Localization of signaling receptors maximizes cellular information acquisition in spatially structured natural environments

Wang, Zitong Jerry; Thomson, Matt

doi:10.1016/j.cels.2022.05.004

Cited by 5 publications

(6 citation statements)

References 107 publications

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Section: Mathematical Formulation Of Spatial Mapping As Predictive Co...mentioning

confidence: 99%

“….We consider an agent exploring an environment, Ω ⊂ℝ 2 , while acquiring visual information in the form of pixel valued image vectors I x ∈ ℝ m × n given an x ∈ Ω. The agent’s environment Ω is a bounded subset or ℝ 2 that could contain obstructions and holes. In general, at any given time, t , the agent’s state can be characterized by a position x ( t ) and orientation θ ( t ) where x ( t ) and θ ( t ) are coordinates within a global coordinate system unknown to the agent.…”

Section: Mathematical Formulation Of Spatial Mapping As Predictive Co...mentioning

confidence: 99%

“…To show that the auto-encoder cannot learn the environment’s map, we show that any statistical estimator cannot learn the environment’s map from stationary observations. For clarity and brevity, we will provide a proof sketch on a lattice environment X —a closed subset of ℤ 2 .…”

Section: Mathematical Formulation Of Spatial Mapping As Sensory Predi...mentioning

confidence: 99%

“…Consider an environment X—a closed subset of the lattice ℤ 2 with a function that gives an image I x = f ( x ) ⊂ ℝ D for each position x ∈ X. Let the environment’s observations be degenerate such that There exists no decoder that satisfies …”

Section: Mathematical Formulation Of Spatial Mapping As Sensory Predi...mentioning

confidence: 99%

“…Space and time are fundamental physical structures in the natural world, and all organisms have evolved strategies for navigating space to forage, mate, and escape predation. [1][2][3] . In humans and other mammals, the concept of a spatial or cognitive map has been postulated to underlie spatial reasoning tasks [4][5][6] .…”

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confidence: 99%

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Automated construction of cognitive maps with visual predictive coding

Gornet,

Thomson

2023

Preprint

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Humans construct internal cognitive maps of their environment directly from sensory inputs without access to a system of explicit coordinates or distance measurements. While machine learning algorithms like SLAM utilize specialized inference procedures to identify visual features and construct spatial maps from visual and odometry data, the general nature of cognitive maps in the brain suggests a unified mapping algorithmic strategy that can generalize to auditory, tactile, and linguistic inputs. Here, we demonstrate that predictive coding provides a natural and versatile neural network algorithm for constructing spatial maps using sensory data. We introduce a framework in which an agent navigates a virtual environment while engaging in visual predictive coding using a self-attention-equipped convolutional neural network. While learning a next image prediction task, the agent automatically constructs an internal representation of the environment that quantitatively reflects spatial distances. The internal map enables the agent to pinpoint its location relative to landmarks using only visual information.The predictive coding network generates a vectorized encoding of the environment that supports vector navigation where individual latent space units delineate localized, overlapping neighborhoods in the environment. Broadly, our work introduces predictive coding as a unified algorithmic framework for constructing cognitive maps that can naturally extend to the mapping of auditory, sensorimotor, and linguistic inputs.

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Section: Mathematical Formulation Of Spatial Mapping As Predictive Co...mentioning

confidence: 99%

Section: Mathematical Formulation Of Spatial Mapping As Predictive Co...mentioning

confidence: 99%

Section: Mathematical Formulation Of Spatial Mapping As Sensory Predi...mentioning

confidence: 99%

Section: Mathematical Formulation Of Spatial Mapping As Sensory Predi...mentioning

confidence: 99%

mentioning

confidence: 99%

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Automated construction of cognitive maps with visual predictive coding

Gornet,

Thomson

2023

Preprint

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Information theory entering soils and tissues

Sokolowski

2022

Cell Systems

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A probabilistic algorithm for optimising the steady-state diffusional flux into a partially absorbing body

Nicolaou,

Mulder

2023

Sci Rep

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Cells in an aqueous environment absorb diffusing nutrient molecules through nanoscale protein channels in their outer membranes. Assuming that there are constraints on the number of such channels a cell can produce, we ask the question: given a nondepleting source of nutrients, what is the optimal distribution of these channels over the cell surface? We coarse-grain this problem, phrasing it as a diffusion problem with position-dependent Robin boundary conditions on the surface. The aim is to maximize the steady-state total flux through the partially absorbing surface under an integral constraint on the local reactivities. We develop an algorithm to tackle this problem that uses the stored and processed results of a particle-based simulation with reflective boundary conditions to a posteriori estimate absorption flux at essentially negligible additional computational cost. We validate the algorithm against a few cases for which analytical or semi-analytical results are available. We apply it to two examples: a spherical cell in the presence of a point source and a spheroidal cell with an isotropic source at infinity. In the former case, there is a significant gain relative to the homogeneous case, while in the latter case the gain is only $$1\%$$ 1 % .

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Localization of signaling receptors maximizes cellular information acquisition in spatially structured natural environments

Cited by 5 publications

References 107 publications

Automated construction of cognitive maps with visual predictive coding

Automated construction of cognitive maps with visual predictive coding

Information theory entering soils and tissues

A probabilistic algorithm for optimising the steady-state diffusional flux into a partially absorbing body

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