308 research outputs found
Re-evaluating frontopolar and temporoparietal contributions to detection and discrimination confidence
Previously, we identified a subset of regions where the relation between decision confidence and univariate functional magnetic resonance imaging (fMRI) activity was quadratic, with stronger activation for both high and low compared with intermediate levels of confidence. We further showed that, in a subset of these regions, this quadratic modulation appeared only for confidence in detection decisions about the presence or absence of a stimulus, and not for confidence in discrimination decisions about stimulus identity (Mazor et al. 2021). Here, in a pre-registered follow-up experiment, we sought to replicate our original findings and identify the origins of putative detection-specific confidence signals by introducing a novel asymmetric-discrimination condition. The new condition required discriminating two alternatives but was engineered such that the distribution of perceptual evidence was asymmetric, just as in yes/no detection. We successfully replicated the quadratic modulation of subjective confidence in prefrontal, parietal and temporal cortices. However, in contrast with our original report, this quadratic effect was similar in detection and discrimination responses, but stronger in the novel asymmetric-discrimination condition. We interpret our findings as weighing against the detection-specificity of confidence signatures and speculate about possible alternative origins of a quadratic modulation of decision confidence
Dynamic Scaling in the Susceptibility of the Spin-1\2 Kagome Lattice Antiferromagnet Herbertsmithite
The spin-1/2 kagome lattice antiferromagnet herbertsmithite,
ZnCu(OH)Cl, is a candidate material for a quantum spin liquid
ground state. We show that the magnetic response of this material displays an
unusual scaling relation in both the bulk ac susceptibility and the low energy
dynamic susceptibility as measured by inelastic neutron scattering. The
quantity with can be expressed as a
universal function of or . This scaling is discussed in
relation to similar behavior seen in systems influenced by disorder or by the
proximity to a quantum critical point.Comment: 5 pages, 3 figures v2: updated to match published version
Physical Passive Patch Adversarial Attacks on Visual Odometry Systems
Deep neural networks are known to be susceptible to adversarial perturbations
-- small perturbations that alter the output of the network and exist under
strict norm limitations. While such perturbations are usually discussed as
tailored to a specific input, a universal perturbation can be constructed to
alter the model's output on a set of inputs. Universal perturbations present a
more realistic case of adversarial attacks, as awareness of the model's exact
input is not required. In addition, the universal attack setting raises the
subject of generalization to unseen data, where given a set of inputs, the
universal perturbations aim to alter the model's output on out-of-sample data.
In this work, we study physical passive patch adversarial attacks on visual
odometry-based autonomous navigation systems. A visual odometry system aims to
infer the relative camera motion between two corresponding viewpoints, and is
frequently used by vision-based autonomous navigation systems to estimate their
state. For such navigation systems, a patch adversarial perturbation poses a
severe security issue, as it can be used to mislead a system onto some
collision course. To the best of our knowledge, we show for the first time that
the error margin of a visual odometry model can be significantly increased by
deploying patch adversarial attacks in the scene. We provide evaluation on
synthetic closed-loop drone navigation data and demonstrate that a comparable
vulnerability exists in real data. A reference implementation of the proposed
method and the reported experiments is provided at
https://github.com/patchadversarialattacks/patchadversarialattacks.Comment: Accepted to ACCV 202
- …