Neuronal Oscillation Dynamics Fmr1 KO2 mice

In vitro and ex vivo studies have shown consistent indications of hyperexcitability in the Fmr1 KO mouse model of autism spectrum disorder. We recently introduced a method to quantify network-level functional E/I ratio (fEI) from the neuronal oscillations. Here, we used this measure to study whether the implicated synaptic E/I disturbances translate to disturbances in network physiology in the Fmr1 KO model. We performed wireless skull-EEG recordings in wildtype (WT) and knockout (KO) male mice of the Fmr1 KO2 line in two separate experiments as an internal replication. Vigilance-state scoring was used to extract segments of inactive wakefulness as an equivalent behavioural condition to the human resting-state and, subsequently, we performed high-frequency resolution analysis of the fE/I biomarker, long-range temporal correlations (LRTC), and spectral power. We corroborated earlier studies showing increased high-frequency power in Fmr1 KO mice. LRTCs were higher in the gamma frequency ranges. Contrary to expectations, fEI was lower in the KO mice in high frequency ranges, suggesting more inhibition-dominated networks. Exposure to the GABA-agonist clonazepam decreased the fEI in both genotypes, confirming that increasing inhibitory tone results in a reduction of fEI. In addition, clonazepam decreased EEG power and increased LRTCs. These findings show applicability of these new resting-state EEG biomarkers to animal models for translational studies. They allow investigation of the effects of lower-level disturbances in E/I balance in relation to the organization of mass brain activity and how these may result in counterintuitive dynamics

Neuronal Oscillation Dynamics Fmr1 KO2 mice

In vitro and ex vivo studies have shown consistent indications of hyperexcitability in the Fmr1 KO mouse model of autism spectrum disorder. We recently introduced a method to quantify network-level functional E/I ratio (fEI) from the neuronal oscillations. Here, we used this measure to study whether the implicated synaptic E/I disturbances translate to disturbances in network physiology in the Fmr1 KO model. We performed wireless skull-EEG recordings in wildtype (WT) and knockout (KO) male mice of the Fmr1 KO2 line in two separate experiments as an internal replication. Vigilance-state scoring was used to extract segments of inactive wakefulness as an equivalent behavioural condition to the human resting-state and, subsequently, we performed high-frequency resolution analysis of the fE/I biomarker, long-range temporal correlations (LRTC), and spectral power. We corroborated earlier studies showing increased high-frequency power in Fmr1 KO mice. LRTCs were higher in the gamma frequency ranges. Contrary to expectations, fEI was lower in the KO mice in high frequency ranges, suggesting more inhibition-dominated networks. Exposure to the GABA-agonist clonazepam decreased the fEI in both genotypes, confirming that increasing inhibitory tone results in a reduction of fEI. In addition, clonazepam decreased EEG power and increased LRTCs. These findings show applicability of these new resting-state EEG biomarkers to animal models for translational studies. They allow investigation of the effects of lower-level disturbances in E/I balance in relation to the organization of mass brain activity and how these may result in counterintuitive dynamics

Neuronal Oscillation Dynamics Fmr1 KO2 mice

In vitro and ex vivo studies have shown consistent indications of hyperexcitability in the Fmr1 KO mouse model of autism spectrum disorder. We recently introduced a method to quantify network-level functional E/I ratio (fEI) from the neuronal oscillations. Here, we used this measure to study whether the implicated synaptic E/I disturbances translate to disturbances in network physiology in the Fmr1 KO model. We performed wireless skull-EEG recordings in wildtype (WT) and knockout (KO) male mice of the Fmr1 KO2 line in two separate experiments as an internal replication. Vigilance-state scoring was used to extract segments of inactive wakefulness as an equivalent behavioural condition to the human resting-state and, subsequently, we performed high-frequency resolution analysis of the fE/I biomarker, long-range temporal correlations (LRTC), and spectral power. We corroborated earlier studies showing increased high-frequency power in Fmr1 KO mice. LRTCs were higher in the gamma frequency ranges. Contrary to expectations, fEI was lower in the KO mice in high frequency ranges, suggesting more inhibition-dominated networks. Exposure to the GABA-agonist clonazepam decreased the fEI in both genotypes, confirming that increasing inhibitory tone results in a reduction of fEI. In addition, clonazepam decreased EEG power and increased LRTCs. These findings show applicability of these new resting-state EEG biomarkers to animal models for translational studies. They allow investigation of the effects of lower-level disturbances in E/I balance in relation to the organization of mass brain activity and how these may result in counterintuitive dynamics

Neuronal Oscillation Dynamics Fmr1 KO2 mice

In vitro and ex vivo studies have shown consistent indications of hyperexcitability in the Fmr1 KO mouse model of autism spectrum disorder. We recently introduced a method to quantify network-level functional E/I ratio (fEI) from the neuronal oscillations. Here, we used this measure to study whether the implicated synaptic E/I disturbances translate to disturbances in network physiology in the Fmr1 KO model. We performed wireless skull-EEG recordings in wildtype (WT) and knockout (KO) male mice of the Fmr1 KO2 line in two separate experiments as an internal replication. Vigilance-state scoring was used to extract segments of inactive wakefulness as an equivalent behavioural condition to the human resting-state and, subsequently, we performed high-frequency resolution analysis of the fE/I biomarker, long-range temporal correlations (LRTC), and spectral power. We corroborated earlier studies showing increased high-frequency power in Fmr1 KO mice. LRTCs were higher in the gamma frequency ranges. Contrary to expectations, fEI was lower in the KO mice in high frequency ranges, suggesting more inhibition-dominated networks. Exposure to the GABA-agonist clonazepam decreased the fEI in both genotypes, confirming that increasing inhibitory tone results in a reduction of fEI. In addition, clonazepam decreased EEG power and increased LRTCs. These findings show applicability of these new resting-state EEG biomarkers to animal models for translational studies. They allow investigation of the effects of lower-level disturbances in E/I balance in relation to the organization of mass brain activity and how these may result in counterintuitive dynamics

Neuronal Oscillation Dynamics Fmr1 KO2 mice

In vitro and ex vivo studies have shown consistent indications of hyperexcitability in the Fmr1 KO mouse model of autism spectrum disorder. We recently introduced a method to quantify network-level functional E/I ratio (fEI) from the neuronal oscillations. Here, we used this measure to study whether the implicated synaptic E/I disturbances translate to disturbances in network physiology in the Fmr1 KO model. We performed wireless skull-EEG recordings in wildtype (WT) and knockout (KO) male mice of the Fmr1 KO2 line in two separate experiments as an internal replication. Vigilance-state scoring was used to extract segments of inactive wakefulness as an equivalent behavioural condition to the human resting-state and, subsequently, we performed high-frequency resolution analysis of the fE/I biomarker, long-range temporal correlations (LRTC), and spectral power. We corroborated earlier studies showing increased high-frequency power in Fmr1 KO mice. LRTCs were higher in the gamma frequency ranges. Contrary to expectations, fEI was lower in the KO mice in high frequency ranges, suggesting more inhibition-dominated networks. Exposure to the GABA-agonist clonazepam decreased the fEI in both genotypes, confirming that increasing inhibitory tone results in a reduction of fEI. In addition, clonazepam decreased EEG power and increased LRTCs. These findings show applicability of these new resting-state EEG biomarkers to animal models for translational studies. They allow investigation of the effects of lower-level disturbances in E/I balance in relation to the organization of mass brain activity and how these may result in counterintuitive dynamics

Unaffected sensory processing in FMR1 KO mice

Sensory sensitivity problems are a common symptom in autism spectrum disorders and fragile X syndrome. Mainly in the auditory modality, disturbed sensory processing has been found in both fragile-X patients as well as the knockout animals of the corresponding genetic model, the Fmr1 knockout mouse. Here we assessed not only auditory but also visual sensory processing in the second generation Fmr1 KO mice (Mientjes et al., 2006) under freely behaving conditions using electroencephalography readouts. No differences between wildtype and knockout animals were found in single auditory and visual evoked potentials in response to pure sine tones and full-field white light flashes. Visual sensory gating was enhanced in the early but not the late components of the evoked potentials, no changes were found in auditory gating. Synchronization to a steady state flickering visual stimulus seemed to be reduced in the higher harmonic responses of 10Hz, but not 20 or 40Hz, stimulation. However, this effect could not be reproduced in an independent cohort of animals. No differences were found in the intertrial phase consistency, nor in power in response to a chirp stimulus in which the frequency steadily increased. This study could not reproduce earlier found increased amplitudes in auditory stimuli, nor could it convincingly show that synchronization deficits found to be present in response to auditory stimuli also existed in the visual modality. Taken together, no robust auditory and visual processing deficits could be found in the Fmr1 knockout mice. When aiming to study sensory processing in the Fmr1 knockout mice, the appropriate paradigms should be carefully selected to improve translatability and predictive validity