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Y P O C Intensive Course in Transcranial Magnetic Stimulation T O N O D E The cause of, and solution to, some of TMSs variability S And a way to potentially increase its selectivity A E Peter J. Fried, Ph.D. L P October,


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“The cause of, and solution to, some of TMS’s variability And a way to potentially increase its selectivity”

Intensive Course in Transcranial Magnetic Stimulation

Peter J. Fried, Ph.D.

October, 2016

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

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 What is ‘state-dependency’?  Single Pulse TMS (specificity)  Repetitive TMS (meta-plasticity)  Implications for study design

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

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Input Output Something in the middle

The basal or ongoing state of the brain influences the outcome of stimulation

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

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Test pulse (alone) Conditioning Pulse + Test Pulse Intracortical Facilitation (ISI = 8-30ms) Intracortical Inhibition (ISI = 1-6ms)

Modified from: Kobayashi & Pascual-Leone, 2003 (Lancet Neurology)

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

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 What is ‘state-dependency’?  Single Pulse TMS (specificity)

  • Adaptation & Priming

 Repetitive TMS (meta-plasticity)  Implications for study design

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

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Adaptation: Prolonged prior exposure to stimulus reduces neural activity and response to subsequent presentation Priming: Transient prior exposure to stimulus increases neural activity and response to subsequent presentation

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

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

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

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Modified from: Silvanto et al., 2008 (Trends in Cognitive Sciences)

Baseline After adaptation to red After TMS Relative neural activity

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

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Cattaneo & Silvanto, 2008 (NeuroReport)

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

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Cattaneo et al., 2008 (European Journal of Neuroscience)

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

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  neural activity =  TMS susceptibility  Adaptation/Priming can improve selectivity

  • f TMS

 “Functionally independent, spatially

  • verlapping populations of neurons”

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

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 What is ‘state-dependency’?  Single Pulse TMS (specificity)  Repetitive TMS (meta-plasticity)

  • Inter-individual variability
  • Altered impact in disorders
  • Preconditioning, accumulation

 Implications for study design

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

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

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240 pulses 1600 pulses

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

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80% 85% 90% 95% 100% Baseline Post-rTMS

Spatial Accuracy * Modified from Fried et al., 2014

70% 75% 80% 85% 90% 95% 100%

Baseline Post-rTMS

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

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Impact of 1Hz rTMS on Motor-Evoked Potential (MEP), Intracortical Facilatition and Inhibition

Brighina et al., 2005 (Experimental Brain Research)

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

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21 Iezzi E et al., 2008 (J Neurophysio)

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

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

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23 Siebner et al., 2004 (Journal of Neuroscience) Impact of tDCS/rTMS on Motor-Evoked Potential (MEP) amplitude

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

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

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Maeda et al., 2000 (Clinical Neurophysiology)

Impact of rTMS on Motor-Evoked Potentials Impact of daily 1Hz rTMS on visuo-spatial detection

Valero-Cabré et al., 2008 (European Journal of Neuroscience)

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

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Oberman et al., 2012 (European Journal of Neuroscience)

Impact of TBS on Motor-Evoked Potential (MEP) Amplitude

0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 1 2 Log Transformed "time to baseline" values Session Number ASD FXS Control

Oberman et al., 2016 (J Child Adolescent Psychopharm)

Cumulative Impact of Back-to-Back TBS

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

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Fried et al., 2016 (unpublished – DO NOT SHARE!) Excellent

Good Fair Poor Reproducibility Single-pulse measures Paired-pulse measures Post-iTBS measures

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Cronbach's alpha

all

all

Reproducibility of TMS-based neurophysiological and neuroplasticity measures

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

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Fried et al., 2016 (unpublished – DO NOT SHARE!) Excellent

Good Fair Poor Reproducibility Single-pulse measures Paired-pulse measures Post-iTBS measures

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Cronbach's alpha

all AD

Reproducibility of TMS-based neurophysiological and neuroplasticity measures

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

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 Impact of rTMS not absolute

  • Low/High Hz doesn’t always suppress/enhance
  • Can be influenced by disorder

 Assess reliability/stability of outcome variable  Presence of “homeostatic” forces

  • Very short interval (≤ 1s)  basis of rTMS
  • Back-to-back regimens  likely to cancel out
  • Daily sessions  build up facilitation

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

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 What is ‘state-dependency’?  Single Pulse TMS (specificity)  Repetitive TMS (meta-plasticity)  Implications for study design

  • Follow the three C’s
  • Predicting Therapeutic Outcome
  • To sham or not to sham

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

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Easy to control

 Caffeine, Rx  Prior stimulation  Time of day  Food intake  Handedness  Concomitant activity

Less Easy to Control

 Amount of sleep  Menstrual cycle  Stress, mood  Disease heterogeneity  Baseline activity  Expectation  DNA

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

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 Modulates NMDAR-dependent plasticity  Activity-dependent release at synapses

pro-BDNF Mature BDNF

65%: val66val 35%: val66met (less efficient)

Single substitution of Guanine for Adenine results in an amino acid switch from Valine (Val) to Methionine (Met)

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

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 Produced by astrocytes, microglia (in CNS)  Transports cholesterol & fat-soluble vitamins

to neurons

 Three major isoforms:

  • ApoE2 (cys112, cys158): ~7%
  • ApoE3 (cys112, arg158): ~79%
  • ApoE4 (arg112, arg158): ~14%

▪ E3,E4 & E4,E4: Higher risk for Alzheimer’s disease

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

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  • 20

20 40 60 80 OHC DM2

MEP Amplitude (% ∆ from baseline)

All subjects

OHC DM2

BDNF Val/Met & ApoE ε3/ε4 excluded

p = 0.0537 Effect size = 0.35 p = 0.0051* Effect size = 0.52

Unpublished work – please do not share

For full study, see Fried et al., 2016 (J Alzheimer’s Disease)

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

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Fried et al., 2016 (unpublished – DO NOT SHARE!)

p = 0.035

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

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 Collect / Correlate  Control / Counter-balance  Co-opt / Capitalize

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

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

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

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

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

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Li et al., 2014 (Cerebral Cortex)

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

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 Individualized targeting

  • Single node vs. network

 Prime sub-populations of neurons

  • Intrinsic vs. extrinsic engagement

 Assess efficacy online

  • Custom dose

 Leverage placebo effect

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

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 Only ~14% of randomized sham-controlled

trials report blinding success (Broadbent et al. 2011, World J

Bio Psychiatry)

 Patients correctly guessed Tx condition above

chance (Berlim et al. 2013, Int J Neuropsychopharm)

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

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Pros: Easy, fast, cheap No switching coils Similar sensations Cons: Might induce current Won’t fool non-naïve

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real sham

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

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Pros: Similar look and feel Tech getting better Cons: Slow, expensive Must switch coils Still doesn’t feel the same

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real sham

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

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Pros: Easy, fast, cheap Same sensations Cons: Will control site have real effects? Laterality of sensations

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real vertex

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

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Pros: Easy, fast, cheap Same sensations Greater explanatory power Cons: More difficult study design

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Left hemisphere Right hemisphere

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

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What state- dependency?

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