Prefrontal Asymmetry BCI Neurofeedback Datasets

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.

Keywords: PFC asymmetry; dataset; functional near infrared spectroscopy (fNIRS); neurofeedback (NF); visual feedback (VF).

Figure 1

NF Feedback categorization: abstract [HEU], semantic [ANG], and task-related [RAP].

Figure 2

(A) Overview of the apparatus used in our experiments: fNIR Optical Brain Imaging System (fNIR400) by Biopac Systems with one PC dedicated to the data acquisition, and one PC dedicated to running the simulation and visualization of the stimulus presented in real-time to the subjects. (B) The 16-channel sensor placed on the subjects' forehead (C) showing the selected channels for the calculation of the asymmetry values.

Figure 3

Experimental setup for the ANG experiment (see Figure 1 [ANG] for overall visual feedback setup).

Figure 4

Protocol design for the ANG experiment.

Figure 5

Results from the post-hoc analysis of the ANG experiment, illustrating the dynamics of PFC asymmetry over the whole experiment for successful blocks (Left) and unsuccessful blocks (Right) successful blocks demonstrates a significant increase of the left-side oxygenation compared to unsuccessful blocks.

Figure 6

(A,B) Experimental setup for the RAP experiment (see Figure 1 [RAP] for overall visual feedback setup).

Figure 7

Protocol design for the RAP experiment.

Figure 8

Results from the post-hoc analysis of the RAP experiment, illustrating the dynamics of PFC asymmetry over the whole experiment for successful blocks (Left) and unsuccessful blocks (Right) successful blocks demonstrates a significant increase of the left-side oxygenation compared to unsuccessful blocks.

Figure 9

Experimental setup for the HEU experiment (see Figure 1 [HEU] for overall visual feedback setup). A* represent is artificial intelligence search algorithm.

Figure 10

Protocol design for the HEU experiment.

Figure 11

Results from the post-hoc analysis of the HEU experiment, illustrating the dynamics of PFC asymmetry over the whole experiment for successful blocks (Left) and unsuccessful blocks (Right) successful blocks demonstrates a significant increase of the left-side oxygenation compared to unsuccessful blocks.

Figure 12

Diagram providing details of the structure of the overall datasets. The only difference in structures are shown in the blocks data, where (a) is specific to both [ANG] and [RAP] experiments, whilst (b) is specific to the [HEU] experiment.