A Dynamical Bifurcation Model of Bipolar Disorder Based on Learned 2 Expectation

8 Bipolar disorder is a common psychiatric dysfunction characterized by recurring episodes of mania and 9 depression. Despite its prevalence, the causes and mechanisms of bipolar disorder remain largely 10 unknown. Recently, theories focusing on the interaction between emotion and behavior, including those 11 based on dysregulation of the so-called Behavioral Approach System (BAS), have gained popularity. 12 Mathematical models built on this principle predict bistability in mood but do not involve intrinsic 13 biological rhythms arising from interactions between mood and expectation. We develop and analyze a 14 model with clinically meaningful and modifiable parameters that incorporates the interaction between 15 mood and expectation and that exhibits a transition to limit cycle behavior when a mood sensitivity 16 parameter exceeds a threshold value, signalling a transition to a bipolar state. The model also predicts 17 that asymmetry in response to positive and negative events can induce unipolar depression/mania, 18 consistent with clinical observations. Finally, we show how observed effects of lithium and 19 antidepressant-induced mania can be explained within the framework of our proposed model. 20 Corresponding author: Tom Chou, tomchou@ucla.edu Copyright ©2018 The Author(s). Published by MIT Press. All Rights Reserved. == D R A F T April 10, 2018 (Received ) == Journal: COMPUTATIONAL PSYCHIATRY / Title: Authors: Shyr-Shea Chang and Tom Chou INTRODUCTION Bipolar disorder is characterized by cycling between manic and depressive episodes (Geller & Luby, 21 1997). Its prevalence is estimated to be 0.3%−1.5% of the total population (Weissman et al., 1996). The 22 lifetime cost for a single patient can reach several million US dollars (Begley et al., 2001) and medication 23 use associated with bipolar disorder comprises about 7% of that used to treat all mental disorders 24 (Whiteford et al., 2013). Bipolar disorder has a serious societal impact, with early onset a major risk 25 factor for suicide (Hawton, Sutton, Haw, Sinclair, & Harriss, 2005), and 65.5 work days lost per year per 26 patient (Kessler et al., 2006). Despite the significance of bipolar disorder, there is limited understanding 27 of its biological mechanism (Geddes & Miklowitz, 2013). Modern techniques such as functional 28 magnetic resonance imaging (fMRI) have located neural circuits including limbic networks and 29 attentional systems, whose dysfunction may be correlated with bipolar disorder (Chen, Suckling, Lennox, 30 Ooi, & Bullmore, 2011; Strakowski, Adler, Holland, Mills, & DelBello, 2004). However, how the 31 dysfunction of these circuits leads to emotional vulnerability remains unclear. 32 In order to understand the mechanism of bipolar disorder and accelerate the development of treatment 33 (Geddes & Miklowitz, 2013) many mathematical models have been proposed and fit to experimental 34 data. An oscillation in mood, either observed or self-reported, is the defining feature of bipolar disorder 35 (Geller & Luby, 1997). Thus, early models focus on explaining this oscillation (Bonsall, Geddes, 36 Goodwin, & Holmes, 2015; Daugherty et al., 2009; Goldbeter, 2011). The models describe mood as 37 being formed from an intrinsically oscillatory brain circuit and explain self-reported mood scores as well 38 as the effects of medication. Following these studies, a natural next step is to clarify the mechanism of 39 the oscillations and distinguish key differences between normal individuals and patients with bipolar 40 disorder (see also Goldbeter (2011)). A popular theory in psychology states that dysregulation of the 41 Behavioral Approach System (BAS) and the resulting interaction between mood, expectation, and 42 behavior can explain bipolar disorder (Urošević, Abramson, Harmon-Jones, & Alloy, 2008). 43 Psychological observations provide evidence of malfunction of the BAS and models have been built to 44 explain bipolar disorder based on this malfunction (Steinacher & Wright, 2013). A key difference 45 between BAS-based models and previous models is that BAS models show bistability in mood instead of 46 oscillations, and require external input or noise to trigger switching between states of mania and 47 depression (Cochran, Schultz, McInnis, & Forger, 2017). 48