2023 Research Grant Awards
Awarded to Professor Michael Dickinson (BBE)
A neural circuit that regulates the dispersal and foraging ecology of insects
This project will use a broad array of techniques available in Drosophila to gain insight into one of the most ecologically relevant of all animal behaviors: dispersal and foraging ecology. Organisms ranging in scale from bacteria to whales exhibit a behavioral motif in which long straight movements through resource-sparse landscapes (dispersal) are punctuated by intense exploration of resource-rich regions (local search). This project will help synthesize the goal of classic ethology to understand the mechanisms underlying naturalistic and ecologically relevant behaviors with the tools and perspective of modern neuroscience.
Awarded to Professor Angelika Stathopoulos (BBE) and Professor Lior Pachter (BBE)
How do Notch and Fgf signaling interact to control specification of neurons in Drosophila?
Drosophila fibroblast growth factor (FGF) genes and downstream signaling pathway components exhibit conservation with vertebrates. However, while vertebrate fibroblast growth FGFs are secreted in entirety, the Drosophila Pyramus FGF is a Type I transmembrane protein, raising the possibility that Pyr signals in "reverse". The goal of this project is to define and investigate the mechanism by which Pyr and Notch determine the identities of these neurons.
T&C CHEN CENTER FOR SYSTEMS NEUROSCIENCE AWARDS
Awarded to Assistant Professor Wei Gao (EAS) and Professor Yuki Oka (BBE)
Soft Bioelectronics for Monitoring and Controlling Hypertension
Hypertension causes various health complications such as heart failure, inflammation and stroke. As a chronic multi-factorial disorder, hypertension is very challenging to be identified and sequestered. This project aims toward developing soft implantable bioelectronics that will continuously monitor biomarkers for early diagnosis and provide treatment via vagus nerve stimulation. This could provide a general platform for studying a wide variety of disorders and advances closed-loop therapies by accounting for multiple disease biomarkers.
Awarded to Professor Thanos Siapas (BBE) and Professor Long Cai (BBE)
Combining two-photon imaging with spatial transcriptomics
Learning has long been hypothesized to be mediated by activity-driven selective changes of synaptic connections in brain circuits. Activity-dependent gene expression is believed to play a key role in this process, but a complete view of the gene expression changes at trascriptome scale and its relationship to neural activity has been missing. This project aims to develop scalable approaches for combining two-photon imaging with seqFISH+ profiling of all imaged cells to enable characterizing the relationship between neural activity and transcriptional changes during learning.
Awarded to Professor Paul Sternberg (BBE)
Spatially separated detectors for gradient detection
Detecting potential mating partners in a complex landscape of olfactory information is an ancient problem that motile organisms evolved to solve. This project hypothesizes a novel mechanism for odor localization in C. elegans: males compare signal inputs from both head and tail neurons and integrate this information to guide olfactory navigation, which enables high-efficiency spatial searching and sexually dimorphic behaviors. By coupling customized microfluidic chips with a multi-chamber perfusion system, precise optogenetic perturbation and pan-neuronal activity imaging in freely behaving animals, the project will be able to elucidate an algorithm using spatially separated detectors for a single odorant to efficiently chemotax.
Awarded to Research Professor Daniel Wagenaar (BBE) and Professor David Prober (BBE)
A tracking two-photon microscope for studying visually guided behaviors in larval zebrafish
This project will study the neuronal basis of visual processing during hunting behavior, specifically, how the visual system copes with saccade-like movements that severely disrupt visual inputs. Conventional fixed-stage microscopes using visible light impose limitations on studies of visually guided animal behavior. Wagenaar and Prober will develop a two-photon microscope equipped with a 3D tracking system to keep the brain of a freely swimming zebrafish centered and focused under the microscope.
T&C CHEN CENTER FOR SOCIAL AND DECISION NEUROSCIENCE AWARDS
Awarded to Professor John O'Doherty (HSS) and Visiting Associate Ueli Rutishauser (BBE)
Probing the neural correlates of the allocation of control between mixtures of experts in the human basal ganglia with deep-brain electrophysiology
The goal of this project is to examine the role of the human basal ganglia (BG) and its cortical afferents in supporting the selection between different expert systems relevant for solving complex decision problems. O'Doherty and Rutishauser will use a combination of intracranial BG recordings from deep brain stimulation electrodes alongside scalp electroencephalography (EEG) while participants perform a battery of two decision tasks designed to involve multiple expert systems.
T&C CHEN BRAIN-MACHINE INTERFACE CENTER AWARDS
Awarded to Professor Michelle Effros (EAS)
Modeling for Plasticity and Storage
This project works towards building a mathematical model of neuronal memory storage, with a focus on the role of neuronal plasticity in memory formation and persistence. A central mystery of neuronal memory storage is how to understand the effect of ongoing neuronal plasticity, which both enables memory creation and threatens its persistence over time. Using simple stochastic models of neuronal firing and plasticity, this project seeks to understand how the simultaneously creative and destructive natures of neuronal plasticity interact and to capture the limits of the balance between them that enables healthy memory function.
Awarded to Professor Pietro Perona (EAS)
Label-free analysis of behavior across species in the cloud
Perona will develop the science for, and build, a cloud-based system that analyzes video of social behavior of animals in the lab, and in the wild, accurately and inexpensively. This tool will be easy to use and will have transformative effects on discovery in neurobiology and ethology. The technical approach combines self-supervised and unsupervised learning. Transformers, with both continuous and discrete components, model multi-dimensional time-series. Task programming (recently developed in collaboration with Y. Yue at Caltech) will capture scientists' expert knowledge. The data will be aggregated in the cloud, thus enabling Perona to train networks that eventually will work across different setups and/or labs.
Awarded to Professor Yisong Yue (EAS) and Professor Joel Burdick (EAS)
Towards Robust Computational Frameworks for Non-Invasive Brain-Machine Interfaces
The goal of the project is to push the frontiers of non-invasive brain machine interfaces with the aim of accelerating their path towards widespread adoption. Yue and Burdick plan to develop a unified computational framework for non-invasive brain machine interfaces, using devices such as electroencephalography and electromyography. Utilizing their past work in cross-subject and multimodal decoding they hope to: (1) establish baseline performance on cross-subject, cross-session, multimodal data, (2) maximize information content in low bit-rate decoders, (3) improve calibration time across sessions.