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In addition to its role in spatial processing, the retinotopic map in V1 is intricately connected with other visual areas, forming a network that contributes to the integration of various visual features and the construction of a coherent visual percept. This dynamic mapping mechanism is fundamental to our ability to navigate and interpret the visual world effectively.<ref name= kepler1604 >Johannes Kepler (1604) Paralipomena to Witelo whereby The Optical Part of Astronomy is Treated (Ad Vitellionem Paralipomena, quibus astronomiae pars optica traditvr, 1604), as cited by A.Mark Smith (2015) From Sight to Light. Kepler modeled the eye as a water-filled glass sphere, and discovered that each point of the scene taken in by the eye projects onto a point on the back of the eye (the retina).</ref> The correspondence between a given ___location in V1 and in the subjective visual field is very precise: even the [[Blind spot (vision)|blind spots]] of the retina are mapped into V1. In terms of evolution, this correspondence is very basic and found in most animals that possess a V1. In humans and other animals with a [[Fovea centralis|fovea]] ([[Cone cell|cones]] in the retina), a large portion of V1 is mapped to the small, central portion of visual field, a phenomenon known as [[cortical magnification]].<ref>{{cite thesis | vauthors = Barghout L |title=On the Differences Between Peripheral and Foveal Pattern Masking |date=1999 |type=Masters |publisher=University of California, Berkeley|___location=Berkeley, California}}</ref> Perhaps for the purpose of accurate spatial encoding, neurons in V1 have the smallest [[receptive field]] size (that is, the highest resolution) of any visual cortex microscopic regions.
The tuning properties of V1 neurons (what the neurons respond to) differ greatly over time. Early in time (40 ms and further) individual V1 neurons have strong tuning to a small set of stimuli. That is, the neuronal responses can discriminate small changes in visual [[Orientation (mental)|orientations]], [[spatial frequencies]] and [[color]]s (as in the optical system of a [[camera obscura]], but projected onto [[retina]]l cells of the eye, which are clustered in density and fineness).<ref name= kepler1604 /> Each V1 neuron propagates a signal from a retinal cell, in continuation. Furthermore, individual V1 neurons in humans and other animals with [[binocular vision]] have ocular dominance, namely tuning to one of the two eyes. In V1, and primary sensory cortex in general, neurons with similar tuning properties tend to cluster together as [[cortical column]]s. [[David Hubel]] and [[Torsten Wiesel]] proposed the classic ice-cube organization model of cortical columns for two tuning properties: [[ocular dominance columns|ocular dominance]] and orientation. However, this model cannot accommodate the color, spatial frequency and many other features to which neurons are tuned {{Citation needed|date=November 2011}}. The exact organization of all these cortical columns within V1 remains a hot topic of current research.
The receptive fields of V1 neurons<ref>{{cite journal |vauthors=DeAngelis GC, Ohzawa I, Freeman RD |date=October 1995 |title=Receptive-field dynamics in the central visual pathways |journal=Trends in Neurosciences |volume=18 |issue=10 |pages=451–458 |doi=10.1016/0166-2236(95)94496-r |pmid=8545912 |s2cid=12827601}}</ref><ref>{{Cite book |title=The Visual Neurosciences, 2-vol. Set |vauthors=DeAngelis GC, Anzai A |date=2003-11-21 |publisher=The MIT Press |isbn=978-0-262-27012-0 |veditors=Chalupa LM, Werner JS |volume=1 |___location=Cambridge |pages=704–719 |language=en |chapter=A Modern View of the Classical Receptive Field: Linear and Nonlinear Spatiotemporal Processing by V1 Neurons |doi=10.7551/mitpress/7131.003.0052 |chapter-url=https://direct.mit.edu/books/book/5395/chapter/3948206/A-Modern-View-ofthe-Classical-Receptive-Field}}</ref> resemble Gabor functions, so the operation of the visual cortex has been compared to the [[Gabor transform]].{{Citation needed|date=May 2023}}
Later in time (after 100 ms), neurons in V1 are also sensitive to the more global organisation of the scene<ref>{{Cite journal |last=Lamme |first=Victor A.F. |last2=Roelfsema |first2=Pieter R. |date=2000-11 |title=The distinct modes of vision offered by feedforward and recurrent processing |url=https://linkinghub.elsevier.com/retrieve/pii/S016622360001657X |journal=Trends in Neurosciences |volume=23 |issue=11 |pages=571–579 |doi=10.1016/s0166-2236(00)01657-x |issn=0166-2236}}</ref>. These response properties probably stem from recurrent [[feedback]] processing (the influence of higher-tier cortical areas on lower-tier cortical areas) and lateral connections from [[Pyramidal cell|pyramidal neurons]].<ref name="Hupé_1998">{{cite journal | vauthors = Hupé JM, James AC, Payne BR, Lomber SG, Girard P, Bullier J | title = Cortical feedback improves discrimination between figure and background by V1, V2 and V3 neurons | journal = Nature | volume = 394 | issue = 6695 | pages = 784–7 | date = August 1998 | pmid = 9723617 | doi = 10.1038/29537 | bibcode = 1998Natur.394..784H }}</ref> While feedforward connections are mainly driving, feedback connections are mostly modulatory in their effects.<ref name="Angelucci_2003">{{cite journal | vauthors = Angelucci A, Bullier J | title = Reaching beyond the classical receptive field of V1 neurons: horizontal or feedback axons? | journal = Journal of Physiology, Paris | volume = 97 | issue = 2–3 | pages = 141–54 | date = 2003 | pmid = 14766139 | doi = 10.1016/j.jphysparis.2003.09.001 }}</ref><ref name="Bullier_2001">{{cite book | vauthors = Bullier J, Hupé JM, James AC, Girard P | title = The role of feedback connections in shaping the responses of visual cortical neurons | chapter = Chapter 13 the role of feedback connections in shaping the responses of visual cortical neurons | series = Progress in Brain Research | volume = 134 | pages = 193–204 | date = 2001 | pmid = 11702544 | doi = 10.1016/s0079-6123(01)34014-1 | isbn = 978-0-444-50586-6 }}</ref> Evidence shows that feedback originating in higher-level areas such as V4, IT, or MT, with bigger and more complex receptive fields, can modify and shape V1 responses, accounting for contextual or extra-classical receptive field effects.<ref name="Murray_2004">{{cite journal | vauthors = Murray SO, Schrater P, Kersten D | title = Perceptual grouping and the interactions between visual cortical areas | journal = Neural Networks | volume = 17 | issue = 5–6 | pages = 695–705 | date = 2004 | pmid = 15288893 | doi = 10.1016/j.neunet.2004.03.010 }}</ref><ref name="Huang_2007">{{cite journal | vauthors = Huang JY, Wang C, Dreher B | title = The effects of reversible inactivation of postero-temporal visual cortex on neuronal activities in cat's area 17 | journal = Brain Research | volume = 1138 | issue = | pages = 111–28 | date = March 2007 | pmid = 17276420 | doi = 10.1016/j.brainres.2006.12.081 }}</ref><ref name="Williams_2008">{{cite journal | vauthors = Williams MA, Baker CI, Op de Beeck HP, Shim WM, Dang S, Triantafyllou C, Kanwisher N | title = Feedback of visual object information to foveal retinotopic cortex | journal = Nature Neuroscience | volume = 11 | issue = 12 | pages = 1439–45 | date = December 2008 | pmid = 18978780 | pmc = 2789292 | doi = 10.1038/nn.2218 }}</ref>
The visual information relayed by V1 is sometimes described as [[edge detection]].<ref>{{cite journal | vauthors = Kesserwani H | title = The Biophysics of Visual Edge Detection: A Review of Basic Principles | journal = Cureus | volume = 12 | issue = 10 | pages = e11218 | date = October 2020 | pmid = 33269147 | pmc = 7706146 | doi = 10.7759/cureus.11218 | doi-access = free }}</ref> As an example, for an image comprising half side black and half side white, the dividing line between black and white has strongest local contrast (that is, edge detection) and is encoded, while few neurons code the brightness information (black or white per se). As information is further relayed to subsequent visual areas, it is coded as increasingly non-local frequency/phase signals. Note that, at these early stages of cortical visual processing, spatial ___location of visual information is well preserved amid the local contrast encoding (edge detection).
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