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Silhouette Analysis, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Silhouette Coefficient Analysis, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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MathWorks Inc cluster analysis toolbox
Subpopulations of MS Rhythmic Neurons Based on Spike Train Dynamics (A) Simultaneously recorded septal neurons display diverse firing patterns (bottom, ticks) in head-fixed mice running on a Styrofoam ball (top, left). MS neurons were sampled with a silicon probe (top, middle). Note, DiI painted silicon probe depicts recording location in the MS (top, right). (B) Hierarchical clustering of strongly rhythmic MS neurons (rhythmicity index > 0.1, n = 89) into four groups based on rate change score and burst duration as parameters. Left, comparison of rate change score and burst duration for the four groups (median values, Kruskal-Wallis test). Right, <t>silhouette</t> values show high intra-cluster similarity. Cells in each cluster are ordered by decreasing silhouette value (range, −1 to 1). Large positive values indicate group cohesion for each point (cell) toward points in its own cluster versus points in other clusters (see for calculation). (C) Representative simultaneously recorded Teevra and Komal cells show differences in their burst duration. Left, during theta oscillations (s), detected bursts are shorter for Teevra cell (red horizontal lines, bursts detected; colors identify spikes within a burst; arrows, spikes not detected by the algorithm). Middle, inter-spike interval histogram of Teevra cell displays an additional peak at <5 ms (asterisk) compared to Komal cell. Right, the firing rate of a Teevra cell is not modulated by running speed (green, weighted fitting function f = 92.6 Hz – 0.26 × s; where s is the speed), whereas that of a Komal cell increases with running speed (purple, p < 0.005, weighted fitting function f = 60.5 Hz +1.6 × s; where s is the speed, dashed lines, 95% confidence interval). (D) Preferential theta phase of firing of Teevra and Komal cells with rhythmicity index as the radius (RUN periods). Most Komal cells (purple) fire preferentially at the peak of CA1 pyramidal cell layer theta oscillations, whereas most Teevra cells (green) fire phase coupled to the trough with increasing rhythmicity index. See also and explanation and <xref ref-type=Figure S2 . " width="250" height="auto" />
Cluster Analysis Toolbox, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Simi Reality Motion Systems markerless silhouette
Subpopulations of MS Rhythmic Neurons Based on Spike Train Dynamics (A) Simultaneously recorded septal neurons display diverse firing patterns (bottom, ticks) in head-fixed mice running on a Styrofoam ball (top, left). MS neurons were sampled with a silicon probe (top, middle). Note, DiI painted silicon probe depicts recording location in the MS (top, right). (B) Hierarchical clustering of strongly rhythmic MS neurons (rhythmicity index > 0.1, n = 89) into four groups based on rate change score and burst duration as parameters. Left, comparison of rate change score and burst duration for the four groups (median values, Kruskal-Wallis test). Right, <t>silhouette</t> values show high intra-cluster similarity. Cells in each cluster are ordered by decreasing silhouette value (range, −1 to 1). Large positive values indicate group cohesion for each point (cell) toward points in its own cluster versus points in other clusters (see for calculation). (C) Representative simultaneously recorded Teevra and Komal cells show differences in their burst duration. Left, during theta oscillations (s), detected bursts are shorter for Teevra cell (red horizontal lines, bursts detected; colors identify spikes within a burst; arrows, spikes not detected by the algorithm). Middle, inter-spike interval histogram of Teevra cell displays an additional peak at <5 ms (asterisk) compared to Komal cell. Right, the firing rate of a Teevra cell is not modulated by running speed (green, weighted fitting function f = 92.6 Hz – 0.26 × s; where s is the speed), whereas that of a Komal cell increases with running speed (purple, p < 0.005, weighted fitting function f = 60.5 Hz +1.6 × s; where s is the speed, dashed lines, 95% confidence interval). (D) Preferential theta phase of firing of Teevra and Komal cells with rhythmicity index as the radius (RUN periods). Most Komal cells (purple) fire preferentially at the peak of CA1 pyramidal cell layer theta oscillations, whereas most Teevra cells (green) fire phase coupled to the trough with increasing rhythmicity index. See also and explanation and <xref ref-type=Figure S2 . " width="250" height="auto" />
Markerless Silhouette, supplied by Simi Reality Motion Systems, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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MathWorks Inc k-means clustering analysis silhouette routine
Subpopulations of MS Rhythmic Neurons Based on Spike Train Dynamics (A) Simultaneously recorded septal neurons display diverse firing patterns (bottom, ticks) in head-fixed mice running on a Styrofoam ball (top, left). MS neurons were sampled with a silicon probe (top, middle). Note, DiI painted silicon probe depicts recording location in the MS (top, right). (B) Hierarchical clustering of strongly rhythmic MS neurons (rhythmicity index > 0.1, n = 89) into four groups based on rate change score and burst duration as parameters. Left, comparison of rate change score and burst duration for the four groups (median values, Kruskal-Wallis test). Right, <t>silhouette</t> values show high intra-cluster similarity. Cells in each cluster are ordered by decreasing silhouette value (range, −1 to 1). Large positive values indicate group cohesion for each point (cell) toward points in its own cluster versus points in other clusters (see for calculation). (C) Representative simultaneously recorded Teevra and Komal cells show differences in their burst duration. Left, during theta oscillations (s), detected bursts are shorter for Teevra cell (red horizontal lines, bursts detected; colors identify spikes within a burst; arrows, spikes not detected by the algorithm). Middle, inter-spike interval histogram of Teevra cell displays an additional peak at <5 ms (asterisk) compared to Komal cell. Right, the firing rate of a Teevra cell is not modulated by running speed (green, weighted fitting function f = 92.6 Hz – 0.26 × s; where s is the speed), whereas that of a Komal cell increases with running speed (purple, p < 0.005, weighted fitting function f = 60.5 Hz +1.6 × s; where s is the speed, dashed lines, 95% confidence interval). (D) Preferential theta phase of firing of Teevra and Komal cells with rhythmicity index as the radius (RUN periods). Most Komal cells (purple) fire preferentially at the peak of CA1 pyramidal cell layer theta oscillations, whereas most Teevra cells (green) fire phase coupled to the trough with increasing rhythmicity index. See also and explanation and <xref ref-type=Figure S2 . " width="250" height="auto" />
K Means Clustering Analysis Silhouette Routine, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Subpopulations of MS Rhythmic Neurons Based on Spike Train Dynamics (A) Simultaneously recorded septal neurons display diverse firing patterns (bottom, ticks) in head-fixed mice running on a Styrofoam ball (top, left). MS neurons were sampled with a silicon probe (top, middle). Note, DiI painted silicon probe depicts recording location in the MS (top, right). (B) Hierarchical clustering of strongly rhythmic MS neurons (rhythmicity index > 0.1, n = 89) into four groups based on rate change score and burst duration as parameters. Left, comparison of rate change score and burst duration for the four groups (median values, Kruskal-Wallis test). Right, silhouette values show high intra-cluster similarity. Cells in each cluster are ordered by decreasing silhouette value (range, −1 to 1). Large positive values indicate group cohesion for each point (cell) toward points in its own cluster versus points in other clusters (see for calculation). (C) Representative simultaneously recorded Teevra and Komal cells show differences in their burst duration. Left, during theta oscillations (s), detected bursts are shorter for Teevra cell (red horizontal lines, bursts detected; colors identify spikes within a burst; arrows, spikes not detected by the algorithm). Middle, inter-spike interval histogram of Teevra cell displays an additional peak at <5 ms (asterisk) compared to Komal cell. Right, the firing rate of a Teevra cell is not modulated by running speed (green, weighted fitting function f = 92.6 Hz – 0.26 × s; where s is the speed), whereas that of a Komal cell increases with running speed (purple, p < 0.005, weighted fitting function f = 60.5 Hz +1.6 × s; where s is the speed, dashed lines, 95% confidence interval). (D) Preferential theta phase of firing of Teevra and Komal cells with rhythmicity index as the radius (RUN periods). Most Komal cells (purple) fire preferentially at the peak of CA1 pyramidal cell layer theta oscillations, whereas most Teevra cells (green) fire phase coupled to the trough with increasing rhythmicity index. See also and explanation and <xref ref-type=Figure S2 . " width="100%" height="100%">

Journal: Neuron

Article Title: Behavior-Dependent Activity and Synaptic Organization of Septo-hippocampal GABAergic Neurons Selectively Targeting the Hippocampal CA3 Area

doi: 10.1016/j.neuron.2017.10.033

Figure Lengend Snippet: Subpopulations of MS Rhythmic Neurons Based on Spike Train Dynamics (A) Simultaneously recorded septal neurons display diverse firing patterns (bottom, ticks) in head-fixed mice running on a Styrofoam ball (top, left). MS neurons were sampled with a silicon probe (top, middle). Note, DiI painted silicon probe depicts recording location in the MS (top, right). (B) Hierarchical clustering of strongly rhythmic MS neurons (rhythmicity index > 0.1, n = 89) into four groups based on rate change score and burst duration as parameters. Left, comparison of rate change score and burst duration for the four groups (median values, Kruskal-Wallis test). Right, silhouette values show high intra-cluster similarity. Cells in each cluster are ordered by decreasing silhouette value (range, −1 to 1). Large positive values indicate group cohesion for each point (cell) toward points in its own cluster versus points in other clusters (see for calculation). (C) Representative simultaneously recorded Teevra and Komal cells show differences in their burst duration. Left, during theta oscillations (s), detected bursts are shorter for Teevra cell (red horizontal lines, bursts detected; colors identify spikes within a burst; arrows, spikes not detected by the algorithm). Middle, inter-spike interval histogram of Teevra cell displays an additional peak at <5 ms (asterisk) compared to Komal cell. Right, the firing rate of a Teevra cell is not modulated by running speed (green, weighted fitting function f = 92.6 Hz – 0.26 × s; where s is the speed), whereas that of a Komal cell increases with running speed (purple, p < 0.005, weighted fitting function f = 60.5 Hz +1.6 × s; where s is the speed, dashed lines, 95% confidence interval). (D) Preferential theta phase of firing of Teevra and Komal cells with rhythmicity index as the radius (RUN periods). Most Komal cells (purple) fire preferentially at the peak of CA1 pyramidal cell layer theta oscillations, whereas most Teevra cells (green) fire phase coupled to the trough with increasing rhythmicity index. See also and explanation and Figure S2 .

Article Snippet: The silhouette value (MATLAB, Cluster Analysis toolbox, range: −1 to 1) for each point is a measure of how similar that point is to points in its own cluster versus points in other clusters according to the following formula: S i = ( b i − a i ) / max ( a i , b i ) where a i is the average distance from the i th point to the other points in the same cluster as i, and b i is the minimum average distance from the i th point to points in a different cluster, minimized over clusters.

Techniques: Comparison