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Patients with lesions in V1 or striate were found to still be able to discriminate gender and expression of faces.

Although no (actually: hardly any) projections from multisensory or non-visual areas to V1 have been found, auditory input seems to influence neural activity in V1.

LIP projects to V1.

There are significant projections from auditory cortex as well as from polysensory areas in the temporal lobe to parts of V1 where receptive fields are peripheral.

V1 is influenced by auditory stimuli (in different ways).

Miikulainen et al. use their SOM-based algorithms to model the visual cortex.

Miikulainen et al. use a hierarchical version of their SOM-based algorithm to model natural development of visual capabilities.

Response properties of superficial SC neurons is different from those found in mouse V1 neurons.

Lee and Mumford interpret the visual pathway in terms of Bayesian belief propagation: each stage in the processing uses output from the one further up as contextual information and output from the one further down as evidence to update its belief and corresponding output.

Each layer thus calculates probabilities of features of the visual display given noisy and ambiguous input.

Butts and Goldman use Gaussian functions to model the receptive fields of V1 neurons.

Weber presents a continuous Hopfield-like RNN as a model of complex cells in V1. This model receives input from a sparse coding generative Helmholtz machine, described earlier as a model of simple cells in V1, and which produces topography by coactivating neighbors in its "sleep phase". The complex cell model with its horizontal connections is trained to predict the simple cells' activations, while input images undergo small random shifts. The trained network features realistic centre-surround weight profiles (in position- and orientation-space) and sharpened orientation tuning curves.

The number of neurons in the lower stages of the visual processing hierarchy (V1) is much lower than in the higher stages (IT).

Divisive normalization models describe neural responses well in cases of

  • olfactory perception in drosophila,
  • visual processing in retina and V1,
  • possibly in other cortical areas,
  • modulation of responses through attention in visual cortex.

Divisive normalization is probably implemented through (GABA-ergic) inhibition in some cases (fruitfly olfactory system). In others (V1), it seems to be implemented by different means.

Certain neurons in V1 are sensitive to simple features:

  • edges,
  • gratings,
  • line endings,
  • motion,
  • color,
  • disparity

Simple cells are sensitive to the phase of gratings, whereas complex cells are not and have larger receptive fields.

Some cells in V1 are sensitive to binocular disparity.

Pulvinar neurons seem to receive input and project to different layers in visual cortex:

They receive input from layer 5 and project to layers one and three.

Connectivity between pulvinar and MT is similar to connectivity between pulvinar and visual cortex.

LGN receives more feedback projections from V1 than forward connections from the retina.