Neuroscientists have found clear evidence that the infra temporal cortex is indeed required for object recognition; they also found that subsets of this region are responsible for distinguishing different objects.
In addition to its hypothesized role in object recognition, the infra temporal cortex also contains “patches” of neurons that respond preferentially to faces. Beginning in the 1960s, neuroscientists discovered that damage to the infra temporal cortex could produce impairments in recognizing non-face objects, but it has been difficult to determine precisely how important the infra temporal cortex is for this task.
Despite its peripheral location, the retina or neural portion of the eye, is actually part of the central nervous system.
So if one understands this part, even human brain is passing through neutrons to generate an image classification based on inputs of visual cortex, which is the primary cortical region of the brain that receives, integrates, and processes visual information relayed from the retinas. It is in the occipital lobe of the primary cerebral cortex, which is in the most posterior region of the brain
once a sensory input is captured by the retina(eye), it travels through lateral geniculate nucleus in the thalamus and then reaches the visual cortex. The area or part of visual cortex which receives this sensory input is called primary visual cortex which is Brodmann area 17 which basically detects the intensity, shape, size and location of objects in visual field.
occipital visual areas such as Brodmann areas 18 and 19 provide input on spatial vectors to the middle temporal and medial superior temporal cortexes . These areas basically help in generating smooth conjugate pursuit eye movements. Brodmann areas 19 is part of the extrastriate visual cortex that surrounds the primary visual cortex, and which processes visual information.
So now you understand how each part of human brain helps in image recognition and as the deep learning tries to find or one should say make as close as possible algorithm to identify image recognition based on how neural network works.
When you do DLS specialisation, Andrew Ng mentions this part of what deep learning is trying to achieve.
Hope it helps you understand!!!
Keep Learning!!!
Regards
DP