This whole project began thanks to the BCI Database Group, a group that I was lucky enough to join in their mission of categorizing all BCI-related abstracts in order to facilitate future research. All these categories were developed thanks to their work, and the abstracts have all been gathered by them as well.

1. Publication Type (Single-Select): Does the publication describe original research, a review, or some other type of publication?

   • Original Research: Publication developed a new dataset or made a contribution based on an existing dataset.
   • Review: Publication provided a survey of some aspect of the BCI field.
   • Other: Publication is an editorial, tutorial, release of public datasets, etc.

2. Data type (Multi-Select): Does the publication rely on original data, a dataset, or some other type of data?

   • Original Data: Publication developed their own dataset.
   • Dataset: Publication uses an existing dataset.
   • Other: Publication relies on simulated data, theory, or other sources.

3. Population (Multi-Select): The subject(s) used in the publication.

   • Animal: Publication uses animals as the subject/user of the BCI.
   • Healthy: Publication uses healthy humans as the subject/user of the BCI.
   • Clinical: Publication uses a clinical (human) population as the subject/user of the BCI.
   • Other: Publication uses a cell culture or other population for their research.

4. Sub-Population (Multi-Select): A more fine-grained description of the subject population used in the publication.

5. Application (Single-Select): The effect the BCI has on the function of the central nervous system, based on Wolpaw & Wolpaw’s (2012) 5 types of applications, with 2 additional options.

   • Enhance: Enables the CNS to respond to events/produce outputs at a level exceeding its natural ability.
   • Supplement: Provides the CNS with new ways to interact with the world beyond any individual’s natural output.
   • Replace: Provides an alternative system for performing a lost function (following disease/injury). The benefits of the BCI remain only while it is in operation.
   • Restore: Enables a user to regain natural function that has been lost due to disease or injury. The benefits of the BCI, however, only occurs when the system is in use (i.e., they do not induce neural plasticity [contrast with improve below]).
   • Improve: Allows a user to regain lost functionality (following disease/injury) with effects that remain even when the BCI system is not in use.
   • Contribute: Uses a BCI to investigate phenomena in another field.
   • Design: Focuses on the refinement of methods, technologies, or techniques used in multiple BCI applications.

   Note: In some cases, a publication develops a BCI with one application, but states a vision of BCIs used for another application. When applicable, choose the application of BCI implemented, not the hypothetical application.

6. Recording Type (Multi-Select): the type of neural activity recorded.

   • Electrical
   • Magnetic
   • Metabolic

7. Recording Method (Multi-Select): The specific measurement method used.

   • For electrical:
     • Electroencephalography (EEG)
     • Electrocorticography (ECoG)
     • Intracortical
   • For magnetic:
     • Magnetoencephalography (MEG)
   • For metabolic:
     • Functional magnetic resonance imaging (fMRI)
     • Ultrasound
     • Functional near-infrared spectroscopy (fNIRS)

8. Brain Signal (Multi-Select): The type of brain activity that is used in the BCI.

   • Attention
   • Auditory
   • Error
   • Frontal
   • Hybrid
   • Motor
   • Slow Cortical Potential (SCP): SCPs are event-related potentials that are time-locked and phase locked to specific sensorimotor events (i.e., they occur at predictable times before, during, or after specific events; Wolpaw & Wolpaw, 2012).
   • Visual
   • Other: (e.g. affective, consciousness, memory system, speech, spinal cord, subcortical, and tactile)

9. Paradigm (Multi-Select): The method used to elicit the brain signal.

   • For Attention:
     • Alpha: Changes in the alpha band (8–12 Hz) that occur when the user is asked to do an attention-related task (Bougrain et al., 2016).
   • For Auditory:
     • Auditory Evoked Potential (AEP): Stereotyped voltage deflections time-locked to an auditory stimulus.
     • Acoustic Steady-State Response (ASSR): Stable oscillations in activity elicited by repetitive auditory stimuli.
     • P300: A positive deflection in the EEG after a rare auditory stimulus.
   • For Error:
     • Error-Related Negativity (ERN): A negative component of an evoked potential that occurs after a response error (the user realizes they made a mistake; Bougrain et al., 2016)
     • Feedback-Related Negativity (FRN): An evoked potential that occurs after a feedback error (the users given feedback that is different than what they expected; Bougrain et al., 2016).
   • For Frontal:
     • Cognitive Tasks: Based on activity in response to higher cognitive tasks (e.g. mental rotation, mental arithmetic, etc.)
   • For Hybrid:
     • Combinations of other paradigms presented here (e.g. Alpha-SSVEP, P300-SSVEP, etc.)
     • Note: Hybrid describes a BCI where multiple signals and paradigms are used together in asingle BCI system to create an enhanced BCI system. If the publication simply tests alternateparadigms, take advantage of the multi-select.
   • For Motor:
     • Imagery Tasks: Changes in sensorimotor rhythms (SMRs) elicited by the imagination of movement.
     • Movement: Changes in SMRs elicited by actual movement.
   • For Slow Cortical Potential (SCP): SCPs are event-related potentials that are time-locked and phase locked to specific sensorimotor events (i.e., they occur at predictable times before, during, or after specific events; Wolpaw & Wolpaw, 2012).
     • Neurofeedback: Provides the user with feedback of their SCP to aid in their control of this signal.
   • For Visual:
     • motion-onset visual evoked potential (mVEP): a visual evoked potential that is elicited specifically by motion (Wolpaw& Wolpaw, 2012).
     • P300: A positive deflection in the EEG after a rare visual stimulus.
     • rapid serial visual presentation (RSVP): Fast bursts of symbols presented successively at a central location(Acqualagna et al., 2010)
     • steady-state visual evoked potential (SSVEP): Stable oscillations in activity elicited by repetitive visual stimuli
     • visual evoked potential (VEP): Stereotyped voltage deflections time-locked to a visual stimulus.
     • N2pc: A component of an evoked potential that reflects the focusing of attention on a potential target in a visualsearch array (Luck, 2011).
   • For Other: (e.g. affective, consciousness, memory system, speech, spinal cord, subcortical, and tactile)

   **Note: We include speech as “other” despite the fact that it relies on motor output, as speech is typically thought of as a unique function of the motor system.

10. Purpose (Multi-Select): The user application or how the output(s) of the BCI was used.

    • Communication: Used to aid one’s ability to communicate (e.g. text entry, P300 speller).
    • Offline/Online Target Selection: Used to discriminate between various targets/options.
    • Brain Switch: Used to let user control (asynchronously) when the BCI is “on” or “off.”
    • Neuroprosthetic/Robotic Control: Used to power an external prosthetic or robot.
    • Gaming/Computer Control: Used to control a game or computer.
    • Cursor/Movement Control: Used to control a cursor or the movement of a (virtual) object.
    • Clinical/Brain-State Monitoring: Used to detect seizure, drowsiness, etc.
    • Domotics/Environmental Control: Used to control one’s surroundings (e.g. a smart home).
    • Image Triage: Used to order images by relevance or whether they are a “target”
    • Neurofeedback: Used to provide feedback to the user of their current brain state.
    • Other

    Be careful not to choose the motivating purpose (e.g. communication), but the purpose of the implemented BCI (e.g. cursor control).

11. Contribution (Single-Select): The area in which the publication advances the BCI field.

    • Basic Research: Research that seeks to uncover new knowledge aboutBCIs/the nervous system with no goal/objective in mind.
    • Applied Research: Research that seeks to uncover new knowledgewith a specific goal/objective in mind (i.e. there is a problem they wantto solve).
    • Experimental Development: The refinement of a BCI system throughexperiments on either specific subparts of a BCI system or the systemas a whole.
    • Support: The development of tools, software, datasets, etc. to aid BCIresearch.

12. Sub-Contributions

    • Basic Research Sub-Contributions:
      • Ethics: The publication explores ethical questions in BCIs.
      • Neural Signals: The publication explores neural signals that can be used in a BCI.
      • Signal Modeling: The publication models neural signals used in a BCI.
      • User: The publication explores how a user can interact with a BCI (e.g. whether a specific task can be used).
      • Demographics: The publication explores whether a BCI can be used in a certain sub-population of subjects.
      • Signal Measurement/Acquisition: The publication explores potential new techniques for measuring or acquiring neural signals.
      • Other
    • Applied Research Sub-Contributions:
      • Clinical (Assessment): The publication seeks to develop a BCI for assessment of some clinical condition.
      • Clinical (Therapeutic): The publication seeks to develop a BCI as a therapeutic intervention for some clinical condition.
      • Home Use: The publication seeks to develop a BCI for home use (e.g. outside the clinic).
      • Purpose: The publication seeks to develop a BCI for a new purpose or user application.
      • Healthy Population: The publication seeks to develop a BCI for a new population of users.
      • Independent Use: The publication seeks to develop a BCI that can be used independently of the motor system.
      • Collaborative: The publication seeks to develop a collaborative BCI system.
      • Other
    • Experimental Development Sub-Contributions:
      • User: The publication refines a BCI system by changing how the user interacts with the system.
      • Digital Signal Processing (DSP): The publication refines a BCI system by changing the signal processing algorithms/techniques used.
      • Signal Measurement/Acquisition: The publication refines a BCI system by changing how neural signals are measured/acquired.
      • Feedback/Interface: The publication refines a BCI system by changing the feedback given to the user or the user interface.
      • System: The publication refines a BCI system by altering the system as a whole.
      • Other
    • Support Sub-Contributions:

Abstract #1

EEG classification using Learning Vector Quantization (LVQ) is introduced on the basis of a Brain-Computer Interface (BCI) built in Graz, where a subject controlled a cursor in one dimension on a monitor using potentials recorded from the intact scalp. The method of classification with LVQ is described in detail along with first results on a subject who participated in four on-line cursor control sessions. Using this data, extensive off-line experiments were performed to show the influence of the various parameters of the classifier and the extracted features of the EEG on the classification results.

1. Publication Type (Single-Select): Does the publication describe original research, a review, or some other type of publication?

Based on the provided abstract, the first abstract falls under the category of “Original Research” as it describes the development and implementation of a Brain-Computer Interface (BCI) using EEG classification with Learning Vector Quantization (LVQ) methodology, along with presenting results from online cursor control sessions and offline experiments to analyze the influence of various parameters on classification results.