Mathematical and Computational Biosciences Collective Colloquium - Fall 2025
Seminars are typically held on Wednesdays from 1:00 - 2:00 PM as hybrid talks unless otherwise noted. The in-person presentation will take place in CKB 116 with a Zoom option for virtual attendees.
For questions about the seminar schedule, please contact James MacLaurin or Kristina Wicke.
September 17
Sage Chen, New York University (NYU)
Multiplicative feedback gating facilitates rapid learning and flexible computation in recurrent neural circuits
The mammalian forebrain is the seat of higher cognition with architectural parallels to modern machine learning systems. Specifically, the cortex resembles recurrent neural networks (RNNs) while the thalamus resembles feedforward neural networks (FNNs). How such architectural features endow the forebrain with its learning capacity, is unknown. Here, we take inspiration from empirical thalamocortical discovery and develop a multiplicative coupling mechanism between RNN-FNN architectures that collectively enhance their computational strengths and learning. The multiplicative interaction imposes a Hebbian-weight amplification onto synaptic- neuronal coupling, enabling context-dependent gating and rapid switching. Through a wide range of benchmark experiments on working memory, decision making, control, and pattern classification, we demonstrate that multiplicative gating-driven synaptic plasticity achieves 2-100 folds of speed improvement in supervised, reinforcement and unsupervised learning settings, boosting memory capacity, model robustness and generalization of RNNs. We further demonstrate the efficacy and biological plausibility of multiplicative gating in modeling four multiregional RNN-FNN circuits, including (1) a prefrontal cortex-mediodorsal thalamus network for context-dependent probabilistic decision making and context switching (Mukerjee et al. 2021 Nature; Wang et al. 2023 Nat. Commun.), (2) a cortico-thalamic-cortical network for working memory and attention (Panichello and Buschman, 2021 Nature), (3) a cerebellar-thalamic- cortical network for motor task switching (Pemberton et al., 2024 Nat. Commun.), and (4) an entorhinal cortex-hippocampus network for visuospatial navigation and sequence replay. Our model predictions not only validate various experimental findings reported independently from multiple species (rodent, monkey, human), multiple brain structures (MD thalamus, pulvinar, motor thalamus, hippocampal formation), and diverse tasks (cognitive, motor, navigation), but also provide experimentally testable hypotheses in neural perturbation studies.
September 24
David Liberles, Temple University
Patterns of Duplicate Gene Retention Over Different Timescales and With Different Selective Pressure
Gene duplication is an important process leading to gene content evolution in genomes. Three classes of models for gene duplicates will be described. The first model uses a Moran modeling framework to examine gene duplicates that are segregating in a population. Based upon the age of the duplicate and the frequency in the population, a test is performed to ask if the frequency is consistent with neutral processes or if there is evidence for selection on the duplicate itself.
A second modeling framework examines the interplay between dosage balance and functional evolution through subfunctionalization. The model suggests that from whole genome duplication events, dosage balance presents a selective barrier that must be overcome, but ultimately leads to enhanced retention of duplicates. For smaller scale duplicates, the reverse is true.
Lastly, it has been observed that some genes are more likely to be retained after duplication than other genes from a whole genome duplication event. A formal model based upon organismal gene content is presented that provides a time-dependent expectation for duplicate gene retention when different combinations of processes are acting. This modeling framework has been applied to sets of whole genome duplication events in fish and plants, characterizing both the gene contents and preservation processes that have acted.
Together these modeling frameworks provide community tools and present a picture of the processes acting on gene duplicates at different stages.
October 1
Alexa Aucoin and Jie Yang, NJIT Mathematical & Computational Biosciences Collective [Postdoctoral Researchers]
Title/Abstract Forthcoming
October 8
Jon Rubin, University of Pittsburgh
Title/Abstract Forthcoming
October 15
Ashok Litwin Kumar, Columbia University
Title/Abstract Forthcoming
October 22
Maurizio Porfiri, New York University (NYU)
Title/Abstract Forthcoming
October 29
Tatiana Engel, Princeton University
Title/Abstract Forthcoming
November 5
Marcelo Gehara, Rutgers University - Newark
Title/Abstract Forthcoming
November 12
Takuya Ito, IBM T.J. Watson Research Center
Title/Abstract Forthcoming
December 3
Emma Zajdela, Princeton University
Title/Abstract Forthcoming