Issues Magazine

Substrate-Independent Minds

By Randal A. Koene

Our lives are a composite of actions and experiences, and our minds depend on our bodies and the environment – but do they have to?

At, we pull together the expertise and the projects that are needed to achieve what we call substrate-independent minds (SIM). Let me introduce SIM, what it means, what it is about and, in particular, its feasibility.

Predictions of futurists; expectations of technologists and scientists; anticipation and concerns of philosophers; epics of science fiction authors and cinema – all of these tap into the ideas of life extension, life expansion, augmentation, brain–computer interfaces, artificial minds, artificial intelligence and artificial life. What may those things come to mean for the life that we know?

In this life, there is no universal purpose that stands simply to be discovered by scientific investigation. We assign purpose as individuals, as society and as culture. Purpose, meaning and goals are the results of wants and desires that emerge from a mix of intrinsic drives and experience that has shaped our thoughts and emotional associations. Originally, the drives served the survival of our genes, but our interests have already surpassed that. Therefore, it begins with us.

It is in this context that we introduce SIM. What is it? Why would you want it? And how can we do it?

Let us take a step back and look at ourselves as a species and as individuals.

What Are You?

You are a collection of things. You are the result of your experiences. You are your body’s sensations and actions. And you are a unique expression of characteristic responses. But all of those exist in only one place. For you, the universe outside does not exist directly. You cannot even touch it.

When you believe you are touching the smooth surface of a table, the protons and neutrons of the atoms that make up your fingers never collide with those of the table. Almost everything is empty space. Forces initiate electric signals in your fingertips and are carried by nerves into your brain. But you are completely unaware of that current until the information it carries has been processed within your mind.

Everything that you are, and everything that the universe is, exists to you only through that processing. What is processed in your mind is all that you can be aware of and, for you, all that exists. So, when we say that we want to extend or expand life, what we really mean is that we want to extend or expand that processing in your mind. It is this we seek to safeguard.

One way to safeguard the mind is to maintain the thing that implements it and enables it to function right now: the body that contains the brain and the environment upon which that body depends. The whole system in which the mind exists needs to be sustained, with no significant changes, no accidents. If the atmosphere suddenly disappeared, the system would fail and the mind end.

The other way is to directly address the processes that are all that we are. Access them. Treat them like we treat valuable information, like mission-critical programs. Keep them safe by making backups. Correct problems and offer updates. Run the processes in a fault-tolerant implementation. Run them in implementations suited to new environments and new challenges.

image of whole brain emulation and categories of projects to solve requirements

Figure 1. The four requirements of whole brian emulation (WBE), and six categories of projects, each of which can suffice to solve a requirement.

This approach is SIM. Unlike the maintenance approach, SIM is about access. It depends on data acquisition. To be, to exist, the functions of the mind need to carry out their processing on a processing platform, or substrate. But when those functions can be implemented on a variety of processing substrates we have achieved a substrate-independent mind. By analogy, think of programs that are written in platform-independent code.

Maintenance or access – both approaches have value. We need a strategy to objectively compare their pros and cons and their feasibility in the foreseeable future.

Choosing an Approach

The term “mind uploading” has been used to describe a transition from the brain’s implementation of mind functions to SIM. Ideally, we would always recompile functions of mind to make optimal use of a new target substrate. But, at present we do not understand enough about the hierarchy of interacting strategies employed at different cognitive levels of the mind to carry out such optimisation. We do understand a great deal more about the principles of the fundamental biophysical components from which functions of mind emerge.

In neuroscience we have experience in identifying mechanistic aspects of neurophysiology, measuring functional responses and determining modulating contributors. While we may not have a complete descriptive catalogue of all types of neurons, synaptic channels and so forth, we do know how to obtain that information in a specific case when we need it. By analogy, it is as if we know how to read out the assembly language instructions of a program from its executable file, even though we do not have an adequate high level description to write an alternative implementation of the same program.

This is why the vast majority of actual research and development towards SIM is focused on the most conservative route, which we call whole brain emulation (WBE). In whole brain emulation, we aim to replicate the functions of neurophysiology and the structure of neuroanatomy that determines the interactions of basic components. The same general method, brain emulation at increasing resolution and scale, is adopted by pioneers on the advanced frontiers of computational neuroscience and neuroinformatics, frequently with previously unimaginable results. has identified several conceptually distinct approaches, although the following focuses on the WBE approach.

Basic Elements

Every time we describe something, make a representation or create a model, we have to choose the basic elements and the scope of the representation. We may consider components at the element level as “black boxes” that we need to characterise. Different approaches to SIM choose different black box levels.

One set of approaches attempts to characterise whole-person or body behaviour. Re-creations depend on sources such as self-report, life-logs, video recordings and artificial intelligence that attempts to learn about an individual.

Another choice is at the level of the brain or parts of a brain. That is a typical choice for approaches that are based on customised tuning of a general cognitive architecture, or that rely on partial neuroprostheses and brain–computer interfacing.

Bottom-up, there are approaches that opt for black box levels at the resolution of neurons or even the specific morphology of neurons. Those are the levels used in representations that are based on work in computational neuroscience and neuroinformatics. Presently, representations of that kind are the most concrete and usable in reconstructions for feasible WBE.

The times at which neurons produce action potential responses – the spike times of neurons – are the currency of the brain. It is the timing of those spikes that determines whether a synapse will be strengthened, weakened or remain unchanged. The timing therefore determines what is learned, which memories are encoded, how the system evolves, and how we change from moment to moment. Neural spikes are also what drive muscle cells, actuating our ability to move, to react, to speak, and to live in interaction with our environment. In effect, and within an acceptable margin of error, it is the timing of those spikes that a WBE must replicate.

Four Requirements

To achieve WBE we need to (Fig. 1):

  • validate our hypotheses about the data resolution and scope needed for a successful reimplementation;
  • obtain the structural information about what is now known as the brain’s connectome (a comprehensive map of neural connections in the brain);
  • obtain the functional characteristics of the active components that are linked within the connectome; and
  • find a suitable platform on which to re-implement and emulate the functions of mind.

With regards to the first requirement, a modelling resolution is chosen. At and below that level, the functional characterisation of elements is key. The elements need to be simple enough so that we can capture all of their relevant behaviour. Above the chosen level, structural characterisation is key. That defines the interactions enabled by the connectome, which lead to emergent behaviour.

If we attempted to fine-tune parameters or correct measurement errors in a reconstructed network of 86 billion neurons, without functional recordings at high resolution as reference points, then the sheer combinatorial size of the optimisation problem would easily exceed the capabilities of any computational system, either classical or quantum. We have to isolate smaller subsystems to make the problem manageable.

Good engineering practice tells us that it is unwise, unless unavoidable, to rely on a one-step process in which there is no provision for the verification of partial reconstructions. Acquiring data, then building a full reimplementation and pressing “go”, is risky. Having to correct problems in a very complex system, without carrying out smaller steps, greatly increases the degree of difficulty. It is for these reasons, and more, that a practical method for successful WBE should combine structural and functional measurements at large scale and high resolution.

Solution Projects

The four requirements for WBE are very concrete and there are solutions that are feasible by applying the capabilities of science and engineering today. Right now, several projects are in stages of preparation or execution (

The obvious way to acquire a structural connectome is to look at the spatial morphology of cells and fibres in the brain. Electron microscopy provides the resolution needed, and automated sectioning and imaging of a brain gives us the scope. Such volume microscopy is actively developed by several groups (e.g. the ATLUM project at Harvard University).

An entirely different solution to the acquisition of the structural connectome is to use biological barcodes (e.g. distinct artificial sequences of DNA or RNA) to mark pre- and post-synaptic sites throughout the brain. The tags form bidirectional pointers between neurons. After extracting tags at all sites, the sets of pointers provide the structural connectome in terms of synapses between neurons. This biological tool is being developed in the laboratories of Dr Anthony Zador (Cold Spring Harbor Laboratory, New York) and Dr Ed Callaway (Salk Institute, California).

One strategy for taking measurements within the brain is to establish a hierarchy of interfaces, which Dr Suzanne Gildert (D-Wave) called the Demux-Tree approach. Dr Rudolpho Llinas (New York University’s School of Medicine) conceived such a tree where the edges between nodes are formed by nanowires delivered through the vasculature of the brain. Flexible nanowires with a diameter of 500 nm have been developed at New York University’s School of Medicine.

Biological alternatives have the advantage that they readily operate at cellular and sub-cellular resolutions, and can do so in vast numbers throughout the neural tissue. A so-called molecular ticker-tape is being worked on in collaboration between laboratories at MIT, Harvard and Northwestern University, with contributions by Halcyon Molecular. The process writes on strands of DNA to record functional events (e.g. voltage changes).

Finally, based on decades of experience developing integrated circuit technology, we can record in vivo by constructing a Demux-Tree hierarchy composed of nodes only, using wireless micro-neuro-interfaces.


In 2010, Rodrigo Gomez-Martinez (National Microelectronics Center, Barcelona) and his collaborators implanted integrated circuits in living cells. Inspired by such accomplishments, Dr Yael Maguire (MIT) is developing passive communication technology at infrared wavelengths that is intended for incorporation into integrated circuit (IC) recording nodes with a diameter of 8 µm – the size of a red blood cell (Fig. 3). Common 32 nm IC technology can fit 2300 transistors on such an agent – as many as in the original Intel 4004 microprocessor.

The IC can be encased in biocompatible silicon or a protein shell. In addition to the 8 µm hubs that distribute power and aggregate data for delivery, a collection of collaborating agents will include smaller micro-neuro-interfaces to carry out specialised sensing and stimulating tasks in the spaces between cells. It is a hierarchical team composed of nodes at cellular scale.

If we introduce micro-neuro-interfaces at a ratio of one 2 µm agent for each neuron in a human brain and one 8 µm hub for every ten smaller agents, then the agents will occupy about 1 cm3. That is less than one-seven-hundredth of the volume of the brain.

The Combined Toolset for WBE

We can combine technologies that apply to WBE. Biophysical voltage indicators, as developed by the Cohen lab (Harvard University), may allow micro-neuro-interfaces to register voltage changes optically. High resolution recordings on molecular ticker tape may be delivered in vivo using the IC agents. Volume microscopy after the introduction of micro-neuro-interfaces will show the agents at their locations within the tissue.

In the brain, the functions of mind are carried out by a highly parallel network of mostly silent, low-power processors – the neurons. Emulation of those functions will be more efficient on a similar computing substrate, such as so-called “neuromorphic” hardware, which mimics the architecture and function of neural networks.

There is more to achieving SIM than the emulation of mind functions. A crucial matter is that the mind, as in its original biological implementation, must have a full and rich experience within its surroundings. This is called embodiment. We extend beyond our brains, beyond our bodies and into the universe that communicates with us through sensation and interaction. Those input and output transactions must also be provided, but that is a topic that goes beyond the core steps to SIM that are presented here.

All of the WBE projects discussed here are based on a combination of present-day technologies.

In past years I have made it my responsibility to seek out and bring together the pioneers, the investigators, and to identify the technologies. At, I put together, maintain and update road maps for WBE and SIM. An essential task has been to spot key pieces of the puzzle that require urgent attention.

Now we are directly involved with and provide objective oriented coordination and communication between projects, ensuring that results will meet the requirements and will come together to achieve SIM. That accomplishment will give our species the adaptability to handle and the ability to benefit directly from our technological advances, which we will need to thrive during impending new challenges.