Editing Visual system (section)

===Visual association cortex===
{{Main|Two-streams hypothesis}}
As visual information passes forward through the visual hierarchy, the complexity of the neural representations increases. Whereas a V1 neuron may respond selectively to a line segment of a particular orientation in a particular [[Retinotopy|retinotopic]] location, neurons in the lateral occipital complex respond selectively to a complete object (e.g., a figure drawing), and neurons in the visual association cortex may respond selectively to human faces, or to a particular object.

Along with this increasing complexity of neural representation may come a level of specialization of processing into two distinct pathways: the [[dorsal stream]] and the [[ventral stream]] (the [[Two Streams hypothesis]],<ref name=UngerleiderMishkin>{{Cite journal |journal=Behav. Brain Res. |year=1982 |volume=6 |issue=1 |pages=57–77 |title=Contribution of striate inputs to the visuospatial functions of parieto-preoccipital cortex in monkeys |vauthors=Mishkin M, Ungerleider LG |pmid=7126325 |doi=10.1016/0166-4328(82)90081-X |s2cid=33359587 }}</ref> first proposed by Ungerleider and Mishkin in 1982). The dorsal stream, commonly referred to as the "where" stream, is involved in spatial attention (covert and overt), and communicates with regions that control eye movements and hand movements.  More recently, this area has been called the "how" stream to emphasize its role in guiding behaviors to spatial locations. The ventral stream, commonly referred to as the "what" stream, is involved in the recognition, identification and categorization of visual stimuli.

[[File:Gray726 intraparietal sulcus.svg|thumb|right| [[Intraparietal sulcus]] (red)]]

However, there is still much debate about the degree of specialization within these two pathways, since they are in fact heavily interconnected.<ref name=Farivar>{{Cite journal|journal=Brain Res. Rev.|year=2009|title=Dorsal-ventral integration in object recognition|author=Farivar R.|doi=10.1016/j.brainresrev.2009.05.006|pmid=19481571|volume=61|issue=2|pages=144–53|s2cid=6817815}}</ref>

[[Horace Barlow]] proposed the ''[[efficient coding hypothesis]]'' in 1961 as a theoretical model of [[sensory neuroscience|sensory coding]] in the [[brain]].<ref>Barlow, H. (1961) "Possible principles underlying the transformation of sensory messages" in ''Sensory Communication'', MIT Press</ref> Limitations in the applicability of this theory in the [http://www.scholarpedia.org/article/Area_V1 primary visual cortex (V1)] motivated the [[V1 Saliency Hypothesis]] that V1 creates a bottom-up saliency map to guide attention exogenously.<ref name=":0" />  With attentional selection as a center stage, vision is seen as composed of encoding, selection, and decoding stages.<ref name=":1">{{Cite book|last=Zhaoping|first=Li|title=Understanding vision: theory, models, and data|publisher=Oxford University Press|year=2014|isbn=978-0-19-882936-2|location=United Kingdom}}</ref>

The [[default mode network]] is a network of brain regions that are active when an individual is awake and at rest. The visual system's default mode can be monitored during [[resting state fMRI]]:
Fox, et al. (2005) found that "[http://www.pnas.org/content/102/27/9673.full the human brain is intrinsically organized into dynamic, anticorrelated functional networks"],<ref>{{cite journal | last1 = Fox | first1 = Michael D. | display-authors = etal | year = 2005| title =  From The Cover: The human brain is intrinsically organized into dynamic, anticorrelated functional networks| journal = PNAS | volume = 102 | issue = 27| pages = 9673–9678 | doi = 10.1073/pnas.0504136102 | pmid = 15976020 | pmc = 1157105 | bibcode = 2005PNAS..102.9673F | doi-access = free }}</ref> in which the visual system switches from resting state to attention.

In the [[parietal lobe]], the [[lateral intraparietal cortex|lateral]] and ventral intraparietal cortex are involved in visual attention and saccadic eye movements. These regions are in the [[intraparietal sulcus]] (marked in red in the adjacent image).