Tag Archives: neurons

Practice makes perfect: Dendritic Pruning & LTP

Dendritic trees

It was about two years ago today, when I began to get a clearer picture of how the cells of the brain physically change as a result of our thoughts, experiences and actions. The mind is a result of a network of billions of individual brain cells, neurons, that exchange information with each other; much of the communication between neurons occurs through structures known as dendrites. These tree-like structures emerge from the main body of a neuron, the tips of each branch exchanging information with other neurons. As we develop habits & recurring thoughts, the neurons who communicate the most with each other begin to strengthen the dendritic branches that connect them. Simultaneously, the connections between neurons who don’t often speak with one another begins to atrophy, the dendrites start to prune themselves. These processes together encompass the much larger idea of neuroplasticity, the idea that our brain physically changes and adapts.

Dendritic Pruning

One of the best examples of this concept can be seen when drendritic trees of young mammals are compared with adults, we see extensive branching on the younger brains relative to the adults, supporting the idea that with experience unused connections are pruned off. One proposed mechanism by which the brain is capable of such adaptability is long term potentiation (LTP). The speed of neural communication is largely attributed to the electro-chemical nature of the transmission, allowing for large chunks of information to be rapidly shared across networks of millions of cells every second. LTP is a specific pattern of signaling between neurons where hundreds of bursts of electrical currents of a particular frequency are sent between two neurons; resulting in enhanced communication between the two neurons and strengthening of the dendrites involved, from that point onward. There’s a decent amount of speculation currently, looking to LTP as the mechanism by which our neurons prune their dendritic trees. What this means for you & me: the more we repeat an action or thought, the more the neurons involved in that process communicate with one other, resulting in a streamlining & strengthening of the connections between them; by the same token, routine will cause the number of neurons who can communicate with each other to degrade, possibly limiting what we can learn and understand as we age.

A: Neuron of Child | B: Neuron of Adult

More than ever before, we can observe how our physical minds change as a result of our actions and have a measurable candidate for the mechanism behind this adaptability. If the 20th century belonged to physics, the last several decades to genomics, it may not be a stretch to see the recent future of science be dominated with answering the questions of neuroplasticity and our minds as a physical structure.

Citations:
Yi Zuo, Guang Yang, Elaine Kwon & Wen-Biao Gan (2005). Long-term sensory deprivation prevents dendritic spine loss in primary somatosensory cortex Nature, 436 : 10.1038/nature0371
Kelly D. Hartle, Matthew S. Jeffers, Tammy L. Ivanc (2010). Changes in dendritic morphology and spine density in motor cortex of the adult rat after stroke during infancy. Synapse, 9999 (9999A) : 10.1002/syn.20767
Daniel McGowan (2006). Pruning processes Nature Reviews Neuroscience : 10.1038/nrn1997

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Filed under Neurophysiology, Neuroscience

BOLD fMRI, a clear new view of the brain

Hemoglobin carries the oxygen to our cells, which use it as energy. Our neurons use incredible amounts of energy when they fire electrical currents, which create our thoughts, actions, memories and senses. When a neuron fires, it takes up large amounts of oxygen from nearby hemoglobin molecules. As oxygen leaves it causes a change in the iron-rich structure of hemoglobin, which can be detected by Magnetic Resonance Imaging.

Blood-oxygen-level dependent fMRI allows us to see where in the brain oxygen is being consumed, correlating it with nearby neurons firing. This allows us now to literally map the brain based on activity. Which part of the brain is active during certain thoughts? Memories? Motor actions? BOLD fMRI can and has answered many of these questions. Contemporary studies with this technology has touched the edge of what we once thought possible, from algorithms that can scan our brains to guess what our eyes are seeing; to showing how meditation decreases the number of neurons firing in random areas of the mind.  As we begin to settle into a comfortable pace of understanding and uncovering the functions of the brain in-terms of neurotransmitters and receptors, functional imaging of the mind provides a new horizon of understanding the mind as a complete neural network.

Citation:
Aguirre, G. (2002). Experimental Design and the Relative Sensitivity of BOLD and Perfusion fMRI NeuroImage, 15 (3), 488-500 DOI: 10.1006/nimg.2001.0990
Kay KN, Naselaris T, Prenger RJ, & Gallant JL (2008). Identifying natural images from human brain activity. Nature, 452 (7185), 352-5 PMID: 18322462

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Filed under Neuroimaging, Neurophysiology, Neuroscience