Neuroscientists who measured precise patterns of electrical activity directly from the human brain found networks comprising distinct, distant regions that act in concert during memory recall are active in the same way during rest and sleep states.
Writing in the journal Nature, the researchers, from the Stanford University School of Medicine, say their findings support indirect observations from brain imaging studies.
They say their results may also explain why the brain uses so much of the body’s energy during periods when it appears to be “doing nothing,” as a car engine uses up gas when idling.
Our brains are greedy organs; they use 20% of our energy, despite only accounting for 2% of our body weight.
Equally surprising is that our brains burn fuel – in the form of glucose – at the same rate at rest or sleeping as they do during mental or physical activity.
Something else that puzzles scientists is that when in the resting state, the brain appears to be very busy doing nothing in particular – essentially producing lots of useless electrical “noise.”
In fact, this electrical noise is going on all the time, as senior author Josef Parvizi, associate professor of neurology and neurological sciences, explains:
“Increases in brain activity during conscious thoughts and actions represent only the tip of the iceberg. The vast amount of energy consumption by our brain is due to its spontaneous activity at all times when we are not consciously involved in a specific task.”
Over the past 10 years, using functional magnetic resonance imaging (fMRI) to track the flow of blood in the brain – an indirect way to assess brain activity – scientists have begun to notice specific patterns in this neuronal noise.
With fMRI, they have observed brain activity as subjects performed various tasks – from solving mathematical problems to recalling what they had for breakfast – and noticed different types of task are associated with specific patterns of brain activity.
The patterns reveal that networked clusters of distinct and disparate brain regions work together during particular types of tasks, and the imaging profiles of these patterns can be spotted within the spontaneous noise.
Imaging studies have also found some of these task-specific patterns occur during periods when the brain is at rest – or even completely unconscious, such as when subjects are sleeping or under anesthesia.
However, scientists have reserved judgment on this evidence from imaging studies because they are indirect observations of brain electrical activity – they do not pinpoint individual circuits of neurons.
The new study is a big step forward because it directly measures electrical activity in the brain, and unlike fMRI, it can follow the activity over time and match not only the location features of the patterns but also how they vary over time.
Prof. Parvizi and colleagues found location- and time-based patterns of electrical brain activity that occur when subjects are retrieving a memory are also present within their brain noise when they are asleep or resting with their eyes closed.
The technique Prof. Parvizi and colleagues used is called intracranial electrophysiology and it allowed them to eavesdrop on distinct populations of neurons in the brain. It works in millimeters and milliseconds – a resolution that is small enough to obtain meaningful results from an individual brain.
Intracranial electrophysiology readings can only be taken during invasive brain procedures. For this study, the team recruited three epilepsy patients – two women and one man – who were already scheduled to spend a week in Stanford Hospital undergoing invasive brain procedures for medical reasons.
The patients spent several days with electrodes implanted in various parts of their brains, so doctors could find the exact spot where the seizures were coming from. During this time, precise intracranial electrophysiology readings were obtained from key regions of the brain that make up a very important network – the default mode network.
The default mode network is a network of widely distributed parts of the brain and consumes more energy than any other network. It is most active when we are at rest – either with our eyes closed or just staring into space. It appears to kick in when we are doing nothing in particular.
The default mode network is also active when we are retrieving an autobiographical memory – for example, it kicks in when we are asked what we had for breakfast.
However, the default mode network shuts down when we are then asked to do a specific task, such as mental arithmetic.
In previous work, Prof. Parvizi and colleagues were the first team to use direct electrical recording to confirm these unique features of the default mode network.
In this new study, the team was able to take readings of electrical activity in the default mode network when the subjects were awake and performing tasks, and also when they were resting with their eyes shut and when they were asleep.
They found slow, drifting activity patterns hidden in the noise the brain produced when asleep or resting were a direct match for patterns produced when the subjects were being asked to retrieve specific memories.
To confirm that these patterns reflect those spotted in the imaging studies, the team then carried out fMRI scans on the same subjects and found the electrical activity patterns were closely aligned with the blood flow patterns from the fMRI images.
The authors say that while their results resolve one question – that the imaging studies were correct in suggesting the patterns for resting state and memory retrieval were the same – they raise another question: why is our brain spending so much time and energy during rest and sleep on this activity?
The team suggests it could be that the brain is just keeping itself ready for future action – checking the states of its internal relationships and networks so it is ready to go when we wake up.
To emphasize this point, Prof. Parvizi says we should be careful about comparing the brain to computers – just because we refer to it as a network organization, it does not mean it is like a network in the computing sense. He adds:
“The brain is much more than a bunch of ones and zeroes.”
Funds for the study came from the Stanford NeuroVentures Program, the National Institute of Neurological Disorders and Stroke, the National Science Foundation and the National Institute of Mental Health.
In December 2014, Medical News Today learned how researchers used flashes of light to ‘read and write’ electrical signals sent by individual neurons. In the journal Nature Methods, the University College London team describes how the read and write techniques they developed allowed them to activate selected brain cells in different patterns and measure how the circuit responds.