SCS Groups and Labs
IPM Birds Lab
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Significance

Vocal communication is a fundamental aspect of language, enabling social interactions, information exchange, and complex behaviors among individuals. It is a crucial tool for building social bonds, coordinating group activities, and conveying information about the environment, including food sources, predators, and social hierarchies. However, the neural mechanisms underlying vocal perception and learning remain largely unknown. Songbirds, such as the zebra finch (Taeniopygia guttata), stand out as exceptional models for investigating these questions due to their diverse but simple vocal repertoire and remarkable ability to learn songs from tutors in a manner akin to human speech acquisition. Studying these amazing creatures can provide valuable insights into the neurobiology of vocal communication, shedding light on the neural pathways that enable animals to learn complex auditory patterns and use them for social interactions and information exchange.
Surprisingly humans and songbirds share common similarities in their song systems. This is wonderful since they proceed through different evolutionary pathways. However, this similarity helps to understand the human vocal system, memory, and sensorimotor integration by studying songbirds. Furthermore, studying and identification of brain nuclei involved in vocal-motor activities in songbirds provide insights for neuroscientists to find cure methods for speech disorders and even language.

About

At IPM Birds Lab, we are studying birds especially songbirds over various dimensions. One involves studying them in their population, where we aim to examine the swarm behavior of birds in their natural habitat. This requires the capability to detect and analyze bird activities, in real-time, during their natural life. Another focus is on analyzing the vocal behavior of individual birds and their interactions and investigating the meaning of birds' songs and calls. Finally, we aim to record the neural activity of the birds and try to find its correlation with their behaviors. As our lab was established recently, our priority has been developing the necessary tools to support each aspect of our research.


Aviary


Our aviary is an enclosed and roofed patio garden, designed to provide the natural habitat of birds. The roof, constructed from a metallic mesh, allows for the free exchange of air and natural sunlight from the outside. To ensure optimal conditions for our birds, the aviary is equipped with air conditioning inlets and exhaust fans. Additionally, we have installed temperature and moisture sensors to regulate the environment as needed. Thanks to our old pine, birds resort to this pine as their natural shelter, especially when facing bright sunlight during summer days.

Behavioral Studies

Understanding the vocal behavior of songbirds is a very fascinating research area. The strategy for learning the songs from their tutors, uniqueness of songs within some species, having dialects within colonies, and critical periods for birds being able to learn to sing are examples of interesting questions studying these vocal behaviors. Knowing the meaning of their songs and calls, possibility of changing the meaning of their vocalizations through generations, ability to teach the newly ascribed meaning to their vocalizations socially and even communicating with them using their language are some interesting experiments targeting these subjects. These experiments are done in our lab with the aid of machine-learning tools and online song-processing systems.

Neural Studies

Currently, in our lab, we aim to discover the neural correlates for vocal perception in zebra finches. We employ electrophysiological acute recording techniques to gather spiking and local field potential (LFP) data from these birds. To facilitate this, we have developed a customized surgery protocol and tools necessary for neural recording and data analysis. Our research focus is to analyze the neural responses of different brain regions to a diverse range of auditory stimuli. In an experiment, we recorded the neural response of an anesthetized male zebra finch from its HVC area to three different stimuli: the bird’s own song (BOS), pure tones, and white noise. Interestingly, we observed that the two units in this recording responded differently to each stimulus. Moreover, we also noted distinct LFP responses to each stimulus. An example of the results is presented below.

Innovative Collaborations

We welcome groups from other labs and universities, collaborating to pursue common goals. For instance, we hosted a project to develop a miniaturized recording system, designed by researchers at Amirkabir University of Technology, intended for wireless neural recording from small animals. Moreover, in another collaboration, a custom-designed silicon probe, fabricated by researchers at Sharif University of Technology was evaluated at our lab and successful LFP responses to auditory stimuli were recorded.

Our Team

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Resident Investigator

Mahdi Khademian, PhD

Post-Doctoral Researcher
IPM SCS


Miniaturized
Electronic Devices

Mohammad Mahdi Ahmadi, PhD

Sadjad Ahmadi

Energy Harvesting for Miniaturized Electronic Devices

3D Machine Vision
Algorithms

Mohammad Reza Mohammadi, PhD

AmirMahdi Nikoukaran

Team member

Reza AliDoost

Team member

Electrophysiological
Recording

Amirreza Bahramani

Researcher

Zohreh Safarcharati

PhD Candidate

Milad Yekani

Post-Doctoral Researcher

Sana AminNaji

Team member

Behavioral
Research

Zohreh Safarcharati

PhD Candidate

Mahsa
Ravanbakhsh

Team member

Pouya
Mokari

Team member

Tahoura
Morovati

Team member

Founding Member:

Ali Ghazizadeh
Mahdi Khademian

Alumni:

Seyed Amir-Reza Kazemi (Ultrasonic localization of birds, PIT tagging)
Hoomaan Javaheri (Researcher)
Masoumeh Aqamolaei (Miniaturized electrophysiological recording aystem)
Arman Ali-Mohammadi (Birds detection and tracking using machine vision algorithms)
Milad Rahimi (Birds detection and tracking using machine vision algorithms - Thermal imaging)
Alborz Mirzadeh (V.M.D, Surgeon)
Shayan MousaviNia (Birds detection and tracking using machine vision algorithms)
Mohammad Farahmand (Birds detection and tracking using machine vision algorithms)