Mesoscopic Patterns of Neural Activity Support Songbird Cortical Sequences
Publication Date
June 03, 2015
Journal
PLOS Biology
Authors
Jeffrey E. Markowitz, William A. Liberti Iii, Grigori Guitchounts, Tarciso Velho, et al
Volume
13
Issue
6
Pages
e1002158
DOI
https://dx.plos.org/10.1371/journal.pbio.1002158
Publisher URL
http://journals.plos.org/plosbiology/article?id=10.1371%2Fjournal.pbio.1002158
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/26039895
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4454690
Europe PMC
http://europepmc.org/abstract/MED/26039895
Web of Science
000357339600001
Scopus
84934753644
Mendeley
http://www.mendeley.com/research/mesoscopic-patterns-neural-activity-support-songbird-cortical-sequences
Events
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Mendeley | Further Information

{"title"=>"Mesoscopic patterns of neural activity support songbird cortical sequences", "type"=>"journal", "authors"=>[{"first_name"=>"Jeffrey E.", "last_name"=>"Markowitz", "scopus_author_id"=>"57198169197"}, {"first_name"=>"William A.", "last_name"=>"Liberti", "scopus_author_id"=>"55839287200"}, {"first_name"=>"Grigori", "last_name"=>"Guitchounts", "scopus_author_id"=>"55192459500"}, {"first_name"=>"Tarciso", "last_name"=>"Velho", "scopus_author_id"=>"8922442200"}, {"first_name"=>"Carlos", "last_name"=>"Lois", "scopus_author_id"=>"6602349700"}, {"first_name"=>"Timothy J.", "last_name"=>"Gardner", "scopus_author_id"=>"18934504400"}], "year"=>2015, "source"=>"PLoS Biology", "identifiers"=>{"sgr"=>"84934753644", "pmid"=>"26039895", "arxiv"=>"1501.06108", "pui"=>"605060015", "scopus"=>"2-s2.0-84934753644", "doi"=>"10.1371/journal.pbio.1002158", "issn"=>"15457885"}, "id"=>"e0561d11-ce02-3ded-88b3-0178a4a2d902", "abstract"=>"Time-locked sequences of neural activity can be found throughout the vertebrate forebrain in various species and behavioral contexts. From \"time cells\" in the hippocampus of rodents to cortical activity controlling movement, temporal sequence generation is integral to many forms of learned behavior. However, the mechanisms underlying sequence generation are not well known. Here, we describe a spatial and temporal organization of the songbird premotor cortical microcircuit that supports sparse sequences of neural activity. Multi-channel electrophysiology and calcium imaging reveal that neural activity in premotor cortex is correlated with a length scale of 100 µm. Within this length scale, basal-ganglia-projecting excitatory neurons, on average, fire at a specific phase of a local 30 Hz network rhythm. These results show that premotor cortical activity is inhomogeneous in time and space, and that a mesoscopic dynamical pattern underlies the generation of the neural sequences controlling song.", "link"=>"http://www.mendeley.com/research/mesoscopic-patterns-neural-activity-support-songbird-cortical-sequences", "reader_count"=>114, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>2, "Researcher"=>29, "Student > Doctoral Student"=>4, "Student > Ph. D. Student"=>48, "Student > Postgraduate"=>2, "Student > Master"=>6, "Other"=>3, "Student > Bachelor"=>14, "Professor"=>5}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>2, "Researcher"=>29, "Student > Doctoral Student"=>4, "Student > Ph. D. Student"=>48, "Student > Postgraduate"=>2, "Student > Master"=>6, "Other"=>3, "Student > Bachelor"=>14, "Professor"=>5}, "reader_count_by_subject_area"=>{"Engineering"=>11, "Unspecified"=>3, "Biochemistry, Genetics and Molecular Biology"=>2, "Mathematics"=>2, "Agricultural and Biological Sciences"=>56, "Medicine and Dentistry"=>5, "Neuroscience"=>25, "Pharmacology, Toxicology and Pharmaceutical Science"=>1, "Physics and Astronomy"=>2, "Psychology"=>4, "Computer Science"=>3}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>11}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>5}, "Neuroscience"=>{"Neuroscience"=>25}, "Physics and Astronomy"=>{"Physics and Astronomy"=>2}, "Psychology"=>{"Psychology"=>4}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>56}, "Computer Science"=>{"Computer Science"=>3}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>2}, "Mathematics"=>{"Mathematics"=>2}, "Unspecified"=>{"Unspecified"=>3}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>1}}, "reader_count_by_country"=>{"Netherlands"=>1, "United States"=>8, "Japan"=>1, "Chile"=>1, "Germany"=>1}, "group_count"=>6}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/2094612"], "description"=>"<p>The spatial organization of neural activity in HVC in singing birds is unknown. The geometry of neural activity could be described by three schematics that form a continuum: <b>a,</b> a random, disorganized geometry [<a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002158#pbio.1002158.ref008\" target=\"_blank\">8</a>]; <b>b,</b> functional clustering (i.e., nearby cells code for similar elements) with a characteristic length scale [<a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002158#pbio.1002158.ref027\" target=\"_blank\">27</a>]; and <b>c,</b> traveling waves [<a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002158#pbio.1002158.ref028\" target=\"_blank\">28</a>].</p>", "links"=>[], "tags"=>["length scale", "30 Hz network rhythm", "premotor", "sequence generation"], "article_id"=>1435761, "categories"=>["Biological Sciences"], "users"=>["Jeffrey E. Markowitz", "William A. Liberti III", "Grigori Guitchounts", "Tarciso Velho", "Carlos Lois", "Timothy J. Gardner"], "doi"=>"https://dx.doi.org/10.1371/journal.pbio.1002158.g001", "stats"=>{"downloads"=>1, "page_views"=>37, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Three_hypothetical_models_for_the_spatiotemporal_organization_of_the_song_premotor_code_in_HVC_/1435761", "title"=>"Three hypothetical models for the spatiotemporal organization of the song premotor code in HVC.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-06-03 04:47:42"}
  • {"files"=>["https://ndownloader.figshare.com/files/2094613"], "description"=>"<p><b>a,</b> Schematic of the zebra finch brain, showing a simplified song circuit and miniature fluorescence microscope [<a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002158#pbio.1002158.ref034\" target=\"_blank\">34</a>]. <b>b,</b> Field of view, showing a mean fluorescence image of HVC (blood vessels are traced in yellow). <b>c</b>, Several example regions of interest (ROIs) from three trials during a single day of imaging in the same bird, aligned to song (top, spectrogram of example song). <b>d,</b> Peak ΔF/F<sub>0</sub>-normalized trial-averaged activity from all song-related neurons from one animal, sorted from earliest to latest peak. <b>e,</b> ROIs are colored to represent the time of cell firing within song, defined by the time of 50% rise in the onset of the calcium transient (see <b><a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002158#sec007\" target=\"_blank\">Materials and Methods</a></b>). <b>f</b>, The median distance between ROIs is shown as a function of the time between their respective calcium events (<i>n</i> = 2,230 ROI pairs). This reveals that co-active ROIs (difference between event times <50 ms) are significantly closer to each other than if event times were randomly distributed across HVC (<i>p</i> = 0 and <i>p</i> =. 038 for the first two points respectively, bootstrap test, Bonferonni corrected). Dotted lines indicate the 95% confidence interval for the null model (see <b><a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002158#sec007\" target=\"_blank\">Materials and Methods</a></b>), and the solid line indicates the median. Blue highlighting indicates <i>p</i> <.05. <b>g,</b> Histogram of relative distances between each ROI and all ROIs with calcium events >50 ms ahead (<i>n</i> = 1,710 ROI pairs). The distances are not significantly concentrated relative to the null model described in <b>f</b> (<i>p</i> =. 6924, bootstrap test). The 95% confidence interval for the histogram of the null model is indicated by dashed lines. The asymmetry of the null model is a consequence of injecting virus at multiple sites distributed along the anterior-posterior (AP) axis of HVC. (The population of recorded cells was presumably elongated in the AP axis as a result.) See also <b><a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002158#pbio.1002158.s001\" target=\"_blank\">S1 Fig</a>.</b></p>", "links"=>[], "tags"=>["length scale", "30 Hz network rhythm", "premotor", "sequence generation"], "article_id"=>1435762, "categories"=>["Biological Sciences"], "users"=>["Jeffrey E. Markowitz", "William A. Liberti III", "Grigori Guitchounts", "Tarciso Velho", "Carlos Lois", "Timothy J. Gardner"], "doi"=>"https://dx.doi.org/10.1371/journal.pbio.1002158.g002", "stats"=>{"downloads"=>2, "page_views"=>34, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Calcium_imaging_of_HVC_projection_neurons_in_awake_behaving_birds_/1435762", "title"=>"Calcium imaging of HVC projection neurons in awake, behaving birds.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-06-03 04:47:42"}
  • {"files"=>["https://ndownloader.figshare.com/files/2094614"], "description"=>"<p><b>a,</b> Spectral density images [<a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002158#pbio.1002158.ref040\" target=\"_blank\">40</a>] reveal the time-frequency structure in the LFP during singing (<i>n</i> = 64 song-aligned trials. No time warping was applied). In a spectral density image, color indicates the probability density of time-frequency structure (see <b><a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002158#sec007\" target=\"_blank\">Materials and Methods</a></b>). Reliable time-frequency structure emerges as the bird begins to sing and disappears during the short gap between song motifs. <b>b,</b> Trial-averaged band-passed LFPs (25–35 Hz) from a single electrode on three consecutive days (<i>n</i> = 130 trials for the top trace, and <i>n</i> = 200 trials for the middle and bottom traces). Shading indicates 99% bootstrap confidence interval. See also <b><a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002158#pbio.1002158.s002\" target=\"_blank\">S2 Fig</a>.</b></p>", "links"=>[], "tags"=>["length scale", "30 Hz network rhythm", "premotor", "sequence generation"], "article_id"=>1435763, "categories"=>["Biological Sciences"], "users"=>["Jeffrey E. Markowitz", "William A. Liberti III", "Grigori Guitchounts", "Tarciso Velho", "Carlos Lois", "Timothy J. Gardner"], "doi"=>"https://dx.doi.org/10.1371/journal.pbio.1002158.g003", "stats"=>{"downloads"=>7, "page_views"=>32, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Stereotyped_network_activity_during_vocal_production_in_songbird_premotor_cortex_area_HVC_/1435763", "title"=>"Stereotyped network activity during vocal production in songbird premotor cortex area HVC.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-06-03 04:47:42"}
  • {"files"=>["https://ndownloader.figshare.com/files/2094615"], "description"=>"<p><b>a,</b> The average change in phase locking for all birds (PLI<sub>STFT</sub>, see <b><a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002158#sec007\" target=\"_blank\">Materials and Methods</a></b>) between song and awake quiescence indicates that the most stereotyped frequency band in the LFP is centered on 30 Hz. <b>b,</b> The magnitude squared coherence between LFPs and interneurons (<i>n</i> = 17, see <b><a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002158#sec007\" target=\"_blank\">Materials and Methods</a></b>) is highly significant at 30 Hz (<i>p</i> = 0, bootstrap test, Bonferonni corrected). <b>c,</b> For a given pair of recording sites (<i>n</i> = 79), phase shifts in the 25–35 Hz LFP predict interneuron firing pattern distance (r =. 48, <i>p</i> = 8.5e-6, Pearson correlation coefficient). See also <b><a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002158#pbio.1002158.s003\" target=\"_blank\">S3 Fig</a>.</b></p>", "links"=>[], "tags"=>["length scale", "30 Hz network rhythm", "premotor", "sequence generation"], "article_id"=>1435764, "categories"=>["Biological Sciences"], "users"=>["Jeffrey E. Markowitz", "William A. Liberti III", "Grigori Guitchounts", "Tarciso Velho", "Carlos Lois", "Timothy J. Gardner"], "doi"=>"https://dx.doi.org/10.1371/journal.pbio.1002158.g004", "stats"=>{"downloads"=>0, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_phase_of_the_25_8211_35_Hz_LFP_can_be_used_to_study_the_spatial_structure_of_inhibition_/1435764", "title"=>"The phase of the 25–35 Hz LFP can be used to study the spatial structure of inhibition.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-06-03 04:47:42"}
  • {"files"=>["https://ndownloader.figshare.com/files/2094616"], "description"=>"<p>Trial-averaged 25–35 Hz LFP patterns on two consecutive days for six electrodes spaced by 175 μm along the mediolateral axis of HVC. Each tick mark indicates the timing of the local LFP peak, and the color indicates the phase relative to the average phase of all electrodes at that time point. (See breakout illustration top right.) See also <b><a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002158#pbio.1002158.s004\" target=\"_blank\">S4 Fig</a>.</b></p>", "links"=>[], "tags"=>["length scale", "30 Hz network rhythm", "premotor", "sequence generation"], "article_id"=>1435765, "categories"=>["Biological Sciences"], "users"=>["Jeffrey E. Markowitz", "William A. Liberti III", "Grigori Guitchounts", "Tarciso Velho", "Carlos Lois", "Timothy J. Gardner"], "doi"=>"https://dx.doi.org/10.1371/journal.pbio.1002158.g005", "stats"=>{"downloads"=>3, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_A_stereotyped_spatiotemporal_30_Hz_pattern_underlies_premotor_cortical_activity_during_song_/1435765", "title"=>"A stereotyped spatiotemporal 30 Hz pattern underlies premotor cortical activity during song.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-06-03 04:47:42"}
  • {"files"=>["https://ndownloader.figshare.com/files/2094617"], "description"=>"<p><b>a</b>, Shown is the average phase difference between LFPs recorded on two separate electrodes as a function of distance along the dorsoventral (DV) (<i>n</i> = 70), mediolateral (ML) (<i>n</i> = 57), and anterior-posterior (AP) axes (<i>n</i> = 48). This data was collected using four-shank silicon probes (Neuronexus) and commercial microwire probes (TDT). <b>b</b>, Average difference in event times between ROIs observed using calcium imaging. The equation <i>M</i>(1 − exp(−<i>d</i>/<i>λ</i>))+<i>C</i> was fit to data in both <b>a</b> and <b>b</b> using a least squares procedure. In <b>a</b>, the data from each of the axes was separately fit (matching colors); the gray line represents the fit using data combined from the AP and ML axes. Error bars represent standard error of the mean (SEM). See also <b><a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002158#pbio.1002158.s005\" target=\"_blank\">S5 Fig</a>.</b></p>", "links"=>[], "tags"=>["length scale", "30 Hz network rhythm", "premotor", "sequence generation"], "article_id"=>1435766, "categories"=>["Biological Sciences"], "users"=>["Jeffrey E. Markowitz", "William A. Liberti III", "Grigori Guitchounts", "Tarciso Velho", "Carlos Lois", "Timothy J. Gardner"], "doi"=>"https://dx.doi.org/10.1371/journal.pbio.1002158.g006", "stats"=>{"downloads"=>0, "page_views"=>19, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_LFPs_in_the_25_8211_35_Hz_band_and_calcium_events_are_correlated_over_a_100_956_m_length_scale_/1435766", "title"=>"LFPs in the 25–35 Hz band and calcium events are correlated over a 100 μm length scale.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-06-03 04:47:42"}
  • {"files"=>["https://ndownloader.figshare.com/files/2094618"], "description"=>"<p><b>a,</b> Raster plots of three nearby (<200 μm) inhibitory neurons recorded during singing from the same bird. Synchronous pauses are marked with a black triangle. Shown to the right are three conceptual models of timing relationships between inhibitory and projection neuron activity. <b>b,</b> Interneuron firing patterns are uncorrelated in local ensembles, leading to a net local inhibition that is weakly modulated in time. <b>c,</b> Gaps in inhibitory neuron firing activity are locally correlated, leading to synchronous pauses in inhibition, but these pauses are unrelated to projection neuron activity. <b>d,</b> Gaps in inhibitory neuron firing activity are locally correlated, and contribute to defining projection neuron firing times. PN, projection neuron; INT, interneuron.</p>", "links"=>[], "tags"=>["length scale", "30 Hz network rhythm", "premotor", "sequence generation"], "article_id"=>1435767, "categories"=>["Biological Sciences"], "users"=>["Jeffrey E. Markowitz", "William A. Liberti III", "Grigori Guitchounts", "Tarciso Velho", "Carlos Lois", "Timothy J. Gardner"], "doi"=>"https://dx.doi.org/10.1371/journal.pbio.1002158.g007", "stats"=>{"downloads"=>2, "page_views"=>52, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Inhibitory_neuron_firing_patterns_and_three_models_for_projection_neuron_inhibitory_neuron_relationships_/1435767", "title"=>"Inhibitory neuron firing patterns and three models for projection neuron/inhibitory neuron relationships.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-06-03 04:47:42"}
  • {"files"=>["https://ndownloader.figshare.com/files/2094619"], "description"=>"<p><b>a,</b> Burst-triggered averages of 25–35 Hz (top row) and broadband LFPs (bottom) for interneurons (<i>n</i> = 65, <i>p</i> = 0, bootstrap test, see <b><a href=\"http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002158#sec007\" target=\"_blank\">Materials and Methods</a></b>) and (<b>b</b>) HVC<sub>X</sub> neurons (<i>n</i> = 12, <i>p</i> =. 006, bootstrap test). Gray line indicates <i>p</i> =. 05. <b>c,</b> Here, the power of the LFP is binned at the phase of the LFP for each burst time. A clear separation in preferred phase can be seen between HVC<sub>X</sub> neurons and interneurons.</p>", "links"=>[], "tags"=>["length scale", "30 Hz network rhythm", "premotor", "sequence generation"], "article_id"=>1435768, "categories"=>["Biological Sciences"], "users"=>["Jeffrey E. Markowitz", "William A. Liberti III", "Grigori Guitchounts", "Tarciso Velho", "Carlos Lois", "Timothy J. Gardner"], "doi"=>"https://dx.doi.org/10.1371/journal.pbio.1002158.g008", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Spike_field_analysis_reveals_an_alternating_30_Hz_rhythm_in_excitatory_and_inhibitory_cells_/1435768", "title"=>"Spike-field analysis reveals an alternating 30 Hz rhythm in excitatory and inhibitory cells.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-06-03 04:47:42"}
  • {"files"=>["https://ndownloader.figshare.com/files/2094621", "https://ndownloader.figshare.com/files/2094622", "https://ndownloader.figshare.com/files/2094623", "https://ndownloader.figshare.com/files/2094624", "https://ndownloader.figshare.com/files/2094625", "https://ndownloader.figshare.com/files/2094626"], "description"=>"<div><p>Time-locked sequences of neural activity can be found throughout the vertebrate forebrain in various species and behavioral contexts. From “time cells” in the hippocampus of rodents to cortical activity controlling movement, temporal sequence generation is integral to many forms of learned behavior. However, the mechanisms underlying sequence generation are not well known. Here, we describe a spatial and temporal organization of the songbird premotor cortical microcircuit that supports sparse sequences of neural activity. Multi-channel electrophysiology and calcium imaging reveal that neural activity in premotor cortex is correlated with a length scale of 100 µm. Within this length scale, basal-ganglia–projecting excitatory neurons, on average, fire at a specific phase of a local 30 Hz network rhythm. These results show that premotor cortical activity is inhomogeneous in time and space, and that a mesoscopic dynamical pattern underlies the generation of the neural sequences controlling song.</p></div>", "links"=>[], "tags"=>["length scale", "30 Hz network rhythm", "premotor", "sequence generation"], "article_id"=>1435770, "categories"=>["Biological Sciences"], "users"=>["Jeffrey E. Markowitz", "William A. Liberti III", "Grigori Guitchounts", "Tarciso Velho", "Carlos Lois", "Timothy J. Gardner"], "doi"=>["https://dx.doi.org/10.1371/journal.pbio.1002158.s001", "https://dx.doi.org/10.1371/journal.pbio.1002158.s002", "https://dx.doi.org/10.1371/journal.pbio.1002158.s003", "https://dx.doi.org/10.1371/journal.pbio.1002158.s004", "https://dx.doi.org/10.1371/journal.pbio.1002158.s005", "https://dx.doi.org/10.1371/journal.pbio.1002158.s006"], "stats"=>{"downloads"=>27, "page_views"=>39, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Mesoscopic_Patterns_of_Neural_Activity_Support_Songbird_Cortical_Sequences_/1435770", "title"=>"Mesoscopic Patterns of Neural Activity Support Songbird Cortical Sequences", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2015-06-03 04:47:42"}

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{"start_date"=>"2015-01-01T00:00:00Z", "end_date"=>"2015-12-31T00:00:00Z", "subject_areas"=>[]}
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