A Prospective Study of the Impact of Transcranial Alternating Current Stimulation on EEG Correlates of Somatosensory Perception

Abstract

The (8–12 Hz) neocortical alpha rhythm is associated with shifts in attention across sensory systems, and is thought to represent a sensory gating mechanism for the inhibitory control of cortical processing. The present preliminary study sought to explore whether alpha frequency transcranial alternating current stimulation (tACS) could modulate endogenous alpha power in the somatosensory system, and whether the hypothesized modulation would causally impact perception of tactile stimuli at perceptual threshold. We combined electroencephalography (EEG) with simultaneous brief and intermittent tACS applied over primary somatosensory cortex at individuals’ endogenous alpha frequency during a tactile detection task (n = 12 for EEG, n = 20 for behavior). EEG-measured pre-stimulus alpha power was higher on non-perceived than perceived trials, and analogous perceptual correlates emerged in early components of the tactile evoked response. Further, baseline normalized tactile detection performance was significantly lower during alpha than sham tACS, but the effect did not last into the post-tACS time period. Pre- to post-tACS changes in alpha power were linearly dependent upon baseline state, such that alpha power tended to increase when pre-tACS alpha power was low, and decrease when it was high. However, these observations were comparable in both groups, and not associated with evidence of tACS-induced alpha power modulation. Nevertheless, the tactile stimulus evoked response potential (ERP) revealed a potentially lasting impact of alpha tACS on circuit dynamics. The post-tACS ERP was marked by the emergence of a prominent peak ∼70 ms post-stimulus, which was not discernible post-sham, or in either pre-stimulation condition. Computational neural modeling designed to simulate macroscale EEG signals supported the hypothesis that the emergence of this peak could reflect synaptic plasticity mechanisms induced by tACS. The primary lesson learned in this study, which commanded a small sample size, was that while our experimental paradigm provided some evidence of an influence of tACS on behavior and circuit dynamics, it was not sufficient to induce observable causal effects of tACS on EEG-measured alpha oscillations. We discuss limitations and suggest improvements that may help further delineate a causal influence of tACS on cortical dynamics and perception in future studies.

Human Neocortical Neurosolver (HNN): A new software tool for interpreting the cellular and network origin of human MEG/EEG data

“…By keeping model output in close agreement with the data, HNN's underlying model has led to new and generative predictions on the origin of sensory evoked responses and low-frequency rhythms, and changes in these signals across experimental conditions (Jones et al, 2009(Jones et al, , 2007Khan et al, 2015;Lee & Jones, 2013;Sherman et al, 2016;Sliva et al, 2018;Ziegler et al, 2010), described further below. The macro-to micro-scale nature of the HNN software is designed to develop and test hypotheses that can be directly validated with invasive recordings or other imaging modalities (see further discussion in tutorial on Alpha and Beta rhythms).…”

“…The choice of "activation" to the network depends on the simulation experiment. The GUI design is motivated by our prior published studies and was built specifically to simulate sensory evoked responses or spontaneous rhythms, or a combination of the two (Jones et al, 2009(Jones et al, , 2007Khan et al, 2015;Lee & Jones, 2013;Sherman et al, 2016;Sliva et al, 2018;Ziegler et al, 2010). The tutorials described in the Results section below details examples of how to "activate" the network to simulate sensory evoked responses and spontaneous rhythms.…”

“…As a specific example on how to use HNN as a hypothesis testing tool, we have used HNN to evaluate hypothesized changes in EEG measured neural circuit dynamics with non-invasive brain stimulation ( Figure 5). We measured somatosensory evoked responses from brief threshold-level taps to the middle finger tip before and after 10 minutes of ~10Hz transcranial alternating current stimulation (tACS) over contralateral somatosensory cortex (see Sliva et al, 2018 for details). The magnitude of an early peak near ~70ms in the tactile evoked response increased after the tACS session ( Figure 5, top left).…”

“…HNN's underlying mathematical model has been successfully applied to interpret the mechanisms and meaning of these common signals, including sensory evoked responses and oscillations in the alpha (7-14 Hz), beta (15-29Hz) and gamma bands (30-80Hz) (Jones et al, 2009;Jones, Pritchett, Stufflebeam, Hämäläinen, & Moore, 2007;Lee & Jones, 2013;Sherman et al, 2016;Ziegler et al, 2010), and changes with perception (Jones et al, 2007) and aging (Ziegler et al, 2010). The model has also been used to study the impact of non-invasive brain stimulation on circuit dynamics measured with EEG (Sliva et al, 2018), and to constrain more reduced "neural mass models" of laminar activity (Pinotsis et al, 2017). In the clinical domain, HNN's model has also been applied to study MEG-measured circuit deficits in Autism (Khan et al, 2015).…”

Multi-frequency tACS has lasting effects on neural synchrony and audiovisual responses

“…In fact, no entrainment-specific features such as phase-continuity or synchronization to exact stimulation frequencies were observed by Vossen and colleagues, leading to the conclusion that the observed tACS aftereffects on intrinsic activity were most likely plasticity-based. With respect to stimulus processing, a recent EEG study in human subjects [47] has reported significant differences between responses to tactile stimuli recorded prior to and after series of brief intermittent alpha-band tACS (6s, 1mA, several hundred repetitions, frequency tailored to individual's alpha-peak). From modeling, Sliva and colleagues propose a process of local synaptic facilitation, which may have specifically amplified distal "feedback" input (~70 ms post-stimulus) to the SI circuitry.…”