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Binocular neurons
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<h2 id="history">History</h2> <p>In the 19th century <a href="/facts/Charles_Wheatstone/935jnRhj">Charles Wheatstone</a> determined that <a href="/facts/Retinal_disparity/AL5Ydh0m">retinal disparity</a> was a large contributor to <a href="/facts/Depth_perception/R6FK2z6o">depth perception</a>.<a class="footnote-ref" id="fnref:3" href="#fn:3"><sup>3</sup></a> Using a <a href="/facts/Stereoscope/YLMTVd8X">stereoscope</a>, he showed that horizontal disparity is used by the brain to calculate the relative depths of different objects in 3-dimensional space in reference to a fixed point. This process is called <a href="/facts/Stereopsis/AL5Ydh0m">stereopsis</a>. Two main classes of cells in <a href="/facts/Visual_cortex/qmF8F5Sb">visual cortex</a> were identified by <a href="/facts/David_H._Hubel/L565w1o9">David H. Hubel</a> and <a href="/facts/Torsten_Wiesel/DGxnrzSe">Torsten Wiesel</a> in 1962 through their investigation of the cat's <a href="/facts/Primary_visual_cortex/qmF8F5Sb">primary visual cortex</a>.<a class="footnote-ref" id="fnref:4" href="#fn:4"><sup>4</sup></a> These classes were called <a href="/facts/Simple_cell/WVXwG5yq">simple</a> and <a href="/facts/Complex_cell/5pq8kEcl">complex cells</a>, which differ in how their <a href="/facts/Receptive_field/2LIVVKfe">receptive fields</a> respond to light and dark <a href="/facts/Stimulus_(physiology)/aBcpBfYQ">stimuli</a>. <a href="/facts/B%C3%A9la_Julesz/TlSXqGbW">Béla Julesz</a> in 1971 used <a href="/facts/Random_dot_stereogram/RqYNr3H6">random dot stereograms</a> to find that monocular depth cues, such as shading, are not required for stereoscopic vision.<a class="footnote-ref" id="fnref:5" href="#fn:5"><sup>5</sup></a> <a href="/facts/Binocular_disparity/Fj2I1Soj">Disparity</a> selective cells were first recorded in the <a href="/facts/Visual_cortex/qmF8F5Sb">striate cortex (V1)</a> of the cat by Peter Orlebar Bishop and <a href="/facts/John_Douglas_Pettigrew/PYz7cQbL">John Douglas Pettigrew</a> in the late 1960s,<a class="footnote-ref" id="fnref:6" href="#fn:6"><sup>6</sup></a> however this discovery was unexpected and was not published until 1986.<a class="footnote-ref" id="fnref:7" href="#fn:7"><sup>7</sup></a> These <a href="/facts/Binocular_disparity/Fj2I1Soj">disparity</a> selective cells, also known as binocular neurons, were again found in the awake behaving macaque monkey in 1985.<a class="footnote-ref" id="fnref:8" href="#fn:8"><sup>8</sup></a> Additionally, population responses of binocular neurons have been found in human <a href="/facts/Ventral/IpJ1fq2f">ventral</a> and <a href="/facts/Dorsal_(anatomy)/IpJ1fq2f">dorsal</a> <a href="/facts/Visual_cortex/qmF8F5Sb">pathways</a> using <a href="/facts/Functional_magnetic_resonance_imaging/GIayRTAL">fMRI</a>.<a class="footnote-ref" id="fnref:9" href="#fn:9"><sup>9</sup></a> </p> <h2 id="neuroanatomy">Neuroanatomy</h2> <p>Both the <a href="/facts/Dorsal_(anatomy)/IpJ1fq2f">dorsal</a> and <a href="/facts/Ventral/IpJ1fq2f">ventral</a> <a href="/facts/Visual_system/QVcuA27K">pathways</a> contribute to the <a href="/facts/Depth_perception/R6FK2z6o">perception of depth</a>.<a class="footnote-ref" id="fnref:10" href="#fn:10"><sup>10</sup></a> Binocular neurons, in the sense of being activated by stimuli in either eye, are first found in the <a href="/facts/Visual_cortex/qmF8F5Sb">visual cortex</a> in <a href="/facts/Visual_cortex/qmF8F5Sb">layer 4</a>.<a class="footnote-ref" id="fnref:11" href="#fn:11"><sup>11</sup></a><a class="footnote-ref" id="fnref:12" href="#fn:12"><sup>12</sup></a> Binocular neurons appear in the <a href="/facts/Visual_cortex/qmF8F5Sb">striate cortex (V1)</a>, the <a href="/facts/Visual_cortex/qmF8F5Sb">prestriate cortex (V2)</a>, the <a href="/facts/Visual_cortex/qmF8F5Sb">ventral extrastriate area (V4)</a>, the <a href="/facts/Visual_cortex/qmF8F5Sb">dorsal extrastriate area (V5/MT)</a>, <a href="/facts/Temporal_lobe/U2wLVCrg">medial superior temporal area</a>, <a href="/facts/Parietal_lobe/T74NKNTN">caudal intraparietal area</a>, and a collection of areas in the anterior inferior <a href="/facts/Temporal_cortex/U2wLVCrg">temporal cortex</a>.<a class="footnote-ref" id="fnref:13" href="#fn:13"><sup>13</sup></a> Neurons in the <a href="/facts/Visual_cortex/qmF8F5Sb">prestriate cortex (V2)</a> are more sensitive to different disparities than those in the <a href="/facts/Visual_cortex/qmF8F5Sb">striate cortex (V1)</a>.<a class="footnote-ref" id="fnref:14" href="#fn:14"><sup>14</sup></a> Binocular neurons in the <a href="/facts/Visual_cortex/qmF8F5Sb">striate cortex (V1)</a> are only sensitive to absolute <a href="/facts/Binocular_disparity/Fj2I1Soj">disparity</a>, where in other visual cortical areas they are sensitive to relative <a href="/facts/Binocular_disparity/Fj2I1Soj">disparity</a>.<a class="footnote-ref" id="fnref:15" href="#fn:15"><sup>15</sup></a><a class="footnote-ref" id="fnref:16" href="#fn:16"><sup>16</sup></a> </p><p>In the <a href="/facts/Visual_cortex/qmF8F5Sb">prestriate cortex (V2)</a> and <a href="/facts/Visual_cortex/qmF8F5Sb">ventral extrastriate area (V4)</a>, binocular neurons respond most readily to a centre-surround <a href="/facts/Stimulus_(physiology)/aBcpBfYQ">stimulus</a>.<a class="footnote-ref" id="fnref:17" href="#fn:17"><sup>17</sup></a> A centre-surround <a href="/facts/Stimulus_(physiology)/aBcpBfYQ">stimulus</a> consists of a fixed object with another object rotating in a circle around the fixed object. Areas in the anterior inferior temporal cortex respond to surface curvature.<a class="footnote-ref" id="fnref:18" href="#fn:18"><sup>18</sup></a> Binocular neurons in both the <a href="/facts/Parietal_lobe/T74NKNTN">caudal intraparietal area</a> and the <a href="/facts/Visual_cortex/qmF8F5Sb">dorsal extrastriate area (V5/MT)</a> respond to surface slants.<a class="footnote-ref" id="fnref:19" href="#fn:19"><sup>19</sup></a> Binocular neurons in both the <a href="/facts/Temporal_lobe/U2wLVCrg">medial superior temporal area</a> and <a href="/facts/Visual_cortex/qmF8F5Sb">dorsal extrastriate area (V5/MT)</a> respond to surface depth sparation.<a class="footnote-ref" id="fnref:20" href="#fn:20"><sup>20</sup></a> On one hand, the <a href="/facts/Negative_relationship/kTjs0r6G">anticorrelated</a> response of the binocular neurons in the <a href="/facts/Visual_cortex/qmF8F5Sb">striate cortex (V1)</a>, the <a href="/facts/Visual_cortex/qmF8F5Sb">prestriate cortex (V2)</a>, <a href="/facts/Visual_cortex/qmF8F5Sb">dorsal extrastriate area (V5/MT)</a>, and <a href="/facts/Temporal_lobe/U2wLVCrg">medial superior temporal area</a>, all show similar responses.<a class="footnote-ref" id="fnref:21" href="#fn:21"><sup>21</sup></a> On the other hand, binocular neurons in the <a href="/facts/Visual_cortex/qmF8F5Sb">ventral extrastriate area (V4)</a> show weaker <a href="/facts/Negative_relationship/kTjs0r6G">anticorrelated</a> responses in comparison to the other areas. Finally, areas in the anterior inferior temporal cortex do not show any <a href="/facts/Negative_relationship/kTjs0r6G">anticorrelated</a> response.<a class="footnote-ref" id="fnref:22" href="#fn:22"><sup>22</sup></a> </p> <h2 id="function">Function</h2> <p>Binocular neurons create <a href="/facts/Depth_perception/R6FK2z6o">depth perception</a> through computation of <a href="/facts/Binocular_disparity/Fj2I1Soj">relative</a> and absolute disparity created by differences in the <a href="/facts/Interpupillary_distance/T7KGYqdD">distance between the left and right eyes</a>. Binocular neurons in the <a href="/facts/Dorsal_(anatomy)/IpJ1fq2f">dorsal</a> and <a href="/facts/Ventral/IpJ1fq2f">ventral</a> <a href="/facts/Visual_cortex/qmF8F5Sb">pathways</a> combine to create <a href="/facts/Depth_perception/R6FK2z6o">depth perception</a>, however, the two pathways perform differ in the type of stereo computation they perform.<a class="footnote-ref" id="fnref:23" href="#fn:23"><sup>23</sup></a> The <a href="/facts/Dorsal_(anatomy)/IpJ1fq2f">dorsal</a> <a href="/facts/Visual_cortex/qmF8F5Sb">pathway</a> generally performs a <a href="/facts/Cross-correlation/Fs1hY3br">cross-correlation</a> based upon the region of the different retinal images, while the <a href="/facts/Ventral/IpJ1fq2f">ventral</a> <a href="/facts/Visual_cortex/qmF8F5Sb">pathway</a> fixes the multiple matching problem. In combination, the two pathways allow for judgments about <a href="/facts/Depth_perception/R6FK2z6o">stereo depth</a>.<a class="footnote-ref" id="fnref:24" href="#fn:24"><sup>24</sup></a> In general the <a href="/facts/Ventral/IpJ1fq2f">ventral</a> <a href="/facts/Visual_cortex/qmF8F5Sb">pathway</a> is more sensitive to <a href="/facts/Binocular_disparity/Fj2I1Soj">relative disparity</a>. The cells in this pathway are sensitive to the relative depth between different objects or features close to one another in the physical world which is called fine <a href="/facts/Stereopsis/AL5Ydh0m">stereopsis</a>. The <a href="/facts/Dorsal_(anatomy)/IpJ1fq2f">dorsal</a> <a href="/facts/Visual_cortex/qmF8F5Sb">pathway</a> contains <a href="/facts/Cell_(biology)/bLM9UQvy">cells</a> that are more sensitive to coarse <a href="/facts/Stereopsis/AL5Ydh0m">stereopsis</a>. This allows for simple computations of depth based upon the different images in both the left and right eyes, but this computation only occurs when the surfaces analyzed contain a <a href="/facts/Gradient/TsR7uukj">gradient</a> of different depths.<a class="footnote-ref" id="fnref:25" href="#fn:25"><sup>25</sup></a> </p> <h3>Receptive Fields</h3> <p><a href="/facts/Simple_cell/WVXwG5yq">Simple cells</a> have separate regions in their <a href="/facts/Receptive_field/2LIVVKfe">receptive field</a> that respond to light and dark stimuli. Unlike <a href="/facts/Simple_cell/WVXwG5yq">simple cells</a>, the receptive field of <a href="/facts/Complex_cell/5pq8kEcl">complex cells</a> have a mix of regions that respond to light and dark <a href="/facts/Stimulus_(physiology)/aBcpBfYQ">stimuli</a>. The prevailing theory of how <a href="/facts/Simple_cell/WVXwG5yq">simple</a> and <a href="/facts/Complex_cell/5pq8kEcl">complex cells</a> interact is that cells in the <a href="/facts/Lateral_geniculate_nucleus/DcRMnj1J">lateral geniculate nucleus</a> stimulate simple cells, and simple cells in turn stimulate complex cells where then a combination of complex cells create <a href="/facts/Depth_perception/R6FK2z6o">depth perception</a>.<a class="footnote-ref" id="fnref:26" href="#fn:26"><sup>26</sup></a><a class="footnote-ref" id="fnref:27" href="#fn:27"><sup>27</sup></a><a class="footnote-ref" id="fnref:28" href="#fn:28"><sup>28</sup></a> Three different <a href="/facts/Cell_type/1boyDWXb">cell types</a> exist: far cells, near cells, and tuned zero cells. Far cells respond to <a href="/facts/Binocular_disparity/Fj2I1Soj">disparities</a> in planes further away from the plane of <a href="/facts/Fixation_(visual)/nnFUFcd9">fixation</a>, near cells are stimulated by <a href="/facts/Binocular_disparity/Fj2I1Soj">disparities</a> in planes closer than the plane of <a href="/facts/Fixation_(visual)/nnFUFcd9">fixation</a>, and tuned zero cells respond to <a href="/facts/Binocular_disparity/Fj2I1Soj">disparities</a> on the plane of <a href="/facts/Fixation_(visual)/nnFUFcd9">fixation</a>.<a class="footnote-ref" id="fnref:29" href="#fn:29"><sup>29</sup></a><a class="footnote-ref" id="fnref:30" href="#fn:30"><sup>30</sup></a> The <a href="/facts/Plane_(geometry)/tAUtRFcn">plane</a> of <a href="/facts/Fixation_(visual)/nnFUFcd9">fixation</a> is the plane in 3-dimensional space on which the two eyes are focused and is <a href="/facts/Parallel_(geometry)/16r5yq7D">parallel</a> to the <a href="/facts/Coronal_plane/JeB18qFE">coronal plane</a> of the head. </p> <h3>Correspondence Problem</h3> <p>The <a href="/facts/Correspondence_problem/YBe0HbVX">correspondence problem</a> questions how the visual system determines what features or objects contained within the two retinal images come from the same real world objects.<a class="footnote-ref" id="fnref:31" href="#fn:31"><sup>31</sup></a> For example, when looking at a picture of a tree, the visual system must determine that the two retinal images of the tree come from the same actual object in space. If the <a href="/facts/Correspondence_problem/YBe0HbVX">correspondence problem</a> is not overcome in this case, the <a href="/facts/Organism/j8JkL09u">organism</a> would perceive two trees when there is only one. In order to solve this problem, the visual system must have a way of avoiding false-matches of the two retinal images.<a class="footnote-ref" id="fnref:32" href="#fn:32"><sup>32</sup></a> A possible way the <a href="/facts/Visual_system/QVcuA27K">visual system</a> avoids false-matches is that binocular <a href="/facts/Complex_cell/5pq8kEcl">complex cells</a> have cross-matching patches between their <a href="/facts/Receptive_field/2LIVVKfe">receptive fields</a>, meaning that multiple <a href="/facts/Complex_cell/5pq8kEcl">complex cells</a> would be stimulated by same feature.<a class="footnote-ref" id="fnref:33" href="#fn:33"><sup>33</sup></a><a class="footnote-ref" id="fnref:34" href="#fn:34"><sup>34</sup></a> Simulation of real binocular <a href="/facts/Complex_cell/5pq8kEcl">complex cells</a> involves a hierarchical squared summation of multiple simple cell receptive fields where the simple cells sum the contribution from both the right and left retinal images.<a class="footnote-ref" id="fnref:35" href="#fn:35"><sup>35</sup></a> </p> <h3>Energy Models</h3> <p>An energy model, a kind of <a href="/facts/Stimulus-response_model/uH9bA3zR">stimulus-response model</a>, of binocular neurons allows for investigation behind the <a href="/facts/Computational_neuroscience/eclSYyJK">computational function</a> these disparity tuned cells play in the creation of depth perception.<a class="footnote-ref" id="fnref:36" href="#fn:36"><sup>36</sup></a><a class="footnote-ref" id="fnref:37" href="#fn:37"><sup>37</sup></a><a class="footnote-ref" id="fnref:38" href="#fn:38"><sup>38</sup></a><a class="footnote-ref" id="fnref:39" href="#fn:39"><sup>39</sup></a> Energy models of binocular neurons involve the combination of <a href="/facts/Monocular/DglqwGdb">monocular</a> <a href="/facts/Receptive_field/2LIVVKfe">receptive fields</a> that are either shifted in <a href="/facts/Position_(vector)/Tpk5d9f2">position</a> or <a href="/facts/Phase_(waves)/cpGtuVll">phase</a>.<a class="footnote-ref" id="fnref:40" href="#fn:40"><sup>40</sup></a><a class="footnote-ref" id="fnref:41" href="#fn:41"><sup>41</sup></a> These shifts in either <a href="/facts/Position_(vector)/Tpk5d9f2">position</a> or <a href="/facts/Phase_(waves)/cpGtuVll">phase</a> allow for the simulated binocular neurons to be sensitive to <a href="/facts/Binocular_disparity/Fj2I1Soj">disparity</a>. The relative contributions of <a href="/facts/Phase_(waves)/cpGtuVll">phase</a> and <a href="/facts/Position_(vector)/Tpk5d9f2">position</a> shifts in <a href="/facts/Simple_cell/WVXwG5yq">simple</a> and <a href="/facts/Complex_cell/5pq8kEcl">complex cells</a> combine together in order to create <a href="/facts/Depth_perception/R6FK2z6o">depth perception</a> of an object in 3-dimensional space.<a class="footnote-ref" id="fnref:42" href="#fn:42"><sup>42</sup></a><a class="footnote-ref" id="fnref:43" href="#fn:43"><sup>43</sup></a> Binocular <a href="/facts/Simple_cell/WVXwG5yq">simple cells</a> are modeled as <a href="/facts/Artificial_neuron/TSH6nsgg">linear neurons</a>. Due to the <a href="/facts/Linear/fChtg3KC">linear</a> nature of these <a href="/facts/Artificial_neuron/TSH6nsgg">neurons</a>, positive and negative values are encoded by two <a href="/facts/Artificial_neuron/TSH6nsgg">neurons</a> where one neuron encodes the positive part and the other the negative part. This results in the neurons being complements of each other where the <a href="/facts/Excitatory_postsynaptic_potential/fh6J3sUm">excitatory</a> region of one binocular <a href="/facts/Simple_cell/WVXwG5yq">simple cell</a> overlaps with the <a href="/facts/Inhibitory_postsynaptic_potential/Jfm13Wkn">inhibitory</a> region of another.<a class="footnote-ref" id="fnref:44" href="#fn:44"><sup>44</sup></a><a class="footnote-ref" id="fnref:45" href="#fn:45"><sup>45</sup></a> Each <a href="/facts/Artificial_neuron/TSH6nsgg">neuron's</a> response is limited such that only one may have a non-zero response for any time. This kind of limitation is called <a href="/facts/Rectifier/me8XDxND">halfwave-rectifing</a>. Binocular <a href="/facts/Complex_cell/5pq8kEcl">complex cells</a> are modeled as energy neurons since they do not have discrete on and off regions in their receptive fields.<a class="footnote-ref" id="fnref:46" href="#fn:46"><sup>46</sup></a><a class="footnote-ref" id="fnref:47" href="#fn:47"><sup>47</sup></a><a class="footnote-ref" id="fnref:48" href="#fn:48"><sup>48</sup></a><a class="footnote-ref" id="fnref:49" href="#fn:49"><sup>49</sup></a> Energy neurons sum the squared responses of two pairs of <a href="/facts/Artificial_neuron/TSH6nsgg">linear neurons</a> which must be 90 degrees out of <a href="/facts/Phase_(waves)/cpGtuVll">phase</a>.<a class="footnote-ref" id="fnref:50" href="#fn:50"><sup>50</sup></a> Alternatively, they can also be the sum the squared responses of four <a href="/facts/Rectifier/me8XDxND">halfwave-rectified</a> <a href="/facts/Artificial_neuron/TSH6nsgg">linear neurons</a>.<a class="footnote-ref" id="fnref:51" href="#fn:51"><sup>51</sup></a> </p> <h4>Stereo Model</h4> <p>The stereo model is an energy model that integrates both the position-shift model and the phase-difference model.<a class="footnote-ref" id="fnref:52" href="#fn:52"><sup>52</sup></a><a class="footnote-ref" id="fnref:53" href="#fn:53"><sup>53</sup></a> The position-shift model suggests that the receptive fields of left and right simple cells are identical in shape but are shifted <a href="/facts/Horizontal_plane/Hhsu9C8x">horizontally</a> relative to each other. This model was proposed by Bishop and <a href="/facts/John_Douglas_Pettigrew/PYz7cQbL">Pettigrew</a> in 1986.<a class="footnote-ref" id="fnref:54" href="#fn:54"><sup>54</sup></a> According to the phase-difference model the <a href="/facts/Excitatory_postsynaptic_potential/fh6J3sUm">excitatory</a> and <a href="/facts/Inhibitory_postsynaptic_potential/Jfm13Wkn">inhibitory</a> sub-regions of the left and right <a href="/facts/Receptive_field/2LIVVKfe">receptive fields</a> of <a href="/facts/Simple_cell/WVXwG5yq">simple cells</a> are shifted in <a href="/facts/Phase_(waves)/cpGtuVll">phase</a> such that their boundaries overlap. This model was developed by Ohzawa in 1990.<a class="footnote-ref" id="fnref:55" href="#fn:55"><sup>55</sup></a> The stereo model uses <a href="/facts/Fourier_optics/H4bVRGYx">Fourier phase</a> dependence of <a href="/facts/Simple_cell/WVXwG5yq">simple cell</a> responses, and it suggests that the use of the response of only <a href="/facts/Simple_cell/WVXwG5yq">simple cells</a> is not enough to accurately depict the <a href="/facts/Physiology/fh25y2pQ">physiological</a> <a href="/facts/Observation/NTodmzCo">observations</a> found in cat, monkey, and human <a href="/facts/Visual_system/QVcuA27K">visual pathways</a>.<a class="footnote-ref" id="fnref:56" href="#fn:56"><sup>56</sup></a> In order to make the model more representative of <a href="/facts/Physiology/fh25y2pQ">physiological</a> observations, the stereo model combines the responses of both <a href="/facts/Simple_cell/WVXwG5yq">simple</a> and <a href="/facts/Complex_cell/5pq8kEcl">complex cells</a> into a single <a href="/facts/Signal_(electrical_engineering)/41YqUJ8c">signal</a>.<a class="footnote-ref" id="fnref:57" href="#fn:57"><sup>57</sup></a> How this combination is done depends on the incoming <a href="/facts/Stimulus_(physiology)/aBcpBfYQ">stimulus</a>. As one example, the model uses independent Fourier phases for some types of <a href="/facts/Stimulus_(physiology)/aBcpBfYQ">stimuli</a>, and finds the preferred <a href="/facts/Binocular_disparity/Fj2I1Soj">disparity</a> of the complex cells equal to the left-right <a href="/facts/Receptive_field/2LIVVKfe">receptive field</a> shift.<a class="footnote-ref" id="fnref:58" href="#fn:58"><sup>58</sup></a><a class="footnote-ref" id="fnref:59" href="#fn:59"><sup>59</sup></a> For other <a href="/facts/Stimulus_(physiology)/aBcpBfYQ">stimuli</a>, the complex cell becomes less phase sensitive than the <a href="/facts/Simple_cell/WVXwG5yq">simple cells</a> alone, and when the complex cells larger <a href="/facts/Receptive_field/2LIVVKfe">receptive field</a> is included in the <a href="/facts/Mathematical_model/CGhyuxgz">model</a>, the phase sensitivity is returns to results similar to normal physiological observations.<a class="footnote-ref" id="fnref:60" href="#fn:60"><sup>60</sup></a> In order to include the larger <a href="/facts/Receptive_field/2LIVVKfe">receptive fields</a> of complex cells, the <a href="/facts/Mathematical_model/CGhyuxgz">model</a> <a href="/facts/Average/etawWjw4">averages</a> several pairs of <a href="/facts/Simple_cell/WVXwG5yq">simple cells</a> nearby and overlaps their <a href="/facts/Receptive_field/2LIVVKfe">receptive fields</a> to construct the complex cell <a href="/facts/Mathematical_model/CGhyuxgz">model</a>. This allows the complex cell to be phase <a href="/facts/Dependent_and_independent_variables/dINfzIF2">independent</a> for all <a href="/facts/Stimulus_(physiology)/aBcpBfYQ">stimuli</a> presented while still maintaining an equal <a href="/facts/Receptive_field/2LIVVKfe">receptive field</a> shift to the <a href="/facts/Simple_cell/WVXwG5yq">simple cells</a> it is composed of in the <a href="/facts/Mathematical_model/CGhyuxgz">model</a>.<a class="footnote-ref" id="fnref:61" href="#fn:61"><sup>61</sup></a> </p><p>The stereo model is then made from a multitude of <a href="/facts/Complex_cell/5pq8kEcl">complex cell</a> <a href="/facts/Mathematical_model/CGhyuxgz">models</a> that have differing <a href="/facts/Binocular_disparity/Fj2I1Soj">disparities</a> covering a testable range of <a href="/facts/Binocular_disparity/Fj2I1Soj">disparities</a>.<a class="footnote-ref" id="fnref:62" href="#fn:62"><sup>62</sup></a> Any individual <a href="/facts/Stimulus_(physiology)/aBcpBfYQ">stimulus</a> is then distinguishable through finding the <a href="/facts/Complex_cell/5pq8kEcl">complex cell</a> in the population with the strongest response to the <a href="/facts/Stimulus_(physiology)/aBcpBfYQ">stimuli</a>.<a class="footnote-ref" id="fnref:63" href="#fn:63"><sup>63</sup></a><a class="footnote-ref" id="fnref:64" href="#fn:64"><sup>64</sup></a> The stereo model accounts for most non-temporal physiological observations of binocular neurons as well as the <a href="/facts/Correspondence_problem/YBe0HbVX">correspondence problem</a>.<a class="footnote-ref" id="fnref:65" href="#fn:65"><sup>65</sup></a><a class="footnote-ref" id="fnref:66" href="#fn:66"><sup>66</sup></a><a class="footnote-ref" id="fnref:67" href="#fn:67"><sup>67</sup></a> An important aspect of the stereo model is it accounts for <a href="/facts/Binocular_disparity/Fj2I1Soj">disparity</a> attraction and repulsion.<a class="footnote-ref" id="fnref:68" href="#fn:68"><sup>68</sup></a> An example of <a href="/facts/Binocular_disparity/Fj2I1Soj">disparity</a> attraction and repulsion is that at a close distance two objects appear closer in depth than in actuality, and at further distances from each other they appear further in depth than in actuality.<a class="footnote-ref" id="fnref:69" href="#fn:69"><sup>69</sup></a> <a href="/facts/Binocular_disparity/Fj2I1Soj">Disparity</a> attraction and repulsion is believed to be directly related to the physiological properties of binocular neurons in the <a href="/facts/Visual_cortex/qmF8F5Sb">visual cortex</a>.<a class="footnote-ref" id="fnref:70" href="#fn:70"><sup>70</sup></a> Use of the stereo model has allowed for interpretation of the source of differing peak locations found in disparity <a href="/facts/Neural_coding/GSRJ4WJF">tuning curves</a> of some cells in visual cortex. These differing peak locations of the <a href="/facts/Neural_coding/GSRJ4WJF">disparity tuning curves</a> are called characteristic disparity. Due to the lack of defined <a href="/facts/Neural_coding/GSRJ4WJF">disparity tuning curves</a> for <a href="/facts/Simple_cell/WVXwG5yq">simple cells</a>, they cannot have characteristic disparities.,<a class="footnote-ref" id="fnref:71" href="#fn:71"><sup>71</sup></a> but the characteristic disparities can be attributed to <a href="/facts/Complex_cell/5pq8kEcl">complex cells</a> instead.<a class="footnote-ref" id="fnref:72" href="#fn:72"><sup>72</sup></a><a class="footnote-ref" id="fnref:73" href="#fn:73"><sup>73</sup></a> Two limitations of the stereo model is that it does not account for the response of binocular neurons in time, and that it does not give much insight into connectivity of binocular neurons.<a class="footnote-ref" id="fnref:74" href="#fn:74"><sup>74</sup></a><a class="footnote-ref" id="fnref:75" href="#fn:75"><sup>75</sup></a> </p> <h2 id="see-also">See also</h2> <ul><li><a href="/facts/Binocular_rivalry/XrVeDbP9">Binocular rivalry</a></li> <li><a href="/facts/Binocular_vision/koERAQCV">Binocular vision</a></li> <li><a href="/facts/Eye_dominance/fMv4PUFW">Eye dominance</a></li> <li><a href="/facts/Eye_movement_(sensory)/4a9mNbP5">Eye movements</a></li> <li><a href="/facts/Field_of_view/Xp1G4CXF">Field of view</a></li> <li><a href="/facts/Horopter/bbTCafe2">Horopter</a></li> <li><a href="/facts/Interpupillary_distance/T7KGYqdD">Interpupillary distance</a></li> <li><a href="/facts/Monocular_vision/AlWkdvgt">Monocular vision</a></li> <li><a href="/facts/Stereoblindness/T7vn2IKw">Stereoblindness</a></li> <li><a href="/facts/Stereopsis/AL5Ydh0m">Stereopsis</a></li> <li><a href="/facts/Stereopsis_recovery/fXKa0JPI">Stereopsis recovery</a></li> <li><a href="/facts/Stereoscopy/jfHumNV8">Stereoscopy</a></li> <li><a href="/facts/Visual_perception/g7Tfaq2l">Vision</a></li></ul> <h2 id="references">References</h2> <ol> <li id="fn:1"><p>Qian, Ning (1997). 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