O27. Developing a Directly Translational, Non-Subjective Measure of Individual Differences in Negative Affective Bias in Mood and Anxiety Disorders

2019 ◽  
Vol 85 (10) ◽  
pp. S116
Author(s):  
Jessica Aylward ◽  
Lucie Daniel-Watanabe ◽  
Oliver Robinson
2017 ◽  
Author(s):  
Jessica Aylward ◽  
Claire Hales ◽  
Emma Robinson ◽  
Oliver J Robinson

AbstractBackgroundMood and anxiety disorders are ubiquitous but current treatment options are ineffective for large numbers of sufferers. Moreover, recent years have seen a number of promising pre-clinical interventions fail to translate into clinical efficacy in humans. Improved treatments are unlikely without better animal-human translational pipelines. Here, we directly adapt–i.e. back-translate - a rodent measure of negative affective bias into humans, and explore its relationship with a)pathological mood and anxiety symptoms (study one) and b)transient induced anxiety (study two).MethodParticipants who met criteria for mood or anxiety disorder symptomatology according to a face-to-face neuropsychiatric interview were included in the symptomatic group. N = 77(47 asymptomatic; Female = 21; 30 symptomatic; Female = 25) participants completed study one and N = 47 asymptomatic participants (25 female) completed study two. Outcome measures were choice ratios, reaction times and parameters recovered from a computational model of reaction time; the drift diffusion model (DDM).ResultsSymptomatic individuals demonstrated increased negative affective bias relative to asymptomatic individuals (proportion high reward = 0.42(SD = 0.14), and 0.53(SD = 0.17), respectively) as well as reduced DDM drift rate (p = 0.004). No significant effects were observed for the within-subjects anxiety-induction in study 2.ConclusionHumans with pathological anxiety symptoms directly mimic rodents undergoing anxiogenic manipulation. The lack of sensitivity to transient anxiety suggests the paradigm may, moreover, be primarily sensitive to clinically relevant symptoms. Our results establish a direct translational pipeline (and candidate therapeutics screen) from negative affective bias in rodents to pathological mood and anxiety symptoms in humans, and link it to a computational model of reaction time.


2019 ◽  
Vol 50 (2) ◽  
pp. 237-246 ◽  
Author(s):  
Jessica Aylward ◽  
Claire Hales ◽  
Emma Robinson ◽  
Oliver J. Robinson

AbstractBackgroundMood and anxiety disorders are ubiquitous but current treatment options are ineffective for many sufferers. Moreover, a number of promising pre-clinical interventions have failed to translate into clinical efficacy in humans. Improved treatments are unlikely without better animal–human translational pipelines. Here, we translate a rodent measure of negative affective bias into humans, exploring its relationship with (1) pathological mood and anxiety symptoms and (2) transient induced anxiety.MethodsAdult participants (age = 29 ± 11) who met criteria for mood or anxiety disorder symptomatology according to a face-to-face neuropsychiatric interview were included in the symptomatic group. Study 1 included N = 77 (47 = asymptomatic [female = 21]; 30 = symptomatic [female = 25]), study 2 included N = 47 asymptomatic participants (25 = female). Outcome measures were choice ratios, reaction times and parameters recovered from a computational model of reaction time – the drift diffusion model (DDM) – from a two-alternative-forced-choice task in which ambiguous and unambiguous auditory stimuli were paired with high and low rewards.ResultsBoth groups showed over 93% accuracy on unambiguous tones indicating intact discrimination, but symptomatic individuals demonstrated increased negative affective bias on ambiguous tones [proportion high reward = 0.42 (s.d. = 0.14)] relative to asymptomatic individuals [0.53 (s.d. = 0.17)] as well as a significantly reduced DDM drift rate. No significant effects were observed for the within-subjects anxiety-induction.ConclusionsHumans with pathological anxiety symptoms directly mimic rodents undergoing anxiogenic manipulation. The lack of sensitivity to transient anxiety suggests the paradigm might be more sensitive to clinically relevant symptoms. Our results establish a direct translational pipeline (and candidate therapeutics screen) from negative affective bias in rodents to pathological mood and anxiety symptoms in humans.


2021 ◽  
Author(s):  
Anne Kuehnel ◽  
Michael Czisch ◽  
Philipp G Saemann ◽  
Elisabeth B Binder ◽  
Nils B Kroemer ◽  
...  

Background: Chronic stress is an important risk factor in the etiology of mood and anxiety disorders, but exact pathomechanisms remain to be understood. Mapping individual differences of acute stress-induced neurophysiological changes, especially on the level of neural activation and functional connectivity (FC), could provide important insights in how variation in the individual stress response is linked to disease risk. Methods: Using an established psycho-social stress task flanked by two resting-state scans, we measured subjective, physiological, and brain responses to acute stress and recovery in 217 unmedicated participants with and without mood and anxiety disorders. To estimate block-wise changes in stress-induced brain activation and FC, we used hierarchical mixed-effects models based on denoised timeseries within a predefined stress network. We predicted inter- and intra-individual differences in stress phases (anticipation vs. acute stress vs. recovery) and transdiagnostic dimensions of stress reactivity using elastic net and support vector machines. Results: We identified four subnetworks showing distinct changes in FC over time. Subnetwork trajectories predicted the stress phase (accuracy: 71%, pperm<.001) and increases in pulse rate (R2 =.10, pperm<.001). Critically, individual spatio-temporal trajectories of changes across networks also predicted negative affectivity (ΔR2=.08, pperm=.009), but not the presence or absence of a mood and anxiety disorder. Conclusions: Spatio-temporal dynamics of brain network reconfiguration induced by stress reflect individual differences in the psychopathology dimension negative affectivity. These results support the idea that vulnerability for mood and anxiety disorders can be conceptualized best at the level of network dynamics, which may pave the way for improved prediction of individual risk.


2011 ◽  
Author(s):  
D. Ryan Hooper ◽  
Michael J. Ross ◽  
Jillon S. Vander Wal ◽  
Terri L. Weaver

2019 ◽  
Vol 42 (2) ◽  
pp. 158-168
Author(s):  
Janie Houle ◽  
Stephanie Radziszewski ◽  
Préscilla Labelle ◽  
Simon Coulombe ◽  
Matthew Menear ◽  
...  

2001 ◽  
Author(s):  
David J. Nutt ◽  
Caroline Bell ◽  
Christine Masterson ◽  
Clare Short

Author(s):  
Hailey Saunders ◽  
Elizabeth Osuch ◽  
Kelly Anderson ◽  
Janet Martin ◽  
Abraham Kunnilathu ◽  
...  

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