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bair lab / uw neurobiology & biophysics

cross-orientation suppression across
cortical depth in macaque v1

dec 2024 - present / ~12 hrs/week / surgical assistant + computational analysis

Two-photon calcium imaging in anesthetized macaque V1. We present orthogonal plaids and compare responses to a linear prediction from component gratings. I built the full XORI analysis pipeline and assist in non-human primate neurosurgery.

Two-photon imaging + surgery in anesthetized macaque, with a custom Python pipeline for all analysis.

imaging

Two-photon calcium imaging in anesthetized macaque V1 using PHP.eB-CAG-GCaMP6s. Drifting gratings and orthogonal plaids at 50% contrast, 4 Hz, 4 cyc/deg.

  • 28 fields of view, 140 to 518 um deep
  • Superficial through deep layer 2/3
  • Collaboration with Allen Institute and WANPRC

roi extraction

Suite2p for automated cell detection, adapted for primate cortical data. Neuropil correction applied to all traces.

  • 4,785 ROIs across 28 depths
  • Neuropil subtraction and signal cleanup
  • SNR filtering at multiple thresholds

xori metric

For each ROI, build a linear prediction from component grating responses (shifted by 90 degrees, summed with baseline correction). Compare to actual plaid response.

  • S: plaid / linear prediction ratio
  • S > 1 = facilitation, S < 1 = suppression
  • C: Pearson r between predicted and observed tuning

statistics

Mixed-effects models to handle the nested structure: ROIs within depths within sessions. Mediation analysis for covariates.

  • Linear mixed-effects (statsmodels)
  • Random intercepts for session and depth
  • Mediation: spatial frequency (~40%), bandwidth (~21%)

Suppression increases with depth. Facilitation in superficial layer 2/3, suppression in deep layer 2/3.

S vs. depth S (suppression/facilitation strength) decreases with cortical depth, transitioning from facilitation in superficial L2/3 to suppression deeper. Persists after controlling for SNR, baseline fluorescence, and spatial frequency.
C vs. depth C (Pearson correlation between predicted and observed plaid tuning) increases with depth. Linear predictions become more accurate deeper in L2/3, even as responses fall below the linear sum.
spatial clustering S values cluster spatially within individual fields of view, suggesting local organization of suppressive interactions across the cortical surface.
bandwidth gradient Orientation bandwidth increases from ~60 to ~80 degrees with depth. Shows negative correlation with C within sites but positive correlation across sites, revealing complex tuning patterns.
laminar gradient Superficial (140-250 um): high SF, narrow tuning, high OSI, facilitation. Deep (400-518 um): low SF, broad tuning, low OSI, suppression. Gradual transition, not binary.

surgical

I assist in non-human primate neurosurgery: craniotomy prep, optical window implantation, perioperative monitoring. This gives us chronic two-photon imaging access to V1.

computational

I built the entire XORI analysis pipeline. ROI extraction, signal processing, cross-orientation index computation, mixed-effects modeling, mediation analysis, all figures. Every line of analysis code is mine.

in preparation

first-author arXiv preprint

Cross-orientation suppression across cortical depth in macaque V1. Target: April 2026.

in preparation

second-author manuscript

Full study with expanded dataset and additional analyses. Journal TBD.

upcoming

UW Research Symposium poster

University of Washington. May 2026.

presented

SfN 2025 poster

Society for Neuroscience. San Diego, CA. Nov 2025.

presented

WANPRC talk + poster

Washington National Primate Research Center. Seattle, WA. Dec 2025.

poster

Cross-orientation suppression across cortical depth in macaque V1. Presented at SfN San Diego and WANPRC Seattle.

download poster ↗

source code

Full pipeline: Suite2p integration, metric computation, mixed-effects models, mediation analysis, and all figures.

view on github ↗

analysis pipeline

Python Suite2p statsmodels scipy numpy pandas

statistics

linear mixed-effects models mediation analysis bootstrap CIs Pearson/Spearman correlation

visualization

matplotlib seaborn Jupyter scientific figures

imaging + surgery

two-photon microscopy GCaMP6s calcium imaging craniotomy prep optical window implantation

signal processing

neuropil subtraction SNR filtering ROI extraction tuning curve analysis

infrastructure

Git Linux MATLAB LaTeX
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