When the Brain Takes 'BOLD' Steps: Real-Time fMRI Neurofeedback Can Further Enhance the Ability to Gradually Self-regulate Regional Brain Activation

Abstract

Brain-computer interfaces (BCIs) based on real-time functional magnetic resonance imaging (rtfMRI) are currently explored in the context of developing alternative (motor-independent) communication and control means for the severely disabled. In such BCI systems, the user encodes a particular intention (e.g., an answer to a question or an intended action) by evoking specific mental activity resulting in a distinct brain state that can be decoded from fMRI activation. One goal in this context is to increase the degrees of freedom in encoding different intentions, i.e., to allow the BCI user to choose from as many options as possible. Recently, the ability to voluntarily modulate spatial and/or temporal blood oxygenation level-dependent (BOLD)-signal features has been explored implementing different mental tasks and/or different encoding time intervals, respectively. Our two-session fMRI feasibility study systematically investigated for the first time the possibility of using magnitudinal BOLD-signal features for intention encoding. Particularly, in our novel paradigm, participants (n=10) were asked to alternately self-regulate their regional brain-activation level to 30%, 60% or 90% of their maximal capacity by applying a selected activation strategy (i.e., performing a mental task, e.g., inner speech) and modulation strategies (e.g., using different speech rates) suggested by the experimenters. In a second step, we tested the hypothesis that the additional availability of feedback information on the current BOLD-signal level within a region of interest improves the gradual-self regulation performance. Therefore, participants were provided with neurofeedback in one of the two fMRI sessions. Our results show that the majority of the participants were able to gradually self-regulate regional brain activation to at least two different target levels even in the absence of neurofeedback. When provided with continuous feedback on their current BOLD-signal level, most participants further enhanced their gradual self-regulation ability. Our findings were observed across a wide variety of mental tasks and across clinical MR field strengths (i.e., at 1.5T and 3T), indicating that these findings are robust and can be generalized across mental tasks and scanner types. The suggested novel parametric activation paradigm enriches the spectrum of current rtfMRI-neurofeedback and BCI methodology and has considerable potential for fundamental and clinical neuroscience applications.

Keywords: (gradual) self-regulation; (real-time) functional magnetic resonance imaging; brain-computer interface; cognitive strategies; mental tasks; neurofeedback.

Fig. 1

Overview of experimental design. The figure depicts the experimental design for one participant. Bluish and reddish colors indicate no-feedback and feedback conditions, respectively. Greenish colors refer to the two conditions implemented in the functional-localizer run. Resting blocks are indicated by gray cells. Resting and modulation blocks took 26 s each.

Fig. 2

Visual instruction and neurofeedback display. A thermometer-like display on black background was used consisting of ten white rectangles stacked on top of each other. To instruct participants to adjust their BOLD signal to a particular target level, the outline of a certain rectangle turned red for the duration of the modulation trial. During resting blocks no rectangle was colored red. During feedback runs, continuously updated gradual feedback information was additionally provided by filling the rectangles with gray color according to the current BOLD signal intensity reached by the participant in the neurofeedback target region.

Fig. 3

Individual neurofeedback target regions. The figure shows the individually defined neurofeedback target regions overlaid on transversal slices of the participants’ mean anatomy in Talairach space. Note that the selected regions are the widely distributed across the whole cortex. Characteristics of the selected brain regions (anatomical labeling, size, Talairach coordinates etc.) can be derived from Table 2. Remarks: L = left hemisphere; R = right hemisphere.

Fig. 4

Gradual self-regulation ability across both type-of-training conditions (group and single-subject results). A. Mean beta values for each target-level condition across all participants separately for the no-feedback (blue) and feedback (red) condition. Error bars represent standard errors of the means from within-subjects analysis. B. Contrast analysis between target level-specific beta values separately for the no-feedback and feedback condition across all participants. All comparisons reach statistical significance (p < 0.01, see asterisks) except for one contrast (contrasting the medium vs. the low target level in the no-feedback condition). C. Single-subject mean beta values separately for each target-level and type-of-training condition. Participants with a black underline underwent feedback condition first and no-feedback condition second.

Fig. 5

Comparison of individual gradual self-regulation ability across the two type-of-training conditions. The figure depicts individual Fisher z-transformed correlation values between obtained single-trial beta values and desired target levels separately for the no-feedback (blue line) and feedback (red line) condition and their differences (gray bars). In 80% of the participants, single-trial beta values were more correlated with the desired target levels when participants received neurofeedback (vs. being not provided with neurofeedback information). Participants with a black underline underwent feedback condition first and no-feedback condition second). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Fig. 6

Mean heart and breathing rates for each target-level condition. Mean heart (A) and breathing (B) rates of P02-P05 and P09 are plotted separately for each target-level condition. While mean heart rates only showed negligible differences across target-level conditions, slightly increased breathing frequencies at higher target-level conditions can be observed. Error bars indicate variance across participants (±SEM).