One could moderate the number of neurons being recorded from, control the environmental variables, and so on — and then one has returned to the realm of what neuroscientists are doing in any case and we have a specialized technology development project, not a moon shot or a genome project. Still, to understand whether one should focus all energies on greatly increasing the number of neurons being recorded from, we need to answer the theoretical question of what we gain by recording every neuron. If we cannot successfully argue that comprehensive neuronal recordings solve all our problems, then partial observations certainly won’t.
One is not really interested in the particulars of a given animal’s history of all spikes in the brain: one is interested in characterizing the potential dynamics of neurons, under all possible circumstances. This is the well-known “competence/performance” distinction from linguistics. Supposing we record all English sentences spoken by someone, and then play that recording back. No one would say that the tape recorder knew English, even though it repeated the same performance. From a scientific perspective we want to know what the brain is capable of doing in principle, not what it actually does in a specific instance. In other words, we want to understand the laws of brain dynamics, not the details of brain dynamics.
Here is the rub: what sets the laws of the neural network? Well, it is precisely the circuit connections and the physiology of single neurons that the authors have dismissed. The paper would focus all resources into multi-neuron recordings, without any plan to complete the outstanding task of mapping out the anatomical circuitry, itself a huge project, which we have only begun to seriously address and which provides a much closer analog to the Genome project. The physiological properties of neurons depend on carefully studying individual cells or pairs of cells, also not something that is on the agenda. Once the circuit and cellular physiology is known, we can in principle derive the pattern of every spike from every neuron, under every environmental stimulus. Network structure and cellular physiology determine the dynamical laws governing the neurons, and therefore drive the spiking activity. Positing an “emergent level” of spiking activity that cannot even in principle be predicted from the circuits, physiology, and inputs, is a form of mind-body dualism, that is no longer part of scientific thinking, along with vitalism, the idea that there is a separate “life force” that cannot be reduced to the molecular biology of the cell
In fact, this is what the recently funded (and controversial) multi-billion dollar European project is geared towards. The Europeans plan to build a comprehensive simulation of human brain activity, starting from details of individual neurons and micro-circuits. The only problem there is that they don’t actually have the necessary circuits or physiological information (or are extrapolating from the rodent somatosensory cortex to the human). The way to resolve this is not to measure every spike from every neuron, but to map circuit connectivity and measure cellular physiology. It is this recognition that has led us to propose and commence on the project of mapping out mouse brain circuits, a task that is already enormous and will require many more resources to complete.
Let us now return to the fallacious argument that in order to study the collective dynamics of the neuronal network one must record all neurons. The paper exhibits a curious theoretical disconnect: on one hand the authors point to collective phenomena in physics, and on the other hand they forget the basic lesson we have learned from physics: that as far as collective or thermodynamic behavior goes, the full detailed microscopic behavior of the system does not matter. Only some very limited aspects of the microscopic dynamics filter out to the larger length and time scales: systems exhibit “universal” behaviors independent of much microscopic detail.