🧠Neuromorphic Engineering Unit 2 – Neuroscience Fundamentals
Neuroscience fundamentals form the backbone of understanding how our brains work. From neurons and synapses to neural networks and plasticity, these concepts explain how we process information, learn, and adapt to our environment.
Neuromorphic engineering applies these principles to create artificial systems mimicking the brain's efficiency. By studying neurotransmitters, brain structure, and neural circuits, engineers can develop brain-inspired technologies for various applications, from neuroprosthetics to artificial intelligence.
Neuroscience studies the nervous system, including the brain, spinal cord, and peripheral nerves
Neurons are the primary functional units of the nervous system, responsible for processing and transmitting information
Glia are non-neuronal cells that support and maintain the nervous system (astrocytes, oligodendrocytes, and microglia)
Action potentials are electrical impulses generated by neurons to transmit information along their axons
Synapses are specialized junctions between neurons where information is transmitted through chemical or electrical signals
Neurotransmitters are chemical messengers released by neurons at synapses to communicate with other neurons (glutamate, GABA, dopamine)
Neuroplasticity refers to the brain's ability to change and adapt in response to experience, learning, and injury
Neuromorphic engineering aims to design artificial neural systems inspired by the principles of biological neural networks
Neuroanatomy Basics
The central nervous system (CNS) consists of the brain and spinal cord, while the peripheral nervous system (PNS) includes nerves that extend throughout the body
The brain is divided into several regions, each with specific functions:
Cerebral cortex: responsible for higher cognitive functions (perception, language, decision-making)
Cerebellum: involved in motor coordination and balance
The spinal cord transmits sensory and motor information between the brain and the body
White matter consists of myelinated axons that facilitate rapid information transmission, while gray matter contains neuronal cell bodies and synapses
The blood-brain barrier is a selective barrier that regulates the passage of substances between the bloodstream and the brain, maintaining a stable environment for neurons
Ventricles are fluid-filled cavities within the brain that produce and circulate cerebrospinal fluid (CSF)
Neuronal Structure and Function
Neurons have a cell body (soma) containing the nucleus and organelles, dendrites that receive input, and an axon that transmits output
Dendrites are branched extensions that receive signals from other neurons and integrate them at the soma
The axon is a long, thin process that conducts electrical signals away from the soma to other neurons or effector cells (muscles, glands)
The axon hillock is the site of action potential initiation, where the electrical signal begins
Myelin is an insulating sheath around axons that enhances signal transmission speed and efficiency
Ion channels are proteins embedded in the neuronal membrane that allow the selective passage of ions (sodium, potassium, calcium)
The resting membrane potential of a neuron is typically around -70 mV, maintained by the unequal distribution of ions across the membrane
Synaptic Transmission
Synapses can be chemical, where neurotransmitters are released, or electrical, where ions flow directly between neurons through gap junctions
In chemical synapses, the presynaptic neuron releases neurotransmitters into the synaptic cleft, which bind to receptors on the postsynaptic neuron
Neurotransmitter release is triggered by the arrival of an action potential at the presynaptic terminal, causing calcium influx and vesicle fusion
Excitatory neurotransmitters (glutamate) increase the likelihood of the postsynaptic neuron firing an action potential, while inhibitory neurotransmitters (GABA) decrease it
Neurotransmitters are cleared from the synaptic cleft by reuptake into the presynaptic neuron or degradation by enzymes
Synaptic plasticity refers to the ability of synapses to strengthen or weaken over time, underlying learning and memory (long-term potentiation, long-term depression)
Neural Networks and Circuits
Neural networks are interconnected groups of neurons that process and transmit information
Feedforward networks have unidirectional information flow from input to output, while recurrent networks have feedback loops
Parallel processing allows multiple neural pathways to process information simultaneously, enabling complex computations
Oscillations and synchronization of neural activity are important for information processing and communication between brain regions
Neuronal circuits can be excitatory, inhibitory, or modulatory, depending on the types of neurons and neurotransmitters involved
Cortical columns are vertical arrangements of neurons in the cerebral cortex that process similar information
Neuroplasticity and Learning
Neuroplasticity enables the brain to adapt and reorganize in response to experience, learning, and injury
Synaptic plasticity, including long-term potentiation (LTP) and long-term depression (LTD), underlies learning and memory formation
LTP strengthens synaptic connections through repeated activation, while LTD weakens them
Structural plasticity involves changes in neuronal morphology, such as the growth or pruning of synapses and dendrites
Critical periods are developmental windows of heightened plasticity when the brain is particularly sensitive to environmental input (visual system, language acquisition)
Adult neurogenesis is the formation of new neurons in specific brain regions throughout life, contributing to plasticity and learning
Neuroplasticity can be harnessed for rehabilitation after brain injury or stroke, as intact brain regions can compensate for damaged areas
Neurotransmitters and Neuromodulators
Neurotransmitters are chemical messengers released by neurons to transmit signals across synapses
Glutamate is the primary excitatory neurotransmitter in the CNS, involved in learning, memory, and synaptic plasticity
GABA (gamma-aminobutyric acid) is the main inhibitory neurotransmitter, regulating neuronal excitability and preventing excessive activity
Dopamine is involved in reward, motivation, and motor control, and its dysregulation is associated with disorders like Parkinson's and addiction
Serotonin modulates mood, sleep, and appetite, and is targeted by antidepressant medications (SSRIs)
Acetylcholine is involved in attention, learning, and muscle control, and its deficiency is linked to Alzheimer's disease
Norepinephrine is involved in arousal, attention, and stress response, and is part of the sympathetic nervous system
Neuromodulators are substances that modify the effects of neurotransmitters, altering neuronal excitability and synaptic transmission (endocannabinoids, neuropeptides)
Linking Neuroscience to Engineering
Neuromorphic engineering seeks to design artificial neural systems that mimic the principles and functions of biological neural networks
Artificial neural networks (ANNs) are computational models inspired by the structure and function of biological neurons and networks
ANNs consist of interconnected nodes (artificial neurons) that process and transmit information
Brain-machine interfaces (BMIs) enable direct communication between the brain and external devices, with applications in prosthetics, rehabilitation, and communication
Neuroprosthetics aim to restore or enhance sensory, motor, or cognitive functions by interfacing with the nervous system (cochlear implants, retinal prostheses)
Neuromorphic sensors and processors emulate the efficient processing and energy consumption of biological neural systems
Neurorobotics combines neuroscience, robotics, and AI to create robots with brain-inspired control systems and learning capabilities
Computational neuroscience uses mathematical models and simulations to study the function and dynamics of neural systems, informing neuromorphic designs
Neuromorphic engineering can advance our understanding of the brain by providing testable models and platforms for experimentation