Transcranial alternating current stimulation: a review of the underlying mechanisms and modulation of cognitive processes

Abstract

Brain oscillations of different frequencies have been associated with a variety of cognitive functions. Convincing evidence supporting those associations has been provided by studies using intracranial stimulation, pharmacological interventions and lesion studies. The emergence of novel non-invasive brain stimulation techniques like repetitive transcranial magnetic stimulation (rTMS) and transcranial alternating current stimulation (tACS) now allows to modulate brain oscillations directly. Particularly, tACS offers the unique opportunity to causally link brain oscillations of a specific frequency range to cognitive processes, because it uses sinusoidal currents that are bound to one frequency only. Using tACS allows to modulate brain oscillations and in turn to influence cognitive processes, thereby demonstrating the causal link between the two. Here, we review findings about the physiological mechanism of tACS and studies that have used tACS to modulate basic motor and sensory processes as well as higher cognitive processes like memory, ambiguous perception, and decision making.

Keywords: EEG; alpha; electroencephalogram; gamma; oscillations; transcranial alternating current stimulation; transcranial direct current stimulation; transcranial magnetic stimulation.

Figures

Figure 1

Different stimulation paradigms. Top: During tDCS, a direct current will be switched on for a duration of typically a few minutes. Middle: In contrast, tACS uses alternating currents for stimulation that can either be sinusoidal (solid line) or rectangular (dotted line). Bottom: Combining tDCS and tACS results in oscillatory tDCS (otDCS), where the alternating current is superimposed onto a direct current. The alternating current can again be sinusoidal or rectangular.

Figure 2

Comparison of rTMS and tACS. Left: tACS uses sinusoidal currents which are restricted to one frequency as shown by a time-frequency wavelet transform. Right: rTMS, however, spans a wide range of frequencies in addition to the frequency of repetition. Note, that these diagrams depict only the stimulation currents/fields—not possible artifacts that may be elicited in the human brain.

Figure 3

Physiological mechanisms of tACS. Left:In vivo recordings in ferrets show that spontaneous neuronal activity seen in MUA synchronizes to certain phases of LFPs. Right: Stimulating slices of cortex electrically with sinusoidal currents results in a similar synchronization. Interestingly, the inter-burst frequency of the spontaneously occurring activity can be speeded up and slowed down resulting in neural entrainment [adapted from Fröhlich and McCormick (2010)].

Figure 4

Modeling tACS-induced intracranial current flow. Axial view of a human brain visualizing the current density distribution of tDCS/tACS applied at electrode locations F7 (anode, red) and F8 (cathode, blue). A clear maximum in anterior brain areas can be seen. Current densities are 20 times stronger in frontal as compared to occipital cortex. However, tDCS/tACS with large electrodes is not as focal as TMS. Reprinted from Neuling et al. (2012b) with permission of the authors.

Figure 5

Model predictions of how a network of neurons would behave in response to AC stimulation. The firing rates of inhibitory (gray) and excitatory (black) neurons are up- and down-regulated in phase with the AC current. In these raster plots, each dot represents a neural spike. Adapted from Reato et al. (2010).

Figure 6

Network simulation of tACS. (A) Spike timing dependent plasticity: synaptic weights are increased if a post-synaptic potential follows a pre-synaptic spike (long-term potentiation, LTP) and decreased if a post-synaptic potential occurs prior to a pre-synaptic spike (long-term depression, LTD). (B) Schematic illustration of the network: A driving neuron establishes a recurrent loop with each neuron of a hidden layer. The total synaptic delay, Δt, (i.e., the sum of both delays of the loop) varied between 20 and 160 ms. The driving neuron was stimulated with a spike train of 10 Hz repetition rate. (C) Synaptic weights of the back-projection as a function of the total synaptic delay of the recurrent loops: Gray dots display synaptic weights at the start of the simulation, black dots represent synaptic weights after the end of simulation. External stimulation of the driving neuron at 10 Hz resulted in increased weights for recurrent loops with a total delay between 60 and 100 ms, and dramatically reduced synaptic weights for loops with total delays outside this interval. Note, that the highest synaptic weights are observed at 100 ms, i.e., for loops with a resonance frequency near the stimulation frequency. Reprinted from Zaehle et al. (2010) with permission of the authors.

Figure 7

Effects of 40 Hz tACS with 180° phase difference between hemispheres. (A) Configuration of the bistable apparent motion display together with the EEG and tACS electrode montage. EEG electrodes that were used for analyzing interhemispheric coherence are indicated in red. The tACS sponge electrodes were placed bilaterally over the parietal-occipital cortex. This montage leads to 40 Hz stimulation with 180° phase difference between hemispheres. (B) The motion dominance index is significantly enhanced during 40 Hz tACS (black bar) as compared to sham stimulation (white bar), indicating that 40 Hz tACS results in a longer total duration of perceived vertical motion (*P < 0.05). Error bars display the standard error of the mean. (C) Mean coherence within the 30–45 Hz frequency band shows a significant increase from pre-tACS to post-tACS (right), but not from pre-sham to post-sham (left). Error bars correspond to standard errors of the mean; *P < 0.05. Adapted from Strüber et al. (2013) with permission of the authors.