eeg based personalized medicine in adhd and - brainclinics

Mar$jn Arns Director / Researcher Brainclinics PhD Candidate Utrecht University www.brainclinics.com

EEG based Personalized Medicine in ADHD and Depression

Why Personalized Medicine

n  What are the real-‐life effects of: q  S?mulant medica?on and mul?component behavioral therapy in ADHD (MTA-‐trial)

q  An?depressants and CBT in Depression (STAR*D trial)

NIMH-‐MTA study (Molina et al., 2009)

n  NIMH Collabora?ve Mul?site Mul?modal Treatment Study of Children with ADHD.

n  N=579 children n  Random assigment to:

q  14 mo. Medica?on management q  Mul?component behaviour therapy q  Combined q  Usual Community Care

n  8 years follow-‐up!

NIMH-‐MTA trial n  “…no appreciable differences among the children based on their randomized treatment group assignment…” (Molina et al., 2009)

n  Subgroup who did improve over ?me (Class 1) consis?ng of 34% (Swanson et al., 2007)

STAR*D trial (Rush et al., 2006)

n  N=3.671 Depressed pa?ents

n  Randomized to different treatments

STAR*D results (Rush et al., 2006)

n  Remission rates: 36.8% n  Cumula?ve remission rate (4

steps) = 67% n  1/3rd of all depressed pa?ents

are ‘treatment resistant’. n  Switch to CBT in Step 2 similar

results albeit slower response (Thase et al., 2007)

n  Effects of CBT overes?mated due to ‘publica?on bias’ (Cuijpers et al., 2010)

Andrew Witty, chief executive of GSK: “we believe the probability of success is relatively low, (and) we think the cost of attaining success is disproportionally high.” (Miller, 2010).

Personalized Medicine in Psychiatry n  Efficacy of current pharmaceu?cal treatments seem maximal (AD 40%;

Ritalin 70-‐90%) and limited (STAR*D & NIMH-‐MTA) q  Efficacy of newer drugs (i.e. TCA vs. SSRI) are not drama?cally

improved, mainly improved side effect profile q  Several pharmaceu?cal companies (GSK, AstraZeneca) will no longer

invest in the development of psychiatric medica?ons (Miller, 2010) q  Move beyond average efficacy data towards individual treatment!

n  Personalized medicine: Right treatment, for the right person at the right ?me as opposed to ‘Blockbuster’ approach

n  Assumes heterogeneity rather than homogeneity within a psychiatric disorder!

n  10th year anniversary of the Human Genome Project (2011): Implica?ons for psychiatry?

n  Focus on ‘endophenotypes’ or ‘biomarkers’ n  EEG based predictors for treatment outcome

q  Focus on non-‐responders (more clinically relevant, no placebo effects etc.)

What is ‘neuromodula?on’

n  ‘NeuromodulaBon is the alteraBon of nerve acBvity through the applicaBon of electrical impulses or pharmaceuBcal agents delivered directly to a relaBvely focal brain area. ’ (Harvard Neuromodula?onlab)

Moreines, J. L., McClintock, S. M., & Holtzheimer, P. E. (2010). Brain S?mula?on.

Neuromodulation n  These techniques often also focus on ‘dysfunctional

networks’ rather than DSM-IV diagnosis. q  Deep brain stimulation for Depression:

n  Subcallosal cingulate gyrus: Hamani et al. (2011) n  Nucleus Accumbens: Bewernick et al., 2010 n  Anterior and midlateral frontal cx.:Nahas et al., 2010 n  Ventral Capsule / Ventral Striatum (Malone et al., 2009).

q  Intracranial stimulation of auditory cortex in Tinnitus (de Ridder et al., 2006).

q  fMRI Neurofeedback of rostral anterior cingulate in pain (deCharms et al., 2005)

q  QEEG informed Neurofeedback in ADHD (Monastra et al., 2002; Arns et al. submitted)

14

rTMS in the treatment of depression

Rationale: 1)  Patients with left-sided lesions have a higher incidence of depression than the general population (George et al., 1994) 2)  Relative left hypometabolism as compared to right (Baxter et al., 1989 and Abou-Saleh et al., 1999) 3)  Frontal ‘alpha’ asymmetry (Davidson et al., 1990)

rTMS in Depression: Senng

HF and LF rTMS in MDD

n  HF rTMS over Left DLPFC n  Frequencies variable but >5

Hz

n  LF rTMS over Right DLPFC n  Frequency < 1 Hz

Speer et al., 2000

n  First reported by Bickford et al. (1987) in healthy volunteers and first study in Depression by George et al. (1995).

n  Currently > 30 RCT’s of HF rTMS in Depression n  Two independent multi-site double blind placebo controlled

studies demonstrating efficacy of rTMS in treatment ressistant depression (O’Reardon et al., 2007; George et al., 2010)

n  rTMS FDA approved for TRD in the US. n  HR rTMS: ES=0.39 and similar to ES of several

antidepressnts (Schutter et al., 2009) n  LF rTMS: ES=0.63 (Schutter, 2010). n  LF rTMS equal to HF rTMS (Schutter, 2010)

17

Research in Depression

LF vs. HF rTMS

n  Different or the same? q  Clinical efficacy comparable (Schutter, 2010; Fitzgerald

et al., 2003, 2009)

q  Both upregulate BDNF (Zanardini et al., 2006; Yukimasa et al., 2006)

q  Responders to HF and LF rTMS characterized by increased metabolic activity in frontal regions and ACC (Kito et al., 2008; Teneback et a., 1999; Baeken et al., 2009; Pizzagalli, 2011)

HF vs. LF: Specificity? Fitzgerald et al. (2010)

n  RCT, N=219 n  Three groups

q  1 Hz Right DLPFC q  1 Hz Right + 10 Hz Left DLPFC q  1 Hz Right + 1 Hz Left DLPFC

n  No difference between Groups! -> Adequately powered

Working mechanism of rTMS? n  Up or down-regulation of rCBF?

q  Frontal asymmetry hypothesis

n  Connectivity? Resynchronization? ‘…It is possible that the antidepressant effects of the rTMS are not dependent on frequency and laterality. An alternative model is that repetitively stimulating frontal cortex at any frequency results in the strengthening of cortical subcortical/limbic connectivity, somehow restoring normal network function, perhaps through increasing the capacity of cognitive frontal regions to exert control over the emotive limbic subcortical areas of the brain involved in depression…” (Fitzgerald et al.,2010)

To be continued…

Neurofeedback n  Classical conditioning of the EEG was first reported by

Durup & Fassard in 1935 and Loomis, Harvey & Hobart (1936).

n  Reported pairing light to auditory stimulus and habituation.

Classical Conditioning of EEG

n  First experimental studies on conditioning of the alpha blocking response in the 1940’s (Jasper & Shagass, 1941; Knott & Henry, 1941)

n  All of the Pavlovian types of conditioned responses have been demonstrated (Jasper & Shagas, 1941)

n  Not explained by ‘sensitization’ (Knott & Henry, 1941)

n  First study in 1941 demonstrating voluntary control over the alpha blocking response.

n  Still based on classical conditioning principles.

n  Subject pressed a light switch and used sub-vocal verbal commands.

n  Switching light ‘on’ was classically conditioned to stating ‘Stop’

Wyrwicka, Sterman & Clemente (1962)

n  Pairing a neutral auditory stimulus with electrical stimulation of the basal forebrain.

n  Auditory stimulus alone resulting in sleep preparatory behavior.

n  Classical Conditioning

n  〉

Ritalin è

Ritalin çè

Faraone & Buitelaar (2010)

Neurofeedback 2.0? Arns & de Ridder (2011)

Back to the future? Classical conditioning: Pairing auditory stimuli to VNS stimulation. First application in humans in Antwerp (Dirk de Ridder) currently undertaken.

Green = EEG AND conditioning Red = EEG Biofeedback Blue = Neurofeedback

n  Google ngram on book coverage of terms

English literature

German literature Trend is similar for French

EEG: Alpha and Beta

Progression of EEG during Sleep

EEG Vigilance model

For an overview see book chapter Arns, Gunkelman, Olbrich, Sander & Hegerl (2010)

Concept of EEG Vigilance

Time

Sleep on

set w

akefulne

ss

A1

A2

A3

B1

B2/3

Rigid regula?on

Physiological regula?on

Labile regula?on

EEG Vigilance in ADHD

Attention deficit / hyperactivity disorder Hyperactive subtype combined subtype inattentive subtype

Vigilance Autostabilisation Syndrome (e.g. hyperacitivity, sensation seeking, talkativeness)

Cognitive deficits (e.g. impaired sustained attention)

Unstable Vigilance Regulation (trait-like)

Hegerl et al. 2009; Olbrich

EEG Phenotypes in ADHD

n  Visual inspection of the EEG’s of 49 children with ADHD and 49 matched controls by 2 independent raters (avg. IRR: Kappa=0.84).

n  ADHD children treated with stimulant medication, CPT pre- and post-Treatment.

n  Based on EEG Phenotype framework by Johnstone, Gunkelman & Lunt (2005)

Arns, M., Gunkelman, J., Breteler, M., & Spronk, D. (2008). EEG phenotypes predict treatment outcome to stimulants in children with ADHD. J Integr Neurosci, 7, 421-38.

Does EEG predict treatment outcome? -‐ ‘Frontal slow’: Decreased false nega?ve errors: Inaqen?on

-‐ ‘Frontal alpha’: decreased false posi?ve errors: Impulsivity.

n  EEG Vigilance in ADHD: q  spent less time in higher vigilance stages (A1 and A2):

Lower Vigilance q  Showed more switching between vigilance stages

(ADHD: 26%; Controls: 19%): More unstable vigilance regulation

q  Trend for low-vigilance to be associated with worst CPT performance and best response to stimulants

q  Eyes Closed EEG only 2 minutes, suboptimal.

QEEG findings in ADHD

n  Results from computerized EEG analysis or QEEG: q  Increased absolute Theta (Bresnahan, Anderson & Barry, 1999; Chabot & Serfontein, 1996;

Clarke, Barry, McCarthy & Selikowitz, 1998; Clarke, Barry, McCarthy & Selikowitz, 2001c; DeFrance, Smith, Schweitzer, Ginsberg & Sands, 1996; Janzen, Graap, Stephanson, Marshall & Fitzsimmons, 1995; Lazzaro et al., 1999; Lazzaro et al., 1998; Mann, Lubar, Zimmerman, Miller & Muenchen, 1992; Matsuura et al., 1993)

q  Increased absolute Delta: Bresnahan et al., 1999; Clarke et al., 2001c; Kuperman, Johnson, Arndt, Lindgren & Wolraich, 1996; Matsuura et al., 1993

q  Decreased absolute Beta (Callaway, Halliday & Naylor, 1983; Dykman, Ackerman, Oglesby

& Holcomb, 1982; Mann et al., 1992; Matsuura et al., 1993)

n  Data from 250 unmedicated children with ADHD (BRC):

Theta EEG Beta EEG Relative Beta EEG

EEG Vigilance dysregulation in ADHD

n  ADHD characterized by lower EEG Vigilance q  EEG vigilance model q  Many studies reporting excess theta q  Increased absolute Delta (stage C): Bresnahan et al., 1999; Clarke

et al., 2001c; Kuperman, Johnson, Arndt, Lindgren & Wolraich, 1996; Matsuura et al., 1993

q  EEG Phenotype model: n  ADHD: More Frontal Alpha (A3), Frontal Slow (B3), Low

Voltage (B1) n  Controls: More ‘normal EEG’ (A1)

n  Symptoms are a direct result of unstable vigilance regulation (deficits in sustained attention, distractibility) and auto-stabilization behavior (e.g. hyperactivity, “sensation seeking”).

Increased or decreased Beta in ADHD? n  Average group data: n  Decreased absolute beta:

q  Callaway, Halliday, & Naylor, 1983; q  Dykman, Ackerman,Oglesby, & Holcomb, 1982; q  Mann et al., 1992; Matsuura et al., 1993

n  No difference in beta: q  Barry, Clarke, Johnstone, &Brown, 2009; q  Clarke et al., 2001c; q  Lazzaro et al., 1999; q  Lazzaro et al.,1998

n  Excess Beta: q  Kuperman et al., 1996

Increased or decreased Beta in ADHD?

n  Sub-group analysis: n  Excess Beta

q  13%: Chabot, Merkin, Wood, Davenport, & Serfontein, 1996 q  20%: Clarke et al., 1998; Clarke, Barry, McCarthy & Selikowitz,

2001b q  Most prevalent in males

n  Beta Spindles q  Clarke et al (2001a): 10% of excess beta are beta-spindles. q  Arns et al. (2008): 16% of all ADHD have beta spindles

Beta spindles

Clarke et al., 2001

What are beta spindles?

n  Infusion of barbiturates (Schwartz et al., 1971)

n  Observed in a preparation of ‘isolated cortex’ in cat (Gloor et al., 1976)

Paroxysmal example 1

Paroxysmal example 2

What are beta spindles?

n  Infusion of barbiturates h n  Observed in a preparation of ‘isolated cortex’

in cat (Gloor et al., 1976)

n  Irritable cortex, easily kindled cortex?

n  Gibbs & Gibbs (1950) distinguished F1 and F2 as increased or marked increased beta, until 1940’s ‘abnormal’. Currently not considered as such (Niedermeyer & Lopes da Silva (2004) page 161)

n  ‘Paroxysmal fast activity’ or ‘beta band seizure pattern’ during non-REM sleep, rare (4 in 3000) most often in Lennox-Gastaut syndrome (Stern & Engel, 2004; Halasz et al., 2004)

n  ‘occipital slow beta waves’ or ‘quick alpha variants 16-19 Hz’, low prevalence (0.6%) (Vogel, 1970)

n  Excess beta or beta spindling thus a ‘normal variant’, if paroxysmal fast has been excluded.

Frontal Beta Spindles Pre-NF

Frontal Beta Spindles Post-NF

Frontal slow and central beta spindles: Pre-NF

Frontal slow and central beta spindles: Post-NF

Arns, Drinkenburg & Kenemans (submitted)

The effects of QEEG-informed neurofeedback in ADHD: An

open-label pilot study

Naturalistic study

n  All files from patients with a primary diagnosis of ADHD/ADD

n  21 patients including drop-outs, non-responders and responders

n  Diagnosis confirmed with MINI n  Intake, outtake and every 10th session ADHD

symptom checklist, PSQI, BDI n  Last Observation Carried Forward (LOCF) n  Responder: >50% decreased on Inattention and/

or Impulsivity/Hyperactivity

QEEG protocols

n  Frontal Slow n  Frontal Alpha

q  Maybe more prevalent in adult ADD? n  Low Voltage EEG

n  Excess Beta group / Beta Spindles n  Slowed APF group

q  Non-responders to Ritalin.

QEEG protocols

n  Frontal Slow ✔

n  Theta/(beta) protocol: When excess fronto-central slow was observed. Only beta reward if beta was not elevated or beta spindles were not present. Only midline sites (Fz, FCz, Cz)

QEEG protocols

n  Frontal Slow ✔ n  Frontal Alpha




QEEG protocols

n  Frontal Slow ✔ n  Frontal Alpha ✔ n  Frontal Alpha protocol: When excess fronto-central alpha

(mostly EO) was observed. Beta rewards as per above. Only midline sites (Fz, FCz, Cz): Mostly in adult ADHD

QEEG protocols

n  Frontal Slow ✔ n  Frontal Alpha ✔




QEEG protocols


q  Maybe more prevalent in adult ADD? n  Low Voltage EEG ✔

n  SMR Neurofeedback and/or Alpha uptraining during EC at Pz.

QEEG protocols





QEEG protocols



n  Excess Beta group / Beta Spindles ✔ n  Beta-downtraining protocol: When beta spindles or

excess beta was present the the specific frequency of this excess beta (spindles) was downtrained on site with maximal power.

QEEG protocols



n  Excess Beta group / Beta Spindles ✔ n  Slowed APF group


QEEG protocols



n  Excess Beta group / Beta Spindles ✔ n  Slowed APF group ✔

q  Non-responders to Ritalin. q  Post-hoc analysis on APF

QEEG informed protocol selection

n  Often 2 protocols determined: n  Theta/(beta) protocol: When excess fronto-central slow was

observed. Only beta reward if beta was not elevated or beta spindles were not present. Only midline sites (Fz, FCz, Cz)

n  Frontal Alpha protocol: When excess fronto-central alpha (mostly EO) was observed. Beta rewards as per above. Only midline sites (Fz, FCz, Cz): Mostly in adult ADHD

n  Beta-downtraining protocol: When beta spindles or excess beta was present the the specific frequency of this excess beta (spindles) was downtrained on site with maximal power.

n  Low-Voltage EEG: SMR Neurofeedback and/or Alpha uptraining during EC at Pz.

n  SMR Protocol: No clear QEEG deviations and/or sleep problems. n  ‘C3’ and ‘C4’ localized with TMS: specificity

Results

Results

n  Response rate 76% (16/21) n  Non-Responders: 14% n  Drop-outs: 10%

n  Worst case scenario: Response = 76%

n  No child X adult interaction.

Effects on ADHD symptoms

All ‘Time’ effects p<.001

Effects on comorbid symptoms

All ‘Time’ effects p<.001

iAPF

n  No correlation between iAPF and ADHD improvements (A & H/I).

n  Highly significant correlation between frontal iAPF and improvement BDI (p=.002; r=.851)!

Pre- and post-treatment QEEG changes

n  For sub-group of 6 patients who were all treated with SMR NF post-treatment QEEG was available

n  5/6 underwent ‘discrete’ SMR Neurofeedback

n  Decreased SMR post-treatment (p=.009)

Increased N200 amplitude: p=.014

Increased P300 amplitude: p=.004

Conclusion n  QEEG informed neurofeedback potentially more

efficacious, especially for inattention: Requires replication.

n  No firm conclusion on iAPF – NF. n  Possible to rely on evidence based neurofeedback

protocols as the main line and still personalize treatment protocol q  Almost all subjects (18/21) received a form of T/B or

SMR/T neurofeedback

n  QEEG-informed protocol selection vs. QEEG based neurofeedback (chasing the red dot)

Pre- to post changes?

n  Pineda et al. (2008): 10-13 Hz reward in autism resulted in improved mu suppression.

n  SMR decrease? Self regulation skill. n  SMR training = learned self regulation over

mu/SMR circuitry? Similar to SCP NF?

To be continued…

n  Further explanation and discussion at the end

Depression

n  Depression generally characterized by increased alpha (Itil, 1983, Pollock & Schneider, 1990)

n  Increased alpha positive predictor for treatment outcome (Ulrich et al., 1984; Bruder et al 2001)

n  Antidepressants decrease alpha power (Itil 1983)

n  rTMS in Depression n  Predictors for unfavourable treatment

outcome

Martijn Arns Director / Researcher Brainclinics PhD Candidate Utrecht University www.brainclinics.com

Neurophysiological predictors of non-response to rTMS in depression

Arns, Drinkenburg, Fitzgerald & Kenemans

(Submitted)

Study design n  Multi-site open label study n  Inclusion: Primary diagnosis of MDD or

Dysthymic Disorder (MINI) and BDI>14. n  Exclusion: Paroxysmal EEG, Previous ECT. n  BDI and DASS intake, outtake and every 5th

session n  Pre-treatment QEEG and ERP’s n  Post-treatment QEEG and ERP’s for

subgroup of responders n  rTMS combined with psychotherapy

rTMS protocols

n  Magstim Rapid2 and figure-8-coil. n  Site 5 cm. rule n  HF rTMS: L-DLPFC, 10 Hz, 110% MT, 30

trains, 5 s. ITI (1500 pulses/session) n  In case of focal beta-spindles: n  LF rTMS: R-DLPFC, 1 Hz, 110% MT, 120

trains, 10 s. ITI 1 s. (1200 pulses/session). n  Age >55 yrs: + 10% MT (frontal atrophy)

Results

n  Sample: N=90 patients n  HF rTMS: N= 57; LF rTMS: N=33 n  No baseline differences between HF and LF

rTMS n  No differences in clinical efficacy between HF

and LF rTMS

EEG Cordance

Correlation pre-frontal beta cordance with % improvement (p=.044; r=.215)

Leuchter et al., 1999

P300 Amplitude

P300 amplitude at Pz: P=.054

Non-response in depression n  Increased theta

q  Medication: Losiffescu et al., 2009; Knott et al., 1996; 2000

q  rTMS n  Correlation theta and % Improvement

(p=.005; r=-.296)

Depression: Increased Theta sub-‐group n  Increased Theta reflec?ve of lower EEG Vigilance. n  More suscep?ble to s?mulant medica?on?

q  Suffin & Emory (1995); DeBansta et al. (2010) q  Manic Depression: Bschor et al. (2001); Hegerl et al. (2010); Schoenknecht et

al. (2010); q  ADHD: Arns et al. (2008); Sander et al. (2010)

n  Impaired vigilance regula?on the core feature? n  To be con?nued…

Hegerl et al. (2011)

Slowed individual Alpha Peak Frequency (iAPF)

n  Generic predictor for non-response?

n  Red = non-responders n  Black = responders n  N=90

iAPF

Correlation anterior iAPF with % improvement (p=.002; r=.326)

Poten?al of EEG based PM

Discriminant analysis including: -  iAPF Fz -  Pre-frontal Delta and Beta Cordance -  P300 Amplitude Pz P=.001 Area =.814 Correct classification: 10% false positive rate: 53% NR 5% false postive rate: 41% NR

iAPF pre- and post-treatment

n  Baseline high iAPF: decrease in iAPF n  Baseline low iAPF: Increase in iAPF n  Note: Majority 10 Hz rTMS.

P300 Amplitude

Non-responders demonstrated an increased P300 amplitude @ Pz (p=.056; F=3.752; DF=1, 79). Pre- to post-treatment changes in P300 dependent on baseline P300 amplitude

Conclusions n  No difference between HF and LF rTMS

q  Both also upregulate BDNF in HC (Zanardini et al., 2006)

n  LF rTMS first choice treatment: Safer, better tollerated, equipment more affordable.

n  Clinical effects of rTMS + Psychotherapy are better (similar to medication + psychotherapy)

n  Long-term effects likely due to psychotherapy n  Non-responders characterized by:

q  Excess Theta, Increased and Larger P300 amplitude @ Pz, Slow frontal iAPF, Lower pre-frontal perfusion

n  No effects of medication status

Working mechanism of rTMS? n  Up or down-regulation of rCBF?

q  Frontal asymmetry hypothesis

n  Connectivity; Resynchronization! q  No difference between HF and LF rTMS q  ‘Normalization’ of iAPF and P300 amplitude q  Increased rCBF predictor for response to both HF

and LF rTMS, no laterality effects

n  Implications for non-responders?

Predictors for non-response

n  iAPF: Non response to stimulants (ADHD), rTMS (Depression), antidepressants (Ulrich et al.,

1984) and antipsychotics (Itil et al., 1975)

n  Impaired vigilance regulation q  Predictor for response to psychostimulants

(ADHD) q  Predictor for non-response to rTMS and

antidepressants n  How does Neurofeedback work???

iAPF medica?on

Non-responders

Responders

Ulrich et al. (1984)

n  Pa?ents treated with TCA n  Responders exhibit:

q  Decreased alpha power q  Higher baseline iAPF q  Faster iAPF post-‐treatment

n  Red is pre-‐treatment n  Blue is post-‐treatment

rTMS in Depression

Arns et al. (2010) - In agreement with Conca et al. (2000)

ADHD and Psychos?mulants

27%

Fz Pz

APF-ADHD APF-Control APF-’Normal EEG’

n  APF matures with age and can vary between 5-14 Hz and fixed frequency bands do not accomodate deviating APF’s (Klimesch, 1999)

n  Theta/Beta ratio calculated using: q  Fixed Frequency bands (4-7.5 Hz / 12.5-25 Hz) q  ‘Individual’ frequency bands (Based on IBIW method

from Doppelmayr et al., 1998).

Theta/Beta ratio using Fixed frequency bands: Significant effect p=.038

Theta/Beta ratio using Individual frequency bands: NO significant effect

Theta/Beta ratio indeed confounded by slow iAPF group: Unspecific measure.

n  Important to dissociate slow iAPF from theta given different underlying neurophysiology and differences in treatment response!

Acute pain

Chronic pain

Chronic pain

Pre-surgery = RED Post-surgery = PURPLE 12 months Post-Surgery = BLUE Normal = GREEN

iAPF a reflection of fight-flight?

n  iAPF speeds up in response to ‘acute threat’ q  Faster thalamo-cortical information exchange ->

faster response to threat n  With chronic ‘threat’ iAPF slows down

q  Reducing perception of ‘threat’ (chronic pain or chronic stress’) as a ‘coping mechanism’

n  Relief of ‘chronic threat’ normalizes iAPF, but takes time (12 months)

iAPF as an endophenotype?

n  iAPF q  Highly stable across time (Kondacs & Szabo, 1999)

q  Most heritable EEG trait: 71-83% heritability (Posthuma et al., 2001; Beijsterveld & van Baal., 2002)

q  Genetically linked to COMT gene (Bodenmann et al., 2009)

q  iAPF true endophenotype (Gottesman & Gould, 2003)? q  What does this endophenotype reflect other than

non-response? Treatment?

iAPF as a reflection of cerebral blood flow

n  Berger (1934): slowing of the EEG as a result of reduced oxygen.

n  iAPF most sensitive marker to demonstrate low oxygen supply such as in cerebral ischemia (Kraaier et al., 1988; van der Worp et al., 1991; Mosmans et al., 1983)

Largest increase in iAPF for those with an iAPF of below 9 Hz!

n  All correlations were positive (increased APF associated with increased rCBF).

n  Following areas were sign. After correction: q  Bilateral IFG (BA 45): Arousal and attention q  Right insular cortex (BA 13): representation of

internal states and sensory integration q  High APF interpreted as a higher level of task

related attention and preparedness at rest that facilitates task execution.

n  Healthy volunteers: APF 8.8-11.8 Hz

n  iAPF as an endophenotype for non response to treatments.

n  Reflection of reduced cerebral blood flow

n  Implications: q  Dissociate slow iAPF from ‘Theta’ q  Exclude organic causes such as cerebral

ischemia, stenosis, if present treat first q  Development of new treatments for this

endophenotype, aiming to increase rCBF q  Possibilities: HBOT? fNIRS? Transcranial doppler

sonography biofeedback (Duschek et al., 2010)

Impaired vigilance regulation n  Subgroups with this subtype are: n  Responders to psychostimulants

q  Sander et al. (2010): EEG Vigilance q  Excess theta (many studies)

n  Non-responders to rTMS and antidepressants q  Excess theta (Iosiffescu et al., 2009; Knott et al., 1996; 2000)

n  This EEG subgroup has been shown to respond to psychostimulants: q  Depression: Suffin & Emory (1995); DeBansta et al. (2010) q  Manic Depression: Bschor et al. (2001); Hegerl et al. (2010);

Schoenknecht et al. (2010).






Hegerl et al. 2009; Olbrich

ADHD and sleep

n  ADHD patients exhibit excessive sleepiness during the day (Cohen-Zionn & Ancoli-Israel, 2004) and is associated with higher prevalences of sleep problems (Chervin et al., 2002; Konofal et al., 2010)

n  Improvement of sleep results in specific improvements of ADHD symptoms: q  DA therapy to treat restless legs syndrome (Walters

et al., 2000)

q  Adenotonsillectomy in children with moderate sleep and breathing disorders (Ali et al., 1996)

Sleep restriction and improvement

n  Sleep restriction and sleep extension in healthy children of 1 hr. across 3 days resulted in marked differences in memory performance, CPT and RT (Sadeh et al., 2003)

n  ‘ADHD-like’ behavior can be induced in healthy children by sleep restriction (Fallone et al., 2001; Golan et al., 2004)

n  ADHD symptoms can be improved by improving sleep deficits (Dahl et al., 1991)

Sleep onset insomnia (SOI) n  Delayed sleep onset, latency between lights-off

and sleep onset > 30 minutes, > 4 nights per week, > 1 year (Smits et al., 2001)

n  Prevalence: ADHD Children: 72.5%-74.9% (van

der Heijden et al., 2005; 2007) and ADHD adults: 78% (van Veen et al., 2010).

n  70% had onset of SOI before age 3 (van der Heijden

2005), SOI is not explained by sleep hygiene (van der Heijden et al., 2006)

n  Differences in sleep latency, wake up-time, but not for total sleep duration (van der Heijden et al., 2005)

n  Later Dim Light Melatonin onset (DLMO): Delayed circadian rhythm

Van der Heijden et al. 2005

Melatonin treatment in ADHD

n  4-week treatment of ADHD-SOI children n  Sleep normalized (advanced sleep onset (27

min.) and DLMO (44 minutes), to normal values (van der Heijden et al., 2007; Smits et al., 2001)

n  No sign. Effects on ADHD symptoms and sustained attention after 4 weeks.

n  Follow-up after 3.7 yrs.: 70.8 % improved behavior and 60.9% improved mood! (Hoebert et al., 2009)






Sleep onset insomnia, delayed circadian rhythm

Sleep problems as the core pathophysiology in low vigilance ADHD subgroup

n  Prevalence 70-80% in adult and pediatric ADHD

n  Psychostimulants effective, but ‘symptom suppression’. Might explain the lack of effect beyond 2 years (MTA trial)

n  Melatonin affects the core pathophysiology in this sub-group, effects maintained after 3.7 years only if still using melatonin.

n  Neurofeedback???

Neurofeedback and Sleep

n  Sterman, Howe & MacDonald (1970) in Cats n  SMR Neurofeedback (during waking!):

q  Longer epochs of undisturbed sleep q  Increased number of sleep spindles

n  RCT: N=9 NF (SMR); N=8 BF (EMG) n  Primary insomniacs n  Pre- and post-polysomnography n  Both subjective and objective improvements for the

neurofeedback group.

n  Randomized parellel group design n  N=27 healthy subjects n  10 Neurofeedback sessions n  Control group = Randomized-frequency

conditioning q  Improved sleep latency q  Increased sleep spindles during sleep q  Improved retrieval score (memory)

SMR Neurofeedback

n  SMR NF during waking results in increased sleep spindle density during sleep (Sterman et al., 1970; Hoedlmoser et al., 2008)

n  SMR NF decreases sleep latency, increases total sleep time and sleep efficiency (Cortoos et al., 2010; Hoedlmoser et al., 2008; Sterman et al., 1970).

n  SMR NF normalizes sleep in ADHD-SOI patients?

Theta/Beta NF

n  Rewarding 0

n  (Inhibiting A3)

n  Inhibiting B2/3

Theta/Beta

n  It is observed that this treatment results in sleep improvements

n  This procedure increases vigilance n  Unknown how this procedure exerts its effect

on sleep.

Sleep, ADHD… Epilepsy…? n  Neurofeedback best evidence for sleep, ADHD and

epilepsy. n  ES for NF in Epilepsy is small (ES=0.23; Tan et al., 2009). n  GSR biofeedback (increase arousal) reduces epileptic

seizures (Nagai et al., 2004). n  Both spike wave discharges (SWD) and sleep spindles

occur under identical states of vigilance such as relaxed wakefulness and light SWS (Coenen, 1995) and SWD can be terminated by arousing and meaningful stimuli (Coenen, 1995; Shaw, 2003).

n  Osterhagen et al (2010) conditioned SWD and found the opposite effect, interpreted as reinforcement resulting in increased arousal, terminating the SWDs.

n  Sleep deprivation is often used to provoke seizure activity.

Sleep, ADHD… Epilepsy…?

n  Effects of Neurofeedback in epilepsy by: q  Stabilizing and normalizing sleep q  Improved vigilance during the day q  Less occurrences of low vigilance periods q  Decrease in seizure frequency

How does Neurofeedback work?

n  Hypothesis: q  Neurofeedback works primarily by normalizing

and improving sleep quality and hence exerts its effects in insomnia, ADHD (improving sleep onset-insomnia) and epilepsy (decreasing daytime drowsiness)

Implications?

n  In line with the behavioral effects of melatonin taking place after prolonged time, are we ‘over-treating patients’ with neurofeedback?

n  First normalize sleep and …wait…

Neurofeedback follow-up

2-years follow-up

3-6 months follow-up

Patient 1: T/B Neurofeedback 2 X 6 weeks break

Patient 2: SMR/Theta neurofeedback 3 month break

Conclusion n  ‘Impaired vigilance regulation’

q  Respond to stimulant medication: symptom suppression

q  Non-responders to antidepressant treatments q  Core-pathophysiology hypothesized to be sleep

problems such as sleep-onset insomnia q  Treatments should aim at restoring sleep:

melatonin, bright light, neurofeedback. n  Slow iAPF: Endophenotype for non-response to

treatment, related to cerebral perfusion n  Patience… normalization of neurophysiology (iAPF)

and behavior (ADHD symptoms) takes time….

Conclusion

n Patience… normalization of neurophysiology (iAPF) and behavior (ADHD symptoms) takes time….

n Don’t chase the quick-fix

Thank you for your attention!

Thanks to many colleagues and collaborators for making these studies possible: Sabine de Ridder, Dianne Winkelmolen, Vera Kruiver, Rosalinde van Ruth, Dagmar Timmers, Hanneke Friesen, Desiree Spronk, Niels Veth, Mathanje Huisman, Nicole van Merode, Jay Gunkelman, Pim Drinkenburg & Leon Kenemans

eeg based personalized medicine in adhd and - brainclinics

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