Common and Distinct Neural Correlates of Human Avoidance and Safety Learning
Poster No:
570
Submission Type:
Late-Breaking Abstract Submission
Authors:
Lieselotte Claes1,2, Trevor Steward3, Kim Felmingham3, Patrick Laing4, Christopher Davey1, Bradford Moffat5, Rebecca Glarin5, Bram Vervliet2, Ben Harrison1
Institutions:
1Department of Psychiatry, The University of Melbourne, Melbourne, Australia, 2Laboratory of Biological Psychology, KU Leuven, Leuven, Belgium, 3Melbourne School of Psychological Sciences, Melbourne, Australia, 4Department of Psychiatry and Behavioural Sciences, University of Texas, Texas, United States, 5The Melbourne Brain Centre Imaging Unit, Department of Radiology, The University of Melbourne, Melbourne, Australia
First Author:
Lieselotte Claes
Department of Psychiatry, The University of Melbourne|Laboratory of Biological Psychology, KU Leuven
Melbourne, Australia|Leuven, Belgium
Department of Psychiatry, The University of Melbourne|Laboratory of Biological Psychology, KU Leuven
Melbourne, Australia|Leuven, Belgium
Co-Author(s):
Patrick Laing
Department of Psychiatry and Behavioural Sciences, University of Texas
Texas, United States
Department of Psychiatry and Behavioural Sciences, University of Texas
Texas, United States
Bradford Moffat
The Melbourne Brain Centre Imaging Unit, Department of Radiology, The University of Melbourne
Melbourne, Australia
The Melbourne Brain Centre Imaging Unit, Department of Radiology, The University of Melbourne
Melbourne, Australia
Rebecca Glarin
The Melbourne Brain Centre Imaging Unit, Department of Radiology, The University of Melbourne
Melbourne, Australia
The Melbourne Brain Centre Imaging Unit, Department of Radiology, The University of Melbourne
Melbourne, Australia
Introduction:
Persistent avoidance and deficits in safety learning play a major role in maintaining anxiety disorders (Craske et al., 2009; Duits et al. 2015; Lissek et al., 2009). At the brain circuitry level, safety learning has been broadly linked to activity in the ventromedial prefrontal cortex (vmPFC), hippocampus and posterior cingulate cortex (PCC; Fullana et al., 2016). Whether this neural circuitry also drives avoidance learning and associated safety behaviours remains unclear. Our aim was to answer this question using a novel avoidance and safety learning paradigm combined with 7T functional magnetic resonance imaging (fMRI).
Methods:
91 healthy control participants were recruited (age: 22.81 ±4.34 years, 55% female). The paradigm consisted of 2 main task phases, 'conditioning' and 'avoidance'. Participants were first conditioned to two threat stimuli (A+, D+) and a compound safety stimulus (AX-). Participants were then trained to successfully avoid the D+ (avoidable) versus A+ (unavoidable) stimuli. Participant expectancy ratings and avoidance responses confirmed their successful learning of the task contingencies. SPM 12 general linear models were used to characterise brain responses to 1) successful avoidance vs unsuccessful avoidance (D+av vs A+unav), 2) successful avoidance vs safety learning (D+av vs AX-cond) and 3) successful early vs late successful avoidance learning (first vs last 4 trials of D+av ). These contrasts were corrected for multiple comparisons at pFDR<0.05 (KE≥5).
Results:
Successful avoidance versus unsuccessful avoidance learning was associated with significant activation of the lateral frontopolar cortex, posterior vmPFC, dorsolateral prefrontal cortex, primary somatosensory cortex, dorsal PCC, and intraparietal sulcus, among other areas. Successful avoidance versus safety learning also demonstrated broad activation differences including involvement of the anterior and posterior vmPFC, rostral and dorsal anterior cingulate cortex, PCC, dorsolateral prefrontal cortex, and ventral caudate nucleus/accumbens. When comparing early to late avoidance learning, early learning was distinctly associated with activation of the periaqueductal gray (PAG), mediodorsal thalamus, right anterior insular cortex, and right ventrolateral putamen.
Conclusions:
Avoidance learning appears to rely on both shared and distinct brain mechanisms when compared to safety learning, with notable shared involvement of the vmPFC and PCC, but apparent distinct involvement of threat-responsive regions during early avoidance, including PAG, thalamus and insular cortex. To what extent the initial engagement of the threat circuitry influences subsequent avoidance learning and behaviour, including neural computations of safety in vmPFC-PCC, will be important questions for ongoing work.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Learning and Memory:
Learning and Memory Other
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI) 2
Novel Imaging Acquisition Methods:
BOLD fMRI
Keywords:
Affective Disorders
Anxiety
FUNCTIONAL MRI
Learning
Psychiatric Disorders
Other - safety
1|2Indicates the priority used for review
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Provide references using APA citation style.
Duits, P., Cath, D. C., Lissek, S., Hox, J. J., Hamm, A. O., Engelhard, I. M., van den Hout, M. A., & Baas, J. M. P. (2015). Updated meta-analysis of classical fear conditioning in the anxiety disorders. Depression and Anxiety, 32(4), 239–253. https://doi.org/10.1002/da.22353
Fullana, M. A., Harrison, B. J., Soriano-Mas, C., Vervliet, B., Cardoner, N., Àvila-Parcet, A., & Radua, J. (2016). Neural signatures of human fear conditioning: An updated and extended meta-analysis of fMRI studies. Molecular Psychiatry, 21(4), Article 4. https://doi.org/10.1038/mp.2015.88
Lissek, S., Rabin, S. J., McDowell, D. J., Dvir, S., Bradford, D. E., Geraci, M., Pine, D. S., & Grillon, C. (2009). Impaired discriminative fear-conditioning resulting from elevated fear responding to learned safety cues among individuals with panic disorder. Behaviour Research and Therapy, 47(2), 111–118. https://doi.org/10.1016/j.brat.2008.10.017