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Neurons in Cat Primary Visual Cortex cluster by degree of tuning but not by absolute spatial phase or temporal response phase
Neighboring neurons in cat primary visual cortex (V1) have similar preferred orientation, direction, and spatial frequency. How diverse is their degree of tuning for these properties? Are they also clustered in their tuning for the spatial phase of a flashed grating ("absolute spatial phase") or the temporal phase of a drifting grating ("temporal response phase")? To address these questions, we used tetrode recordings to simultaneously isolate multiple cells at single recording sites and record their responses to flashed and drifting gratings of multiple orientations, spatial frequencies, and spatial/temporal phases.
We recorded the responses of 761 cells presented with drifting gratings and 409 cells presented with flashed gratings. We found that orientation tuning width, spatial frequency tuning width and direction selectivity index all showed significant clustering. Absolute spatial phase and temporal response phase, however, showed no clustering. We also present an algorithm that improves the performance of spike-sorting algorithms, for use in analyzing cells recorded using tetrodes. A cluster of spikes corresponding to a putative cell obtained through automatic or manual spike sorting algorithms may contain spikes from other cells with similarly-shaped waveforms.
Our algorithm preferentially removes contaminating spikes from other cells, thereby decreasing the level of contamination of each unit. We call this procedure "pruning", as it entails removing portions of the cluster that are determined to be more likely to contain contaminating spikes than the cluster as a whole. Testing of the algorithm on data in which "ground truth" is known shows excellent performance, for example on average giving a percentage reduction in false positive spikes 8.2 times the percentage reduction in true positive spikes, and reducing the degree of contamination by an average of about 13%
Measuring Entanglement using Programmable Holograms
The Einstein–Podolsky–Rosen (EPR) paradox proposes an entangled quantum state in high dimensional non-commuting observables, position and momentum. We experimentally demonstrate a novel method for measuring spatial correlations in joint position and joint momentum space for entangled photons in an EPR-like state. Research in the field of quantum optics can provide insight into quantum information processing, communication, quantum key distribution, and further investigation into the EPR paradox and locality. Unlike existing techniques, we take measurements of non-commuting observables using a static configuration. A 405nm pump laser incident on a Bismuth Borate nonlinear crystal produces an EPR state as a pair of 810nm photons through the process of spontaneous parametric downconversion. To measure spatial correlations, we take advantage of holograms displayed on digital micromirror devices (DMDs). This method allows for control over the basis that is measured only by changing what hologram is displayed on the DMD, without having to add lenses or other bulk optic components. The field interaction that generates a hologram can be computationally simulated and displayed on the DMD allowing for a momentum mode projection onto the incident state. Collection of joint position and joint momentum correlations provide an entanglement witness. Verification of entanglement using this technique provides the framework to investigate projections onto arbitrary states and explore further quantum communication advances
The Law of Employee Benefit Plans
What are commonly called “fringe benefits” in union agreements are formed out of threads taken from many parts of the fabric of law: a large skein of contract law; binding threads from the law of trusts, agency and taxation; and many colorful strands from a host of labor law statutes. The legal principles are for the most part not unique or novel. Rather, the accumulation of new economic and social arrangements has brought together a variety of familiar legal rules that take on the appearance of a system or body of interrelated legal doctrines. In light of the current Congressional investigations, there may soon be special legislation for employee benefit plans. Such legislation will be woven from threads of the present law on the subject; hence, this paper will undertake to trace the salient filaments of that law
Improving the Robustness of Quantized Deep Neural Networks to White-Box Attacks using Stochastic Quantization and Information-Theoretic Ensemble Training
Most real-world applications that employ deep neural networks (DNNs) quantize
them to low precision to reduce the compute needs. We present a method to
improve the robustness of quantized DNNs to white-box adversarial attacks. We
first tackle the limitation of deterministic quantization to fixed ``bins'' by
introducing a differentiable Stochastic Quantizer (SQ). We explore the
hypothesis that different quantizations may collectively be more robust than
each quantized DNN. We formulate a training objective to encourage different
quantized DNNs to learn different representations of the input image. The
training objective captures diversity and accuracy via mutual information
between ensemble members. Through experimentation, we demonstrate substantial
improvement in robustness against attacks even if the attacker is
allowed to backpropagate through SQ (e.g., > 50\% accuracy to PGD(5/255) on
CIFAR10 without adversarial training), compared to vanilla DNNs as well as
existing ensembles of quantized DNNs. We extend the method to detect attacks
and generate robustness profiles in the adversarial information plane (AIP),
towards a unified analysis of different threat models by correlating the MI and
accuracy.Comment: 9 pages, 9 figures, 4 table
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