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The time it takes to elicit a visual cortical response plus the time to elicit a saccade from cortex (FEF) is longer than the time it takes for humans to orient towards faces.

Nakano et al. take this as further evidence for a sub-cortical (retinotectal) route of face detection.

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

Humans' (and other mammals') brains are devoted to a large part to visual processing.

Vision is an important if not the most important source of sensory input for humans' (and other mammals').

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.

Congenital blindness leads to tactile and auditory stimuli activating early dorsal cortical visual areas.

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

LGN and V4 have distinct layers for each eye.

Most neurons in the visual cortex (except v4) are binocular.

Usually, input from one eye is dominant, however.

The distribution of monocular dominance in visual cortex neurons is drastically affected by monocular stimulus deprivation during early development.

A possible ascending pathway from SC to visual cortex through the pulvinar nuclei (pulvinar) may be responsible for the effect of SC activity on visual processing in the cortex.

There may be an indirect ascending pathway from intermediate SC to the thalamic reticular nucleus.

Feature-based visual attention facilitates object detection across the visual field.

The effects of visual attention are more pronounced in later stages of visual processing (in the visual cortex).

Spatial attention does not seem to affect the selectivity of visual neurons—just the vigour of their response.

Spatial visual attention increases the activity of neurons in the visual cortex whose receptive fields overlap the attended region.

Feature-based visual attention increases the activity of neurons in the visual cortex which respond to the attended feature.

Spatial and feature-based visual attention are additive: together, they particularly enhance the activity of any neuron whose receptive field encompasses the attended region, contains a stimulus with the attended feature, and prefers that feature.

It has been found that stimulating supposed motor neurons in the SC facilitates visual processing in the part of visual cortex whose receptive field is the same as that of the SC stimulated neurons.

Feature-based visual attention facilitates neural responses across the visual field (in visual cortex).

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

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

Neurons at later stages in the hierarchy of visual processing extract very complex features (like faces).

Spatial attention raises baseline activity in neurons whose RF are where the attention is even without a visual stimulus (in visual cortex).

There are projections from visual cortex to SC.

There is a disynaptic connection from SC to the dorsal stream visual cortex, probably through the pulvinar.

Weber presents a Helmholtz machine extended by adaptive lateral connections between units and a topological interpretation of the network. A Gaussian prior over the population response (a prior favoring co-activation of close-by units) and training with natural images lead to spatial self-organization and feature-selectivity similar to that in cells in early visual cortex.

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.

It has been found that stimulating supposed motor neurons in the SC enhances responses of v4 neurons with the same receptive field as the SC neurons.

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

In the Sprague effect, removing (or deactivating) one visual cortex eliminates visually induced orienting behavior to stimuli in the contralateral hemifield.

Lesioning (or deactivating) the contralateral SC restores the orienting behavior.

The heminanopia that follows unilateral removal of the cortex that mediates visual behavior cannot be explained simply in classical terms of interruption of the visual behavior cannot be explained simply in classical terms of interruption of the visual radiations that serve cortical function.
Explanation fo the deficit requires a broader point of view, namely, that visual attention and perception are mediated at both forebrain and midbrain levels, which interact in their control of visually guided behavior.''

(Sprague, 1966)

There is reason to believe that color information reaches the SC via cortical routes.

Disparity-selective cells in visual cortical neurons have preferred disparities of only a few degrees whereas disparity in natural environments ranges over tens of degrees.

The possible explanation offered by Zhao et al. assumes that animals actively keep disparity within a small range, during development, and therefore only selectivity for small disparity develops.

Zhao et al. present a model of joint development of disparity selectivity and vergence control.

Zhao et al.'s model develops both disparity selection and vergence control in an effort to minimize reconstruction error.

It uses a form of sparse-coding to learn to approximate its input and a variation of the actor-critic learning algorithm called natural actor critic reinforcement learning algorithm (NACREL).

The teaching signal to the NACREL algorithm is the reconstruction error of the model after the action produced by it.

When asked to ignore stimuli in the visual modality and attend to the auditory modality, increased activity in the auditory temporal cortex and decreased activity in the visual occipital cortex can be observed (and vice versa).

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.

Visual cortex is not fully developed at birth in primates.

The fact that visual cortex is not fully developed at birth, but newborn children prefer face-like visual stimuli to other visual stimuli could be explained by the presence of a subcortical face-detector.

The fact that visual cortex is not fully developed at birth, but newborn children prefer face-like visual stimuli to other visual stimuli could be explained by the presence of a subcortical face-detector.

Looking behavior in newborns may be dominated by non-cortical processes.

Different parts of the visual field feed into the cortical and subcortical visual pathways more or less strongly in humans.

The nasal part of the visual field feeds more into the cortical pathway while the peripheral part feeds more into the sub-cortical pathway.

In one experiment, newborns reacted to faces only if they were (exclusively) visible in their peripheral visual field, supporting the theory that the sub-cortical pathway of visual processing plays a major role in orienting towards faces in newborns.

It makes sense that sub-cortical visual processing uses peripheral information more than cortical processing:

• sub-cortical processing is concerned with latent monitoring of the environment for potential dangers (or conspecifiics)
• sub-cortical processing is concerned with watching the environment and guiding attention in cortical processing.

The visual cortex is hierarchically organized.

There seems to be an ascending pathway from superficial SC to the medial temporal area (MT) through the pulvinar nuclei (inferior pulvinar).

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.

The part of the visual cortex dedicated to processing signals from the fovea is much greater than that dealing with peripheral signals.

Cells in inferotemporal cortex are highly selective to the point where they approach being grandmother cells.

There are cells in inferotemporal cortex which respond to (specific views on / specific parts of) faces, hands, walking humans and others.

Marr speaks of vision as one process, whose task is to generate `a useful description of the world'. However, there is more than one actual goal of vision (though they share similar properties) and thus there are different representations and algorithms being used in the different parts of the brain concerned with these goals.