Glickfeld-And-Hull-Laboratories/ImagingCode-Glickfeld-Hull
Oct 2024 – Feb 2026
16 Months active
Languages Used
MATLABPython
Technical Skills
Data AnalysisImage ProcessingNeuroscienceScientific ComputingNeuroscience ResearchScripting
Celine
PROFILE
Celine
Celine Cammarata developed and maintained advanced neural data analysis pipelines for the Glickfeld-And-Hull-Laboratories/ImagingCode-Glickfeld-Hull repository, focusing on multi-day visual neuroscience experiments. She engineered robust MATLAB and Python workflows for data extraction, alignment, and visualization, integrating GPU-accelerated image processing and eye-tracking calibration to improve accuracy and throughput. Her work included refactoring and consolidating scripts for reproducibility, implementing configuration management for experimental setups, and enhancing statistical modeling for behavioral and electrophysiological data. By streamlining data management and automating analysis across diverse experimental conditions, Celine enabled scalable, reproducible research and accelerated the transition from raw data to publication-ready results.
Overall Statistics
Feature vs Bugs
89%Features
Repository Contributions
107Total
Bugs
4
Commits
107
Features
34
Lines of code
76,236
Activity Months16
Your Network
26 people
Work History
February 2026
2 Commits • 1 Features
Feb 1, 2026February 2026 monthly summary for Glickfeld-And-Hull-Laboratories ImagingCode-Glickfeld-Hull: Delivered enhancements to eye-tracking calibration and pupil data extraction to improve alignment and metric accuracy across cameras, strengthened data processing workflows, and streamlined integration with existing data structures. Implemented targeted calibration adjustments based on recording date and removed outdated functions to improve maintainability. A notable bug fix corrected pixel calibration for the camera, boosting measurement reliability across experiments.
2 Commits • 1 Features
Feb 1, 2026February 2026 monthly summary for Glickfeld-And-Hull-Laboratories ImagingCode-Glickfeld-Hull: Delivered enhancements to eye-tracking calibration and pupil data extraction to improve alignment and metric accuracy across cameras, strengthened data processing workflows, and streamlined integration with existing data structures. Implemented targeted calibration adjustments based on recording date and removed outdated functions to improve maintainability. A notable bug fix corrected pixel calibration for the camera, boosting measurement reliability across experiments.
February 2026
January 2026
10 Commits • 2 Features
Jan 1, 2026January 2026 monthly summary for repository Glickfeld-And-Hull-Laboratories/ImagingCode-Glickfeld-Hull: Implemented end-to-end enhancements to DART imaging analytics and strengthened dataset readiness. The work focused on two main deliverables: (1) Retinotopy Analysis Pipeline Enhancements for DART Data, consolidating MATLAB retinotopy capabilities for data loading, processing, alignment to matched datasets, time-course extraction, trial segmentation, and enhanced saving/parameter handling, with added support for pupil data handling and visualization; and (2) DART Dataset Updates and Documentation, refreshing experimental data entries and datasheets, updating instruction sheets and quickRet configurations for new sessions, and expanding dataset metadata with i2229, i2231, and YM90K return data to improve analysis readiness. These efforts tightened data integrity, improved reproducibility, and accelerated analytic readiness for DART experiments.)
January 2026
10 Commits • 2 Features
Jan 1, 2026January 2026 monthly summary for repository Glickfeld-And-Hull-Laboratories/ImagingCode-Glickfeld-Hull: Implemented end-to-end enhancements to DART imaging analytics and strengthened dataset readiness. The work focused on two main deliverables: (1) Retinotopy Analysis Pipeline Enhancements for DART Data, consolidating MATLAB retinotopy capabilities for data loading, processing, alignment to matched datasets, time-course extraction, trial segmentation, and enhanced saving/parameter handling, with added support for pupil data handling and visualization; and (2) DART Dataset Updates and Documentation, refreshing experimental data entries and datasheets, updating instruction sheets and quickRet configurations for new sessions, and expanding dataset metadata with i2229, i2231, and YM90K return data to improve analysis readiness. These efforts tightened data integrity, improved reproducibility, and accelerated analytic readiness for DART experiments.)
December 2025
15 Commits • 4 Features
Dec 1, 2025December 2025 monthly summary for Glickfeld-Hull ImagingCode: Delivered across neural data visualization and processing, DART alignment, two-photon dataset matching tooling, and expanded experimental configuration. Achievements focused on data fidelity, cross-day session alignment, and scalable visualization. Data sheet integrity and session identifier cleanliness were improved to ensure reliable analyses, supporting faster onboarding of new experiments and drug-condition studies.
15 Commits • 4 Features
Dec 1, 2025December 2025 monthly summary for Glickfeld-Hull ImagingCode: Delivered across neural data visualization and processing, DART alignment, two-photon dataset matching tooling, and expanded experimental configuration. Achievements focused on data fidelity, cross-day session alignment, and scalable visualization. Data sheet integrity and session identifier cleanliness were improved to ensure reliable analyses, supporting faster onboarding of new experiments and drug-condition studies.
December 2025
November 2025
8 Commits • 5 Features
Nov 1, 2025November 2025 focused on delivering scalable data-processing enhancements for ImagingCode-Glickfeld-Hull, with an emphasis on timing accuracy, accelerated computation, and multi-day experimental workflow improvements. Core work delivered includes frame timing correction using photodiode signals with enhanced visualization, GPU-accelerated image stack registration, and substantial DART pipeline upgrades. Additional pipeline restructuring and new experimental setups were implemented to improve data fidelity, session organization, and visualization across multi-day experiments.
November 2025
8 Commits • 5 Features
Nov 1, 2025November 2025 focused on delivering scalable data-processing enhancements for ImagingCode-Glickfeld-Hull, with an emphasis on timing accuracy, accelerated computation, and multi-day experimental workflow improvements. Core work delivered includes frame timing correction using photodiode signals with enhanced visualization, GPU-accelerated image stack registration, and substantial DART pipeline upgrades. Additional pipeline restructuring and new experimental setups were implemented to improve data fidelity, session organization, and visualization across multi-day experiments.
October 2025
7 Commits • 2 Features
Oct 1, 2025October 2025 monthly summary focusing on key accomplishments, major deliverables, and business impact for the ImagingCode-Glickfeld-Hull repository. This period centered on strengthening the DART pipeline configuration, improving robustness of neural analysis, and ensuring data integrity across multi-day experiments. Deliverables emphasize maintainability, reproducibility, and scalable analysis workflows that reduce manual intervention and accelerate scientific iteration.
7 Commits • 2 Features
Oct 1, 2025October 2025 monthly summary focusing on key accomplishments, major deliverables, and business impact for the ImagingCode-Glickfeld-Hull repository. This period centered on strengthening the DART pipeline configuration, improving robustness of neural analysis, and ensuring data integrity across multi-day experiments. Deliverables emphasize maintainability, reproducibility, and scalable analysis workflows that reduce manual intervention and accelerate scientific iteration.
October 2025
September 2025
16 Commits • 1 Features
Sep 1, 2025September 2025 performance summary for ImagingCode-Glickfeld-Hull. Delivered consolidated DART multi-day imaging data extraction and analysis pipeline enhancements enabling scalable, cross-day two-photon experiments. Implemented new extraction scripts with versioning and documentation; expanded cross-day alignment and multi-day visualization; established a dedicated DART pipeline folder and finalized pipeline scripts. Fixed input-structure handling issues in the extraction script and refined experiment configuration to improve reproducibility and data integrity. The work accelerates experimental throughput, improves data quality, and provides a solid foundation for expanded analyses and collaboration.
September 2025
16 Commits • 1 Features
Sep 1, 2025September 2025 performance summary for ImagingCode-Glickfeld-Hull. Delivered consolidated DART multi-day imaging data extraction and analysis pipeline enhancements enabling scalable, cross-day two-photon experiments. Implemented new extraction scripts with versioning and documentation; expanded cross-day alignment and multi-day visualization; established a dedicated DART pipeline folder and finalized pipeline scripts. Fixed input-structure handling issues in the extraction script and refined experiment configuration to improve reproducibility and data integrity. The work accelerates experimental throughput, improves data quality, and provides a solid foundation for expanded analyses and collaboration.
August 2025
8 Commits • 2 Features
Aug 1, 2025August 2025 monthly summary for ImagingCode-Glickfeld-Hull focusing on delivering robust cross-day data management, multi-size experiment support, and plotting improvements that drive longitudinal analyses and faster research cycles. Key outcomes include dataset updates, new experimental entries, refactored extraction/analysis pipelines, and enhanced documentation. These workstreams improve data integrity, enable cross-day alignment, and extend analysis capabilities across varying stimulus sizes.
8 Commits • 2 Features
Aug 1, 2025August 2025 monthly summary for ImagingCode-Glickfeld-Hull focusing on delivering robust cross-day data management, multi-size experiment support, and plotting improvements that drive longitudinal analyses and faster research cycles. Key outcomes include dataset updates, new experimental entries, refactored extraction/analysis pipelines, and enhanced documentation. These workstreams improve data integrity, enable cross-day alignment, and extend analysis capabilities across varying stimulus sizes.
August 2025
July 2025
2 Commits • 1 Features
Jul 1, 2025July 2025 monthly work summary for Glickfeld-And-Hull-Laboratories/ImagingCode-Glickfeld-Hull. Focused on delivering an enhanced neural data analysis pipeline for multi-day visual neuroscience experiments and enabling running-onset analysis across days. Key improvements include refactoring core scripts, improved trial processing and cell selection, and enhanced visualization and saving mechanisms; added dedicated running-onset analysis support with new scripts (runOnsetConcat.m, runOnsetDataCollect.m) and updates to multiDay aggregation scripts to accommodate running-onset studies across multi-day experiments. Commits include: aed4b48525baad5c629f1bbff7f69d8abfcfcd22 (Minor updates) and d6e31c63ef9fd4612f06f087fed89af43abbbcbe (run onset).
July 2025
2 Commits • 1 Features
Jul 1, 2025July 2025 monthly work summary for Glickfeld-And-Hull-Laboratories/ImagingCode-Glickfeld-Hull. Focused on delivering an enhanced neural data analysis pipeline for multi-day visual neuroscience experiments and enabling running-onset analysis across days. Key improvements include refactoring core scripts, improved trial processing and cell selection, and enhanced visualization and saving mechanisms; added dedicated running-onset analysis support with new scripts (runOnsetConcat.m, runOnsetDataCollect.m) and updates to multiDay aggregation scripts to accommodate running-onset studies across multi-day experiments. Commits include: aed4b48525baad5c629f1bbff7f69d8abfcfcd22 (Minor updates) and d6e31c63ef9fd4612f06f087fed89af43abbbcbe (run onset).
June 2025
2 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary for Glickfeld-And-Hull-Laboratories/ImagingCode-Glickfeld-Hull. Focused on delivering YM90K experiment configuration and data processing improvements to enhance reproducibility, reduce setup time, and improve data integrity across runs. Implemented streamlined YM90K workflows with new experimental configurations, refactored data processing to remove interactive prompts by hardcoding sensible defaults, adjusted file save locations, and added checks for experimental data fields. Introduced a dedicated setup configuration for mouse i2207 and updated session timing parameters, including a day_id adjustment to align data processing. These changes support reliable, scalable experimental runs and faster data-to-insight cycles.
2 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary for Glickfeld-And-Hull-Laboratories/ImagingCode-Glickfeld-Hull. Focused on delivering YM90K experiment configuration and data processing improvements to enhance reproducibility, reduce setup time, and improve data integrity across runs. Implemented streamlined YM90K workflows with new experimental configurations, refactored data processing to remove interactive prompts by hardcoding sensible defaults, adjusted file save locations, and added checks for experimental data fields. Introduced a dedicated setup configuration for mouse i2207 and updated session timing parameters, including a day_id adjustment to align data processing. These changes support reliable, scalable experimental runs and faster data-to-insight cycles.
June 2025
May 2025
9 Commits • 3 Features
May 1, 2025May 2025 monthly summary for Glickfeld-And-Hull-Laboratories/ImagingCode-Glickfeld-Hull. Focused on delivering robust analysis tooling, data organization, and publication-ready outputs, while addressing key data integrity issues. Key work spanned DART analysis tooling and publication figure generation, ITI-based onset analysis, and data structure refinements, accompanied by targeted bug fixes that improve labeling accuracy and trace storage. What was delivered: - DART Analysis Tooling and Publication Figure Generation: Implemented end-to-end DART tooling, OSI integration, and publication-grade figure generation across scripts, including the VIP_ReviewerFigure.m script, regression analyses, and improved data extraction for reproducibility and cross-study comparability. Commit highlights include f3afd929… (noise correlation regression), e2fc55db… (regression to compare betas), a7586a5f… (common operations/plots), 18f12794… (plotting updates), 02499a90… (Figure code), and 5b1aea6f… (Figure code for DART paper). - ITI Run Onset Finder: Added a new function to extract neural activity around running onsets within inter-trial intervals, with sanity checks and related script adjustments. Commit: d8a2ee73041a… (Before changing procedure to find running onsets). - Data Organization: Experimental Parameter Datastructures: Introduced a new datasheet for experimental configurations and refactored data processing to accommodate the new data structures. Commit: 39c0c049f8f3… (Making figure code, new datasheet). - Noise Correlation Extraction Bug Fix and Labeling Improvements: Fixed how processed traces are stored in noise correlation extraction, updated labels to SST (instead of VIP), and added boundary checks around locomotion alignment. Commit: 876913f6d7f9… (Fixed noise corr algorithm in extraction size script). Overall impact and business value: - Accelerated end-to-end analysis from data ingestion to publication-ready outputs, enabling faster cycles for manuscripts and presentations. - Improved data integrity and configurability via new experimental parameter datastructures, reducing setup time for new experiments. - Reduced risk of mislabeling and misinterpretation by aligning labels to SST and tightening boundary handling around locomotion alignment. - Strengthened reproducibility and cross-study comparability through publication-grade figure tooling and robust regression analyses. Technologies and skills demonstrated: - MATLAB-based analysis tooling, figure generation, and regression analytics. - Data modeling and refactoring for experimental configurations (data structures and datasheets). - Validation and QA practices via sanity checks in ITI onset detection and boundary management in noise correlation workflows. - OSI integration for analytics tooling and a focus on production-grade outputs for dissemination.
May 2025
9 Commits • 3 Features
May 1, 2025May 2025 monthly summary for Glickfeld-And-Hull-Laboratories/ImagingCode-Glickfeld-Hull. Focused on delivering robust analysis tooling, data organization, and publication-ready outputs, while addressing key data integrity issues. Key work spanned DART analysis tooling and publication figure generation, ITI-based onset analysis, and data structure refinements, accompanied by targeted bug fixes that improve labeling accuracy and trace storage. What was delivered: - DART Analysis Tooling and Publication Figure Generation: Implemented end-to-end DART tooling, OSI integration, and publication-grade figure generation across scripts, including the VIP_ReviewerFigure.m script, regression analyses, and improved data extraction for reproducibility and cross-study comparability. Commit highlights include f3afd929… (noise correlation regression), e2fc55db… (regression to compare betas), a7586a5f… (common operations/plots), 18f12794… (plotting updates), 02499a90… (Figure code), and 5b1aea6f… (Figure code for DART paper). - ITI Run Onset Finder: Added a new function to extract neural activity around running onsets within inter-trial intervals, with sanity checks and related script adjustments. Commit: d8a2ee73041a… (Before changing procedure to find running onsets). - Data Organization: Experimental Parameter Datastructures: Introduced a new datasheet for experimental configurations and refactored data processing to accommodate the new data structures. Commit: 39c0c049f8f3… (Making figure code, new datasheet). - Noise Correlation Extraction Bug Fix and Labeling Improvements: Fixed how processed traces are stored in noise correlation extraction, updated labels to SST (instead of VIP), and added boundary checks around locomotion alignment. Commit: 876913f6d7f9… (Fixed noise corr algorithm in extraction size script). Overall impact and business value: - Accelerated end-to-end analysis from data ingestion to publication-ready outputs, enabling faster cycles for manuscripts and presentations. - Improved data integrity and configurability via new experimental parameter datastructures, reducing setup time for new experiments. - Reduced risk of mislabeling and misinterpretation by aligning labels to SST and tightening boundary handling around locomotion alignment. - Strengthened reproducibility and cross-study comparability through publication-grade figure tooling and robust regression analyses. Technologies and skills demonstrated: - MATLAB-based analysis tooling, figure generation, and regression analytics. - Data modeling and refactoring for experimental configurations (data structures and datasheets). - Validation and QA practices via sanity checks in ITI onset detection and boundary management in noise correlation workflows. - OSI integration for analytics tooling and a focus on production-grade outputs for dissemination.
April 2025
13 Commits • 5 Features
Apr 1, 2025April 2025 monthly summary for Glickfeld-Hull ImagingCode-Glickfeld-Hull. Delivered a cohesive set of feature enhancements across EPSC detection, multi-day/slice data analytics, and data management, with substantial improvements in data quality, reproducibility, and visualization. Focused on business value by enabling faster, more reliable analyses and publish-ready visuals for multi-day experiments.
13 Commits • 5 Features
Apr 1, 2025April 2025 monthly summary for Glickfeld-Hull ImagingCode-Glickfeld-Hull. Delivered a cohesive set of feature enhancements across EPSC detection, multi-day/slice data analytics, and data management, with substantial improvements in data quality, reproducibility, and visualization. Focused on business value by enabling faster, more reliable analyses and publish-ready visuals for multi-day experiments.
April 2025
March 2025
4 Commits • 2 Features
Mar 1, 2025Concise monthly summary for 2025-03 focusing on key deliverables, major improvements, and business value for ImagingCode-Glickfeld-Hull. Highlights include: (1) Neural Data Analysis Enhancements with a locomotion-gated analysis script and refinements to green-channel imaging pipeline, plus standardized defaults for red/green wavelengths and improved visualization/reporting. (2) Codebase cleanup and event analysis metric enhancements, including removal of unused MATLAB scripts and enhanced event reporting metrics in YM90K_slice_240122.m. (3) Overall impact: increased data processing accuracy, faster reporting, improved reproducibility, and clearer visualization for stakeholder communication.
March 2025
4 Commits • 2 Features
Mar 1, 2025Concise monthly summary for 2025-03 focusing on key deliverables, major improvements, and business value for ImagingCode-Glickfeld-Hull. Highlights include: (1) Neural Data Analysis Enhancements with a locomotion-gated analysis script and refinements to green-channel imaging pipeline, plus standardized defaults for red/green wavelengths and improved visualization/reporting. (2) Codebase cleanup and event analysis metric enhancements, including removal of unused MATLAB scripts and enhanced event reporting metrics in YM90K_slice_240122.m. (3) Overall impact: increased data processing accuracy, faster reporting, improved reproducibility, and clearer visualization for stakeholder communication.
February 2025
3 Commits • 1 Features
Feb 1, 2025February 2025 performance summary for ImagingCode-Glickfeld-Hull: Delivered a unified data processing pipeline and implemented critical edge-case fixes, improving reproducibility and reducing run setup time for single-direction experiments. Key changes include consolidating multi-day processing into a single comprehensive analysis script to streamline stimulus-response extraction, locomotion analysis, and cell-type correlations; and updating dataset/experiment naming for clarity. Commits underpinning these changes include 26641cdf08997a43f0d2af829bd48cdf18a7e597 (Merging MATLAB scripts), 5d6abde4c8650dd8ad81ab89ea3f99b103342de2 (testing push), and d54f807e0b6097941d2eddb2f0e33eb0bbbeeb08 (Added a line for finding the "preferred" direction when there is only one direction). These changes enhance reproducibility, accelerate analysis, and improve maintainability.
3 Commits • 1 Features
Feb 1, 2025February 2025 performance summary for ImagingCode-Glickfeld-Hull: Delivered a unified data processing pipeline and implemented critical edge-case fixes, improving reproducibility and reducing run setup time for single-direction experiments. Key changes include consolidating multi-day processing into a single comprehensive analysis script to streamline stimulus-response extraction, locomotion analysis, and cell-type correlations; and updating dataset/experiment naming for clarity. Commits underpinning these changes include 26641cdf08997a43f0d2af829bd48cdf18a7e597 (Merging MATLAB scripts), 5d6abde4c8650dd8ad81ab89ea3f99b103342de2 (testing push), and d54f807e0b6097941d2eddb2f0e33eb0bbbeeb08 (Added a line for finding the "preferred" direction when there is only one direction). These changes enhance reproducibility, accelerate analysis, and improve maintainability.
February 2025
December 2024
5 Commits • 2 Features
Dec 1, 2024December 2024 monthly summary for ImagingCode-Glickfeld-Hull: Delivered advanced MATLAB tooling for multi-day neural and behavioral data analysis and a neural activity extraction framework with photodiode integration. Implemented cross-day experiment alignment, enhanced visualization, and robust timing checks to improve data integrity. Added utilities for running onset detection and counter timing analysis, and established behavior-correlation analyses with pupil size and locomotion. These efforts streamline preprocessing, enable longitudinal studies, and support scalable, reproducible research workflows.
December 2024
5 Commits • 2 Features
Dec 1, 2024December 2024 monthly summary for ImagingCode-Glickfeld-Hull: Delivered advanced MATLAB tooling for multi-day neural and behavioral data analysis and a neural activity extraction framework with photodiode integration. Implemented cross-day experiment alignment, enhanced visualization, and robust timing checks to improve data integrity. Added utilities for running onset detection and counter timing analysis, and established behavior-correlation analyses with pupil size and locomotion. These efforts streamline preprocessing, enable longitudinal studies, and support scalable, reproducible research workflows.
November 2024
2 Commits • 1 Features
Nov 1, 2024November 2024 monthly summary for Glickfeld-Hull ImagingCode repository. Delivered enhancements to DART data analysis, updated experimental parameters, and expanded data analysis capabilities. Key artifacts include new DART data entries, scripts for single-day and slice analysis, and refreshed multi-day workflows, along with a refined half-decay metric in network suppression analysis and a multi-wavelength comparison tool. All changes are traceable with committed changes and change-control backups to support reliability and auditability.
2 Commits • 1 Features
Nov 1, 2024November 2024 monthly summary for Glickfeld-Hull ImagingCode repository. Delivered enhancements to DART data analysis, updated experimental parameters, and expanded data analysis capabilities. Key artifacts include new DART data entries, scripts for single-day and slice analysis, and refreshed multi-day workflows, along with a refined half-decay metric in network suppression analysis and a multi-wavelength comparison tool. All changes are traceable with committed changes and change-control backups to support reliability and auditability.
November 2024
October 2024
1 Commits • 1 Features
Oct 1, 2024Month 2024-10: Focused development on neural data processing and analysis for visual stimuli experiments. In the ImagingCode-Glickfeld-Hull repository, delivered a significant pipeline enhancement that refactors data processing and analysis scripts, introduces new experimental data entries, adjusts response analysis time windows, and refines cell segmentation and timecourse extraction methods to improve accuracy and efficiency of neural response analyses. These changes streamline data workflows, improve reproducibility, and enable faster insights for visual stimulus experiments.
October 2024
1 Commits • 1 Features
Oct 1, 2024Month 2024-10: Focused development on neural data processing and analysis for visual stimuli experiments. In the ImagingCode-Glickfeld-Hull repository, delivered a significant pipeline enhancement that refactors data processing and analysis scripts, introduces new experimental data entries, adjusts response analysis time windows, and refines cell segmentation and timecourse extraction methods to improve accuracy and efficiency of neural response analyses. These changes streamline data workflows, improve reproducibility, and enable faster insights for visual stimulus experiments.
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Quality Metrics
Correctness85.4%
Maintainability82.6%
Architecture80.6%
Performance74.4%
AI Usage21.8%
Skills & Technologies
Programming Languages
MATLABPython
Technical Skills
Behavioral AnalysisBehavioral Data ProcessingCode RefactoringConfiguration ManagementData AnalysisData ConfigurationData ManagementData ProcessingData VisualizationElectrophysiologyElectrophysiology Data AnalysisExperimental ConfigurationExperimental Data EntryExperimental Data HandlingExperimental Data Management
Repositories Contributed To
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