Information

Specified effect of trans cranial electric stimulation on neurotransmitters


Can a specific voltage from a trans cranial stimulation activate specific neurotransmitter receptors or channels? By specific, it means receptors dedicated to specific neurotransmitters such as acetylcholine, dopamine, etc.


Background

The growing use of transcranial electric and magnetic (EM) brain stimulation in basic research and in clinical applications necessitates a clear understanding of what constitutes the dose of EM stimulation and how it should be reported.

Methods

This paper provides fundamental definitions and principles for reporting of dose that encompass any transcranial EM brain stimulation protocol.

Results

The biologic effects of EM stimulation are mediated through an electromagnetic field injected (via electric stimulation) or induced (via magnetic stimulation) in the body. Therefore, transcranial EM stimulation dose ought to be defined by all parameters of the stimulation device that affect the electromagnetic field generated in the body, including the stimulation electrode or coil configuration parameters: shape, size, position, and electrical properties, as well as the electrode or coil current (or voltage) waveform parameters: pulse shape, amplitude, width, polarity, and repetition frequency duration of and interval between bursts or trains of pulses total number of pulses and interval between stimulation sessions and total number of sessions. Knowledge of the electromagnetic field generated in the body may not be sufficient but is necessary to understand the biologic effects of EM stimulation.

Conclusions

We believe that reporting of EM stimulation dose should be guided by the principle of reproducibility: sufficient information about the stimulation parameters should be provided so that the dose can be replicated.


Electroconvulsive Therapy

Electroconvulsive therapy (ECT) uses an electric current to treat serious mental disorders. This type of therapy is usually considered only if a patient's illness has not improved after other treatments (such as antidepressant medication or psychotherapy) are tried, or in cases where rapid response is needed (as in the case of suicide risk and catatonia, for example).

ECT: Why it’s done

ECT is most often used to treat severe, treatment-resistant depression, but it may also be medically indicated in other mental disorders, such as bipolar disorder or schizophrenia. It also may be used in life-threatening circumstances, such as when a patient is unable to move or respond to the outside world (e.g., catatonia), is suicidal, or is malnourished as a result of severe depression.

ECT can be effective in reducing the chances of relapse when patients undergo follow-up treatments. Two major advantages of ECT over medication are that ECT begins to work quicker, often starting within the first week, and older individuals respond especially quickly.

ECT: How it works

Before ECT is administered, a person is sedated with general anesthesia and given a medication called a muscle relaxant to prevent movement during the procedure. An anesthesiologist monitors breathing, heart rate and blood pressure during the entire procedure, which is conducted by a trained medical team, including physicians and nurses. During the procedure:

  • Electrodes are placed at precise locations on the head.
  • Through the electrodes, an electric current passes through the brain, causing a seizure that lasts generally less than one minute. Because the patient is under anesthesia and has taken a muscle relaxant, it is not painful and the patient cannot feel the electrical impulses.
  • Five to ten minutes after the procedure ends, the patient awakens. He or she may feel groggy at first as the anesthesia wears off. But after about an hour, the patient usually is alert and can resume normal activities.

A typical course of ECT is administered about three times a week until the patient's depression improves (usually within 6 to 12 treatments). After that, maintenance ECT treatment is sometimes needed to reduce the chances that symptoms will return. ECT maintenance treatment varies depending on the needs of the individual, and may range from one session per week to one session every few months. Frequently, a person who undergoes ECT also takes antidepressant medication or a mood stabilizing medication.

ECT Side Effects

The most common side effects associated with ECT include:

Some people may experience memory problems, especially of memories around the time of the treatment. Sometimes the memory problems are more severe, but usually they improve over the days and weeks following the end of an ECT course.

Research has found that memory problems seem to be more associated with the traditional type of ECT called bilateral ECT, in which the electrodes are placed on both sides of the head.

In unilateral ECT, the electrodes are placed on just one side of the head—typically the right side because it is opposite the brain's learning and memory areas. Unilateral ECT has been found to be less likely to cause memory problems and therefore is preferred by many doctors, patients and families.


Experimental and Computational Results

Experiment Results of Aδ-Fibers for Pulse-Train Electrical Stimulation

The injection current threshold to generate pain perception via Aδ-fibers was experimentally obtained for pulse-train electrical stimulation at a fixed frequency (30 Hz). As shown in Figure 3A , the threshold decreased with an increase in the pulse number and converged after five consecutive pulses. The synaptic effect generated a reduction of the threshold by 2.3 times for multiple-pulse stimulation of five or more consecutive pulses to a single pulse. Higher variability was observed for a few pulses due to intrinsic skin morphology and needle depth variability in the experiments, which will be discussed below. Thus, the measured perception thresholds were normalized by the average of the thresholds from six to ten pulses ( Figure 3B ). The reaction time of the volunteers in Table 1 requires more time for a larger number of pulses.

(A) Experimental perception threshold variation with pulse number by a pulse-train electrical stimulation (mean value and standard deviation, n = 8), and (B) its normalization by the average of the thresholds from six to ten pulses (mean value and standard deviation).

TABLE 1

The reaction time of perception threshold at a different number of pulses and frequencies.

Pulse numberReaction time [s] (Mean ± SD)Frequency [Hz]Reaction time [s] (Mean ± SD)
10.521 ± 0.112100.642 ± 0.060
20.487 ± 0.073200.586 ± 0.087
30.496 ± 0.088300.508 ± 0.078
40.559 ± 0.126400.508 ± 0.041
50.606 ± 0.124500.479 ± 0.054
60.615 ± 0.110600.490 ± 0.117
70.641 ± 0.059800.484 ± 0.098
80.631 ± 0.0691000.427 ± 0.083
90.609 ± 0.0632000.422 ± 0.094
100.641 ± 0.113

The dependence of the threshold was also investigated for frequency (10 Hz to 200 Hz), as shown in Figure 4A for six pulses. The mean value of the minimum threshold was found at 30 Hz (10 Hz and 80 Hz), which converged at a mean frequency of 120 Hz (80 Hz to 200 Hz). The threshold was reduced by up to 26% of the maximum value. To reduce the intrinsic variability in the experiments, the threshold was normalized by the mean value of the converged threshold, which was defined as the threshold at a frequency of 80 Hz to 200 Hz ( Figure 4B ). The normalized curve shows a clear tendency, confirming the bottom peak at 30 Hz. As shown in Table 1 , the reaction time was slower at lower frequencies.

(A) Experimental perception threshold variation with frequency by a pulse-train electrical stimulation (mean value and standard deviation, n = 9), and (B) its normalization by the average of the thresholds between 80 Hz and 200 Hz (mean value and standard deviation) (Mean value and standard deviation).

Verification of Aδ-Fibers and Synaptic Effect by Evoked Potentials

We detected evoked potentials from Aδ-fiber stimulation using single-pulse stimulation. Table 2 shows the peak latency of pain-related evoked potentials that were not significantly affected by pulse width (330� ms). These reaction times were faster than those when the participant pressed the button under the same conditions in our previous study (470 ms to 520 ms) (Tanaka et al., 2021).

TABLE 2

Experimental threshold and peak latency of pain-related evoked potentials by single-pulse stimulation (mean value and standard deviation, n = 3).

Pulse width (μs)Threshold [mA] (Mean ± SD)Reaction time by evoked potential latency [s] (Mean ± SD)
600.983 ± 0.1520.363 ± 0.020
1000.647 ± 0.0840.364 ± 0.085
2000.487 ± 0.0210.330 ± 0.039
4000.330 ± 0.0450.370 ± 0.035
8000.323 ± 0.0210.380 ± 0.101
16000.257 ± 0.0490.391 ± 0.015

We also verified synaptic effects using evoked potential measurements. Figure 5 shows the evoked potentials for different numbers of consecutive stimulation pulses. The stimulation amplitude was fixed for all conditions (perception threshold of eight pulses). We observed pain-related evoked potentials at eight and six pulses, but not for two or four pulses, which agrees with the higher stimulation intensities for fewer pulses, as observed in Figure 3 .

Electroencephalogram waveforms of pain-related evoked potentials by a pulse-train electrical stimulation (frequency of 30 Hz and pulse width of 400 μs, n = 2). The peak detection corresponds to values over three times the standard deviation of prestimulus time.

Development of a Computational Synaptic Model

The electrical parameters of the synaptic model were found to coincide with the experimental data shown in Figure 3 . The least-squares error between the experimental and computational results was adopted.

The synaptic model considers the effect of the number of activated presynaptic neurons (estimated computationally by the multiscale model of Aδ-fibers in section “Multiscale Modeling of Aδ-Fibers”) and their afferent spike sequence (number of stimulating pulses). Both inputs were used to determine the activation of postsynaptic neurons using a synaptic model. The parameters of the synaptic model are as follows: synaptic weight (w), rise time (τr), and fall time (τf).

First, more fibers are activated at higher injection current as the region where activation occurred became larger (broader and deeper) from a biophysical perspective. The number of stimulated fibers was estimated using the multiscale Aδ-fiber model for different injection currents, considering a uniform fiber density (Ebenezer et al., 2007). Thereafter, the relationship between the number of fibers and injection current was obtained, as shown in Appendix A. Next, the synaptic weight was determined so that the estimated number of fibers activate the postsynaptic neuron under single-pulse stimulation condition (no synaptic effect condition). Second, the number of fibers (corresponding to the current amplitude of the IES) required to activate the postsynaptic neuron was computed for different numbers of train pulses. The required number of fibers to activate the postsynaptic neuron was used to determine the perception thresholds based on the relationship between the number of fibers and the injection current. Third, the parameters τr and τf were adjusted to fit the experimental thresholds for each number of pulses, as shown in Figure 3 . The fitted parameters of the synaptic model are presented in Table 3 .

TABLE 3

Estimated synaptic model parameters based on the measured results.

ParameterValue
Number of fibers at a single pulse71
Rise time constant (τr)4.0 ms
Fall time constant (τf)5.0 ms
Synapse weight (w)8.1 × 10 𠄳

The computational results for the perception threshold are shown in Figure 6 . The computed perception threshold corresponded to the injection current (IES) required to activate the postsynaptic neuron (that is, eliciting an action potential) using the integrated multiscale model of Aδ-fibers with the synaptic model with different numbers of stimulation pulses. A good match to the experimental results was obtained by changing the relatively small space parameter of the synaptic model. The mean error was 14 㯊.

Computed results of the effect of pulse number by pulse-train electrical stimulation (experimental mean value and standard deviation, n = 8).


Additional information

Specification

COMPONENT LIST
Oasis Pro – Serial Number
Stimulus cable with ear clips
Storage Bag
9-Volt Alkaline Battery
Oasis Pro Operator’s Manual

OPTIONAL ACCESSORIES
MET Kit
MET Probe Kit
tDCS Kit
DAVID Session Editor

Instructions

OPERATING INSTRUCTIONS (Excerpts)

QUICK START
Get comfortable CES and MET can run for up to 3 hours at a time. Sessions can be run while relaxing or during light activity such as reading, walking, listening to music or working at a computer. Connect power Insert a 9V battery. Follow the diagram inside the battery compartment. Connect the ear clips Remove any metal jewelry from your ears. Wet your earlobes with tap water, saliva or a tiny amount of conductive gel and attach the clips: black to left ear, red to right ear. Connect the ear clip cable to the CES jack ( ) on the side of the device. Turn on the Oasis Pro Push and hold until the power light comes on. The number LEDs will display the battery level before displaying the last session used. Select a session length Tap to select a session length (the top row of icons): 20 minutes, 45 minutes, or 3 hours. User Designed is empty by default. Select a session Tap the INT or to highlight a session number. The frequency of the highlighted session is displayed on the icons. Tap to start the session. The number will blink to confirm the selection. See the list of sessions for information (page 9). Adjust the intensity The Oasis Pro will check your connection (page 6). As soon as the graph clears, you can increase the intensity by tapping or holding INT . Adjust the intensity until the pulses can just barely be felt. Relax and enjoy The Oasis Pro will automatically shut off when the session completes.

SELECTING A SESSION
The Oasis Pro has four (4) standard session groups (20 minute , 45 minute , 3 hour , and user designed ). Each group offers eight (8) sessions. The session number is indicated by the lit number between the intensity and select controls. If no number is lit, then the group has no sessions programmed into it. Press and release the power button ( ) to switch between groups. The lit group icon will change. Press the INT or to highlight a session number. If no sessions are available in a group, no numbers will be lit. The frequency and mode icons associated with the session light up to indicate what frequency range and CES pulse type will be used. Press the select button ( ) to start the highlighted session. The session number will flash and the session will begin after a five (5) second delay.

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Experimental and Computational Results

Experiment Results of Aδ-Fibers for Pulse-Train Electrical Stimulation

The injection current threshold to generate pain perception via Aδ-fibers was experimentally obtained for pulse-train electrical stimulation at a fixed frequency (30 Hz). As shown in Figure 3A, the threshold decreased with an increase in the pulse number and converged after five consecutive pulses. The synaptic effect generated a reduction of the threshold by 2.3 times for multiple-pulse stimulation of five or more consecutive pulses to a single pulse. Higher variability was observed for a few pulses due to intrinsic skin morphology and needle depth variability in the experiments, which will be discussed below. Thus, the measured perception thresholds were normalized by the average of the thresholds from six to ten pulses (Figure 3B). The reaction time of the volunteers in Table 1 requires more time for a larger number of pulses.

Figure 3. (A) Experimental perception threshold variation with pulse number by a pulse-train electrical stimulation (mean value and standard deviation, n = 8), and (B) its normalization by the average of the thresholds from six to ten pulses (mean value and standard deviation).

Table 1. The reaction time of perception threshold at a different number of pulses and frequencies.

The dependence of the threshold was also investigated for frequency (10 Hz to 200 Hz), as shown in Figure 4A for six pulses. The mean value of the minimum threshold was found at 30 Hz (10 Hz and 80 Hz), which converged at a mean frequency of 120 Hz (80 Hz to 200 Hz). The threshold was reduced by up to 26% of the maximum value. To reduce the intrinsic variability in the experiments, the threshold was normalized by the mean value of the converged threshold, which was defined as the threshold at a frequency of 80 Hz to 200 Hz (Figure 4B). The normalized curve shows a clear tendency, confirming the bottom peak at 30 Hz. As shown in Table 1, the reaction time was slower at lower frequencies.

Figure 4. (A) Experimental perception threshold variation with frequency by a pulse-train electrical stimulation (mean value and standard deviation, n = 9), and (B) its normalization by the average of the thresholds between 80 Hz and 200 Hz (mean value and standard deviation) (Mean value and standard deviation).

Verification of Aδ-Fibers and Synaptic Effect by Evoked Potentials

We detected evoked potentials from Aδ-fiber stimulation using single-pulse stimulation. Table 2 shows the peak latency of pain-related evoked potentials that were not significantly affected by pulse width (330� ms). These reaction times were faster than those when the participant pressed the button under the same conditions in our previous study (470 ms to 520 ms) (Tanaka et al., 2021).

Table 2. Experimental threshold and peak latency of pain-related evoked potentials by single-pulse stimulation (mean value and standard deviation, n = 3).

We also verified synaptic effects using evoked potential measurements. Figure 5 shows the evoked potentials for different numbers of consecutive stimulation pulses. The stimulation amplitude was fixed for all conditions (perception threshold of eight pulses). We observed pain-related evoked potentials at eight and six pulses, but not for two or four pulses, which agrees with the higher stimulation intensities for fewer pulses, as observed in Figure 3.

Figure 5. Electroencephalogram waveforms of pain-related evoked potentials by a pulse-train electrical stimulation (frequency of 30 Hz and pulse width of 400 μs, n = 2). The peak detection corresponds to values over three times the standard deviation of prestimulus time.

Development of a Computational Synaptic Model

The electrical parameters of the synaptic model were found to coincide with the experimental data shown in Figure 3. The least-squares error between the experimental and computational results was adopted.

The synaptic model considers the effect of the number of activated presynaptic neurons (estimated computationally by the multiscale model of Aδ-fibers in section “Multiscale Modeling of Aδ-Fibers”) and their afferent spike sequence (number of stimulating pulses). Both inputs were used to determine the activation of postsynaptic neurons using a synaptic model. The parameters of the synaptic model are as follows: synaptic weight (w), rise time (τr), and fall time (τf).

First, more fibers are activated at higher injection current as the region where activation occurred became larger (broader and deeper) from a biophysical perspective. The number of stimulated fibers was estimated using the multiscale Aδ-fiber model for different injection currents, considering a uniform fiber density (Ebenezer et al., 2007). Thereafter, the relationship between the number of fibers and injection current was obtained, as shown in Appendix A. Next, the synaptic weight was determined so that the estimated number of fibers activate the postsynaptic neuron under single-pulse stimulation condition (no synaptic effect condition). Second, the number of fibers (corresponding to the current amplitude of the IES) required to activate the postsynaptic neuron was computed for different numbers of train pulses. The required number of fibers to activate the postsynaptic neuron was used to determine the perception thresholds based on the relationship between the number of fibers and the injection current. Third, the parameters τr and τf were adjusted to fit the experimental thresholds for each number of pulses, as shown in Figure 3. The fitted parameters of the synaptic model are presented in Table 3.

Table 3. Estimated synaptic model parameters based on the measured results.

The computational results for the perception threshold are shown in Figure 6. The computed perception threshold corresponded to the injection current (IES) required to activate the postsynaptic neuron (that is, eliciting an action potential) using the integrated multiscale model of Aδ-fibers with the synaptic model with different numbers of stimulation pulses. A good match to the experimental results was obtained by changing the relatively small space parameter of the synaptic model. The mean error was 14 㯊.

Figure 6. Computed results of the effect of pulse number by pulse-train electrical stimulation (experimental mean value and standard deviation, n = 8).


Transcranial Alternating Current Stimulation

While rarely discussed for TDCS, the problem of indirect brain stimulation is better recognized for TACS. It is known that alternating current stimulation of the retina induces the visual perception of phosphenes (Schutter, 2016). While TACS-induced phosphenes were initially thought to be solely caused by the stimulation of the primary visual cortex (Kanai, 2008), a row of studies has demonstrated that volume conduction in the head allows for direct retinal stimulation for a wide range of montages, even for those that are not targeting visual areas (Schwiedrzik, 2009 Schutter and Hortensius, 2010 Kar and Krekelberg, 2012). The direct activation of the retina through TACS is also suggested by electric field modeling demonstrating that, depending on montage, stimulation intensities as low as 500 㯊 may result in sufficiently strong electric fields in the retina (Laakso and Hirata, 2013).

Retinal phosphenes present a general problem for studies trying to link a brain function to the specific frequency of the TACS intervention in the presumed cortical target area. Experiments in the cat visual cortex have shown that pulsed visual stimulation, similar to TACS-induced phosphenes, can entrain neuronal assemblies in the visual cortex via the retino-thalamic pathway. Entrainment may not only be observable in the stimulated frequency but also in first- and second-order harmonics and throughout many areas of the visual system (Gray and McCormick, 1996). Also, human studies indicate that pulsating visual input can entrain EEG oscillations (Robinson, 1983) and that this effect is not confined to the early visual cortex. In fact, pulsed visual stimulation in the alpha, beta, and gamma frequency range has been shown to modulate excitability of the primary motor cortex (Strigaro etਊl., 2013) and also impacts cognitive performance: Williams and co-workers (Williams, 2001) demonstrated that words could be better remembered when they were preceded by a small flickering stimulus at 10.0 Hz. The effect was frequency specific as other frequencies (8 Hz, 11.7 Hz) did not induce this effect. This effect can even be observed for sub-consciously perceived pulsed visual stimulation and impacts cognitive performance in patients and healthy volunteers (Knez, 2014). Additionally, the effect of visual flickers scales with the distance of the flicker frequency to the individual alpha peak frequency (Gulbinaite etਊl., 2017), indicating that the behavioral effect of flickering light is indeed based on indirect entrainment of endogenous brain oscillations through the retino-thalamic pathway.

The fact that retinal phosphenes are perceived during TACS and not during TDCS is not due to differences in retinal current flow or field strength between the techniques but has a physiological origin. The ganglion cells of the retina form highly sensitive receptive fields as they are tuned to fire at either onset or offset of a stimulus. The accentuation of both beginning and end of a stimulus emphasizes stimuli that change over time, making the retina more susceptible to AC when compared with DC stimulation (Meister and Berry, 1999).

While indirect brain stimulations via afferent nerves can present a challenge for the demonstration of unambiguous structure𠄿unction relationships demonstrated with TACS and TDCS, there are several ways to minimize or control the expected contribution of indirect cortex stimulation. One option that has been shown to reduce sensory side effects of concomitant nerve stimulation is the use of more focal pseudo-monopolar montages (Heise etਊl., 2016), as their focality decreases the extent of extra-cortical tissue stimulation. The use of electric field modeling tools is also recommended as they allow the researcher to estimate the focality of their chosen montage. However, most existing head models do not include high-definition segmentations of extracranial tissue and are therefore not ideal in predicting the amount of extra-cortical stimulation. While focal montages may reduce sensory side effects, they do not mitigate the issue completely, and there may be stimulation locations where significant concurrent nerve stimulation is hard to avoid. Here, active control conditions are additionally needed to match the contribution of peripheral co-stimulation.

To reduce cutaneous stimulation directly under the electrode, several studies have suggested the application of a topical anesthetic (DaSilva etਊl., 2011 McFadden etਊl., 2011). This can successfully decrease the tingling and burning sensations associated with TES and can be recommended for better blinding but it should be borne in mind that topical anesthetics are not likely to decrease the amount of indirect brain stimulation via the non-cutaneous sensory routes discussed above.

The use of focal electrode montages informed by electrical field modeling could be combined to minimize peripheral co-stimulation. A recent study by Khatoun etਊl. (2018) compared the effectiveness of standard and focal TACS montages to entrain physiological tremor and elicit phosphenes. The standard bipolar montages used a peak amplitude of 1.9 mA and an extra-cephalic return electrode to target either the prefrontal cortex and M1, respectively, while the high-current focal stimulation employed a 4 ×ਁ montage at 4.5 mA centered over M1-HAND. They found that only the focal montage over M1 entrained physiological tremor without eliciting phosphenes. Both bipolar montages elicited phosphenes and entrained tremor, rendering it possible that the tremor may have been mediated via the phosphenes rather via a direct modulation of specific brain areas. Finally, an additional control experiment applying high-current focal stimulation to the occipital cortex failed to elicit phosphenes, suggesting that retinal stimulation was causing the phosphenes in the non-focal montages. Khatoun etਊl. (2018) used electric field modeling to visualize the focality of montages. The study by Khatoun etਊl. (2018) illustrates the inherent ambiguity when interpreting TES-related behavioral modulation using non-focal montages. The study also introduces strategies to minimize and estimate the impact of non-cortical stimulation.


DISCUSSION

Continuous TBS to the M1 increases GABA concentration when compared with control stimulation, without any significant effect on Glx levels. GABAergic activity therefore may be a mechanism by which long-lasting aftereffects of TBS on corticospinal excitability are generated. This is consistent with preclinical data suggesting the importance of the GABAergic mechanisms in LTD-like phenomena within the neocortex in freely moving animals (Hess et al. 1996 Komaki et al. 2007 Trepel and Racine 2000). More indirectly, it may be related to the decreases in local sensorimotor cortex GABA concentrations during successful motor learning in humans (Floyer-Lea et al. 2006).

GABA is produced in neurons by decarboxylation of glutamate by the enzyme glutamic acid decarboxylase (GAD65). The GAD65 isoform is associated with synaptic vesicles and is likely to be involved in synthesizing GABA for neurotransmission (Martin and Rimvall 1993 Martin et al. 1991a,b). In contrast, the GAD67 isoform is distributed more widely in the cytoplasm and is thought to be important in synthesizing GABA for cytosolic use. GAD is the rate-limiting step in production of GABA. In vitro, neuronal activity is associated with increases in the active isoform of GAD65 (de Graaf et al. 2003). In neural stem cell–derived cultures, depolarization of the neurons also leads to an increase in the active isoform of GAD65 (Gakhar-Koppole et al. 2008). Induction of synthesis thus likely enables enhanced GABAergic activity in vivo.

It is important to note that MRS is sensitive only to changes in the overall concentration of a neurotransmitter and cannot inform our understanding of changes within the receptors at the synapses. Specifically, the lack of a change in this measure of Glx does not contradict previous pharmacological studies that show abolition of the effects of cTBS after N-methyl- d -aspartate (NMDA)-receptor antagonism (Huang et al. 2007), but instead strongly suggests that these changes are due to changes in the NMDA receptors themselves.

The aftereffects of cTBS on motor cortex are commonly assessed from their effects on the amplitude of electromyographic responses (MEPs) evoked in a small intrinsic hand muscle by a standard single TMS pulse (Huang et al. 2005). At intensities commonly used for TBS, the effect of TMS is cortical and thus results from stimulation of either excitatory or inhibitory synaptic inputs to layer V pyramidal neurons (Di Lazzaro et al. 1998). A reduced MEP after cTBS therefore indicates either a reduction in the net efficiency of excitatory stimulation by the TMS pulse or an increase in intracortical inhibition.

Our results here—suggesting increased GABAergic inhibition contributes to the aftereffects of TBS—were unexpected. Previous work has shown that the effects of cTBS are abolished by administration of memantine at concentrations sufficient to antagonize NMDA function in the human brain (Huang et al. 2007 Teo et al. 2007). Thus it has usually been assumed that the aftereffects are due to an action on glutamatergic transmission, which leads to a reduction in cortical excitability via an LTD-like action on the excitatory synapses activated by the TMS test pulses.

Integration of the neuropharmacological results with the MRS data suggests a new hypothesis regarding cTBS action. cTBS is applied at a low intensity (80% AMT), which is below the threshold for activating the excitatory inputs to pyramidal neurons (Ziemann et al. 1996). The intensity is the same as that used in a common double-pulse paradigm to assess short-interval intracortical inhibition (SICI) in the motor cortex (Kujirai et al. 1993). To elicit SICI, two TMS pulses are applied through the same coil with the first pulse being subthreshold intensity (usually 80% AMT) and the second pulse large enough on its own to elicit an MEP. If the interval between the pulses is between 1 and 5 ms then the MEP is suppressed. Pharmacological studies suggest the effect is due to activation of the GABAA-ergic neurons by the first pulse (Di Lazzaro et al. 2000, 2008b Muller-Dahlhaus et al. 2008 Werhahn et al. 1999). Whether the GABAA neurons are activated directly by the TMS pulse or indirectly via an excitatory synaptic input is unclear there is some evidence that it may be the latter (Bestmann et al. 2003).

Whatever the precise mechanism, these data imply that cTBS (600 stimuli) at 80% AMT activates a population of cortical GABAA-ergic interneurons. The increase in GABAergic activity is then sustained by induction of GAD65 and subsequent increased GABA concentration within the cytoplasm of the GABAA-ergic interneuron.

However, this simple formulation does not account for the decrease in SICI (a TMS measure of relative GABAergic transmission) found with cTBS (Huang et al. 2005, 2008). To account for this, we propose an extension of this simple formulation into a mixed model in which effects are mediated by changes in both glutamatergic and GABAergic signaling within local excitation–inhibition networks (Logothetis 2008). The excitability of the cortical output neurons (as reflected by the MEP) is controlled by associative mechanisms of LTD, whereby both NMDA-receptor–dependent mechanisms and GABA input control excitability (Tsumoto 1992).

There is one more important aspect that may help to explain our present findings. LTD of GABAA synapses is predominantly presynaptic, being mediated through endocannabinoids (Tsumoto 1992). On the other hand, LTD at glutamatergic synapses is more likely to involve postsynaptic changes (Hess and Donoghue 1996). Previous work shows that cTBS reduces the effectiveness of excitatory inputs to MEP generators in motor cortex, as well as the effectiveness of the circuits mediating short-intracortical inhibition (SICI) (Huang et al. 2008). In both cases, cTBS is likely to provoke activity in GABAergic and glutamatergic circuits that may be followed by an increased synthesis of both transmitters. However, on termination of cTBS, presynaptic LTD at GABAergic neurons prevents further GABA release. This leads to increased presynaptic GABA levels that in turn increase the MRS signal. On the other hand, presynaptic release of glutamate is unchanged and no accumulation of glutamate should occur. Consequently, no changes in Glx should occur.

This explanation would make the previous pharmacological studies—suggesting that the aftereffects of cTBS are NMDA-receptor dependent (Huang et al. 2007)—consistent with the results from this study showing an increase in GABA activity. The reduction in SICI can be accounted for because this phasic test of relative GABAA activity in the paired-pulse paradigm would be less effective in the context of a baseline of increased, ongoing inhibition. Although this cannot be proved from these data, this model provides a framework for further testing in future experiments.

There are limitations to our experiment. The measure of total GABA within the voxel gives no information concerning subcellular localization and thus our interpretation can only be speculative. Because sensitivity did not allow a full relaxation time characterization, it remains possible that the increases in apparent concentration arise simply from redistribution of GABA from pools in which it is relatively immobilized, such as by association with MMs, and therefore MR “invisible” (Matthews et al. 1986). However, such large relaxation time changes with short-term changes in functional state would be unprecedented as far as we are aware. It is also possible that the result sreflect a change in the volume of the cells within the voxel. However, we have controlled for this by considering the GABA:NAA ratio rather than using GABA absolute quantification. In addition, there is no significant change in the creatine concentration after stimulation.

There are some questions raised by the current study that should be addressed in future investigations. First, due to the constraints of the technique we have acquired data only from the brain tissue in the stimulated sensorimotor cortex and therefore a future study is needed to clearly distinguish the local and more general effects of tDCS on neurotransmitter levels.

In addition, we are unable to determine the direct relationship between neurotransmitter changes as assessed by MRS and neurophysiological changes as assessed by TMS. However, at this point the experiments required to investigate this relationship remain technically challenging. Subjects were moved out of the scanner for stimulation and there was a delay of about 20 min between the end of stimulation and the start of MRS measurements, which then demanded a further 20 min. Shorter-lived neurochemical changes would not be able to be defined. However, the neurophysiological aftereffects of 600 pulses of cTBS, as applied in the present study, are relatively stable for ≤1 h (Huang et al. 2005, 2008), suggesting that the dynamics of the underlying neurochemical changes also occur over a similar period. In addition it would be of interest to investigate the effects of intermittent TBS in a similar study. There is evidence that iTBS and cTBS affect different intracortical circuits (Di Lazzaro et al. 2005, 2008a), so different effects might be expected.

A significant variability in the Glx measure was seen in both stimulation conditions. In our experience this is often seen in MRS studies and may represent an interaction between the resonance and the neighboring water peak. However, although this interaction would be expected to add variance to the signal, as seen here, no trend toward a significant change in Glx measures with cTBS was seen.

cTBS to the contralesional hemisphere is a promising tool for neurorehabilitation in chronic stroke. In many contexts, inhibitory stimulation to the unaffected hemisphere has led to more robust increases in cortical excitability and motor function on the affected side (Di Lazzaro et al. 2008b Fregni et al. 2005). TBS, in particular, is a stimulation technique that uses low intensities and is well tolerated in both healthy controls (Huang and Rothwell 2004) and stroke patients (Di Lazzaro et al. 2006 Talelli et al. 2007). This study adds direct evidence that TBS induces LTP- and LTD-like plasticity in the human motor cortex (Huang et al. 2005). It has allowed a more refined hypothesis regarding the mechanism of action that can be tested in future experiments. With a stronger neurophysiological rationale, it can be applied with greater confidence in therapeutic trials (Di Lazzaro et al. 2008a Fregni et al. 2005), taking advantage of its excellent tolerability (Di Lazzaro et al. 2006 Huang and Rothwell 2004 Talelli et al. 2007).


This article is based on a consensus conference, promoted and supported by the International Federation of Clinical Neurophysiology (IFCN), which took place in Siena (Italy) in October 2018. The meeting intended to update the ten-year-old safety guidelines for the application of transcranial magnetic stimulation (TMS) in research and clinical settings (Rossi et al., 2009). Therefore, only emerging and new issues are covered in detail, leaving still valid the 2009 recommendations regarding the description of conventional or patterned TMS protocols, the screening of subjects/patients, the need of neurophysiological monitoring for new protocols, the utilization of reference thresholds of stimulation, the managing of seizures and the list of minor side effects.

New issues discussed in detail from the meeting up to April 2020 are safety issues of recently developed stimulation devices and pulse configurations duties and responsibility of device makers novel scenarios of TMS applications such as in the neuroimaging context or imaging-guided and robot-guided TMS TMS interleaved with transcranial electrical stimulation safety during paired associative stimulation interventions and risks of using TMS to induce therapeutic seizures (magnetic seizure therapy).

An update on the possible induction of seizures, theoretically the most serious risk of TMS, is provided. It has become apparent that such a risk is low, even in patients taking drugs acting on the central nervous system, at least with the use of traditional stimulation parameters and focal coils for which large data sets are available. Finally, new operational guidelines are provided for safety in planning future trials based on traditional and patterned TMS protocols, as well as a summary of the minimal training requirements for operators, and a note on ethics of neuroenhancement.


The Comparison of the Effects of Different Transcranial Electrical Stimulation (tES) Paradigms on Beta-Amyloid (Aβ 25-35)-Induced Memory Impairment upon Morris Water Maze Task in Male Rats

Citation: Zarifkar AH, Zarifkar A, Nami M, Rafati A, Aligholi H, et al. (2018) The Comparison of the Effects of Different Transcranial Electrical Stimulation (tES) Paradigms on Beta-Amyloid (A&beta 25-35)-Induced Memory Impairment upon Morris Water Maze Task in Male Rats. J Neurol Neurosci Vol.9 No.4:265. doi: 10.21767/2171-6625.1000265

Abstract

Background: In light of therapeutic limitations in Alzheimer's disease (AD), recent alternative or add-on treatment approaches such as non-invasive brain stimulation through transcranial electrical stimulation (tES) have gained attention. Translational studies have postulated that transcranial direct current stimulation (tDCS) is potentially a novel therapeutic option to reverse or stablize cognitive impairments. The aim of this study was to comparatively evaluate the effects of the four main paradigms of tES, including tDCS, transcranial alternative current stimulation (tACS), transcranial random noise stimulation (tRNS), and transcranial pulse current stimulation (tPCS) on beta amyloid 25-35 (A&beta 25-35)-induced memory impairment in male rats submitted to the Morris water maze (MWM) task.

Method: To develop AD model in Sprague-Dawley male rats weighing 250-270, the cannula was implanted bilaterally into the hippocampi. A&beta 25-35 (5 &mug/2.5 ml/ day) was microinjected bilaterally for 4 days. Then, tES was applied to the animals for 6 days. Subsequently, rats&rsquo learning and memory function was evaluated on day 11-14 in MWM task.

Results: Our findings indicated that tDCS, tACS, tRNS reduced escape latency, while such an effect was not observed in tPCS paradigm. In terms of the duration of animals&rsquo presence in the platform quadrant, tDCS and tACS increased the outcome measure.

Conclusion: We conclude that tDCS and tACS are more effective than the other two examined paradigms of tES in ameliorating learning and memory impairments.

Keywords

Alzheimer's Disease Beta amyloid 25-35 Learning Memory Morris water maze tES

Introduction

Alzheimer's disease (AD) is a progressive disorder characterized by the loss of neurons and synapses, especially in the hippocampus, which eventually leads to forgetfulness. AD affects cognitive and behavioral functions as a result of synaptic dysfunction. The pathophysiology of Alzheimer's disease roots in the aging-dependent extracellular plaques of beta-amyloid peptides (A&beta) and intercellular neurofebrillary tangles (NFT), consisting of the hyperphosphorilation tau protein [1-3]. The treatment of AD subjects to limitations such as drug metabolism, side effects, or inadequate clinical response. As such, induction of neuroplastic changes by noninvasive techniques such as transcranial electrical stimulation (tES) has gained momentum over the past years [4]. The stimulation is done by applying direct current (DC) over the scalp using electrodes which are encapsulated by sponge embedded in saline or rubber electrodes with guiding gels [5]. This technique can induce long-term and polarityspecific changes in the excitability of the motor cortex in humans [6]. In the most common method, an electrode is placed on a specific area, while the other electrode is placed on another area to complete the flow circuit [7]. The position of the electrode is necessary to determine the orientation and spatial distribution of the current and finally the effectiveness of intervention [8]. This method is shown to provide valuable effects in the treatment of neuropsychiatric disorders such as depression, anxiety, chronic pain, Parkinson's disease and AD, as well as the course of rehabilitation in cognitive impairments [9]. The four main paradigms of tES are transcranial direct current stimulation (tDCS), transcranial alternative current stimulation (tACS), transcranial random noise stimulation (tRNS), and transcranial pulse current stimulation (tPCS).

tDCS which is the most widely practiced technique in neurotransmission modulation, depends on the activate electrode polarity to induce cortical excitability changes. The polarity-dependent mechanisms are known to cause: 1) membrane depolarization (increased spontaneous firing through anodal stimulation, or 2) membrane hyperpolarization (reducing spontaneous firing and irritability) with cathodal suppression [6].

TACS is another type of neuromodulation proposed to modify the excitability of the human cortex. This method is a balanced flow of alternating biphasic pulses through alternating electrical charges. Compared to tDCS tACS allows manipulation of cerebrospinal excitability not only on the basis of severity, but also the applied current frequency. Unlike tDCS, which has inhibitory effects due to polarity, the effects of tACS are determined by the current frequency and independent of the polarization of the electrodes [10].

TRNS is a special form of tACS. During tRNS, a low-frequency alternating current is applied, causing alterations in the intensity and frequency of the flow randomly. Stimulation is biphasic. Like tACS, various forms of noise can be applied based on the frequency range. In most studies, a spectrum of frequencies is used between 1 Hz to 640 Hz (full spectrum) or 101 to 640 Hz (high frequency stimulation). Indeed, 99% of the current generated by the noise stream is in the range of 1 mA [11].

In tPCS the direct current is discontinued and the two parameters i.e., plus duration (PD) and Inter-pulse interval (IPI) are added. Compared to anodal tDCS, anodal tPCS is a oneway flow of positive pulses separated by predetermined Interpulse intervals. Based on time duration, the range of pulses and IPIs, tPCS produces different degrees of net direct current components [12].

Of the four methods described, tDCS is the most studied with its mechanisms investigated. Clinical studies have shown that tDCS is a potential therapeutic tool. Many studies on the clinical applications of tDCS show that this method is effective in the treatment of many disorders, including those refractories to medication therapy, including post-stroke motor disorder [13], aphasia after stroke [14], epilepsy [15], chronic pain [16] and Parkinson's disease [17]. Several studies have also shown that the use of tDCS can improve memory in Alzheimer's patients [18,19].

In addition to the existing evidence on clinical benefits in disease conditions, using tDCS in healthy people can improve declarative memory and working memory, as well as other cognitive functions [20,21]. Nevertheless, the exact pathways involved in tDCS effects are not fully understood and further studies are needed for its routine clinical use. It is believed that the application of an electric field with sufficient strength and time causes a rapid increase in the electrical conductivity of cell membranes. This is due to an increase in permeability for small and large ions and molecules. However, knowledge about the effects of neurotransmission, neurochemical markers, neuronal pathways, or neuronal interactions is incomplete.

The mechanisms of action of tDCS in AD include altered neuronal activity, changes in blood flow to the brain, changes in osmotic activity of brain, changes in brain functional communication patterns, synaptic and non-synaptic effects, and neurotransmitter modulation [22]. Thus, tDCS might be potentially considered as a suitable add-on treatment for improving cognitive function in AD based on the pathophysiology of the disease.

Many studies have addressed the effects of tDCS in patients with AD [22]. The numbers of animal studies which are using this technique to explore the mechanisms of tDCS are increasing [23]. Yu Sh and colleagues revealed that tDCS application after the onset of cognitive dysfunction caused by AD leads to some positive effects on motor behavior [24].

A study in 2016 found that anodal tDCS had beneficial effects on behavioral and spatial memory in animal models of traumatic brain injury (TBI) [25]. Another recent study shows that anodal tDCS increases the long-term potentiation of the hippocampus and improves learning and memory functions [26]. More recently, Ronso et al. showed that tDCS with training improves cognition in anomic AD and frontotemporal dementia [27].

In a case study in 2016, application of tDCS as an adjuvant to the traditional treatment had a stabilizing effect on overall patient cognitive function and led to improved performance on all the secondary outcome measures [28]. Another study also postulated that the synergetic use of tDCS and cognitive training appeared to slow down the cognitive decline in AD [29]. Considering the impairing effects of A&beta on learning and memory and suggested neuroprotective effect of tES, this study was designed to comparatively evaluate the effects of different tES paradigms on learning and memory impairment induced by A&beta in Morris water maze and finally to determine which of the tES paradigms is (are) more effective in this regard.

Materials and Methods

Adult male Sprague-Dawely rats weighing 250&ndash270 g were usedAnimals were maintained at room temperature (25 ± 2°C) under standard 12&ndash12 h light&ndashdark cycle with lights on at 7:00 A.M. Food and water were available ad libitum. The experimental protocols were approved by the ethics committee of Shiraz University of Medical Sciences and the animal care was according to the NIH Guide for the care and use of laboratory animals (IR.SUMS.REC.1395.S974). Fifty six rats were randomly divided into the 7 groups (n=8 in each group) including the control group, the sham group, the A&beta group, the A&beta + anodal tDCS group, the A&beta + tACS group, the A&beta + tRNS group and the A&beta + tPCS group.

A&beta 25-35 was purchased from Sigma, USA and electrical stimulation device was purchased from Medina Teb Company, Iran. Ketamine and xylazine were provided by Alfasan Woerden Company, the Netherlands.

On the day of surgery, rats were anesthetized with intrapritoneal injection of mixed ketamine (100 mg/kg) and xylazine (10 mg/kg). The rats were mounted into a stereotaxic frame and according to Paxinos brain atlas, stainless steel guide cannula (22-gauge) were implanted bilaterally into the dorsal hippocampi (AP &minus 3.8, ML ± 2.2, DV &minus 2.7). To apply electrical stimulation, a plastic tube (inner diameter: 2 mm) was mounted on the right frontal cortex. The cannula and plastic tube were anchored to the skull using stainless screws and acrylic cement.

A&beta 25-35 preparation

A&beta peptide (25-35) was dissolved in sterile distilled water at a concentration of 2 &mug/&mul and was stored in &minus70°C. Aggregation of A&beta 25-35 was done by in-vitro incubation at 37°C for 4 days [30].

Drug administration

In order to inject the drug, a 10 &mul Hamilton syringe was connected to the injection cannula through a short piece of polyethylene tube, the injection cannula was inserted 0.5mm below the tip of guide cannula. A&beta 25-35 (5 &mug/2.5 ml/day) or its vehicle (distilled water) was injected bilaterally on days 1 to 4. All microinjections were carried out at the speed of 1 ml/min and the needle was left in the place for additional 5 min to minimize the back-flow of the solution.

Induction of electrical stimulation

The plastic tube which was placed on the skull surface on surgery day, was filled with sponge and saline. Rats were covered with a towel and the electrodes were inserted. The anodal electrode was placed into the plastic tube above the right frontal cortex. The cathodal electrode, with a larger contact area, was placed onto the ventral thorax with a corset. To reduce the contact impedance, sponges were moistened with saline solution prior to electrical stimulation.

TES were applied to the awake and freely moving rats for one week, 20 min per session, with current intensities of 200 &muA, the current intensity was ramped for 10 s. Sham stimulation (electrodes were placed, but no stimulation was applied) was performed in the sham and the A&beta groups.

Ten days after surgery (day 11), behavioral assessment using the Morris water maze (MWM) task was carried out.

Behavioral testing

Morris water maze apparatus: The water maze has been explained previously [31]. It was a black circular pool with a diameter of 140 cm and a height of 70 cm, filled with 20°C water to a depth of 25cm. The maze was divided into four equal quadrants and release points that were designed at each quadrant as N, E, S, and W. A hidden circular platform (11cm in diameter), was positioned in the center of the southwest quadrant, submerged 1.5 cm beneath the surface of the water. Fixed, extra maze visual cues were present at various locations around the maze (i.e., Computer, a door, a window, bookshelves, posters). A charged coupled device (CCD) camera was mounted above the center of the maze so that the animal motion could be recorded and sent to the computer. The path of animal's swimming was automatically recorded by a computerized system (Noldus EthoVision, v13) (Noldus Company, The Netherlands) and then analyzed by calculating several parameters, e.g. latency to find the platform as well as the swimming speed.

Procedure: The rats were trained in a protocol containing of 4 days training session. During the first three days a hidden platform, submerged about 1.5cm below water surface was put in the center of south- west quadrant. The platform location was fixed during those 3 days. A block session consisted off our trials with four different starting points. Each rat was placed in the water facing the wall of the tank at one of the four designated starting points (north, east, South and West) and allowed to swim and find the hidden platform.

During each trial, the rat was given 90s opportunity to find the hidden platform. After mounting the platform, the animals were allowed to stay there for 20s until the next trial. Was started. After end of the training, the animal was dried by a towel and returned to its home cage. On day 4, the hidden platform was removed and the retention testing (probe trial) was performed. The probe trial consisted of a 60s free-swim period without a platform and the time spent in the target quadrant was recorded. After probe trial a visible platformcovered by a piece of aluminum foil and not being submerged in water-was placed in another position (the South-East quadrant) to test the rat&rsquos motivation, visual ability and sensorimotor coordination.

Data analysis

All behavioral tests and decoding were performed blind. All statistical tests were undertaken using IBM SPSS statistics v22.0. Data were analyzed by repeated measure and one-way analysis of variance (ANOVA) followed by post hoc test for multiple comparison. All results have been shown as means ± Standard Error of Mean (S.E.M). In all statistical comparisons, p<0.05 is considered as significant difference.

Results

The effects of vehicle A&beta or (and) anodal tDCS tACS tRNS tPCS on water maze spatial learning and memory is represented in Figure 1. Figures 1A and 1B show animals&rsquo learning ability during 3 consecutive days of training.

Figure 1A The effect of saline, A&beta25-35 or (and) tDCS tACS tRNS tPCS on escape latency. A) The learning patterns of the animals treated by saline, A&beta25-35 or (and) tDCS tACS tRNS tPCS during training sessions.

Figure 1B The escape latency to the hidden platform during days 1&ndash3 of training. Data are represented as mean ± SEM. *p<0.05 and **p<0.01 represent the difference between A&beta25-35 and control group. ##p<0.01and ###p<0.001 represents the difference between animals which receive A&beta25-35 and saline and A&beta25-35 + tDCS tACS tRNS (n=8).

Figure 1A shows the escape latency to reach the hidden platform. This figure demonstrates a negative linear correlation between the escape latency and training days across groups, indicating that all groups have learnt the platform location. Moreover, the repeated measure analysis showed a significant difference of escape latency between groups (p<0.001). Post-hoc Tukey's test following repeated measure analysis, revealed that escape latency in A&beta receiving group is significantly greater than vehicle receiving group (P value<0.001).

Treatment with tDCS tACS and tRNS (p<0.005) reversed A&beta- induced impairment. Treatment with tPCS did not reverse A&beta- induced impairment. To compare how rats, behave in different days of the training, one-way ANOVA was used, and its results showed significant difference between groups in all days (day 1: p value=0.002, F (8,55)=4.331 day 2: p value<0.001, F (8,55)=8.280 day 3: p value<0.001, F (8, 55)=7.945).

Figure 2 shows the effects of vehicle or (and) tDCS tACS tRNS tPCS beta amyloid or (and) tDCS tACS tRNS tPCS administration on mean swimming velocity during days of training. One-way ANOVA of swimming speed did not show significant differences between groups (P value=0.975, F (8, 55)=0.312), which means that the animal's performance is not affected by the swimming speed.

Figure 2: The effect of vehicle, A&beta25-35 or (and) tDCS tACS tRNS tPCS on mean swimming velocity (n=8). Swimming velocity did not show significant difference between groups. Data are represented as mean ± S.E.M (n=8).

Figures 3 and 4 shows animals' performance in probe trial test. Figure 3 shows the frequency of animals&rsquo entrance into platform and its proximity. One-way ANOVA revealed a significant difference between groups (P value=0.003, F (8, 55) =4.184).

Figure 3: Animals frequency of entrance into the platform and its proximity. This figure shows that A&beta25-35 treatment decreases animals entrance into platform or its proximity area while tDCS and tPCS restored this disturbance. **p<0.01 represents the difference between sham and A&beta25-35 groups. #p<0.05 represents the difference between A&beta25-35 and A&beta25-35 + tDCS and A&beta25-35 + tPCS groups. Data are represented as mean ± S.E.M (n=8).

Figure 4: The time spent in the platform area and its proximity. These data reveal that A&beta25-35 deteriorated animals memory there is a significant difference between A&beta25-35 and A&beta25-35 + tDCS and A&beta25-35 + tACS and control group. *p<0.01 represents the difference between control and A&beta25-35 groups. #p<0.05 represents the difference between control and A&beta25-35 and A&beta25-35 + tDCS and A&beta25-35 + tACS groups. Data are represented as mean ± S.E.M (n=8).

Post-hoc Tukey's test showed that the frequency of entry into the platform area and its proximity is significantly decreased in A&beta-treated group, while tDCS and tPCS treatment reversed that memory impairment. Treatment with tACS and tRNS did not show any significant difference as compared to the A&beta-treated group.

Figure 4 shows the time spent in the platform area and its proximity. One-way ANOVA revealed a significant difference between groups (P value<0.001, F (8, 55) =6.656). Post-hoc Tukey's test showed that the time spent in the platform area and its proximity is significantly decreased in A&beta-treated group, while tDCS and tACS treatment reversed that memory impairment. Treatment with tRNS and tPCS did not show any significant difference as compared to the A&beta treated group.

The effects of vehicle or (and) tDCS tACS tRNS tPCS A&beta or (and) tDCS tACS tRNS tPCS on animals&rsquo performance in visible platform test is depicted in Figure 5.

Figure 5 The effect of vehicle, A&beta25-35 or (and) tDCS tACS tRNS tPCS on escape latency to the visible platform during fourth day of training. There is no significant difference between groups. Data are represented as mean ± S.E.M (n=8).

The escape latency to reach the visible platform is shown in this Figure 5. One-way ANOVA test on the escape latency to the visible platform did not show significant differences between groups (P value=0.724, F (8, 55)= 0.605). This finding suggests that A&beta did not affect animals' motivation or sensorimotor coordination.

Discussion

Our findings revealed that different paradigms of tES prevented A&beta-induced memory deficit in MWM task. The A&beta- treated rats had longer escape latencies to reach the hidden platform while tES paradigms prevented such a disturbance. MWM is widely used to study the cognitive deficits in the rodent model of AD [32]. In a study conducted in 2014, it was shown that injection of A&beta 25-35 into the hippocampus caused memory impairment in MWM task [30], which was in agreement to our findings. Since MWM is a behavior test that depends on the hippocampus In the previous study, it has been shown that the anodal tDCS enhances long term potentiation in the mouse hippocampus and improves memory, spatial learning and the performance of the animals in the MWM task [26].

Previous studies showed that the path of current-flow between the electrodes penetrates not only the cortex but also sub-cortical structures including the hippocampus [33]. In earlier reports, tDCS was shown to affect the brain cortex below the stimulation electrode [34]. The neurophysiological, behavioral and molecular changes investigated in previous investigations were all related to the hippocampal function [35,36]. Indeed, the anodal tDCS enhanced LTP at hippocampal CA3-CA1 synapses and improved the spatial and recognition memory assessed by two validated behavioral tests of the hippocampus-dependent memory tasks, i.e., morris water maze and novel objective recognition test [37].

In our investigation, among the four paradigms studied tDCS, tACS, tRNS reduced escape latency, while such an effect was not observed in the tPCS method. In terms of the duration of the presence in the platform quadrant, tDCS and tACS increased measure. Since the swimming speeds of all groups were not statistically different, it could be concluded that tES paradigms prevented the A&beta-induced memory deterioration. The finding that A&beta did not influence the visible platform task measures proposes that the impairing effect seen was not related to its effect on animals' visual-motor or motivation.

Results from other existing behavioral and histological reports indicate that the proposed repetitive anodal tDCS treatment can protect spatial learning and memory dysfunction of A&beta 1&ndash40-lesioned AD rats [38]. Our findings confirmed the results of the previous studies, with the difference that in this study, six sessions of electrical stimulation were carried out. Additionally, tDCS tACS and tRNS intervention ameliorated the animals&rsquo behavior. Unlike tDCS, the other three stimulus patterns had not been much studied earlier while the current study examined the effect of the three other stimulation paradigms on spatial memory.

Earlier studies have shown that tACS can modulate cortical excitability, Electroencephalography (EEG) oscillations and cognitive processes [39-41]. In addition, it has been shown that tACS can modulate brain oscillations and affect the cognitive functions [42,43]. It is also said that cognitive functions change with a selective intervention in brain oscillations [44]. In the present research, the effect of this paradigm on spatial memory was determined. Abnormal brain rhythms are associated with pathological conditions and such rhythms vary in AD patients [45]. As such research is trying to unveil the effects of brain rhythm modulations through tACS paradigm on neurobehavioral outcomes in disease conditions such as AD [45].

The prevailing hypothesis about the action of tACS is that alternating fields can increase or decrease the power of oscillatory rhythms in the brain, and in a frequency-dependent manner, through synchronizing and desynchronizing neuronal networks [10]. This study could at least partly document the positive effects of tACS in that respect.

Previous studies have shown that transcranial high frequency tRNS increases the brain excitability [46,47]. In a study by Paul Mulquiney et al., it has been shown that tRNS can improve working memory performance [48]. Likewise, our study revealed the effect of tRNS on the improvement of the performance of memory-impaired rats in training session of MWM task.

On the other hand, previous reports have indicated that anodal tPCS, with a specific pulse duration, has significant effects on cortical excitability compared to tDCS in healthy people [12]. Meanwhile, in our study, tPCS in comparison with the other three paradigms, had no significant effects on the escape latency and the time spent in the platform area. This might have been due to the number of stimulation sessions or the power of the electrical current to reach the underneath structures or perhaps due to the type of disorder or behavioral test studied. Nevertheless, tPCS had a significant impact on the entrance frequency to the platform quadrant. Regarding the number of sessions, the results of our study showed that tDCS, tACS and tRNS paradigms had better effects in different stages of MWM task.

Conclusion

Based on our findings and those of the previous studies, the effect of tDCS on the improvement of A&beta-induced memory impairment in MWM task appears to be well supported. Additionally, the current investigation proposed that other stimulation paradigms may retain efficiency in remediating cognitive impairments in a rodent model of AD. Overall, the results of this study showed that the use of multiple sessions of different paradigms of tES can reverse the memory impairment induced by A&beta in a rat model that tDCS and tACS had better effects on animal behavior in morris water maze task.

Therefore, based on such evidence, it could be expected that in addition to tDCS application in the treatment of AD, other stimulation paradigms may be considered as add-on neuromodulation strategies in AD. More research is of course required to postulate such an impact in clinical settings.

Acknowledgement

This work was derived from the PhD thesis of Amir Hossein Zarifkar and supported by a grant (number 12527) from Shiraz University of Medical Sciences.