A new computational model reveals how ketamine, a widely used anesthetic and antidepressant, influences brain activity by blocking NMDA receptors in the cerebral cortex. This blockage alters neuronal activation patterns, leading to altered states of consciousness and potential therapeutic benefits for depression.

Key Insights from the Model

• Accurately replicates real brain wave patterns: The model aligns with real observations of brain waves in humans and animals administered with ketamine.
• Suggests a mechanism for ketamine’s antidepressant effects: The results indicate a potential mechanism involving increased gamma activity.
• Offers a deeper understanding of ketamine’s effects: By simulating the drug’s interaction with NMDA receptors, the model clarifies how ketamine alters neuronal activity.

Research Details

The research, published on May 20 in the Proceedings of the National Academy of Sciences, involved scientists from MIT, Boston University, Massachusetts General Hospital, and Harvard University. Ketamine blocks NMDA receptors in the cerebral cortex, modulating the release of the excitatory neurotransmitter glutamate. When the neuron channels regulated by NMDA receptors open, they usually close slowly, allowing ions to enter and exit the neurons. However, ketamine slows the tension buildup across the neuron’s membrane, leading to an altered state of excitation and neuronal spikes.

How the Model Works

The study focused on the biophysical modeling of the effects of NMDA receptor blockage by ketamine in the cerebral cortex. NMDA receptors play a crucial role in modulating the release of glutamate, an excitatory neurotransmitter. Blocking these receptors affects the ion flow in neural channels, influencing the electrical properties of neurons and their communication. The model incorporates how this blocking and unblocking mechanism influences neuronal activity, surpassing previous models.

Key Results

Simulations using this model led to several important predictions and explanations:

• Disinhibition of network activity: Ketamine may suppress certain inhibitory interneurons, thus disinhibiting the network.
• Gamma frequency oscillations: The model predicts that blocking and unblocking NMDA receptors can create bursts of neuronal activation that synchronize into gamma frequency waves.
• Periodic down states: At higher doses, the model explains the emergence of periodic down states, characterized by slow delta waves, which interrupt gamma activity and contribute to loss of consciousness.

Potential Antidepressant Connection

The model also suggests a possible link between ketamine’s effects on gamma activity and its antidepressant properties. Increased gamma activity induced by ketamine could stimulate neurons that release a health-promoting peptide called VIP. This peptide has been associated with benefits such as reduced inflammation, potentially explaining ketamine’s longer-lasting therapeutic effects. However, further experimental validation is needed to confirm this connection.

Introduction

Ketamine, recognized as an essential medicine by the World Health Organization, is used in varying doses for sedation, pain control, general anesthesia, and as a treatment for treatment-resistant depression. While scientists know its target in brain cells and have observed how it affects brain activity, they have not fully understood how these two aspects are connected. A recent study by a research team from several leading institutions in Boston uses computational modeling to bridge this gap and provide new insights into how ketamine works.

The Computational Model

Key Discoveries

The biophysical model developed by researchers accurately simulates how different doses of ketamine alter the activity of a model brain network, including key neuron types present in the cortex. The simulations successfully replicated brain waves observed via EEG electrodes in human volunteers and animals treated with ketamine. At low doses, ketamine increased the power of gamma waves (30-40 Hz), while at higher doses, which cause unconsciousness, gamma waves were interrupted by very slow-frequency delta wave states.

Predicted Mechanisms

The research predicts that ketamine can disinhibit network activity by turning off certain inhibitory interneurons. This release of excitatory and inhibitory neurons allows them to vigorously increase activity, leading to ketamine’s excited state. Another predicted mechanism is that ketamine synchronizes bursts of neuronal spikes into gamma waves through the activation of phasic inhibitory interneurons.

Antidepressant Effects

The model suggests that the gamma activity increase induced by ketamine could stimulate neurons that express VIP, a peptide known for its health-promoting effects, such as reducing inflammation. This effect could explain the longer-lasting antidepressant benefits of ketamine beyond its direct effects on NMDA receptors.

Conclusions and Future Implications

This study offers new insights into how ketamine alters brain activity, paving the way for potential improvements in the drug’s administration and therapeutic effectiveness. Although some of the proposed connections need further experimental validation, the findings provide a solid foundation for future studies and clinical applications.

Acknowledgments

The research was funded by various entities, including the JPB Foundation, the Picower Institute for Learning and Memory, the Simons Center for The Social Brain, and the National Institutes of Health. The study’s co-authors include Marek Kowalski, Oluwaseun Akeju, Earl K. Miller, led by Emery N. Brown, Nancy Kopell, and Michelle McCarthy.

Source: MIT