For the first time, two senior postdoctoral researchers earned the annual Innovator Awards this year at the Princeton Neuroscience Institute (PNI), along with the traditional two awards reserved for pairs of collaborating interdisciplinary faculty members.

“There’s a dearth of funding opportunities for senior postdoctoral researchers,” said Mala Murthy, Ph.D., PNI's director and the Karol and Marnie Marcin ’96 professor of neuroscience. “By opening up PNI’s Innovator Awards to postdoctoral scholars, we aim to support exciting new research directions undertaken in collaboration with their advisors, and to facilitate transitions to the next career stage.” 

PNI postdoctoral research associate Rich Pang, Ph.D., and associate research scholar Chris Langdon, Ph.D. are the inaugural postdoc innovator awardees, as well as faculty member duos Uri Hasson, Ph.D. and Casey Lew-Williams, Ph.D., and Andrew Leifer, Ph.D. and Joshua Shaevitz, Ph.D.

Employing Machine Learning to Bridge Behavior and Whole-Brain Activity

Pang works across the labs of Dr. Murthy, PNI professor Jonathan Pillow, Ph.D., and associate PNI faculty member and the John Archibald Wheeler/Battelle professor of physics William Bialek, Ph.D. Pang’s project will use recurrent neural networks to analyze troves of whole-brain activity recordings to better understand how neural activity propagates throughout the brain and how it produces behavior.

“All of the neural data I have studied to date has been from recordings of small numbers of neurons or in very limited conditions,” Pang wrote in his application. “This proposal is a new direction into the analysis and modeling of large-scale recordings across a variety of complex conditions.”

Inspired by recent work from the lab of Hakan Türeci, Ph.D., a theoretical physicist and professor of electrical and computer engineering at Princeton, Pang will explore if Türeci’s newly developed framework for charting nonlinear dynamic systems, dubbed “eigentests,” can further reveal the computational properties of neural networks. 

Similar to Pang, Langdon, an associate research scholar in the lab of PNI associate professor Tatiana Engel, Ph.D., will use the Innovator Award funds to support his work on using recurrent neural networks to bridge our understanding of brain circuit connectivity, neural activity, and behavior.

“Chris’s project has the potential to transform our understanding of how cognitive functions arise from dynamic interactions in neural circuits,” Engel wrote about Langdon’s proposal. “Confirmation of theoretical predictions about the existence of functional cell types and their relationship to the neural response dimensionality may reveal a universal organizing principle of cortical circuits.”

Watching 1,000 Days of Home Movies to Learn How Children Develop Language

The old parenting adage goes that when you start a family and have kids, “the days are long, but the years are short”.

For PNI and psychology professor Uri Hasson, Ph.D. and associated PNI faculty member Casey Lew-Willaims, Ph.D., each day is about 1,500 hours long and stretches out until a child’s third birthday. 

That’s because Hasson and Lew-Williams will use their funds to support their unprecedented research that tracks children from the day they arrive home from the hospital until their third birthday.

Multiple cameras and microphones are installed across different rooms in each participating family’s house to track the development of fifteen babies in their natural home environment. In total, each three-year-old will have the most comprehensive and detailed home videos ever collected of the first 1000 days of their lives. 

In doing so, Hasson and Lew-Williams aim to gain a better understanding of how children naturally learn language by interacting with their supportive social environments. 

After resolving various ethical and technical obstacles, Hasson and Lew-Williams have recruited a diverse group of 15 families across New Jersey and Pennsylvania, including mixed-race, multigenerational, and LGBTQ+ families, which reflects each state’s demographics.

The Innovator Award funds will help support the team’s current recording endeavors and help build on their deep learning pipeline to sort through the petabytes of data collected across the project.

“With 100,000 one-minute audiovisual clips uploaded daily, we are collecting 36.5 million minutes annually, making the dataset too large to be manually labeled by human annotators,” the team wrote in their application. “The machine learning module will enable our team to quantify, for the first time, the natural, everyday statistics in infants’ environments that give rise to learning.”

Furthermore, their data will enable them to build a new generation of large language models capable of learning language from the child-centered linguistic input that each child receives in their natural environments.

Mapping How Brain Hormones Circulate to Understand Neuronal Communication

The pioneering neuroscientist Eve Marder often quips that neural circuit diagrams, like connectomes, are “…absolutely necessary but completely insufficient for understanding nervous system function.”

Missing from the brain’s road map is a fuller understanding of the traffic patterns, speed limits, and other cues that dictate how cells talk to one another. Neuroscientists have often focused on classic chemical messengers, like GABA and glutamate, but those neurotransmitters are only one of many modes of communication.

Unlike neurotransmitters, which go from one neuron to the next in like, neuropeptides are released from large packets that can travel many cells away from its host. That makes understanding who each cell is trying to communicate with much trickier to track.

To address this, PNI and physics associate professor Andrew Leifer, Ph.D., and associated PNI professor Joshua Shaevitz, Ph.D. will collaborate for their Innovator Award to better understand where neuropeptides and what rules govern their communication style by studying such phenomena in the roundworm Caenorhabditis elegans. C. elegans, as it’s often abbreviated, has a relatively simple nervous system totaling 302 well understood and mapped neurons.

Leifer and Shaevitz aim to take advantage of the roundworm’s manageable roadmap by adding a new layer of understanding how peptides travel along its neural circuitry.

“We propose to use sophisticated new peptide sensors and volumetric functional imaging to directly measure brain-wide neuropeptide dynamics in C. elegans, including where peptides go once released, how quickly they diffuse, and how anatomy influences their dynamics,” Leifer and Shaevitz wrote in their proposal. “The speed, extent and principles that govern how peptides travel will provide insights into their role in neural function.”

The Innovator Awards are generously supported by Endowments from the McDonnell Center for Systems Neuroscience, the Bezos Center for Neural Circuit Dynamics, and the Scully Center for the Neuroscience of Mind and Behavior.