Biology subjects

Houvenaghel, J.-F.

Publications and source records attributed to Houvenaghel, J.-F..

4 recordsLinked to original sources

bioRxiv2024

Functional connectivity is dominated by aperiodic, rather than oscillatory, coupling

Functional connectivity has attracted significant interest in the identification of specific circuits underlying brain (dys-)function. Classical analyses to estimate functional connectivity (i.e., filtering electrophysiological signals in canonical frequency bands and using connectivity metrics) assume that these reflect oscillatory networks. However, this approach conflates non-oscillatory, aperiodic neural activity with oscillations; raising the possibility that these functional networks may reflect aperiodic rather than oscillatory activity. Here, we provide the first study quantifying, in two different human electroencephalography (EEG) databases, the contribution of aperiodic activity on reconstructed oscillatory functional networks in resting state. We found that more than 99% of delta, theta, and gamma functional networks, more than 90% of beta functional networks and between 23 and 55% of alpha functional networks were actually driven by aperiodic activity. While there is no universal consensus on how to identify and quantify neural oscillations, our results demonstrate that oscillatory functional networks are drastically sparser than commonly assumed. These findings suggest that most functional connectivity studies focusing on resting state actually reflect aperiodic networks instead of oscillations-based networks. We highly recommend that oscillatory network analyses first check the presence of aperiodicity-unbiased neural oscillations before estimating their statistical coupling to strengthen the robustness, interpretability, and reproducibility of functional connectivity studies.

neuroscience↗

bioRxiv2023

Changes in electrophysiological aperiodic activity during cognitive control in Parkinson's disease

Cognitive symptoms in Parkinsons disease (PD) are common and can significantly affect patients quality of life. Therefore, there is an urgent clinical need to identify a signature derived from behavioral and/or neuroimaging indicators that could predict which patients are at increased risk for early and rapid cognitive decline. Recently, converging evidence identified electroencephalogram (EEG) aperiodic activity as meaningful physiological information associated with age, development, cognitive and perceptual states or pathologies. In this study, we aimed to investigate aperiodic activity in PD during cognitive control and characterize its possible association with behavior. Here, we recorded high-density EEG (HD-EEG) in 30 healthy controls and 30 PD patients during a Simon task. We analyzed task-related behavioral data in the context of the activation-suppression model and extracted aperiodic parameters (offset, exponent) at both scalp and source levels. Our results showed behavioral alterations of cognitive control as well as higher offsets in patients in the parieto-occipital areas, suggesting increased excitability in PD. A small congruence effect on aperiodic parameters in pre- and post-central brain areas was also found, possibly associated with task execution. Significant differences in aperiodic parameters between the resting state, pre- and post-stimulus phases all across the scalp and cortex confirmed that the observed changes in aperiodic activity are linked to task execution. No correlation was found between aperiodic activity and behavior or clinical features. Our findings provide evidence that EEG aperiodic activity in PD is characterized by greater offsets, and that aperiodic parameters differ depending on arousal state. However, our results do not support the hypothesis that the behavior-related differences observed in PD are related to aperiodic changes. Overall, this study highlights the importance of considering aperiodic activity contributions in brain disorders and further investigating the relationship between aperiodic activity and behavior.

neuroscience↗

bioRxiv2020

Low-frequency subthalamic neural oscillations are involved in explicit and implicit facial emotional processing - a local field potential study

In addition to the subthalamic nucleus (STN) role in motor control, STN deep brain stimulation (DBS) for Parkinsons disease (PD) has also uncovered its involvement in cognitive and limbic processing. STN neural oscillations analyzed through local field potential (LFP) recordings have been shown to contribute to emotional (mostly in the alpha band [8-12 Hz]) and cognitive processing (theta [4-7 Hz] and beta [13-30 Hz] bands). In this study, we aimed at testing the hypothesis that STN oscillatory activity is involved in explicit and implicit processing of emotions. To achieve this objective, we used a task that presented patients with fearful emotional facial expressions and asked them to identify the emotion (explicit task) or gender associated with the face (implicit task). We evaluated emotion and task effects on STN neural oscillations power and intertrial phase consistency. Our results revealed that accuracy was lower in the implicit task. Increased STN delta power and decreased alpha and beta power were observed after stimulus presentation. However, there was no influence of emotional facial expression, i.e. neutral versus fear, nor task demands. Intertrial phase consistency in the delta and theta band increased after stimulus onset, in the same time-period as delta power increased. However, similarly to oscillatory power, no changes related to emotional fear expression or task demand were found. These findings suggest that STN oscillatory activity is not specifically involved in explicit and/or implicit processing of emotions, and that power and phase synchronization changes might be more related to overall task-execution mechanisms. These conjectures remain to be confirmed. Highlights- STN LFPs were recorded during an emotional/gender recognition task in PD patients. - STN delta power increased, and alpha and beta power decreased after stimulus onset. - Power changes were not influenced by emotional fearful expression or task demands. - Delta/theta intertrial phase consistency increased after stimulus onset. - Intertrial phase consistency was not affected by emotional valence or task demands. - The observed STN activity was likely related to general task-execution mechanisms.

neuroscience↗

bioRxiv2018

Subthalamic nucleus local field potentials recordings reveal subtle effects of promised reward during conflict resolution in Parkinson’s disease

Cognitive action control depends on cortical-subcortical circuits, involving notably the subthalamic nucleus (STN), as evidenced by local field potentials recordings (LFPs) studies. The STN consistently shows an increase in theta oscillations power during conflict resolution. Some studies have shown that cognitive action control in Parkinsons disease (PD) could be influenced by the occurrence of monetary reward. In this study, we investigated whether incentive motivation could modulate STN activity, and notably STN theta activity, during response conflict resolution. To achieve this objective, we recorded STN LFPs during a motivated Simon task in PD patients who had undergone deep brain stimulation surgery. Behavioral results revealed that promised rewards increased the difficulty in resolving conflict situations, thus replicating previous findings. Signal analyses locked on the imperative stimulus onset revealed the typical pattern of increased theta power in a conflict situation. However, this conflict-related modulation of theta power was not influenced by the size of the reward cued. We nonetheless identified a significant effect of the reward size on local functional organization (indexed by inter-trial phase clustering) of theta oscillations, with higher organization associated with high rewards while resolving conflict. When focusing on the period following the onset of the reward cue, we unveiled a stronger beta power decrease in higher reward conditions. However, these LFPs results were not correlated to behavioral results. Our study suggests that the STN is involved in how reward information can influence computations during conflict resolution. However, considering recent studies as well as the present results, we suspect that these effects are subtle.

neuroscience↗