Emotional responses (intensity/valence) fulfill RDoC criteria but remain excluded from diagnostic classifications of mood disorders
Abstract
Categorical classifications of depression, such as DSM-5 and ICD, are limited by high clinical heterogeneity, arbitrary diagnostic thresholds, and weak links to underlying pathophysiology. In line with the Research Domain Criteria (RDoC) framework, this article proposes a dimensional and mechanistic approach centered on emotional responses as core transdiagnostic features of mood disorders. Emotional responses are conceptualized along two fundamental dimensions: intensity (arousal) and hedonic valence. Evidence from clinical, psychophysiological, neuroimaging, and preclinical studies indicates that depressive episodes may be characterized by either emotional hyporeactivity (emotional blunting and reduced responsiveness) or emotional hyperreactivity (heightened distress, anxiety, irritability, and emotional lability), the latter being closely associated with mixed features, particularly in bipolar depression. In parallel, depression is marked by maladaptive valence attribution, encompassing anhedonia related to reward-system dysfunction and a pervasive negativity bias. Preclinical findings implicate dysregulated basolateral amygdala circuits in valence attribution and demonstrate the reversibility of negativity bias with antidepressant interventions. Integrating emotional intensity and valence within an RDoC-informed framework provides a biologically grounded account of depressive heterogeneity, refines the characterization of mixed states, and offers clinically relevant guidance for treatment selection. This perspective supports the development of personalized therapeutic strategies and the systematic inclusion of emotional dimensions in clinical research.
Versions
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BibTeX
@misc{henry2026emotional,
title = {{Emotional responses (intensity/valence) fulfill RDoC criteria but remain excluded from diagnostic classifications of mood disorders}},
author = {Chantal Henry and Chlöé Müh and Claire-Hélène de Badts and Mariana Alonso and Lucie Berkovitch},
howpublished = {PsyArXiv},
year = {2026},
month = sep,
doi = {10.31234/osf.io/hcv5t_v1},
url = {https://osf.io/preprints/psyarxiv/hcv5t_v1/},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Emotional responses (intensity/valence) fulfill RDoC criteria but remain excluded from diagnostic classifications of mood disorders
AU - Chantal Henry
AU - Chlöé Müh
AU - Claire-Hélène de Badts
AU - Mariana Alonso
AU - Lucie Berkovitch
PY - 2026
DA - 2026/09/08
PB - PsyArXiv
DO - 10.31234/osf.io/hcv5t_v1
UR - https://osf.io/preprints/psyarxiv/hcv5t_v1/
AB - Categorical classifications of depression, such as DSM-5 and ICD, are limited by high clinical heterogeneity, arbitrary diagnostic thresholds, and weak links to underlying pathophysiology. In line with the Research Domain Criteria (RDoC) framework, this article proposes a dimensional and mechanistic approach centered on emotional responses as core transdiagnostic features of mood disorders. Emotional responses are conceptualized along two fundamental dimensions: intensity (arousal) and hedonic valence. Evidence from clinical, psychophysiological, neuroimaging, and preclinical studies indicates that depressive episodes may be characterized by either emotional hyporeactivity (emotional blunting and reduced responsiveness) or emotional hyperreactivity (heightened distress, anxiety, irritability, and emotional lability), the latter being closely associated with mixed features, particularly in bipolar depression. In parallel, depression is marked by maladaptive valence attribution, encompassing anhedonia related to reward-system dysfunction and a pervasive negativity bias. Preclinical findings implicate dysregulated basolateral amygdala circuits in valence attribution and demonstrate the reversibility of negativity bias with antidepressant interventions. Integrating emotional intensity and valence within an RDoC-informed framework provides a biologically grounded account of depressive heterogeneity, refines the characterization of mixed states, and offers clinically relevant guidance for treatment selection. This perspective supports the development of personalized therapeutic strategies and the systematic inclusion of emotional dimensions in clinical research.
ER -