by Janet Kwazniak
The very word ‘willpower’ implies a metaphor: that actions (and inhibition of actions) are a matter of conscious will and that they require the use of a resource or source of power. What powers the will is willpower. This is a sort of folk psychology – it takes a special sort of effort to have self-control, make a decision, solve a problem or resolve conflict. People vary in how much of this special effort they can sustain and it is limited. Will is like a muscle and it can tire, but if ‘exercised’ it can become stronger. Baumeister and others investigated this view of willpower experimentally. This metaphor is supported by showing that different tasks that were thought to require willpower interfered with one another. This phenomenon was called “ego depletion”. (I find that name hints at a Freudian picture.) It also appeared that tasks associated with willpower required glucose and this might be the limited fuel. This was a nice clear picture – the metaphor was holding up. But – this is one of those metaphors that is true if you believe it. If you believe that willpower is required to do hard mental work, that it is limited and can be used up, then that is what you will find.
But then the doubts came. Job and others showed the ego depletion works only if the subject believes the theory and Clarkson and others showed that the subject had to believe that they were short of energy for sugar to be limiting. It seems that gargling sugar water is as effective swallowing it. Some people think that physical exercise depletes willpower and for them it does. Others believe that exercise is mentally invigorating and surprise, it is. This history is reviewed by Brass (see citation below).
Doubts have also been shown in the area of conscious will as opposed to decisions and other ‘will’-requiring tasks having to be conscious. So both the will and the power in willpower are now suspect.
Brass and others also outline another way to look at willpower. The brain compares the predicted reward of doing something with the predicted effort. This is what affects what people decide to do, manage to do, and manage not to do. So instead of calling it willpower, we now can call it self-control and leave the old baggage behind. People vary in what they bring to the table when making the comparison of reward to effort. That is really what is involved in some people being able to resist temptation and others not. They include different values in the assessment of reward versus effort. The interference between tasks is thought to be due to the tasks requiring the same set of brain regions, and those areas not being good at doing two things at the same time.
Interestingly, most of the tasks that are described as drawing on willpower are tasks that involve the mPFC (medial pre-frontal cortex), and in particular the ACC (anterior cingulate cortex) . … The research outlined here suggests that the mPFC, and in particular the ACC, might be a central node in the neural circuit related to willpower. From what we know about the ACC, however, it is not plausible to assume that it provides a common resource, but rather that it has a kind of regulatory function determining the level of effort that is invested in a task. In a recent position paper, Holroyd and Yeung argued that the ACC is involved in choosing between different behavioural options and determining the level of effort that is invested in executing the chosen behavioural option. This description is consistent with the idea that the ACC implements a regulatory mechanism that determines the intentional investment in a specific response option or task. Accordingly, there is strong evidence for construing willpower as a regulatory function that can be related to specific brain structures in the mPFC. While such a regulatory mechanism is evidently required in situations of self-control and complex choice, we argue that any kind of intentional decision draws to some degree on this mechanism.
Brass M, Lynn MT, Demanet J, & Rigoni D (2013). Imaging volition: what the brain can tell us about the will. Experimental brain research. Experimentelle Hirnforschung. Experimentation cerebrale, 229 (3), 301-12 PMID: 23515626
fMRI: Adrift on Ten-Second Waves?
For the first time, neuroscientists have directly observed a slow, steady fluctuation – a ‘wave’ – in the blood flow to the brain.
The oscillation, which has a frequency of 0.1 Hz, or one cycle every 10 seconds, is mysterious, and could have big implications for neuroscience.
The researchers, led by Aleksandr Rayshubskiy of Columbia university, used a fancy camera to record high-resolution movies of the surface of the brain of a patient who’d had her skull opened up during surgery for a brain tumour.
By illuminating the brain with red, green, and blue lights, Rayshubskiy et al were able to measure oxygenated (HbO) and deoxygenated (HbR) blood along with total blood flow (HbT) – all thanks to the fact that oxygenated blood is redder.
This revealed that in some bits of the brain surface, the amount of total blood, and oxygenated blood, changed with a consistent 0.1 Hz rhythm:
A second patient, with epilepsy, did not show the same activity, however.
Further investigation showed the waves to be closely correlated with the expansion and contraction of certain small arteries. Therefore, the phenomenon seems to be myogenic (muscle-based) in origin, as it’s smooth muscle that controls artery size.
This isn’t the first time that 10-second blood flow waves have been suggested to exist in the brain, but until now, they’ve never been observeddirectly – and their origin has been a mystery. We now know it’s myogenic although what function it serves is anyone’s guess.
But why does it matter?
As a neuroscientist, I’m most interested in what it could mean for fMRIscans. fMRI is a cornerstone of modern neuroscience and it’s based on measuring the amount of deoxygenated haemoglobin (HbR) in different brain regions.
fMRI picks up neural activity indirectly because brain activity uses oxygen, and therefore alters HbR. Now the changes that fMRI picks up last around 6-12 seconds… in other words, a neural activation “peak” could easily be confused with one of those 0.1 Hz waves.
If that’s not bad enough, these waves would be especially harmful for functional connectivity fMRI. If these 10-second waves extend over large chunks of the brain, they might look very much like a coherent pattern ofactivation. Nightmare.
However… let’s not panic yet.
The 0.1 Hz cycle that Rayshubskiy found, remember, did not involve deoxyhaemoglobin at all – it was a change in oxygenated blood. Which makes sense, because that’s the kind of blood that arteries carry.
So one wouldn’t expect fMRI to be affected, at least not directly. Phew!
However… actually, Rayshubskiy et al claim that 10-second cycles do show up on fMRI (though they don’t try to explain it.) Here’s their fMRI data from the same patient who got the brain camera:
This data was recorded using an standard fMRI sequence, with a time resolution of 2 seconds. A 0.1 Hz wave is seen in the areas they show, but I do worry that they might have selected those areas precisely because they show that.
…manual inspection of voxel time-courses [was used] to identify the ROIs and corresponding time-courses shown in Figures 4D, E and F.
Which sounds a lot like the old fMRI ‘voodoo error‘ i.e. cherry picking brain areas that fit your model (perhaps by chance).
So what I’m saying is, this fMRI result might be voodoo… and that would begood news for fMRI. Rather ironic.
Luckily, it should be easy to try to replicate these results, because the Rayshubskiy fMRI protocol was a standard one. There are hundreds of neuroscientists who could reanalyze some comparable existing data, and look for 0.1 Hz oscillations.
If they don’t show up, the 10 second waves would still be an interesting physiological phenomenon, but one that fMRI users might be able to safely ignore.
Rayshubskiy A, Wojtasiewicz TJ, Mikell CB, Bouchard MB, Timerman D, Youngerman BE, McGovern RA, Otten ML, Canoll PD, McKhann GM 2nd, & Hillman EM (2013). Direct, intraoperative observation of approx. 0.1 Hz hemodynamic oscillations in awake human cortex: implications for fMRI.
Random Brain Waves Save Free Will?
A new paper adds to the perennial free will debate, by casting doubt on the famous Libet experiment.
Back in 1983, neuroscientists led by Benjamin Libet found that, about two seconds before someone presses a button ‘of their own free will’, a negative electrical potential – dubbed the Readiness Potential (RP) – began to build up in the cortex. Their EEG study showed that the brain seemed to have ‘decided’ before the conscious mind did – bad news for free will.
Since then, the meaning of the RP has been extensively debated. But the new study by Han-Gue Jo and colleagues of Freiburg makes a strong case that the “RP” is not really a ‘thing’ at all.
They say that, in the two seconds before a button press, you see both negative and positive changes, in roughly equal numbers. There are slightly more negative ones, so on average, there is a small negative “RP”, but only on average.
Almost half the button presses were not preceded by a negative potential, yet the button still got pressed – which means that the negative “RP” can’t directly reflect the decision to press.
Jo et al also ran a comparison condition, where participants had to listen to a beep, instead of pressing a button. So there was no ‘free choice’ to make, yet there were potential shifts in the two seconds before the beeps, just as there were before button presses. The difference was that in the beep task, there were equal numbers of positive and negative potentials, and they cancelled out to zero on average.
Jo et al say that these shifts are more or less random, spontaneous background changesin the brain – nothing to do with ‘readiness’ or decisions.
But why then are negative potentials more common just before movements? They suggest that
the negative deflections facilitate a movement in the near future, but they are not a neural sign of decision processes to move.
In other words, they don’t reflect a choice being made, rather they contribute to making a choice. Random brain changes influencing our choices… is that good news for free will?
Anyway, Jo et al did find a more substantial negative RP preceding button presses – albeit only about half a second beforehand. This occurred whether or not the ongoing slow wave was positive or negative:
Could this -0.5 second ‘late RP’ be the real marker of the decision to move? If so, it would still precede the moment of the conscious decision, which on average occurred at -0.25 seconds before the button got pushed.
Han‑Gue Jo, Thilo Hinterberger, Marc Wittmann, Tilmann Lhündrup Borghardt, & Stefan Schmidt (2013). Spontaneous EEG fluctuations determine the readiness potential: is preconscious brain activation a preparation process to move? Exp Brain Res DOI: 10.1007/s00221-013-3713-z
On Volition: Decision funnel - the Brass model
by Janet Kwasniak
Marcel Brass’ group has published a very wide ranging and interesting article on volition (citation below). They look at what fMRI results have shown (and not shown) on a number of questions regarding how volition works in the brain. Near the end of the paper they outline their own model of the progression of stages from goals to actions.
Here is their figure 1: Brain regions in the medial frontal cortex that have been implicated in human volition. SMA supplementary motor area, preSMA pre-supplementary motor area, RCZ rostral cingulate zone, dmPFC dorsomedial prefrontal cortex, vmPFC ventromedial prefrontal cortex
And here is their section on the funnel model:
Based on the research outlined above, we propose an extension of the WWW model (whether, what, when) of intentional action. This extension assumes that intentional action follows a kind of funnel-like organization that is related to an anterior-posterior gradient within the medial frontal cortex. It is, however, crucial to note that while this model focuses on the role of the mPFC (medial prefrontal cortex) in intentional action, we assume that areas in the lateral pre-frontal cortex, subcortical regions, and parietal regions are involved in intentional control of action as well.
Our model assumes that early stages of intentional action are related to anterior prefrontal brain regions. These brain regions process complex and heterogeneous information that is only broadly determined by specific task instructions or goals. Processing in these brain regions provide a sort of informational background, or intuition, and has a biasing function towards later processing stages. This complex set of information is funnelled when information travels more posteriorly and enters later stages of intentional action. Regions in the RCZ (rostral cingulate zone) are related to choices between different response options. Such choices are biased by bottom-up information but also by concrete instructions that operate as a top-down influence and thus are a result of the interplay between top-down and bottom-up processing. Furthermore, the RCZ determines the level of effort that is invested in pursuing a specific behaviour and thus regulates the ‘willpower’ that is invested in a specific choice. When a specific response option is selected, this information is transferred to brain areas more closely related to the motor system, namely SMA/PreSMA (supplementary motor area/pre-supplementary area). Here, the impulse to initiate a specific response is generated. At this point in the processing stream, it is still possible to disengage from the intention to act or to change the intended behaviour. Intentional inhibition is achieved by a signal from the dorso-medial prefrontal cortex that down-regulates activation in the SMA/preSMA. As a working hypothesis, we assume that the subjective experience of volition results from supra-threshold activation in brain circuits that are involved in the control of intentional action. Such subjective experiences are phenomenologically rich because they can be related to any level of the processing stream, ranging from intuitive feelings to concrete urges to act.
The funnel-like organization of human volition guarantees that choices are based on a broad scope of information. At the same time, it also ensures that we can choose very quickly and efficiently when necessary. Whether our choices are primarily determined by intuitions and introspective thoughts, or by explicit deliberation and task instructions, strongly depends on the specific task context and the time frame of our choices.
Brass M, Lynn MT, Demanet J, & Rigoni D (2013). Imaging volition: what the brain can tell us about the will. Experimental brain research. Experimentelle Hirnforschung. Experimentation cerebrale, 229 (3), 301-12 PMID: 23515626
Question about superior memory
Alright, Hi. I have a question. Sort of. My friends have been pushing me to look into this, so here goes. I have a really, really uncanny ability to learn- to absorb and retain information, I mean. I have never once studied for a test, I very rarely even read the textbooks for my courses, don’t do the homework I never take notes during class (I’m usually doodling) and yet, somehow, I always receive high marks on test and quizzes. And I retain information for much, much longer than most of my classmates do. (For years, as opposed to “The test is over and I no longer remember.”) And I’m always absorbing, too. Not just in class. I thought this was normal until I realized that… Well, that it wasn’t. And I’ve got to know why. What is going on here? Is there some kind of abnormal physical structure in my brain? (Something to do with the Hippocampus, perhaps, associated with memory-making?) Or is it something to do with my development as a young child, when those structures were forming? (I grew up in a bilingual household, speaking French. And I was read Shakespeare by second grade. My mother and father are both highly educated- my father never went to college, of course, but he is a paramedic and has vast knowledge of the human body. ) Is it a learning style thing? (Supposedly I’m somewhere between audio and visual.) Help me understand this!
Thanks for your submission! Although I am no expert, I do have some friends at UC Irvine working on cases such as yours. It sounds to me (though correct me if I’m wrong) that you have a highly superior autobiographical memory (HSAM) - the ability to recall events very precisely without use of mnemonics or practice. Though it’s difficult to understand exactly what mechanisms underly your ability, an MRI study on HSAM subjects has shown enlargement in the left temporoparietal junction (incorporates information from sensory systems and internal sensations), left posterior insula, and the lentiform nucleus (linked to OCD - I’m not insinuating anything, just thought you would find that interesting). As to why, as far as I know no correlations have been made between upbringing and HSAM, so your particular ability is probably due mainly to genetics. That being said, development in an intellectual environment always elevates cognitive function. (They presented at SFN in 2011 - Highly Superior Autobiographical Memory (HSAM): An investigation of the behavioral and neuroanatomical components)
I would be interested to see if your short term memory also shows significant differences from controls. It may be worth taking an online working memory test just to see.
Whole-brain functional imaging at cellular resolution using light-sheet microscopy
Here’s the abstract:
Brain function relies on communication between large populations of neurons across multiple brain areas, a full understanding of which would require knowledge of the time-varying activity of all neurons in the central nervous system. Here we use light-sheet microscopy to record activity, reported through the genetically encoded calcium indicator GCaMP5G, from the entire volume of the brain of the larval zebrafish in vivo at 0.8 Hz, capturing more than 80% of all neurons at single-cell resolution. Demonstrating how this technique can be used to reveal functionally defined circuits across the brain, we identify two populations of neurons with correlated activity patterns. One circuit consists of hindbrain neurons functionally coupled to spinal cord neuropil. The other consists of an anatomically symmetric population in the anterior hindbrain, with activity in the left and right halves oscillating in antiphase, on a timescale of 20 s, and coupled to equally slow oscillations in the inferior olive.
Sleep cleans our brains, renews our synapses, consolidates our memories
by Deric Bownds
Xie et al. have used an elegant two-photon imaging technique to compare awake and sleeping mouse brains. They find that metabolic waste products of neural activity are cleared out of the sleeping brain at a faster rate than during the awake state:
…convective fluxes of interstitial fluid increased the rate of β-amyloid clearance during sleep. Thus, the restorative function of sleep may be a consequence of the enhanced removal of potentially neurotoxic waste products that accumulate in the awake central nervous system.
The review of this work by Underwood has a nice graphic of the fluid-filled channels (pale blue) that expand to flush out waste:
The role of sleep in memory consolidation is well known, and further work of Tononi’s group has suggested that in rats, sleep maintains an overall synaptic balance, by uniformly dialing down synapses that have expanded their activity during the day. (I have also previously pointed to work on fruit flies by Tononi’s group coming to a similar conclusion.)
Work of this sort suggests that the 50-70 million Americans who have insufficient sleep or some kind of sleep disorder (like sleep apnea) are carrying around extra garbage in their brains during the day and have brain synaptic connection that haven’t recovered from previous days’ activities, both factors that would seem likely to compromise our mental function!
Change of Information Processing in Loss and Recovery of Consciousness
One of the most elusive aspects of the human brain is the neural fingerprint of the subjective feeling of consciousness. While a growing body of experimental evidence is starting to address this issue, to date we are still hard pressed to answer even basic questions concerning the nature of consciousness in humans as well as other species. In the present study we follow a recent theoretical construct according to which the crucial factor underlying consciousness is the modality with which information is exchanged across different parts of the brain. In particular, we represent the brain as a network of regions exchanging information (as is typically done in a comparatively young branch of mathematics referred to as graph theory), and assess how different levels of consciousness induced by anesthetic agent affect the quality of information exchange across regions of the network. Overall, our findings show that what makes the state of propofol-induced loss of consciousness different from all other conditions (namely, wakefulness, light sedation, and consciousness recovery) is the fact that all regions of the brain appear to be functionally further apart, reducing the efficiency with which information can be exchanged across different parts of the network.
Psychedelic drugs cause cortical desynchronization
by Deric Bownds
From Muthukumaraswamy et al.:
Psychedelic drugs produce profound changes in consciousness, but the underlying neurobiological mechanisms for this remain unclear. Spontaneous and induced oscillatory activity was recorded in healthy human participants with magnetoencephalography after intravenous infusion of psilocybin—prodrug of the nonselective serotonin 2A receptor agonist and classic psychedelic psilocin. Psilocybin reduced spontaneous cortical oscillatory power from 1 to 50 Hz in posterior association cortices, and from 8 to 100 Hz in frontal association cortices. Large decreases in oscillatory power were seen in areas of the default-mode network. Independent component analysis was used to identify a number of resting-state networks, and activity in these was similarly decreased after psilocybin. Psilocybin had no effect on low-level visually induced and motor-induced gamma-band oscillations, suggesting that some basic elements of oscillatory brain activity are relatively preserved during the psychedelic experience. Dynamic causal modeling revealed that posterior cingulate cortex desynchronization can be explained by increased excitability of deep-layer pyramidal neurons, which are known to be rich in 5-HT2A receptors. These findings suggest that the subjective effects of psychedelics result from a desynchronization of ongoing oscillatory rhythms in the cortex, likely triggered by 5-HT2A receptor-mediated excitation of deep pyramidal cells.
Information sharing as a measure of brain consciousness
by Deric Bownds
King et al. make measurements they suggest are a signature of conscious state in awake but noncommunicating patients. I pass on the summary, abstract, and one of their figures (and, the first graphic, thanks to Jean-Rémi King, who offers the unedited PDF of the article here):
• Theories of consciousness link conscious access to global information integration
• 181 EEG recordings were acquired, including 143 from VS and MCS patients
• Information sharing across current sources was estimated with a new measure
• The results suggest that unconscious patients have lower global information sharing
Neuronal theories of conscious access tentatively relate conscious perception to the integration and global broadcasting of information across distant cortical and thalamic areas. Experiments contrasting visible and invisible stimuli support this view and suggest that global neuronal communication may be detectable using scalp electroencephalography (EEG). However, whether global information sharing across brain areas also provides a specific signature of conscious state in awake but noncommunicating patients remains an active topic of research. We designed a novel measure termed “weighted symbolic mutual information” (wSMI) and applied it to 181 high-density EEG recordings of awake patients recovering from coma and diagnosed in various states of consciousness. The results demonstrate that this measure of information sharing systematically increases with consciousness state, particularly across distant sites. This effect sharply distinguishes patients in vegetative state (VS), minimally conscious state (MCS), and conscious state (CS) and is observed regardless of etiology and delay since insult. The present findings support distributed theories of conscious processing and open up the possibility of an automatic detection of conscious states, which may be particularly important for the diagnosis of awake but noncommunicating patients.
Figure - wSMI Increases with Consciousness, Primarily over Centroposterior Regions(A) The median wSMI that each EEG channel shares with all other channels is depicted for each state of consciousness.(B) 120 pairs formed by 16 clusters of EEG channels are depicted as 3D arcs whose height is proportional to the Euclidian distance separating the two clusters. Line color and thickness are proportional to the mean wSMI shared by the corresponding cluster pair.
Overcome Your Fears While You Sleep
by Breanna Draxler
Nightmares aren’t the only things that can haunt your slumber. Researchers can now trigger fears while you’re sleeping—in order to help you overcome them.
Neurologist Jay Gottfried, who authored the study, told the Washington Post,
“Sleep sort of stamps memories in more strongly. That’s when a lot of memory formation can take place.”
To test this, the researchers showed pictures of two faces to 15 participants. With each face came a particular odor—new sneaker, lemon, clove, etc.—as well as a little electric shock. After repeating this conditioning, participants came to fear their particular face/smell/shock combos.
Then the participants went to sleep. During their deep sleep period, when memories are thought to be formed, the researchers repeatedly wafted one of the face-associated odors at each participant, to expose the unconscious brain to the fear stimulus.
Rise and Shine
Once awake, the participants showed less fear (measured by sweat and brain activity) at the sight of the face they “smelled” during the night, than the one whose scent they hadn’t been exposed to during dreams. Study author Katherina Hauner told CBS News,
“While this particular odorant was being presented during sleep, it was reactivating the memory of that face over and over again which is similar to the process of fear extinction during exposure therapy.”
Exposure therapy works by having people face their fears, little by little, until they’re no longer afraid. But for some people and some fears, even a little bit of exposure can be too much. Subconscious exposure to fear offers a potential way to get around this.
The researchers say their method, published in Nature Neuroscience this week, could also work for preexisting fear by conditioning a person to associate a particular smell with that fear. That’s good, if far-off, news for anyone with arachnophobia, trypophobia, or even post-traumatic stress disorder (PTSD).
Theory of Mind and the mind of the market
The financial community has been in a striking tizzy over the fact that the Federal Reserve didn’t do what they were predicting, i.e. start to dial back on their economic stimulus. The financial community also has not been very good at predicting or knowing when a financial bubble is growing. Perhaps work like this piece by Martino et al. casts some mechanistic light on this. They demonstrate that the ability to infer the intentions and mental states of other individuals (“theory of mind”) biases evaluation when people interact not with individuals but with complex modern institutions like financial markets, contributing to the formation of economics bubbles. Here is their summary:
The ability to infer intentions of other agents, called theory of mind (ToM), confers strong advantages for individuals in social situations. Here, we show that ToM can also be maladaptive when people interact with complex modern institutions like financial markets. We tested participants who were investing in an experimental bubble market, a situation in which the price of an asset is much higher than its underlying fundamental value. We describe a mechanism by which social signals computed in the dorsomedial prefrontal cortex affect value computations in ventromedial prefrontal cortex, thereby increasing an individual’s propensity to ‘ride’ financial bubbles and lose money. These regions compute a financial metric that signals variations in order flow intensity, prompting inference about other traders’ intentions. Our results suggest that incorporating inferences about the intentions of others when making value judgments in a complex financial market could lead to the formation of market bubbles.
Coma: researchers observe never-before- detected brain activity
Researchers from the University of Montreal and their colleagues have found brain activity beyond a flat line EEG, which they have called Nu-complexes (from the Greek letter n). According to existing scientific data, researchers and doctors had established that beyond the so-called “flat line” (flat electroencephalogram or EEG), there is nothing at all, no brain activity, no possibility of life. This major discovery suggests that there is a whole new frontier in animal and human brain functioning.
The researchers observed a human patient in an extreme deep hypoxic coma under powerful anti-epileptic medication that he had been required to take due to his health issues. “Dr. Bogdan Florea from Romania contacted our research team because he had observed unexplainable phenomena on the EEG of a coma patient. We realized that there was cerebral activity, unknown until now, in the patient’s brain,” says Dr. Florin Amzica, director of the study and professor at the University of Montreal’s School of Dentistry.
Dr. Amzica’s team then decided to recreate the patient’s state in cats, the standard animal model for neurological studies. Using the anesthetic isoflurane, they placed the cats in an extremely deep—but completely reversible—coma. The cats passed the flat (isoelectric) EEG line, which is associated with silence in the cortex (the governing part of the brain). The team observed cerebral activity in 100% of the cats in deep coma, in the form of oscillations generated in the hippocampus, the part of the brain responsible for memory and learning processes. These oscillations, unknown until now, were transmitted to the master part of the brain, the cortex. The researchers concluded that the observed EEG waves, or Nu-complexes, were the same as those observed in the human patient.
Dr. Amzica stresses the importance of understanding the implications of these findings. “Those who have decided to or have to ‘unplug’ a near-brain-dead relative needn’t worry or doubt their doctor. The current criteria for diagnosing brain death are extremely stringent. Our finding may perhaps in the long term lead to a redefinition of the criteria, but we are far from that. Moreover, this is not the most important or useful aspect of our study,” Dr. Amzica said.
From Nu-complexesto therapeutic comas
The most useful aspect of this finding is the therapeutic potential, the neuroprotection, of the extreme deep coma. After a major injury, some patients are in such serious condition that doctors deliberately place them in an artificial coma to protect their body and brain so they can recover. But Dr. Amzica believes that the extreme deep coma experimented on the cats may be more protective.
“Indeed, an organ or muscle that remains inactive for a long time eventually atrophies. It is plausible that the same applies to a brain kept for an extended period in a state corresponding to a flat EEG,” says Professor Amzica. “An inactive brain coming out of a prolonged coma may be in worse shape than a brain that has had minimal activity. Research on the effects of extreme deep coma during which the hippocampus is active, through Nu-complexes. is absolutely vital for the benefit of patients.”
“Another implication of this finding is that we now have evidence that the brain is able to survive an extremely deep coma if the integrity of the nervous structures is preserved,” said lead author of the study, Daniel Kroeger. “We also found that the hippocampus can send ‘orders’ to the brain’s commander in chief, the cortex. Finally, the possibility of studying the learning and memory processes of the hippocampus during a state of coma will help further understanding of them. In short, all sorts of avenues for basic research are now open to us.”