Sebastian Seung is a Princeton neuroscientist who leads a project to map the "connectome," a new term for the brain/mind, parallel to the term "genome." Just as the genome is our genetic information, encoded in the macromolecules of DNA, the connectome is mental information, stored in the trillions of connections between the ten billion neurons in our brain.

It is Seung's ambitious goal to map the complete set of connections between neurons in brains, initially those of small animals, but ultimately of human brains. To achieve this, he is using the latest computer tools of artificial intelligence and machine learning, with the help of hundreds of thousands of volunteers around the world in Eyewire, an online game or puzzle in which humans identify and tag neurons in two-dimensional layers (slices of brain tissue), to train machine learning that can create the full three-dimensional map of neurons and their connections.

The National Institute of Health is supporting Human Connectome Projects and a Connectome Coordination Facility. These projects have made major progress mapping the major neuron pathways between different brain regions as shown below. Seung's project is much more ambitious, hoping to map the trillions of synaptic connections between the billions of neurons.

Brain pathways. Coloured 3-dimensional magnetic resonance imaging (MRI) scan of the white matter pathways of the brain, side view. White matter is composed of myelin-coated nerve cell fibres that carry information between nerve cells in the cerebrum of the brain (top half of image) and the brain stem (bottom centre). This image was created by an MRI scanner sensitised to the movement of water around the brain. Blue represents neural pathways from the top to the bottom of the brain, green represents pathways from the front (left) to the back (right), and red shows pathways between the right and left hemispheres of the brain.

Seung says that one

approach is to use the connectome to build a computer simulation of the spiking of neurons in a network, then run the simulation and watch the neurons to see the order in which they spike during memory recall. It’s only natural to dream of scaling up this approach to an entire brain. Uploading is the ultimate way of testing the hypothesis “You are your connectome.”

Connectome: How the Brain's Wiring Makes Us Who We Are (p. 258).

But there is a vast difference between computing machines and a mind/brain. Philosophers of mind deny the possibility of a machine having a subjective experience, especially having "feelings," and what they call the "qualia," the "what's it's like to" taste an apple, or to see the "blueness" in the sky.

Seung describes the storage of memories or experiences in strengthened synaptic connections between neurons. He cites the work of Eric Kandel and Donald Hebb.

Seung says "Hebb was way ahead of his time." (p. 82) Hebb proposed what is called a "cell assembly," a group of neurons "wired together" by strengthened synapses simply because they had "fired together" by sensations that sent trains of activation spikes along them.

A Hebbian assembly can store a memory that can be recalled by any new experience that fires just some of the wired-together neurons. This is the idea that neurons that have been wired together will later fire together, perhaps just by thinking about related concepts. This is a neural model for the "association of ideas" (John Locke, David Hume).

Hebbian assemblies are also similar in some ways to Herbert Simon's "blackboard" model for human cognition, in which various items could be written to a blackboard which was visible to other systems that could read and write on the blackboard. As a model for human consciousness, Simon's blackboard resembles the Theater of Consciousness and Global Workspace Theory of Bernard Baars. A blackboard architecture is an important part of most computer "expert systems."

A vital difference between neuron assemblies in brains and network connections in computers is that when a Hebbian assembly fires it can stimulate activity in the brain's emotional centers (e.g., the amygdala), reproducing emotions felt in the original experience (pain, pleasure, fear, comfort), which adds valuable meaning and context to the current experience.

In William James' "stream of consciousness," a new experience can generate a "blooming, buzzing, confusion" of related ideas from past experiences, providing the possible alternatives for new actions that are the basis for his two-stage model of free will.

While Seung emphasizes the brain's "wiring" as what makes us who we are, information philosophy emphasizes the stored information and the cellular communication of information over the "wires" as constituting our identity and individual personality.

But this is just a difference in emphasis. Seung's human connectome will some day let us see exactly where human experiences are recorded in brains and how they are later reproduced as value-based guides to our decisions and actions in future experiences. See our Experience Recorder and Reproducer.

Something Seung wrote about a "celebrity neuron" seems to describe its dependence on being previously wired together in a Hebbian assembly.

If a neuron spikes in response to Jennifer Aniston but not other celebrities, we might think that the neuron’s function is the detection of Jen. But this neuron is embedded in a network of many other neurons. It would be a mistake to think of this neuron as a lone genius, detecting Jen all by itself. Newton’s words ring even truer for neurons than for Newton: “If a neuron sees further, it is only by standing on the shoulders of other neurons.”

(Connectome, p.65)

In terms of information science and our ERR, a single neuron simply cannot contain enough information content to reproduce the experience of Jennifer Aniston. Indeed, the information is not even in the many synaptic connections in the Hebbian assembly. It is in the total experience reproduced by the connected neurons all firing again, bringing back visions, sounds, and other senses, but also related feelings about Jennifer.