Transient Responses to Rapid Changes in Mean and Variance in Spiking Models
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{"title"=>"Transient responses to rapid changes in mean and variance in spiking models", "type"=>"journal", "authors"=>[{"first_name"=>"Peyman", "last_name"=>"Khorsand", "scopus_author_id"=>"6506617330"}, {"first_name"=>"Frances", "last_name"=>"Chance", "scopus_author_id"=>"6603400527"}], "year"=>2008, "source"=>"PLoS ONE", "identifiers"=>{"pui"=>"352749097", "issn"=>"19326203", "doi"=>"10.1371/journal.pone.0003786", "scopus"=>"2-s2.0-56849099297", "pmid"=>"19023442", "sgr"=>"56849099297"}, "id"=>"6aafcfdf-9753-35f3-bfb1-cb9dbfa5f54e", "abstract"=>"The mean input and variance of the total synaptic input to a neuron can vary independently, suggesting two distinct information channels. Here we examine the impact of rapidly varying signals, delivered via these two information conduits, on the temporal dynamics of neuronal firing rate responses. We examine the responses of model neurons to step functions in either the mean or the variance of the input current. Our results show that the temporal dynamics governing response onset depends on the choice of model. Specifically, the existence of a hard threshold introduces an instantaneous component into the response onset of a leaky-integrate-and-fire model that is not present in other models studied here. Other response features, for example a decaying oscillatory approach to a new steady-state firing rate, appear to be more universal among neuronal models. The decay time constant of this approach is a power-law function of noise magnitude over a wide range of input parameters. Understanding how specific model properties underlie these response features is important for understanding how neurons will respond to rapidly varying signals, as the temporal dynamics of the response onset and response decay to new steady-state determine what range of signal frequencies a population of neurons can respond to and faithfully encode.", "link"=>"http://www.mendeley.com/research/transient-responses-rapid-changes-mean-variance-spiking-models", "reader_count"=>10, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>3, "Student > Doctoral Student"=>1, "Researcher"=>5, "Student > Ph. D. Student"=>1}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>3, "Student > Doctoral Student"=>1, "Researcher"=>5, "Student > Ph. D. Student"=>1}, "reader_count_by_subject_area"=>{"Engineering"=>1, "Agricultural and Biological Sciences"=>8, "Physics and Astronomy"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>8}}, "reader_count_by_country"=>{"Germany"=>1}, "group_count"=>0}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/915474"], "description"=>"<p>A) Response to a step of mean input current with τ<sub>s</sub> = 0 ms. B) Response to a current step with τ<sub>s</sub> = 5 ms. C) Response to a step in noise for τ<sub>s</sub> = 0 ms. D) Response to a step in noise for τ<sub>s</sub> = 5 ms. For (A) and (B), the variance of synaptic component was 36000 mV<sup>2</sup>-ms. For (C) and (D), the variance of synaptic component (prior to the noise step) was 4000 mV<sup>2</sup>-ms.</p>", "links"=>[], "tags"=>["firing", "rates"], "article_id"=>585936, "categories"=>["Neuroscience", "Biological Sciences"], "users"=>["Peyman Khorsand", "Frances Chance"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0003786.g004", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_QIF_model_firing_rates_in_response_to_a_jump_in_mean_input_current_or_noise_/585936", "title"=>"QIF model firing rates in response to a jump in mean input current or noise.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-11-21 01:38:56"}
  • {"files"=>["https://ndownloader.figshare.com/files/915684"], "description"=>"<p>A) Probability distribution of the conductance-based model, plotted against membrane potential (V) and the potassium gating variable (n). The variance of the synaptic component was 1000 mV<sup>2</sup>-ms. B) Firing rate of the conductance-based model in response to a step of input current. The synaptic time constant, τ<sub>s</sub>, was 0 ms. The variance of synaptic component was 4000 mV<sup>2</sup>-ms. C) Firing rate of the conductance-based model in response to a step of noise, with τ<sub>s</sub> = 0 ms. The variance of synaptic component (prior to the noise step) was 2250 mV<sup>2</sup>-ms.</p>", "links"=>[], "tags"=>["conductance-based"], "article_id"=>586148, "categories"=>["Neuroscience", "Biological Sciences"], "users"=>["Peyman Khorsand", "Frances Chance"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0003786.g006", "stats"=>{"downloads"=>2, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Membrane_potential_distribution_of_the_conductance_based_model_/586148", "title"=>"Membrane potential distribution of the conductance-based model.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-11-21 01:42:28"}
  • {"files"=>["https://ndownloader.figshare.com/files/915977"], "description"=>"<p>The top panels of EIF firing rates in response to jumps in mean input current and the bottom panels are EIF firing rates in response to jumps in noise. As in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0003786#pone-0003786-g007\" target=\"_blank\">figures 7</a> and <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0003786#pone-0003786-g008\" target=\"_blank\">8</a>, for panels (A) and (C), τ<sub>s</sub> = 0 ms, and for panels (B) and (D), τ<sub>s</sub> = 5 ms. As in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0003786#pone-0003786-g008\" target=\"_blank\">Fig. 8</a>, noise variance was 4000 mV<sup>2</sup>-ms for (A) and (B), or 2250 mV<sup>2</sup>-ms prior to the step in noise for (C) and (D).</p>", "links"=>[], "tags"=>["oscillatory", "responses", "jumps"], "article_id"=>586437, "categories"=>["Neuroscience", "Biological Sciences"], "users"=>["Peyman Khorsand", "Frances Chance"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0003786.g009", "stats"=>{"downloads"=>0, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_EIF_oscillatory_responses_to_jumps_in_mean_input_current_and_noise_/586437", "title"=>"EIF oscillatory responses to jumps in mean input current and noise.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-11-21 01:47:17"}
  • {"files"=>["https://ndownloader.figshare.com/files/452476"], "description"=>"<div><p>The mean input and variance of the total synaptic input to a neuron can vary independently, suggesting two distinct information channels. Here we examine the impact of rapidly varying signals, delivered via these two information conduits, on the temporal dynamics of neuronal firing rate responses. We examine the responses of model neurons to step functions in either the mean or the variance of the input current. Our results show that the temporal dynamics governing response onset depends on the choice of model. Specifically, the existence of a hard threshold introduces an instantaneous component into the response onset of a leaky-integrate-and-fire model that is not present in other models studied here. Other response features, for example a decaying oscillatory approach to a new steady-state firing rate, appear to be more universal among neuronal models. The decay time constant of this approach is a power-law function of noise magnitude over a wide range of input parameters. Understanding how specific model properties underlie these response features is important for understanding how neurons will respond to rapidly varying signals, as the temporal dynamics of the response onset and response decay to new steady-state determine what range of signal frequencies a population of neurons can respond to and faithfully encode.</p></div>", "links"=>[], "tags"=>["transient", "responses", "changes", "variance", "spiking", "models"], "article_id"=>149126, "categories"=>["Neuroscience", "Biological Sciences"], "users"=>["Peyman Khorsand", "Frances Chance"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0003786", "stats"=>{"downloads"=>12, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Transient_Responses_to_Rapid_Changes_in_Mean_and_Variance_in_Spiking_Models/149126", "title"=>"Transient Responses to Rapid Changes in Mean and Variance in Spiking Models", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2008-11-21 02:32:06"}
  • {"files"=>["https://ndownloader.figshare.com/files/916178"], "description"=>"<p>A) Firing rate of the conductance-based model in response to a step of input current. The synaptic time constant, τ<sub>s</sub>, was 0 ms. The variance of synaptic component was 722.5 mV<sup>2</sup>-ms. B) Firing rate of the conductance-based model in response to a step of noise, with τ<sub>s</sub> = 0 ms. The variance of synaptic component was 160 mV<sup>2</sup>-ms.</p>", "links"=>[], "tags"=>["responses", "conductance-based"], "article_id"=>586632, "categories"=>["Neuroscience", "Biological Sciences"], "users"=>["Peyman Khorsand", "Frances Chance"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0003786.g011", "stats"=>{"downloads"=>3, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Oscillating_responses_of_the_conductance_based_model_under_lower_noise_conditions_/586632", "title"=>"Oscillating responses of the conductance-based model under lower noise conditions.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-11-21 01:50:32"}
  • {"files"=>["https://ndownloader.figshare.com/files/915400"], "description"=>"<p>A) Probability distribution of the QIF model membrane potential. B) Probability distribution of the EIF model. For both panels, τ<sub>s</sub> = 0 ms and the variance of synaptic component was 9000 mV<sup>2</sup>-ms, resulting in an average firing rate of 20 Hz.</p>", "links"=>[], "tags"=>["distributions", "qif", "eif"], "article_id"=>585852, "categories"=>["Neuroscience", "Biological Sciences"], "users"=>["Peyman Khorsand", "Frances Chance"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0003786.g003", "stats"=>{"downloads"=>1, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Membrane_potential_distributions_of_QIF_and_EIF_models_/585852", "title"=>"Membrane potential distributions of QIF and EIF models.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-11-21 01:37:32"}
  • {"files"=>["https://ndownloader.figshare.com/files/915830"], "description"=>"<p>For the top panels, the jumps in firing rate were driven by steps in mean input current. For the bottom panels, the model neurons are responding to steps in noise. In panels (A) and (C), τ<sub>s</sub> = 0 ms and the variance of synaptic component was 10 mV<sup>2</sup>-ms. In panels (B) and (D), τ<sub>s</sub> = 5 ms. Prior to the step in noise, the variance of synaptic component was 90 mV<sup>2</sup>-ms in (C) and 40 mV<sup>2</sup>-ms for the variance in synaptic component and 10 mV<sup>2</sup>-ms for the external input variance in (D).</p>", "links"=>[], "tags"=>["oscillating", "jumps"], "article_id"=>586288, "categories"=>["Neuroscience", "Biological Sciences"], "users"=>["Peyman Khorsand", "Frances Chance"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0003786.g007", "stats"=>{"downloads"=>1, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_LIF_oscillating_response_to_jumps_in_mean_input_current_and_noise_/586288", "title"=>"LIF oscillating response to jumps in mean input current and noise.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-11-21 01:44:48"}
  • {"files"=>["https://ndownloader.figshare.com/files/915160"], "description"=>"<p>A and B) Membrane potential probability distributions with (A) τ<sub>s</sub> = 0 ms or (B) τ<sub>s</sub> = 5 ms. I<sub>m</sub> was adjusted to that the overall firing rate was 20 Hz. The variance (σ) of the noise was 640 mV<sup>2</sup>-ms. In (A), the nonzero value of P(V) at V = V<sub>th</sub> arises from the finite time steps that we use by necessity in our simulations. C and D) The value of the probability distribution at spike threshold, P(V<sub>th</sub>), as a function of I<sub>m</sub> and τ<sub>s</sub> under (C) low noise and (D) high noise conditions. E and F) Absolute value of the first derivative of the probability distribution at threshold, |∂P(V<sub>th</sub>)|. In the low noise regime the variance of the synaptic component was 160 mV<sup>2</sup>-ms and in the high noise regime it was 1440 mV<sup>2</sup>-ms. (Input is given in mV, the resulting membrane potential depolarization).</p>", "links"=>[], "tags"=>["lif", "neurons", "finite"], "article_id"=>585624, "categories"=>["Neuroscience", "Biological Sciences"], "users"=>["Peyman Khorsand", "Frances Chance"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0003786.g001", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Membrane_potential_profile_of_a_population_of_LIF_neurons_within_a_finite_interval_of_time_/585624", "title"=>"Membrane potential profile of a population of LIF neurons within a finite interval of time.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-11-21 01:33:44"}
  • {"files"=>["https://ndownloader.figshare.com/files/916096"], "description"=>"<p>LIF τ<sub>decay</sub> (A), QIF τ<sub>decay</sub> (B), and EIF τ<sub>decay</sub> (C) are given as functions of final noise magnitude (noise level after the jump in noise). For the QIF model (B), the decay time constants measured from responses to a jump in mean are given by empty squares and the decay time constant measured from responses to jumps in noise are given by filled circles. τ<sub>0</sub> = 1 ms and σ<sub>0</sub><sup>2</sup> = 0.1 mV<sup>2</sup>-ms.</p>", "links"=>[], "tags"=>["decay", "constants", "integrate-and-fire", "models", "functions"], "article_id"=>586550, "categories"=>["Neuroscience", "Biological Sciences"], "users"=>["Peyman Khorsand", "Frances Chance"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0003786.g010", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Oscillation_decay_time_constants_for_the_integrate_and_fire_models_vary_as_power_functions_of_noise_/586550", "title"=>"Oscillation decay time constants for the integrate-and-fire models vary as power functions of noise.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-11-21 01:49:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/915901"], "description"=>"<p>The top panels are QIF firing rates in response to jumps in mean input current and the bottom panels are QIF firing rates in response to jumps in noise. For panels (A) and (C), τ<sub>s</sub> = 0 ms. For panels (B) and (D), τ<sub>s</sub> = 5 ms. The variance in synaptic component was 4000 mV<sup>2</sup>-ms for (A) and (B), or 2250 mV<sup>2</sup>-ms prior to the step in noise for (C) and (D).</p>", "links"=>[], "tags"=>["qif", "responses", "jumps"], "article_id"=>586360, "categories"=>["Neuroscience", "Biological Sciences"], "users"=>["Peyman Khorsand", "Frances Chance"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0003786.g008", "stats"=>{"downloads"=>3, "page_views"=>19, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Oscillatory_QIF_responses_to_jumps_in_mean_input_current_and_noise_/586360", "title"=>"Oscillatory QIF responses to jumps in mean input current and noise.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-11-21 01:46:00"}
  • {"files"=>["https://ndownloader.figshare.com/files/915583"], "description"=>"<p>A) Response to a current step with τ<sub>s</sub> = 0 ms. B) Response to a current step with τ<sub>s</sub> = 5 ms. C) Response to a step in noise for τ<sub>s</sub> = 0 ms. D) Response to a step in noise for τ<sub>s</sub> = 5 ms. As in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0003786#pone-0003786-g004\" target=\"_blank\">Fig. 4</a>, for panels (A) and (B), the variance of synaptic component was 36000 mV<sup>2</sup>-ms. For (C) and (D), the variance of the synaptic component (prior to the noise step) was 4000 mV<sup>2</sup>-ms.</p>", "links"=>[], "tags"=>["firing", "rates"], "article_id"=>586044, "categories"=>["Neuroscience", "Biological Sciences"], "users"=>["Peyman Khorsand", "Frances Chance"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0003786.g005", "stats"=>{"downloads"=>4, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_EIF_model_firing_rates_in_response_to_a_jump_in_mean_input_current_or_noise_/586044", "title"=>"EIF model firing rates in response to a jump in mean input current or noise.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-11-21 01:40:44"}
  • {"files"=>["https://ndownloader.figshare.com/files/915301"], "description"=>"<p>Each panel is the firing rate of an LIF neuron in response to A) a step in mean input current with τ<sub>s</sub> = 0 ms, B) a step in mean input current with τ<sub>s</sub> = 5 ms, C) a step in input current noise with τ<sub>s</sub> = 0 ms, or D) a step in input current noise with τ<sub>s</sub> = 5 ms. In (A) there exists a small instantaneous jump that arises because of the finite time steps used in our simulations. For panels (A–C), the variance of the synaptic component was 1440 mV<sup>2</sup>-ms (prior to the input step). In (D), the variance of the synaptic component was 1000 mV<sup>2</sup>-ms and the variance of the external input (prior to the step) was 40 mV<sup>2</sup>-ms.</p>", "links"=>[], "tags"=>["neuron", "firing", "rates", "steps"], "article_id"=>585757, "categories"=>["Neuroscience", "Biological Sciences"], "users"=>["Peyman Khorsand", "Frances Chance"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0003786.g002", "stats"=>{"downloads"=>1, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_LIF_neuron_firing_rates_in_response_to_steps_in_mean_and_noise_/585757", "title"=>"LIF neuron firing rates in response to steps in mean and noise.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-11-21 01:35:57"}

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  • {"unique-ip"=>"1", "full-text"=>"0", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2012", "month"=>"12"}
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  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2012", "month"=>"11"}
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  • {"unique-ip"=>"1", "full-text"=>"0", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2013", "month"=>"7"}
  • {"unique-ip"=>"3", "full-text"=>"2", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2013", "month"=>"9"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2013", "month"=>"11"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2013", "month"=>"12"}
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  • {"unique-ip"=>"2", "full-text"=>"4", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"4"}
  • {"unique-ip"=>"2", "full-text"=>"3", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"4"}
  • {"unique-ip"=>"4", "full-text"=>"5", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"5"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"6"}
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  • {"unique-ip"=>"4", "full-text"=>"2", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"2"}
  • {"unique-ip"=>"3", "full-text"=>"3", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"8"}
  • {"unique-ip"=>"4", "full-text"=>"4", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"9"}
  • {"unique-ip"=>"4", "full-text"=>"2", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"7"}
  • {"unique-ip"=>"5", "full-text"=>"3", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"8"}
  • {"unique-ip"=>"6", "full-text"=>"4", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2014", "month"=>"9"}
  • {"unique-ip"=>"7", "full-text"=>"7", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"10"}
  • {"unique-ip"=>"4", "full-text"=>"2", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"2"}
  • {"unique-ip"=>"6", "full-text"=>"2", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"11"}
  • {"unique-ip"=>"4", "full-text"=>"3", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"1"}
  • {"unique-ip"=>"5", "full-text"=>"3", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"2", "year"=>"2015", "month"=>"11"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"12"}
  • {"unique-ip"=>"11", "full-text"=>"2", "pdf"=>"10", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"1"}
  • {"unique-ip"=>"4", "full-text"=>"2", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2016", "month"=>"3"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"4"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"5"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"6"}
  • {"unique-ip"=>"4", "full-text"=>"3", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"9"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"10"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"11"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"12"}
  • {"unique-ip"=>"1", "full-text"=>"0", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"2"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2017", "month"=>"3"}
  • {"unique-ip"=>"2", "full-text"=>"1", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"4"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"6"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"7"}
  • {"unique-ip"=>"2", "full-text"=>"1", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"10"}
  • {"unique-ip"=>"3", "full-text"=>"3", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"11"}
  • {"unique-ip"=>"3", "full-text"=>"3", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"3"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"1"}
  • {"unique-ip"=>"13", "full-text"=>"13", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"5"}
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  • {"unique-ip"=>"4", "full-text"=>"4", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"10"}
  • {"unique-ip"=>"3", "full-text"=>"3", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"9"}
  • {"unique-ip"=>"9", "full-text"=>"8", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"12"}
  • {"unique-ip"=>"9", "full-text"=>"8", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"11"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"2"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"3"}
  • {"unique-ip"=>"5", "full-text"=>"4", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2019", "month"=>"4"}
  • {"unique-ip"=>"7", "full-text"=>"9", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"5"}
  • {"unique-ip"=>"5", "full-text"=>"4", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2019", "month"=>"8"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2019", "month"=>"9"}
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Relative Metric

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