Network level characteristics in the emotion recognition network after unilateral temporal lobe surgery

Area of Science:

• Neuroscience
• Cognitive Neuroscience
• Social Neuroscience

Background:

• The amygdala is crucial for emotion recognition.
• Previous research indicated temporal lobe surgery (TLS) does not impair emotion recognition.
• The neural network basis for this preserved function remains unclear.

Purpose of the Study:

• To investigate the network-level neural basis of preserved emotion recognition after temporal lobe surgery (TLS).
• To compare network characteristics of the emotion recognition network in TLS patients and healthy controls.
• To test predictions from basic emotion theory versus psychological construction theory regarding network compensation.

Main Methods:

• Utilized generalized psychophysiological interaction (gPPI) and graph theory indices.
• Defined the emotion recognition network in TLS patients and healthy controls.
• Analyzed five network-level indices: characteristic path length, global efficiency, clustering coefficient, local efficiency, and small-worldness.

Main Results:

• No significant increase in non-amygdalar connections was observed in TLS patients compared to controls.
• TLS did not lead to substantial global reorganization of the emotion recognition network.
• Preserved behavioral emotion recognition in TLS is not associated with massive connectivity changes at the network level.

Conclusions:

• The emotion recognition network demonstrates robustness and functional compensation for structural damage.
• Preserved emotion recognition after amygdala resection occurs without significant global network reorganization.
• Findings align with psychological construction theory, suggesting flexible neural processing of emotions.