The Role of Priors, Surprise and Brain Damage on Mental Model Updating by Alexandre Leo ...

161 Pages·2017·8.65 MB·English

Adapting to Change: The Role of Priors, Surprise and Brain Damage on Mental Model
Updating

by
Alexandre Leo Stephen Filipowicz

A thesis
presented to the University of Waterloo
in the fulfillment of the
thesis requirement for the degree of
Doctor of Philosophy
in
Psychology

Waterloo, Ontario, Canada, 2017
© Alexandre Leo Stephen Filipowicz 2017
Examining Committee Membership

The following served on the Examining Committee for this thesis. The decision of the
Examining Committee is by majority vote.

External Examiner Dr. Suzanna Becker
Professor

Supervisor(s) Dr. James Danckert
Professor

Dr. Britt Anderson
Associate Professor

Internal Member Dr. Stephanie Denison
Assistant Professor

Internal-external Member Dr. Paul Marriott
Professor

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Author’s Declaration

I hereby declare that I am the sole author of this thesis. This is a true copy of the thesis,
including any required final revisions, as accepted by my examiners.

I understand that my thesis may be made electronically available to the public.

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Abstract
To make sense of the world, humans build mental models that guide actions and
expectations. These mental models need to be receptive to change and updated when they
no longer accurately predict observations from an environment. Although ubiquitous in
our everyday lives, research is still uncovering the factors that guide mental model
building and updating. A significant challenge arises from the need to characterize how
mental models can be both robust to noisy, stochastic fluctuations, while also being
flexible to environmental changes. The current thesis explores this trade-off by
examining some of the main components involved in updating. Chapter 2 proposes a
novel task to measure the influence of prior mental models on the way new information is
integrated. Chapter 3 tests the role of unexpected, ‘surprising’ events on our ability to
detect changes in the environment. Chapter 4 measures the strategies used to explore new
mental models, after a change has been detected, and how specific forms of brain damage
influence these strategies. The results from this thesis provide novel insights into the
behavioural and neural mechanisms that underlie mental model updating. The last chapter
situates these results in existing literature, and suggests directions for future research.

iv
Acknowledgements

I would like to begin by thanking my supervisors, Dr. James Danckert & Dr. Britt
Anderson, for their tremendous support and guidance throughout my graduate studies.
You have both been instrumental in developing my skills as a researcher and I could not
have asked for better academic mentors. I would also like to thank the members of my
defense committee, Dr. Suzanna Becker, Dr. Paul Marriott, and Dr. Stephanie Denison,
for offering to read and comment on my thesis work. Your time and effort are deeply
appreciated.
To the present/past members of the DAAG Lab and Brittlab, thank you for your
years of comments, advice, and camaraderie. I would particularly like to thank Nadine
Quehl for all of her help with patient recruitment, and Dr. Elisabeth Stöttinger (my
unofficial third supervisor), Dr. Derick Valadao, and Syaheed Jabar for the stimulating
(and often challenging) discussions that were crucial in developing to the work presented
in this thesis.
To my parents, Christine and Stephen, thank you for always encouraging my
interests and providing me with an enriching environment in which to grow. To my
brother Josef, thank you for keeping me in check. To my children William and
Madeleine, thank you for lighting my life and being there when I needed you most.
And finally and most importantly, to my wife Candice, thank you for your
incredible love and support throughout these often trying times. None of this would have
been possible without you.

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For June.

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Table of Contents

List of Tables ...................................................................................................................... x

List of Figures .................................................................................................................... xi

Chapter 1: Introduction ....................................................................................................... 1

Chapter 2: The Influence of Priors on Mental Model Building .......................................... 4

2.1. Introduction .............................................................................................................. 4

2.2. Experiment 2.1: Methods ......................................................................................... 8

Participants .................................................................................................................. 8

Plinko task environment ............................................................................................. 9

Experimental conditions ........................................................................................... 11

Measuring accuracy .................................................................................................. 12

Measuring learning rates ........................................................................................... 13

Characterizing participant prior mental models ........................................................ 14

2.3 Experiment 2.1: Results .......................................................................................... 15

Participants exhibit heterogeneous prior mental models .......................................... 15

Prior group performance when exposed to Wide Gaussian distributions ................. 17

Prior group performance when exposed to Narrow Gaussian distribution ............... 22

2.4. Experiment 2.1: Discussion ................................................................................... 24

Chapter 3: The Role of Surprise in Change Detection ..................................................... 27

3.1. Introduction ............................................................................................................ 27

3.2. Experiment 3.1: Methods ....................................................................................... 30

Participants ................................................................................................................ 30

Experimental conditions ........................................................................................... 30

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Computing surprise ................................................................................................... 31

3.3. Experiment 3.1: Results ......................................................................................... 35

Updating accuracy is worse with no breaks .............................................................. 35

Participants can represent a number of distinct distributions ................................... 40

Participants in the continuous condition demonstrate more hysteresis .................... 40

Surprise positively predicts updating in the continuous condition ........................... 41

3.4. Experiment 3.1: Discussion ................................................................................... 44

3.5. Experiment 3.2: Methods ....................................................................................... 45

Participants ................................................................................................................ 45

Experimental conditions ........................................................................................... 45

3.6. Experiment 3.2: Results ......................................................................................... 49

Updating is worst for low surprise shifts .................................................................. 49

High surprise shifts do not always lead to better updating ....................................... 53

3.7. Experiment 3.2: Discussion ................................................................................... 63

3.8. Discussion .............................................................................................................. 65

Chapter 4: The Influence of Brain Damage on Exploration ............................................. 67

4.1. Introduction ............................................................................................................ 67

4.2. Experiment 4.1: Methods ....................................................................................... 73

Participants ................................................................................................................ 73

Lesion tracing and analysis ....................................................................................... 78

PROBE Task ............................................................................................................. 79

Computational Models .............................................................................................. 84

PROBE model ........................................................................................................... 84

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Reinforcement Learning (RL) Model ....................................................................... 87

Model fitting methods ............................................................................................... 87

4.3. Experiment 4.1: Results ......................................................................................... 88

Demographic differences .......................................................................................... 88

Behvavioural Performance ........................................................................................ 89

Updating Performance in Recurrent vs Open Sessions ............................................ 92

Good and Poor Updaters ........................................................................................... 96

Model fits of patient behaviour ............................................................................... 104

Model parameter differences between participant groups ...................................... 108

Lesion analyses ....................................................................................................... 109

4.4. Experiment 4.1: Discussion ................................................................................. 113

Chapter 5: General Discussion ........................................................................................ 122

References ....................................................................................................................... 128

Appendix 1 ...................................................................................................................... 143

Model descriptions ...................................................................................................... 143

PROBE model description ...................................................................................... 143

Reinforcement Learning model description ............................................................ 149

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List of Tables
Table 2.1. Mean performance parameters for prior distribution groups. ………………..20

Table 3.1. Experiment 3.2 estimated performance parameters. …………………………39

Table 3.2. Comparison of expected surprise measures for each switch type. ………......48

Table 3.3. Experiment 3.2 estimated performance parameters. …………………………52

Table 3.4. Influence of trial and surprise on likelihood of updating. ……………………62

Table 4.1 Patient demographics for RBD group. ………………………………………..75

Table 4.2 Patient demographics for LBD group. ………………………………………..75

Table 4.3 PROBE and RL Model Parameter Fits. ……………………………………..105

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