Combining tCS and EEG Y P O C T O N O D Davide Cappon, PhD - PowerPoint PPT Presentation

Combining tCS and EEG Y P O C T O N O D Davide Cappon, PhD E S - Berenson-Allen Center for Non-invasive Brain Stimulation, Department of Cognitive Neurology | Beth Israel Deaconess Medical Center | Harvard Medical School | Boston, MA, USA A E dcappon@bidmc.harvard.edu L P Boston, 23 rd June 2019

Y P O axies that can be seen today make up ju C T O N O D E S A E L P NASA

Observable Universe Y P O C T O N O D E S A E L P

Observable Universe Planet Earth Y P O C T O N O D E S A E L P

Outline Y Measuring tCS effects with EEG • P O ➢ Measuring effects outside the motor cortex C ➢ Measuring focality of tCS interventions T O N Basics of EEG • O ➢ EEG signal: features and opportunities D ➢ Analysis (ERP,Power, ...) E S ➢ Experimental example of EEG-tCS combination A E L Beyond EEG • P ➢ TMS-EEG recording

Corticospinal excitability as an index of Brain excitability Y Applied to tCS: limitation for online recording, only after effects P O C T O N O D E S A E L P

Measuring tCS effects without EEG Y P O C T O N O D E S A E L P First evidence of tDCS after effect from Nitsche and Paulus, 2000 Changes in cortical excitability assessed using TMS-EMG

tDCS effect on corticospinal excitability:Online and Offline effects Santarnecchi et al., 2014 Y P O C T O N O D E S A E L P

tDCS Effects on the motor cortex: pre/during/post Y P PRE ONLINE POST (30’) O Anodal and Cathodal (15’) (15’) C tDCS modulate (increase/decrease T excitability) right after O the stimulation respect N to Sham. O No significant effects D During the stimulation. E S Still limited to A E the motor L cortex! P

Are we stimulating the motor cortex? Kuo et al., 2013 Y P O C T O N O D E S A Montage, Timing, Stimulation site, E L Duration, Intensity, etc. suggest a P complex scenario underlying tCS HD-tDCS effects TMS-EMG is not enough

Multifactorial model Y P O Brain state C Behavioural scores (electrophysiological T recording - EEG) O N Electrophysiological Individual trait ? O …Brain… responses – (personality, cognitive D EEG/ERPs/etc.. profile) E Behavioural performance Genetics S Neuroimaging ($$$) (e.g. BDNF) Physiological measurements (EKG, A EDR,..) E Neuroimaging ($$$) EEG/ERPs/??? L fMRI? P BEFORE DURING AFTER

Targeting Optimization Y P O C T O N O D E S A E L P

Open questions.. Y • the effect of tCS on Non-Motor regions? P O C • distant effects and changes in the interplay between regions T (connectivity)  Network effects? O N O D E S • the Online effects of tCS on brain activity other than A “excitability”? E L P Useful information to define tCS parameters and increase efficacy of interventions

Electroencephalography Y P 1875 : Richard Caton (1842-1926) measured currents in between the cortical O surface and the skull, in dogs and monkeys C T O 1929 : Hans Berger (1873-1941) first EEG in humans (his young son), description of N alpha and beta waves O D E S A E L P 1950s. Grey Walter ( 1910 – 1977). Invention of topographic EEG maps.

Electroencephalography Where does the signal come from? Y P • Signals stem from synchronous activity of large (~1000s) O groups of neurons close to each other and exhibiting similar C patterns of activity T • Most of the signal generated by pyramidal neurons in the O cortex (parallel to each other, oriented perpendicular to the surface) N O • EEG measures synaptic currents , not action potentials (currents flow in opposite directions and cancel out!) D E S A E L P

Electroencephalography Primary intracellular currents give rise to volume Y currents and a magnetic field P O Magnetic field C MEG pick-up coils Current T Electrical potential O difference (EEG) N scalp O Magnetic field D skull E S cortex A Volume E currents L P Volume currents yield potential differences on the scalp that can be measured by EEG

Pros and cons of EEG Y P O C T O N O D E S A E L P

Y P O C T O N EEG recording and analysis O D E S A E L P

EEG recording • International 10-20 system Y High-Density EEG • Left side: odd numbers P (64-256 Channels) • Right side: even numbers O C • Numbers increase from the hemispheric line towards the edges. Letter indicates brain regions (lobes). T O N O D E S A E L P

EEG recording Y • EEG records potential differences at the scalp using a set of P active electrodes and a reference O • The ground electrode is important to eliminate noise from the C amplifier circuit T • Potential differences are then amplified O N O D • The representation of the EEG channels is referred to as a montage E – Unipolar/Referential ⇒ potential S difference between electrode and A E designated reference L – Bipolar ⇒ represents difference P between adjacent electrodes (e.g. ECG, EOG)

EEG recording Y 1. SPONTANEOUS P O • Meaningful data with ~5’ of recording C • Eyes open/closed T O 2. EVOKED N O D E S A E L P

EEG analysis From ERPs to Waveform Y P Time domain: O -> when do things (amplitudes) happen? C TIME T O N O Frequency domain (spectral): D -> magnitudes and frequencies of waves- no time information. E S A E L P Time-frequency (wavelet analysis): -> when do which frequencies occur?

EEG features Y P O C T O N O D E S A E L P fMRI

Time domain Analysis Y Event Relate Potentials Advantages: computationally simple P ERPs O C Example of auditory evoked potentials T O N O D E S A E L P

Frequency Domain Analysis (EEG) How to disentangle oscillations Y Jean Joseph Fourier (1768–1830): P O “ An arbitrary function, continuous or with discontinuities, de C ned in a finite interval by an arbitrarily capricious graph can always be expressed as a sum of sinusoids”. T O N O D E S A E L P

Time- Frequency Domain Analysis (EEG) Y P O C T O N O D E S A E L P

Connectivity Analysis (EEG) Connectivity based on… Y P O .Phase (eg. phase-slope index) C .Power (eg. coherence) T O .Cross-frequency coupling N O D E S A E L P

Connectivity Analysis (EEG) two bars approached, briefly Hipp et al., 2013 overlapped while a click sound was played, and moved apart ambiguous audiovisual stimulus: from each other Y P O C T O N O D E S A E L P

Connectivity Analysis (EEG) Y Cohen et al., 2013 P O C T O N O D E S A E L P

Advantages of tCS + EEG Y • Understanding the role of brain oscillations in both motor and non- P motor regions , in both the healthy and pathological brain O C T O • Measure both local and distant effects. N O D E S • Guide tCS intervention on the basis of and online/offline monitoring A of brain states. E L P How can tCS + EEG be implemented?

tCS + EEG approaches Y P tCS Resting or Resting or O OFFLINE Event related Event related (no EEG C EEG EEG recording) T O N ? EEG Resting or Resting or O ONLINE recording Event related Event related D EEG EEG during tCS E S A E ? L EEG-Guided, tCS guided by Resting or Resting or P closed-loop Event related Event related EEG EEG system EEG recording

tCS and EEG: variables Y P O C T O N O D E S A E L P

EEG-Guided tCS: Location Faria et al., 2012 Y P O C EEG evaluation of a patient with T Continuous spike-wave discharges O during slow-wave sleep allowed N identification of an epileptogenic focus. O D E S Cathodal tDCS over the focus A resulted in a significant decrease in E interictal spikes. L P

EEG-Guided tCS: Stimulation Parameters (Frequency, phase,etc.) Zahele et al., 2012 Frequency Y P Individual Alpha frequency O C T O N O D E S A E • tACS on the occipital cortex at individual alpha frequency L P • Resting EEG  increase in alpha in parieto-central electrodes, no effects on surrounding frequencies

EEG-Guided tCS: Stimulation Parameters (Frequency, phase,etc.) Vossen et al., 2015 Frequency Y Individual Alpha frequency P O C T O N O D E S A E L P

EEG-Guided tCS: Stimulation Parameters (Frequency, phase,etc.) Neuling et al., 2012 Phase Y P O C T O N O D E S A E L P

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State dependency: Eyes Open vs. Eyes Closed Neuling et al., 2013 Y P Significant increase in alpha-power O after individual-alpha frequency tACS C when applied with Eyes open , but no T O with Eyes closed . N O D E S A E L P

State-Trait dependency Y P O C T O N O Neurotrasmitters balance Cortical “excitability” D E S Fatigue, wakefulness, attention, habituation to stimuli  A can Variability in E Flip the effect the response to Head-tissue morphology Silvanto et al., 2007 L tCS P age Hormonal levels Circadian rhythm

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Closed-Loop Diagram Y P O C T O N O D E S A E L P