Mind uploading
Whole brain emulation or mind uploading (sometimes called mind transfer) is the hypothetical process of transferring or copying a conscious mind from a brain to a non-biological substrate by scanning and mapping a biological brain in detail and copying its state into a computer system or another computational device. The computer would have to run a simulation model so faithful to the original that it would behave in essentially the same way as the original brain, or for all practical purposes, indistinguishably.The simulated mind is assumed to be part of a virtual reality simulated world, supported by an anatomic 3D body simulation model. Alternatively, the simulated mind could be assumed to reside in a computer inside (or connected to) a humanoid robot or a biological body, replacing its brain.Whole brain emulation is discussed by futurists as a "logical endpoint" 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. Among futurists and within the transhumanist movement it is an important proposed life extension technology, originally suggested in biomedical literature in 1971.It is a central conceptual feature of numerous science fiction novels and films.Whole brain emulation is considered by some scientists as a theoretical and futuristic but possible technology,although mainstream research funders and scientific journals remain skeptical. Several contradictory predictions have been made about when a whole human brain can be emulated; some of the predicted dates have already passed. Substantial mainstream research and development are however being done in relevant areas including development of faster super computers, virtual reality, brain-computer interfaces, animal brain mapping and simulation, connectomics and information extraction from dynamically functioning brains.The question whether an emulated brain can be a human mind is debated by philosophers, and may be viewed as impossible by those who hold a dualistic view of the human mind, which is common in many religions.
Overview
The human brain contains about 100 billion nerve cells called neurons, 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 neuroscientists consensus is that the human mind is largely an emergent property of the information processing of this neural network.Importantly, 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."The concept of mind uploading is based on this mechanistic view of the mind, and denies the vitalist view of human life and consciousness.Many eminent computer scientists and neuroscientists have predicted that computers will be capable of thought and even attain consciousness, including Koch and Tononi,Douglas Hofstadter, Jeff Hawkins, Marvin Minsky,Randal A.Koene,and Rodolfo Llinas.Such a machine intelligence capability might provide a computational substrate necessary for uploading.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." 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.[citation needed] Using these models, some have estimated that uploading may become possible within decades if trends such as Moore's Law continue. The prospect of uploading human consciousness in this manner raises many ilosophical questions involving identity, individuality and if the soul and mind can be defined as the information content of the brain, as well as numerous problems of medical ethics and morality of the process.1- Immortality/Backup
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 reducing or eliminating mortality risk. This general proposal appears to have been first made in the biomedical literature in 1971 by biogerontologist George M. Martin of the University of Washington.
2- SpeedupA computer-based intelligence such as an upload could potentially think much faster than a human even if it were no more intelligent. Human neurons exchange electrochemical signals with a maximum speed of about 150 meters per second, whereas the speed of light is about 300 million meters per second, about two million times faster. Also, neurons can generate a maximum of about 200 to 1000 action potentials or "spikes" per second, whereas the number of signals per second in modern[when?] computer chips is about 3 GHz[citation needed] (about 20 million times greater) and expected to increase by at least a factor 100. Therefore, even if the computer components responsible for simulating a brain were not significantly smaller than a biological brain, and even if the temperature of these components was not significantly lower, Eliezer Yudkowsky of the Singularity Institute for Artificial Intelligence calculates a theoretical upper bound for the speed of a future artificial neural network. It could in theory run about 1 million times faster than a real brain, experiencing about a year of subjective time in only 31 seconds of real time.However, in practice this massively parallel implementation would require separate computational units for each of the hundred billion neurons and each of the hundred trillion synapses. That requires an enormously large computer or artificial neural network in comparison with today's super-computers.In a less futuristic implementation, time-sharing would allow several neurons to be emulated sequentially by the same computational unit. Thus the size of the computer would be restricted, but the speedup would be lower. Assuming that cortical minicolumns organized into hypercolumns are the computational units, mammal brains can be emulated by today's super computers, but with slower speed than in a biological brain.
3- Multiple/parallel existence
Another concept explored in science fiction is the idea of more than one running "copy" of a human mind existing at once. Such copies could potentially allow an "individual" to experience many things at once, and later integrate the experiences of all copies into a central mentality at some point in the future, effectively allowing a single sentient being to "be many places at once" and "do many things at once"; this concept has been explored in fiction. Such partial and complete copies of a sentient being raise interesting questions regarding identity and individuality.
Relevant technologies and techniques1- Computational capacity
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", has stated that "it is not goal to build an intelligent neural network", based solely on the computational demands such a project would have.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.Five years later, after successful simulation of part of a rat brain, the same scientist was much more bold and optimistic. In 2009, when he was director of the Blue Brain Project, he claimed that A detailed, functional artificial human brain can be built within the next 10 years
2- Simulation model scale
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, 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 modeled.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.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.
3- 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. This network map should show the connectivity of the whole nervous system, including the spinal cord, sensory receptors, and muscle cells.Destructive scanning of the human brain including synaptic details is possible as of end of 2010.A full brain map should also reflect the synaptic strength (the "weight") of each connection. It is unclear if the current technology allows that.It is proposed that short-term memory and working memory is prolonged or repeated firing of neurons, as well as intra-neural dynamic processes. Since the electrical and chemical signal state of the synapses and neurons may be hard to extract, the uploading might result in that the uploaded mind perceives a memory loss of the events immediately before the time of brain scanning.A full brain map would occupy less than 2 x 1016 bytes (20000 TB) and would store the addresses of the connected neurons, the synapse type and the synapse "weight" for each of the brains' 1015 synapses.
4- 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, thus capturing the structure of the neurons and their interconnections.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.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.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 which 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.
5- Brain imaging
It may also 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.
6- Brain-computer interfaces
Brain-computer interfaces (BCI) (also known as neuro-computer interfaces, direct neuron interfaces or cerebral interfaces) constitute one of the hypothetical technologies for the reading of information in the dynamically functioning brain[citation needed]. The production of this or a similar device may be essential to the possibility of mind uploading a living human subject.
Current research
An artificial neural network described as being "as big and as complex as half of a mouse brain" was run on an IBM blue gene supercomputer by a University of Nevada research team in 2007. A simulated time of one second took ten seconds of computer time. The researchers said they had seen "biologically consistent" nerve impulses flowed through the virtual cortex. However, the simulation lacked the structures seen in real mice brains, and they intend to improve the accuracy of the neuron model.Blue Brain is a project, launched in May 2005 by IBM and the Swiss Federal Institute of Technology in Lausanne, with the aim to create a computer simulation of a mammalian cortical column, down to the molecular level.The project uses a supercomputer based on IBM's Blue Gene design to simulate the electrical behavior of neurons based upon their synaptic connectivity and complement of intrinsic membrane currents. The initial goal of the project, completed in December 2006,was the simulation of a rat neocortical column, which can be considered the smallest functional unit of the neocortex (the part of the brain thought to be responsible for higher functions such as conscious thought), containing 10,000 neurons (and 108 synapses). Between 1995 and 2005, Henry Markram mapped the types of neurons and their connections in such a column. In November 2007,the project reported the end of the first phase, delivering a data-driven process for creating, validating, and researching the neocortical column. The project seeks to eventually reveal aspects of human cognition and various psychiatric disorders caused by malfunctioning neurons, such as autism, and to understand how pharmacological agents affect network behavior.An organization called the Brain Preservation Foundation was founded in 2010 and is offering a Brain Preservation Technology prize to promote exploration of brain preservation technology in service of humanity. The Prize, currently $106,000, will be awarded in two parts, 25% to the first international team to preserve a whole mouse brain, and 75% to the first team to preserve a whole large animal brain in a manner that could also be adopted for humans in a hospital or hospice setting immediately upon clinical death. Ultimately the goal of this prize is to generate a whole brain map which may be used in support of separate efforts to upload and possibly 'reboot' a mind in virtual space.
