Domain general learning: Infants use social and non-social cues when learning object statistics.

Previous research has shown that infants can learn from social cues. But is a social cue more effective at directing learning than a non-social cue? This study investigated whether 9-month-old infants (N = 55) could learn a visual statistical regularity in the presence of a distracting visual sequence when attention was directed by either a social cue (a person) or a non-social cue (a rectangle). The results show that both social and non-social cues can guide infants' attention to a visual shape sequence (and away from a distracting sequence). The social cue more effectively directed attention than the non-social cue during the familiarization phase, but the social cue did not result in significantly stronger learning than the non-social cue. The findings suggest that domain general attention mechanisms allow for the comparable learning seen in both conditions

Climate model simulation of winter warming and summer cooling following the 1991 Mount Pinatubo volcanic eruption

We simulate climate change for the 2-year period following the eruption of Mount Pinatubo in the Philippines on June 15, 1991, with the ECHAM4 general circulation model (GCM). The model was forced by realistic aerosol spatial-time distributions and spectral radiative characteristics calculated using Stratospheric Aerosol, and Gas Experiment II extinctions and Upper Atmosphere Research Satellite-retrieved effective radii. We calculate statistical ensembles of GCM simulations with and without volcanic aerosols for 2 years after the eruption for three different sea surface temperatures (SSTs): climatological SST, El Nino-type SST of 1991-1993, and La Nina-type SST of 1984-1986. We performed detailed comparisons of calculated fields with observations, We analyzed the atmospheric response to Pinatubo radiative forcing and the ability of the GCM to reproduce it with different SSTs. The temperature of the tropical lower stratosphere increased by 4 K because of aerosol absorption of terrestrial longwave and solar near-infrared radiation. The heating is larger than observed, but that is because in this simulation we did not account for quasi-biennial oscillation (QBO) cooling and the cooling effects of volcanically induced ozone depletion. We estimated that both QBO and ozone depletion decrease the stratospheric temperature by about 2 K. The remaining 2 K stratospheric warming is in good agreement with observations. By comparing the runs with the Pinatubo aerosol forcing with those with no aerosols, we find that the model calculates a general cooling of the global troposphere, but with a clear winter warming pattern of surface air temperature over Northern Hemisphere continents. This pattern is consistent with the observed temperature patterns. The stratospheric heating and tropospheric summer cooling are directly caused by aerosol radiative effects, but the winter warming is indirect, produced by dynamical responses to the enhanced stratospheric latitudinal temperature gradient. The aerosol radiative forcing, stratospheric thermal response, and summer tropospheric cooling do not depend significantly on SST. The stratosphere-troposphere dynamic interactions and tropospheric climate response in winter are sensitive to SST

Decoding the activity of neuronal populations in macaque primary visual cortex

Visual function depends on the accuracy of signals carried by visual cortical neurons. Combining information across neurons should improve this accuracy because single neuron activity is variable. We examined the reliability of information inferred from populations of simultaneously recorded neurons in macaque primary visual cortex. We considered a decoding framework that computes the likelihood of visual stimuli from a pattern of population activity by linearly combining neuronal responses and tested this framework for orientation estimation and discrimination. We derived a simple parametric decoder assuming neuronal independence and a more sophisticated empirical decoder that learned the structure of the measured neuronal response distributions, including their correlated variability. The empirical decoder used the structure of these response distributions to perform better than its parametric variant, indicating that their structure contains critical information for sensory decoding. These results show how neuronal responses can best be used to inform perceptual decision-making