Neural Plasticity: Encouraging The Brain To Change After Stroke

Transcription

1 Neural Plasticity: Encouraging The Brain To Change After Stroke Athol Mann Lecture, May 14th, 2015 Don Beaven Fellowship Jeffrey A. Kleim, Ph.D. Associate Professor School of Biological and Health Systems Engineering Arizona State University

2 -3 lbs -100 Billion Neurons. -110,000 miles of axons. -1 x synapses.

3 The Brain Breaks Down Over Time -we lose 1.8g of brain every year after the age of Gray Matter Volume (ml) Age

4 Medical Advances Are Aging Us Insulin Penicillin Influenza Vaccine Polio Vaccine Heart Transplant AIDS Virus Identified Human Genome Mapped 45 yrs 78yrs Life Expectancy

5 Population Over 65 (USA) 100 Population (Millions)

6 Stroke -third largest killer in NZ. -25 strokes/day. -9,000 strokes/year. -60,000 stroke survivors.

7 How Do We Treat Stroke? Clot Busters (tpa) Rehabilitation

8 The Paradigm Shift In Neurorehabilitation I. The recognition that brain injury is not an acute medical disorder. II. Biomedical engineering is playing a key role in optimizing treatment development and delivery. III. Our understanding of neural plasticity is guiding the development of novel, more effective therapies.

9 Encouraging the nervous system to change it s physiological state to re-engage neural circuits into a relearning state Learning Relearning

10 Neural Plasticity

11 Why should we care about neural plasticity?

12 Neurorehabilitation: Exploiting Neural Plasticity Neurorehabilitation Behavioral Signals Neurorehabilitation Neural Signals Neural Plasticity Functional Improvement (Kleim, 2012)

13 Using Animal Models To Develop Therapies

14 Rat Model of Upper Extremity Function

15 Measuring Upper Extremity Function In Rats Gross Motor Function Fine Motor Function

16 Skilled Reaching

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18 Rat Motor Maps: Intracortical Microstimulation (ICMS)

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20 Skill learning induces map plasticity Kleim et al., 1998

21 Synaptogenesis is localized to reorganized areas Synapses/Neuron URC SRC Synapses/Neuron URC * SRC Synapses/Neuron URC SRC Kleim et al., (2002).

22 Using Animal Models To Develop Therapies

23 Rat Model of Stroke

24 % Success Rehabilitation-Dependent Motor Recovery Stroke Rehab 20 No Rehab 10 Pre Day 35 42

25 Electrical Stimulation Increases Motor Map Area Kindling LTP Pre-Stimulation Post-Stimulation

26 Cortical Stimulation & Rehabilitative Training

27 60 50 Stroke Reaching Accuracy 40 %Success * * * * * * * * Stim No Stim 10 0 Pre Day

28 Phase III CS/RT Clinical Trial (Northstar: EVEREST) -2.5 hrs per day, 6 weeks -50Hz, 50% motor threshold -up to 13mA (Levy et al., In press)

29 % Patients Reaching Clinical End Point 60 % Patients Stim Ctrl 10 0 Week 4 Week 12 Week 24 Follow Up (Levy et al., In press)

30 % Recovery Motor Recovery After Stroke Rodent Monkey Human

31 Why Do Animal Studies Always Work? Salience Intensity Specificity Repetition Difficulty Timing

32 Behavioral Signals Driving Neural Plasticity Salience Repetition Specificity Intensity Difficulty Timing Kleim et al., 2012

33 Patient Vs Animal Rehabilitation 350 Repetitions During Therapy Kuys et al. Time Engaged In Movement 300 Repetitions/Hour Ada et al. Bernhardt et al. Latham et al. Bernhardt et al. 50 Rat Monkey Patient % Total Therapy Time

34 Why Can t We Achieve This In Patients? Behavioral Signals Neurorehabilitation Fatigue Spasticity Attention Depression Limited Time Neural Signals Neural Plasticity Functional Improvement

35 This Can Be Done Clinically Repetitions Active Movement Repetitions ARAT Session 10 B1 B2 B P1 P2 Birkenmeyer et al., 2010

36 The More Repetition The Greater The Improvement 25 Repetition And Motor Improvement 20 Change In ARAT Total Number of Repetitions Berkenmeier et al., 2010

37 Constrain Induced Movement Therapy Intensity: 6 hours/day. Repetition: days. Difficulty: shaping on progressively harder tasks Salience: ADL tasks.

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39 The Most Powerful Driver of Plasticity Is Experience Training a stroke patient to walk again is like training you for the Olympics....except we are encouraged to use performance enhancers.

40 Clinically Exploiting Neural Signals Neurophysiological: -rtms -TDCS -VNS Neuropharmacological: -L-DOPA -Fluoxetine

41 Transcranial Magnetic Stimulation

42 rtms To Treat Aphasia Inhibitory rtms Excitatory rtms Khedr et al., 2014

43 rtms Enhances Language Recovery Post-Stroke 25 Language HSS Score Ctrl rtms Pre Post 1Mo 2Mo Khedr et al., 2014

44 Transcranial Direct Current Stimulation (TDCS)

45 Transcranial Direct Current Stimulation Study Measure Result Hummel (2005) Jebsen Hesse (2007) Boggio (2007) KIm (2010) Lindenberg (2010) Geroin (2011) Madhavan (2011) Tanaka (2011) Bolognini (2011) Nair (2011) Rossi (2012) Zimerman (2012) Fugl-Meyer Jebsen Fugl-Meyer Fugl-Meyer 6 Min walk Tracking accuracy Knee extension MAL/Fugl-Meyer Fugl-Meyer Fugl-Meyer Digit sequence

46 Commercially Available TDCS

47 Can Genotype Influence Treatment Efficacy? Neurorehabilitation Behavioral Signals Neurorehabilitation Neural Signals Neural Plasticity Functional Improvement

48 Pharmacogenomics -Single Nucleotide Polymorphisms (SNPs). -affect the action of 110 FDA approved drugs Dermatology Neurology Cardiology Hematology Virology Oncology Psychiatry

49 CYP2D6 Gene Polymorphism: -encodes the enzyme that metabolizes codeine into morphine. -over 100 different polymorphisms. Ultra Metabolizers -75% more morphine. -2x more likley to overdose Poor Metabolizers -0% morphine

50 Polymorphisms In Plasticity Genes

51 Genetic Influences On The Capacity For Plasticity Human BDNF Val/Met 66 Polymorphism: -20% population is val/met (heterozygous) -4% population is met/met (homozygous) -results in aberrant BDNF transport/release

52 Is The BDNF Polymorphism Associated With Abnormal Experience-Dependent Cortical Plasticity? Map 1 Map 2 30 Mins Training Kleim et al., (2006).

53 Val/Val Val/Met Met/Met Pre-training * Map Area Pre-training Post-training Area (cm 2 ) Post-training 3.0 Val/Val Val/Met Met/Met Kleim et al., (2006).

54 0.30 Tracking Error Met Val Lap Number (McHughen et al, 2010)

55 Not from the U.S.? Click here to go to our international version Close SWITCH TO: CNN INTERNATIONAL Sign up Log in SEARCH Home Video NewsPulse U.S. World Politics Justice Entertainment Tech Health Living Travel Opinion ireport Money Sports Blame genetics for bad driving, study finds October 29, :41 a.m. EDT (CNN) -- The next time you see a motorist obliviously straddling two lanes, don't fault bad driving, but genetics. In a study published recently in the journal Cerebral Cortex, researcher Steven Cramer found that people with a certain gene variant performed more than 30 percent worse on a driving test than people without it. Feedback A study found that a gene variant found in about 30 percent of Americans may provoke bad driving. STORY HIGHLIGHTS Study finds bad driving may have genetic basis People with certain gene variant performed worse on driving test that those without it Nearly 30 percent of Americans have variant, according to study RELATED TOPICS The study by Cramer, a neurology professor at the University of California Irvine, might also help explain why there are so many bad drivers on U.S. highways: About 30 percent of Americans have the variant. Ordinarily, when a person performs a task, a protein called brainderived neurotrophic factor (BDNF) is secreted to the area of the brain that is associated with that activity. The protein helps facilitate communication among brain cells and helps retain memory. NewsPulse Today's five most popular stories Friend of rape victim blasts school officials

56 BDNF Polymorphism and Stroke Recovery 4.0 Mod Rankin Scale 3.5 BDNF-SNP Control 3.0 * Admission 1 Month 3 Months (Kim et al., 2013)

57 APOE-4 Polymorphism and Stroke Recovery 40 % Achieving Minimal Disability Control APOE-4-SNP (Cramer et al., 2013)

58 70 rtms 60 Fugl-Meyer Met Val/Val Pre-TMS Post-TMS Follow-Up (Chang et al., 2014)

59 Pharmacogenomics 100 Genotype 1 Response Genotype 2 Genotype 3 Dose

60 Therapogenomics? 100 Genotype 1 Response Genotype 2 Genotype 3 Treatment

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62 When Hodgkin and I finished writing the 1952 papers, each of us moved to other lines of work because we could not see how to make progress on the mechanism of channel action. Any idea of analyzing the channels by patch clamp or molecular biology would have seemed to us to be...science fiction. The thought of applying this to patient populations was beyond science fiction. Sir Andrew Huxley, 1995

63 Arizona State University Jeremy Blazer Dan Gulick Lisa Irimita Jessica Schiltz Nagheme Thomas Zuha Warraich Kristen Okada Sonia Malek John Templeton Matthew Welz Jeff Boychuk U.C. Irvine Medical Center Steve Cramer, M.D. Sheila Chan Richard Jimenez Vincent Procaccio, Ph.D. Kellan Schallert

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