The effect of acute ketamine on dynamic functional connectivity in rats
Poster No:
1241
Submission Type:
Abstract Submission
Authors:
Emilie Wielezynski1, Giuseppe Alteriis2, Eilidh MacNicol2, Michel Mesquita3, Davide DiCenso2, Eugene Kim2, Federico Turkheimer22, Diana Cash2
Institutions:
1Kings College London, London, United Kingdom, 2King's College London, London, United Kingdom, 3L&M Data Science, London, United Kingdom
First Author:
Co-Author(s):
Introduction:
Ketamine, an N-methyl-D-aspartate receptor antagonist, acts as an anaesthetic at high doses and a model of psychosis and antidepressant at sub-anaesthetic doses (Hack et al., 2023). It modulates brain functional connectivity patterns linked to its treatment and psychomimetic effects (Anticevic et al., 2015; Abdallah et al., 2017), but its dynamic, time-varying effects remain unclear.This study applied dynamic functional connectivity analysis to examine ketamine's acute effects at whole-brain and network levels.
Methods:
A pharmacological MRI paradigm measured changes in blood-oxygen-level dependent signal, a proxy of neural activity used to characterise functional networks (Schwarz et al., 2009). In male Sprague-Dawley rats, racemic (R, S)-ketamine (25mg/ml, n=15) or saline (n=16) was administered 5 minutes into a 20-minute scan. The 25mg/ml dose is commonly used to study sub-anaesthetic ketamine effects in rodent models (Polis et al., 2019). Rats were initially anaesthetised with isoflurane and maintained with medetomidine infusion (Grandjean et al., 2020). Pre-processing returned subject-wise timeseries of 128 regions of interest (ROI). Functional connectivity analyses, completed with an in-house Python script, extracted time-varying connectivity and metastability measures globally (all ROI) and at the network level. This followed eigenvector decomposition of Pearson-correlation matrices calculated with a sliding window approach (de Alteriis et al., 2024). Global connectivity, measuring state synchrony, is the sum of squared eigenvalues; metastability, a measure of state variance, is the standard deviation. Recurrent phase-locking states were identified through k-means clustering of leading eigenvectors (Lord et al., 2019) and statistically assessed for ketamine's effects on state repertoire.
Results:
We analyzed global connectivity and metastability in 128 regions, comparing pre- and post-injection effects for ketamine and saline groups using different window sizes (Fig 1.). Ketamine administration significantly elevated global connectivity and metastability, with increased variability observed at smaller window sizes, while no significant changes were found in the saline group. Dependent t-tests confirmed significant increases in global connectivity and metastability across all canonical resting-state networks post-ketamine injection (p < 0.01). The strongest effects were seen in the Salience and Default Mode Networks. In contrast, the saline group showed no significant changes in global connectivity or metastability (p > 0.05). Phase-locking (PL) states were identified as distinct patterns of synchronized neural activity, where regions either aligned globally (PL State 1) or formed separate clusters (PL States 2–4) involving bilateral areas like the brainstem, cortex, hippocampus, and basal ganglia. Ketamine increased the durability, of PL state 3 including the dorsal hippocampus, lateral parietal association cortex and prefrontal cortex, while decreasing the probability of a PL state 2 including the cerebellum, striatum and rhinal cortex.
·Figure 1
Conclusions:
Dynamic functional connectivity analysis shows that ketamine increases global connectivity and metastability in rats, aligning with its pharmacokinetics. This enhanced connectivity, particularly in the default mode and salience networks, may underlie its antidepressant and psychomimetic effects by improving brain state transitions. Ketamine also increased dwell time in cortico-thalamic and sensorimotor connectivity states, linking its effects to mechanisms seen in schizophrenia and mood disorders. These findings offer insights into ketamine's neurobiological mechanisms and highlight the translational value of dynamic connectivity analyses for developing new treatments for depression.
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural) 1
Task-Independent and Resting-State Analysis
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Anatomy and Functional Systems
Novel Imaging Acquisition Methods:
BOLD fMRI
Physiology, Metabolism and Neurotransmission:
Pharmacology and Neurotransmission 2
Keywords:
Affective Disorders
ANIMAL STUDIES
FUNCTIONAL MRI
Glutamate
MRI
Psychiatric
Other - Ketamine
1|2Indicates the priority used for review
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