Coincidence is a peculiar thing. We typically think of a coincidence as the occurrence of two events that happen to occur at the same time, but that have no underlying connection. We all experience coincidences throughout our lives, but rarely attribute any meaning or purpose to them. If, for example, your phone rings at the exact moment that you’re reaching for it, you may be amazed at the coincidence, but you realize that reaching for your phone is not what caused it to ring. Likewise, it is unlikely that the phone will ring the next time you reach for it. These coincidences occur all the time, and we typically brush them off as being completely insignificant. For the brain, however, coincidence carries much more meaning and has far greater significance.

On Monday, we posted an article about how magnesium supplement may help prevent or reverse age-related dementia and Alzheimer’s disease. Although the researchers that performed this study do not know exactly how increasing Mg2+ in the diet (and ultimately the brain) is able to help improve learning and memory, neuroscience studies have shown that Mg2+ plays a critical role in helping neurons form memories through “coincidence detection.” One of the major theories of how neurons in the brain store information is through a process called long term potentiation (LTP). In our previous post, we explained how neurons form synaptic connections with each other and how those connections are strengthened when new memories are formed. But in a brain of 86 billion neurons and 100 trillion synapses, how do neurons know which connections should be strengthened?

In 1949, the psychologist Donald Hebb postulated that if two neurons were activated at the same time, the connections (i.e. synapses) between them would be strengthened through LTP. Conversely, if the neurons were not activated within a certain time window, their connections would be weakened. “Hebbian learning,” as it is now known, is one of the classical theories of how neurons code new memories. Magnesium plays a fundamental role in detecting when two neurons are activated at the same time, a phenomenon called “coincidence detection,” which is described in the following schematic:

The figure below shows a cartoon of how neuroscientists think magnesium helps “detect” when two neurons were activated at the same time. When NeuronThe functional unit of the nervous system, a nerve cell that... More A talks to Neuron B, glutamateThe principal excitatory neurotransmitter in the nervous sys... More binds to the NMDA channel and opens it. However, no LTP occurs because the magnesium ion blocks the channel! If Neuron B is activated, magnesium unblocks the channel but since Neuron A is not active, no glutamate is bound and the channel does not open. Only when both Neuron A and Neuron B are activated does the NMDA receptor become activated: magnesium unblocks the channel and glutamate opens the channel. In this way, the NMDA receptor acts as a “coincidence detector” that detects the simultaneous activation of both Neuron A and Neuron B.  As Donald Hebb hypothesized, when both neurons are activated at the same time, their connections are strengthened!


Although neuroscientists do not fully understand how increasing brain magnesium helps with LTP and ultimately learning, it is clear that magnesium is very important in the process! Interestingly, a 2003 study by the Centers for Disease Control found that a large majority of people in the United States does not consume an adequate amount of magnesium each day. Given its importance in long term potentiation, learning, and memory, we at Knowing Neurons encourage you to eat foods that are rich in magnesium such as rice, wheat, oats, almonds, cashews, and dark leafy greens. If none of those foods pique your appetite, then you’ll be happy to know that dark chocolate has some of the highest magnesium of all!


Written by Ryan Jones.



Ford ES. & Mokdad AH. (2003). Dietary Magnesium Intake in a National Sample of U.S. Adults, The Journal of Nutrition, 133(9) 2879-2882. PMID: 12949381

Images made by Ryan Jones. 

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