Much of the current hope of reconstructing a functioning brain rests on connectomics: the ambition to construct a complete wiring diagram, or “connectome,” of all the synaptic connections between neurons in the mammalian brain. Unfortunately connectomics, while an important part of basic research, falls far short of the goal of reconstructing a mind, in two ways. First, we are far from constructing a connectome. The current best achievement was determining the connections in a tiny piece of brain tissue containing 1,700 synapses; the human brain has more than a hundred billion times that number of synapses. While progress is swift, no one has any realistic estimate of how long it will take to arrive at brain-size connectomes. (My wild guess: centuries.)

Second, even if this goal were achieved, it would be only a first step toward the goal of describing the brain sufficiently to capture a mind, which would mean understanding the brain’s detailed electrical activity. If neuron A makes a synaptic connection onto neuron B, we would need to know the strength of the electrical signal in neuron B that would be caused by each electrical event from neuron A. The connectome might give an average strength for each connection, but the actual strength varies over time. Over short times (thousandths of a second to tens of seconds), the strength is changed, often sharply, by each signal that A sends. Over longer times (minutes to years), both the overall strength and the patterns of short-term changes can alter more permanently as part of learning. The details of these variations differ from synapse to synapse. To describe this complex transmission of information by a single fixed strength would be like describing air traffic using only the average number of flights between each pair of airports.

Underlying this complex behavior is a complex structure: Each synapse is an enormously complicated molecular machine, one of the most complicated known in biology, made up of over 1,000 different proteins with multiple copies of each. Why does a synapse need to be so complex? We don’t know all of the things that synapses do, but beyond dynamically changing their signal strengths, synapses may also need to control how changeable they are: Our best current theories of how we store new memories without overwriting old ones suggest that each synapse needs to continually reintegrate its past experience (the patterns of activity in neuron A and neuron B) to determine how fixed or changeable it will be in response to the next new experience. Take away this synapse-by-synapse malleability, current theory suggests, and either our memories would quickly disappear or we would have great difficulty forming new ones. Without being able to characterize how each synapse would respond in real time to new inputs and modify itself in response to them, we cannot reconstruct the dynamic, learning, changing entity that is the mind.

But that’s not all. Neurons themselves are complex and variable. Axons vary in their speed and reliability of transmission. Each neuron makes a treelike branching structure that reaches out to receive synaptic input from other neurons, as a tree’s branches reach out to sunlight. The branches, called dendrites, differ in their sensitivity to synaptic input, with the molecular composition as well as shape of a dendrite determining how it would respond to the electrical input it receives from synapses.