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How to measure
and improve
brain-based
outcomes that
matter in health
care
How to measure and improve brain-based
outcomes that matter in health care
Chaired by: Alvaro Fernandez,
CEO of SharpBrain...
A Neurobiological
Substrate of Psychiatric
Disorders
Madeleine Goodkind, PhD
Staff Psychologist, New Mexico VA Healthcare ...
Introduction
 An example: PTSD
 Heterogeneity within the diagnosis
 Comorbidity is the norm
 Common symptoms across di...
Research Domain Criteria
(RDoC)
 NIMH’s Strategic Plan: “Develop, for research
purposes, new ways of classifying mental d...
Why RDoC?
 Genes
 Common polymorphisms associated with a range
of psychiatric diagnoses
 Overlapping susceptibility acr...
 Are there common areas of the brain impacted by
psychiatric illness?
 Voxel-based Morphometry (VBM)
 Statistical appro...
 Search across VBM studies of psychiatric disorders
 Major Depressive Disorder
 Bipolar Disorder
 Schizophrenia
 OCD,...
 Across diagnoses, 2 regions of common decreased
tissue volume:
2
4
6
Z
dACC
RL
insula
VBM Meta-analysis of
Psychiatric I...
Functional Connectivity
 In healthy controls, these 3 regions (dACC, bilateral
anterior insula)…
- Coactivate during task...
-3
-2
-1
0
1
2
-3 -2 -1 0 1 2 3
-3
-2
-1
0
1
2
-3 -2 -1 0 1 2 3
 In healthy controls,
regional brain volume is
associated...
Conclusions
 Dorsal anterior cingulate and anterior insula
 Fundamental role in self-awareness, interoception, cognitive...
Thank you
& questions?
Randy McIntosh
Rotman Research Institute - Baycrest
How do
we bring it
together?
We can
gather
over 1
TB of
data on
your
brain
Need for a large-scale network-based thinking
time delays via long range connections
local connectivity
neural mass
Large-...
Sanz Leon et al Front NeuroInformatics 2013
Real data are fed into
TheVirtualBrain to make a
person’s own brain model
Function
Structure
Modeled
Original
Connections ...
Virtual brain- data fitting
Ritter et al, Brain Connectivity, 2013
Fitting of individual’s EEG
wave forms
Stroke
Virtual Brain
Anatomical Model
Change in
Communication
Preliminary tests suggest the
parameter values for local
populations in a patient also predict
recovery of motor function!...
Whole brain Subcortical regions
Epilepsy patient: Geometry
Epilepsy patient: Fiber tracts
Epilepsy patient: Complex partial seizure
Simulation: Complex seizure – the whole system
Task: Spread between
both hippocampi
Run simulations:
Different epilepto-
g...
26
Personalized brain models
27
Constructing subject-specific
Virtual Brains
Schirner, Rothmeier, Jirsa, McIntosh, Ritter (2015) Neuroimage
An automate...
Scalp
Surface
Regional
Map
Cortical
Surface
Electroencephalo
graphy
EEG
Functional
MRIStructural
Connections
Personalized
...
Presented by:
Chris Berka
CEO & Co-Founder
EEG Biomarkers: Day & Night
For over fifteen years, ABM has pioneered the development
of mobile, scalable, and easy-to-use platform technologies
to mo...
Electroencephalography (EEG) provides cost-effective
neuroassessment that is exquisitely sensitive to CNS
disease and trea...
FDA cleared mobile wireless EEG features:
• Lightweight & comfortable headset
• Rapid, efficient set-up & cleaning
• 20m w...
Epoch-by-Epoch
Changes Over Time
Epoch lengths ranging from
0.5 sec to several minutes
Power Spectral Densities
1-40 Hz, R...
AMP Introduction
Alertness & Memory Profiler
Clinical Research Applications
• Quantified excessive daytime sleepiness and
...
• FDA cleared for assessment of sleep architecture and sleep continuity
• Record 16+ hrs without battery charge; Easily se...
CNS Disease and
Cognitive/Clinical
Symptom
Nighttime EEG Daytime EEG
Parkinson’s Disease
and Dementia
REM Sleep w/o Atonia...
Bandwidth Power Spectral Density
(PSD) Analysis
• Analyzed a (Biogen-owned) database of
Healthy controls and Alzheimer’s p...
Low Resolution Electromagnetic Tomography Analysis
• LORETA 3D source analysis can
identify and map excessive and/or
reduc...
Example of Coherence Analyses in Parkinson’s
Patients implanted for DBS:
Illustration of abnormal theta
coherence patterns...
Emotion Elicitation Testbed:
International Affective Picture System (IAPS)
• 1000+ emotionally stimulating pictures
• Desi...
• Heart Rate Variability increases in response to stressful stimuli in both groups
• PTS subjects exhibit increased gamma ...
Closed-loop EEG/FES Neurorehabilitation
EEG provides real-time spatial and spectral information during adaptive rehab
Part...
Summit is on Lunch.
(we will resume at 12:30pm Pacific Time)
Chat forums will be available during the Watercooler session
To learn more, visit sharpbrains.com
How to mea­sure and improve brain-based out­comes that mat­ter in health care
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How to mea­sure and improve brain-based out­comes that mat­ter in health care

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Pio­neers advanc­ing health research, pre­ven­tion and treat­ment will help us under­stand emerg­ing best prac­tices where tar­geted assess­ments, mon­i­tor­ing and inter­ven­tions can trans­fer into sig­nif­i­cant health­care and qual­ity of life outcomes.
-- Chair: Alvaro Fer­nan­dez, CEO & Co-Founder of SharpBrains
-- Dr. Madeleine S Good­kind, staff psy­chol­o­gist at New Mex­ico VA Health Care System
-- Dr. Randy McIn­tosh, Vice-president of Research and Direc­tor of Baycrest’s Rot­man Research Institute
-- Chris Berka, CEO and Co-Founder of Advanced Brain Mon­i­tor­ing (ABM)

Presentation @ The 2015 SharpBrains Virtual Summit http://sharpbrains.com/summit-2015/agenda

Published in: Health & Medicine
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How to mea­sure and improve brain-based out­comes that mat­ter in health care

  1. 1. How to measure and improve brain-based outcomes that matter in health care
  2. 2. How to measure and improve brain-based outcomes that matter in health care Chaired by: Alvaro Fernandez, CEO of SharpBrains Dr. Madeleine S Goodkind, Staff Psychologist at New Mexico VA Health Care System Dr. Randy McIntosh, VP of R&D at Baycrest’s Rotman Research Institute Chris Berka, CEO and Co-Founder of Advanced Brain Monitoring (ABM)
  3. 3. A Neurobiological Substrate of Psychiatric Disorders Madeleine Goodkind, PhD Staff Psychologist, New Mexico VA Healthcare System Assistant Clinical Professor, University of New Mexico School of Medicine
  4. 4. Introduction  An example: PTSD  Heterogeneity within the diagnosis  Comorbidity is the norm  Common symptoms across diagnoses  Most studies, grants, treatments follow a categorical approach
  5. 5. Research Domain Criteria (RDoC)  NIMH’s Strategic Plan: “Develop, for research purposes, new ways of classifying mental disorders based on dimensions of observable behavior and neurobiological measures”.  Emphasis:  Dimensions that cut across diagnoses  Neuroscience and behavioral science above descriptive phenomenology
  6. 6. Why RDoC?  Genes  Common polymorphisms associated with a range of psychiatric diagnoses  Overlapping susceptibility across > 30,000 cases  Brain  Common processes (cognition, emotion regulation) rely on distributed brain regions  Disrupted in psychopathology  Brain is organized into coherent functional networks  Abberant brain organization and networks in psychopathology Cross-Disorder Group of the Psychiatric Genomics Consortium, The Lancet, 2013; Menon, TICS, 2011; Whitfield-Gabrieli & Ford, Annu Rev Clin Psychol, 2012
  7. 7.  Are there common areas of the brain impacted by psychiatric illness?  Voxel-based Morphometry (VBM)  Statistical approach to identify differences in brain anatomy between groups of people  Break the brain down into voxels (3-D pixels) and compare Strengths  Assesses entire brain; standardized methods  Stable measure in patients  Lots of studies with lots of diagnoses Structural markers in Psychiatric Illness
  8. 8.  Search across VBM studies of psychiatric disorders  Major Depressive Disorder  Bipolar Disorder  Schizophrenia  OCD, PTSD, and other anxiety disorders  Substance Use Disorders  193 studies, with 212 comparisons between patients and controls  7381 patients; 8511 controls VBM Meta-analysis of Psychiatric Illnesses
  9. 9.  Across diagnoses, 2 regions of common decreased tissue volume: 2 4 6 Z dACC RL insula VBM Meta-analysis of Psychiatric Illnesses bilateral anterior insula dorsal anterior cingulate cortex
  10. 10. Functional Connectivity  In healthy controls, these 3 regions (dACC, bilateral anterior insula)… - Coactivate during tasks dACC insula cingulate R insulaL insula overlap (MACM) cingulate R insulaL insula overlap (FC) - Show functional connectivity during resting state
  11. 11. -3 -2 -1 0 1 2 -3 -2 -1 0 1 2 3 -3 -2 -1 0 1 2 -3 -2 -1 0 1 2 3  In healthy controls, regional brain volume is associated with cognitive performance Correlations with cognition Left Insula executivefunction(z-score) sustainedattention(z-score) gray matter volume (z-score) -3 -2 -1 0 1 2 -3 -2 -1 0 1 2 3 executivefunction(z-score) dACC
  12. 12. Conclusions  Dorsal anterior cingulate and anterior insula  Fundamental role in self-awareness, interoception, cognitive control, and emotional processing  Part of a coherent network (Salience Network)  Transdiagnostic gray matter loss in psychiatric illness  Commonalities, not just differences  Address overreliance on categories and exclusive focus on clinical symptoms in psychiatric nosology  Psychopathologies involve dysfunction of processes (cognition, emotion regulation) relying on distributed brain networks  Implications for treatment
  13. 13. Thank you & questions?
  14. 14. Randy McIntosh Rotman Research Institute - Baycrest
  15. 15. How do we bring it together? We can gather over 1 TB of data on your brain
  16. 16. Need for a large-scale network-based thinking time delays via long range connections local connectivity neural mass Large-scale brain networks
  17. 17. Sanz Leon et al Front NeuroInformatics 2013
  18. 18. Real data are fed into TheVirtualBrain to make a person’s own brain model Function Structure Modeled Original Connections This means you can use it now to directly link computational models to data
  19. 19. Virtual brain- data fitting Ritter et al, Brain Connectivity, 2013 Fitting of individual’s EEG wave forms
  20. 20. Stroke Virtual Brain Anatomical Model Change in Communication
  21. 21. Preliminary tests suggest the parameter values for local populations in a patient also predict recovery of motor function! Mapping the dynamic landscape in stroke recovery
  22. 22. Whole brain Subcortical regions Epilepsy patient: Geometry
  23. 23. Epilepsy patient: Fiber tracts
  24. 24. Epilepsy patient: Complex partial seizure
  25. 25. Simulation: Complex seizure – the whole system Task: Spread between both hippocampi Run simulations: Different epilepto- genicity values for cross-hippocampus paths Jirsa et al Brain (2014); Proix et al JNS (under review); Proix et al (in preparation)
  26. 26. 26 Personalized brain models
  27. 27. 27 Constructing subject-specific Virtual Brains Schirner, Rothmeier, Jirsa, McIntosh, Ritter (2015) Neuroimage An automated pipeline for constructing personalized virtual brains from multimodal neuroimaging data
  28. 28. Scalp Surface Regional Map Cortical Surface Electroencephalo graphy EEG Functional MRIStructural Connections Personalized Virtual Brain
  29. 29. Presented by: Chris Berka CEO & Co-Founder EEG Biomarkers: Day & Night
  30. 30. For over fifteen years, ABM has pioneered the development of mobile, scalable, and easy-to-use platform technologies to monitor and interpret physiological signals. • Recipient of over $32 mm in government R&D funding • 20 patents issued; 11 patents-pending • ISO 13485 and FDA Device Manufacturer • Clinical trial capabilities: • Scalable data acquisition and analyses • Study site training, certification, and support • Fully compliant with all regulatory guidelines (21 CFR Part 11; HIPPA) • Inc. 5000 Fastest Growing Companies five consecutive years • 70+ papers validating suite of technologies • Worldwide distribution networks • Over 500 customers worldwide including 14 Fortune 500 clients Company Profile
  31. 31. Electroencephalography (EEG) provides cost-effective neuroassessment that is exquisitely sensitive to CNS disease and treatment efficacy Daytime EEG captures activation of neural circuits during resting state or while performing neurocognitive tasks. ABM Stat X-Series EEG systems acquire up to 24 channels of EEG during resting state or activation tasks. Nighttime EEG captures sleep quality and architecture as well as discrete processes underlying cognitive functions (e.g., memory consolidation). ABM Sleep Profiler™, multi-night sleep architecture, spindles, atonia, hypoxemia, and arousals Converging EEG biomarkers confer increased reliability, sensitivity, and specificity, for tracking disease progression and/or treatment response.
  32. 32. FDA cleared mobile wireless EEG features: • Lightweight & comfortable headset • Rapid, efficient set-up & cleaning • 20m wireless transmission with real-time signal quality monitoring • Saves data in EDF for compatibility • Secure data management portal
  33. 33. Epoch-by-Epoch Changes Over Time Epoch lengths ranging from 0.5 sec to several minutes Power Spectral Densities 1-40 Hz, Relative or Absolute Custom bins or bands Traditional Bands Delta (1-3) Theta (3-7) Alpha (8-13) Beta (13-30) Gamma (25-40) High Gamma (40+) Wavelets Topographic Mapping frontal, central, parietal, left, midline, right Automated detection of epileptiform EEG Event Locked Analyses Events can be external stimuli, responses, or biological Pre- and Post-Event Analyses ERPs Averaged over trials Averaged over sites for single-trial ERPs Enables regional comparisons Measurement tools for amplitude latency area-under-the-curve PERPs (PSDs) ERD / ERS Event related B-Alert Metrics LORETA/sLORETA 3D Imaging Resting-state brain connectivity analysis and modeling EEG coherence and phase-related analyses Compute amplitude asymmetry Real-time 3-Dimensional Source and Network Dynamics Brodmann Areas: source correlations, coherence, and phase differences Adaptive neurofeedback: Z-Score, and LORETA Z-Score EEG Analysis Approaches
  34. 34. AMP Introduction Alertness & Memory Profiler Clinical Research Applications • Quantified excessive daytime sleepiness and neurocognitive deficits in OSA patients (NYU); quantified treatment outcomes CPAP and oral appliance therapy • Validated nutraceutical Omega-3 fatty acids efficacy in mitigating effects of sleep deprivation • Creating neurocognitive drug profiles: amphetamines, benzos, marijuana • Characterizing HIV-associated cognitive decline (UCSD, Sharp Hospital) • Identifying biomarkers for Mood Disorders, PTSD • Characterizing cognitive decline in PD/PDD (Scripps, UI) 10 neuro-psych tests with synchronized EEG and/or ECG from any B-Alert system JAVA-based platform for web delivery to any tablet or desktop interface Automated measures of cognitive engagement and workload, with comparison to normative database
  35. 35. • FDA cleared for assessment of sleep architecture and sleep continuity • Record 16+ hrs without battery charge; Easily self-applied before bed • Frontal EEG, pulse rate, snoring, head movement and position, with optional EMG or ECG • Automated sleep staging - Validation: International Archives of Medicine • Cloud based processing, over-scoring, and report generation In-home Sleep Studies
  36. 36. CNS Disease and Cognitive/Clinical Symptom Nighttime EEG Daytime EEG Parkinson’s Disease and Dementia REM Sleep w/o Atonia, EMG, Sleep Disordered Breathing, Limb Movements Asymmetries in ERPs, PSDs, and Band Ratios across Brain Regions during Resting State Mood and Anxiety REM Latency, REM Duration and Density, Light NREM, Autonomic Activation ERPs, HRV, Cordance, & Circuit-Level Engagement during Emotion Tasks Memory Functions Slow Wave Activity, Sleep Quality, Spindle Frequency and Type ERPs, Phase-Amplitude Coupling (PAC), and Coherence during Memory Tasks Attention/Executive Processes Sleep Continuity, Spindle Density, REM Density, Hypoxemia ERPs, Coherence, & Circuit-Level Engagement during Vigilance and Executive Function Tasks EEG-Based Biomarkers
  37. 37. Bandwidth Power Spectral Density (PSD) Analysis • Analyzed a (Biogen-owned) database of Healthy controls and Alzheimer’s patients: • Computed PSDs for all standard bands: delta, theta, alpha, sigma, beta, gamma. • Found statistically significant differences between AD (L) and healthy controls (R) in: – alpha: largest decrease in the parietal, posterior temporal, and right temporal – sigma: universal decrease across all regions – beta: universal decrease across all regions • Significance determined by one-way ANOVA (p < 0.05). • Results align with findings in the literature. EEG-Based AD Analysis
  38. 38. Low Resolution Electromagnetic Tomography Analysis • LORETA 3D source analysis can identify and map excessive and/or reduced current sources in the brain. • Can analyze amplitude asymmetry, EEG coherence, and EEG phase.  can compare these measures against a database of age- matched controls to detect abnormalities. Elevated sLORETA current sources were present in the parietal lobe of the postcentral gyrus and the inferior parietal lobule with a maximum at 7 Hz (Brodmann areas 2, 5, & 40) Example of LORETA with AD
  39. 39. Example of Coherence Analyses in Parkinson’s Patients implanted for DBS: Illustration of abnormal theta coherence patterns (i.e., increase in frontal, decrease in parietal) characteristic of Parkinson’s Disease (Sarnthein, 2007). Eyes Closed Z-Scored FFT Coherence from a PD patient (1005) in Theta (L), Beta (C), and High Beta (R).
  40. 40. Emotion Elicitation Testbed: International Affective Picture System (IAPS) • 1000+ emotionally stimulating pictures • Designed to investigate positive, negative, and neutral emotions • Normative ratings were developed from a large sample • Emotional Faces Image Recognition – N170 component is modulated with emotion: – Negative stimulus - Amplitude increase – Mood disorder patients – amplitude increase abolished Other Empathy/Emotion Elicitation Testbeds: • Empathy Videos: social interation, aimed to elicit mu suppression (UCSD) • Narrative Networks: storytelling paradigm based upon themes of justice (DARPA, Boeing) • Eustress/Distress Videos: clips that evoke humor and/or stress (Loma Linda Univ.) • Mental Imagery: visualization of different emotional states *Lang, P.J., Bradley, M.M., & Cuthbert, B.N. (2008). International affective picture system (IAPS): Affective ratings of pictures and instruction manual. Technical Report A-8. University of Florida, Gainesville, FL Biomarkers of Emotion
  41. 41. • Heart Rate Variability increases in response to stressful stimuli in both groups • PTS subjects exhibit increased gamma activity in response to stressful stimuli • PTS group displays a heightened response at initial stimulus onset, suggesting recognition of task but impaired attention resources and processing. • Data suggest a possible association with hypervigilance. ERPs during 3CVT Post Traumatic Stress Assessment
  42. 42. Closed-loop EEG/FES Neurorehabilitation EEG provides real-time spatial and spectral information during adaptive rehab Partnership with U Miami Project to Cure Paralysis EEG maps cortical plasticity post-injury & throughout rehab Spinal Cord Injury
  43. 43. Summit is on Lunch. (we will resume at 12:30pm Pacific Time) Chat forums will be available during the Watercooler session
  44. 44. To learn more, visit sharpbrains.com

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