705082_1.txt
and Training_GoNoGo_010705082_1.txt
. Any logfile recorded as part of the second session, after the break, is denoted by an additional _2
at the end of the file name, for example: mainExperScript_010705082_2.log
, GoNoGo_010705082_2.txt
, motion_state_010705082_2.txt
and Training_GoNoGo_010705082_2.txt
.
In some cases where running the training block was not necessary (e.g. for the second recording session after the break, or the participant had already completed the training block shortly before the start of the experiment), the logfile name contains an additional _noTraining
string, and no manually created training logfile was generated in this case, for example: mainExperScript_noTraining_010705042.log
and GoNoGo_noTraining_010705042.txt
.
About the Logfiles_Processed folder:
The
GoNoGo_{participantID}_processed.txt
is the same as theGoNoGo_{participantID}.txt
, with the difference that it has 2 additional columns:- Column EmoState: contains the emotional valence (
positive/neutral/negative
) of each presented image. The classification into the 3 categories was conducted based on Grühn & Scheibe, 2008. - Column ZeroClusters: contains
1
for all trials except those which belong to a cluster of 6 consecutive non-responses; those latter trials are assigned the value0
in this column
- Column EmoState: contains the emotional valence (
The
mainExperScript_{participantID}_processed.txt
is the same as themainExperScript_{participantID}.log
, with the difference that every placeholder 'pic_display' event code has been replaced with an appropriate string of the following structure:StimOnset_MotState_EmoState_DistPrevNoGo_{distanceNum}_ButtonResp_{Button}_ZeroCluster_{ZeroClusters}_RT_{RespTime}_BlockNum_{Block}
. TheDistPrevNoGo
is followed by a number that indicates how many trials before the current one the last NoGo trial happened (distanceNum).
About the EEGstruct_Raw folder:
Contains .set
and .fdt
files, which are formats used by EEGLAB. EEGLAB is an open-source MATLAB toolbox for electrophysiological signal processing and analysis. Here is an example of loading an EEG dataset, using the pop_loadset function provided by EEGLAB:
EEGstruct = pop_loadset('010705027.set')
.set
files contain the metadata and .fdt
files contain the raw data.
Alternatively, if the user prefers to work with .mat
files only, they can load each EEG structure only once using pop_loadset, and then save it as a .mat
file as follows:
save('010705027.mat','EEGstruct','-v7.3')
Each of these folders essentially contains a structure, the fields of which have been populated with EEG and behavioral data. Specifically, the field data contains a (channels)x(time points) matrix with the raw EEG data; the field event contains a structure where field type contains the event names (e.g. sitting_hit_negative
, walking_corrRej_positive
) and field latency contains the EEG time point at which the event occured.
About the metadata.xlsx:
This Excel file contains metadata about the whole dataset, organized into 2 sheets, the Young Adults
sheet and the Older adults
sheet. Each sheet contains metadata for the respective age group indicated by the sheet name. The first 5 columns are common across the 2 sheets:
- Column ID: The 9-digit participant ID which is also the name of the individual participant data folders, e.g.
010705001
. The last 3 digits represent an incrementally-assigned number from 1-102. - Column Age: Participant's age at the time of the recording
- Column Speed: treadmill speed, in miles per hour
- Column Sex:
F
for female,M
for male - Column Dominant hand (coincides with the hand used to provide button-press responses):
R
for right hand,L
for left hand
The Older adults
sheet includes one additional, 6th column MoCA score containing the MoCA scores for each of the older participants.
Sharing/Access information
Data for this project will only be shared via Dryad.
Data was not derived from any other sources.
Code/Software
The code will be provided here.
Associated Datasets
In the context of this study, data were also collected from young adults while performing the 1-back Go/NoGo response inhibition task and concurrently walking on a treadmill. These young adult data can be found in the Dryad dataset titled Mobile Brain-Body Imaging (MoBI) dual-tasking datasets (response inhibition while walking): Young adults.
Methods
This dataset was collected using the Mobile Brain-Body Imaging modality, involving synchronous recordings of 3 data streams:
1) EEG (BioSemi Inc., Amsterdam, The Netherlands)
2) Behavioral responses to the designed Go/NoGo task (Presentation, Neurobehavioral Systems Inc., Berkeley, CA, USA)
3) Full-body kinematics (OptiTrack, NaturalPoint, Inc., Corvallis, OR, USA).
To record these 3 data streams in a time-synchronized manner, the Lab Streaming Layer (LSL: https://labstreaminglayer.org/#/) was used.
The data included are raw, except for the behavior-related logfiles, for which both raw and processed versions are provided (see README file for details).