interconnections, share computational loads, learn from past events, process sensory data, and do motor functions. All of these can be boiled down to this worker bee module. Describing the next layer of specification, neurons can be grouped into four functions, sensors neurons that interface with the senses, interneurons in the brain that focus on computation and learning, interneurons in the central nervous system that focus on connections and signal processing of the information being transported, and motor neurons that focus on motor control. To accomplish many activities requires two or more of these functional neuron categories to work together. Note that none of these functions capture the unique qualities found in human beings or the special qualities that are part of humans’ Imago Dei charter. b. structural classification Structural classification (Fig. 18) captures the number of connections a type of neuron can have. The three classes are unipolar and pseudo unipolar, bipolar, and multipolar. A unipolar neuron has a single dendrite. A bipolar neuron has one dendrite and one axon. Multipolar neurons are typical in the nervous system and have long axons. This type of architectural classification approach groups neurons by their physiology. Neuroscience research is actively working to characterize neuron operation neurons when they can be exposed in their operational mode. In contrast to functional descriptions, this structural taxonomy highlights the observable features accessible by physical observation. Biological neuron structure takes advantage of the three-dimensional space where they exist to make connections. Each structural classification does the same basic function of transferring information through the organism, with each also doing signal conditioning or computational processing of the information. Unipolar neurons exist in invertebrates like insects but not in humans. They are part of gland and muscle function. Pseudo-unipolar neurons exist as sensory neurons. Their primary function is to route sensor data back to the brain for processing. Bipolar neurons represent the classical structure of a neuron in one input node via the dendrite and one output node with the axon and synapses. Multipolar neurons are the most common type of neuron and are heavily populated in the central nervous system. This diversity in structural options for the neuron shows how flexible its general capability can be utilized to serve many functions (Ludwig 2023). 3. Biological versus artificial neuron comparison The discussion in the architecture framework section introduced the comparison of biological and artificial neurons, thinking within the application context of neural networks. Tab. 2 shows the similarities and differences between these two approaches. • For the material layer, biological neurons leverage biomolecules that form nucleotides. Their physical properties are altered by adding elements like phosphate groups. The materials of artificial neurons center around semiconductors. Physical properties can be altered by doping the semiconductor substrate in specific locations when building the correct order of materials via material deposition, one stage at a time. • For the components and devices layer, there are two parts: bdd BDD Neuron Functional Classification Neuron Function <<block>> Sensory Neuron <<block>> Interneuron - Brain <<block>> Motor Neuron <<block>> <<system>> Neuron Functional Classifications parts : Motor Neuron {unique} : Interneuron - Brain {unique} : Sensory Neuron {unique} : Interneuron - CNS {unique} <<block>> Interneuron - CNS Figure 17. Neuron functional classifications. bdd BDD Neuron Structural Classifications Neuron Structure <<block>> Unipolar and Pseudo Unipolar <<block>> Bipolar <<block>> Multipolar <<block>> Neuron Structural Classifications parts : Unipolar and Pseudo Unipolar {unique} : Bipolar {unique} : Multipolar {unique} Figure 18. Neuron structural classifications. ELEMENT BIOLOGICAL NEURON ARTIFICIAL NEURON Material Biomolecules Semiconductors Component Proteins Doping, Device Physics Device Receivers, Transmitters, Ligands Transistors Layout Cell Layout Chip Packaging Receive Connect Dendrites Crossbar Interconnections Transmit Connect Axons Crossbar Interconnections Transmit Synapse Signal Transmitters Transmit Protocol Receive Dendrite Signal Receptors Receive Protocol Memory Nerve Body Embedded Local Memory CPU Nerve Body and Axons Microcontroller, Processing Unit Form Factor Modular Neuron Nerve Cell Neuromorphic Chip Energy External Chemical (e.g., ATP) Energy External Electrical Energy Table 2. Biological vs. Artificial Neuron Comparison JOHANSEN Human brain function 2023 ICC 302
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