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Which kind of electrical brain activity is associated with consciousness and why?

Which kind of electrical brain activity is associated with consciousness and why?


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According to this article The ethical brain

At the end of the week 5 into the 6 (42-43 days) the first electrical brain activity occurs in a pre-born developing human.

And according to the same article

This activity, however, is not coherent activity of the kind that underlies human consciousness, or even the coherent activity seen in a shrimp's nervous system

My question is, which kind of electrical brain activity is associated with consciouness and why?


Gamma band oscillations (GBO) (Wikipedia) (NCBI) are 30-90 Hz electrical waves generated by the brain and are thought to possibly be associated with cognition and consciousness (Panagiotaropoulos, 2012). Some evidence for this putative relationship can be seen with experiments such as pre-pulse inhibition (PPI), which can describe how our sensations are interpreted by the brain. Also, PPI may be aberrant in Schizophrenic patients (who have altered cognition). Changes to PPI are associated with aberrant GBO, which could imply an association between GBO and an individual's interpretation of stimuli, their cognition and by extension consciousness.

But of course, the counter-argument is that the intrinsic activity of the brain isn't changed, merely how the brain processes stimuli. However, all forms of measuring cognition that I've studied involve investigating responses to external stimuli, so as far as I know, this is a universal problem. Furthermore, there's a lot we still don't know about consciousness and no model or measurement is perfect. This article gives quite a nice overview on neural correlates of consciousness.


What Role Do Brain Waves Play in Regulating Consciousness?

Key points

  • While different brain regions have distinct functional roles, increasingly these are being shown to be linked in a highly coordinated way.
  • One way such coordination takes place is via electrical brain "waves," synchronised electrical pulses that connect the activity of brain regions.
  • Brain waves can be categorised by their frequency, and the different frequencies perform different types of coordinating roles in the brain.
  • Although brain waves mediate global brain activity in other species, it may be that in humans language transforms their role in a unique fashion.

While different brain regions have distinct functional roles, increasingly these are being shown to be linked in a highly coordinated way. One way such coordination takes place is via electrical brain "waves"—synchronised electrical pulses from masses of neurons communicating with each other—whose character varies depending on the state of alertness of the organism in which they occur.

These insights about brain waves have coincided with a shift among some scientists away from a view that reduces the brain to the behaviour of its individual components. For instance, neuroscientist Earl Miller views previous theories about how the brain works as tending to see it as "a giant clock, and if you figure out each gear, you’ll figure out the brain."

In contrast, Miller believes the brain is better understood as "networks interacting in a very dynamic, fluid way," with oscillating brain waves, which he sees as "the most powerful signal in the brain" central to the coordination of such networks. Another neuroscientist, Robert Knight, has a similar viewpoint. He believes that "you’ve got to have a way to get brain areas communicating. What oscillations do is provide a routing mechanism." Importantly, brain waves can carry out such routing extremely rapidly. Such waves may tune out extraneous information by temporarily shutting down unnecessary communication lines.

Brain waves can be categorized by their frequency. Alpha waves (8 to 12 Hz) are dominant during quiet thoughts and in some meditative states beta waves (13 to 32 Hz) dominate our normal waking state of consciousness when attention is directed towards cognitive tasks and the outside world and gamma waves (33 to 100 Hz) are the fastest brain waves, and relate to simultaneous processing of information from different brain areas.

One topic that Miller has investigated is the involvement of brain waves in working memory. This form of memory allows us to hold multiple pieces of information in mind—a telephone number, the time of an appointment that day, or a grocery list for our evening meal—from a few minutes to several hours. Miller notes that "working memory allows you to choose what to pay attention to, choose what you hold in mind, and choose when to make decisions and take action. It's all about wresting control from the environment to your own self. Once you have something like working memory, you go from being a simple creature that's buffeted by the environment to a creature that can control the environment."

In one recent study, Miller and his colleagues found that the primate brain uses beta waves to consciously switch between different pieces of information. The findings add to insights that emerged from another study by Miller’s team, which found that gamma waves are associated with encoding and retrieving sensory information. They also found that when gamma waves increased in intensity, beta rhythms decreased, and vice versa.

Previous studies have indicated that beta waves are associated with "top-down" information such as a current goal, how to achieve this, and the rules of a task. This suggests that beta waves determine which pieces of information can be read out from working memory. Miller believes that beta waves act like a signal that gates access to working memory. They clear out working memory, and can act as a switch from one thought or item to another.

Miller’s team have been focusing on the prefrontal cortex, a brain region that has long been suspected to mediate "higher" thought processes. The latest studies indicate that this brain region helps construct an internal model of the world, sending "top-down" signals that convey this model to lower-level regions. Meanwhile, other regions of the brain send raw sensory input to areas of the prefrontal cortex, in the form of "bottom-up" signals.

Differences between the top-down model and the bottom-up sensory information allow the brain to figure out what it is experiencing, and to tweak its internal model accordingly.

This model would explain how attention works—for instance, a person can focus on a particular picture while ignoring a noise in the background. It may also explain how different pieces of information might be juggled around in the brain while we try to solve a problem creatively. It suggests a directing role for the prefrontal cortex in this process, but argues against the idea that this region is all-powerful, for the fact that this brain region requires incoming signals from these other regions shows it is also directed by them.

Although brain waves appear to mediate global brain activity in other species, the "culturally mediated" view of the brain I have been developing in this blog predicts a link between human brain wave activity and language, in a way that is not found in other species. Investigating how language affects the coordinating role of different brain waves associated with various aspects of human consciousness is likely to be a fertile area for future studies.

Brain waves display what is known as "non-linear dynamics." Such dynamics occur throughout nature and are distinguished by having no organising centre. This is important given the potential role of brain waves as mediators of consciousness, since this non-linear dynamic behaviour would mean that there is no need for consciousness to be centred in any specific part of the brain, conjuring up visions of a controlling homunculus or soul.

Instead, consciousness would be a property of the whole organ. And it seems entirely feasible that such order out of chaos also operates in an animal brain—say that of your pet dog or cat—explaining how its attention is suddenly taken up by something novel in its environment, whether a squirrel, a tasty snack, or just the sight of you.

However, in humans, superimposed on this mechanism for switching attention from one thing to another, language also surely plays a unique and higher guiding role—acting through brain waves, but doing so in a structured way that can only occur in our species because of the word meaning and grammatical structure that language alone can provide.


Introduction

Advances in neuroscience have now made it possible to study the biological basis of consciousness. Indeed, in recent years an increasing amount of attention has been directed to this subject (Crick and Koch, 2003 Edelman, 2003 Velmans and Schneider, 2007 Zelazo et al., 2007). Our own efforts to account for key aspects of consciousness at a biological level have taken two forms. The first involved the proposal of a neuroscientifically based global brain theory commonly referred to as Neural Darwinism (Edelman, 1978, 1987 Edelman and Tononi, 2000). This theory proposes the functioning of a Dynamic Core generated by a neural process, reentry, to link dispersed cortical and thalamic areas and account for the relation between perception and conscious memory. The second theory (Baars, 1988) was propounded mainly from a cognitive psychological point of view. This Global Workspace theory hypothesizes that a number of brain components constitute an integrative workspace that serves to reconcile the narrow momentary capacity of conscious contents with a widespread recruitment of unconscious brain functions, including long-term memory.

In the present account, we reconcile and expand on these early notions by considering consciousness as a biological phenomenon, one that is a product of both evolution and development. We believe that such a biological approach can address and even dispose of several concerns articulated by philosophers of mind and others. We propose that a biological account of consciousness does not require metaphysical proposals, mathematical reduction, or “strange physics.” We also maintain that previously argued categories such as selfhood and phenomenal experience can be explained biologically in terms of patterns of neural activity.

At the outset, it is important to distinguish primary sensorimotor consciousness from higher-order consciousness (Edelman, 1992, 2003). Primary consciousness occurs in animals lacking any linguistic capabilities, and is an essential process even in humans. After the invention of language it was possible to escape the “remembered present” of primary consciousness by referring to internal linguistic tokens. As a result, possession of true language with syntax in humans gives rise to higher-order consciousness allowing its possessor to be conscious of being conscious. We emphasize this distinction to make the point that our overarching task here is to account in biological terms for primary consciousness. At the same time, such an account necessarily depends on investigation of human subjects, with their ability verbally to report, as the richest source of relevant data.


Electrical Brain Stimulation May Alleviate Obsessive-Compulsive Behaviors

Obsessive-compulsive disorder (OCD) is marked by repetitive, anxiety-inducing thoughts, urges and compulsions, such as excessive cleaning, counting and checking. These behaviors are also prevalent in the general population: one study in a large sample of U.S. adults found more than a quarter had experienced obsessions or compulsions at some point in their life. Although most of these individuals do not develop full-blown OCD, such symptoms can still interfere with daily life. A new study, published on January 18 in Nature Medicine, hints that these behaviors may be alleviated by stimulating the brain with an electrical current&mdashwithout the need to insert electrodes under the skull.

Robert Reinhart, a neuroscientist at Boston University, and his group drew on two parallel lines of research for this study. First, evidence suggests that obsessive-compulsive behaviors may arise as a result of overlearning habits&mdashleading to their excessive repetition&mdashand abnormalities in brain circuits involved in learning from rewards. Separately, studies point to the importance of high-frequency rhythms in the so-called high-beta/low-gamma range (also referred to as simply beta-gamma) in decision-making and learning from positive feedback.

Drawing on these prior observations, Shrey Grover, a doctoral student in Reinhart&rsquos lab, hypothesized with others in the team that manipulating beta-gamma rhythms in the orbitofrontal cortex (OFC)&mdasha key region in the reward network located in the front of the brain&mdashmight disrupt the ability to repetitively pursue rewarding choices. In doing so, the researchers thought, the intervention could reduce obsessive-compulsive behaviors associated with maladaptive habits.

To test this hypothesis, Grover and his colleagues carried out a two-part study. The first segment was aimed at identifying whether the high-frequency brain activity influenced how well people were able to learn from rewards. The team recruited 60 volunteers and first used electroencephalography to pinpoint the unique frequencies of beta-gamma rhythms in the OFC that were active in a given individual while that person took part in a task that involved associating symbols with monetary wins or losses. Previous work had shown that applying stimulation based on the particular patterns of rhythms in a person&rsquos brain may enhance the effectiveness of the procedure.

The participants were then split into three groups, all of whom received a noninvasive form of brain stimulation known as transcranial alternating current stimulation (tACS), which was applied to the OFC for 30 minutes over five consecutive days. Each group had a different type of stimulation: One received personalized currents tuned to an individual&rsquos beta-gamma frequencies. Another was exposed to an &ldquoactive&rdquo placebo, consisting of stimulations at a lower frequency. And the third was a &ldquopassive&rdquo placebo group in which no significant current was applied to the brain. Those who received the personalized beta-gamma stimulation became less able to make optimal choices on the reward-based learning tasks&mdashchanges not observed in the two placebo groups.

Further assessment of the participants&rsquo behavior using computational models of reward-based learning suggested that the personalized tACS disrupted the learning process by making people more likely to try out different options rather than sticking with only one&mdasheven if they were less likely to result in a reward.

These findings set the stage for the second part of the study, in which the team set out to examine whether manipulating the beta-gamma rhythms typically engaged during reward-based learning would influence obsessive-compulsive behaviors. The researchers carried out a similar set of experiments on another set of volunteers: 64 people who did not have a formal OCD diagnosis but who exhibited symptoms such as checking, hoarding and obsessing. Participants received either personalized beta-gamma stimulation or an active placebo. Those in the personalized beta-gamma group experienced a reduction in compulsive behaviors that persisted for up to three months. And those with more of those obsessive-compulsive characteristics prior to stimulation exhibited the biggest changes.

According to Grover, the team decided to study people with symptoms of OCD but no diagnosis of the disorder because researchers have increasingly been viewing obsessive-compulsive behaviors on a mild-to-severe spectrum. And even in the absence of clinically diagnosed OCD, such symptoms can cause significant distress. &ldquoBy examining a nonclinical population exhibiting a range of obsessive-compulsive behaviors, we were able to examine the effectiveness of [an intervention] that may be helpful to a larger pool of individuals,&rdquo Grover says. Yet the researchers&rsquo findings also suggest &ldquothat if we were to extend such an intervention to individuals diagnosed with obsessive-compulsive disorder or to other conditions of compulsivity&mdashgambling disorder, addiction, some forms of eating disorders&mdash-we might be able to observe strong effects.&rdquo

The long-lasting effects on obsessive-compulsive behaviors is &ldquoquite impressive,&rdquo says Trevor Robbins, a professor of cognitive neuroscience at the University of Cambridge, who was not involved in this research. &ldquo[Neuromodulation] is certainly a treatment that should be investigated rigorously for conditions like OCD.&rdquo

Carolyn Rodriguez, a psychiatrist and neuroscientist at Stanford University, who was also not involved in the study, says that because it was carried out in a nonclinical population without a formal diagnosis, the implications of these findings remain to be seen. &ldquoThe neurobiology of people who are nonclinical but have these kinds of behaviors may be different than individuals who are diagnosed with OCD,&rdquo she adds. &ldquoThese findings are an interesting start, [but] we need to understand how it's relevant to people who have OCD.&rdquo Rodriguez also points out that there are already several treatments available for the condition, including medication, therapy and a Food and Drug Administration&ndashapproved device that utilizes transcranial magnetic stimulation (TMS), a noninvasive method that uses magnetic fields to stimulate the brain. (Rodriguez is currently leading a clinical trial of TMS for OCD.)

The potential therapeutic effects of tACS on memory, food craving and other neural processes have been tested in dozens of studies in the past. Questions have been raised about whether this method actually exerts any meaningful changes in the brain, however. In the new study, what, exactly, the high-frequency tACS did to the brain remains unknown. But Grover notes that the researchers&rsquo two placebo conditions&mdashparticularly the one that involves stimulating at a different frequency&mdashprovide strong evidence that the high-frequency stimulation was responsible for the behavioral effects the team observed.

Grover and his colleagues are currently working on further experiments to pinpoint the mechanisms underlying their intervention. And they hope to conduct studies with clinical populations diagnosed with OCD in the near future. &ldquo[The recent paper] is just a preliminary step toward further understanding why this high-frequency activity is so important for obsessive-compulsive behavior,&rdquo Grover says. &ldquoThe fact that we can observe changes in these symptoms even now suggests there may actually be clinical benefit to this&mdashand gives us all the more reason to try to extend the findings of this research.&rdquo


Surge of Brain Activity Accompanies 'Aha!' Moments

In the study, which appears in the April issue of PloS Biology , researchers compared brain activity in two different experiments.

In the first, study participants were given a series of word problems to solve designed to evoke a distinct "Aha!" moment about half the time they were solved. Using brain imaging techniques, researchers found that activity increased in a small part of the right lobe of the brain called the temporal lobe when the participants reported experiencing creative insight during problem solving. Little activity was detected in this area during noninsight solutions.

Researchers say previous studies have shown that this right temporal lobe may be important for drawing distantly related information together, which is a key component of insight.

In the second experiment, researchers monitored the participants' brainwave activity using an electroencephalogram (EEG) during insight and noninsight problem solving tasks.

The study showed that about one-third of a second before the "Aha!" moment, there was a sudden burst of high-frequency brain waves. This type of activity is associated with high-level processing of information, and researchers say it was also centered in the same right temporal lobe area.

In addition, a second smaller wave of electrical activity was seen on EEG. About 1.5 seconds before the moment of insight, there was an increase in lower frequency brain waves in this area of the brain, which disappeared when the high-frequency activity began.

Researchers say this "gating" effect might occur to allow weak solution-related activity to gain momentum and then burst into consciousness as insight.

"This is like closing your eyes so you can concentrate when you are trying to solve a difficult problem," says researcher John Kounios of Drexel University in a news release. "But in this case, your brain is blocking out just the visual inputs to your right hemisphere."

Researchers say that these clues may help scientists better understand the creative insight process and its impact on the brain.


The nerve cell

5.0 The brain code: maps + waves

Neurons can be coordinated in a number of ways. One is for large-scale rhythms to drive populations of neurons, like the conductor of a symphony orchestra. When many neurons fire in unison, their activity adds up, just as a large crowd of people sounds louder when they are chanting in unison.

There is a limit, however, to the way billions of neurons can be coordinated. Epileptic seizures have long been believed to be caused by neural scar tissue, called the epileptic focus, which sends out intense, slow, and regular waves that recruit more and more brain regions so that spreading populations of neurons begin to chant the same song. The result is a loss of consciousness and physical seizure activity.

Somehow the brain must coordinate thousands of neurons that work together to achieve a specific cognitive task, like perceiving a coffee cup. But the coffee cup ensemble cannot grow so large as to recruit all of the brain. It must be able to recruit new neurons and also leave those that are irrelevant to seeing a coffee cup.

In 1929, Hans Berger, a psychiatrist, first observed brain waves over the occipital cortex in his young son. Berger was able to do that because his equipment could amplify the small voltages involved. He was also lucky in that he was able to observe alpha waves, regular sine waves that oscillate between 8 and 12 Hz, when his son closed his eyes. When he opened his eyes, the alpha wave (arbitrarily named “alpha” because it was the first regular waveform found in humans) was interrupted by complex and fast activity, which were called beta and gamma waves.

For many years only “raw” EEG waves could be observed. Most raw EEG waveforms are complex, and regular waves like alpha live in an ocean of complex waves with many different origins, at many frequencies and amplitudes. The simple signals are swamped. However, when high-speed computers came into use, it became possible to analyze complex waveforms very quickly. What were originally simple-looking waves in EEG are now filtered from the complex waves of the full-spectrum EEG all over the head. We therefore tend to talk about “frequency bands” rather than simple frequencies to include anything between 8 and 12 Hz in the alpha band, for example. It is important to remember that our current way of slicing up the EEG frequency range is still somewhat arbitrary. There is no particular reason why alpha waves are called alpha waves. It is possible that we will learn to group the frequencies differently.

Table 3.1 gives a useful set of brain waves as we currently understand them. Regular EEG rhythms are now believed to signal distinct, coordinated processes. For example, a high density of gamma rhythms has been related to conscious visual perception and to the process of discovering a solution to a simple word problem.

Table 3.1 . EEG Frequencies and their Associated Functions

Name and exampleDescription
Delta is the slow wave characteristic of deep, unconscious sleep. It is less than 4 Hz, and similar EEG frequencies appear in epileptic seizures and loss of consciousness, as well as some comatose states. It is therefore thought to reflect the brain of an unconscious person.
The Delta frequency tends to have the highest amplitude and the slowest frequency. Delta waves increase with decreasing awareness of the physical world.
Theta activity has a frequency of 3.5 to 7.5 Hz.
Theta waves are thought to involve many neurons firing synchronously. Theta rhythms are observed during some sleep states, and in states of quiet focus, for example meditation. They are also manifested during some short term memory tasks, and during memory retrieval.
Theta waves seem to communicate between the hippocampus and neocortex in memory encoding and retrieval.
Alpha waves range between 7.5 and 13 Hz and arise from synchronous (in phase) electrical activity of large groups of neurons. They are also called Berger's waves in memory of the founder of EEG.
Alpha waves are predominantly found in scalp recordings over the occipital lobe during periods of relaxation, with eyes closed but still awake. Conversely alpha waves are attenuated with open eyes as well as by drowsiness and sleep.
Beta activity is ‘fast’ irregular activity, at low voltage (12–25 Hz).
Beta waves are associated with normal waking consciousness, often active, busy, or anxious thinking and active concentration.
Beta is usually seen on both sides of the brain in symmetrical distribution and is most evident frontally. It may be absent or reduced in areas of cortical damage.
Gamma generally ranges between 26 and 70 Hz, centered around 40 Hz.
Gamma waves are thought to signal active exchange of information between cortical and other regions. It is seen during the conscious state and in REM dreams (Rapid Eye Movement). Note that gamma and beta activity may overlap in their typical frequency ranges, because there is still disagreement on the exact boundaries between these frequency bands.

Obviously, the brain must balance the degree of coordination against the need for local neurons to work on local functions. There must be a balance between neuronal integration and differentiation ( Edelman & Tononi, 2000 ).

5.1 Synchrony and phase-locking

Regular EEG rhythms are now believed to coordinate widely separated cells and “cell assemblies.” For example, gamma rhythm has been related to conscious visual perception and to the process of discovering a solution to a simple word problem. Alpha rhythms are traditionally associated with relaxation, but they now seem to play many different roles. Theta rhythms coordinate the hippocampal region and the frontal cortex during the retrieval and consolidation of memories. The delta rhythm of deep sleep is believed to coordinate faster rhythms to facilitate consolidation of learned events ( Kemp et al., 2004 ).

Figure 3.21 shows a simple hypothesis about how regular brain rhythms may coordinate the firing of millions of separate cells. Neurons that fire at the peak of the delta wave (for example) add a tiny amount of electrochemical activity to the whole chorus. Neurons that fire during the trough subtract their activity from the whole. Thus, neurons that fire in sync with the dominant rhythm are strengthened by feedback from millions of others that are following the same overall rhythm, while those that are out of sync are weakened. Such a mechanism would tend to reinforce a dominant rhythm.

Figure 3.21 . EEG and single-unit activity in waking and deep sleep. Conventional EEG measures the brain's electrical field over the scalp. Each EEG trace in the figure is a complex sum of underlying neuronal activity in the upper layer of cortex. Slow-wave sleep EEG reflects the simultaneous ‘buzz’ and ‘pause’ of billions of neurons, also called ‘up’ and ‘down’ states. Because waking-state neurons do not fire and pause synchronously, their voltages do not add up to large waves. The waking EEG looks small, irregular, and faster than slow-wave sleep. It is believed that waking (and REM dreaming) therefore involves more differentiated information processing in much the same way that a stadium full of talking people serves to process more information than the same people all chanting in unison. The unison chanting is largely redundant (you can predict the crowd chants from just one person) so the information content is lower (see Section 6.2).

Source: Adapted from Steriade, 2006 .

But synchronized firing is not enough. Different coalitions of neurons must be able to represent inputs, which compete against other coalitions to recruit new members. Such a model is shown in Figure 3.22 , where it supports a kind of Darwinian competition between different populations of nerve cells.

Figure 3.22 . Inhibitory cells synchronize excitatory neurons. How inhibitory neurons drive synchrony in excitatory cells. (a) Coding by synchrony. If two excitatory cells (black) display random spike trains, they will rarely drive a common downstream cell above threshold (gray). By contrast, when synchronized by an inhibitory interneuron (red) these neurons, firing at the same overall rate, will now reliably activate the downstream neuron. (b) Phase coding. If five pyramidal neurons (black) are firing at different rates, the introduction of a rhythmic inhibitory cell will tend to drive the excitatory cells to fire at the same time.

Source: Mann and Paulson, 2007 .

The brain is often called a massively parallel organ, because there is no central command post that tells all the neurons what to do. There are, however, a number of ways in which neurons can be coordinated. As we mentioned earlier in the chapter, one way is for large-scale rhythms to pace populations of neurons, much like the conductor of a symphony orchestra. When many neurons fire in unison, their activity adds up, just as a large crowd of people sounds louder when they are chanting in unison. There is a limit to this, however. Epileptic seizures have long been believed to be caused by neural scar tissue, called the epileptic focus, which sends out intense, slow, and regular waves that recruit other brain regions, so that spreading populations of neurons begin to chant the same song. The result is a loss of consciousness and physical seizure activity.

Obviously, the brain must balance the degree of pacing and coordination against the need for local neurons to work on local functions. There must be a balance between integration and differentiation ( Edelman & Tononi, 2000 ).


Brain Imaging

You have learned how brain injury can provide information about the functions of different parts of the brain. Increasingly, however, we are able to obtain that information using brain imaging techniques on individuals who have not suffered brain injury. In this section, we take a more in-depth look at some of the techniques that are available for imaging the brain, including techniques that rely on radiation, magnetic fields, or electrical activity within the brain.

Techniques Involving Radiation

A computerized tomography (CT) scan involves taking a number of x-rays of a particular section of a person’s body or brain (Figure 12). The x-rays pass through tissues of different densities at different rates, allowing a computer to construct an overall image of the area of the body being scanned. A CT scan is often used to determine whether someone has a tumor, or significant brain atrophy.

Figure 12. A CT scan can be used to show brain tumors. (a) The image on the left shows a healthy brain, whereas (b) the image on the right indicates a brain tumor in the left frontal lobe. (credit a: modification of work by “Aceofhearts1968″/Wikimedia Commons credit b: modification of work by Roland Schmitt et al)

Positron emission tomography (PET) scans create pictures of the living, active brain ( Figure 13 ). An individual receiving a PET scan drinks or is injected with a mildly radioactive substance, called a tracer. Once in the bloodstream, the amount of tracer in any given region of the brain can be monitored. As brain areas become more active, more blood flows to that area. A computer monitors the movement of the tracer and creates a rough map of active and inactive areas of the brain during a given behavior. PET scans show little detail, are unable to pinpoint events precisely in time, and require that the brain be exposed to radiation therefore, this technique has been replaced by the fMRI as an alternative diagnostic tool. However, combined with CT, PET technology is still being used in certain contexts. For example, CT/PET scans allow better imaging of the activity of neurotransmitter receptors and open new avenues in schizophrenia research. In this hybrid CT/PET technology, CT contributes clear images of brain structures, while PET shows the brain’s activity.

Figure 13. A PET scan is helpful for showing activity in different parts of the brain. (credit: Health and Human Services Department, National Institutes of Health)

Techniques Involving Magnetic Fields

In magnetic resonance imaging (MRI), a person is placed inside a machine that generates a strong magnetic field. The magnetic field causes the hydrogen atoms in the body’s cells to move. When the magnetic field is turned off, the hydrogen atoms emit electromagnetic signals as they return to their original positions. Tissues of different densities give off different signals, which a computer interprets and displays on a monitor. Functional magnetic resonance imaging (fMRI) operates on the same principles, but it shows changes in brain activity over time by tracking blood flow and oxygen levels. The fMRI provides more detailed images of the brain’s structure, as well as better accuracy in time, than is possible in PET scans (Figure 14). With their high level of detail, MRI and fMRI are often used to compare the brains of healthy individuals to the brains of individuals diagnosed with psychological disorders. This comparison helps determine what structural and functional differences exist between these populations.

Figure 14. An fMRI shows activity in the brain over time. This image represents a single frame from an fMRI. (credit: modification of work by Kim J, Matthews NL, Park S.)

Link to Learning

Techniques Involving Electrical Activity

In some situations, it is helpful to gain an understanding of the overall activity of a person’s brain, without needing information on the actual location of the activity. Electroencephalography (EEG) serves this purpose by providing a measure of a brain’s electrical activity. An array of electrodes is placed around a person’s head (Figure 15). The signals received by the electrodes result in a printout of the electrical activity of his or her brain, or brainwaves, showing both the frequency (number of waves per second) and amplitude (height) of the recorded brainwaves, with an accuracy within milliseconds. Such information is especially helpful to researchers studying sleep patterns among individuals with sleep disorders.

Figure 15. Using caps with electrodes, modern EEG research can study the precise timing of overall brain activities. (credit: SMI Eye Tracking)


Escape From Oblivion: Innovative Experiment Shows How the Brain Reboots After Deep Anesthesia

Millions of surgical procedures performed each year would not be possible without the aid of general anesthesia, the miraculous medical ability to turn off consciousness in a reversible and controllable way.

Researchers are using this powerful tool to better understand how the brain reconstitutes consciousness and cognition after disruptions caused by sleep, medical procedures requiring anesthesia, and neurological dysfunctions such as coma.

In a new study published in the journal eLife, a team led by anesthesiologists George Mashour, M.D., Ph.D. of University of Michigan Medical School, Michigan Medicine, Max Kelz, M.D., Ph.D. of the University of Pennsylvania Medical School, and Michael Avidan, MBBCh of the Washington University School of Medicine used the anesthetics propofol and isoflurane in humans to study the patterns of reemerging consciousness and cognitive function after anesthesia.

In the study, 30 healthy adults were anesthetized for three hours. Their brain activity was measured with EEG and their sleep-wake activity was measured before and after the experiment. Each participant was given cognitive tests—designed to measure reaction speed, memory, and other functions—before receiving anesthesia, right after the return of consciousness, and then every 30 minutes thereafter.

The study team sought to answer several fundamental questions: Just how does the brain wake up after profound unconsciousness—all at once or do some areas and functions come back online first? If so, which?

“How the brain recovers from states of unconsciousness is important clinically but also gives us insight into the neural basis of consciousness itself,” says Mashour.

After the anesthetic was discontinued and participants regained consciousness, cognitive testing began. A second control group of study participants, who did not receive general anesthesia and stayed awake, also completed tests over the same time period.

Analyzing EEG and test performance, the researchers found that recovery of consciousness and cognition is a process that unfolds over time, not all at once. To the investigators’ surprise, one of the brain functions that came online first was abstract problem solving, controlled by the prefrontal cortex, whereas other functions such as reaction time and attention took longer to recover.

“Although initially surprising, it makes sense in evolutionary terms that higher cognition needs to recover early. If, for example, someone was waking up to a threat, structures like the prefrontal cortex would be important for categorizing the situation and generating an action plan,” says Kelz.

The EEG readings revealed that the frontal regions of the brain were especially active around the time of recovery. Importantly, within three hours of being deeply anesthetized for a prolonged period of time, participants were able to recover cognitive function to approximately the same level as the group that stayed awake during that time. Furthermore, their sleep schedule in the days after the experiment did not appear to be affected.

“This suggests that the healthy human brain is resilient, even with a prolonged exposure to deep anesthesia. Clinically, this implies that some of the disorders of cognition that we often see for days or even weeks during recovery from anesthesia and surgery—such as delirium—might be attributable to factors other than lingering effects of anesthetic drugs on the brain,” says Avidan.

Reference: “Recovery of consciousness and cognition after general anesthesia in humans” by George A Mashour, Ben JA Palanca, Mathias Basner, Duan Li, Wei Wang, Stefanie Blain-Moraes, Nan Lin, Kaitlyn Maier, Maxwell Muench, Vijay Tarnal, Giancarlo Vanini, E Andrew Ochroch, Rosemary Hogg, Marlon Schwartz, Hannah Maybrier, Randall Hardie, Ellen Janke, Goodarz Golmirzaie, Paul Picton, Andrew R McKinstry-Wu, Michael S Avidan and Max B Kelz, 10 May 2021, eLife.
DOI: 10.7554/eLife.59525

This study was funded by a collaborative grant from the James S. McDonnell Foundation, St. Louis, MO National Institutes of Health (Bethesda, MD, USA) grant T32GM112596 and the anesthesiology departments of the University of Michigan, University of Pennsylvania and Washington University.


Which kind of electrical brain activity is associated with consciousness and why? - Biology

Natural phenomena are reducible to quantum events in principle, but quantum mechanics does not always provide the best level of analysis. The many-body problem, chaotic avalanches, materials properties, biological organisms, and weather systems are better addressed at higher levels.

Animals are highly organized, goal-directed, adaptive, selectionist, information-preserving, functionally redundant, multicellular, quasi-autonomous, highly mobile, reproducing, dissipative systems that conserve many fundamental features over remarkably long periods of time at the species level. Animal brains consist of massive, layered networks of specialized signaling cells with 10,000 communication points per cell, and interacting up to 1000 Hz. Neurons begin to divide and differentiate very early in gestation, and continue to develop until middle age.

Waking brains operate far from thermodynamic equilibrium under delicate homeostatic control, making them extremely sensitive to a range of physical and chemical stimuli, highly adaptive, and able to produce a remarkable range of goal-relevant actions.

Consciousness is “a difference that makes a difference” at the level of massive neuronal interactions in the most parallel-interactive anatomical structure of the mammalian brain, the cortico-thalamic (C-T) system. Other brain structures are not established to result in direct conscious experiences, at least in humans. However, indirect extra-cortical influences on the C-T system are pervasive. Learning, brain plasticity and major life adaptations may require conscious cognition.

While brains evolved over hundreds of millions of years, and individual brains grow over months, years and decades, conscious events appear to have a duty cycle of ∼ 100 ms , fading after a few seconds. They can of course be refreshed by inner rehearsal, re-visualization, or attending to recurrent stimulus sources.

These very distinctive brain events are needed when animals seek out and cope with new, unpredictable and highly valued life events, such as evading predators, gathering critical information, seeking mates and hunting prey. Attentional selection of conscious events can be observed behaviorally in animals showing coordinated receptor orienting, flexible responding, alertness, emotional reactions, seeking, motivation and curiosity, as well as behavioral surprise and cortical and autonomic arousal. Brain events corresponding to attentional selection are prominent and widespread. Attention generally results in conscious experiences, which may be needed to recruit widespread processing resources in the brain.

Many neuronal processes never become conscious, such as the balance system of the inner ear. An air traveler may “see” the passenger cabin tilt downward as the plane tilts to descend for a landing. That visual experience occurs even at night, when the traveler has no external frame of spatial reference. The passengerʼs body tilt with respect to gravity is detected unconsciously via the hair cells of the vestibular canals, which act as liquid accelerometers. However, that sensory activity is not experienced directly. It only becomes conscious via vision and the body senses. The vestibular sense is therefore quite different from visual perception, which “reports” accurately to a conscious field of experience, so that we can point accurately to a bright star on a dark night. Vestibular input is also precise but unconscious.

Conscious cognition is therefore a distinct kind of brain event. Many of its features are well established, and must be accounted for by any adequate theory. No non-biological examples are known.

Penrose and Hameroff have proposed that consciousness may be viewed as a fundamental problem in quantum physics. Specifically, their ‘orchestrated objective reduction’ (Orch-OR) hypothesis posits that conscious states arise from quantum computations in the microtubules of neurons. However, a number of microtubule-associated proteins are found in both plant and animal cells (like neurons) and plants are not generally considered to be conscious.

Current quantum-level proposals do not explain the prominent empirical features of consciousness. Notably, they do not distinguish between closely matched conscious and unconscious brain events, as cognitive-biological theories must. About half of the human brain does not support conscious contents directly, yet neurons in these “unconscious” brain regions contain large numbers of microtubules.

QM phenomena are famously observer-dependent, but to the best of our knowledge it has not been shown that they require a conscious observer, as opposed to a particle detector. Conscious humans cannot detect quantum events “as such” without the aid of special instrumentation. Instead, we categorize the wavelengths of light into conscious sensory events that neglect their quantum mechanical properties.

In science the burden of proof is on the proposer, and this burden has not yet been met by quantum-level proposals. While in the future we may discover quantum effects that bear distinctively on conscious cognition ‘as such,’ we do not have such evidence today.

Highlights

► Natural phenomena are reducible to quantum events, but this does not always provide the best level of analysis. ► Current QM proposals do not explain the major empirical features of consciousness. ► Animal species that show consciousness do not violate the laws of physics, but they do not directly follow from known physics either. ► There are striking differences between brain regions and events that support conscious experiences and those that do not. ► While in the future we might find QM phenomena that bear distinctively on consciousness, none are known so far.


What is the function of the various brainwaves?

Ned Herrmann is an educator who has developed models of brain activity and integrated them into teaching and management training. Before founding the Ned Herrmann Group in 1980, he headed management education at General Electric, where he developed many of his ideas. Here is his explanation.

It is well known that the brain is an electrochemical organ researchers have speculated that a fully functioning brain can generate as much as 10 watts of electrical power. Other more conservative investigators calculate that if all 10 billion interconnected nerve cells discharged at one time that a single electrode placed on the human scalp would record something like five millionths to 50 millionths of a volt. If you had enough scalps hooked up you might be able to light a flashlight bulb.

Even though this electrical power is very limited, it does occur in very specific ways that are characteristic of the human brain. Electrical activity emanating from the brain is displayed in the form of brainwaves. There are four categories of these brainwaves, ranging from the most activity to the least activity. When the brain is aroused and actively engaged in mental activities, it generates beta waves. These beta waves are of relatively low amplitude, and are the fastest of the four different brainwaves. The frequency of beta waves ranges from 15 to 40 cycles a second. Beta waves are characteristics of a strongly engaged mind. A person in active conversation would be in beta. A debater would be in high beta. A person making a speech, or a teacher, or a talk show host would all be in beta when they are engaged in their work.

The next brainwave category in order of frequency is alpha. Where beta represented arousal, alpha represents non-arousal. Alpha brainwaves are slower, and higher in amplitude. Their frequency ranges from 9 to 14 cycles per second. A person who has completed a task and sits down to rest is often in an alpha state. A person who takes time out to reflect or meditate is usually in an alpha state. A person who takes a break from a conference and walks in the garden is often in an alpha state.

The next state, theta brainwaves, are typically of even greater amplitude and slower frequency. This frequency range is normally between 5 and 8 cycles a second. A person who has taken time off from a task and begins to daydream is often in a theta brainwave state. A person who is driving on a freeway, and discovers that they can't recall the last five miles, is often in a theta state--induced by the process of freeway driving. The repetitious nature of that form of driving compared to a country road would differentiate a theta state and a beta state in order to perform the driving task safely.

Individuals who do a lot of freeway driving often get good ideas during those periods when they are in theta. Individuals who run outdoors often are in the state of mental relaxation that is slower than alpha and when in theta, they are prone to a flow of ideas. This can also occur in the shower or tub or even while shaving or brushing your hair. It is a state where tasks become so automatic that you can mentally disengage from them. The ideation that can take place during the theta state is often free flow and occurs without censorship or guilt. It is typically a very positive mental state.

The final brainwave state is delta. Here the brainwaves are of the greatest amplitude and slowest frequency. They typically center around a range of 1.5 to 4 cycles per second. They never go down to zero because that would mean that you were brain dead. But, deep dreamless sleep would take you down to the lowest frequency. Typically, 2 to 3 cycles a second.

When we go to bed and read for a few minutes before attempting sleep, we are likely to be in low beta. When we put the book down, turn off the lights and close our eyes, our brainwaves will descend from beta, to alpha, to theta and finally, when we fall asleep, to delta.

It is a well known fact that humans dream in 90 minute cycles. When the delta brainwave frequencies increase into the frequency of theta brainwaves, active dreaming takes place and often becomes more experiential to the person. Typically, when this occurs there is rapid eye movement, which is characteristic of active dreaming. This is called REM, and is a well known phenomenon.

When an individual awakes from a deep sleep in preparation for getting up, their brainwave frequencies will increase through the different specific stages of brainwave activity. That is, they will increase from delta to theta and then to alpha and finally, when the alarm goes off, into beta. If that individual hits the snooze alarm button they will drop in frequency to a non-aroused state, or even into theta, or sometimes fall back to sleep in delta. During this awakening cycle it is possible for individuals to stay in the theta state for an extended period of say, five to 15 minutes--which would allow them to have a free flow of ideas about yesterday's events or to contemplate the activities of the forthcoming day. This time can be an extremely productive and can be a period of very meaningful and creative mental activity.

In summary, there are four brainwave states that range from the high amplitude, low frequency delta to the low amplitude, high frequency beta. These brainwave states range from deep dreamless sleep to high arousal. The same four brainwave states are common to the human species. Men, women and children of all ages experience the same characteristic brainwaves. They are consistent across cultures and country boundaries.

Research has shown that although one brainwave state may predominate at any given time, depending on the activity level of the individual, the remaining three brain states are present in the mix of brainwaves at all times. In other words, while somebody is an aroused state and exhibiting a beta brainwave pattern, there also exists in that person's brain a component of alpha, theta and delta, even though these may be present only at the trace level.

It has been my personal experience that knowledge of brainwave states enhances a person's ability to make use of the specialized characteristics of those states: these include being mentally productive across a wide range of activities, such as being intensely focused, relaxed, creative and in restful sleep.


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