The brain is a remarkably intricate and complex system in which the biophysical properties of neurons and networks dictate the dynamics emerging on the global scale to carry out a myriad of behavioral and cognitive functions. These biophysical properties encompass structural elements like anatomical connectivity and gene expression profiles defining functional characteristics of cells. Until recently, our ability to measure these properties experimentally was mostly confined to local circuits, providing only snapshots of the brain's complex functions. Despite these limitations, numerous theories and models have emerged to elucidate the brain's dynamics based on available information. While many of these models successfully explain how the brain can perform specific computations in localized regions, we still do not have models that recognize the brain as an integrated system, where every analytical level from molecular to behavioral intricately interacts. The vast space accommodating plausible dynamical accounts for the brain's global-scale operations poses a challenge. Meaningfully modeling brain-wide dynamics proves difficult without additional constraints that reasonably narrow down the solution space.
Recent coordinated efforts have launched long-term, large-scale experiments, which have begun to yield detailed maps of brain-wide activity and structural characteristics at an unprecedented level of detail. Examples include (but not limited to) the Brainwide Map and Electrophysiology Atlas from the International Brain Laboratory, a whole-brain connectome of Drosophila from the FlyWire consortium, a single-cell resolution macaque transcriptome by the Chinese Academy of Sciences, as well as the Human and Non-Human Primate cell atlas by BRAIN Initiative - Cell Census Network (BICCN). Such endeavors, once aspirational, are now concrete. Large-scale recordings have also become increasingly accessible even within individual labs. These datasets present a unique opportunity to gain insights into brain functions on the global scale and as an integrated system.
These breakthroughs present a pivotal moment for the field. The challenge now lies in forging new theories and computational frameworks capable of integrating these rich datasets. Analytical tools and mathematical/statistical frameworks need to be generalized to draw conclusions from large-scale multi-area neural recordings. Multi-omics should guide the next generation of brain-wide models, but at this point it is not clear how this can be achieved. Our proposed workshop includes recent work that tackles these challenges. Most important of all, large-scale neural recordings and multi-omics represent two highly complementary approaches towards understanding the brain as a whole. There is a great deal of untapped potential in improving our understanding of large-scale neural recordings by incorporating knowledge from multi-omics. Conversely, neural recordings provide invaluable insights into how the brain operates that can benefit omic-based approaches. To highlight and exploit this synergy, our proposed workshop aims to unite these two communities towards the common goal of developing a holistic understanding of brain-wide dynamics and elucidating the distributed computations that underlie cognition.Â
Our workshop is of particular interest to a wide audience of neuroscientists, including:
(1) experimentalists recording large-scale activity from multiple brain areas in different species
(2) data analysts seeking to draw conclusions from large-scale recordings
(3) experimentalists constructing omic maps and cell atlases
(4) theorists aiming to understand how the brain operates using multi-omics data
(5) modelers building whole-brain models based on multi-omics and large-scale recordings
(6) anyone working at the intersection of any of the above objectives
The confirmed speakers span a diverse range of topics and species within the themes of large-scale neural recordings and high-resolution multi-omics. The proposed workshop will include talks about acquiring, analyzing, and modeling:
(1) large-scale recordings from C. elegans, larval zebrafish, mice and humans
(2) connectomes in Drosophila and macaque monkeys
(3) transcriptomes in mice, macaque monkeys, and humans
(4) computational models based on large-scale recordings and multi-omics of Drosophila, mice and macaque monkeys
(5) recent interdisciplinary works (both theoretical and experimental) that involve both large-scale recordings and multi-omics
We anticipate that the interdisciplinary objective of this workshop will result in stimulating exchanges about the potential integration of large-scale recordings and multi-omics, ultimately contributing to the fostering of new research directions. In general, many fields of neuroscience are excited by the opportunities arising from the recent surge in high-quality neural and omic data, and as such, we believe that the theme of this workshop will resonate well with a significant population of Cosyne attendees.