Orbital period change of Dimorphos due to the DART kinetic impact.

The Double Asteroid Redirection Test (DART) spacecraft successfully performed the first test of a kinetic impactor for asteroid deflection by impacting Dimorphos, the secondary of near-Earth binary asteroid (65803) Didymos, and changing the orbital period of Dimorphos. A change in orbital period of approximately 7 min was expected if the incident momentum from the DART spacecraft was directly transferred to the asteroid target in a perfectly inelastic collision1, but studies of the probable impact conditions and asteroid properties indicated that a considerable momentum enhancement (ß) was possible2,3. In the years before impact, we used lightcurve observations to accurately determine the pre-impact orbit parameters of Dimorphos with respect to Didymos4-6. Here we report the change in the orbital period of Dimorphos as a result of the DART kinetic impact to be -33.0 ± 1.0 (3σ) min. Using new Earth-based lightcurve and radar observations, two independent approaches determined identical values for the change in the orbital period. This large orbit period change suggests that ejecta contributed a substantial amount of momentum to the asteroid beyond what the DART spacecraft carried.

Gain mechanisms for contextually guided visuomotor transformations.

A prevailing question in sensorimotor research is the integration of sensory signals with abstract behavioral rules (contexts) and how this results in decisions about motor actions. We used neural network models to study how context-specific visuomotor remapping may depend on the functional connectivity among multiple layers. Networks were trained to perform different rotational visuomotor associations, depending on the stimulus color (a nonspatial context signal). In network I, the context signal was propagated forward through the network (bottom-up), whereas in network II, it was propagated backwards (top-down). During the presentation of the visual cue stimulus, both networks integrate the context with the sensory information via a mechanism similar to the classic gain field. The recurrence in the networks hidden layers allowed a simulation of the multimodal integration over time. Network I learned to perform the proper visuomotor transformations based on a context-modulated memory of the visual cue in its hidden layer activity. In network II, a brief visual response, which was driven by the sensory input, is quickly replaced by a context-modulated motor-goal representation in the hidden layer. This happens because of a dominant feedback signal from the output layer that first conveys context information, and then, after the disappearance of the visual cue, conveys motor goal information. We also show that the origin of the context information is not necessarily closely tied to the top-down feedback. However, we suggest that the predominance of motor-goal representations found in the parietal cortex during context-specific movement planning might be the consequence of strong top-down feedback originating from within the parietal lobe or from the frontal lobe.

A nonparametric quantification of neural response field structures.

The response fields of higher cortical neurons are usually approximated with smooth mathematical functions for the purpose of population parameterization or theoretical modeling. We used instead two nonparametric methods (principal component analysis and independent component analysis), which provided a basis for the response field clustering. Although both methods performed satisfactorily, the principal component analysis space is more straightforward to calculate. It also gave a clear preference toward the smallest number of functional response field classes. Clustering was performed with both K-means and superparamagnetic clustering algorithms with similar results. We also show that the shapes of the eigenvectors remain consistent regardless of the response field data sets size. This finding reflects the fact that the response fields were generated by the same neural network and encode the same underlying process.