Transcranial Alternating Current for Oscillopathies

tDCS has been applied to a spectrum of diseases, including depression, Parkinson's disease (PD), dementia and others, on the basis of the concept of dysfunctional brain areas: modulating the hypo-or hyper-function of the indicated brain regions via anodal or cathodal tDCS has shown evidence of clinical symptom improvement, although generally short lasting and often with discordant results among studies. Conversely, tACS has only rarely been applied to people with disease, with discordant results. Its application to healthy individuals to boost sleep and sleep-related memory formation and working memory has, however, been shown to be effective. If consensus on stimulation patterns (continuous vs. alternating) is, however, lacking, the same holds true for frequencies, although evidence from computational and animal studies demonstrates that tACS is very effective at entraining the network at the frequency of the applied stimulation, with theta noticeably efficacious at improving cognitive performances in memory tasks.

Whether a different paradigm, tailored to specific neurophysiological signatures, and not to the phenotype of the underlying dysfunction (i.e. applying inhibitory tDCS on the hyperfunctioning cortical area of a given disease or vice-versa), could lead to better and long-lasting clinical results is not yet defined.

Therefore, this proposed study has two fundamental questions: 1) is a re-categorization of pathologies based on their oscillatory activities and related scalp distribution. Indeed, the answer the investigators are seeking is whether the investigators could identify clear neurophysiological markers that could lead to a new diagnostic classification. From a translational perspective the question is: 2) could these markers eventually guide therapeutic options? If these points are proved, the investigators expect to expand the results to other oscillopathies (i.e. schizophrenia or insomnia).

The objective of this project is thus two-staged: a first stage will define neurophysiologic markers of diverse diseases, overcoming the traditional symptom-based classification of pathologies. In the second stage, these features will be translated into a tailored non-invasive brain stimulation (NIBS) protocol. Indeed, focusing on oscillatory rhythms dysfunctions, tACS, that entrains specific EEG frequencies, instead of tDCS, that hypo-hyperpolarizes indiscriminately vast brain regions, will be applied.

In the first stage, selected pathologies among the broader spectrum of thalamo-cortical-dysrhythmias (TCDs) will be categorized on the basis of their prevalent EEG rhythm; in addition, oscillatory brain response to external perturbation (frequency bands synchronization or desynchronization in response to TMS stimulation as defined by EEG-TMS co-registration) will be obtained. The identified EEG frequency will subsequently be extracted from EEG to visualize scalp defective areas. The investigators will identify:

• the prevailing EEG rhythm in a resting, standard EEG by means of power spectral analysis, based on Fourier transform;
• a more detailed insight into brain reactivity and its oscillatory response as a reaction to random, non-entraining TMS stimulation with EEG co-registration, a method that appears to elicit state-dependent brain oscillatory response; Pathologies presenting with analogous neurophysiological signatures will be grouped together in order to define an appropriate, common stimulation paradigm, independently of symptom phenotype.

In the second stage the investigators will attempt to tailor tACS on the basis of the previously defined categories. The scalp area of the dysfunctional rhythm will aid in the selection of the stimulation site, whereas the stimulation paradigm will be established on the basis of the prevailing EEG bands at rest and after perturbation - i.e. transcranial stimulation will be low frequency (4 Hz) alternating (tACS) for diseases characterized by a pathological increase of fast rhythms, and vice-versa (30 Hz), in order to entrain the defective EEG band. A clear-cut, long-lasting improvement of clinical symptoms is expected.

Our expected result is to be able to set up appropriate and effective tACS stimulation paradigms based on disease neurophysiological markers rather than on clinical symptoms. Given the large number of pathologies encompassed in the TCD spectrum, this therapeutic option could become a promising non-invasive, cost-effective therapeutic option with a wide field of applications.

Pathologies to be included are:

• PD: altered thalamo-cortical loop that reflects, through the thalamus, the beta prevalence in the deep nuclei loop and reverberates to the cortex.
• Neuropathic pain (NP): evidence of increased high theta band power (7-8Hz), especially over frontal and somatosensory cortex. The generation of low-frequency activity by the thalamocortical circuit results in a long-term pathological equilibrium in the cortical pain matrix. 2 - Methods

2.1. Pre- (T0), post-stimulation (T1) and 4weeks follow-up (T2) clinical assessment

• PD: UPDRS III, Dynamic Gait Index
• NP: Neuropathic Pain Questionnaire (NPQ), VAS for pain, Short Form 36-item Health Survey (SF-36) Possible therapy modification dictated by the individual's clinical status will be recorded.

2.2. T0, T1 and T2 neuropsychological assessment All patient groups will undergo the following neuropsychological tests battery. Anxiety state and trait will be measured and BDI administered.

• Montreal Cognitive Assessment (MoCA)
• State-Trait Anxiety Inventory (STAY) Y1 e Y2
• Beck Depression Inventory (BDI) II
• Rey Auditory Verbal Learning Test
• Rey-Osterrieth Complex Figure Test version I and III
• Modified Taylor Test
• Geriatric depression scale (short form)
• Cifrario
• Phonemic fluency test
• Edinburgh handedness Test
• Short-form Intelligence Test (TIB)
• Hopkins Verbal learning test revised (HVLTR)
• Trail making test

2.3. Signal analysis T0, T1 and T2 resting EEG analysis. EEG will be acquired using an TMS compatible EEG amplifier (BrainAmp 32MRplus, BrainProducts GmbH, Munich, Germany) and a cap providing 30 Ag/AgCl electrodes positioned according to a 10/20 system. Data will be processed in Matlab (MathWorks, Natick, MA) using scripts based on EEGLAB (http://www.sccn.ucsd.edu/eeglab), as well as a dedicated home-made code created for this study. Visible artifacts in the EEG will be removed using an independent component analysis procedure and EEG will be band-pass filtered from 1 to 30 Hz. EEG data will be divided into epochs of 2 s and a fast Fourier transform (FFT) will be applied to non-overlapping epochs, and averaged across epochs. Based on power spectra density, relative powers (%) in delta (1-4 Hz), theta (4-7Hz), alpha (8-12 Hz), and beta (13-30 Hz) frequency ranges will be evaluated.

A one sample z-test will be applied to compare the map of the patient to the grand average of the controls (a group of 20 healthy subjects). Thus, the statistical map defines the sensors in which relative power from an individual patient differs statistically from that of a reference population (control group).

Pre-stimulation (T0) EEG-TMS co-registration TMS will be performed using a Dymeg in biphasic pulse configuration (DuoMag, EMS, Italy) which generates a maximum magnetic field of 1.5 T. TMS will be delivered through a figure-of-eight focal coil over the dominant primary motor area (M1). Motor evoked potentials (MEPs) will be recorded from the left/right thenar eminence muscle with Ag/AgCl surface electrodes fixed to the skin with a belly-tendon montage. Stimulus intensity will be set at 110% of motor threshold intensity. 100 TMS single-pulse stimuli will be delivered at random, with inter-trial interval between 8-15 s.

EEG will be acquired using the same magnetic resonance compatible EEG system previously described. EEG data will be analysed using a time-frequency procedure to characterize TMS-induced oscillations. Time-frequency analysis will be performed with continuous Morlet wavelet transform, which provides a time course after magnetic stimulation of the relative power in the main frequency bands, as described above. Profiles for each subject will be averaged from the post-stimulus trials and normalized to the baseline value.

2.4. TADCS stimulation paradigm Stimulation will be applied by a battery driven external stimulator (BrainStim, EMS, Bologna, Italy) via two sponge electrodes (5x7cm). The anodal electrode will be placed over the scalp area corresponding to the defective network node as derived by EEG source analysis. The cathodal electrode will be placed over the ipsilateral mastoid. A sinusoidal current, ranging from 1 to 2mA will be delivered; stimulation frequency will be derived from the defective EEG band - i.e. if low frequency oscillations prevail, stimulation will be at 30 Hz; if high frequency oscillations prevail, stimulation will be at 4 Hz. Sham stimulation, according to consensus statement, will be delivered as random noise stimulation (RNS) with electrodes located at the same sites as active stimulation and Sham Sessions will last 30 minutes, and repeated for two weeks on 5 consecutive days per week separated by a 2 days interval. A random Noise Stimulation (RNS) with an amplitude 1 to 2 mA will be applied.

2.5. Ethical Committee Approval The study involves stimulation of human subjects and as such will require Ethical approval. The investigators obtained Ethical Approval from the Ethics Committee of the University Hospital, Padova (3507/15).

2.6. Statistical analysis and study power Data will be summarized using descriptive statistics. Appropriated 95% confidence intervals (CIs) for each outcome will be produced.

2.6.1. First phase The proportion of people with PD displaying EEG beta peak (FFT) and the 95% binomial CI will be computed. The same analysis will be performed for people with NP displaying EEG theta peak (FFT).

2.6.2. Second phase 2.6.2.1. Primary analyses A repeated measures test (ANCOVA) will be used to evaluate differences in UPDRS score and NPQ score between T0 and T1.

2.6.2.2. Secondary analyses Cross sectional evaluation at pre- and post-treatment between PD with beta Peak and PD with other EEG peaks will be run using the independent sample t test. Same analysis will be performed to evaluate differences at T0 and T1 between NP subjects with theta Peak vs NP with other EEG peaks.

Further analyses could be performed using analysis of variance (ANOCOVA) to account for these predictors: age, sex, disease severity at T0, interaction with other frequency bands, pre- and post-stimulation therapy after real and active sham tACS modification, drugs. Repeated measures models could be used.

2.6.3. Signal analysis

Analysis of variance (ANOVA) for repeated measures will be applied to the relative power with the factor ''time'' (T0, T1 and T2); the sphericity assumption will be assessed using Mauchly's test. Greenhouse-Geisser epsilon adjustments for non-sphericity will be applied where appropriate. A post hoc paired sample two tailed t-test adjusted for multiple comparisons with the Bonferroni method will be used. Statistical significance will be set at p < 0.05, corrected. Two-dimensional grand mean t-maps of the relative power will be computed from the t-values to check the topographical distribution of the significance.

2.6.4. Study power To compute the total sample size of the project the investigators will first compute the sample size for phase II. Given sample size for phase II, sample size for phase I will be computed accounting for potential drop-outs.

Phase II sample size Two different populations will be investigated (PD, NP) hence no correction for multiplicity will be performed.

People with PD and NP A sample size of 15 achieves 92% power to detect a mean of paired differences (UPDRS pre- and post-stimulation score difference) of 4.0 with an estimated standard deviation of differences of 4.3 and with significance level (alpha) of 0.05 using a two-sided paired t-test in people with PD displaying EEG beta (FFT). The same assumption will be assumed for NPQ decrease, hence a total of 30 subjects will be required, 15 for each category.

Phase I sample size The investigators expect all people with PD to have a beta frequency peak, while those with NP will be in the theta band. A sample size of 15 people with NP produces a one sided 97.5 binomial CI of 79.61%-100% given that the expected proportion of theta is 100%. A sample size of 15 people with PD produces a one sided 97.5 binomial CI of 79.61%-100% given that the expected proportion of beta is 100%.

Total sample size In order to account for potential drop outs the investigators will recruit 20 people with NP and 20 people with PD, giving a total sample size of 40 patients.