Understanding the retinal basis of vision across species
The vertebrate retina first evolved some 500 million years ago in ancestral marine
chordates. Since then, the eyes of different species have been tuned to best support their …
chordates. Since then, the eyes of different species have been tuned to best support their …
From water to land: Evolution of photoreceptor circuits for vision in air
When vertebrates first conquered the land, they encountered a visual world that was
radically distinct from that of their aquatic ancestors. Fish exploit the strong wavelength …
radically distinct from that of their aquatic ancestors. Fish exploit the strong wavelength …
Interpreting the retinal neural code for natural scenes: From computations to neurons
Understanding the circuit mechanisms of the visual code for natural scenes is a central goal
of sensory neuroscience. We show that a three-layer network model predicts retinal natural …
of sensory neuroscience. We show that a three-layer network model predicts retinal natural …
Predictive information in a sensory population
Guiding behavior requires the brain to make predictions about the future values of sensory
inputs. Here, we show that efficient predictive computation starts at the earliest stages of the …
inputs. Here, we show that efficient predictive computation starts at the earliest stages of the …
Efficient sensory encoding and Bayesian inference with heterogeneous neural populations
The efficient coding hypothesis posits that sensory systems maximize information
transmitted to the brain about the environment. We develop a precise and testable form of …
transmitted to the brain about the environment. We develop a precise and testable form of …
Toward a unified theory of efficient, predictive, and sparse coding
A central goal in theoretical neuroscience is to predict the response properties of sensory
neurons from first principles. To this end,“efficient coding” posits that sensory neurons …
neurons from first principles. To this end,“efficient coding” posits that sensory neurons …
Systematic errors in connectivity inferred from activity in strongly recurrent networks
Understanding the mechanisms of neural computation and learning will require knowledge
of the underlying circuitry. Because it is difficult to directly measure the wiring diagrams of …
of the underlying circuitry. Because it is difficult to directly measure the wiring diagrams of …
Unsupervised image saliency detection with Gestalt-laws guided optimization and visual attention based refinement
Visual attention is a kind of fundamental cognitive capability that allows human beings to
focus on the region of interests (ROIs) under complex natural environments. What kind of …
focus on the region of interests (ROIs) under complex natural environments. What kind of …
Data-driven emergence of convolutional structure in neural networks
Exploiting data invariances is crucial for efficient learning in both artificial and biological
neural circuits. Understanding how neural networks can discover appropriate …
neural circuits. Understanding how neural networks can discover appropriate …
Minimal models and canonical neural computations: The distinctness of computational explanation in neuroscience
M Chirimuuta - Synthese, 2014 - Springer
In a recent paper, Kaplan (Synthese 183: 339–373, 2011) takes up the task of extending
Craver's (Explaining the brain, 2007) mechanistic account of explanation in neuroscience to …
Craver's (Explaining the brain, 2007) mechanistic account of explanation in neuroscience to …