Neurally Encoding Time for Olfactory Navigation
Publication Date
January 05, 2016
Journal
PLOS Computational Biology
Authors
In Jun Park, Andrew M. Hein, Yuriy V. Bobkov, Matthew A. Reidenbach, et al
Volume
12
Issue
1
Pages
e1004682
DOI
https://dx.plos.org/10.1371/journal.pcbi.1004682
Publisher URL
http://journals.plos.org/ploscompbiol/article?id=10.1371%2Fjournal.pcbi.1004682
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/26730727
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4711578
Europe PMC
http://europepmc.org/abstract/MED/26730727
Web of Science
000369366100021
Scopus
84956788745
Mendeley
http://www.mendeley.com/research/neurally-encoding-time-olfactory-navigation
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Mendeley | Further Information

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Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/2620815"], "description"=>"<p>Instantaneous odor concentration (expressed as % of source concentration) at (A) x = 50 cm, (B) x = 100 cm, (C) x = 150 cm, (D) x = 200 cm, (E) x = 250 cm from the source along the odor plume centerline, and (F) y = 5 cm, (G) y = 10 cm from the odor plume centerline at x = 150 cm.</p>", "links"=>[], "tags"=>["odor plume", "neuron", "odor cues", "information processing", "odor pulses", "encode", "odor source", "spatiotemporal behavior", "use recurrence theory", "odor encounters", "Neurally Encoding Time", "Olfactory Navigation Accurately encoding time", "odor arrivals", "odor field"], "article_id"=>1632913, "categories"=>["Uncategorised"], "users"=>["In Jun Park", "Andrew M. Hein", "Yuriy V. Bobkov", "Matthew A. Reidenbach", "Barry W. Ache", "José C. Príncipe"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1004682.g002", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Odor_plume_PLIF_videos_taken_at_15_locations_/1632913", "title"=>"Odor plume PLIF videos taken at 15 locations.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-01-18 14:25:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/2620817"], "description"=>"<p>Black points in the recurrence plots indicate that recurrence occurs; white regions indicate that recurrence does not occur (see <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004682#sec002\" target=\"_blank\">Results</a>).</p>", "links"=>[], "tags"=>["odor plume", "neuron", "odor cues", "information processing", "odor pulses", "encode", "odor source", "spatiotemporal behavior", "use recurrence theory", "odor encounters", "Neurally Encoding Time", "Olfactory Navigation Accurately encoding time", "odor arrivals", "odor field"], "article_id"=>1632915, "categories"=>["Uncategorised"], "users"=>["In Jun Park", "Andrew M. Hein", "Yuriy V. Bobkov", "Matthew A. Reidenbach", "Barry W. Ache", "José C. Príncipe"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1004682.g003", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Recurrence_plots_upper_panels_and_corresponding_concentration_time_series_lower_panels_for_selected_locations_in_the_plume_A_x_50_cm_B_x_150_cm_from_the_source_along_the_plume_centerline_and_C_y_10_cm_from_the_centerline_at_x_150_cm_where_height_is_2_5_c/1632915", "title"=>"Recurrence plots (upper panels) and corresponding concentration time series (lower panels) for selected locations in the plume: (A) x = 50 cm, (B) x = 150 cm from the source along the plume centerline, and (C) y = 10 cm from the centerline at x = 150 cm, where height is 2.5 cm from the substratum.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-01-18 14:25:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/2620819"], "description"=>"<p>(A) Example trajectory in reconstructed phase space. Two types of recurrence time index are obtained by averaging time intervals between all successive recurrent points (<math><msub><mi>T</mi><mo>¯</mo><mn>1</mn></msub></math>) or only returning points (<math><msub><mi>T</mi><mo>¯</mo><mn>2</mn></msub></math>) in a circle of radius <i>r</i> centered at a reference point <b>x</b><sub>0</sub>. To estimate <math><msub><mi>T</mi><mo>¯</mo><mn>1</mn></msub></math>, the refractory period of at least some bORNs in the population would need to be short relative to the times between successive recurrence points. <math><msub><mi>T</mi><mo>¯</mo><mn>2</mn></msub></math> can be estimated with longer refractory periods. (B) Mean (points) and standard deviation of <math><msub><mi>T</mi><mo>¯</mo><mn>1</mn></msub></math> and <math><msub><mi>T</mi><mo>¯</mo><mn>2</mn></msub></math> indices for positions in downstream direction. (C) Mean and standard deviation of <math><msub><mi>T</mi><mo>¯</mo><mn>1</mn></msub></math> and <math><msub><mi>T</mi><mo>¯</mo><mn>2</mn></msub></math> indices for positions in cross-stream direction.</p>", "links"=>[], "tags"=>["odor plume", "neuron", "odor cues", "information processing", "odor pulses", "encode", "odor source", "spatiotemporal behavior", "use recurrence theory", "odor encounters", "Neurally Encoding Time", "Olfactory Navigation Accurately encoding time", "odor arrivals", "odor field"], "article_id"=>1632917, "categories"=>["Uncategorised"], "users"=>["In Jun Park", "Andrew M. Hein", "Yuriy V. Bobkov", "Matthew A. Reidenbach", "Barry W. Ache", "José C. Príncipe"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1004682.g004", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Recurrence_time_and_position_in_the_plume_/1632917", "title"=>"Recurrence time and position in the plume.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-01-18 14:25:55"}
  • {"files"=>["https://ndownloader.figshare.com/files/2620821"], "description"=>"<p>(A) Search strategy based on a pair of sensors. The searcher compares measurements of the time since the last odor arrival, Δ, or measurements of concentration, <i>C</i>, registered by left and right sensors and steers in the direction of the shorter time or higher concentration. (B) Example trajectory of bORN-based strategy (initial position is x = 150 cm, y = 0 cm). The searcher begins at the “start” point and stops at the “end” point. The trajectory is continuous, with decisions made at every dot. Points that end outside the plume indicate that the searcher backtracks to its previous position. (C, D) Mean and standard error for number of steps required for strategies based on measurements of concentration (blue) and time since last encounter (bORN strategy, red) as a function of starting location relative to the source.</p>", "links"=>[], "tags"=>["odor plume", "neuron", "odor cues", "information processing", "odor pulses", "encode", "odor source", "spatiotemporal behavior", "use recurrence theory", "odor encounters", "Neurally Encoding Time", "Olfactory Navigation Accurately encoding time", "odor arrivals", "odor field"], "article_id"=>1632919, "categories"=>["Uncategorised"], "users"=>["In Jun Park", "Andrew M. Hein", "Yuriy V. Bobkov", "Matthew A. Reidenbach", "Barry W. Ache", "José C. Príncipe"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1004682.g005", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Search_strategy_using_bORNs_or_measurements_of_concentration_/1632919", "title"=>"Search strategy using bORNs or measurements of concentration.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-01-18 14:25:50"}
  • {"files"=>["https://ndownloader.figshare.com/files/2620826", "https://ndownloader.figshare.com/files/2620828", "https://ndownloader.figshare.com/files/2620829"], "description"=>"<div><p>Accurately encoding time is one of the fundamental challenges faced by the nervous system in mediating behavior. We recently reported that some animals have a specialized population of rhythmically active neurons in their olfactory organs with the potential to peripherally encode temporal information about odor encounters. If these neurons do indeed encode the timing of odor arrivals, it should be possible to demonstrate that this capacity has some functional significance. Here we show how this sensory input can profoundly influence an animal’s ability to locate the source of odor cues in realistic turbulent environments—a common task faced by species that rely on olfactory cues for navigation. Using detailed data from a turbulent plume created in the laboratory, we reconstruct the spatiotemporal behavior of a real odor field. We use recurrence theory to show that information about position relative to the source of the odor plume is embedded in the timing between odor pulses. Then, using a parameterized computational model, we show how an animal can use populations of rhythmically active neurons to capture and encode this temporal information in real time, and use it to efficiently navigate to an odor source. Our results demonstrate that the capacity to accurately encode temporal information about sensory cues may be crucial for efficient olfactory navigation. More generally, our results suggest a mechanism for extracting and encoding temporal information from the sensory environment that could have broad utility for neural information processing.</p></div>", "links"=>[], "tags"=>["odor plume", "neuron", "odor cues", "information processing", "odor pulses", "encode", "odor source", "spatiotemporal behavior", "use recurrence theory", "odor encounters", "Neurally Encoding Time", "Olfactory Navigation Accurately encoding time", "odor arrivals", "odor field"], "article_id"=>1632924, "categories"=>["Uncategorised"], "users"=>["In Jun Park", "Andrew M. Hein", "Yuriy V. Bobkov", "Matthew A. Reidenbach", "Barry W. Ache", "José C. Príncipe"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1004682.s001", "https://dx.doi.org/10.1371/journal.pcbi.1004682.s002", "https://dx.doi.org/10.1371/journal.pcbi.1004682.s003"], "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Neurally_Encoding_Time_for_Olfactory_Navigation_/1632924", "title"=>"Neurally Encoding Time for Olfactory Navigation", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2016-01-18 14:25:52"}
  • {"files"=>["https://ndownloader.figshare.com/files/2620813"], "description"=>"<p>(A) Electrophysiological recordings of spontaneous bursting from three bORNs with different intrinsic burst frequencies (left), and bursting pattern of a single bORN (right) stimulated with odor (blue marks). Trials aligned in order of increasing time since last burst (bottom to top). Note that bORN does not respond to stimulus when time since last burst is short (bottom 4 trials) and instead, continues to burst spontaneously, (B) Probability of bursting in response to odorant as a function of time since last burst <i>τ</i>. Blue points are electrophysiologial data; blue line is sigmoid fit to data. Red curve represents the probability that the bORN will go <i>τ</i> seconds before bursting spontaneously (1—CDF of spontaneous inter-burst interval). Together, these curves tune the bORN to be most sensitive to odors that arrive with a particular frequency. (C) Probability of bursting in response to a stimulus as a function of stimulus frequency for two bORNs tuned by different evoked and spontaneous burst functions. (D) Raster plot (upper) and burst histogram (lower) of a heterogeneous population of 210 bORNs constructed from multiple single-neuron electrophysiological recordings showing spontaneous bursting and responses to odor stimuli (blue marks). This reconstructed population of bORNs encodes time between two odor stimuli (20.7 s). (E) The time interval between odor stimuli can be decoded from the bursting pattern of a heterogeneous bORN population shown in (D) using a simple maximum likelihood procedure (decoded interval is 23.2 s). Data are from [<a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004682#pcbi.1004682.ref019\" target=\"_blank\">19</a>].</p>", "links"=>[], "tags"=>["odor plume", "neuron", "odor cues", "information processing", "odor pulses", "encode", "odor source", "spatiotemporal behavior", "use recurrence theory", "odor encounters", "Neurally Encoding Time", "Olfactory Navigation Accurately encoding time", "odor arrivals", "odor field"], "article_id"=>1632911, "categories"=>["Uncategorised"], "users"=>["In Jun Park", "Andrew M. Hein", "Yuriy V. Bobkov", "Matthew A. Reidenbach", "Barry W. Ache", "José C. Príncipe"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1004682.g001", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Encoding_and_decoding_time_since_the_last_odor_encounter_from_a_population_of_bORNs_experimental_data_from_the_spiny_lobster_Panulirus_argus_/1632911", "title"=>"Encoding and decoding time since the last odor encounter from a population of bORNs (experimental data from the spiny lobster <i>Panulirus argus</i>).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-01-18 14:25:49"}

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Relative Metric

{"start_date"=>"2016-01-01T00:00:00Z", "end_date"=>"2016-12-31T00:00:00Z", "subject_areas"=>[]}
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