Abstract
In traditional fMRI, individuals respond to exogenous stimuli and are naïve to the effects of the stimuli on their neural activity patterns. Changes arising in the fMRI signal are analyzed post-hoc to elucidate the spatial and temporal activation of brain regions associated with the tasks performed. The advent of real-time fMRI has enabled a new method to systematically alter brain activity across space and time using neurofeedback training (NFT), providing a new tool to study internally-driven processes such as neuroplasticity. In this work, we combined n-back practice with fMRI-NFT of the left dorsolateral prefrontal cortex (DLPFC) to better understand the relationship between open- and closed-loop neuromodulation. FMRI data were acquired during both traditional n-back and NFT across five imaging sessions. Region-of-interest (ROI) and voxel-wise 2 × 2 within subjects ANOVAs were carried out to determine the effects of, and interaction between, training session and neuromodulation type. A main effect of training session was identified for only a single, highly focused cluster that shared spatial properties with the fMRI-NFT target region (left DLPFC). This finding indicates that combined open- and closed-loop neuroplastic enhancement techniques result in focal changes that are confined to the target area of NFT, and do not affect up- or down-stream network components that are normally engaged during working memory. Additionally, we identified a main effect of neuromodulation type for 15 clusters with significantly different activation between open- and closed-loop neuromodulation during training, 12 of which demonstrated higher activity during the open-loop neuromodulation. Our results, taken together with previous reports, indicate that fMRI-NFT combined with n-back practice leads to a highly focal volume exhibiting neuroplasticity without additional network effects.
Highlights
Evidence shows that neuroplasticity follows specific learningdependent changes in behavior (Kleim et al, 2004)
Recent advances in functional magnetic resonance imaging acquisition and reconstruction times have enabled the use of real-time blood oxygen level-dependent (BOLD) signals combined with neurofeedback training (NFT) to induce and control localized neuroplasticity (Ogawa et al, 1990; Logothetis et al, 2001; Megumi et al, 2015)
We demonstrated the ability of healthy human subjects to gain increasing control over neural activity of the left dorsolateral prefrontal cortex (DLPFC), and showed that neuroplastic effects associated with increased control led to improved cognitive performance (Sherwood et al, 2016)
Summary
Evidence shows that neuroplasticity follows specific learningdependent changes in behavior (Kleim et al, 2004). Recent advances in functional magnetic resonance imaging (fMRI) acquisition and reconstruction times have enabled the use of real-time blood oxygen level-dependent (BOLD) signals combined with neurofeedback training (NFT) to induce and control localized neuroplasticity (Ogawa et al, 1990; Logothetis et al, 2001; Megumi et al, 2015). In traditional fMRI, individuals respond to exogenous stimuli that activate specific brain regions or networks. During these tasks, the participants are naïve to the timing and location of the induced neural activity (open-loop neuromodulation). The ability to volitionally control neural activity, as trained in fMRI-NFT, holds the potential to be translated into in-home care routines, where they could be implemented without specialized equipment or professional supervision (Vaughan et al, 2006; Mak and Wolpaw, 2009)
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