Biology subjects

Abdoun, O.

Publications and source records attributed to Abdoun, O..

9 recordsLinked to original sources

bioRxiv2026

Nondual mindfulness meditation alters self representation and brain connectome in expert meditators

Nonduality is a foundational but conceptually elusive notion across several contemplative traditions. Nondual traditions challenge the assumption that a subject-object structure characteristic of ordinary experience is an intrinsic feature of conscious awareness. However, little remains known about the neurocognitive mechanisms associated with such experiential state. Here, we investigated how Open Presence (OP) meditation, a form of non-dual mindfulness practice, modulates bodily self-representation and large-scale brain functional organization. We combined the Full-Body Illusion Experience (FBIE), a virtual reality paradigm manipulating bodily self-processing, with resting-state functional connectivity gradient analyses in expert meditators (>10,000 hours of practice) and meditation novices. We hypothesized that OP would attenuate bodily self susceptibility as measured by FBIE and increase large-scale integration of functional brain networks, consistent with prior findings linking reduced self-boundaries and ego-dissolution to increased connectome integration. Seventy-five participants (28 experts, 47 novices) underwent fMRI scanning during OP meditation. Brain network organization was assessed using connectivity gradients and network dispersion/ eccentricity metrics. Group differences were evaluated using bootstrap statistics and support vector classification. Compared with novices, expert practitioners showed reduced global network eccentricity during OP, particularly within dorsal attention, ventral attention, and frontoparietal networks, suggesting greater large-scale integration of functional networks. These neural patterns were positively correlated with FBIE self-report measures and negatively with cognitive defusion scores, a construct thought to reflect reduced self-grasping toward thoughts and mental contents. Together, these findings suggest that nondual meditation is associated with alterations in self-representation and increased large-scale functional integration, providing candidate neural markers of nondual awareness.

neuroscience↗

bioRxiv2026

Distinct SMA beta bursts support the development of anticipatory postural control in children

To produce smooth and coordinated movements, the brain generates anticipatory postural adjustments (APA) - feedforward motor commands that counteract predicted postural disturbances before they occur. Although APA emerge early in life, their maturation extends into early adulthood, yet little is known about the underlying neural mechanisms. Using magnetoencephalography during a naturalistic bimanual load-lifting task, we investigated anticipatory postural control in children aged 7-12 years. In this task, lifting a load from the contralateral postural forearm induces upward elbow rotation, which is anticipatorily counteracted by inhibition of Biceps brachii postural activity, stabilizing forearm posture. Surprisingly, despite greater variability in inhibition timing and less efficient forearm stabilization in children, the mechanism of anticipatory inhibition was consistent with that recently described in adults: it was mediated by transient oscillatory beta bursts (19-24 Hz), associated with reduced supplementary motor area (SMA) excitability indexed by high-gamma (90-130 Hz) power suppression, and preceded by directed influences from lateral prefrontal and ventral premotor cortex. However, burst frequency was lower in children, and an additional APA mechanism was recruited: while 19-24 Hz bursts were linked to immediate SMA suppression and stronger muscle inhibition, higher-frequency bursts (24-29 Hz) were associated with delayed ([~]100 ms) SMA suppression mediated by alpha activity (8 Hz), which attenuated post-inhibition forearm instability. These results reveal that children in middle childhood already engage adult-like neural mechanisms for anticipatory inhibition, while additionally recruiting a compensatory mechanism to counteract postural imprecision, providing new insights into the neural basis of APA maturation and its alteration in neurodevelopmental conditions.

neuroscience↗

bioRxiv2025

No evidence of neural feature-specific pre-activation during the prediction of an upcoming stimulus

Our brains constantly make predictions about upcoming events based on prior knowledge of the environment. Although several neural mechanisms have been proposed to support this capacity, it is not yet clear how the brain makes such predictions. A compelling hypothesis is that the brain preactivates a sensory template of a predictable stimulus before it appears. In a recent study, Demarchi et al. had participants listen to sequences of sounds with different levels of predictability. For some sequences, participants could anticipate the next sound (in regular sequences), for others not (in random sequences). Using magnetoencephalography recordings and machine-learning methods to decode sounds from brain signals, Demarchi et al. concluded that auditory predictions pre-activate tone-specific neural templates before the sound onset. In our reanalysis of their data, we demonstrate that their results can be fully explained by a bias induced by the structure of the sequences: because the most likely stimulus also happens to be physically close to the previous one, spurious higher-than-chance decoding performance arises before the sound onset. We provide general criteria to assess whether a study is affected by this confound and requires a reexamination. We conclude that there is no evidence of anticipatory predictive perception in the Demarchi et al. dataset, and that existing evidence for feature-specific pre-activation during prediction in humans remains inconclusive.

neuroscience↗

bioRxiv2025

Learning Amidst Noise: The Complementary Roles of Neural Predictive Activity and Representational Changes

The ability to extract structured sensory patterns from a noisy environment is fundamental to cognition, yet how the brain learns complex regularities remains unclear. Using magnetoencephalography during a visuomotor task, we tracked the neural dynamics as humans learned non-adjacent temporal dependencies embedded in noise. We reveal that learning is supported by two temporally dissociable mechanisms. Neural predictive activity emerged rapidly, with stimulus-specific patterns appearing before stimulus onset and preceding measurable behavioral improvements. This is followed by a slower build-up of representational change, characterized by an increased neural pattern similarity between statistically dependent, non-adjacent elements. Both processes are supported by a distributed consortium of networks, with the sensorimotor and dorsal attentional networks playing a central role. These findings suggest that both neural predictive activity and representational changes contribute to learning regularities, revealing a temporal hierarchy in which neural predictive activity precedes behavioral improvement and is followed by neural representational changes, possibly facilitating the gradual consolidation of knowledge into stable neural representations.

neuroscience↗

bioRxiv2025

High-beta bursts in SMA mediate anticipatory muscle inhibition in a bimanual motor task

In motor networks, inhibition has been associated with oscillatory activity in the mu (8-12 Hz) or beta (13-30 Hz) bands, yet how these rhythms ultimately influence muscle activity remains unclear. The Bimanual Load-Lifting Task (BLLT) elicits anticipatory inhibition of the elbow flexors in the load-supporting arm during voluntary load-lifting, providing a suitable model to study oscillatory mechanisms of muscle inhibition. We recorded magnetoencephalography (MEG) in adult participants performing the BLLT. Optimal postural stabilization occurred when Biceps brachii inhibition preceded unloading by [~]10-40 ms. Stronger muscle inhibition within this time window was associated with reduced high-gamma (90-130 Hz) power, potentially reflecting reduced excitability, and increased high-beta power in the contralateral Supplementary Motor Area (SMA), with high-gamma power reduction partially mediating the effect of high-beta power on anticipatory inhibition. Furthermore, trials containing beta bursts (22-28 Hz) exhibited both optimally timed anticipatory inhibition and concurrent reduction in high-gamma power. These findings suggest that optimal anticipatory inhibition in the load-supporting elbow flexor is linked to reduced SMA excitability mediated by inhibitory beta bursts. More broadly, they provide new evidence linking beta bursts to the inhibitory control of muscle function, and contribute to a better understanding of motor anticipation.

neuroscience↗

bioRxiv2024

Steerable Tape-Spring Needle for Autonomous Sharp Turns Through Tissue

Steerable needles offer a minimally invasive method to deliver treatment to hard-to-reach tissue regions. We introduce a new class of tape-spring steerable needles capable of sharp turns ranging from 15 to 150 degrees with a turn radius as low as 3mm, which minimizes surrounding tissue damage. In this work, we derive and experimentally validate a geometric model for our steerable needle design. We evaluate both manual and robotic steering of the needle along a Dubins path in 7 kPa and 13 kPa tissue phantoms, simulating our target clinical application in healthy and unhealthy liver tissue. We conduct experiments to measure needle robustness to stiffness transitions between non-homogeneous tissues. We demonstrate progress towards clinical use with needle tip tracking via ultrasound imaging, navigation around anatomical obstacles, and integration with a robotic autonomous steering system.

bioengineering↗

bioRxiv2023

A Tape Spring Steerable Needle Capable of Sharp Turns

ObjectiveTo make steerable needles more effective, researchers have been trying to minimize turning radius, develop mechanics-based models, and simplify control. This paper introduces a novel cable-driven steerable needle that has a 3mm turning radius based on tape spring mechanics, which sets a new minimum turn radius in stiffness-matched tissue models. Methods: We characterize the turn radius and the forces that affect control and performance and create predictive models to estimate required insertion forces and maximum insertion depth. Finally, we demonstrate the performance of a task outside the capabilities of a conventional needle. Results: Minimal force is required to maintain bends, allowing surrounding tissue to fix them in place, and minimal energy is required to propagate bends, allowing the device to navigate easily through various tissue phantoms. The turn radius of the device is independent of surrounding tissue stiffness, making for simple and precise control. We show that all aspects of performance depend on minimizing the tip cutting force. Under ultrasound guidance, we successfully navigate into and then follow a deep blood vessel model at a steep angle of approach. Conclusion: This design allows the system to accurately control the direction of the device while maintaining a smaller turn radius than other steerable needles, providing the potential to broaden access to challenging targets in patients.

bioengineering↗

bioRxiv2022

Time-resolved dynamic computational modeling of human EEG recordings reveals gradients of generative mechanisms for the MMN response

Despite attempts to unify the different theoretical accounts of the mismatch negativity (MMN), there is still an ongoing debate on the neurophysiological mechanisms underlying this complex brain response. On one hand, neuronal adaptation to recurrent stimuli is able to explain many of the observed properties of the MMN, such as its sensitivity to controlled experimental parameters. On the other hand, several modeling studies reported evidence in favor of Bayesian learning models for explaining the trial-to-trial dynamics of the human MMN. However, direct comparisons of these two main hypotheses are scarce, and previous modeling studies suffered from methodological limitations. Based on reports indicating spatial and temporal dissociation of physiological mechanisms within the timecourse of mismatch responses in animals, we hypothesized that different computational models would best fit different temporal phases of the human MMN. Using electroencephalographic data from two independent studies of a simple auditory oddball task (n = 82), we compared adaptation and Bayesian learning models ability to explain the sequential dynamics of auditory deviance detection in a time-resolved fashion. We first ran simulations to evaluate the capacity of our design to dissociate the tested models and found that they were sufficiently distinguishable above a certain level of signal-to-noise ratio (SNR). In subjects with a sufficient SNR, our time-resolved approach revealed a temporal dissociation between the two model families, with high evidence for adaptation during the early MMN window (from 90 to 150-190 ms post-stimulus depending on the dataset) and for Bayesian learning later in time (170-180 ms or 200-220ms). In addition, Bayesian model averaging of fixed-parameter models within the adaptation family revealed a gradient of adaptation rates, resembling the anatomical gradient in the auditory cortical hierarchy reported in animal studies. Author summaryThe ability to detect and adapt to changes in the environment is an essential feature for survival of living beings. Two main theories have been proposed to explain how the brain performs such an automatic task in the auditory domain. The first one, adaptation, emphasizes the ability of auditory cortical and sub-cortical neurons to attenuate their response to repeated stimuli, which renders the brain more sensitive to deviations from expected sensory inputs. The second one, Bayesian learning, further involves higher-level cortical regions which would update their predictions about incoming stimuli, depending on their performance at predicting previous ones. These two views may not be mutually exclusive, but few experimental works compared them directly. We used computational models inspired from both accounts to assess which view may provide a better fit of two independent electrophysiological datasets from similar auditory experiments. Evidence from a large sample of 82 human subjects provided a complex picture, with adaptation processes seemingly dominating the early phase of auditory brain response, and Bayesian learning processes appearing later on. Our results converge with other recent works in animals and points to the necessary reconciliation of those two theories for a better understanding of auditory perception and statistical learning.

neuroscience↗

bioRxiv2022

When do we become more prone to distraction? Progressive evolution of the different components of distractibility from early to late adulthood.

Life expectancy has steadily increased for over a century; we thus live longer and are more likely to experience cognitive difficulties such as increased distractibility which can hamper autonomy. This cross-sectional behavioral study aimed to characterize the decline of the cognitive components of distractibility during typical aging, and the onset of this decline. 191 participants from 21 to 86 years old, distributed within seven age groups, were tested using the Competitive Attention Test. Results indicate that cognitive components contributing to distractibility follow different trajectories with aging: voluntary orienting remains stable from 21 to 86 years old, sustained attention decreases while distraction increases between 26 and 86 years old, finally, impulsivity is lower in older compared to younger adults. Increased distractibility in older adults thus seems to result from a dominance of involuntary over voluntary attention processes, whose detrimental effect on performance is partly compensated by enhanced recruitment of motor control.

neuroscience↗