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Structure of a typical neuron with Schwann cells in the peripheral nervous system. Neurons are highly specialized for the processing and transmission of cellular signals. Given the diversity of functions performed in different parts of the nervous system, there is a wide variety in their shape, size, and electrochemical properties.
Morphology is the study of the shape and structure of biological organisms, while morphogenesis is the study of the biological development of the shape and structure of organisms. Therefore, neuromorphology focuses on the specifics of the structure of the nervous system and not the process by which the structure was developed.
The first list shows number of neurons in their entire nervous system. The second list shows the number of neurons in the structure that has been found to be representative of animal intelligence. [1] The human brain contains 86 billion neurons, with 16 billion neurons in the cerebral cortex. [2] [1]
These include sensory neurons that transmute physical stimuli such as light and sound into neural signals, and motor neurons that transmute neural signals into activation of muscles or glands; however in many species the great majority of neurons participate in the formation of centralized structures (the brain and ganglia) and they receive all ...
Central nervous system neurons (17 P) E. Efferent neurons (6 P) R. Receptor cells (2 C, 4 P) Pages in category "Neurons"
Neurons are polarised cells that are specialised for the conduction of action potentials also called nerve impulses. [1] They can also synthesise membrane and protein. Neurons communicate with other neurons using neurotransmitters released from their synapses, and they may be inhibitory, excitatory or neuromodulatory. [5]
Nerve cells (often called neurons) are further classified as sensory, motor, or mixed nerves. In the central nervous system , the analogous structures are known as nerve tracts . [ 1 ] [ 2 ]
This is the basic structure used for artificial neurons, which in a neural network often looks like y i = φ ( ∑ j w i j x j ) {\displaystyle y_{i}=\varphi \left(\sum _{j}w_{ij}x_{j}\right)} where y i is the output of the i th neuron, x j is the j th input neuron signal, w ij is the synaptic weight (or strength of connection) between the ...