The UAMS/PRI Brain Imaging Research Center (BIRC)

PRI Advisory Board meeting, February 7, 2017Topics• Why the significant financial investment?• What goals drove its development?• What is it and why should I be excited about it?• Who is it?• What does it value as its greater

accomplishments?• Where is it going?• How can I help it?

The “why” of your Brain Imaging Research Center

• Psychiatric disorders are brain disorders• Most psychiatric disorders are developmental disorders

reflecting altered brain development• Susceptible and resilient responses to risk factors

reflect brain responses to these risk factors• The course of illness reflects the course of brain

functional and structural organization • Treatment response is determined by (1) brain states

prior to treatment and (2) brain changes during treatment

Human functional brain imaging is the biotechnology of psychiatry, seeking the “how” behind these associations

The challenge of defining human brain-behavior relationships

The adult human brain is an amazingly complex information processing system• Its estimated 86 billion neurons each make

an average of 100,000 connections resulting in 8.6 quadrillion possible functional interactions

• Complex brain functions represent the product of time-varying combinations of its functional connectivity

• The BIRC focus is on exploration of spatial-temporal properties of brain organization

The “what” in your Brain Imaging Research Center

A center of excellence in brain imaging technology development and its application to

clinical problem solvingAnd…

A center of excellence in education, training and career development towards a next generation of

more impacting imaging scientists

The “where” of your Brain Imaging Research Center

The promise of functional brain imaging

Behavior

Experience

Behavior

Experience

Behavior

Experience

Behavior

Experience

The single most impressive/important thing that we have learned from functional brain imaging

TIM

E

“Birth gives you a brain. Life turns it into a mind”

Modified from Jeffrey Eugenides

The “what” in your Brain Imaging Research Center

Areas of technology, research and training emphasis:• Outcomes related to early life exposure to

trauma and adversity• Human brain development• Women’s health• Human brain variation: cognition• Drug addiction

Wildeman et al. JAMA Pediatrics168(8):706-713, 2014

Age-Specific Risk for First Confirmed Maltreatment in 2011

Proportion of Children Having Ever Experienced Confirmed Maltreatment in 2011

Estimated cumulative risk of confirmed maltreatment of US children

Synthetic cohort life tables for 2003-2011 CPS data of confirmed cases

The “Who” in your Brain Imaging Research Center

Practical examples of the focus, approach, outcomes and impact of the BIRC: Drug

addiction

Addiction is a chronically relapsing, trauma-related, developmental disorder and major public health problem associated with partially effective

treatments

Stages of the Addiction Process and Corresponding Strategies to Halt

AddictionD

RU

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Impulsive Use

ADDICTION

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INITIATION

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Risk/Resiliency Factors

trauma

4

12

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3Addiction as an acquired brain state

Altered decision making in at-risk adolescents

Predicting treatment response

3

1

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Variation in risk for relapse4

The resilient brain5

Addiction as an acquired brain disorder

Neurobiological advances from the brain disease model of addiction

Volkow ND, Koob GF, McClellan ATN Eng J Med 374(4):363371, 2016

Brain signature of addiction

Performance accuracyTraining sample (LOOCV)

specificity 90%sensitivity 85%

Test sample (independent)specificity 90%sensitivity 75%

Individual addiction classification scores predict trait impulsiveness and cocaine use

Cocaine dependent subjectsBIS-11 (motor impulsiveness): r = 0.43, p < 0.01cocaine use (years): r = 0.52, p < 0.005

Healthy comparison subjectsBIS-11 (motor impulsiveness): r =0.48, p < 0.05

Inferences• Cocaine addiction related to disorganization of the brain

mechanisms of behavioral control• Represents acquired brain state due to prolonged, intermittent

cocaine abuse

Stages of the Addiction Process and Corresponding Strategies to Halt

AddictionD

RU

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MS

TIME

Impulsive Use

ADDICTION

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Treatment

Intervention

None

INITIATION

Prevention

MAINTENANCEDE

VELO

PMEN

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Risk/Resiliency Factors

trauma

4

12

5

3Addiction as an acquired brain state

Altered decision making in at-risk adolescents

Predicting treatment response

3

1

2

Variation in risk for relapse4

The resilient brain5

Impulsive choice behavior in adolescence as a modifiable risk factor

for addition

the heightened impatience of adolescence predicts adolescent drug use and is

predicted by variation in the faculty for future-oriented thought

Figure 1. Valuation Network: Larger Later (LL) Choice Trials vs. Control Trials

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00.20.40.60.8

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LL vs. Control trials

lnK

R = 0.45p = 0.013

amygdala

hippocampus

ventromedial prefrontal cortex

insula

1a. Network Map: Regions of Coactivation

1b. Correlation between lnkand Network Activation

Greater network activation related to preference for the present predicts more impulsive choices

Controlling for age, sex and drug use frequency: r = 0.56, p = 0.004

$350 today? or

$1,000 in 6 months?

-1.5

-1

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0

0.5

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SS vs. Control trials

lnK

R = -0.41p = 0.023

Figure 2. Cognitive Control/Executive Function Network: Smaller Sooner (SS) Choice Trials vs. Control Trials

mid-cingulate cortex

dorsomedialprefrontal cortex

dorsolateralprefrontal cortex

precuneus

inferior parietal cortex

2a. Network Map: Regions of Coactivation

2b. Correlation between lnkand Network Activation

Greater network activation related to preference for the future predicts less impulsive choices

Controlling for age, sex and drug use frequency: r = -0.44, p = 0.029

$350 today? or

$1,000 in 6 months?

-1.8

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Valu

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Net

wor

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Cognitive Control Network

r= -0.67, p< 0.0001

Individual differences in choice impulsivity due to relative activation of two neural processing networks? .

Competition between brain states of present and future preference predicts choice impulsivity

All decision making vs control trials

Stages of the Addiction Process and Corresponding Strategies to Halt

AddictionD

RU

G U

SE P

RO

BLE

MS

TIME

Impulsive Use

ADDICTION

Com

pulsi

ve U

se

Treatment

Intervention

None

INITIATION

Prevention

MAINTENANCEDE

VELO

PMEN

T

Risk/Resiliency Factors

trauma

4

12

5

3Addiction as an acquired brain state

Altered decision making in at-risk adolescents

Predicting treatment response

3

1

2

Variation in risk for relapse4

The resilient brain5

What behavioral and brain states predict treatment attempts to reduce adolescent

drug misuse?

Each year of delay in the onset of adolescent drug misuse decreases the probability of adult drug use

disorders by 8-10%

Predicting drug use in at-risk adolescents$350 today?

or $1,000 in 6

months?

Level of recruitment of a pDMN involved in episodic future thinking predicts subsequent decreases in drug use during treatment

The future of the BIRC and the furtherance of its impact

Data Science!

Typical resting state fMRI study has approximately 113 million data elements

Q&A: Joshua Gordon, NIMH Director Psychiatry needs more

mathematics The US National Institute of Mental Health (NIMH) has a new director. On 12 September, psychiatrist Joshua Gordon took the reins at the institute, which has a budget of US$1.5 billion. He previously researched how genes predispose people to psychiatric illnesses by acting on neural circuits, at Columbia University in New York City. His predecessor, Thomas Insel, left the NIMH to join Verily Life Sciences, a start-up owned by Google’s parent company Alphabet, in 2015. Gordon says that his priorities at the NIMH will include “low-hanging clinical fruit, neural circuits and mathematics — lots of mathematics”, and explains to Nature what that means.

Keith Bush PhD

Education:BS Chemical Engineering, Univ PennMS Computer Science, Colorado StatePhD Computer Science, Colorado StatePostDoc in Machine Learning, McGill Univ

Career Goal: Become an international leader in the research and development of computational neuroscience and its clinical applications.

Career Workforce Setting: academia

Career Development Plan: Exploit real-time fMRI-guided neuromodulation in engineering control systems to characterize the neural basis of volition and its relationship to psychiatric disorders, emphasizing mood and emotion disregulation.

Skill Development Focus: Develop expert knowledge of the neurological and psychophysiological bases of cognitive control and emotion processing.

Assistant Professor

Michael Chung PhD

Education:BS Biology, National Central University,

TaiwanMS Statistics, University of ArkansasPhD Mathematics, University of Arkansas

Career Goal: an independent, productive investigator exploring the population-level multivariate association of genetic and neuroimaging variables with risk for and expression of drug use and other behavioral states

Career Workforce Setting: academia

Career Development/Mentoring Plan: Big data science approach integrating human neuroscience, genetics, computer science, and mathematics

Skill Development Focus: Application of deep learning and machine learning to high dimensional brain imaging and genetic data within large data bases

T32 Post-doctoral traineeMentors: Keith Bush and Clint Kilts

Thank you