This archive contains spike trains simultaneously recorded from ganglion cells in the tiger salamander retina with a multi-electrode array while viewing a repeated natural movie clip. These data have been analyzed in previous papers, notably Puchalla et al. Neuron 2005 and Schneidman et al. Nature 2006.
Recent advances in experimental techniques have allowed the simultaneous recordings of
populations of hundreds of neurons, fostering a debate about the nature of the collective
structure of population neural activity. Much of this debate has focused on the
empirical findings of a phase transition in the parameter space of maximum entropy
models describing the measured neural probability distributions, interpreting this phase
transition to indicate a critical tuning of the neural code. Here, we instead focus on the
possibility that this is a first-order phase transition which provides evidence that the
real neural population is in a `structured', collective state. We show that this collective
state is robust to changes in stimulus ensemble and adaptive state. We find that the
pattern of pairwise correlations between neurons has a strength that is well within the
strongly correlated regime and does not require fine tuning, suggesting that this state is
generic for populations of 100+ neurons. We find a clear correspondence between the
emergence of a phase transition, and the emergence of attractor-like structure in the
inferred energy landscape. A collective state in the neural population, in which neural
activity patterns naturally form clusters, provides a consistent interpretation for our
Berryman, Eleanor J.; Winey, J. M.; Gupta, Yogendra M.; Duffy, Thomas S.
Stishovite (rutile-type SiO2) is the archetype of dense silicates and may occur in post-garnet eclogitic rocks at lower-mantle conditions. Sound velocities in stishovite are fundamental to understanding its mechanical and thermodynamic behavior at high pressure and temperature. Here, we use plate-impact experiments combined with velocity interferometry to determine the stress, density, and longitudinal sound speed in stishovite formed during shock compression of fused silica at 44 GPa and above. The measured sound speeds range from 12.3(8) km/s at 43.8(8) GPa to 9.8(4) km/s at 72.7(11) GPa. The decrease observed at 64 GPa reacts a decrease in the shear modulus of stishovite, likely due to the onset of melting. By 72 GPa, the measured sound speed agrees with the theoretical bulk sound speed indicating loss of all shear stiffness due to complete melting. Our sound velocity results provide direct evidence for shock-induced melting, in agreement with previous pyrometry data.
Taylor, Jenny A.; Bratton, Benjamin P.; Sichel, Sophie R.; Blair, Kris M.; Jacobs, Holly M.; DeMeester, Kristen E.; Kuru, Erkin; Gray, Joe; Biboy, Jacob; VanNieuwenhze, Michael S.; Vollmer, Waldemar; Grimes, Catherine L.; Shaevitz, Joshua W.; Salama, Nina R.
Helical cell shape is necessary for efficient stomach colonization by Helicobacter pylori, but the molecular mechanisms for generating helical shape remain unclear. We show that the helical centerline pitch and radius of wild-type H. pylori cells dictate surface curvatures of considerably higher positive and negative Gaussian curvatures than those present in straight- or curved-rod bacteria. Quantitative 3D microscopy analysis of short pulses with either N-acetylmuramic acid or D-alanine metabolic probes showed that cell wall growth is enhanced at both sidewall curvature extremes. Immunofluorescence revealed MreB is most abundant at negative Gaussian curvature, while the bactofilin CcmA is most abundant at positive Gaussian curvature. Strains expressing CcmA variants with altered polymerization properties lose helical shape and associated positive Gaussian curvatures. We thus propose a model where CcmA and MreB promote PG synthesis at positive and negative Gaussian curvatures, respectively, and that this patterning is one mechanism necessary for maintaining helical shape.
Monitoring the attention of others is fundamental to social cognition. Most of the literature on the topic assumes that our social cognitive machinery is tuned specifically to the gaze direction of others as a proxy for attention. This standard assumption reduces attention to an externally visible parameter. Here we show that this assumption is wrong and a deeper, more meaningful representation is involved. We presented subjects with two cues about the attentional state of a face: direction of gaze and emotional expression. We tested whether people relied predominantly on one cue, the other, or both. If the traditional view is correct, then the gaze cue should dominate. Instead, people employed a variety of strategies, some relying on gaze, some on expression, and some on an integration of cues. We also assessed people’s social cognitive ability using two, independent, standard tests. If the traditional view is correct, then social cognitive ability, as assessed by the independent tests, should correlate with the degree to which people successfully use the gaze cue to judge the attention state of the face. Instead, social cognitive ability correlated best with the degree to which people successfully integrated the cues together, instead of with the use of any one specific cue. The results suggest a rethink of a fundamental component of social cognition: monitoring the attention of others involves constructing a deep model that is informed by a combination of cues. Attention is a rich process and monitoring the attention of others involves a similarly rich representation.
Hill, K. W.; Gao, L.; Kraus, B. F.; Bitter, M.; Efthimion, P. C.; Pablant, N. A.; Schneider, M. B.; Thorn, D. B.; Chen, H.; Kauffman, R. L.; Liedahl, D. A.; MacDonald, M. J.; MacPhee, A. J.; Scott, H. A.; Stoupin, S.; Doron, R.; Stambulchik, E.; Maron, Y.; Lahmann, B.
This distribution compiles numerous physical properties for 2,585 intrinsically disordered proteins (IDPs) obtained by coarse-grained molecular dynamics simulation. This combination comprises "Dataset A" as reported in "Featurization strategies for polymer sequence or composition design by machine learning" by Roshan A. Patel, Carlos H. Borca, and Michael A. Webb (DOI: 10.1039/D1ME00160D). The specific IDP sequences are sourced from version 9.0 of the DisProt database. The simulations were performed using the LAMMPS molecular dynamics engine. The interactions used for simulation are obtained from R. M. Regy , J. Thompson , Y. C. Kim and J. Mittal , Improved coarse-grained model for studying sequence dependent phase separation of disordered proteins, Protein Sci., 2021, 1371 —1379.
This distribution contains experimentally measured data for the extent of retained enzyme activity post thermal stressing for three distinct enzymes: glucose oxidase, lipase, and horseradish peroxidase. The data is used to form conclusions and develop machine learning models as reported in the publication "Machine Learning on a Robotic Platform for the Design of Polymer-Protein Hybrids" by Matthew Tamasi, Roshan Patel, Carlos Borca, Shashank Kosuri, Heloise Mugnier, Rahul Upadhya, N. Sanjeeva Murthy, Michael Webb*, and Adam Gormley. Details regarding the experimental protocols are reported in the aforementioned paper but are briefly discussed in the README.