Abstract

Prefrontal cortex (PFC) asymmetry is an important marker in affective neuroscience and has attracted significant interest, having been associated with studies of motivation, eating behavior, empathy, risk propensity, and clinical depression. The data presented in this paper are the result of three different experiments using PFC asymmetry neurofeedback (NF) as a Brain-Computer Interface (BCI) paradigm, rather than a therapeutic mechanism aiming at long-term effects, using functional near-infrared spectroscopy (fNIRS) which is known to be particularly well-suited to the study of PFC asymmetry and is less sensitive to artifacts. From an experimental perspective the BCI context brings more emphasis on individual subjects' baselines, successful and sustained activation during epochs, and minimal training. The subject pool is also drawn from the general population, with less bias toward specific behavioral patterns, and no inclusion of any patient data. We accompany our datasets with a detailed description of data formats, experiment and protocol designs, as well as analysis of the individualized metrics for definitions of success scores based on baseline thresholds as well as reference tasks. The work presented in this paper is the result of several experiments in the domain of BCI where participants are interacting with continuous visual feedback following a real-time NF paradigm, arising from our long-standing research in the field of affective computing. We offer the community access to our fNIRS datasets from these experiments. We specifically provide data drawn from our empirical studies in the field of affective interactions with computer-generated narratives as well as interfacing with algorithms, such as heuristic search, which all provide a mechanism to improve the ability of the participants to engage in active BCI due to their realistic visual feedback. Beyond providing details of the methodologies used where participants received real-time NF of left-asymmetric increase in activation in their dorsolateral prefrontal cortex (DLPFC), we re-establish the need for carefully designing protocols to ensure the benefits of NF paradigm in BCI are enhanced by the ability of the real-time visual feedback to adapt to the individual responses of the participants. Individualized feedback is paramount to the success of NF in BCIs.

Highlights

  • AND RATIONALEThere is growing interest in sharing datasets for Brain-Computer Interfaces (BCI), to facilitate comparison of technical approaches

  • Because the hemodynamic response measured by fNIRS occurs in ∼7 s, we discarded the first 7 s of data in each View and NF epoch for determining block success

  • This way we characterized each block with a dichotomous success value and a continuous success score (Cohen’s d or d for short) that reflects the distance between the distribution of asymmetry values between View and NF epochs within the same block

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Summary

INTRODUCTION

There is growing interest in sharing datasets for Brain-Computer Interfaces (BCI), to facilitate comparison of technical approaches Their availability is of particular relevance for applications in which there is significant diversity of practice and lack of standardized protocols, such as Neurofeedback (NF) (Ros et al, 2020). We introduce three datasets obtained as part of fNIRS BCI experiments The originality of these datasets is that they were produced in a BCI context yet using a NF paradigm, in which users control their Prefrontal Cortex (PFC) asymmetry. The use of a NF approach to BCI is characterized by an emphasis on RoI activation over long-term effects, often with minimal training compared to clinical uses of NF It is of particular interest when the RoI signal is not under direct volitional control, as the NF channel assists the user in controlling the signal. HEU (Cavazza et al, 2017) uses BCI input to a hybrid humanAI system

PFC Asymmetry in Neuroscience Research
Neurofeedback Concepts
Common Description of fNIRS NF Experiments
Representativity and Interest of the Dataset
Apparatus
Data Formats
Generic Data
Subjects
Blocks
Time Series Discussion
CONCLUSIONS
Epochs
ETHICS STATEMENT
Full Text
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