Recent studies suggest that transcranial electrical stimulation (tES) can be performed during functional magnetic resonance imaging (fMRI). The novel approach of using concurrent tES-fMRI to modulate and measure targeted brain activity/connectivity may provide unique insights into the causal interactions between the brain neural responses and psychiatric/neurologic signs and symptoms, and importantly, guide the development of new treatments. However, tES stimulation parameters to optimally influence the underlying brain activity may vary with respect to phase difference, frequency, intensity, and electrode's montage among individuals. Here, we propose a protocol for closed-loop tES-fMRI to optimize the frequency and phase difference of alternating current stimulation (tACS) for two nodes (frontal and parietal regions) in individual participants. We carefully considered the challenges in an online optimization of tES parameters with concurrent fMRI, specifically in its safety, artifact in fMRI image quality, online evaluation of the tES effect, and parameter optimization method, and we designed the protocol to run an effective study to enhance frontoparietal connectivity and working memory performance with the optimized tACS using closed-loop tES-fMRI. We provide technical details of the protocol, including electrode types, electrolytes, electrode montages, concurrent tES-fMRI hardware, online fMRI processing pipelines, and the optimization algorithm. We confirmed the implementation of this protocol worked successfully with a pilot experiment.

Recent studies suggest that transcranial electrical stimulation (tES) can be performed during functional magnetic resonance imaging (fMRI). The novel approach of using concurrent tES‐fMRI to modulate and measure targeted brain activity/connectivity may provide unique insights into the causal interactions between the brain neural responses and psychiatric/neurologic signs and symptoms, and importantly, guide the development of new treatments. However, tES stimulation parameters to optimally influence the underlying brain activity may vary with respect to phase difference, frequency, intensity, and electrode's montage among individuals. Here, we propose a protocol for closed‐loop tES‐fMRI to optimize the frequency and phase difference of alternating current stimulation (tACS) for two nodes (frontal and parietal regions) in individual participants. We carefully considered the challenges in an online optimization of tES parameters with concurrent fMRI, specifically in its safety, artifact in fMRI image quality, online evaluation of the tES effect, and parameter optimization method, and we designed the protocol to run an effective study to enhance frontoparietal connectivity and working memory performance with the optimized tACS using closed‐loop tES‐fMRI. We provide technical details of the protocol, including electrode types, electrolytes, electrode montages, concurrent tES‐fMRI hardware, online fMRI processing pipelines, and the optimization algorithm. We confirmed the implementation of this protocol worked successfully with a pilot experiment.

Real-time fMRI neurofeedback (rtfMRI-nf) left amygdala (LA) training is a promising intervention for major depressive disorder (MDD). We have previously proposed that rtfMRI-nf LA training may reverse depression-associated regional impairments in neuroplasticity and restore information flow within emotion-regulating neural circuits. Inflammatory cytokines as well as the neuroactive metabolites of an immunoregulatory pathway, i.e. the kynurenine pathway (KP), have previously been implicated in neuroplasticity. Therefore, in this proof-of-principle study, we investigated the association between rtfMRI-nf LA training and circulating inflammatory mediators and KP metabolites. Based on our previous work, the primary variable of interest was the ratio of the NMDA-receptor antagonist, kynurenic acid to the NMDA receptor agonist, quinolinic acid (KynA/QA), a putative neuroprotective index. We tested two main hypotheses. i. Whether rtfMRI-nf acutely modulates KynA/QA, and ii. whether baseline KynA/QA predicts response to rtfMRI-nf.Twenty-nine unmedicated participants who met DSM-5 criteria for MDD based on the Mini-International Neuropsychiatric Interview and had current depressive symptoms (Montgomery-Åsberg Depression Rating Scale (MADRS) score > 6) completed two rtfMRI-nf sessions to upregulate LA activity (Visit1 and 2), as well as a follow-up (Visit3) without rtfMRI-nf. All visits occurred at two-week intervals. At all three visits, the MADRS was administered to participants and serum samples for the quantification of inflammatory cytokines and KP metabolites were obtained. First, the longitudinal changes in the MADRS score and immune markers were tested by linear mixed effect model analysis. Further, utilizing a linear regression model, we investigated the relationship between rtfMRI-nf performance and immune markers. After two sessions of rtfMRI-nf, MADRS scores were significantly reduced (t[58] = −4.07, p = 0.009, d = 0.56). Thirteen participants showed a ≥ 25% reduction in the MADRS score (the partial responder group). There was a significant effect of visit (F[2,58] = 3.17, p = 0.05) for the neuroprotective index, KynA to 3-hydroxykynurenine (3-HK), that was driven by a significant increase in KynA/3-HK between Visit1 and Visit3 (t[58] = 2.50, p = 0.03, d = 0.38). A higher baseline level of KynA/QA (β = 5.23, p = 0.06; rho = 0.49, p = 0.02) was associated with greater ability to upregulate the LA. Finally, for exploratory purposes correlation analyses were performed between the partial responder and the non-responder groups as well as in the whole sample including all KP metabolites and cytokines. In the partial responder group, greater ability to upregulate the LA was correlated with an increase in KynA/QA after rtfMRI-nf (rho = 0.75, p = 0.03). The results are consistent with the possibility that rtfMRI-nf decreases metabolism down the so-called neurotoxic branch of the KP. Nevertheless, non-specific effects cannot be ruled out due to the lack of a sham control. Future, controlled studies are needed to determine whether the increase in KynA/3HK and KynA/QA is specific to rtfMRI-nf or whether it is a non-specific correlate of the resolution of depressive symptoms. Similarly, replication studies are needed to determine whether KynA/QA has clinical utility as a treatment response biomarker.

Left amygdala fMRI neurofeedback training with positive valenced autobiographical memory recall (LA-NF) is a promising intervention for major depressive disorder (MDD). We investigated the association between LA-NF and the kynurenine pathway (KP) metabolites, which have previously been implicated in neuroplasticity. The primary outcome was the ratio of NMDA-receptors’ antagonist to agonist - kynurenic acid (KynA) to quinolinic acid (KynA/QA), which forms the putative neuroprotective index. We tested two main hypotheses: i) whether LA-NF acutely modulates KynA/QA, and ii) whether baseline KynA/QA predicts response to LA-NF.

Recent studies suggest that transcranial electrical stimulation (tES) can be performed during functional magnetic resonance imaging (fMRI). The novel approach of using concurrent tES-fMRI to modulate and measure targeted brain activity/connectivity may provide unique insights into the causal interactions between the brain neural responses and psychiatric/neurologic signs and symptoms, and importantly, guide the development of new treatments. However, tES stimulation parameters to optimally influence the underlying brain activity in health and disorder may vary with respect to phase, frequency, intensity and electrode’s montage. Here, we delineate how a closed-loop tES-fMRI study of frontoparietal network modulation can be designed and performed. We also discuss the challenges of running a concurrent tES-fMRI, describing how we can distinguish clinically meaningful physiological changes caused by tES from tES-related artifacts. There is a large methodological parameter space including electrode types, electrolytes, electrode montages, concurrent tES-fMRI hardware, online fMRI processing pipelines and closed-loop optimization algorithms that should be carefully selected for closed-loop tES-fMRI brain modulation. We also provide technical details on how safety and quality of tES-fMRI settings can be tested, and how these settings can be monitored during the study to ensure they do not exceed safety standards. The initial results of feasibility and applicability of closed-loop tES-fMRI are reported and potential hypotheses for the outcomes are discussed. Highlight points Methodological details of a closed-loop tES-fMRI study protocol are provided. The protocol is performed successfully on a frontoparietal network without side-effects. The temperature of electrodes in concurrent tES-fMRI remains in the safe range. Properly setup concurrent tES does not introduce MRI artifacts and noise. Simplex optimizer could be used to find an optimal tES stimulation parameter.

The ventromedial prefrontal cortex (vmPFC) is involved in regulation of negative emotion and decision-making, emotional and behavioral control, and active resilient coping. This pilot study examined the feasibility of training healthy subjects (n = 27) to self-regulate the vmPFC activity using a real-time functional magnetic resonance imaging neurofeedback (rtfMRI-nf). Participants in the experimental group (EG, n = 18) were provided with an ongoing vmPFC hemodynamic activity (rtfMRI-nf signal represented as variable-height bar). Individuals were instructed to raise the bar by self-relevant value-based thinking. Participants in the control group (CG, n = 9) performed the same task; however, they were provided with computer-generated sham neurofeedback signal. Results demonstrate that (a) both the CG and the EG show a higher vmPFC fMRI signal at the baseline than during neurofeedback training; (b) no significant positive training effect was seen in the vmPFC across neurofeedback runs; however, the medial prefrontal cortex, middle temporal gyri, inferior frontal gyri, and precuneus showed significant decreasing trends across the training runs only for the EG; (c) the vmPFC rtfMRI-nf signal associated with the fMRI signal across the default mode network (DMN). These findings suggest that it may be difficult to modulate a single DMN region without affecting other DMN regions. Observed decreased vmPFC activity during the neurofeedback task could be due to interference from the fMRI signal within other DMN network regions, as well as interaction with task-positive networks. Even though participants in the EG did not show significant positive increase in the vmPFC activity among neurofeedback runs, they were able to learn to accommodate the demand of self-regulation task to maintain the vmPFC activity with the help of a neurofeedback signal.