Natural ITD statistics predict human auditory spatial perception

A neural code adapted to the statistical structure of sensory cues may optimize perception. We investigated whether interaural time difference (ITD) statistics inherent in natural acoustic scenes are parameters determining spatial discriminability. The natural ITD rate of change across azimuth (ITDrc) and ITD variability over time (ITDv) were combined in a Fisher information statistic to assess the amount of azimuthal information conveyed by this sensory cue. We hypothesized that natural ITD statistics underlie the neural code for ITD and thus influence spatial perception. To test this hypothesis, sounds with invariant statistics were presented to measure human spatial discriminability and spatial novelty detection. Human auditory spatial perception showed correlation with natural ITD statistics, supporting our hypothesis. Further analysis showed that these results are consistent with classic models of ITD coding and can explain the ITD tuning distribution observed in the mammalian brainstem.

A Bi-Invariant Statistical Model Parametrized by Mean and Covariance on Rigid Motions

This paper aims to describe a statistical model of wrapped densities for bi-invariant statistics on the group of rigid motions of a Euclidean space. Probability distributions on the group are constructed from distributions on tangent spaces and pushed to the group by the exponential map. We provide an expression of the Jacobian determinant of the exponential map of S E ( n ) which enables the obtaining of explicit expressions of the densities on the group. Besides having explicit expressions, the strengths of this statistical model are that densities are parametrized by their moments and are easy to sample from. Unfortunately, we are not able to provide convergence rates for density estimation. We provide instead a numerical comparison between the moment-matching estimators on S E ( 2 ) and R 3 , which shows similar behaviors.

Natural ITD statistics predict human auditory spatial perception

A neural code adapted to the statistical structure of sensory cues may optimize perception. We investigated whether interaural time difference (ITD) statistics inherent in natural acoustic scenes are parameters determining spatial discriminability. The natural ITD rate of change across azimuth (ITDrc) and ITD variability over time (ITDv) were combined in a Fisher information statistic for assessing the amount of azimuthal information conveyed by this sensory cue. We hypothesized that natural ITD statistics drive the neural code for ITD and thus influence spatial perception. Human spatial discriminability and spatial novelty detection of sounds with invariant statistics correlated with natural ITD statistics. The lack of natural statistics in the stimuli suggests that this correlation results from natural statistics driving the neural code. Additionally, the density distribution of ITD tuning matching natural statistics is consistent with classic models of ITD coding and can explain the ITD tuning distribution observed in the mammalian brainstem.Impact statementHuman brain has incorporated natural statistics of spatial cues to the neural code supporting perception of sound location.Major subject areaNeuroscience;Research organismHuman;

Results and Analysis of Implicit Large Eddy Simulations of Equilibrium Spatially Developing Turbulent Boundary Layers at Multiple Mach Numbers

Equilibrium turbulent flat plate boundary layers with time invariant statistics were obtained at Mach numbers 1.7, 2.3, and 2.9. These are to be used as the initial condition for Large Eddy Simulations (LES) or Direct Numerical Simulations (DNS) of shock wave/turbulent boundary layer interactions utilizing a body force-based method. The results obtained are supplemented by an analysis of the mean and statistical properties of the respective boundary layers. The spanwise extent of the domain required to allow adequate decorrelation between the centerline and the boundaries is investigated by extensively probing the flowfields obtained. This is done to quantify the coherent structures of the turbulent flow. Specifically, two point correlations and integral length scales are used to investigate spanwise decorrelation distances in an attempt to pick a computational domain which is large enough to permit decorrelation downstream but small enough to minimize computational costs. It is shown that by examining the precursor events in the upstream region, namely the generalized stability criterion, it is possible to provide estimates for the force field parameters necessary for transition for a given flow, with only a small portion of the domain in the neighborhood of the trip. The technique is made even more efficient by investigating the possibility of determining these parameters using a two-dimensional simulation. Additionally, the three flow fields obtained are surveyed to confirm that they are suitable for subsequent SBLI simulations. We check that (i)they possess the expected turbulent characteristics and (ii)there is no signature of the tripping mechanism.