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    MathWorks Inc custom-developed matlab software
    Custom Developed Matlab Software, 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
    https://www.bioz.com/product/custom+developed+software/pm40389518-51-7-8
    Average 90 stars, based on 1 article reviews
    custom-developed matlab software - by Bioz Stars, 2026-09
    90/100 stars

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    Fluorescence:

    Article Title: NF-κB memory coordinates transcriptional responses to dynamic inflammatory stimuli
    Article Snippet: .. Nuclear and cytoplasmic DsRed and/or mCerulean3 fluorescence for single cells were evaluated over the course of the experiment by analyzing time course fluorescence images with custom developed software (MATLAB). ..

    Article Title: Measuring Differences in Compositional Properties of Bone Tissue by Confocal Raman Spectroscopy
    Article Snippet: Background fluorescence in the spectra was subtracted by a modified polynomial fitting algorithm [ 22 ], and the raw peak intensities were calculated for ν 1 Phosphate at 960-962cm -1 (ν 1 PO 4 ) [ 10 , 23 ], ν 2 Phosphate at 431-433cm -1 (ν 2 PO 4 ) [ 10 ], ν 4 Phosphate at 584-589cm -1 (ν 4 PO 4 ) [ 10 , 23 ], Type-B carbonate at 1071-1072cm -1 (Carb) [ 23 ], Proline at 855-857cm -1 [ 23 , 24 ], Amide III at 1247-1248cm -1 [ 10 , 23 ], CH 2 -wag at 1451-1452cm -1 [ 10 , 23 ], and Amide I at 1666-1667cm -1 [ 10 , 23 ] ( ) using custom developed software (Matlab, Mathworks, Inc., Natick, MA). .. Background fluorescence in the spectra was subtracted by a modified polynomial fitting algorithm [ 22 ], and the raw peak intensities were calculated for ν 1 Phosphate at 960-962cm -1 (ν 1 PO 4 ) [ 10 , 23 ], ν 2 Phosphate at 431-433cm -1 (ν 2 PO 4 ) [ 10 ], ν 4 Phosphate at 584-589cm -1 (ν 4 PO 4 ) [ 10 , 23 ], Type-B carbonate at 1071-1072cm -1 (Carb) [ 23 ], Proline at 855-857cm -1 [ 23 , 24 ], Amide III at 1247-1248cm -1 [ 10 , 23 ], CH 2 -wag at 1451-1452cm -1 [ 10 , 23 ], and Amide I at 1666-1667cm -1 [ 10 , 23 ] ( ) using custom developed software (Matlab, Mathworks, Inc., Natick, MA). ..

    Article Title: Measuring Differences in Compositional Properties of Bone Tissue by Confocal Raman Spectroscopy
    Article Snippet: Calculating Raman Properties Background fluorescence in the spectra was subtracted by a modified polynomial fitting algorithm [ 22 ], and the raw peak intensities were calculated for ν 1 Phosphate at 960-962cm -1 (ν 1 PO 4 ) [ 10 , 23 ], ν 2 Phosphate at 431-433cm -1 (ν 2 PO 4 ) [ 10 ], ν 4 Phosphate at 584-589cm -1 (ν 4 PO 4 ) [ 10 , 23 ], Type-B carbonate at 1071-1072cm -1 (Carb) [ 23 ], Proline at 855-857cm -1 [ 23 , 24 ], Amide III at 1247-1248cm -1 [ 10 , 23 ], CH 2 -wag at 1451-1452cm -1 [ 10 , 23 ], and Amide I at 1666-1667cm -1 [ 10 , 23 ] ( ) using custom developed software (Matlab, Mathworks, Inc., Natick, MA). .. Calculating Raman Properties Background fluorescence in the spectra was subtracted by a modified polynomial fitting algorithm [ 22 ], and the raw peak intensities were calculated for ν 1 Phosphate at 960-962cm -1 (ν 1 PO 4 ) [ 10 , 23 ], ν 2 Phosphate at 431-433cm -1 (ν 2 PO 4 ) [ 10 ], ν 4 Phosphate at 584-589cm -1 (ν 4 PO 4 ) [ 10 , 23 ], Type-B carbonate at 1071-1072cm -1 (Carb) [ 23 ], Proline at 855-857cm -1 [ 23 , 24 ], Amide III at 1247-1248cm -1 [ 10 , 23 ], CH 2 -wag at 1451-1452cm -1 [ 10 , 23 ], and Amide I at 1666-1667cm -1 [ 10 , 23 ] ( ) using custom developed software (Matlab, Mathworks, Inc., Natick, MA). ..

    Software:

    Article Title: NF-κB memory coordinates transcriptional responses to dynamic inflammatory stimuli
    Article Snippet: .. Nuclear and cytoplasmic DsRed and/or mCerulean3 fluorescence for single cells were evaluated over the course of the experiment by analyzing time course fluorescence images with custom developed software (MATLAB). ..

    Article Title: Measuring Differences in Compositional Properties of Bone Tissue by Confocal Raman Spectroscopy
    Article Snippet: Background fluorescence in the spectra was subtracted by a modified polynomial fitting algorithm [ 22 ], and the raw peak intensities were calculated for ν 1 Phosphate at 960-962cm -1 (ν 1 PO 4 ) [ 10 , 23 ], ν 2 Phosphate at 431-433cm -1 (ν 2 PO 4 ) [ 10 ], ν 4 Phosphate at 584-589cm -1 (ν 4 PO 4 ) [ 10 , 23 ], Type-B carbonate at 1071-1072cm -1 (Carb) [ 23 ], Proline at 855-857cm -1 [ 23 , 24 ], Amide III at 1247-1248cm -1 [ 10 , 23 ], CH 2 -wag at 1451-1452cm -1 [ 10 , 23 ], and Amide I at 1666-1667cm -1 [ 10 , 23 ] ( ) using custom developed software (Matlab, Mathworks, Inc., Natick, MA). .. Background fluorescence in the spectra was subtracted by a modified polynomial fitting algorithm [ 22 ], and the raw peak intensities were calculated for ν 1 Phosphate at 960-962cm -1 (ν 1 PO 4 ) [ 10 , 23 ], ν 2 Phosphate at 431-433cm -1 (ν 2 PO 4 ) [ 10 ], ν 4 Phosphate at 584-589cm -1 (ν 4 PO 4 ) [ 10 , 23 ], Type-B carbonate at 1071-1072cm -1 (Carb) [ 23 ], Proline at 855-857cm -1 [ 23 , 24 ], Amide III at 1247-1248cm -1 [ 10 , 23 ], CH 2 -wag at 1451-1452cm -1 [ 10 , 23 ], and Amide I at 1666-1667cm -1 [ 10 , 23 ] ( ) using custom developed software (Matlab, Mathworks, Inc., Natick, MA). ..

    Article Title: Measuring Differences in Compositional Properties of Bone Tissue by Confocal Raman Spectroscopy
    Article Snippet: Calculating Raman Properties Background fluorescence in the spectra was subtracted by a modified polynomial fitting algorithm [ 22 ], and the raw peak intensities were calculated for ν 1 Phosphate at 960-962cm -1 (ν 1 PO 4 ) [ 10 , 23 ], ν 2 Phosphate at 431-433cm -1 (ν 2 PO 4 ) [ 10 ], ν 4 Phosphate at 584-589cm -1 (ν 4 PO 4 ) [ 10 , 23 ], Type-B carbonate at 1071-1072cm -1 (Carb) [ 23 ], Proline at 855-857cm -1 [ 23 , 24 ], Amide III at 1247-1248cm -1 [ 10 , 23 ], CH 2 -wag at 1451-1452cm -1 [ 10 , 23 ], and Amide I at 1666-1667cm -1 [ 10 , 23 ] ( ) using custom developed software (Matlab, Mathworks, Inc., Natick, MA). .. Calculating Raman Properties Background fluorescence in the spectra was subtracted by a modified polynomial fitting algorithm [ 22 ], and the raw peak intensities were calculated for ν 1 Phosphate at 960-962cm -1 (ν 1 PO 4 ) [ 10 , 23 ], ν 2 Phosphate at 431-433cm -1 (ν 2 PO 4 ) [ 10 ], ν 4 Phosphate at 584-589cm -1 (ν 4 PO 4 ) [ 10 , 23 ], Type-B carbonate at 1071-1072cm -1 (Carb) [ 23 ], Proline at 855-857cm -1 [ 23 , 24 ], Amide III at 1247-1248cm -1 [ 10 , 23 ], CH 2 -wag at 1451-1452cm -1 [ 10 , 23 ], and Amide I at 1666-1667cm -1 [ 10 , 23 ] ( ) using custom developed software (Matlab, Mathworks, Inc., Natick, MA). ..

    Article Title: Skin Temperature Prediction in Lower Limb Prostheses
    Article Snippet: .. Processing was performed with custom developed software (using Matlab®, Mathworks). ..

    other:

    Article Title: Advances in quantitative muscle ultrasonography using texture analysis of ultrasound images.
    Article Snippet: FILIPPO MOLINARI,* CRISTINA CARESIO,*y U. RAJENDRA ACHARYA,zx MUTHU RAMA KRISHNAN MOOKIAH,z and MARCO ALESSANDRO MINETTOyk *Biolab, Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy; yDivision of Endocrinology, Diabetology and Metabolism, Department of Medical Sciences, University of Turin, Turin, Italy; zDepartment of Electronics and Computer Engineering, Ngee Ann Polytechnic, Singapore; xDepartment of Biomedical Engineering, SIM University, Singapore; and kDivision of Physical Medicine and Rehabilitation, Department of Surgical Sciences, University of Turin, Turin, Italy

    Article Title: Diffuse reflectance spectroscopy accurately identifies the pre-cortical zone to avoid impending pedicle screw breach in spinal fixation surgery
    Article Snippet: Diffuse reflectance spectral data analysis Spectral analysis was performed with custom developed software using Matlab (MathWorks Inc., Natick, MA).

    Article Title: Quantification of Retinal Ganglion Cell Morphology in Human Glaucomatous Eyes
    Article Snippet: Retinal images were corrected for eye length and converted from degrees to millimeters according to the method introduced by Bennett et al. We first manually marked GCL soma coordinates (x, y, z) using custom developed software in MATLAB (Mathworks Inc., Natick, MA, USA), which permits reliable cell identification through simultaneous visualization of B-scans in both fast and slow directions and an en face projection at the depth-of-interest ( ).

    Article Title: After Effects of Cerebellar Continuous Theta Burst Stimulation on Reflexive Saccades and Smooth Pursuit in Humans.
    Article Snippet: The use of cerebellar repetitive transcranial magnetic stimulation has been attempted for perturbing reflexive and voluntary eye movements, but discrepancies are seen between the results of distinct studies possibly due to the different stimulation sites, intensities, and paradigms.. We describe the after effects of 20 and 40 s continuous Theta Burst Stimulation (cTBS) as compared to sham stimulation, applied over the lateral cerebellar vermis and paravermis on Reflexive Saccades (RS) and Smooth Pursuit (SP) eye movements, recorded in the 30 min following stimulation.. The experiments were carried out in eight healthy volunteers, and eye movements were recorded monocularly with video-oculography.

    Modification:

    Article Title: Measuring Differences in Compositional Properties of Bone Tissue by Confocal Raman Spectroscopy
    Article Snippet: Background fluorescence in the spectra was subtracted by a modified polynomial fitting algorithm [ 22 ], and the raw peak intensities were calculated for ν 1 Phosphate at 960-962cm -1 (ν 1 PO 4 ) [ 10 , 23 ], ν 2 Phosphate at 431-433cm -1 (ν 2 PO 4 ) [ 10 ], ν 4 Phosphate at 584-589cm -1 (ν 4 PO 4 ) [ 10 , 23 ], Type-B carbonate at 1071-1072cm -1 (Carb) [ 23 ], Proline at 855-857cm -1 [ 23 , 24 ], Amide III at 1247-1248cm -1 [ 10 , 23 ], CH 2 -wag at 1451-1452cm -1 [ 10 , 23 ], and Amide I at 1666-1667cm -1 [ 10 , 23 ] ( ) using custom developed software (Matlab, Mathworks, Inc., Natick, MA). .. Background fluorescence in the spectra was subtracted by a modified polynomial fitting algorithm [ 22 ], and the raw peak intensities were calculated for ν 1 Phosphate at 960-962cm -1 (ν 1 PO 4 ) [ 10 , 23 ], ν 2 Phosphate at 431-433cm -1 (ν 2 PO 4 ) [ 10 ], ν 4 Phosphate at 584-589cm -1 (ν 4 PO 4 ) [ 10 , 23 ], Type-B carbonate at 1071-1072cm -1 (Carb) [ 23 ], Proline at 855-857cm -1 [ 23 , 24 ], Amide III at 1247-1248cm -1 [ 10 , 23 ], CH 2 -wag at 1451-1452cm -1 [ 10 , 23 ], and Amide I at 1666-1667cm -1 [ 10 , 23 ] ( ) using custom developed software (Matlab, Mathworks, Inc., Natick, MA). ..

    Article Title: Measuring Differences in Compositional Properties of Bone Tissue by Confocal Raman Spectroscopy
    Article Snippet: Calculating Raman Properties Background fluorescence in the spectra was subtracted by a modified polynomial fitting algorithm [ 22 ], and the raw peak intensities were calculated for ν 1 Phosphate at 960-962cm -1 (ν 1 PO 4 ) [ 10 , 23 ], ν 2 Phosphate at 431-433cm -1 (ν 2 PO 4 ) [ 10 ], ν 4 Phosphate at 584-589cm -1 (ν 4 PO 4 ) [ 10 , 23 ], Type-B carbonate at 1071-1072cm -1 (Carb) [ 23 ], Proline at 855-857cm -1 [ 23 , 24 ], Amide III at 1247-1248cm -1 [ 10 , 23 ], CH 2 -wag at 1451-1452cm -1 [ 10 , 23 ], and Amide I at 1666-1667cm -1 [ 10 , 23 ] ( ) using custom developed software (Matlab, Mathworks, Inc., Natick, MA). .. Calculating Raman Properties Background fluorescence in the spectra was subtracted by a modified polynomial fitting algorithm [ 22 ], and the raw peak intensities were calculated for ν 1 Phosphate at 960-962cm -1 (ν 1 PO 4 ) [ 10 , 23 ], ν 2 Phosphate at 431-433cm -1 (ν 2 PO 4 ) [ 10 ], ν 4 Phosphate at 584-589cm -1 (ν 4 PO 4 ) [ 10 , 23 ], Type-B carbonate at 1071-1072cm -1 (Carb) [ 23 ], Proline at 855-857cm -1 [ 23 , 24 ], Amide III at 1247-1248cm -1 [ 10 , 23 ], CH 2 -wag at 1451-1452cm -1 [ 10 , 23 ], and Amide I at 1666-1667cm -1 [ 10 , 23 ] ( ) using custom developed software (Matlab, Mathworks, Inc., Natick, MA). ..



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    Hippocampal neuronal activity represents object <t>exploration</t> during OPR task (A) Normalized firing rate of hippocampal single-units in relation to object exploration in the sample phase of the OPR task. Units increasing their firing rate over 2 SD for at least 200 ms from object exploration onset (time 0) were classified as activated neurons (object cells, n = 114). The remaining non-encoding neuronal population did not significantly change its firing rate in relation to object exploration ( n = 136). (B) Average pairwise crosscorrelograms between object cells (red, n = 353 pairs) and non-encoding neurons (black, n = 812 pairs). Synchrony between object cells was significantly larger ( p < 8.5 × 10e-10, Wilcoxon rank-sum test). Average peri-event crosscorrelograms between hippocampal units and sleep oscillations showing consistent differences between object cells and non-encoding cells: slow wave activity (C, p < 6.1 × 10e-4), spindles (D, p < 6.4 × 10e-3) and ripples (E, p < 1.6 × 10e-3). Wilcoxon rank-sum test.
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    MathWorks Inc custom developed matlab software tool
    Hippocampal neuronal activity represents object <t>exploration</t> during OPR task (A) Normalized firing rate of hippocampal single-units in relation to object exploration in the sample phase of the OPR task. Units increasing their firing rate over 2 SD for at least 200 ms from object exploration onset (time 0) were classified as activated neurons (object cells, n = 114). The remaining non-encoding neuronal population did not significantly change its firing rate in relation to object exploration ( n = 136). (B) Average pairwise crosscorrelograms between object cells (red, n = 353 pairs) and non-encoding neurons (black, n = 812 pairs). Synchrony between object cells was significantly larger ( p < 8.5 × 10e-10, Wilcoxon rank-sum test). Average peri-event crosscorrelograms between hippocampal units and sleep oscillations showing consistent differences between object cells and non-encoding cells: slow wave activity (C, p < 6.1 × 10e-4), spindles (D, p < 6.4 × 10e-3) and ripples (E, p < 1.6 × 10e-3). Wilcoxon rank-sum test.
    Custom Developed Matlab Software Tool, 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
    https://www.bioz.com/product/custom+developed+software/pm37985488-65-11-13
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    Image Search Results


    Hippocampal neuronal activity represents object exploration during OPR task (A) Normalized firing rate of hippocampal single-units in relation to object exploration in the sample phase of the OPR task. Units increasing their firing rate over 2 SD for at least 200 ms from object exploration onset (time 0) were classified as activated neurons (object cells, n = 114). The remaining non-encoding neuronal population did not significantly change its firing rate in relation to object exploration ( n = 136). (B) Average pairwise crosscorrelograms between object cells (red, n = 353 pairs) and non-encoding neurons (black, n = 812 pairs). Synchrony between object cells was significantly larger ( p < 8.5 × 10e-10, Wilcoxon rank-sum test). Average peri-event crosscorrelograms between hippocampal units and sleep oscillations showing consistent differences between object cells and non-encoding cells: slow wave activity (C, p < 6.1 × 10e-4), spindles (D, p < 6.4 × 10e-3) and ripples (E, p < 1.6 × 10e-3). Wilcoxon rank-sum test.

    Journal: iScience

    Article Title: Sleep-dependent decorrelation of hippocampal spatial representations

    doi: 10.1016/j.isci.2024.110076

    Figure Lengend Snippet: Hippocampal neuronal activity represents object exploration during OPR task (A) Normalized firing rate of hippocampal single-units in relation to object exploration in the sample phase of the OPR task. Units increasing their firing rate over 2 SD for at least 200 ms from object exploration onset (time 0) were classified as activated neurons (object cells, n = 114). The remaining non-encoding neuronal population did not significantly change its firing rate in relation to object exploration ( n = 136). (B) Average pairwise crosscorrelograms between object cells (red, n = 353 pairs) and non-encoding neurons (black, n = 812 pairs). Synchrony between object cells was significantly larger ( p < 8.5 × 10e-10, Wilcoxon rank-sum test). Average peri-event crosscorrelograms between hippocampal units and sleep oscillations showing consistent differences between object cells and non-encoding cells: slow wave activity (C, p < 6.1 × 10e-4), spindles (D, p < 6.4 × 10e-3) and ripples (E, p < 1.6 × 10e-3). Wilcoxon rank-sum test.

    Article Snippet: Scoring was performed by quantifying the exploration time of each object using custom-developed software in MATLAB.

    Techniques: Activity Assay

    Place cells are more excitable and synchronized than non-spatial neurons during sleep (A and B) Example place cell (A) and non-spatial cell (B) simultaneously recorded in the same experimental session, during the test phase (rat GV11, session 03). Left, spatial trajectory (black) and single spikes (red) discharged during arena exploration. Large white circles depict object location. Right, heat maps. (C) Average firing rates of place cells (PC, n = 192) and non-spatial cells (NS, n = 324) according to task phase. Note place cells are consistently more active than non-spatial cells (two-way ANOVA, p = 3.7 × 10e-21). Task stages were also different within groups (Kruskal-Wallis test, p = 4.9 × 10e-9 for place cells and p = 1.4 × 10e-6 for non-spatial cells). (D) Average firing rates of place cells and non-spatial cells according to sleep phase. Note place cells are consistently more active than non-spatial cells (two-way ANOVA, p = 3.1 × 10e-10). Sleep phases were also different within groups (Wilcoxon signed rank test, p = 1.37 × 10e-10 for place cells and p = 6.6 × 10e-8 for non-spatial cells). (E) Peak pairwise crosscorrelogram amplitude for place cells and non-spatial cells according to task phase. Note place cells are consistently more synchronized than non-spatial cells, particularly during sleep (Kruskal-Wallis test, p = 4.8 × 10e-26 for place cells and p = 0.20 for non-spatial cells). (F) Peak pairwise crosscorrelogram amplitude for place cells and non-spatial cells according to sleep phase. Note place cells are consistently more synchronized than non-spatial cells (two-way ANOVA, p = 1.8 × 10e-167), particularly during NREM. Sleep phases were also different within groups (Wilcoxon rank-sum test, p = 7.9 × 10e-26 for place cells and p = 4.5 × 10e-33 for non-spatial cells). (G) Average pairwise crosscorrelograms between place cells (red, n = 1,503 pairs) and non-spatial neurons (black, n = 4,221 pairs). Synchrony between place cells was significantly larger (Wilcoxon rank-sum test, p = 3.8 × 10e-89). Average peri-event crosscorrelogram between hippocampal units and sleep oscillations showing consistent differences between place cells and non-spatial cells: slow wave activity (H, p = 2.3 × 10e-7), spindles (I, p = 1.6 × 10e-7), and ripples (J, p = 4.1 × 10e-8). Wilcoxon rank-sum test. Asterisks indicate significant differences, p < 0.05, pairwise Tukey’s test. See also <xref ref-type=Figures S9 and . " width="100%" height="100%">

    Journal: iScience

    Article Title: Sleep-dependent decorrelation of hippocampal spatial representations

    doi: 10.1016/j.isci.2024.110076

    Figure Lengend Snippet: Place cells are more excitable and synchronized than non-spatial neurons during sleep (A and B) Example place cell (A) and non-spatial cell (B) simultaneously recorded in the same experimental session, during the test phase (rat GV11, session 03). Left, spatial trajectory (black) and single spikes (red) discharged during arena exploration. Large white circles depict object location. Right, heat maps. (C) Average firing rates of place cells (PC, n = 192) and non-spatial cells (NS, n = 324) according to task phase. Note place cells are consistently more active than non-spatial cells (two-way ANOVA, p = 3.7 × 10e-21). Task stages were also different within groups (Kruskal-Wallis test, p = 4.9 × 10e-9 for place cells and p = 1.4 × 10e-6 for non-spatial cells). (D) Average firing rates of place cells and non-spatial cells according to sleep phase. Note place cells are consistently more active than non-spatial cells (two-way ANOVA, p = 3.1 × 10e-10). Sleep phases were also different within groups (Wilcoxon signed rank test, p = 1.37 × 10e-10 for place cells and p = 6.6 × 10e-8 for non-spatial cells). (E) Peak pairwise crosscorrelogram amplitude for place cells and non-spatial cells according to task phase. Note place cells are consistently more synchronized than non-spatial cells, particularly during sleep (Kruskal-Wallis test, p = 4.8 × 10e-26 for place cells and p = 0.20 for non-spatial cells). (F) Peak pairwise crosscorrelogram amplitude for place cells and non-spatial cells according to sleep phase. Note place cells are consistently more synchronized than non-spatial cells (two-way ANOVA, p = 1.8 × 10e-167), particularly during NREM. Sleep phases were also different within groups (Wilcoxon rank-sum test, p = 7.9 × 10e-26 for place cells and p = 4.5 × 10e-33 for non-spatial cells). (G) Average pairwise crosscorrelograms between place cells (red, n = 1,503 pairs) and non-spatial neurons (black, n = 4,221 pairs). Synchrony between place cells was significantly larger (Wilcoxon rank-sum test, p = 3.8 × 10e-89). Average peri-event crosscorrelogram between hippocampal units and sleep oscillations showing consistent differences between place cells and non-spatial cells: slow wave activity (H, p = 2.3 × 10e-7), spindles (I, p = 1.6 × 10e-7), and ripples (J, p = 4.1 × 10e-8). Wilcoxon rank-sum test. Asterisks indicate significant differences, p < 0.05, pairwise Tukey’s test. See also Figures S9 and .

    Article Snippet: Scoring was performed by quantifying the exploration time of each object using custom-developed software in MATLAB.

    Techniques: Activity Assay

    Stability of spatial representations decreases across sleep Examples of place cells recorded in the exploration phases of the OPR task (A) or the open field (C). Average spatial correlation of place cells in relation to NREM duration for the OPR task (B, computed between test and sample phases, r = −0.53, p = 0.03, Spearman’s correlation) or the open field (D, computed between after and before sleep, r = 0.07, p = 0.97, Spearman’s correlation). Examples of population vector correlation maps obtained from sessions with different NREM durations for the OPR task (E, n = 15 sessions) and the open field (G, n = 9 sessions). Population vector correlation (stability index) in relation to NREM duration for the OPR task (F, r = −0.55, p = 0.028, Spearman’s correlation) and open field (H, r = 0.35, p = 0.36, Spearman’s correlation). Only significant linear regressions are plotted.

    Journal: iScience

    Article Title: Sleep-dependent decorrelation of hippocampal spatial representations

    doi: 10.1016/j.isci.2024.110076

    Figure Lengend Snippet: Stability of spatial representations decreases across sleep Examples of place cells recorded in the exploration phases of the OPR task (A) or the open field (C). Average spatial correlation of place cells in relation to NREM duration for the OPR task (B, computed between test and sample phases, r = −0.53, p = 0.03, Spearman’s correlation) or the open field (D, computed between after and before sleep, r = 0.07, p = 0.97, Spearman’s correlation). Examples of population vector correlation maps obtained from sessions with different NREM durations for the OPR task (E, n = 15 sessions) and the open field (G, n = 9 sessions). Population vector correlation (stability index) in relation to NREM duration for the OPR task (F, r = −0.55, p = 0.028, Spearman’s correlation) and open field (H, r = 0.35, p = 0.36, Spearman’s correlation). Only significant linear regressions are plotted.

    Article Snippet: Scoring was performed by quantifying the exploration time of each object using custom-developed software in MATLAB.

    Techniques: Plasmid Preparation