Imbalanced Excitation and Inhibition Disrupts Neural Activity

Published on April 12, 2023

Just like a symphony, the brain relies on a delicate balance between excitatory and inhibitory neurons. This harmony, known as the excitation/inhibition (E/I) balance, is crucial for proper brain function. However, when this balance is disrupted, the consequences can be far-reaching. In this study, scientists investigated the effects of an imbalanced E/I ratio on neural dynamics and information transmission in a simulated spiking neural network model. By manipulating the number of inhibitory neurons and their synaptic weights, they discovered that an increased E/I ratio led to strengthened excitatory connections, decreased complexity of neural activity, and reduced information transmission between different groups of neurons. These findings shed light on the relationship between E/I imbalance and brain disorders characterized by excessive connections and low complexity of activity. To dive deeper into this fascinating research, explore the full article!

Excitatory and inhibitory neurons are fundamental components of the brain, and healthy neural circuits are well balanced between excitation and inhibition (E/I balance). However, it is not clear how an E/I imbalance affects the self-organization of the network structure and function in general. In this study, we examined how locally altered E/I balance affects neural dynamics such as the connectivity by activity-dependent formation, the complexity (multiscale entropy) of neural activity, and information transmission. In our simulation, a spiking neural network model was used with the spike-timing dependent plasticity rule to explore the above neural dynamics. We controlled the number of inhibitory neurons and the inhibitory synaptic weights in a single neuron group out of multiple neuron groups. The results showed that a locally increased E/I ratio strengthens excitatory connections, reduces the complexity of neural activity, and decreases information transmission between neuron groups in response to an external input. Finally, we argued the relationship between our results and excessive connections and low complexity of brain activity in the neuropsychiatric brain disorders.

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