Graph theory analysis of whole brain functional connectivity to assess disturbances associated with suicide attempts in bipolar disorder

Abstract

Brain targets to lower the high risk of suicide in Bipolar Disorder (BD) are needed. Neuroimaging studies employing analyses dependent on regional assumptions could miss hubs of dysfunction critical to the pathophysiology of suicide behaviors and their prevention. This study applied intrinsic connectivity distribution (ICD), a whole brain graph‐theoretical approach, to identify hubs of functional connectivity (FC) disturbances associated with suicide attempts in BD. ICD, from functional magnetic resonance imaging data acquired while performing a task involving implicit emotion regulation processes important in BD and suicide behaviors, was compared across 40 adults with BD with prior suicide attempts (SAs), 49 with BD with no prior attempts (NSAs) and 51 healthy volunteers (HVs). Areas of significant group differences were used as seeds to identify regional FC differences and explore associations with suicide risk-related measures. ICD was significantly lower in SAs than in NSAs and HVs in bilateral ventromedial prefrontal cortex (vmPFC) and right anterior insula (RaIns). Seed connectivity revealed altered FC from vmPFC to bilateral anteromedial orbitofrontal cortex, left ventrolateral PFC (vlPFC) and cerebellum, and from RaIns to right vlPFC and temporopolar cortices. VmPFC and RaIns ICD were negatively associated with suicidal ideation severity, and vmPFC ICD with hopelessness and attempt lethality severity. The findings suggest that SAs with BD have vmPFC and RaIns hubs of dysfunction associated with altered FC to other ventral frontal, temporopolar and cerebellar cortices, and with suicidal ideation, hopelessness, and attempt lethality. These hubs may be targets for novel therapeutics to reduce suicide risk in BD.

An Agent-Based Model to Reproduce the Boolean Logic Behaviour of Neuronal Self-Organised Communities through Pulse Delay Modulation and Generation of Logic Gates

“…Such indicators would deliver useful information on the topological characteristics of the connectome, so that certain clustered areas-known as "hubs" [92]-could be avoided (shorter paths) or crossed (longer paths), whereas vulnerability-related indicators could provide very valuable information on which alternative paths to follow when certain connections (structural or functional) are damaged or even severed-neuroplasticity in practice. They have already been studied on a brain regional level [93][94][95][96], but not on a neuron level like suggested here.…”

An agent based model (ABM) to reproduce the boolean logic behaviour of neuronal self organized communities through pulse delay modulation and generation of logic gates

“…They would deliver useful information on the topological characteristics of the connectome, so that certain clustered areas –known as “hubs” [86]– could be avoided (shorter paths) or crossed (longer paths), whereas vulnerability-related indicators could provide very valuable information on which alternative paths to follow when certain connections (structural or functional) are damage or even severed - neuroplasticity in practice. Such parameters have already been studied on a brain regional level [87, 88, 89, 90], but not on a neuron level like suggested here. A graph-based approach entails two self-evident ramifications for brain networks: the multi-scale approach - in both time [91] and space [92] and the involvement of Graph Neural Networks [93, 94, 95, 96, 97] or similarly-flavoured neural network techniques [98, 99] - notwithstanding the aforementioned caveats.…”

Review of the Brain’s Behaviour after Injury and Disease for Its Application in an Agent-Based Model (ABM)

“…It affects 1 in 100 people worldwide and lists among the leading causes of disability for young patients, yielding cognitive and behavioural impairment which may induce cardiopathies [ 309 ] and/or lead to suicide during the worst episodes [ 310 ]. Connectivity issues are similar to those of MDD, adding an important decoupling between functional and structural pathways that is strongly correlated with suicide attempts [ 311 , 312 ].…”

“…Graph (neural) networks are also pertinent because of their ability to capture the network’s topology—that is, structural connectivity [ 460 ]—and include it into the information flow, with the backbone of graph theory behind it [ 238 , 312 , 461 , 462 , 463 ]. Some examples have already been cited, providing promising results [ 28 , 31 , 32 ].…”