# Development of a "smart aviary" to probe neural dynamics of complex social behaviors in a gregarious songbird

> **NIH NIH R34** · UNIVERSITY OF PENNSYLVANIA · 2024 · $343,050

## Abstract

SUMMARY
 The nervous system of social species has evolved to perceive and evaluate signals within a social
context. Social information therefore must impact how the brain processes information, yet little is
still known about how the brain integrates social information to produce actions in a social context.
This lack of knowledge exists in part because social context is difficult to quantify and because the
majority of studies are performed in species that do not have a particularly rich social structure. Here
we propose to study the brown-headed cowbird (Molothrus ater), a highly gregarious songbird
species whose social behavior has been well studied and where vocal and non-vocal communication
signals form a central and critical component of its social system.
 We have created a “smart aviary” equipped with cameras and microphones that is capable of
monitoring behavior in each individual during the entire breeding season. Our aim is to create a fully
automated system using computer vision and machine learning technology to evaluate moment-to-
moment behavioral interactions between all member of the group (9 females and 7 males) over the
entire breeding season. We have assembled an interdisciplinary team of engineers, neurobiologists
and computational scientists, to create a platform where we can record
dynamics
quantify
learning
directly
the
segment
invasive
in
enable
social
develop
quantify
associated
social
and evaluate how brain
are shaped within a complex social context over an ethologically relevant timescale. To
 moment-to-moment behavior in each individual bird, we are developing a novel machine
 approach that tracks each bird and predicts its position, orientation, pose, and shape
from images using artificial neural networks and a 3D articulated mesh model. By collecting
output of the model over consecutive frames we will obtain a pose trajectory, which we will
and classify into discrete behaviora l types. We also aim to develop a miniature non-
wirelessly powered and transmitting recording device optimized for long duration recording
our aviary that critically does not impact bird individual or social behavior. Such a device would
 us to link neural activation patterns to discrete behavioral events (e.g. male song) within the
context in which these specific events occurred. Supplied with our rich dataset, we aim to
mathematical tools necessary to generate social network models that will allow us to
the specific state of the bird social network associated with neural activation patterns
with individual behavioral events. To the best of our nowledge, the proposal to link
network state to neural activation in a precise quantitative manner has never before been
,
k
attempted. Through these efforts, we will be well positioned to subsequently pursue a Targeted Brain
Circuits Projects R01 to investigate in a quantitative manner how social context influences brain
activity.

## Key facts

- **NIH application ID:** 10786687
- **Project number:** 1R34DA059507-01
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** Firooz Aflatouni
- **Activity code:** R34 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $343,050
- **Award type:** 1
- **Project period:** 2024-04-15 → 2026-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10786687

## Citation

> US National Institutes of Health, RePORTER application 10786687, Development of a "smart aviary" to probe neural dynamics of complex social behaviors in a gregarious songbird (1R34DA059507-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10786687. Licensed CC0.

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