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Mind uploading, also known as whole brain emulation (WBE), is the hypothetical futuristic process of scanning a physical structure of the brain accurately enough to create an emulation of the mental state (including long-term memory and “self”) and copying it to a computer in a digital form. The computer would then run a simulation of the brain’s information processing, such that it would respond in essentially the same way as the original brain and experience having a sentient conscious mind.[1][2][3]
Substantial mainstream research in related areas is being conducted in animal brain mapping and simulation, development of faster supercomputers, virtual reality, brain–computer interfaces, connectomics, and information extraction from dynamically functioning brains.[4] According to supporters, many of the tools and ideas needed to achieve mind uploading already exist or are currently under active development; however, they will admit that others are, as yet, very speculative, but say they are still in the realm of engineering possibility.
Mind uploading may potentially be accomplished by either of two methods: copy-and-upload or copy-and-delete by gradual replacement of neurons (which can be considered as a gradual destructive uploading), until the original organic brain no longer exists and a computer program emulating the brain takes control over the body. In the case of the former method, mind uploading would be achieved by scanning and mapping the salient features of a biological brain, and then by storing and copying, that information state into a computer system or another computational device. The biological brain may not survive the copying process or may be deliberately destroyed during it in some variants of uploading. The simulated mind could be within a virtual reality or simulated world, supported by an anatomic 3D body simulation model. Alternatively the simulated mind could reside in a computer inside (or either connected to or remotely controlled) a (not necessarily humanoid) robot or a biological or cybernetic body.[5]
Among some futurists and within the part of transhumanist movement, mind uploading is treated as an important proposed life extension technology. Some believe mind uploading is humanity’s current best option for preserving the identity of the species, as opposed to cryonics. Another aim of mind uploading is to provide a permanent backup to our “mind-file”, to enable interstellar space travels, and a means for human culture to survive a global disaster by making a functional copy of a human society in a computing device. Whole brain emulation is discussed by some futurists as a “logical endpoint”[5] of the topical computational neuroscience and neuroinformatics fields, both about brain simulation for medical research purposes. It is discussed in artificial intelligence research publications as an approach to strong AI (Artificial general intelligence) and to at least weak superintelligence. Another approach is seed AI, which wouldn’t be based on existing brains. Computer-based intelligence such as an upload could think much faster than a biological human even if it were no more intelligent. A large-scale society of uploads might, according to futurists, give rise to a technological singularity, meaning a sudden time constant decrease in the exponential development of technology.[6] Mind uploading is a central conceptual feature of numerous science fiction novels, films, and games.
Overview
Neuron anatomical modelSimple artificial neural network
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The human brain contains, on average, about 86 billion nerve cells called neurons,[7] each individually linked to other neurons by way of connectors called axons and dendrites. Signals at the junctures (synapses) of these connections are transmitted by the release and detection of chemicals known as neurotransmitters. The established neuroscientific consensus is that the human mind is largely an emergent property of the information processing of this neural network.[8]
Neuroscientists have stated that important functions performed by the mind, such as learning, memory, and consciousness, are due to purely physical and electrochemical processes in the brain and are governed by applicable laws. For example, Christof Koch and Giulio Tononi wrote in IEEE Spectrum:
Consciousness is part of the natural world. It depends, we believe, only on mathematics and logic and on the imperfectly known laws of physics, chemistry, and biology; it does not arise from some magical or otherworldly quality.[9]
The concept of mind uploading is based on this mechanistic view of the mind, and denies the vitalist view of human life and consciousness.[10]
Eminent computer scientists and neuroscientists have predicted that specially programmed[clarification needed] computers will be capable of thought and even attain consciousness, including Koch and Tononi,[9] Douglas Hofstadter,[11] Jeff Hawkins,[11] Marvin Minsky,[12] Randal A. Koene, Alan Turing, and Rodolfo Llinás.[13]
However, even though uploading is dependent upon such a general capability, it is conceptually distinct from general forms of AI in that it results from dynamic reanimation of information derived from a specific human mind so that the mind retains a sense of historical identity (other forms are possible but would compromise or eliminate the life-extension feature generally associated with uploading). The transferred and reanimated information would become a form of artificial intelligence, sometimes called an infomorph or “noömorph”.[citation needed]
Many theorists have presented models of the brain and have established a range of estimates of the amount of computing power needed for partial and complete simulations.[5][citation needed] Using these models, some have estimated that uploading may become possible within decades if trends such as Moore’s law continue.[14]
Theoretical benefits and applications
“Immortality” or backup
Main article: Digital immortality
In theory, if the information and processes of the mind can be disassociated from the biological body, they are no longer tied to the individual limits and lifespan of that body. Furthermore, information within a brain could be partly or wholly copied or transferred to one or more other substrates (including digital storage or another brain), thereby – from a purely mechanistic perspective – reducing or eliminating “mortality risk” of such information. This general proposal was discussed in 1971 by biogerontologist George M. Martin of the University of Washington.[15]
Space exploration
An “uploaded astronaut” could be used instead of a “live” astronaut in human spaceflight, avoiding the perils of zero gravity, the vacuum of space, and cosmic radiation to the human body. It would allow for the use of smaller spacecraft, such as the proposed StarChip, and it would enable virtually unlimited interstellar travel distances.[16]
Relevant technologies and techniques
The focus of mind uploading, in the case of copy-and-transfer, is on data acquisition, rather than data maintenance of the brain. A set of approaches known as loosely coupled off-loading (LCOL) may be used in the attempt to characterize and copy the mental contents of a brain.[17] The LCOL approach may take advantage of self-reports, life-logs and video recordings that can be analyzed by artificial intelligence. A bottom-up approach may focus on the specific resolution and morphology of neurons, the spike times of neurons, the times at which neurons produce action potential responses.
Computational complexity
Estimates of how much processing power is needed to emulate a human brain at various levels, along with the fastest and slowest supercomputers from TOP500 and a $1000 PC. Note the logarithmic scale. The (exponential) trend line for the fastest supercomputer reflects a doubling every 14 months. Kurzweil believes that mind uploading will be possible at neural simulation, while the Sandberg & Bostrom report is less certain about where consciousness arises.[18]
Advocates of mind uploading point to Moore’s law to support the notion that the necessary computing power is expected to become available within a few decades. However, the actual computational requirements for running an uploaded human mind are very difficult to quantify, potentially rendering such an argument specious.
Regardless of the techniques used to capture or recreate the function of a human mind, the processing demands are likely to be immense, due to the large number of neurons in the human brain along with the considerable complexity of each neuron.
In 2004, Henry Markram, lead researcher of the “Blue Brain Project“, stated that “it is not [their] goal to build an intelligent neural network”, based solely on the computational demands such a project would have.[19]
It will be very difficult because, in the brain, every molecule is a powerful computer and we would need to simulate the structure and function of trillions upon trillions of molecules as well as all the rules that govern how they interact. You would literally need computers that are trillions of times bigger and faster than anything existing today.[20]
Five years later, after successful simulation of part of a rat brain, Markram was much more bold and optimistic. In 2009, as director of the Blue Brain Project, he claimed that “A detailed, functional artificial human brain can be built within the next 10 years.”[21]
Required computational capacity strongly depend on the chosen level of simulation model scale:[5]
| Level | CPU demand (FLOPS) | Memory demand (Tb) | $1 million super‐computer (Earliest year of making) |
| Analog network population model | 1015 | 102 | 2008 |
| Spiking neural network | 1018 | 104 | 2019 |
| Electrophysiology | 1022 | 104 | 2033 |
| Metabolome | 1025 | 106 | 2044 |
| Proteome | 1026 | 107 | 2048 |
| States of protein complexes | 1027 | 108 | 2052 |
| Distribution of complexes | 1030 | 109 | 2063 |
| Stochastic behavior of single molecules | 1043 | 1014 | 2111 |
Simulation model scale
A high-level cognitive AI model of the brain architecture is not required for brain emulationSimple neuron model: Black-box dynamic non-linear signal processing systemMetabolism model: The movement of positively charged ions through the ion channels controls the membrane electrical action potential in an axon.
Since the function of the human mind and how it might arise from the working of the brain’s neural network, are poorly understood issues, mind uploading relies on the idea of neural network emulation. Rather than having to understand the high-level psychological processes and large-scale structures of the brain, and model them using classical artificial intelligence methods and cognitive psychology models, the low-level structure of the underlying neural network is captured, mapped and emulated with a computer system. In computer science terminology,[dubious – discuss] rather than analyzing and reverse engineering the behavior of the algorithms and data structures that resides in the brain, a blueprint of its source code is translated to another programming language. The human mind and the personal identity then, theoretically, is generated by the emulated neural network in an identical fashion to it being generated by the biological neural network.
On the other hand, a molecule-scale simulation of the brain is not expected to be required, provided that the functioning of the neurons is not affected by quantum mechanical processes. The neural network emulation approach only requires that the functioning and interaction of neurons and synapses are understood. It is expected that it is sufficient with a black-box signal processing model of how the neurons respond to nerve impulses (electrical as well as chemical synaptic transmission).
A sufficiently complex and accurate model of the neurons is required. A traditional artificial neural network model, for example multi-layer perceptron network model, is not considered as sufficient. A dynamic spiking neural network model is required, which reflects that the neuron fires only when a membrane potential reaches a certain level. It is likely that the model must include delays, non-linear functions and differential equations describing the relation between electrophysical parameters such as electrical currents, voltages, membrane states (ion channel states) and neuromodulators.
Since learning and long-term memory are believed to result from strengthening or weakening the synapses via a mechanism known as synaptic plasticity or synaptic adaptation, the model should include this mechanism. The response of sensory receptors to various stimuli must also be modelled.
Furthermore, the model may have to include metabolism, i.e. how the neurons are affected by hormones and other chemical substances that may cross the blood–brain barrier. It is considered likely that the model must include currently unknown neuromodulators, neurotransmitters and ion channels. It is considered unlikely that the simulation model has to include protein interaction, which would make it computationally complex.[5]
A digital computer simulation model of an analog system such as the brain is an approximation that introduces random quantization errors and distortion. However, the biological neurons also suffer from randomness and limited precision, for example due to background noise. The errors of the discrete model can be made smaller than the randomness of the biological brain by choosing a sufficiently high variable resolution and sample rate, and sufficiently accurate models of non-linearities. The computational power and computer memory must however be sufficient to run such large simulations, preferably in real time.
Scanning and mapping scale of an individual
When modelling and simulating the brain of a specific individual, a brain map or connectivity database showing the connections between the neurons must be extracted from an anatomic model of the brain. For whole brain simulation, this network map should show the connectivity of the whole nervous system, including the spinal cord, sensory receptors, and muscle cells. Destructive scanning of a small sample of tissue from a mouse brain including synaptic details is possible as of 2010.[22]
However, if short-term memory and working memory include prolonged or repeated firing of neurons, as well as intra-neural dynamic processes, the electrical and chemical signal state of the synapses and neurons may be hard to extract. The uploaded mind may then perceive a memory loss of the events and mental processes immediately before the time of brain scanning.[5]
A full brain map has been estimated to occupy less than 2 x 1016 bytes (20,000 TB) and would store the addresses of the connected neurons, the synapse type and the synapse “weight” for each of the brains’ 1015 synapses.[5][failed verification] However, the biological complexities of true brain function (e.g. the epigenetic states of neurons, protein components with multiple functional states, etc.) may preclude an accurate prediction of the volume of binary data required to faithfully represent a functioning human mind.
Serial sectioning
A possible method for mind uploading is serial sectioning, in which the brain tissue and perhaps other parts of the nervous system are frozen and then scanned and analyzed layer by layer, which for frozen samples at nano-scale requires a cryo-ultramicrotome, thus capturing the structure of the neurons and their interconnections.[23] The exposed surface of frozen nerve tissue would be scanned and recorded, and then the surface layer of tissue removed. While this would be a very slow and labor-intensive process, research is currently underway to automate the collection and microscopy of serial sections.[24] The scans would then be analyzed, and a model of the neural net recreated in the system that the mind was being uploaded into.
There are uncertainties with this approach using current microscopy techniques. If it is possible to replicate neuron function from its visible structure alone, then the resolution afforded by a scanning electron microscope would suffice for such a technique.[24] However, as the function of brain tissue is partially determined by molecular events (particularly at synapses, but also at other places on the neuron’s cell membrane), this may not suffice for capturing and simulating neuron functions. It may be possible to extend the techniques of serial sectioning and to capture the internal molecular makeup of neurons, through the use of sophisticated immunohistochemistry staining methods that could then be read via confocal laser scanning microscopy. However, as the physiological genesis of ‘mind’ is not currently known, this method may not be able to access all of the necessary biochemical information to recreate a human brain with sufficient fidelity.
Brain imaging
Process from MRI acquisition to whole brain structural network[25]Magnetoencephalography
It may be possible to create functional 3D maps of the brain activity, using advanced neuroimaging technology, such as functional MRI (fMRI, for mapping change in blood flow), magnetoencephalography (MEG, for mapping of electrical currents), or combinations of multiple methods, to build a detailed three-dimensional model of the brain using non-invasive and non-destructive methods. Today, fMRI is often combined with MEG for creating functional maps of human cortex during more complex cognitive tasks, as the methods complement each other. Even though current imaging technology lacks the spatial resolution needed to gather the information needed for such a scan, important recent and future developments are predicted to substantially improve both spatial and temporal resolutions of existing technologies.[26]
Brain simulation
Main article: Brain simulation
There is ongoing work in the field of brain simulation, including partial and whole simulations of some animals. For example, the C. elegans roundworm, Drosophila fruit fly, and mouse have all been simulated to various degrees.[citation needed]
The Blue Brain Project by the Brain and Mind Institute of the École Polytechnique Fédérale de Lausanne, Switzerland is an attempt to create a synthetic brain by reverse-engineering mammalian brain circuitry.