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{"title"=>"Similarity of Cortical Activity Patterns Predicts generalization Behavior", "type"=>"journal", "authors"=>[{"first_name"=>"Crystal T.", "last_name"=>"Engineer", "scopus_author_id"=>"24166339900"}, {"first_name"=>"Claudia A.", "last_name"=>"Perez", "scopus_author_id"=>"24166983000"}, {"first_name"=>"Ryan S.", "last_name"=>"Carraway", "scopus_author_id"=>"24166490700"}, {"first_name"=>"Kevin Q.", "last_name"=>"Chang", "scopus_author_id"=>"55886527000"}, {"first_name"=>"Jarod L.", "last_name"=>"Roland", "scopus_author_id"=>"28268057700"}, {"first_name"=>"Andrew M.", "last_name"=>"Sloan", "scopus_author_id"=>"7005636503"}, {"first_name"=>"Michael P.", "last_name"=>"Kilgard", "scopus_author_id"=>"6603889432"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"pui"=>"370046449", "doi"=>"10.1371/journal.pone.0078607", "isbn"=>"1932-6203", "pmid"=>"24147140", "issn"=>"19326203", "scopus"=>"2-s2.0-84885772476", "sgr"=>"84885772476"}, "id"=>"fcb0dd4a-0b41-3fbd-8a50-b81b7db2f5e5", "abstract"=>"Humans and animals readily generalize previously learned knowledge to new situations. Determining similarity is critical for assigning category membership to a novel stimulus. We tested the hypothesis that category membership is initially encoded by the similarity of the activity pattern evoked by a novel stimulus to the patterns from known categories. We provide behavioral and neurophysiological evidence that activity patterns in primary auditory cortex contain sufficient information to explain behavioral categorization of novel speech sounds by rats. Our results suggest that category membership might be encoded by the similarity of the activity pattern evoked by a novel speech sound to the patterns evoked by known sounds. Categorization based on featureless pattern matching may represent a general neural mechanism for ensuring accurate generalization across sensory and cognitive systems.", "link"=>"http://www.mendeley.com/research/similarity-cortical-activity-patterns-predicts-generalization-behavior", "reader_count"=>25, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>3, "Researcher"=>7, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>5, "Student > Postgraduate"=>2, "Student > Master"=>3, "Other"=>1, "Professor"=>2, "Unspecified"=>1}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>3, "Researcher"=>7, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>5, "Student > Postgraduate"=>2, "Student > Master"=>3, "Other"=>1, "Professor"=>2, "Unspecified"=>1}, "reader_count_by_subject_area"=>{"Engineering"=>3, "Unspecified"=>4, "Environmental Science"=>1, "Nursing and Health Professions"=>1, "Mathematics"=>1, "Agricultural and Biological Sciences"=>6, "Neuroscience"=>4, "Psychology"=>4, "Computer Science"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>3}, "Neuroscience"=>{"Neuroscience"=>4}, "Psychology"=>{"Psychology"=>4}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>6}, "Computer Science"=>{"Computer Science"=>1}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>1}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>4}, "Environmental Science"=>{"Environmental Science"=>1}}, "reader_count_by_country"=>{"United States"=>3, "Switzerland"=>1, "Germany"=>1}, "group_count"=>2}

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• http://doi.org/10.1016/j.brs.2018.09.013
• http://doi.org/10.3389/fnins.2014.00161
• http://doi.org/10.1002/aur.1883
• http://doi.org/10.1016/j.bbr.2013.10.021
• http://doi.org/10.3389/fnins.2014.00132
• http://doi.org/10.1016/j.cub.2020.02.047
• http://doi.org/10.1002/dneu.22175
• http://doi.org/10.1016/j.heares.2014.03.007
• http://doi.org/10.3389/fpsyg.2014.01543
• http://doi.org/10.1016/j.brainres.2014.03.049
• http://doi.org/10.3389/fnsys.2014.00137
• http://doi.org/10.3934/Neuroscience.2014.3.185

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• {"type"=>"COMMENT", "annotationUri"=>"info:doi/10.1371/annotation/aabf110f-34f2-45ca-8e88-7e8feef244ce", "title"=>"Publisher's Note: Error in Title", "body"=>"The word \"Generalization\" was incorrectly italicized and was not correctly capitalized in the article title. The correct title is: Similarity of Cortical Activity Patterns Predicts Generalization Behavior. The correct citation is: Engineer CT, Perez CA, Carraway RS, Chang KQ, Roland JL, et al. (2013) Similarity of Cortical Activity Patterns Predicts Generalization Behavior. PLoS ONE 8(10): e78607. doi:10.1371/journal.pone.0078607", "isRemoved"=>false, "created"=>"2013-12-19T21:33:04Z", "lastModified"=>"2013-12-19T21:33:04Z", "creator"=>{"userId"=>"80539"}, "highlightedText"=>"", "competingInterestStatement"=>{"creatorWasPrompted"=>true, "hasCompetingInterests"=>false}, "parentArticle"=>{"doi"=>"info:doi/10.1371/journal.pone.0078607", "state"=>"published", "journals"=>{"PLoSONE"=>{"journalKey"=>"PLoSONE", "eIssn"=>"1932-6203", "title"=>"PLOS ONE"}}}, "replyTreeSize"=>0, "mostRecentActivity"=>"2013-12-19T21:33:04Z", "replies"=>[]}

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• {"id"=>"390653118796427264", "text"=>"馴染みのなる刺激から新奇刺激の処理へ。Similarity of Cortical Activity Patterns Predicts generalization Behavior http://t.co/hS9wNML5jx", "created_at"=>"2013-10-17T01:38:56Z", "user"=>"uranus_2", "user_name"=>"マーキュリー２世", "user_profile_image"=>"http://abs.twimg.com/sticky/default_profile_images/default_profile_5_normal.png"}

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Figshare

• {"files"=>["https://ndownloader.figshare.com/files/1240103"], "description"=>"<p>Rows differ in voicing (top row is ‘dad’, bottom row is ‘tad’), while columns differ in gender (left three columns are female, right three columns are male). Frequency is represented on the <i>y</i> axis (0–35 kHz) and time on the <i>x</i> axis (-50 to 500 ms). Speech sounds were shifted one octave higher to accommodate the rat hearing range. </p>", "links"=>[], "tags"=>["grouped"], "article_id"=>825066, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Crystal T. Engineer", "Claudia A. Perez", "Ryan S. Carraway", "Kevin Q. Chang", "Jarod L. Roland", "Andrew M. Sloan", "Michael P. Kilgard"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0078607.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Spectrograms_of_each_speech_sound_grouped_by_gender_and_voicing_/825066", "title"=>"Spectrograms of each speech sound grouped by gender and voicing.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-10-16 04:59:35"}
• {"files"=>["https://ndownloader.figshare.com/files/1240104"], "description"=>"<p>(<b>a</b>) Gender Task rats successfully generalized from the pitch discrimination task, and accurately pressed the lever more often in response to novel female ‘dad’ sounds than novel male ‘dad’ sounds on the first day of testing. Red symbols represent target sounds, blue symbols represent non-target sounds, and black symbols represent target or non-target sounds from the previous task. Circle symbols indicate ‘dad’ stimuli, while triangle symbols indicate ‘tad’ stimuli. Error bars indicate s.e.m. across rats. The solid line indicates average percent lever press to silent catch trials, with s.e.m. indicated by the dotted lines. (<b>b</b>) Gender Task rats successfully generalized from the gender ‘dad’ categorization task, and accurately pressed the lever more often in response to novel female ‘tad’ sounds than novel male ‘tad’ sounds on the first day of testing. The sounds presented in subplot d are identical. (<b>c</b>) Voicing Task rats successfully generalized from the voicing discrimination task, and accurately pressed the lever more often in response to novel temporally compressed ‘dad’ than novel temporally compressed ‘tad’. (<b>d</b>) Voicing Task rats successfully generalized from the voicing temporal compression categorization task, and accurately pressed the lever more often in response to ‘dad’ spoken by multiple novel speakers than ‘tad’ spoken by multiple novel speakers.</p>", "links"=>[], "tags"=>["voicing", "categorization"], "article_id"=>825067, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Crystal T. Engineer", "Claudia A. Perez", "Ryan S. Carraway", "Kevin Q. Chang", "Jarod L. Roland", "Andrew M. Sloan", "Michael P. Kilgard"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0078607.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Generalization_performance_for_the_gender_and_voicing_categorization_tasks_/825067", "title"=>"Generalization performance for the gender and voicing categorization tasks.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-10-16 04:59:35"}
• {"files"=>["https://ndownloader.figshare.com/files/1240105"], "description"=>"<p>Multi-unit data was collected from 441 recording sites in eleven anesthetized experimentally naïve adult rats. Average post-stimulus time histograms (PSTH) derived from twenty repeats were ordered by the characteristic frequency (kHz) of each recording site (<i>y</i> axis). Time is represented on the <i>x</i> axis (-5 to 50 ms). The firing rate of each site is represented in grayscale, where black indicates 450 spikes/s. For comparison, the mean population PSTH evoked by each sound is plotted above the corresponding neurogram. To facilitate comparison between the naïve and trained responses, the mean PSTH y axis is set to 450 Hz for all neurogram figures. For naïve rats, ‘tad’ female #3 evokes the maximum peak firing rate (351 Hz) across the twelve sounds. As in Figure 1, rows differ in voicing (top row is ‘dad’, bottom row is ‘tad’), while columns differ in gender (left three columns are female, right three columns are male). </p>", "links"=>[], "tags"=>["depicting", "onset", "a1", "neurons"], "article_id"=>825068, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Crystal T. Engineer", "Claudia A. Perez", "Ryan S. Carraway", "Kevin Q. Chang", "Jarod L. Roland", "Andrew M. Sloan", "Michael P. Kilgard"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0078607.g003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Neurograms_depicting_the_onset_response_of_rat_A1_neurons_to_speech_sounds_/825068", "title"=>"Neurograms depicting the onset response of rat A1 neurons to speech sounds.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-10-16 04:59:35"}
• {"files"=>["https://ndownloader.figshare.com/files/1240106"], "description"=>"<p>(<b>a</b>) The normalized Euclidean distance (neural similarity) between the response pattern for each novel sound and the response pattern for each of the two template sounds is correlated with generalization performance on the gender ‘dad’ task. Positive values are more similar to the target template, while negative values are more similar to the non-target template. Target sounds are red, and non-target sounds are blue. The sound name abbreviation is printed next to each data point, see Methods. Solid lines indicate the best linear fit. (<b>b</b>) The neural similarity between each novel sound and the template sounds is correlated with generalization performance on the gender ‘tad’ task. (<b>c</b>) The neural similarity between the response pattern for each novel sound and the response pattern for each of the two template sounds is correlated with generalization performance on the voicing temporal compression categorization task. (<b>d</b>) The neural similarity between each novel sound and the template sounds is correlated with generalization performance on the voicing multiple speaker task.</p>", "links"=>[], "tags"=>["correlates", "generalization", "voicing", "categorization"], "article_id"=>825069, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Crystal T. Engineer", "Claudia A. Perez", "Ryan S. Carraway", "Kevin Q. Chang", "Jarod L. Roland", "Andrew M. Sloan", "Michael P. Kilgard"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0078607.g004"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Neural_correlates_of_generalization_performance_for_the_gender_and_voicing_categorization_tasks_/825069", "title"=>"Neural correlates of generalization performance for the gender and voicing categorization tasks.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-10-16 04:59:35"}
• {"files"=>["https://ndownloader.figshare.com/files/1240107"], "description"=>"<p>(<b>a</b>) The Euclidean distance (spectral similarity) between the spectrogram for each novel sound and the spectrogram for each of the two template sounds is weakly correlated with generalization performance on the gender ‘dad’ task. Positive values are more similar to the target template, while negative values are more similar to the non-target template. The sound name abbreviation is printed next to each data point, see Methods. Solid lines indicate the best linear fit. (<b>b</b>) The spectral similarity between each novel sound and the template sounds is weakly correlated with generalization performance on the gender ‘tad’ task. (<b>c</b>) The spectral similarity between the spectrogram for each novel sound and the spectrogram for each of the two template sounds is weakly correlated with generalization performance on the voicing temporal compression categorization task. (<b>d</b>) The spectral similarity between each novel sound and the template sounds is weakly correlated with generalization performance on the voicing multiple speaker task.</p>", "links"=>[], "tags"=>["correlates", "generalization", "voicing", "categorization"], "article_id"=>825070, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Crystal T. Engineer", "Claudia A. Perez", "Ryan S. Carraway", "Kevin Q. Chang", "Jarod L. Roland", "Andrew M. Sloan", "Michael P. Kilgard"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0078607.g005"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Spectrogram_correlates_of_generalization_performance_for_the_gender_and_voicing_categorization_tasks_/825070", "title"=>"Spectrogram correlates of generalization performance for the gender and voicing categorization tasks.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-10-16 04:59:35"}
• {"files"=>["https://ndownloader.figshare.com/files/1240108"], "description"=>"<p>Peak firing rate for target and non-target sounds differs in high frequency neurons for gender distinctions, and differs in low frequency neurons for voicing distinctions. <b>(a)</b> For the gender task using ‘dad’ stimuli, target female ‘dad’ sounds evoke a larger response in high frequency neurons compared to non-target male ‘dad’ sounds. Each of the 441 A1 recording sites from experimentally naïve rats were binned by characteristic frequency into one of five bins each spanning one octave. Error bars indicate s.e.m. across each of the sounds. <b>(b)</b> For the gender task using ‘tad’ stimuli, target female ‘tad’ sounds evoke a larger response in high frequency neurons compared to non-target male ‘tad’ sounds. <b>(c)</b> For the voicing temporal compression task, target ‘dad’ sounds evoke a larger response in low frequency neurons compared to non-target ‘tad’ sounds. <b>(d)</b> For the voicing multiple speaker task, target ‘dad’ sounds evoke a larger response in low frequency neurons compared to non-target ‘tad’ sounds.</p>", "links"=>[], "tags"=>["firing", "differences", "neurons", "voicing"], "article_id"=>825071, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Crystal T. Engineer", "Claudia A. Perez", "Ryan S. Carraway", "Kevin Q. Chang", "Jarod L. Roland", "Andrew M. Sloan", "Michael P. Kilgard"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0078607.g006"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Peak_firing_rate_differences_in_high_and_low_frequency_neurons_for_gender_and_voicing_distinctions_/825071", "title"=>"Peak firing rate differences in high and low frequency neurons for gender and voicing distinctions.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-10-16 04:59:35"}
• {"files"=>["https://ndownloader.figshare.com/files/1240109"], "description"=>"<p>Peak firing rate for target and non-target sounds differs in fast neurons for gender distinctions, and differs in slow neurons for voicing distinctions. (<b>a</b>) For the gender task using ‘dad’ stimuli, target female ‘dad’ sounds evoke a larger response in fast neurons that respond to tones in less than 10 ms compared to non-target male ‘dad’ sounds. Each of the 441 A1 recording sites from experimentally naïve rats were binned by onset latency into one of five bins each spanning one millisecond. Error bars indicate s.e.m. across each of the sounds. (<b>b</b>) For the gender task using ‘tad’ stimuli, target female ‘tad’ sounds evoke a larger response in fast neurons compared to non-target male ‘tad’ sounds. (<b>c</b>) For the voicing temporal compression task, target ‘dad’ sounds evoke a larger response in slow neurons that respond to tone slower than 13 ms compared to non-target ‘tad’ sounds. (<b>d</b>) For the voicing multiple speaker task, target ‘dad’ sounds evoke a larger response in slow neurons compared to non-target ‘tad’ sounds. </p>", "links"=>[], "tags"=>["firing", "differences", "latency", "neurons", "voicing"], "article_id"=>825072, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Crystal T. Engineer", "Claudia A. Perez", "Ryan S. Carraway", "Kevin Q. Chang", "Jarod L. Roland", "Andrew M. Sloan", "Michael P. Kilgard"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0078607.g007"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Peak_firing_rate_differences_in_fast_and_slow_latency_neurons_for_gender_and_voicing_distinctions_/825072", "title"=>"Peak firing rate differences in fast and slow latency neurons for gender and voicing distinctions.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-10-16 04:59:35"}
• {"files"=>["https://ndownloader.figshare.com/files/1240110"], "description"=>"<p>Percent of variance explained (R²) increases as the population size increases. Neural similarity using the onset activity pattern from individual anesthetized (black line) or awake (gray line) multi-unit sites was best correlated with behavior when more than 20 sites were used. Error bars indicate s.e.m. across the four tasks. </p>", "links"=>[], "tags"=>["percent", "variance", "explained", "generalization", "tasks", "anesthetized"], "article_id"=>825073, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Crystal T. Engineer", "Claudia A. Perez", "Ryan S. Carraway", "Kevin Q. Chang", "Jarod L. Roland", "Andrew M. Sloan", "Michael P. Kilgard"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0078607.g008"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Average_percent_of_variance_explained_across_the_four_generalization_tasks_using_awake_and_anesthetized_responses_/825073", "title"=>"Average percent of variance explained across the four generalization tasks using awake and anesthetized responses.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-10-16 04:59:35"}
• {"files"=>["https://ndownloader.figshare.com/files/1240111", "https://ndownloader.figshare.com/files/1240112", "https://ndownloader.figshare.com/files/1240113", "https://ndownloader.figshare.com/files/1240114", "https://ndownloader.figshare.com/files/1240115", "https://ndownloader.figshare.com/files/1240116", "https://ndownloader.figshare.com/files/1240117", "https://ndownloader.figshare.com/files/1240118"], "description"=>"<div><p>Humans and animals readily generalize previously learned knowledge to new situations. Determining similarity is critical for assigning category membership to a novel stimulus. We tested the hypothesis that category membership is initially encoded by the similarity of the activity pattern evoked by a novel stimulus to the patterns from known categories. We provide behavioral and neurophysiological evidence that activity patterns in primary auditory cortex contain sufficient information to explain behavioral categorization of novel speech sounds by rats. Our results suggest that category membership might be encoded by the similarity of the activity pattern evoked by a novel speech sound to the patterns evoked by known sounds. Categorization based on featureless pattern matching may represent a general neural mechanism for ensuring accurate generalization across sensory and cognitive systems. </p> </div>", "links"=>[], "tags"=>["cortical", "patterns"], "article_id"=>825074, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Crystal T. Engineer", "Claudia A. Perez", "Ryan S. Carraway", "Kevin Q. Chang", "Jarod L. Roland", "Andrew M. Sloan", "Michael P. Kilgard"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0078607.s001", "https://dx.doi.org/10.1371/journal.pone.0078607.s002", "https://dx.doi.org/10.1371/journal.pone.0078607.s003", "https://dx.doi.org/10.1371/journal.pone.0078607.s004", "https://dx.doi.org/10.1371/journal.pone.0078607.s005", "https://dx.doi.org/10.1371/journal.pone.0078607.s006", "https://dx.doi.org/10.1371/journal.pone.0078607.s007", "https://dx.doi.org/10.1371/journal.pone.0078607.s008"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Similarity_of_Cortical_Activity_Patterns_Predicts_generalization_Behavior/825074", "title"=>"Similarity of Cortical Activity Patterns Predicts <i>generalization</i> Behavior", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2013-10-16 04:59:35"}

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Relative Metric

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F1000Prime