Santra, R. | bioRxiv Science

bioRxiv2025

Mapping brain function underlying naturalistic motor observation and imitation using high-density diffuse optical tomography

BackgroundAutism spectrum disorder (ASD), a condition defined by deficits in social communication, restricted interests, and repetitive behaviors, is associated with early impairments in motor imitation that persist through childhood and into adulthood. Alterations in the mirror neuron system (MNS), crucial for interpreting and imitating actions, may underlie these ASD-associated differences in motor imitation. High-density diffuse optical tomography (HD-DOT) overcomes logistical challenges of functional magnetic resonance imaging to enable identification of neural substrates of naturalistic motor imitation. ObjectiveWe aim to investigate brain function underlying motor observation and imitation in autistic and non-autistic adults. We hypothesize that HD-DOT will reveal greater activation in regions associated with the MNS during motor imitation than motor observation, and that MNS activity will negatively correlate with autistic traits and motor fidelity. MethodsWe imaged brain function using HD-DOT in N = 100 participants as they engaged in observing or imitating a sequence of arm movements. Additionally, during imitation, participant movements were simultaneously recorded with 3D cameras for computer-vision-based assessment of motor imitation (CAMI). Cortical responses were estimated using general linear models, and multiple regression was used to test for associations with autistic traits, assessed via the Social Responsiveness Scale-2 (SRS), and imitation fidelity, assessed via CAMI. ResultsBoth observing and imitating motor movements elicited significant activations in higher-order visual and MNS regions, including the inferior parietal lobule, superior temporal gyrus, and inferior frontal gyrus. Imitation additionally exhibited greater activation in the superior parietal lobule, primary motor cortex, and supplementary motor area. Notably, the right temporal-parietal junction exhibited activation during observation but not during imitation. Higher autistic traits were associated with increased activation during motor observation in the right superior parietal lobule. No significant correlation between brain activation and CAMI scores was observed. ConclusionsOur findings provide robust evidence of shared and task-specific cortical responses underlying motor observation and imitation, emphasizing the differential engagement of MNS regions during motor observation and imitation.

neuroscience↗

bioRxiv2020

Single-femtosecond atomic-resolution observation of a protein traversing a conical intersection

The structural dynamics of a molecule are determined by the underlying potential energy landscape. Conical intersections are funnels connecting otherwise separate energy surfaces. Posited almost a century ago 1, conical intersections remain the subject of intense scientific investigation 2-4. In biology, they play a pivotal role in vision, photosynthesis, and DNA stability 5,6. In ultrafast radiationless de-excitation 1,7, they are vital to ameliorating photon-induced damage. In chemistry, they tightly couple the normally separable nuclear and electronic degrees of freedom, precluding the Born-Oppenheimer approximation 8. In physics, they manifest a Berry phase, giving rise to destructive interference between clockwise and anti-clockwise trajectories around the conical intersection 9. Accurate theoretical methods for examining conical intersections are at present limited to small molecules. Experimental investigations are challenged by the required time resolution and sensitivity. Current structure-dynamical understanding of conical intersections is thus limited to simple molecules with around 10 atoms, on timescales of about 100 fs or longer 10. Spectroscopy can achieve better time resolution, but provides only indirect structural information. Here, we present single-femtosecond, atomic-resolution movies of a 2,000-atom protein passing through a conical intersection. These movies, extracted from experimental data by geometric machine learning, reveal the dynamical trajectories of de-excitation via a conical intersection, yield the key parameters of the conical intersection controlling the de-excitation process, and elucidate the topography of the electronic potential energy surfaces involved.

biophysics↗