Visual and Non-Visual Contributions to the Perception of Object Motion during Self-Motion
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{"title"=>"Visual and Non-Visual Contributions to the Perception of Object Motion during Self-Motion", "type"=>"journal", "authors"=>[{"first_name"=>"Brett R.", "last_name"=>"Fajen", "scopus_author_id"=>"6603782054"}, {"first_name"=>"Jonathan S.", "last_name"=>"Matthis", "scopus_author_id"=>"53164518200"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "scopus"=>"2-s2.0-84873579450", "pui"=>"368311245", "doi"=>"10.1371/journal.pone.0055446", "isbn"=>"1932-6203", "sgr"=>"84873579450", "pmid"=>"23408983"}, "id"=>"68b27108-39a3-3891-b65f-79b261efa8ad", "abstract"=>"Many locomotor tasks involve interactions with moving objects. When observer (i.e., self-)motion is accompanied by object motion, the optic flow field includes a component due to self-motion and a component due to object motion. For moving observers to perceive the movement of other objects relative to the stationary environment, the visual system could recover the object-motion component - that is, it could factor out the influence of self-motion. In principle, this could be achieved using visual self-motion information, non-visual self-motion information, or a combination of both. In this study, we report evidence that visual information about the speed (experiment 1) and direction (experiment 2) of self-motion plays a role in recovering the object-motion component even when non-visual self-motion information is also available. However, the magnitude of the effect was less than one would expect if subjects relied entirely on visual self-motion information. Taken together with previous studies, we conclude that when self-motion is real and actively generated, both visual and non-visual self-motion information contribute to the perception of object motion. We also consider the possible role of this process in visually guided interception and avoidance of moving objects.", "link"=>"http://www.mendeley.com/research/visual-nonvisual-contributions-perception-object-motion-during-selfmotion", "reader_count"=>36, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>6, "Researcher"=>7, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>9, "Student > Postgraduate"=>3, "Other"=>2, "Student > Master"=>3, "Student > Bachelor"=>1, "Lecturer"=>2, "Professor"=>1}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>6, "Researcher"=>7, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>9, "Student > Postgraduate"=>3, "Other"=>2, "Student > Master"=>3, "Student > Bachelor"=>1, "Lecturer"=>2, "Professor"=>1}, "reader_count_by_subject_area"=>{"Engineering"=>1, "Unspecified"=>1, "Agricultural and Biological Sciences"=>2, "Medicine and Dentistry"=>2, "Neuroscience"=>6, "Philosophy"=>1, "Sports and Recreations"=>1, "Psychology"=>21, "Social Sciences"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>2}, "Neuroscience"=>{"Neuroscience"=>6}, "Social Sciences"=>{"Social Sciences"=>1}, "Sports and Recreations"=>{"Sports and Recreations"=>1}, "Psychology"=>{"Psychology"=>21}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>2}, "Unspecified"=>{"Unspecified"=>1}, "Philosophy"=>{"Philosophy"=>1}}, "reader_count_by_country"=>{"Colombia"=>1, "Canada"=>1, "Japan"=>1, "United Kingdom"=>1, "Germany"=>1}, "group_count"=>5}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/483639"], "description"=>"<div><p>Many locomotor tasks involve interactions with moving objects. When observer (i.e., self-)motion is accompanied by object motion, the optic flow field includes a component due to self-motion and a component due to object motion. For moving observers to perceive the movement of other objects relative to the stationary environment, the visual system could recover the object-motion component – that is, it could factor out the influence of self-motion. In principle, this could be achieved using visual self-motion information, non-visual self-motion information, or a combination of both. In this study, we report evidence that visual information about the speed (Experiment 1) and direction (Experiment 2) of self-motion plays a role in recovering the object-motion component even when non-visual self-motion information is also available. However, the magnitude of the effect was less than one would expect if subjects relied entirely on visual self-motion information. Taken together with previous studies, we conclude that when self-motion is real and actively generated, both visual and non-visual self-motion information contribute to the perception of object motion. We also consider the possible role of this process in visually guided interception and avoidance of moving objects.</p> </div>", "links"=>[], "tags"=>["non-visual", "contributions", "self-motion"], "article_id"=>156172, "categories"=>["Physiology", "Neuroscience"], "users"=>["Brett R. Fajen", "Jonathan S. Matthis"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0055446"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Visual_and_Non_Visual_Contributions_to_the_Perception_of_Object_Motion_during_Self_Motion__/156172", "title"=>"Visual and Non-Visual Contributions to the Perception of Object Motion during Self-Motion", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-07 01:42:52"}
  • {"files"=>["https://ndownloader.figshare.com/files/492031"], "description"=>"<p>(A) Optic flow field generated by an observer moving over a ground surface and an object (yellow dot) moving from right to left. (B) The component of optic flow due to self-motion independent of object motion. (C) The component of optic flow due to object motion independent of self-motion. The optic flow field (A) is the vector sum of the self-motion (B) and object-motion (C) components.</p>", "links"=>[], "tags"=>["decomposition", "self-motion", "object-motion"], "article_id"=>162551, "categories"=>["Physiology", "Neuroscience"], "users"=>["Brett R. Fajen", "Jonathan S. Matthis"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0055446.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Optic_flow_field_and_decomposition_into_self_motion_and_object_motion_components_/162551", "title"=>"Optic flow field and decomposition into self-motion and object-motion components.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-07 00:42:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/492160"], "description"=>"<p>(A–E) Sequence of events on each trial in Experiment 1. (F) Screenshot of virtual environment viewed through the HMD.</p>", "links"=>[], "tags"=>["events", "experiments"], "article_id"=>162689, "categories"=>["Physiology", "Neuroscience"], "users"=>["Brett R. Fajen", "Jonathan S. Matthis"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0055446.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Sequence_of_events_in_Experiments_1_/162689", "title"=>"Sequence of events in Experiments 1.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-07 00:44:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/492250"], "description"=>"<p>Predictions for normal and catch trials in Experiment 1. (A) and (B) depict the optic flow field on normal trials and catch trials, respectively. Gray vectors depict the optic flow of the stationary background and yellow vectors depict the optic flow of the moving objects. (C) and (D) show the object-motion component (dotted lines) and how it is recovered by subtracting the self-motion component (faded dash lines) from the optic flow of the moving objects.</p>", "links"=>[], "tags"=>["physiology", "neuroscience"], "article_id"=>162779, "categories"=>["Physiology", "Neuroscience"], "users"=>["Brett R. Fajen", "Jonathan S. Matthis"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0055446.g003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Experiment_1_predictions_/162779", "title"=>"Experiment 1 predictions.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-07 00:46:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/492362"], "description"=>"<p>Percentage of passable judgments as a function of required speed for a representative subject. Solid black curve represents best-fitting sigmoid function and dotted line indicates critical value of required speed.</p>", "links"=>[], "tags"=>["physiology", "neuroscience"], "article_id"=>162881, "categories"=>["Physiology", "Neuroscience"], "users"=>["Brett R. Fajen", "Jonathan S. Matthis"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0055446.g004"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Sigmoid_fit_/162881", "title"=>"Sigmoid fit.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-07 00:48:01"}
  • {"files"=>["https://ndownloader.figshare.com/files/492393"], "description"=>"<p>Percentage of passable judgments (A) and critical value of required speed (B) in Experiment 1. Error bars indicate ±1 SE. Note that the estimate of critical required speed on normal trials in (B) is based on data from all 15 initial conditions. It is also possible to estimate critical required speed based on the data from the subset of normal trials with initial conditions that match those on catch trials. When critical required speed is estimated using the latter method, the mean and standard error (M = 2.14 m/s, SE = 0.09) are nearly identical to the mean and standard error based on the data from all normal trials (M = 2.12 m/s, SE = 0.09).</p>", "links"=>[], "tags"=>["physiology", "neuroscience"], "article_id"=>162926, "categories"=>["Physiology", "Neuroscience"], "users"=>["Brett R. Fajen", "Jonathan S. Matthis"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0055446.g005"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Experiment_1_results_/162926", "title"=>"Experiment 1 results.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-07 00:48:46"}
  • {"files"=>["https://ndownloader.figshare.com/files/492489"], "description"=>"<p>Predictions for normal and catch trials in Experiment 2 for a trial in which the object moves from right to left. (A) and (B) depict the optic flow field on normal trials and catch trials, respectively. Gray vectors depict the optic flow of the stationary background and yellow vectors depict the optic flow of the moving objects. (C) and (D) show the object-motion component (dotted lines) and how it is recovered by subtracting the self-motion component (faded dash lines) from the optic flow of the moving objects.</p>", "links"=>[], "tags"=>["physiology", "neuroscience"], "article_id"=>163011, "categories"=>["Physiology", "Neuroscience"], "users"=>["Brett R. Fajen", "Jonathan S. Matthis"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0055446.g006"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Experiment_2_predictions_/163011", "title"=>"Experiment 2 predictions.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-07 00:50:11"}
  • {"files"=>["https://ndownloader.figshare.com/files/492581"], "description"=>"<p>Percentage of passable judgments (A) and critical value of required speed (B) in Experiment 2. Error bars indicate ±1 SE. As in Experiment 1, critical required speed can also be estimated using the subset of normal trials with initial conditions that match those on catch trials. Using this method, the critical required speed (M = 1.54 m/s, SE = 0.05) is nearly identical to the critical required speed based on all initial conditions (M = 1.56 m/s, SE = 0.05).</p>", "links"=>[], "tags"=>["physiology", "neuroscience"], "article_id"=>163110, "categories"=>["Physiology", "Neuroscience"], "users"=>["Brett R. Fajen", "Jonathan S. Matthis"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0055446.g007"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Experiment_2_results_/163110", "title"=>"Experiment 2 results.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-07 00:51:50"}
  • {"files"=>["https://ndownloader.figshare.com/files/492648"], "description"=>"<p>(A) Top down view of an obstacle crossing an observer’s future path. W is the width of the observer’s body, z<sub>o</sub> and z<sub>m</sub> are the positions along the z-axis of the observer and the moving obstacle respectively, g is the spatial gap between the obstacle and the z-axis, and the shaded region is the locomotor path of the observer. (B) Optical specification of <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055446#pone.0055446.e002\" target=\"_blank\">Equation 2</a>. (C) Side view of observer and obstacle, showing angular declination of base of obstacle (γ) and eyeheight. (D) Top down view of observer and obstacle, showing visual angle of gap (α) and obstacle (<i>φ</i>).</p>", "links"=>[], "tags"=>["locomotor"], "article_id"=>163172, "categories"=>["Physiology", "Neuroscience"], "users"=>["Brett R. Fajen", "Jonathan S. Matthis"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0055446.g008"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Information_about_minimum_locomotor_speed_/163172", "title"=>"Information about minimum locomotor speed.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-07 00:52:52"}
  • {"files"=>["https://ndownloader.figshare.com/files/492741"], "description"=>"<p>Percentage of passable judgments in Experiment 1.</p>", "links"=>[], "tags"=>["passable", "judgments"], "article_id"=>163267, "categories"=>["Physiology", "Neuroscience"], "users"=>["Brett R. Fajen", "Jonathan S. Matthis"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0055446.t001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Percentage_of_passable_judgments_in_Experiment_1_/163267", "title"=>"Percentage of passable judgments in Experiment 1.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-07 00:54:27"}
  • {"files"=>["https://ndownloader.figshare.com/files/492770"], "description"=>"<p>Percentage of passable judgments in Experiment 2.</p>", "links"=>[], "tags"=>["passable", "judgments"], "article_id"=>163298, "categories"=>["Physiology", "Neuroscience"], "users"=>["Brett R. Fajen", "Jonathan S. Matthis"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0055446.t002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Percentage_of_passable_judgments_in_Experiment_2_/163298", "title"=>"Percentage of passable judgments in Experiment 2.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-07 00:54:58"}

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Relative Metric

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