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Observational Fear as a Model of Affective Empathy in Mice

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Emotion modelling towards affective pathogenesis.

¹Director, Community Mental Health, Peninsula Health, Davey St Clinic, Frankston, and Adjunct Senior Lecturer, School of Psychology, Psychiatry and Psychological Medicine, Monash University, Clayton, VIC, Australia.

Australasian Psychiatry : Bulletin of Royal Australian and New Zealand College of Psychiatrists

|December 17, 2009

Summary

This summary is machine-generated.

This study proposes a network model of emotional families to understand affective pathogenesis. It suggests morbid emotional states arise from activating specific emotion sites, offering a new heuristic for psychiatric research.

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Area of Science:

Psychiatry
Affective Science
Computational Neuroscience

Background:

Current psychiatric models lack integration between pathological states and normal systems.
The explicit causes of affective disorders remain largely unknown.
Understanding the interplay between arousal and emotion is crucial for affective pathogenesis.

Purpose of the Study:

To explore the interaction of arousal and emotion in affective pathogenesis.
To evaluate methods for linking emotional experiences with psychiatric disorders.
To propose a novel model for understanding emotional dysregulation in affective disorders.

Main Methods:

Evaluation of existing methods linking emotion and psychiatric disorder.
Development of a network model representing emotions as quantal gradients.
Application of non-linear dynamic theory to affective pathogenesis.

Main Results:

A network model of emotional families is presented.
Emotions are conceptualized as existing on quantal gradients.
Morbid emotional states are theorized as activations of distal emotion sites.
The phenomenology of affective disorders is described using this network model.

Conclusions:

Metaphoric models of emotion possess face validity.
The proposed network model may serve as a useful heuristic for psychiatric research.
Further exploration of dynamic emotion systems could advance understanding of affective disorders.