Each person has their own brain. It doesn't matter how one uses it, but precisely this organ allows us to exist as human beings. It has many essential functions that essentially control the entire organism. For us, its main function is the ability to create, maintain, and restore our consciousness. Essentially, it's us. Every time we fall asleep, we disappear for a while. And when we wake up, we recognize ourselves and start existing again. But sometimes the brain can be damaged or even die. In this case, we cannot recover. But we really want to. There are several ways to do this, but I want to consider in this technical assignment precisely the path of creating an artificial brain and gradually transferring consciousness to this brain, in order to slightly prolong our lives and also expand its capabilities by expanding its possibilities. For example, controlling other parts of the body remotely in the event of the loss of such a capability by the physical brain, or with various digital devices. Forward.
Project Goals
The main goal of the project is to create a technical specification for the creation of an artificial brain based on semiconductor elements deposited on silicon plates, interconnected by radio communication. This connection should serve as a "template" for recording signals received from the biological brain for the purpose of duplicating its neural connections and returning these reactions to the biological brain instead of parts of the biological brain that have lost the ability to do so.
Necessary Steps
To create an artificial brain, 86 billion artificial neurons are required. Each of them must control 10,000 synapses.
First, it is necessary to develop a model of a neuron on silicon plates. Neurons on silicon plates can be made in the form of electronic structures that mimic the behavior of biological neurons. Each neuron must have its nucleus, axons for signal transmission, and dendrites for receiving signals from other neurons.
Synapses can be made in the form of electronic structures that store information about another synapse with which it must establish a connection (address, frequency, and access codes), the strength of this connection (a calculator that decides whether to transmit the received signal and whether to strengthen or weaken the connection). The nucleus must perform the service tasks of the neuron's functioning. The connection between synapses must be established using radio communication using CDMA technology to ensure communication between different plates.
Axons:In biological neurons, axons transmit electrical impulses (action potentials) away from the cell body to other neurons or target cells.
Electronic structures emulating axons need to efficiently propagate signals while maintaining signal integrity.
One approach is to use conductive materials such as copper or doped silicon to create pathways for signal transmission.
Signal amplification and regeneration may be necessary to maintain signal strength over long distances, similar to the role of voltage-gated ion channels in biological axons.
Axon terminals could be designed to interface with dendrites of other neurons, facilitating signal transmission between neurons.
Dendrites: Dendrites in biological neurons receive signals from axon terminals of other neurons.
Electronic dendrites must be capable of receiving and integrating incoming signals, similar to the dendritic integration of synaptic inputs in biological neurons.
They may incorporate analog or digital circuitry to process incoming signals, such as amplification, filtering, or spike generation.
Dendritic branches could be designed to connect to multiple axons, allowing for convergence of inputs from multiple sources.
Plasticity mechanisms, such as synaptic strengthening or weakening, could be implemented to simulate learning and memory processes occurring at dendritic synapses.
Nuclei: The nucleus of a biological neuron contains the genetic material and regulates cellular functions.
Electronic structures emulating nuclei may involve control circuits responsible for coordinating the neuron's activities and regulating gene expression, analogous to the role of transcription factors in biological nuclei.
They may incorporate control logic, memory elements, and communication interfaces to coordinate the neuron's responses to incoming signals and modulate synaptic connections.
Nuclei could also be responsible for tasks such as self-repair, energy management, and overall system integration within the artificial brain.
Detailed Analysis
4.1. Radio Communication:
The address of each dendrite must be encoded in a 64-bit format.
Each dendrite must also be able to receive signals at a unique frequency, initially unknown to it. All dendrites must be able to receive signals at the base frequency. During the first contact, the axon must take a free frequency and transmit it to the dendrite with a specific address at the base frequency. These frequencies should be in the range of 100MHz - 2.5GHz. Since the maximum operating frequency of the brain is about 200 Hz, synchronous transmission of signals by all axons with a frequency of 10 kHz and a duration of 50 microseconds will be sufficient. At each step of establishing connections between neurons, communication can only occur between 1 axon and 1 dendrite at the base frequency. This is sufficient because according to the latest data, no more than 1000 new connections are formed in the human brain per second.
One alternative approach for implementing radio communication in the context described would involve a frequency-hopping spread spectrum (FHSS) technique. FHSS is a method commonly used in wireless communication systems to improve reliability and security by rapidly switching frequencies over a wide band. Here's how it could be implemented for the scenario outlined:
Frequency Allocation:
Each dendrite is assigned a unique 64-bit address encoded in a specific format.
Initially, all dendrites are capable of receiving signals at the base frequency, which is within the range of 100MHz - 2.5GHz.
Frequency Hopping:
During the initial contact between an axon and a dendrite, the axon selects a free frequency within the specified range.
The axon transmits this frequency information to the dendrite using the base frequency.
The dendrite then tunes to the specified frequency to establish communication with the axon.
Synchronous Transmission:
All axons transmit signals synchronously with a frequency of 10 kHz and a duration of 50 microseconds.
This synchronous transmission ensures that all axons are operating in coordination, facilitating efficient communication across the network.
Connection Establishment:
At each step of establishing connections between neurons, communication occurs between one axon and one dendrite at the base frequency.
This ensures that each connection is established without interference from other axons or dendrites.
Limited Bandwidth Utilization:
By using FHSS, the system can utilize a wide range of frequencies within the specified range.
This allows for efficient utilization of available bandwidth while minimizing the risk of interference and congestion.
4.2. Connection Strength:
The strength of the connection can be amplified from 0 (if the connection disappears) to 1 (if it works with each signal). After establishing the connection, it should be weak (1/21 in size). With each new signal, it should be amplified by 1/21. At the same time, there should be a reverse process of weakening the connection over time or with the simultaneous action of another axon (I do not know how it works yet). Accordingly, when a signal appears on the dendrite of a neuron, it must be transmitted through the axon of the dendrite only after a certain number of repetitions of the signal. For example, with a weak connection - after 21 signals at the input - 1 at the output, while the connection should be strengthened by 1/21. In case of degradation and disappearance of the connection, the dendrite must return to the base frequency.
4.3. Initial Establishment of Connections:
It can go in two ways. First, it can be the emulation of brain development from an embryo to a person by sending signals, external and internal, from virtual organs. Secondly, it can be the transfer of states of neural connections from the existing brain using as yet undetermined scanners.
4.4. Means of Communication with the Artificial Brain:
For the existence of an artificial brain, a device must be created that will perform the functions of sensory organs. For example, if it becomes necessary to replace a small part of the brain with an artificial one, then after recording the state of the connections of this part on the artificial brain, it is necessary to constantly collect signals from neighboring synapses that contacted the biological part at a frequency of 10 kHz and transmit them to the input synapses of the artificial brain, as well as return signals to the biological brain when they appear in the artificial brain. For this, synapses that interact with the artificial brain must be made in the same way as in the artificial brain. At the same time, another part of the device must be equipped with synapses of the biological brain. The study of connections of neighboring synapses must be carried out using high-frequency current as when studying the logistics of computer networks.
Outcome
The implementation of this technical assignment will not allow for an easy transfer of consciousness to a new carrier. But the creation of such a device will allow for necessary research and also help people replace some parts of the brain with artificial ones. In the future, even to a complete replacement of the brain with an artificial one.
Functional Requirements for a Brain reading machine:
Measurement of Neuron Parameters:
Resting Potential
Threshold Potential
Action Potential Amplitude
Measurement of Synapse Parameters:
Synapse Type (excitatory, inhibitory)
Synaptic Strength
Coordinates of Presynaptic and Postsynaptic Parts
Measurement of Neurotransmitter Parameters:
Neurotransmitter Name
Neurotransmitter Concentration
Measurement of Receptor Parameters:
Receptor Name
Receptor Concentration
Measurement of Glial Cell Parameters:
Glial Cell Type
Glial Cell Function
Assuming we have a frozen brain, how can we use a laser to read the above information, slice the read layer, and remove the remnants?
Algorithm of the System Operation
Fluorescent Labeling:
The brain sample is treated with fluorescent markers that specifically bind to target molecules (neurotransmitters, receptors, etc.).
Laser Scanning:
A high-resolution laser scanner reads fluorescent signals from the brain surface. The laser beam induces fluorescence from the labels, and detectors capture the signal intensity.
The following parameters are analyzed:
Resting Potential and Threshold Potential: Through fluorescent markers sensitive to ion concentrations.
Action Potential Amplitude: By changes in fluorescent signal sensitive to voltage.
Synapse Type: Through different fluorescent labels for excitatory and inhibitory synapses.
Concentration of Neurotransmitters and Receptors: By the intensity of the respective fluorescent signals.
Type and Function of Glial Cells: By specific fluorescent markers.
Layer Removal:
After scanning, the tissue layer is removed using laser ablation.
The laser system carefully removes the scanned layer to expose the next tissue layer.
Cycle Repetition:
The process of scanning and layer removal is repeated for subsequent layers of the brain.
Technologies and Equipment
Laser Scanner:
A high-resolution laser for reading fluorescent signals.
Detectors to capture fluorescence intensity.
Fluorescent Markers:
Specific markers for neurons, synapses, neurotransmitters, receptors, and glial cells.
Laser Ablation System:
A laser setup for precise slicing and removal of tissue layers.
Example Workflow
Fluorescent Processing:
The brain sample is infused with fluorescent markers.
Scanning:
The laser scans the surface, capturing fluorescent signals and transmitting data to a computer for analysis.
Ablation:
The laser removes the scanned tissue layer, preparing the next layer for scanning.
Analysis and Recording:
Collected data are analyzed and recorded for further use.
Conclusion
This method provides a streamlined and targeted approach to reading parameters from the surface of a frozen brain with subsequent layer removal. The use of fluorescent markers and laser scanning efficiently captures the necessary parameters, while laser ablation ensures precise removal of scanned layers.
