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Pregnancy Timeline by SemestersDevelopmental TimelineFertilizationFirst TrimesterSecond TrimesterThird TrimesterFirst Thin Layer of Skin AppearsEnd of Embryonic PeriodEnd of Embryonic PeriodFemale Reproductive SystemBeginning Cerebral HemispheresA Four Chambered HeartFirst Detectable Brain WavesThe Appearance of SomitesBasic Brain Structure in PlaceHeartbeat can be detectedHeartbeat can be detectedFinger and toe prints appearFinger and toe prints appearFetal sexual organs visibleBrown fat surrounds lymphatic systemBone marrow starts making blood cellsBone marrow starts making blood cellsInner Ear Bones HardenSensory brain waves begin to activateSensory brain waves begin to activateFetal liver is producing blood cellsBrain convolutions beginBrain convolutions beginImmune system beginningWhite fat begins to be madeHead may position into pelvisWhite fat begins to be madePeriod of rapid brain growthFull TermHead may position into pelvisImmune system beginningLungs begin to produce surfactant
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How does that Aha! moment happen in the brain?

Science identifies moments of brain activity based on the length of specific brain waves and their frequency over time. Research suggests that alpha waves may allow more information to be internalized as they signal the brain is more relaxed. This discovery may help development of non-pharmacological treatment for epilepsy, attention-deficit/hyperactivity disorder, depression and more Aha! moments if we learn to control our own alpha waves.

Research results were published in the journal Scientific Reports.

The human brain is always electrically active. Neurons are small, but complex computing devices exchanging information using very short electrical impulses. Impulses are distributed over time, and appear in various parts of the brain, causing fluctuations along the brain surface. Similar to how we use a cardiogram to explore the heart via elctrical impulses, we use devices such as electroencephalograms, to register impulse fluctuations and guage brain activity.

Types of brain activity can be distinguished by the speed of specific impulses — known as alpha, beta, gamma, theta, and delta waves. With electroencephalography, these waves can be registered, recoded to reflect the intensity by their brightness on a computer screen, and represented moving in real time. This is the mechanical basis for neurofeedback technology.
With the help of biofeedback, a person can learn to regulate the activity of his or her own brain.

The first time neurofeedback was discussed as a method that could be used to teach a person to regulate the electromagnetic activity of his or her brain was in research conducted by Joe Kamiya of the University of Chicago in the 1960s. Kamiya showed that by receiving feedback on your own brain activity, you can learn to affect this activity by altering the dominance of specific brain waves.

More recent experiments conducted by the HSE [Higher School of Economics National Research University] Centre for Cognition & Decision Making and the Institute of Problems of Mechanical Engineering, located in Moscow, Russia, researchers used electroencephalography to assess the intensity of brain alpha waves. Alpha waves are correlated with a person's ability to relax, manage stress, and internalize new information.

The current study involved 18 people, nine of whom were in the experimental group receiving real time feedback on their mental efforts, i.e., they were able to watch the color saturation reflected from their own alpha wave activity on a computer screen. Conversely, the control group received false feedback on their computer screens, with changes in the intensity of the red color not truly reflecting their own alpha wave activity.

Over a period of two days, both groups carried out five two-minute sessions per day. Research subjects were not provided with any strategy to help them achieve the best results.

At the end of the first day, the entire experimental group showed an increase in alpha wave activity, while alpha wave activity was slightly lower at the beginning of the second day than at the end of the first. But throughout the second day, activity continued to grow and exceed levels seen at the end of the first day. Two days of training in this neurofeedback model was enough to significantly increase alpha wave activity. However, this increase was not seen in the control group.

Alpha wave activity is not stationary, but occurs in the form of bursts, each of which can be characterised by its duration and amplitude. Another important parameter is the number of such bursts per measure of time.

'We became interested in what exactly changes during feedback - the amplitude of each burst, its length, or how often these bursts occur,' explains Professor Alexey Ossadtchi, who is a senior research fellow in the Centre for Cognition & Decision Making and one of the study authors.

'These are three completely different metrics as far as neurophysiology is concerned. When amplitude increases, the size of the corresponding neuron population increases, and when the duration grows, short-term regulatory mechanisms with feedback are directly involved and allow the brain to maintain high alpha wave activity for a longer period of time. An increase in the frequency of bursts shows that under the influence of a person's intentional effort, the brain more easily enters a state in which the alpha rhythm dominates.'
After experimenters compared how much the amplitude, duration, and frequency of bursts changed during the training process of all participants on different days, it was discovered alpha wave bursts, in particular, undergo the most significant changes over time.

In other words, after training using the neurofeedback model, a person learns to control entry into a complete alpha state. This is new information in the study of neurofeedback mechanisms.

'It turned out that the frequency of alpha wave bursts in particular is a coached metric that we can use to influence alpha wave activity as a whole, unlike amplitude and duration, which are likely coded at a lower level,' explains Professor Ossadtchi. 'This means that in therapy and in training, we have to give people feedback specifically on the parameter that they are truly able to influence - in our case, for every entry into the [alpha] state and for every new burst. It's preferred that a person receive such reinforcement with as little delay as possible. That is what we are working on now.'

The researchers assume that the data they collected are valid not only for alpha waves, but for other types of electromagnetic frequencies as well. A similar experiment will be conducted soon on different types of waves.
The neurofeedback training model helps lower the likelihood of epileptic seizures, eliminate some manifestations of attention deficit/hyperactivity disorder, and provides relief to a person with depression.

Neurofeedback as a technology has been shown to help athletes control their psycho-emotional state, can be used to master meditation, improve memory, and help increase concentration. According to the researchers, knowing specifically which regulatory mechanisms are activated during a certain form of neurofeedback allows one to significantly increase the efficiency of this technology, while it also provides access to new resources in the human brain that have not yet been studied.

Although the first experiments on alpha-neurofeedback date back nearly six decades ago, when Joseph Kamiya reported successful operant conditioning of alpha-rhythm in humans, the effectiveness of this paradigm in various experimental and clinical settings is still a matter of debate. Here, we investigated the changes in EEG patterns during a continuously administered neurofeedback of P4 alpha activity. Two days of neurofeedback training were sufficient for a significant increase in the alpha power to occur. A detailed analysis of these EEG changes showed that the alpha power rose because of an increase in the incidence rate of alpha episodes, whereas the amplitude and the duration of alpha oscillations remained unchanged. These findings suggest that neurofeedback facilitates volitional control of alpha activity onset, but alpha episodes themselves appear to be maintained automatically with no volitional control – a property overlooked by previous studies that employed continuous alpha-power neurofeedback. We propose that future research on alpha neurofeedback should explore reinforcement schedules based on detection of onsets and offsets of alpha waves, and employ these statistics for exploration and quantification of neurofeedback induced effects.

All authors: Alexei Ossadtchi, Tatiana Shamaeva, Elizaveta Okorokova, Victoria Moiseeva and Mikhail A. Lebedev.

Consistently ranked as one of Russia’s top universities, the Higher School of Economics (HSE) is a leader in Russian education and one of the preeminent economics and social sciences universities in Eastern Europe and Eurasia. Having rapidly grown into a well-renowned research university over two decades, HSE sets itself apart with its international presence and cooperation.

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Jul 31, 2017   Fetal Timeline   Maternal Timeline   News   News Archive

The goal of neurofeedback training is to enhance alpha wave color greater than average wave (top row, rightmost column). Electrodes exhibiting significant changes are pointed to by arrows. Image credit:
HSE Centre for Cognition & Decision Making, Institute of Problems of Mechanical Engineering

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