Architecture of the Brain

First, the brain is organized into functionally specific areas, and second, neurons in different parts of the vertebrate nervous system, indeed in all nervous systems, are quite similar.

Small comparison with Computers

A gross observation between computer’s transistors and human neurons is that there a big difference of numbers:

• trillions of transistors vs billions of neurons.
• 6 orders of magnitude frequency difference.
• Many many neural types and different types of connections.
• And the digital vs analog and chemical modes of communication.
• Parallel processor abilities.
• Fixed vs plastic architectures But this is comparing with transistors with one higher level object, so this comparison might not be completely fair.

And only some brain areas are similar to real neural networks

David Marr’s Tri-level approach

Computational Level: what kinds of computation is the system doing? Why does it do these things (highest level things) (e.g. intentions and beliefs with ToM).

Algorithmic Representational Level: how does the system do what it does? What processes does it effectively manipulate?

Physical level: how does the system implement it on the physical level (chemical or physical processes of brain firing).

For the brain, the first level it is debatable (not clear what the brain is trying to solve), and the representational level is just incomprehensible. Neuroscientists usually just measure at the physical/hardware level.

What does the Brain do?

This attempts to answer the computational level problem: Some debated things are:

• Brain creates a model of the environment.
  • Having models of the world is useful to predict what they are likely to do and plan accordingly.
• The brain makes internal decisions on different time scales (goals).
• This internal decisions (intents) are used to make actions.
  • We want to predict the consequence of our actions on the environment.
• It is able to evaluate their actions (perhaps survival, safety, or other details) and update the internal model of the world.

And we would ask how the brain does all this.

The development of the brain

It first starts with an elongated neural tube. The different parts of development are named by the stage of development, also related to the evolution steps.

Parts of the brain

Cortex

We have the largest density of cells in the cortex, this is the part of the brain mostly correlated with intelligence. many many abilities correlate with the size of the cortex.

Structure of the Cortex

Cortex has very similar structure (also for other mammalian species!) This lead to cortical column theory, parts of the cortex have some specific functional properties. The experiment on cats provides good evidence on this theory. Another good experiment is the one in 1990 by Sur et Al. (Universal swappable computing engines). They proved the plasticity and reorganization capabilities of brain regions during development.

Actor Critic Model of the brain

We studied actor critic methods in RL Function Approximation. It seems that the brain implements similar modules:

Something very similar to this model happens in the dopamine neurons (providing rewards gives difference in expectations and actual rewards, this is called reward prediction errors.) When we have conditioned stimulus the surge in dopamine happens during the cue, not the actual reward itself. This works for positive errors (not expecting anything while receiving food, where we have a surge of dopamine), and negative errors (not receiving food even if we are expecting it).

Areas of brain processing

The striatum

The striatum area seems to converge processing from the dopaminergic pathways and the cortical areas. Medium spiny neurons form trisynaptic connections with the cortex and the VTA (ventral tegmental area). If the dopamine binds to D1 receptors, it becomes weaker, if D2 the connection becomes stronger. D1 stimulates movement while D2 inhibits it. It starts with very complex signal and ends up with a few actuator neurons (some thousands).

The learning loops becomes shorter with time, (From conscious learning to unconscious execution).

The brain stem

The brain stem is made of the medulla, Pons, and Midbrain.

Medulla

The medulla, the most caudal portion of the brain stem, is a direct extension of the spinal cord and resem- bles the spinal cord both in organization and function. Neuronal groups in the medulla participate in regulat- ing blood pressure and respiration. The medulla also contains neuronal groups that are early components of pathways that mediate taste, hearing, and main- tenance of balance as well as the control of neck and facial muscles.

Pons

The pons lies rostral to the medulla and protrudes from the ventral surface of the brain stem. The ventral portion of the pons contains the pontine nuclei, groups of neurons that relay information about movement and sensation from the cerebral cortex to the cerebel- lum. The dorsal portion of the pons contains structures involved in respiration, taste, and sleep.

Midbrain

\[...\]

The midbrain also contains components of the auditory and visual systems. Finally, several regions of the midbrain give rise to pathways that are connected to the extraocular muscles that control eye movements.

The thalamus

This is one of the most complex brain areas. it has a role in consciousness, different firing patterns here if you are asleep or not. It receives information from sensory areas, but above all from cortical areas. The thalamic reticular nucleus acts as a gateway between thalamus and cortical connections, they are called attention centers (like amygdala) and modulate the thalamic information to the cortex.

The entire cortex is connected to the thalamus, it also controls the communication between different brain regions.

The Hippocampus

It sits near the enthorinal cortex (this sends much input into the hippocampus, mainly in two pathways) Dentate Gyrus or dentate region -> CA3 -> CA1 (the output of the hippocampus, connected to the rest of the brain).

• Entorhinal cortex has about 200k cells (10-20% interneurons)
• Dentate Gyrus has about 1.2kk granule cells. (some sort of a sparse encoder, it is separating patterns)
  • 4k basket cells
  • 32k Hilar interneurons (20k mossy cells)
• CA3/CA1 about 330k/420k piramidal cells.
  • CA3 has many auto-associative recurrent architectures, it is believed to be doing pattern completion after separation with a given context.

The dentate gyrus has much more neurons than other neurons.

Functional areas

Mostly the maps to the functions of the brain has been developed by analysis of damages on these regions. A notable example is Phineas Gage’s case on frontal cortex damage. He completely changed his personality. (valuation and planning abilities).

Broca’s area is used for speech production: they can understand sentences but could not produce words.

Wernicke’s area: cannot interpret speeches, they can produce sentences, but they are irrelevant.

Object recognition areas

In animals it is possible to use optical techniques to turn on or off specific parts of the neural regions. fMRI uses the activated oxygen levels in certain parts of the human brain, and consumes more energy on those parts. It is a quite precised method. Good for images. The fusiform face area was a quite nice discovery: there is a specific region in the brain that activates just by looking at parts of the face. Or another is parahippocampal place area, that activates for places (houses, landscapes, corners of the room, but doesn’t respond for other things, objects, or abstract art). Extrastriate body area: responds to body parts (no faces, no random cartoons, yes stickman).

There are other neurons that activate for specific parts of the brain.

Hierarchical organization of visual processing

This has been the main inspiration for visual processing architectures. They start to recognize simple features, and then compose them in more complex shapes. In visual things there are V1, V2, V4 TEO, and cortex areas, in quite organized parts. Convolutional nets are not RNN, they do not use higher contextual information to inform back the small parts. Context is important for humans. Here information is bidirectional.

In visual processing, there are two streams of connections that give different information on

• Where (Dorsal, vestibular information about body positions (eye, arm etc…), that help in action planning)
• What (Ventral, more in object recognition)
• They share the first layers (v1,v2) for low level details. They tested this in object discrimination and landmark discrimination tasks with dorsal and ventral damages.

Looking at the visual stream, we observe that the organization of the parts is not casual, the information gets into the somatosensory area. Posterior parietal cortex uses the information to build model of yourself (egocentric maps).