This title appears in the Scientific Report :
2021
Please use the identifier:
http://hdl.handle.net/2128/28436 in citations.
Signal denoising through modular topography
Signal denoising through modular topography
To navigate in a dynamic and noisy environment, the brain must create reliable and meaningful representations from sensory inputs that are often ambiguous, incomplete or corrupt. From these noisy inputs, cortical circuits extract the relevant features to forge a ground truth against which internally...
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Personal Name(s): | Zajzon, Barna (Corresponding author) |
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Dahmen, David / Morrison, Abigail / Duarte, Renato | |
Contributing Institute: |
Computational and Systems Neuroscience; INM-6 Jara-Institut Brain structure-function relationships; INM-10 Computational and Systems Neuroscience; IAS-6 |
Imprint: |
2021
|
Conference: | 30th Annual Computational Neuroscience Meeting, Online (Germany), 2021-07-03 - 2021-07-07 |
Document Type: |
Poster |
Research Program: |
Computational Principles |
Link: |
OpenAccess |
Publikationsportal JuSER |
To navigate in a dynamic and noisy environment, the brain must create reliable and meaningful representations from sensory inputs that are often ambiguous, incomplete or corrupt. From these noisy inputs, cortical circuits extract the relevant features to forge a ground truth against which internally generated signals from inferential processes can be evaluated. Since information that fails to permeate the cortical hierarchy can not influence sensory perception and decision-making, it is critical that external stimuli are encoded and propagated through different processing stages in a manner that minimizes signal degradation.In this study, we hypothesize that stimulus-specific pathways akin to cortical topographic maps may provide the structural scaffold for such signal routing. A pervasive structural feature of the mammalian neocortex, topographic projections can imprint spatiotemporal features of (noisy) sensory inputs onto the cortex by preserving the relative organization of cells between distinct populations. Here, we investigate whether the feature-specific pathways within such maps can guide and route stimulus information throughout the system while retaining representational fidelity.We demonstrate that, in a large modular circuit of spiking neurons comprising multiple sub-networks, topographic projections can help the system reduce sensory and intrinsic noise to enable an accurate propagation of stimulus representations. Moreover, by regulating the effective connectivity and local E/I balance, modular topographic precision can instantiate a de-facto denoising auto-encoder, whereby the system's internal representation is gradually improved and signal-to-noise ratio increased as the input signal is transmitted through the network. Such a denoising function arises beyond a critical transition point in the sharpness of the feed-forward projections, and is characterized by the emergence of inhibition-dominated regimes where population responses along stimulated maps are amplified and others are weakened.In addition, we demonstrate that this is a generalizable and robust structural effect, largely independent of the underlying architectural specificities. Using mean-field approximations, we gain deeper insight into the mechanisms responsible for the qualitative changes in the system's behavior and show that these depend only on the modular topographic connectivity and stimulus intensity. The general dynamical principle revealed by the theoretical predictions suggest that such a denoising property may be a universal, system-agnostic feature of topographic maps. Finally, our results indicate that structured projection patterns can enable a wide range of behaviorally relevant regimes observed under various experimental conditions: maintaining stable representations of multiple stimuli across cortical circuits; amplifying certain features while suppressing others, resembling winner-take-all circuits; and endow circuits with metastable dynamics (winnerless competition), assumed to be fundamental in a variety of tasks. |