Mathematical and Computational Biosciences Collective Colloquium - Spring 2026

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.

Zoom link for seminars: https://njit-edu.zoom.us/j/99264610662?pwd=zFOFhY2fJ0HMdedKu5aPROv3zaKJrg.1

*******************************************************************************************************

February 04

Jorge Golowasch and Kristina Wicke, NJIT

Faculty Research Overview

*******************************************************************************************************

February 11

Danielle Bassett, University of Pennsylvania

How Costly is Your Brain's Activity Pattern

Neural systems in general—and the human brain in particular—are organized as networks of interconnected components. Across a range of spatial scales from single cells to macroscopic areas, biological neural networks are neither perfectly ordered nor perfectly random. Their heterogeneous organization supports---and simultaneously constrains---complex patterns of activity. How does the network constraint affect the cost of a specific brain's pattern? In this talk, I will use the formalism of network control theory to define a notion of network economy: the idea that a biological neural network’s organization partially determines the energetic cost of reaching a neural state, maintaining a neural state, and transitioning between neural states. Then, I will demonstrate how the principle of network economy can inform our study of neural system function in health and disease.

*******************************************************************************************************

February 18

James MacLaurin and Victor Matveev, NJIT

Faculty Research Overview

*******************************************************************************************************

February 25

Noah Cowan, Johns Hopkins University

Control and recalibration of path integration in the hippocampus

The hippocampus is thought to serve as a “cognitive map” wherein the events of an animal’s experience are encoded within a spatiotemporal framework. To continuously update the animal’s position and orientation on this internal map, the hippocampal system integrates self-motion signals over time. External landmarks provide feedback to correct the errors in the position estimate that would otherwise inevitably accumulate. Using a novel virtual reality apparatus, we discovered that if path integration is biased, such that the animal consistently under- or overestimates its movement through space, the landmarks (Jayakumar et al, Nature, 2019) or optic flow cues (Madhav et al, Nature Neuroscience 2024) in the environment can serve as a teaching signal for recalibration of the path integrator. Using a biophysically plausible attractor neural network model of path integration, we show that for landmark- based recalibration the path integration error, or its integral, must be encoded at the level of individual neurons in order to enable path integration recalibration (Secer et al, 2025, Nat Comm). Using this prediction, we turned back to the physiological data and discovered a rate code for error at the level of individual neurons. Finally, I’ll describe our team’s recent discovery that Area 29e, an understudied parahippocampal field, serves as specialized visuospatial hub that may carry landmark signals for anchoring hippocampal representations of space to the external world (Secer et al., bioRxiv, 2025).

This body work is the result of an equal collaboration with the lab of Prof. James Knierim, generously funded by the NIH and ARO.

*******************************************************************************************************