Dynamic Regulation of Internal Experience

Jessica Andrews-Hanna, Ph.D.Department of Psychology; Cognitive Science Program

University of Arizona

2

Zac Irving Kieran Fox

Joanna Arch

Randy BucknerMarie Banich

Tor Wager

Sona DimidjianRosi Kaiser

Marina Lopez-Sola

Lindsay IvesRamsey Wilcox

Jessica Renger

Sydney FreidmanQuentin Raffaelli

Jonathan Smallwood

Nathan SprengDiego Pizzagalli

Tal Yarkoni

Thank You!

KalinaChristoff

Mary-Frances O’Connor

HERE AND NOW

What are you doing right now?

Were you thinking about

something other than what you were doing?

46.9%“YES”

Killingsworth & Gilbert, Science, 2010

Off-Task Thinking (i.e. “Mind-Wandering”)

“You are today where your thoughts have brought you;

you will be tomorrow where your thoughts take you.”

– James Allen (1864–1912), author.

5

How to harness the adaptive potential of human thought?

How to promote enduring change?

• Task-Related and Task-Unrelated Cognition GREEN GREEN

• Static and Dynamic Approaches

measurement

Time

measurements

Time

• Behavioral, Physiological, and Neural

• Lab and Real-World Contexts

Are our thoughts largely positive or negative? Constructive or unconstructive?

How fused are we with our thoughts? Do they bother us and “loom large” in our

mind?

Smallwood & Andrews-Hanna, FrontiersPsych, 2013; Andrews-Hanna, Smallwood & Spreng, ANYAS, 2014; Christoff, Irving, Fox, Spreng & Andrews-Hanna, NRN, 2016; Andrews-Hanna et al., in press

DYNAMIC REGULATION / CONTROL of:

WHATtopics our thoughts

concern

HOWwe relate to our

thoughts

Do we let our thoughts interfere with important activities?

WHENour thoughts occur

Are they influenced by constraints on cognition? Do our thoughts transition with

ease?

PROCESSESby which our thoughts

initiate and unfold

DYNAMIC REGULATION / CONTROL of:

Christoff, Irving, Fox, Spreng & Andrews-Hanna, NRN, 2016; Andrews-Hanna et al., in press

A Taxonomy of Thought

Christoff, Irving, Fox, Spreng & Andrews-Hanna, NRN, 2016; Andrews-Hanna et al., in press

Highly Dynamic Thoughts

Conte

nt

Time

Highly Rigid Thought / Little Dynamic “Flow”

Conte

nt

Time

Dynamics of Internal Experience

• Emotions in daily life(all types of thought)

Trampe et al., PLOS One, 2015Fox, Andrews-Hanna et al., 2015; in prep;Mills et al., submitted

• 11 studies of off-task thought, (N> 5,000)

Patterns of Thought – What is “Normal”?

On average, people tend to think about mildly positive topics, even when those topics are

unrelated to the task at hand.

“We are all preoccupied with internal thoughts. These thoughts can often be a source of excitement, anxiety, or irritation. In this experiment, we are interested in what kinds of thoughts have been on your mind lately.”

“MY COLLEGE GPA”Future-OrientedSelf-RelevantImportant / Of ValueRecurring ThoughtPositiveSocially-OrientedVividModerately Specific

…

“UPCOMING HAWAII TRIP”

“MISS MY PARENTS”“CLIMB PIKE’S PEAK”

Andrews-Hanna et al, FrontiersPsych, 2013

Thought Content, Continued…

Strongly Disagree Strongly DisagreeNeither

Self-Relevant

Of Value/Importance

Central to Self-Identity

Recurrent Thought

Strongly Agree

Personally-significant

Strongly Disagree Strongly DisagreeNeither

Social / Involve Other People

Strongly Agree

Somewhat social

Valence

Neutral Strongly PositiveStrongly Negative

Somewhat positive

Future

Past

Present/Non-temporal

Andrews-Hanna et al., 2013

Future oriented

Positive, Constructive Content is the Norm

Andrews-Hanna et al., FrontiersPsych, 2013

Depression / Negative

Affect (BDI-II + PANAS-Gen)

Rumination(RRS + RRQ-Rumination)

Mindfulness(FFMQ)

Effect Size (Standardized β)

Personal Significance / Recurrency

Valence(Posvs. Neg)

Temporal Orientation (Future vs. Past)

Specificity / Imagery

***

*

More personally-significant/ recurrent

More negative

Effect Size (Standardized β)

*

Lessspecific/ imagery

Effect Size (Standardized β)

*

*

More specific/ imagery

Less personally-significant/ recurrent

More positive*

Andrews-Hanna et al., FrontiersPsych, 2013

Well-Being Correlates of Thought Content

43% of variance explainedby thought content

31% of variance explained by thought content

45% of variance explainedby thought content

• Develop an international database of daily thinking patterns.• Explore their content, correlates, and consequences

https://play.google.com/store/apps

Where’s My Mind? App

Andrews-Hanna & Arch, in prep

• MDD = Less variable off-task thought content as related to symptoms in an experimental setting (Hoffman et al., JAD, 2016)

• Rumination predicts subsequent negative affect (Moberly & Watkins, J. Abnormal Psych, 2008)

• Negative (especially self-relevant) material more salient, “sticky,” and remembered better in MDD (Matthews & MacLeod, Ann Rev Clin Psych, 2005; Gotlib & Joorman, Ann Rev Clin Psy, 2010)

Affective Constraints on Cognition

Critical Personal

Comments

N-Back Task (1 and 2-back)

Praiseworthy Personal

Comments

N-Back Task (1 and 2-back)

Kaiser, Andrews-Hanna, Metcalf, & Dimidjian, Cog Therapy Res, 2015

Heightened Salience of Negative Information

No relationships with individual

difference measures

following praise

• Daily events perceived as more stressful in MDD (Bylsma et al., J. Abnormal Psych, 2011)• MDD and GAD = heightened & extended rumination à poorer subsequent affect &

worse symptoms (Ruscio et al., J. Abnormal Psy, 2015)

• Broad impairments in executive function in MDD (i.e. poorer inhibition, shifting, working memory updating) (Snyder, Psych Bull, 2014)

Affective Constraints on Cognition

Learned patterns of thinking and feeling a certain way

Time

Constrain thought content

Strong automatic (affective)

biases

Broad impairments in

executive function

Restrict “flow” and impede dynamic

regulation of thought

Brain mechanisms

Default Network

Salience Network

Frontoparietal Control Network

The Default Network

Default Network

• Initially defined as regions that “deactivate” during tasks as compared to “rest” (Shulman et al., JOCN, 1997; Raichle et al., PNAS, 2001)

• Subsequently called a “task-negative network” (Fox et al., PNAS, 2005)

TASK < REST

The Default Network

Default Network

• Initially defined as regions that “deactivate” during tasks as compared to “rest” (Shulman et al., JOCN, 1997; Raichle et al., PNAS, 2001)

• Subsequently called a “task-negative network” (Fox et al., PNAS, 2005)

• Better characterized by role in internally-guided cognition (Buckner, Andrews-Hanna, Schacter, ANYAS, 2008; Andrews-Hanna, Smallwood, Spreng, ANYAS, 2014)

AUTOBIOGRAPHICAL MEMORY

PROSPECTION

MENTALIZING

The Default Network

Default Network

• Comprised of at least two subsystems that interact through core “hubs” (Andrews-Hanna et al., Neuron, 2010)

The Default Network

Default Network

Affective personal significance/meaning

Meta-cognitive reflection (mentalizing self and other)

Constructive episodic simulation

• Comprised of at least two subsystems that interact through core “hubs” (Andrews-Hanna et al., Neuron, 2010)

• Components contribute differently to internally-guided cognition (Andrews-Hanna, Smallwood, Spreng, 2014)

• Also engaged when “mind-wandering” (Fox et al., NI, 2015; Andrews-Hanna et al., JNeurophys, 2010).

• DMN core may be source of automatic constraints; MT subsystem may be a source of variability / spontaneity (Christoff et al., NRN, 2016)

Frontoparietal Control Network

• Dynamic regulation of external and internal attention based on nature of task (Spreng et al., JOCN, 2010; Andrews-Hanna, Smallwood, Spreng, ANYAS, 2013)

• May buffer internal thought and external attention from distracting information (Smallwood et al., Brain Res, 2011)

• Source of “deliberate” constraints on thought (Christoff et al., NRN, 2016)

Frontoparietal Control Network

Salience Network

• Bottom-up attention to salient external and internal information (Corbetta et al., Neuron, 2008; Hermans et al., 2011)

• Communicates with frontoparietal control network and default / dorsal attention networks to up-regulate attentional resources to internal or external sources (Uddin, NRN, 2015)

• Source of “automatic constraints” on thought (Christoff et al., NRN, 2016)

Salience NetworkAversive > Neutral Films Propanolol

(beta-blocker) reduced HR

and connectivity of salience network

SN regulated by locus coeruleus vis

noradrenergic arousal mechanisms

Are brain network dynamics altered

in mood and anxiety disorders?

• Structural alterations in default, control & salience network in MDD (Drevets et al., Brain Struct Func, 2008; Koolschijn et al., HBM, 2009)

• Hyperactivity of default network in MDD (Sheline et al., PNAS, 2009; Whitfield-Gabrieli& Ford, ARCP, 2012)

• Heightened SN and amygdala activity in response to negative stimuli in MDD and anxiety; reduced frontoparietal control activity (Hamilton et al., AmJPsych, 2012; Etkin & Wager, 2007)

Neural Alterations in Mood & Anxiety Disorders

Kaiser, Andrews-Hanna, et al., SCAN, 2015

Task-related connectivity between ACC and PCC

increased with depressive symptoms

• Salience network hyperconnectivity relates to anxiety (Seeley et al., JNeurosci, 2007)

• Increase default network vs. “task positive” network dominance during rest states in MDD (Hamilton et al., BioPsych, 2011)

• Correlates with rumination

Neural Alterations in Mood & Anxiety Disorders

Hamilton et al., BioPsych, 2011

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Frontoparietal Control Network

Dorsal Attention NetworkDefault Network

Bias towards internal thoughts

Bias away fromexternal environment

General deficits in cognitive control

Kaiser, Andrews-Hanna, Wager, & Pizzagalli, JAMA Psych, 2015

Increased inDepressionReduced inDepression

Meta-Analysis of Resting State Connectivity in Depression

ALSO: 1) Dysfunctional DN-FPCN-salience network connectivity

2) Reduced limbic – accumbens and amygdala connectivity

Static connectivity

Dynamic connectivity

Measuring Brain Dynamics with Dynamic Connectivity

Hutchison et al., Neuroimage, 2013

Dynamic connectivity measures can be more sensitive markers of mental health than static measures (e.g. Damaraju et al., Neuroimage Clinical, 2014)

Measure of connectivity Accuracy predicting group status (HC, SCZ, BPD)

Static rs-fcMRI 70%Dynamic rs-fcMRI 80.5%Static + Dynamic rs-fcMRI 90%

Vanhaudenhuyse et al., JOCN, 2010; Zabelina & Andrews-Hanna, Curr Opinion Neurol, 2016, Kuyci, NI, 2017

Fluctuations in spontaneous mental states occurs at similar frequencies as resting state fMRI

Dynamic Connectivity May Relate to Ongoing Cognition

Kaiser et al., Neuropsychopharm, 2015

Dynamic connectivity in MDD

• Decreased dynamic connectivity within default network in MDD

• Increased dynamic connectivity between MPFC and both insula and dLPFC

Learned patterns of thinking and feeling a certain way

Time

Constrain thought content

Strong automatic (affective)

biases

Broad impairments in

executive function

Restrict dynamic “flow” and regulation

of thought

Default NetworkSalience Network

Frontoparietal Control Network

Promoting Enduring Change

Lane, Ryan, Nadel & Greenberg, Behav Brain Sci, 2015

Promoting Enduring Change

Lane, Ryan, Nadel & Greenberg, Behav Brain Sci, 2015

Constructive meta-cognitive reflection / reappraisal

Episodic simulation / memory retrieval

Make new meaning out of

maladaptive thought patterns

Reconsolidated internal experience

Time

Default NetworkSalience Network

Frontoparietal Control Network

Reduce automatic (affective)

biases

Strengthen attentional

control

Facilitate dynamic “flow” and regulation

of thought

Less affectively constrained

thought content

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Thank You!

KalinaChristoff

Mary-Frances O’Connor

Zac Irving Kieran Fox

Joanna Arch

Randy BucknerMarie Banich

Tor Wager

Sona DimidjianRosi Kaiser

Marina Lopez-Sola

Lindsay IvesRamsey Wilcox

Jessica Renger

Sydney FreidmanQuentin Raffaelli

Jonathan Smallwood

Nathan SprengDiego Pizzagalli

Tal Yarkoni