Dichotomous impact of afferent sensory noise on grid-patterned firing and path integration in a continuous attractor network model DOI
H.S. Nagaraj, Rishikesh Narayanan

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 20, 2024

A bstract Background The continuous attractor network (CAN) model has been effective in explaining grid-patterned firing the rodent medial entorhinal cortex, with strong lines of experimental evidence and widespread utilities understanding spatial navigation path integration. surprising lacuna CAN analyses is paucity quantitative studies on impact afferent sensory noise Here, we evaluate accuracy position estimates derived from pattern flow velocity. Motivated by ability border cells to act as an error-correction mechanism, also assess interaction between cell inputs performance. Methodology We used established 2D that received velocity a virtual animal traversing arena generate firing. estimated activity compute activity-based estimate at each time step. tracked difference real positions function called it deviation integrated (DIP). defined be additive Gaussian, different levels achieved changing variance. introduced north east connected them grid based co-activity patterns. For noise, computed DIP metrics for presence vs . absence cells. Importantly, avoid potential bias owing use single trajectory computing these measurements, performed all simulations across 50 trajectories. Results scores (as DIP) showed pronounced trajectory-to-trajectory variability, even noise-free network. With introduction variability prevailed unveiled dichotomous activity. Specifically, low improved estimation without altering In contrast, high impaired well activity, although were more sensitive compared stochastic resonance observed relationship level was partially explained noisy rectification nonlinearity neural transfer function. Finally, levels, grid-score addition inputs. Across population trajectories, yielded modest changes both measurements levels. Implications Our demonstrate robustness models does not extend other functions model. Stochastic reference implies biological CANs could evolve yield optimal performance (path integration) systems. An important methodological implication emerges our observations critical need account Given nature conclusions are bound erroneous thereby warranting multiple Together, unveil roles improving obtained models.

Language: Английский

Delay-induced multiple firing resonance in a coupled neuronal motif DOI

Hongfang Tan,

S. Xian

Nonlinear Dynamics, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 13, 2025

Language: Английский

Citations

0
Ion-channel degeneracy and heterogeneities in the emergence of signature physiological characteristics of dentate gyrus granule cells DOI
S. Sindhu Kumari, Rishikesh Narayanan

Journal of Neurophysiology, Journal Year: 2024, Volume and Issue: 132(3), P. 991 - 1013

Published: Aug. 7, 2024

A recent study from our laboratory had demonstrated pronounced heterogeneities in a set of 17 electrophysiological measurements obtained large population rat hippocampal granule cells. Here, we demonstrate the manifestation ion-channel degeneracy heterogeneous morphologically realistic conductance-based cell models that were validated against these and their cross-dependencies. Our analyses show single neurons are complex entities whose functions emerge through intricate interactions among several functionally specialized subsystems.

Language: Английский

Citations

1
The Brain's Best Kept Secret Is Its Degenerate Structure DOI
Larissa Albantakis, Christophe Bernard, Naama Brenner

et al.

Journal of Neuroscience, Journal Year: 2024, Volume and Issue: 44(40), P. e1339242024 - e1339242024

Published: Oct. 2, 2024

Degeneracy is defined as multiple sets of solutions that can produce very similar system performance. seen across phylogenetic scales, in all kinds organisms. In neuroscience, degeneracy be the constellation biophysical properties a neuron's characteristic intrinsic and/or mechanisms determine circuit outputs or behavior. Here, we present examples at levels organization, from single-cell behavior, small circuits, large and, cognition, drawing conclusions work ranging bacteria to human cognition. allows individual-to-individual variability within population creates potential for evolution.

Language: Английский

Citations

0
Dichotomous impact of afferent sensory noise on grid-patterned firing and path integration in a continuous attractor network model DOI
H.S. Nagaraj, Rishikesh Narayanan

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 20, 2024

A bstract Background The continuous attractor network (CAN) model has been effective in explaining grid-patterned firing the rodent medial entorhinal cortex, with strong lines of experimental evidence and widespread utilities understanding spatial navigation path integration. surprising lacuna CAN analyses is paucity quantitative studies on impact afferent sensory noise Here, we evaluate accuracy position estimates derived from pattern flow velocity. Motivated by ability border cells to act as an error-correction mechanism, also assess interaction between cell inputs performance. Methodology We used established 2D that received velocity a virtual animal traversing arena generate firing. estimated activity compute activity-based estimate at each time step. tracked difference real positions function called it deviation integrated (DIP). defined be additive Gaussian, different levels achieved changing variance. introduced north east connected them grid based co-activity patterns. For noise, computed DIP metrics for presence vs . absence cells. Importantly, avoid potential bias owing use single trajectory computing these measurements, performed all simulations across 50 trajectories. Results scores (as DIP) showed pronounced trajectory-to-trajectory variability, even noise-free network. With introduction variability prevailed unveiled dichotomous activity. Specifically, low improved estimation without altering In contrast, high impaired well activity, although were more sensitive compared stochastic resonance observed relationship level was partially explained noisy rectification nonlinearity neural transfer function. Finally, levels, grid-score addition inputs. Across population trajectories, yielded modest changes both measurements levels. Implications Our demonstrate robustness models does not extend other functions model. Stochastic reference implies biological CANs could evolve yield optimal performance (path integration) systems. An important methodological implication emerges our observations critical need account Given nature conclusions are bound erroneous thereby warranting multiple Together, unveil roles improving obtained models.

Language: Английский

Citations

0