After having reviewed the vision system in detail, some aspects seem more clear. The forming of a visual concept involves the integration of smaller, low-level parts of the visual system. The smallest components, the photoreceptors, compose the ON- and OFF-center receptive fields of bipolar and ganglion cells. The ganglion cells then send action potentials onward through the LGN to the striate cortex, where first steps of integration happen in layers outside of layer IVC. Binocularity, meaning responsiveness to stimuli coming from either eye, happens in layers superficial to layer IVC. Another form of integration, happening outside layer IVC, is the integration of smaller receptive fields into bar-shaped fields. These fields can be selective of different features, e.g. orientation or direction of movement.
Progressing on to other cortical areas, they further integrate the information from lower structures, with different areas taking care of different operations. Area V5, receiving input from areas V2, V3 and direct axons from layer IVB of V1, is associated with motion selectivity. Areas running in the ventral stream, e.g. area 4, area IT and the fusiform face area are associated with color, shape and even face detection. Their real functioning is much more complex, as most areas receive signals from cells associated with most of these functions.
The idea behind concept forming is the gradually increasing integration of all of these parts of the system. In pattern recognition, many areas activate simultaneously, so there is no single area at the top of the hierarchy, responsible for coming up with the final image. With this said, my current view of concept forming resembles more the gradient-like manner in which colors are perceived: rather than a single set of neurons at a specific area firing on the recognition of a given pattern, maybe the image is formed more like a synchronized approximation involving a variety of areas.
The course is coming to an end and it is time to draw some concluding lines about the functions of the nervous system. All in all it is an immensely complex system, with probably still much more to be learned than is currently known. The enhanced brain scanning technology gets ever more accurate, with not having to settle for gross level images, but rather the firing of individual neurons at constantly reducing time delays. The overall progress of neuroscience seems, to me, to follow a more general shift in science, where whole systems, rather than just a few main variables are increasingly getting the credit they deserve. The woods are being distinguished from the trees. We see this in environmental studies where the fragility of whole ecosystems, and the importance of even the smaller parts participating in it, are being noticed. The same line of thinking applies to brain models, where certain areas are no longer thought to be individually in charge of certain functions. Rather than one area taking care of e.g. constructing the visual image, it is born from a co-operation of so many different areas. Not withstanding the brains incredible and mysterious tendency for substituting lost functional areas with other ones.
On learning about the brain, the toughest part for me has been to memorize the names, structures and functions of the myriad of different areas, as well as the knowledge of how each part communicates with one another. The complexity seems, at times, startling and one wonders how can this system be ever fully understood. It also begs the question of how far in general is the collective human mental capacity capable of managing the whole picture.
Surely, different inner fields of neuroscience focus on very narrow aspects and single individuals don’t even try to comprehend the whole picture. That said, it will be interesting to see in the future, are we capable of coping with the full mass of information. In the field of physics, a “collapse” or compression of information holding equations to simplified forms can be seen every now and then. I wonder if the same thing is possible with “descriptive” information? Or will the task of information holding and thus the formation of any meaningful new theories be outsourced to some future AI? Also, today’s brain models seem to be far from complete. The more accurate image we want to create requires taking into account more and more details, eventually going to the level of the whole body. It will be interesting to see is it possible to construct a feasible “mind-brain-structure”, without all the feedback loops of other bodily systems.
Muscle movement is a necessity to express behavior initiated in the cortex of the brain. The overall picture of descending pathways seems nowadays pretty clear. The central motor system is arranged as a hierarchy of control: the neocortex takes care of the planning together with the basal ganglia of the forebrain. After a quick meeting, they come up with a strategy. The strategy is sent onward to the tactics department (motor cortex and cerebellum), which flip through the files of previous success and decide the best set of actions to execute. They in turn send their plans to the level of execution (which is just one step above the proletarian level aka “the muscle”). The two executives, the brain stem and spinal cord, activate the motor neuron and interneuron pools, altering motivational speeches and threats of co-operation negotiations. In all, the whole show is run like the R&D department of Nokia, except with a better success rate and an inclination for improvement.
Looking at the big picture, we seem to be missing one important part of the hierarchy: the investors. If the neocortex is coming up with the business strategy, who is it trying to please? Which part of the brain constructs the necessity to want something in the first place? Could the lower company levels just cast off the investors and start working solely for the common benefit? Or would it lead to a conflict of interests, causing the organism to dash around aimlessly like a beheaded chicken?
As partly distinct from the rest of the brain, the optic system seems to be a relatively clearly perceived entity. Far from simple in functioning, its outlines can be categorized into the eye and its structure, the cells of the retina, the optic nerve pathways and the brain areas which the optic nerves lead to. Many structures can already be explained in remarkable detail, however, the current challenge lies in explaining the way images form from the signals initiated by the retinal cells.
Most of the axons from the optic tract innervate the lateral geniculate nucleus (LGN) of the dorsal thalamus, where the information is passed onward to cortical areas of the occipital, temporal and parietal lobes. Around two dozen cortical areas have been identified to be part of visual information processing, many of which functions are still largely unclear. However, it seems different parts manage different aspects of the processing. E.g. from the two large-scale cortical streams involved, the dorsal stream appears to analyse visual motion and visual control of action, while the ventral stream is thought to be involved in building a perception of the visual world and recognition of objects.
For me, the most devouring question lies in how in the world are the initial electrical signals transformed into a subjective experience of seeing? Where in the brain does the image of the visual field reside?
Apparently, the current hypothesis of perception is that certain groups of neurons, receptive fields, are activated according to different objects of the physical world (e.g. the face of my clamorous nocturnal neighbor which occasionally resembles a punching bag). Yet, this approach opens up more questions than it answers: concepts of objects are also utilized in the act of thinking. How do thoughts utilize the concepts built by the visual system? How do initial concepts form? Which was first: the concept or the visual? Where do thoughts come from and who does the thinking? How did this text come into being, and is it understood by anyone?