10.5061/DRYAD.04T19
Boie, Sebastian D.
MIND Research Institute
Connor, Erin G.
University of Colorado Boulder
McHugh, Margaret
University of Colorado Boulder
Nagel, Katherine I.
New York University Langone Medical Center
Ermentrout, G. Bard
University of Pittsburgh
Crimaldi, John P.
University of Colorado Boulder
Victor, Jonathan D.
MIND Research Institute
Data from: Information-theoretic analysis of realistic odor plumes: what
cues are useful for determining location?
Dryad
dataset
2019
National Science Foundation
http://dx.doi.org/10.13039/100000001
NSF PHY1555891, NSF PHY1555862, NSF PHY 1555916, NSF PHY 1555933
2019-06-07T00:00:00Z
en
https://doi.org/10.1371/journal.pcbi.1006275
11792892688 bytes
1
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Many species rely on olfaction to navigate towards food sources or mates.
Olfactory navigation is a challenging task since odor environments are
typically turbulent. While time-averaged odor concentration varies
smoothly with the distance to the source, instaneous concentrations are
intermittent and obtaining stable averages takes longer than the typical
intervals between animalsâ€™ navigation decisions. How to effectively sample
from the odor distribution to determine sampling location is the focus on
this article. To investigate which sampling strategies are most
informative about the location of an odor source, we recorded three
naturalistic stimuli with planar lased-induced fluorescence and used an
information-theoretic approach to quantify the information that different
sampling strategies provide about sampling location. Specifically, we
compared multiple sampling strategies based on a fixed number of coding
bits for encoding the olfactory stimulus. When the coding bits were all
allocated to representing odor concentration at a single sensor,
information rapidly saturated. Using the same number of coding bits in two
sensors provides more information, as does coding multiple samples at
different times. When accumulating multiple samples at a fixed location,
the temporal sequence does not yield a large amount of information and can
be averaged with minimal loss. Furthermore, we show that
histogram-equalization is not the most efficient way to use coding bits
when using the olfactory sample to determine location.
Fast Flow - average plume and snapshotsThe file contains three data sets:
"average", "snapshot_1" and "snapshot_2".
The data corresponds to Fig.1 (A1-A3).fastflow_snapshots.hdf5Slow Flow -
averaged plume and snapshotsThe file contains three data sets:
"average", "snapshot_1" and "snapshot_2".
The data corresponds to Fig.1 (B1-B3).slowflow_snapshots.hdf5Boundary Flow
- averaged plume and snapshotsThe file contains three data sets:
"average", "snapshot_1" and "snapshot_2".
The data corresponds to Fig.1 (C1-C3).boundaryflow_snapshots.hdf5Fast Flow
- narrowgrid, single samplecontains ("sample_0" -
"sample_9") and correspond to 4 minute epochs of timeseries
data.fastflow_narrowgrid_single.hdf5Fast Flow - narrowgrid, binaral
transversalcontains ("sample_L_0" - "sample_L_9") and
("sample_R_0" - "sample_R_9") which correspond to 4
minute epochs at two locations (left and
right).fastflow_narrowgrid_binaral_transversal.hdf5Fast Flow - narrowgrid,
binaral longitudinalcontains ("sample_L_0" -
"sample_L_9") and ("sample_R_0" -
"sample_R_9") which correspond to 4 minute epochs at two
locations (left and
right).fastflow_narrowgrid_binaral_longitudinal.hdf5Fast Flow - widegrid,
single samplecontains ("sample_0" - "sample_9") and
correspond to 4 minute epochs of timeseries
data.fastflow_widegrid_single.hdf5Fast Flow, widegrid, binaral
transversalcontains ("sample_L_0" - "sample_L_9") and
("sample_R_0" - "sample_R_9") which correspond to 4
minute epochs at two locations (left and
right).fastflow_widegrid_binaral_transversal.hdf5Fast Flow - widegrid,
binaral longitudinalcontains ("sample_L_0" -
"sample_L_9") and ("sample_R_0" -
"sample_R_9") which correspond to 4 minute epochs at two
locations (left and right).fastflow_widegrid_binaral_longitudinal.hdf5Slow
Flow - narrowgrid, single samplecontains ("sample_0" -
"sample_8") and correspond to 4 minute epochs of timeseries
data.slowflow_narrowgrid_single.hdf5Slow Flow - widegrid, single
samplecontains ("sample_0" - "sample_9") and
correspond to 4 minute epochs of timeseries
data.slowflow_widegrid_single.hdf5Slow Flow - narrowgrid, binaral
longitudinalcontains ("sample_L_0" - "sample_L_8") and
("sample_R_0" - "sample_R_8") which correspond to 4
minute epochs at two locations (left and
right).slowflow_narrowgrid_binaral_longitudinal.hdf5Slow Flow -
narrowgrid, binaral transversalcontains ("sample_L_0" -
"sample_L_8") and ("sample_R_0" -
"sample_R_8") which correspond to 4 minute epochs at two
locations (left and
right).slowflow_narrowgrid_binaral_transversal.hdf5Slow Flow - widegrid,
binaral longitudinalcontains ("sample_L_0" -
"sample_L_8") and ("sample_R_0" -
"sample_R_8") which correspond to 4 minute epochs at two
locations (left and right).slowflow_widegrid_binaral_longitudinal.hdf5Slow
Flow - widegrid, binaral transversalcontains ("sample_L_0" -
"sample_L_8") and ("sample_R_0" -
"sample_R_8") which correspond to 4 minute epochs at two
locations (left and
right).slowflow_widegrid_binaral_transversal.hdf5Boundary Flow -
narrowgrid, single samplecontains ("sample_0" -
"sample_9") and correspond to 4 minute epochs of timeseries
data.boundaryflow_narrowgrid_single.hdf5Boundary Flow - widegrid, single
samplecontains ("sample_0" - "sample_9") and
correspond to 4 minute epochs of timeseries
data.boundaryflow_widegrid_binaral_single.hdf5Boundary Flow - narrowgrid,
binaral longitudinalcontains ("sample_L_0" -
"sample_L_9") and ("sample_R_0" -
"sample_R_9") which correspond to 4 minute epochs at two
locations (left and
right).boundaryflow_narrowgrid_binaral_longitudinal.hdf5Boundary Flow -
narrowgrid, binaral transversalcontains ("sample_L_0" -
"sample_L_9") and ("sample_R_0" -
"sample_R_9") which correspond to 4 minute epochs at two
locations (left and
right).boundaryflow_narrowgrid_binaral_transversal.hdf5Boundary Flow -
widegrid, binaral longitudinalcontains ("sample_L_0" -
"sample_L_9") and ("sample_R_0" -
"sample_R_9") which correspond to 4 minute epochs at two
locations (left and
right).boundaryflow_widegrid_binaral_longitudinal.hdf5Boundary Flow -
widegrid, binaral transversalcontains ("sample_L_0" -
"sample_L_9") and ("sample_R_0" -
"sample_R_9") which correspond to 4 minute epochs at two
locations (left and
right).boundaryflow_widegrid_binaral_transversal.hdf5Boundary Flow -
narrowgrid, binaral transversal (half spacing)contains
("sample_L_0" - "sample_L_9") and
("sample_R_0" - "sample_R_9") which correspond to 4
minute epochs at two locations (left and
right).boundaryflow_narrowgrid_binaral_transversal_halfspacing.hdf5Boundary Flow - widegrid, binaral transversal (double spacing)contains ("sample_L_0" - "sample_L_9") and ("sample_R_0" - "sample_R_9") which correspond to 4 minute epochs at two locations (left and right).boundaryflow_widegrid_binaral_transversal_doublespacing.hdf5Boundary Flow - widegrid, binaral transversal (half spacing)contains ("sample_L_0" - "sample_L_9") and ("sample_R_0" - "sample_R_9") which correspond to 4 minute epochs at two locations (left and right).boundaryflow_widegrid_binaral_transversal_halfspacing.hdf5Fast Flow - narrowgrid, binaral transversal (double spacing)contains ("sample_L_0" - "sample_L_9") and ("sample_R_0" - "sample_R_9") which correspond to 4 minute epochs at two locations (left and right).fastflow_narrowgrid_binaral_transversal_doublespacing.hdf5Fast Flow - narrowgrid, binaral transversal (half spacing)contains ("sample_L_0" - "sample_L_9") and ("sample_R_0" - "sample_R_9") which correspond to 4 minute epochs at two locations (left and right).fastflow_narrowgrid_binaral_transversal_halfspacing.hdf5Fast Flow - widegrid, binaral transversal (double spacing)contains ("sample_L_0" - "sample_L_9") and ("sample_R_0" - "sample_R_9") which correspond to 4 minute epochs at two locations (left and right).fastflow_widegrid_binaral_transversal_doublespacing.hdf5Fast Flow - widegrid, binaral transversal (half spacing)contains ("sample_L_0" - "sample_L_9") and ("sample_R_0" - "sample_R_9") which correspond to 4 minute epochs at two locations (left and right).fastflow_widegrid_binaral_transversal_halfspacing.hdf5Slow Flow - narrowgrid, binaral transversal (double spacing)contains ("sample_L_0" - "sample_L_8") and ("sample_R_0" - "sample_R_8") which correspond to 4 minute epochs at two locations (left and right).slowflow_narrowgrid_binaral_transversal_doublespacing.hdf5Slow Flow - narrowgrid, binaral transversal (half spacing)contains ("sample_L_0" - "sample_L_8") and ("sample_R_0" - "sample_R_8") which correspond to 4 minute epochs at two locations (left and right).slowflow_narrowgrid_binaral_transversal_halfspacing.hdf5Slow Flow - widegrid, binaral transversal (double spacing)contains ("sample_L_0" - "sample_L_8") and ("sample_R_0" - "sample_R_8") which correspond to 4 minute epochs at two locations (left and right).slowflow_widegrid_binaral_transversal_doublespacing.hdf5Slow Flow - widegrid, binaral transversal (half spacing)contains ("sample_L_0" - "sample_L_8") and ("sample_R_0" - "sample_R_8") which correspond to 4 minute epochs at two locations (left and right).slowflow_widegrid_binaral_transversal_halfspacing.hdf5Boundary Flow - narrowgrid, binaral transversal (double spacing)contains ("sample_L_0" - "sample_L_9") and ("sample_R_0" - "sample_R_9") which correspond to 4 minute epochs at two locations (left and right).boundaryflow_narrowgrid_binaral_transversal_doublespacing.hdf5