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mr peabody

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The control interrupt model of psychedelic action

by James L. Kent | Psychedelic Information Theory

The brain is an information processing organ that uses top-down signal modulation to control the flow of bottom-up sensory input. Feedback modulation of incoming signal is an example of self-stabilizing control in a signal processing system. Using the tenets of cognition and control theory it is possible to describe a model in which hallucinogens periodically interrupt the top-down modulatory control of perception to create sensory interference patterns, multisensory frame destabilization, and altered states of consciousness.

Bottom-up perception, top-down control

What we perceive as waking consciousness is a synthesis of bottom-up sensation modified by top-down expectation and analysis. Incoming sensation is gated by the top-down focus of the subject. Inhibitory feedback subtracts background noise while excitatory feedback resolves and amplifies salient data. This configuration describes a signal filter/amplifier with an inhibitory/excitatory feedback loop to control signal focus and content discrimination. The top-down filtering and focusing of incoming sensory signal is an autonomic reflex and is perceptually seamless; the brain blocks background noise, transitions focus, and recognizes objects smoothly and without disrupting subjective frame continuity.

Constraint, control, and feedback inhibition

Feedback excitation is applied in sensory circuits to amplify salient input, but the majority of the brain’s feedback circuits are inhibitory, meaning that human consciousness is more constrained than unconstrained. In dynamical information processing systems, signal constraint and error correction is applied through negative feedback to subtract or cancel perturbation and noise entering the signal channel; this is known as control theory. In sensory networks, such as the layers of the cortex or the retina, fast inhibition is applied laterally to boost contrast discrimination in sensory detail; this is called lateral inhibition. Fast inhibition in the cortex can also be applied from the bottom-up as well as laterally, this is called the synaptic triad of fast inhibition. Inhibition can also be applied from the top-down, allowing the cortex to gate sensory input from the thalamus; this is called feedback inhibition, and it is typically tonic, meaning top-down feedback produces an inhibitory effect over many consecutive spike trains for extended periods of channeled focus. When the brain is alert and focused, this also means it is highly constrained by inhibitory feedback.

In human consciousness control is applied through negative feedback to constrain perception. When people express their fears about psychedelics, the most commonly voiced concern is the fear is losing control; this is because psychedelics subvert the constraints of sensory feedback control to allow perception and behavior to become unconstrained by tonic inhibition. Tonic inhibition is expressed from learned concepts about the self and ego, and suppresses what is considered abnormal or outside the acceptable range of consciousness. Linear consciousness is constrained and focused on real-time ego behavior; nonlinear consciousness is unconstrained and goes wherever it is driven by input state variables, or set and setting.

In order for a perceptual system to transition from a linear to a nonlinear state, negative feedback control must be subverted. If control is entirely removed then perception becomes totally unconstrained, leaving a system that is quickly overloaded with too much information. If control is placed in a state where it is partially removed or in a toggled superposition where it is alternately in control and not in control over the period of a rapid oscillation, then the constraints of linear sensory throughput will bifurcate into a nonlinear spectrum of multi-stable output with signal complexity correlating to the functional interruption of control. Common entheogenic wisdom states that you must relinquish control and submit to the experience to get the most out of psychedelics. Holding onto control causes negative experiences and amplifies anxiety; letting go of control and embracing unconstrained perception is a central psychedelic tenet. This demonstrates that psychedelics directly subvert feedback control over linear perception to promote states of unconstrained consciousness.

Control interrupt model of psychedelic action

Before the mind can start hallucinating the top-down modulatory control of consciousness must first be interrupted. Interrupting top-down control of consciousness allows the mind to destabilize into novel information processing configurations. When top-down control of waking consciousness is destabilized, neural oscillators in the brain will spontaneously organize into coherence with the most energetic local drivers. This process can be described in terms of oscillator entrainment and resonance; when the modulatory driver maintaining global oscillator coherence is interrupted, uncoupled oscillators will naturally fall into synchrony with most energetic periodic drivers in the environment. In this state the normally inflexible configurations of consciousness and perception become extensible and open to the influence of environmental feedback. This explains why psychedelics create synesthesia or cross-sensory representations of energetic sensory drivers, and why set and setting have a profound influence on the tone and content of a psychedelic experience.

When top-down modulatory control of consciousness is interrupted, the seamless nature of multisensory perception degrades and the subject begins to experience hallucinations. Early indicators of modulatory interruption would include periodic high-frequency distortion or noise in sensory networks. In tactile networks this periodic interruption may be felt as parasthesia, or phantom tingling and throbbing; in visual networks it may be perceived as phosphenes, or strobing or pulsating of light intensity, possibly fast enough to produce geometric hallucinations; in audio networks it may be perceived as tinnitus, ringing, humming, buzzing, or tones that cycle up and down in pitch. These are all descriptions of field-based hallucinations generated in response to periodic interruptions along multisensory signal pathways. The speed and intensity of the control interrupt, and thus the speed and intensity of the hallucinations, are a direct result of the hallucinogen’s pharmacodynamics and method of ingestion.


Using an ADSR envelope we can model the intensity with which any
hallucinogen interrupts multisensory frame perception.


Control interrupt envelopes

Using control interrupts as the source of hallucinogenesis, we can model hallucinogenic frame distortion of multisensory perception the same way we model sound waves produced by synthesizers; by plotting the attack, decay, sustain, and release (ADSR envelope) of the hallucinogenic interrupt as it effects consciousness. For example, nitrous oxide (N20) inhalation alters consciousness in such a way that all perceptual frames arise and fall with a predictable “wah-wah-wah” time signature. The throbbing “wah-wha-wah” of the N20 experience is a stable standing wave formation that begins when the molecule hits the neural network and ends when it is metabolized, but for the duration of N20 action the “wah-wah-wah” completely penetrates all modes of sensory awareness with a strobe-like intensity. The periodic interrupt of N20 can be modeled as a perceptual wave ambiguity that toggles back and forth between consciousness and unconsciousness at roughly 8 to 11 frames-per-second, or @8-11hz.5 Consciousness rises at the peak of each “wah” and diminishes in the valleys in between. On sub-anesthetic doses, N20 creates a looping effect where frame content overlaps into the following frame, causing a perceptual cascade similar to fractal regression. We can thus model the interrupt envelope of N20 as having a rounded attack, fast decay, low sustain, medium release, with an interrupt frequency of @8-11hz. Any psychoactive substance with a similar interrupt envelope will produce results that feel similar to the N20 experience. (Fig. 3) For instance, Smoked Salvia divinorum (vaporized Salvinorin A&B, or Salvia) has an interrupt envelope similar to N20, except Salvia has a harder attack, a slightly longer decay, a more intense sustain, a slightly longer release, and a slightly faster interrupt frequency (@12-15hz). These slight changes in the frequency and shape of interrupt envelope cause Salvia to feel more physically intense, more hallucinatory, and more disorienting than N20, even though they share a similar throbbing or tingling sensation along the same frequency range.


Modeling the interrupt envelope for N2O and Salvia we can see N2O
has a hard but rounded attack and decay. In contrast Salvia has a
slightly faster and more intense ADSR profile, describing a more
biting and disorienting effect on multisensory perception.


Using interrupt envelopes we can contrast smoked Salvia or inhaled N20 with vaporized DMT (N,N-dimethyltryptamine), which when smoked has similar onset and duration to both substances but very different hallucinogenic effects. Unlike the throbbing periodicity of N20, vaporized DMT produces an interrupt frequency associated with high-pitched carrier waves and high-speed frame flicker (24-30+ hz). The frequency of DMT’s interrupt is so rapid the entire body ramps up in panicked response to the new driver. The rate of DMT’s visual frame flicker is fast enough to instantly produce and sustain geometric hallucinations and fully realized animations.7 Taking these subjective effects into account we can model DMT’s interrupt envelope as having a moderate attack, long decay, medium sustain, long release, and high frequency (24-30+hz). The moderate attack means DMT’s perceptual frame interference is less of a physical throbbing than N20, but because of a higher frequency and longer frame release the rendering of DMT hallucination is more fluid, detailed, seamlessly aliased, and fades longer over a higher number of frames.

The interrupt envelopes modeled here are approximate and based on reported subjective effects, but may also give some insight into the pharmacodynamics of each substance.8 Following the logic of the Control Interrupt Model, it can be assumed that each hallucinogen has a unique interrupt envelope based on receptor affinity, receptor density, rate of metabolism, and so on, and each unique interrupt envelope creates a distinct type of interference pattern in multisensory perception. The interrupt envelope for any substance will also change if the substance is ingested orally as opposed to vaporized or injected; the speed of absorption into the bloodstream will naturally affect the intensity of ADSR values. This is why each psychedelic can produce unique sensations and hallucinations, and why each psychedelic can produce subtle variations in the speed and intensity of hallucination depending on method of ingestion.

By modeling the interrupt envelope of a psychoactive substance it is possible to accurately predict its subjective results on multisensory perception. Non-drug sources of hallucination, such as those caused by psychosis, deprivation, fever, or schizophrenia, may also have unique and quantifiable control interrupt envelopes related to erratic multisensory frame modulation.

Control interrupt and shamanism

If consciousness must have a top-down control frequency to remain stable, and psychedelics produce a periodic interruption of this control frequency, then the interaction between the perceptual control frequency and the periodic hallucinogenic interrupt can be described as a wave interference pattern in global oscillator coherence. Subjects on moderate doses of psychedelics can override the hallucinogenic interrupt and retain global coherence via energetic physical movement or repetitive behaviors like chanting or dancing. Conversely, if the subject lies motionless then the interrupt fully destabilizes consciousness into a depersonalized dreamlike trance. These reports indicate that even though psychedelics destabilize top-down modulatory control of consciousness, feedback control and system stability can be entrained back into coherence via external periodic drivers, including rhythmic motor activity, drumming, singing, chanting, rocking back and forth, dancing, and so on. It is no accident that these are also the basic formal elements of shamanic ritual.

In physical terms, the shaman is the primary energetic driver, or resonator, in the production of a standing hallucinogenic interference pattern in the consciousness of the subject. By prescribing a psychedelic substance the shaman introduces the control frequency interrupt, and through ritual craft and showmanship the shaman applies new periodic drivers to influence the tone and texture of the resulting interference pattern. By mixing the hallucinogenic control interrupt with a custom periodic driver the shaman can fully entrain consciousness and manipulate all facets of the subject’s mind with high precision. This description of the precision wave-based manipulation of neural oscillators within the psychedelic state can be called applied psychedelic science, physical shamanism, or Shamanism in the Age of Reason.

 
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mr peabody

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Everyone should understand the potential heart risk of psychedelics

The Psychedelic Scientist | Dec 6 2019

An important part of building a healthy psychedelic community is being fully aware of the risks of psychedelics.

This includes both being educated about the risk of trauma and injury from challenging psychedelic experiences, but also the potential physiological harm they can do to us.

It appears that occasional large doses of psychedelics don’t do much harm to healthy individuals, as long as they are properly looked after to prevent really damaging traumatic experiences. But we don’t have any evidence yet that regular microdosing is safe.

There are reports of people microdosing for many months in succession, with no ill effects aside from tiredness. But there is always the chance that with longer term microdosing regimens, unwanted physiological side effects could start building up. Ingesting any substance over a long period, no matter how harmless they are in single doses, could cause significant changes in your body.

Here’s what we know so far about the potential risks of taking frequent doses of psychedelics…

MDMA and heart disease

Various studies have shown that there is a link between regular, high-dose MDMA use and heart defects. Although the conclusion of this research is that the occasional dose of MDMA will not harm you, it has potential implications for frequent, long-term psychedelic use – especially microdosing – and I’ll explain how.

MDMA’s harmful effects on the heart are due to its activation of the 5-HT2B receptor. This receptor is present all over the heart, and convincing evidence suggests that the long-term activation of this receptor leads to the formation of ‘valvular strands’, which can lead to Valvular Heart Disease (VHD) in extreme cases.

Classic psychedelics, including LSD and psilocybin, also activate this 5-HT2B receptor.

Again – cases of VHD are only found in people who use MDMA very frequently (several times a week) and at high doses. The question we want to answer is: do the classic psychedelics (LSD and psilocybin) activate the 5-HT2B receptors in our hearts as much as MDMA? And – is there a risk of VHD with long-term usage, like microdosing?

LSD, psilocybin, and the 5-HT2B receptor

LSD and psilocybin work by mimicking the effect of our natural neurotransmitter, serotonin. Therefore both these psychedelics activate a wide range of serotonin receptors, including the 5-HT2B receptor. The real question is, are these psychedelics activating the 5-HT2B receptor enough to cause damage to the heart?

Unfortunately, we don’t have a clear answer to that question yet. We know that LSD and psilocybin bind strongly to the 5-HT2B receptor, but we don’t know how comparable this is to the way that MDMA (and other cardiotoxic molecules) binds to 5-HT2B. So right now, there is no way of knowing for sure if there is any risk.

We can, however, make some educated speculation.

We can look at a previous study of a compound that definitely causes heart damage through the 5-HT2B receptor: fenfluramine. This was a weight-loss drug that was withdrawn in the 90s after a small percentage of people developed heart disease after using it.

Studies found that fenfluramine roughly doubled the risk of developing VHD after a 90-day treatment course, at a dose of around 30mg/day. Fenfluramine has an affinity (Ki) for the 5-HT2B receptor of around 30nM.

LSD has a similar affinity for the 5-HT2B receptor as fenfluramine, a Ki of around 30nM. However, when we take a dose of LSD, it is several hundred times less than a single dose of fenfluramine (100ug compared to 30mg). So it’s highly unlikely that a single dose of LSD, even if it’s a high dose, would have any immediate cardiotoxicity.

With microdosing, it’s a different story. A typical microdosing regimen involves taking the equivalent of around 3ug/day, several thousand times less than fenfluramine. However, the main reason that fenfluramine is cardiotoxic is because it is taken every day in a continuous regimen.

The comparison to fenfluramine isn’t great – it’s quite possible that a daily dose of fenfluramine affects the 5-HT2B receptor in a vastly more harmful way than intermittent microdoses.

Overall, it seems reasonable to assume that microdosing probably has nowhere near the heart risk associated with fenfluramine. At the same time, it’s also very possible that even very minor, but frequent activation of the 5-HT2B receptor could slightly increase our risk of heart disease.

Conclusions

It seems likely that single large dose psychedelic experiences, and short-term microdosing routines, are relatively safe for your body. Decades of anecdotal reports and epidemiological studies back this up.

What remains to be seen is whether long-term microdosing regimens (i.e. for many months or even years) have a potential to damage the heart. This is why it is sensible to microdose for no longer than 90 days, and spread out your microdosing regimens throughout the year. If you have a pre-existing heart condition, it is especially important to avoid extended periods of microdosing.

It’s important for the community to be aware of these potential risks. I often come under fire for “scaremongering” when I bring up this research. But the reality is that educating ourselves about the science, and showing that we have a firm understanding of psychedelic safety, gives us the best chance of defeating the authorities hell-bent on shutting down our movement.

 
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mr peabody

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The neuroscience of psychedelic drugs

by Ruairi Mackenzie | Technology Networks | 13 Dec 2019

Psychedelic drugs have long been exiled to the fringes of medicine, dismissed as recreational drugs with limited therapeutic potential. That all changed with the breakthrough therapy status granted last year to psilocybin, the active compound found in psychedelic mushrooms, for its ability to rapidly reverse treatment-resistant depression. This has led to an explosion of interest in the field, with new institutes opening and new disorders identified as targets for psychedelic therapy. In our latest interview series, we discuss the potential of psychedelics to revolutionize clinical neuroscience with thought leaders in the field.

Professor David Nutt, Edmond J. Safra Professor of Neuropsychopharmacology at Imperial College London, has never been afraid to stick his head above the parapet on the topic of drugs. His repeated calling-out of the failures of contemporary drug policy has seen him butt heads with academics and politicians alike . But there are signs that opinions about the use of drugs in science and society are tilting at last. The opening of Imperial’s Center for Psychedelic Research, where Nutt is Deputy Head, was one clear indication that the wider field is becoming more open to the therapeutic potential of psychedelics. In this interview with Professor Nutt, we discuss pot, policy and the potential of psilocybin.

Two major new centers for psychedelic research, at Imperial and Johns Hopkins, have been established in the last year. How significant are these developments for psychedelic research?

I think it’s great that there are centers being set up in academic institutions, that’s why we set ours up. The main thing about them is the fact that they’ve been set up in two of the top medical research institutes in the world essentially says that psychedelic research is now accepted as a major branch of medicine, particularly in psychiatry and neuroscience. That’s why they’re so important.

Another recreational drug that has become more widespread in research is cannabis, but the science of cannabis seems less established than the recreational cannabis industry, which has taken off in the US. Do you think the that acceptance of a drug in clinical and recreational use are linked inextricably or are they separate issues?

Well I think the point to make – I think this is a fundamental point, the most important thing I’m going to tell you – is that our research on the neuroscience of psychedelics was the reason we then moved into the clinic, because our first studies on psilocybin, using FMRI imaging, showed surprising, unexpected brain effects which were predictive, we thought, of it being antidepressant. This antidepressant trial, funded by the MRC, that we conducted was predicated on the neuroscience. It was translational science. The brain changed in the same way as it changes with frequency of depression, so we tried it in depression. It’s forward translational science. That’s completely different from cannabis, where that drug has been widely used therapeutically and eventually the medical profession was dragged screaming and protesting to use it. I believe that our science of psychedelics, particularly psilocybin, has been the driver for us doing it, but it’s also given other people the confidence to move it to the clinic because it is no longer just based on self-report from anecdotes of people using mushrooms in their living room.

The studies involved in using psychedelics are very different from casual use and generally their safety seems to require a controlled environment in which they can be taken therapeutically. Is there a way to make these drugs safe to take outside that environment?

One of the reasons we were allowed to do the psilocybin depression study was that I persuaded the MHRA that psilocybin was a very safe drug, because we know about a million young people in Britain a year use mushrooms and there’s very little harm.

I have no worries about people using it recreationally, but I do have worries about depressed people using it recreationally because we have found that the effects of psilocybin in depression are usually very difficult, painful and challenging and I would not have been comfortable with people self-medicating in the middle of a mountain in Wales with mushrooms if they go through the kind of trips that our depressed patients went through. If you’re using these for medicine, you need to have appropriate psychotherapy and medical cover. If you’re using them for recreation, well as long as you’re aware of the risks and you’re not suffering from major mental illness, they’re probably relatively safe.

With the treatment of mental health disorders, it seems unlikely we’ll find some kind of cure-all. Which indications are psychedelics most promising for?

Pretty much all the trials have been done with psilocybin and the areas of clear efficacy are depression – that’s our trial – smoking cessation – that was the Matt Johnson [a Professor at Johns Hopkins] trial and alcoholism, that’s the Michael Bogenschutz [of NYU] trial.

There are also two rather beautiful studies that were blinded studies done in anxiety and depression in people who are facing end of life stress, done by Johns Hopkins and by New York University. Those are the best indications we have at present. There’s also been one rather nice ayahuasca study. Ayahuasca is a preparation of the psychedelic DMT. It’s usually used in Latin America, so with ayahuasca, there’s been a Brazilian study showing that Ayahuasca can work in depression.

What links depression, tobacco, smoking and alcoholism, we believed - this is our theory – that in these three indications people’s brain gets locked into a way of thinking from which it is hard to disengage. Smoker’s crave cigarettes; they think about cigarettes enormously when they’re trying to stop, or when they have stopped. Alcoholics crave alcohol; their brain is consumed thinking about alcohol and depressed people’s brains are consumed by depressive ruminations. The common factor in those three disorders is the inability of the brain to disengage from maladaptive brain processes.

What psychedelics do in the actual trip itself is have a powerful disrupting effect on brain circuits which underpin those repetitive processes. It’s that disruption that allows people to escape from disorder. Our belief is that any disorder that is accompanied by what you might called locked-in overthinking, could respond. That could also include other forms of addiction, like heroin addiction. We’re teeing up to do a heroin study soon, but also OCD, where people are over engaged in avoidance and fear of responding, avoiding the fearful consequences.

I do not believe psychedelics will be helpful in disorders such as ADHD or schizophrenia or bipolar disorder, but they will be I think useful with disorders that are internalizing disorders. Disorders where people get locked into an internal mindset from which they can’t escape. We’re also setting up to do a trial in anorexia where people have an excessive preoccupation with body image.

Are there any myths around these drugs that you’d like to disperse?

Yes! The first is the continual lying about the fact that these are addictive. The United Nations say they’re addictive, the FDA say they’re addictive, the Misuse of Drugs Act says they’re harmful and addictive. These drugs are anti-addictive. They do not cause addiction. One of the reasons they are banned is because people said they were addictive when they’re not; they treat addiction. They don’t cause addiction. The reason they don’t cause addiction is partly because they treat addiction and partly because they produce a very rapid tolerance or desensitization and that occurs so fast that people stop using. There’s a very nice study the US military did, where on the third day the effects wore off. It is one of the reasons they don’t use it in warfare because they realized the Russians could pre-treat their people to develop tolerance for a couple of days. They don’t cause dependence; they don’t cause addiction.

The other myth is they make you crazy. They don’t make you crazy. They might make people who have a propensity to be psychotic more psychotic, but they don’t produce enduring changes in people, negative changes in people’s mental state. If anything they tend to produce enduring positive changes in people. The third myth of course is that they’re very dangerous but as far as I can see there’s almost no deaths from these drugs ever in the history of the world, except from misadventure and of course it is definitely not wise to be taking a psychedelic when you’re sitting on the cliffs in Dover, like a couple of kids did a few years ago at Beachy Head. It’s very silly to go to a place where you are at risk if you’re tripping. In hospital settings, in controlled settings, recreationally these drugs have a low propensity to cause harm.

Psychedelic drugs were very much made out to be dangerous in the 1970s and 1980s, which has hindered research. Is this kind of demonization driven by policy makers or can science play a role now in making sure those same mistakes aren’t repeated?

The demonization was all political, it all goes back to the Vietnam War, to the fact that young men didn’t want to fight in a war in a place they’d never heard and didn’t want to fight against an enemy they’d never seen for a cause they didn’t understand and they refused to fight. They went to San Francisco, they listened to the Grateful Dead, they took acid and they started the anti-war movement. LSD is the only drug that has ever been banned because it changed the way people voted! In those days, you couldn’t ban a drug just because people were using it, you had to find harm. The hysteria about the harms of psychedelics was all created by the drug enforcement agency and the CIA that justified banning it. Once LSD was banned as is almost always the case, they tried to ban every other drug which might be used instead of it. They banned psilocybin, they banned DMT etc. The banning of these drugs is a political act and it was opposed by many scientists at the time.

Will the establishment of large centers like the ones at Imperial and Hopkins stop scientists being ignored again?

It’s a great question. I think you need to ask scientists that, they don’t usually tell me the truth. If they like what I do they say it’s great, but if they don’t, they rarely confront me because I’m quite combative! I don’t know what proportion of scientists are on board with [the centers] but a surprising number of very senior people,professors from top institutions around the world have come up to me, by themselves, shaken my hand and said thanks for doing this, we couldn’t do it, but you can, thank you.

There’s a huge stigma against these drugs. Here’s a true story. I wrote a definitive paper on how the regulations, the scheduling of these drugs destroyed research. I wrote in Nature Reviews Neuroscience, about five years ago. The journal contracted it and said the condition was I had to get an American author. I rang up a friend of mine who works in this field in America and I said, great news, we’re going to be contracted to write a Nature Reviews Neuroscience paper on how the drug laws impede research and they said to, “Oh thanks David, but if I put my name to this paper I will never get a grant from the NIH, so I can’t do it. If I do this, they will believe that I’m fighting them, and they won’t fund my research.”

Of course, they’re not funding psychedelic research anyway, but they wouldn’t fund the other research this person was doing. In the end I had to find an American, I found Dave Nichols, even older than me, who was prepared to. He was past getting grants and he was prepared to write it with me. The pressure from NIDA (National Institute on Drug Abuse) and the NIAAA (National Institute on Alcohol Abuse and Alcoholism) and the NIMH (National Institute on Mental Health) on scientists in America to comply with the status quo, which is that these are dangerous illegal drugs, is stopping research.

A final question on another big story – the licensing of esketamine to treat depression – what is your take on these findings?

It’s very exciting. The thing you need to know about esketamine is it probably works in the same way initially as psilocybin. It disrupts repetitive thinking in depression. It produces similar disorganization of brain connectivity as you get with psilocybin but the esketamine effect doesn’t last very long. It only lasts two or three days. You have to take it twice a week. The [therapeutic] effects of psilocybin, they last for weeks, months or years, not in everyone but in some people. The reason for that is that 5-HT2A receptor which is the target of psilocybin is the receptor which allows you to think differently. esketamine basically causes a disruption of brain functioning, but it doesn’t activate the recovery process whereas psilocybin does.

Do you think the same designation that’s been given to esketamine will be given to psilocybin based on these more enduring results?

I hope so. There is another fundamental difference. The esketamine is given to people who have not fully responded to an SSRI, but you cannot use psilocybin in those people because SSRIs block the effect of psilocybin. The methodology for the psilocybin trial is that you’ve got to get people off the SSRIs, which is quite difficult sometimes. Esketamine is a sort of top-up, where psilocybin is a different, more powerful medication which you have to have people free of other medication to be able to use it. They will be used in quite different populations, I think.

 
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Study uncovers psilocybin-induced changes in brain connectivity*

by Eric Dolan | PsyPost | Jan 20 2020

New research published in Biological Psychology sheds light on the neurophysiological underpinnings of the psychedelic experience. The study provides new details about how psilocybin — the active component in “magic” mushrooms — changes the communication patterns between regions of the brain.

Psychedelics are currently being investigated for the treatment of psychiatric disorders. However, it is still unclear how they change brain activity and connectivity to induce their unique effects,” explained study author Katrin Preller of the University of Zurich and Yale University.

We therefore conducted a study to investigate the time-dependent effects of psilocybin on brain connectivity and the association between changes in brain connectivity and receptor pharmacology.”

In the study, 23 healthy human participants underwent MRI brain scanning 20 minutes, 40 minutes, and 70 minutes after receiving either psilocybin or a placebo. The researchers observed reduced connectivity between brain areas involved in planning and decision-making but increased connectivity between areas involved in sensation and movement while the participants were under the influence of the psychedelic drug.

Preller and her colleagues conducted a similar study on LSD, and obtained “virtually identical” results.

Psilocybin – similar to LSD – induced a pattern of brain connectivity that is characterized by increased synchronization of sensory brain regions and decreased connectivity of associative networks,” she told PsyPost.

Increased sensory processing but altered integration of this sensory information may therefore underlie the psychedelic state and explain the symptoms induced by psilocybin. Furthermore, this pattern of changes in connectivity was closely associated with spatial expression of the serotonin 2A and 1A receptors – pinpointing these receptors as critical for the effects of psilocybin.”

Another drug called ketanserin, a serotonin 2A antagonist, prevented the effects of both psilocybin and LSD, suggesting that changes in brain connectivity caused by these psychedelic drugs are linked to stimulation of the serotonin 2A receptor.

In this study we investigated different time points from administration to subjective peak effects. Future studies need to investigate how psilocybin impacts brain connectivity during a later phase and post-acutely,” Preller noted.

*From the article here :
 
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An existential crisis in neuroscience

by Grigori Guitchounts | NAUTILUS | 23 Jan 2020

We’re mapping the brain in amazing detail—but our brain can’t understand the picture.

On a chilly evening last fall, I stared into nothingness out of the floor-to-ceiling windows in my office on the outskirts of Harvard’s campus. As a purplish-red sun set, I sat brooding over my dataset on rat brains. I thought of the cold windowless rooms in downtown Boston, home to Harvard’s high-performance computing center, where computer servers were holding on to a precious 48 terabytes of my data. I have recorded the 13 trillion numbers in this dataset as part of my Ph.D. experiments, asking how the visual parts of the rat brain respond to movement.

Printed on paper, the dataset would fill 116 billion pages, double-spaced. When I recently finished writing the story of my data, the magnum opus fit on fewer than two dozen printed pages. Performing the experiments turned out to be the easy part. I had spent the last year agonizing over the data, observing and asking questions. The answers left out large chunks that did not pertain to the questions, like a map leaves out irrelevant details of a territory.

But, as massive as my dataset sounds, it represents just a tiny chunk of a dataset taken from the whole brain. And the questions it asks—Do neurons in the visual cortex do anything when an animal can’t see? What happens when inputs to the visual cortex from other brain regions are shut off?—are small compared to the ultimate question in neuroscience: How does the brain work?

The nature of the scientific process is such that researchers have to pick small, pointed questions. Scientists are like diners at a restaurant: We’d love to try everything on the menu, but choices have to be made. And so we pick our field, and subfield, read up on the hundreds of previous experiments done on the subject, design and perform our own experiments, and hope the answers advance our understanding. But if we have to ask small questions, then how do we begin to understand the whole?

Neuroscientists have made considerable progress toward understanding brain architecture and aspects of brain function. We can identify brain regions that respond to the environment, activate our senses, generate movements and emotions. But we don’t know how different parts of the brain interact with and depend on each other. We don’t understand how their interactions contribute to behavior, perception, or memory. Technology has made it easy for us to gather behemoth datasets, but I’m not sure understanding the brain has kept pace with the size of the datasets.

Some serious efforts, however, are now underway to map brains in full. One approach, called connectomics, strives to chart the entirety of the connections among neurons in a brain. In principle, a complete connectome would contain all the information necessary to provide a solid base on which to build a holistic understanding of the brain. We could see what each brain part is, how it supports the whole, and how it ought to interact with the other parts and the environment. We’d be able to place our brain in any hypothetical situation and have a good sense of how it would react.

The question of how we might begin to grasp the entirety of the organ that generates our minds has been pressing me for a while. Like most neuroscientists, I’ve had to cultivate two clashing ideas: striving to understand the brain and knowing that’s likely an impossible task. I was curious how others tolerate this doublethink, so I sought out Jeff Lichtman, a leader in the field of connectomics and a professor of molecular and cellular biology at Harvard.



Lichtman’s lab happens to be down the hall from mine, so on a recent afternoon, I meandered over to his office to ask him about the nascent field of connectomics and whether he thinks we’ll ever have a holistic understanding of the brain. His answer—“No”—was not reassuring, but our conversation was a revelation, and shed light on the questions that had been haunting me. How do I make sense of gargantuan volumes of data? Where does science end and personal interpretation begin? Were humans even capable of weaving today’s reams of information into a holistic picture? I was now on a dark path, questioning the limits of human understanding, unsettled by a future filled with big data and small comprehension.

Lichtman likes to shoot first, ask questions later. The 68-year-old neuroscientist’s weapon of choice is a 61-beam electron microscope, which Lichtman’s team uses to visualize the tiniest of details in brain tissue. The way neurons are packed in a brain would make canned sardines look like they have a highly evolved sense of personal space. To make any sense of these images, and in turn, what the brain is doing, the parts of neurons have to be annotated in three dimensions, the result of which is a wiring diagram. Done at the scale of an entire brain, the effort constitutes a complete wiring diagram, or the connectome.

To capture that diagram, Lichtman employs a machine that can only be described as a fancy deli slicer. The machine cuts pieces of brain tissue into 30-nanometer-thick sections, which it then pastes onto a tape conveyor belt. The tape goes on silicon wafers, and into Lichtman’s electron microscope, where billions of electrons blast the brain slices, generating images that reveal nanometer-scale features of neurons, their axons, dendrites, and the synapses through which they exchange information. The Technicolor images are a beautiful sight that evokes a fantastic thought: The mysteries of how brains create memories, thoughts, perceptions, feelings—consciousness itself—must be hidden in this labyrinth of neural connections.

A complete human connectome will be a monumental technical achievement. A complete wiring diagram for a mouse brain alone would take up two exabytes. That’s 2 billion gigabytes; by comparison, estimates of the data footprint of all books ever written come out to less than 100 terabytes, or 0.005 percent of a mouse brain. But Lichtman is not daunted. He is determined to map whole brains, exorbitant exabyte-scale storage be damned.

Lichtman’s office is a spacious place with floor-to-ceiling windows overlooking a tree-lined walkway and an old circular building that, in the days before neuroscience even existed as a field, used to house a cyclotron. He was wearing a deeply black sweater, which contrasted with his silver hair and olive skin. When I asked if a completed connectome would give us a full understanding of the brain, he didn’t pause in his answer. I got the feeling he had thought a great deal about this question on his own.

I think the word ‘understanding’ has to undergo an evolution,” Lichtman said, as we sat around his desk. “Most of us know what we mean when we say ‘I understand something.’ It makes sense to us. We can hold the idea in our heads. We can explain it with language. But if I asked, ‘Do you understand New York City?’ you would probably respond, ‘What do you mean?’ There’s all this complexity. If you can’t understand New York City, it’s not because you can’t get access to the data. It’s just there’s so much going on at the same time. That’s what a human brain is. It’s millions of things happening simultaneously among different types of cells, neuromodulators, genetic components, things from the outside. There’s no point when you can suddenly say, ‘I now understand the brain,’ just as you wouldn’t say, ‘I now get New York City.’

“But we understand specific aspects of the brain,” I said. “Couldn’t we put those aspects together and get a more holistic understanding?”

I guess I would retreat to another beachhead, which is, ‘Can we describe the brain?’ ” Lichtman said. “There are all sorts of fundamental questions about the physical nature of the brain we don’t know. But we can learn to describe them. A lot of people think ‘description’ is a pejorative in science. But that’s what the Hubble telescope does. That’s what genomics does. They describe what’s actually there. Then from that you can generate your hypotheses.”

“Why is description an unsexy concept for neuroscientists?”

Biologists are often seduced by ideas that resonate with them,” Lichtman said. That is, they try to bend the world to their idea rather than the other way around. “It’s much better—easier, actually—to start with what the world is, and then make your idea conform to it,” he said. Instead of a hypothesis-testing approach, we might be better served by following a descriptive, or hypothesis-generating methodology. Otherwise we end up chasing our own tails. “In this age, the wealth of information is an enemy to the simple idea of understanding,” Lichtman said.



“How so?” I asked.

Let me put it this way,” Lichtman said. “Language itself is a fundamentally linear process, where one idea leads to the next. But if the thing you’re trying to describe has a million things happening simultaneously, language is not the right tool. It’s like understanding the stock market. The best way to make money on the stock market is probably not by understanding the fundamental concepts of economy. It’s by understanding how to utilize this data to know what to buy and when to buy it. That may have nothing to do with economics but with data and how data is used.”

“Maybe human brains aren’t equipped to understand themselves,” I offered.

Late one night, after a long day of trying to make sense of my data, I came across a short story by Jorge Louis Borges that seemed to capture the essence of the brain mapping problem. In the story, “On Exactitude in Science,” a man named Suarez Miranda wrote of an ancient empire that, through the use of science, had perfected the art of map-making. While early maps were nothing but crude caricatures of the territories they aimed to represent, new maps grew larger and larger, filling in ever more details with each edition. Over time, Borges wrote, “the Art of Cartography attained such Perfection that the map of a single Province occupied the entirety of a City, and the map of the Empire, the entirety of a Province.” Still, the people craved more detail. “In time, those Unconscionable Maps no longer satisfied, and the Cartographers Guilds struck a Map of the Empire whose size was that of the Empire, and which coincided point for point with it.”

The Borges story reminded me of Lichtman’s view that the brain may be too complex to be understood by humans in the colloquial sense, and that describing it may be a better goal. Still, the idea made me uncomfortable. Much like storytelling, or even information processing in the brain, descriptions must leave some details out. For a description to convey relevant information, the describer has to know which details are important and which are not. Knowing which details are irrelevant requires having some understanding about the thing you’re describing. Will my brain, as intricate as it may be, ever be able to make sense of the two exabytes in a mouse brain?

Humans have a critical weapon in this fight. Machine learning has been a boon to brain mapping, and the self-reinforcing relationship promises to transform the whole endeavor. Deep learning algorithms (also known as deep neural networks, or DNNs) have in the past decade allowed machines to perform cognitive tasks once thought impossible for computers—not only object recognition, but text transcription and translation, or playing games like Go or chess. DNNs are mathematical models that string together chains of simple functions that approximate real neurons. These algorithms were inspired directly by the physiology and anatomy of the mammalian cortex, but are crude approximations of real brains, based on data gathered in the 1960s. Yet they have surpassed expectations of what machines can do.

The secret to Lichtman’s progress with mapping the human brain is machine intelligence. Lichtman’s team, in collaboration with Google, is using deep networks to annotate the millions of images from brain slices their microscopes collect. Each scan from an electron microscope is just a set of pixels. Human eyes easily recognize the boundaries of each blob in the image (a neuron’s soma, axon, or dendrite, in addition to everything else in the brain), and with some effort can tell where a particular bit from one slice appears on the next slice. This kind of labeling and reconstruction is necessary to make sense of the vast datasets in connectomics, and have traditionally required armies of undergraduate students or citizen scientists to manually annotate all chunks. DNNs trained on image recognition are now doing the heavy lifting automatically, turning a job that took months or years into one that’s complete in a matter of hours or days. Recently, Google identified each neuron, axon, dendrite, and dendritic spike—and every synapse—in slices of the human cerebral cortex. “It’s unbelievable,” Lichtman said.

Scientists still need to understand the relationship between those minute anatomical features and dynamical activity profiles of neurons—the patterns of electrical activity they generate—something the connectome data lacks. This is a point on which connectomics has received considerable criticism, mainly by way of example from the worm: Neuroscientists have had the complete wiring diagram of the worm C. elegans for a few decades now, but arguably do not understand the 300-neuron creature in its entirety; how its brain connections relate to its behaviors is still an active area of research.

Still, structure and function go hand-in-hand in biology, so it’s reasonable to expect one day neuroscientists will know how specific neuronal morphologies contribute to activity profiles. It wouldn’t be a stretch to imagine a mapped brain could be kickstarted into action on a massive server somewhere, creating a simulation of something resembling a human mind. The next leap constitutes the dystopias in which we achieve immortality by preserving our minds digitally, or machines use our brain wiring to make super-intelligent machines that wipe humanity out. Lichtman didn’t entertain the far-out ideas in science fiction, but acknowledged that a network that would have the same wiring diagram as a human brain would be scary. “We wouldn’t understand how it was working any more than we understand how deep learning works,” he said. “Now, suddenly, we have machines that don’t need us anymore.”

Yet a masterly deep neural network still doesn’t grant us a holistic understanding of the human brain. That point was driven home to me last year at a Computational and Systems Neuroscience conference, a meeting of the who’s-who in neuroscience, which took place outside Lisbon, Portugal. In a hotel ballroom, I listened to a talk by Arash Afraz, a 40-something neuroscientist at the National Institute of Mental Health in Bethesda, Maryland. “The model neurons in DNNs are to real neurons what stick figures are to people, and the way they’re connected is equally as sketchy,” he suggested.



Afraz is short, with a dark horseshoe mustache and balding dome covered partially by a thin ponytail, reminiscent of Matthew McConaughey in True Detective. As sturdy Atlantic waves crashed into the docks below, Afraz asked the audience if we remembered René Magritte’s “Ceci n’est pas une pipe” painting, which depicts a pipe with the title written out below it. Afraz pointed out that the model neurons in DNNs are not real neurons, and the connections among them are not real either. He displayed a classic diagram of interconnections among brain areas found through experimental work in monkeys—a jumble of boxes with names like V1, V2, LIP, MT, HC, each a different color, and black lines connecting the boxes seemingly at random and in more combinations than seems possible. In contrast to the dizzying heap of connections in real brains, DNNs typically connect different brain areas in a simple chain, from one “layer” to the next. “Try explaining that to a rigorous anatomist,” Afraz said, as he flashed a meme of a shocked baby orangutan cum anatomist. “I’ve tried, believe me,” he said.

I, too, have been curious why DNNs are so simple compared to real brains. Couldn’t we improve their performance simply by making them more faithful to the architecture of a real brain? To get a better sense for this, I called Andrew Saxe, a computational neuroscientist at Oxford University. Saxe agreed that it might be informative to make our models truer to reality. “This is always the challenge in the brain sciences: We just don’t know what the important level of detail is,” he told me over Skype.

How do we make these decisions? “These judgments are often based on intuition, and our intuitions can vary wildly,” Saxe said. “A strong intuition among many neuroscientists is that individual neurons are exquisitely complicated: They have all of these back-propagating action potentials, they have dendritic compartments that are independent, they have all these different channels there. And so a single neuron might even itself be a network. To caricature that as a rectified linear unit”—the simple mathematical model of a neuron in DNNs—“is clearly missing out on so much.”

As 2020 has arrived, I have thought a lot about what I have learned from Lichtman, Afraz, and Saxe and the holy grail of neuroscience: understanding the brain. I have found myself revisiting my undergrad days, when I held science up as the only method of knowing that was truly objective (I also used to think scientists would be hyper-rational, fair beings paramountly interested in the truth—so perhaps this just shows how naive I was).

It’s clear to me now that while science deals with facts, a crucial part of this noble endeavor is making sense of the facts. The truth is screened through an interpretive lens even before experiments start. Humans, with all our quirks and biases, choose what experiment to conduct in the first place, and how to do it. And the interpretation continues after data are collected, when scientists have to figure out what the data mean. So, yes, science gathers facts about the world, but it is humans who describe it and try to understand it. All these processes require filtering the raw data through a personal sieve, sculpted by the language and culture of our times.

It seems likely that Lichtman’s two exabytes of brain slices, and even my 48 terabytes of rat brain data, will not fit through any individual human mind. Or at least no human mind is going to orchestrate all this data into a panoramic picture of how the human brain works. As I sat at my office desk, watching the setting sun tint the cloudless sky a light crimson, my mind reached a chromatic, if mechanical, future. The machines we have built—the ones architected after cortical anatomy—fall short of capturing the nature of the human brain. But they have no trouble finding patterns in large datasets. Maybe one day, as they grow stronger building on more cortical anatomy, they will be able to explain those patterns back to us, solving the puzzle of the brain’s interconnections, creating a picture we understand. Out my window, the sparrows were chirping excitedly, not ready to call it a day.

 
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Hylight

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i agree that the brain is complex at times but overwhelming as a good grasp at the understanding of the whole comprehension that can be quite interesting when seen.
and yes indeed. it is quite a good focus of study.
 

mr peabody

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How serotonin modulates behavior

MIT | Neuroscience News | 20 Feb 2020

A new NIH funded study will use C. elegans to discover the secrets behind serotonin’s influence on behavior.

In popular experience the story of how serotonin modulates the brain might seem simple: pop an antidepressant, serotonin levels go up, mood improves. But neuroscientists acknowledge how little they know about how the neurotransmitter affects circuits and behavior in the incredibly complex human brain. To reveal the basics of how serotonin really works, scientists at MIT’s Picower Institute for Learning and Memory, funded by a new $1.16 million, four-year grant from the National Institutes of Health, will employ a far simpler model: the nematode worm C. elegans.

Though it is tiny, transparent and sports a nervous system with only 302 neurons, C. elegans is a powerful system for studying how serotonin modulates brain states, said the grant’s principal investigator Steven Flavell, Lister Brothers Career Development Professor in the Picower Institute and assistant professor in the Department of Brain and Cognitive Sciences. C. elegans and mammals share much of the same basic molecular machinery for emitting and receiving serotonin. But unlike in a mammal, all the neurons and their connectivity has been precisely mapped out in C. elegans and scientists can exert powerful genetic control over each cell, including those that express each of the worm’s five distinct serotonin receptors. Moreover, Flavell’s lab has developed an innovative imaging system that can reliably image the calcium activity of virtually every neuron in real time, even as a worm freely slithers and wriggles around in response to experimental manipulations.


The Flavell lab has developed the ability to image the activity of virtually every C. elegans neuron in real-time,
even in a freely moving and behaving worm.


Essentially, Flavell’s team can take nearly full control of the worm’s serotonergic system and simultaneously observe the response of virtually every neuron in the whole brain. This gives them needed capabilities that aren’t available in mammals to figure out how varying patterns of serotonin release can stimulate distinct receptors (or combinations of them) on a multitude of neurons in a variety of circuits to modulate different behaviors.

Focus on feeding

“By taking advantage of a well-defined paradigm for serotonergic function and cutting-edge imaging technologies, we are well positioned to examine how patterned serotonin release activates distinct receptor types throughout a circuit to change the large-scale activity patterns that give rise to behavior,” Flavell said.

In December 2018, Flavell’s lab published a paper in Cell showing how a particular C. elegans neuron called NSM senses when a worm has started feeding on bacteria and signals other neurons via serotonin to slow the worm down to savor the meal. Since then, his lab has studied how manipulating NSM’s serotonin release patterns affects the worm’s slowing behavior and has begun to map out which serotonin receptors on which neurons play a role in those effects, for instance by genetically knocking out individual receptors, or combinations of receptors, to see what changes.

With the new grant, the lab will expand on these studies and go well beyond to systematically achieve three aims: mapping out which combinations of serotonin receptors mediate serotonin’s effect on behavior and identifying the exact neurons where they function; analyzing how serotonin alters whole-brain activity; and determining how serotonin-responsive circuits and whole brain activity differs when worms must balance aversive stimuli with appetitive food cues. While the first two sets of experiments will elucidate how the brain deploys serotonin to modulate behavior, the third aim will show how those dynamics change in more complex environments.

Surprisingly, these fundamental issues related to serotonin signaling remain poorly understood,” Flavell said. “Resolving them would greatly enhance our understanding of the serotonergic system.”

 
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mr peabody

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Ketamine found to reverse neural changes that underlie depression-related behaviors*

Neuroscience News | April 11, 2019

The formation of prefrontal cortex dendritic spine formation sustains the remission of depressive related symptoms and behaviors following ketamine treatment by restoring lost spines.

Researchers have identified ketamine-induced brain-related changes that are responsible for maintaining the remission of behaviors related to depression in mice — findings that may help researchers develop interventions that promote lasting remission of depression in humans.

Major depression is one of the most common mental disorders in the United States, with approximately 17.3 million adults experienced a major depressive episode in 2017. However, many of the neural changes underlying the transitions between active depression, remission, and depression re-occurrence remain unknown. Ketamine, a fast-acting antidepressant which relieves depressive symptoms in hours instead of weeks or longer, provides an opportunity for researchers to investigate the short- and long-term biological changes underlying these transitions.

“Ketamine is a potentially transformative treatment for depression, but one of the major challenges associated with this drug is sustaining recovery after the initial treatment,” said study author Conor Liston, M.D., Ph.D., of Weill Cornell Medicine, New York City.

To understand mechanisms underlying the transition from active depression to remission in humans, the researchers examined behaviors related to depression in mice. Researchers took high-resolution images of dendritic spines in the prefrontal cortex of mice before and after they experienced a stressor. Dendritic spines are protrusions in the part of neurons that receive communication input from other neurons. The researchers found that mice displaying behaviors related to depression had increased elimination of, and decreased the formation of, dendritic spines in their prefrontal cortex compared with mice not exposed to a stressor. This finding replicates prior studies linking the emergence of behaviors related to depression in mice with dendritic spine loss.

In addition to the effects on dendritic spines, stress reduced the functional connectivity and simultaneous activity of neurons in the prefrontal cortex of mice. This reduction in connectivity and activity was associated with behaviors related to depression in response to stressors. Liston’s group then found that ketamine treatment rapidly restored functional connectivity and ensemble activity of neurons and eliminated behaviors related to depression. Twenty-four hours after receiving a single dose of ketamine, mice exposed to stress showed a reversal of behaviors related to depression and an increase in dendritic spine formation when compared to stressed mice that had not received ketamine. These new dendritic spines were functional, creating working connections with other neurons.

The researchers found that while behavioral changes and changes in neural activity in mice happened quickly (three hours after ketamine treatment), dendritic spine formation happened more slowly (12-24 after hours after ketamine treatment). While further research is needed, the authors suggest these findings might indicate that dendritic spine regrowth may be a consequence of ketamine-induced rescue of prefrontal cortex circuit activity.

Although dendritic spines were not found to underly the fast-acting effects of ketamine on behaviors related to depression in mice, they were found to play an important role in maintaining the remission of those behaviors. Using a new technology developed by Haruo Kasai, Ph.D., and Haruhiko Bito, Ph.D., collaborators at the University of Tokyo, the researchers found that selectively deleting these newly formed dendritic spines led to the re-emergence of behaviors related to depression.

“Ketamine is the first new anti-depressant medication with a novel mechanism of action since the 1980s. Its ability to rapidly decrease suicidal thoughts is already a fundamental breakthrough,” said Janine Simmons, M.D., Ph.D., chief of the NIMH Social and Affective Neuroscience Program. “Additional insights into ketamine’s longer-term effects on brain circuits could guide future advances in the management of mood disorders.”

*From the article here :
 
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mr peabody

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Dr. Dirk Jancke

How serotonin balances communication within the brain

by Ruhr-Universitaet-Bochum | Medical Xpress | 7 April 2020

The brain is steadily engaged in thought. These internal communications are also usually bombarded with external sensory events. Hence, the impact of the two neuronal processes need to be permanently fine-tuned to avoid their imbalance. A team of scientists at the Ruhr-Universität Bochum (RUB) has now revealed the role of the neurotransmitter serotonin in this mechanism. They discovered that distinct serotonergic receptor types control the gain of both streams of information in a separable manner. Their findings may facilitate new concepts of diagnosis and therapies for neuronal disorders related to malfunction of the serotonin system. The study is published online in the open access journal eLife on 7 April 2020.

Impacting on different streams of information in the brain

Dr. Dirk Jancke, head of the Optical Imaging Group at the Institute of Neural Computation, says, "Imagine sitting with your family at dinner, and a heated debate is going on about how to properly organize some internal affairs. Suddenly, the phone starts ringing; you are picking up while family discussion goes on. In order to understand the calling party correctly, the crowd in the back must speak lower or the caller needs to speak up. Thus, the loudness of each internal background conversation and external call need to be properly adjusted to ensure non-interfered, separable information transfer." As in this anecdote, comparable brain processes involve serotonin.

Serotonin is a neurotransmitter of the central nervous system, commonly called the "happy hormone" because it contributes to changes in brain state and is often associated with effects on mood. The study of the RUB team now demonstrates that serotonin participates also in the scaling of current sensory input and ongoing brain signals.

Controlling neuronal release of serotonin with light

The RUB neuroscientists discovered the underlying mechanisms in experiments that investigated cortical processing of visual information. For their study, they used genetically modified mice in which the release of serotonin could be controlled by light. This mouse line was developed by the group of Professor Stefan Herlitze, Department of General Zoology and Neurobiology, to enable specific activation of serotonergic neurons by an implanted light fiber.

Combining this technique with optical imaging, the RUB team found that increasing levels of serotonin in the visual brain leads to concurrent suppression of ongoing activity and activity evoked by visual stimuli. Two types of receptors played a distinct major role here. "This was surprising to us, because both receptors are not only co-expressed in specific neurons, but also widely distributed across different cell types in the brain," says Zohre Azimi, first author of the study.

Separable action of these receptors allows distinct modulations of information carrying internal brain communication and evoked sensory signals. Low serotonin levels, as they typically occur during sleep at night, favor internal brain communication, and thus, may promote important functions of dreaming. "Dysfunction in the interplay of these receptors, on the other hand, harbors the risk of an overemphasis of either internally or externally driven information channels," says Jancke. "For example, irregular 5-HT receptor distributions caused by genetic predisposition may become manifest in an imbalanced perception of inner and outside world, similar as seen in clinical pictures of depression and autism."

The scientists hope that their findings contribute to a better understanding of how serotonin affects fundamental brain processes. In turn, their study may trigger future research in developing receptor-specific drugs that benefit patients with serotonin-related psychiatric diseases.

 
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mr peabody

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Neuroscientists uncover how magic mushrooms 'rebalance' the brain

by Emma Betwel | INVERSE | 17 April 2020

New models of the brain are bringing us one step closer to psilocybin-based medicine.

There's no reset button on your brain. But the more scientists learn about magic mushrooms, the more we know that they're about as close to a reset button as we can get.

Psilocybin — the hallucinogenic chemical in certain mushrooms — can reshape cells in the brain, and increasingly, shows potential for treating addiction or depression. Now, using new brain models, scientists are getting a better idea of how it all happens.

Scientists constructed a model of the human brain on psilocybin, illuminating how magic mushrooms allow our brain to access untapped potential. This model shows that, under the influence of psilocybin, the brain creates a feedback loop of neuron activity and neurotransmitter release (the chemical messengers that neurons use to communicate).

This finding was published Monday in Proceedings of the National Academy of Sciences.

That dynamic creates a one-two punch that could allow the brain to tap into otherwise inaccessible states, including the "destabilization" of individual brain networks and the creation of a more "global" network across the brain.

"That destabilization is one hypothesis that scientists have used to explain why magic mushrooms can create psychedelic experiences. But it could also underscore why it has potential as treatment for disorders like depression," explains Morten Kringlebach, the study's first author and a senior research fellow at the University of Oxford.

"Using this model will be crucial for truly understanding how psilocybin can rebalance neuropsychiatric disorders such as treatment-resistant depression and addiction," Kringlebach tells Inverse.

How do magic mushrooms affect the brain?

This study is based on brain images taken from nine participants who were either injected with psilocybin or a placebo. The scientists used those images to create a "whole-brain connectome" which provides a picture of all the physical neurons in the brain, as well as the activity of the neurotransmitters that are being shuttled back and forth.

"During your average day in the human brain, neurons are constantly firing and neurotransmitters are traveling well-trodden paths through the brain, somewhat like cars on a freeway. On magic mushrooms, those networks are 'destabilized,'" Kringlebach explains.

Previous research has shown that new networks appear in tandem. It's as if those cars on the freeway were given free rein to stray from the highway and take back roads towards new destinations.

Scientists are beginning to understand how this works. For instance, psilocybin (as well as psychedelics like DMT) mimic serotonin, a neurotransmitter related to feelings of happiness or love. Kringelbach suggests that these mushrooms do more than simply affect serotonin flow in the brain.

"We wanted to investigate the role of neurotransmission in dynamically changing the activity in whole-brain networks — and how this changes neurotransmitter release in return," he explains.

The models showed that the brain is able to tap into new networks by coupling the effects of neuron activity and the release of neurotransmitters, like serotonin. The release of neurotransmitters and the firing of neurons work together – and when you have one without the other, the whole system falls apart.

When the scientists adjusted their model to have these processes work independently, they found that they weren't able to recreate the same "destabilization" of networks that you would usually see when someone is on magic mushrooms. The same breakdown in their pattern happened when they replaced the typical serotonin receptors utilized by magic mushrooms (5-HT2A receptors) with other types of serotonin receptors.

Taken together, this suggests that both the receptors themselves, and the patterns of neuron activity are necessary for psilocybin to really work.

The future of magic mushrooms

"Knowing that both receptors and neuron activity are needed, could help better understand how to use the drug as a therapy. In turn, these models can help us visualize an enduring mystery within the human brain," says Kringlebach.

"It has long been a puzzle how the brain's fixed anatomical connectome can give rise to so many radically different brain states; from normal wakefulness to deep sleep and altered psychedelic states," he says.

We only have a fixed amount of hardware in the brain, yet we're running highly complicated software that produces dreams, consciousness, and — if someone is on a drug like DMT — "breakthrough experiences."

If the magic mushrooms demonstrate anything, it's that the brain can learn to use its fixed hardware in very different ways, if the right ingredients are involved. The trick is figuring out what tools the brain needs to run different types of software on that hardware.

In the future, the team hopes that their model could help us learn how we can run different types of software in our brains, and in doing so, help treat conditions like depression.

"This new model will give us the much needed, causal tools for potentially designing new interventions to alleviate human suffering in neuropsychiatric disorders," Kringlebach says.

 
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MountainTrails

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I like this latest article, especially the conceptual model that relates to networks and software. However, I'm not sure about the "fixed anatomical connectome puzzlingly leads to different brain states" (paraphrased) part. On a gross simplified level, the nervous system is more or less static (fixed). But it seems to me -- it seems obvious, actually -- that the actions/role of synapses and neurotransmitters is exactly what makes the brain nondeterministic, and allows the different brain states and subcircuitry associated with a thought, all on that one network. The signal can change literally at every synapse, in an analog kind of way.
 

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Neuronal and neurotransmitter systems dynamic coupling explains the effects of psilocybin

UPF Barcelona | Neuroscience News | 16 April 2020

Computational simulations reveal the integration of both neuronal and neurotransmitter systems at a whole-brain level is vital to fully understand the effects of psilocybin on brain activity.

Interest in research into the effects of psilocybin has increased significantly in recent years due to its promising therapeutic effects in neuropsychiatric disorders such as depression, anxiety and addiction.

It is widely accepted that the brain’s powerful ability to adapt its behaviour flexibly is largely due to the neurotransmitter system. Psilocybin is the substance responsible for the psychoactive effect caused by nearly 200 species of fungi. This substance has a particular affinity for serotonin receptors found primarily in the brain, but also in other parts of the body such as the stomach. Upon consumption, psilocybin selectively changes the function of serotonin receptors, thus generating an altered state of consciousness characterized by the dissolution of the ego, changes in the quality and attribution of thoughts, impaired visual and sensory perception, and greater awareness of repressed memories.

An international team of researchers has developed a computational biophysical model of the entire brain that integrates real data about its anatomical structural connectivity, the functional dynamics of neurons and a map which shows the concentration of serotonin receptors in various brain regions.

This international research, published on 13 April in the journal Proceedings of the National Academy of Sciences, was led by Gustavo Deco, ICREA research professor and director of the Center for Brain and Cognition at the Department of Information and Communication Technologies (DTIC) at UPF, with the participation of Josephine Cruzat, a member of his team, Morten Kringelbach, a neuroscientist at the University of Oxford (UK), and other scientists from research centres in Germany, Denmark, the US, Portugal and the UK.

This work has shown that the new dynamic model of the whole brain is capable of addressing one of the major challenges in neuroscience: to explain the paradoxical flexibility of brain function despite having a fixed anatomical structure

Study of psilocybin’s mechanisms of action in humans

This theoretical and experimental study modelled the interaction between neuronal and neurotransmitter systems throughout the brain to explain how psilocybin affects brain activity. To study the drug’s mechanisms of action, Morten Kringelbach, Josephine Cruzat and Gustavo Deco analysed data from functional magnetic resonance imaging (fMRI) in 16 healthy subjects. In the experiment, participants were given small doses of psilocybin intravenously or saline solution (placebo effect) while in the scanner, to measure their brain function. The experimental part of the study was carried out at Imperial College London under the direction of Robin Carthart-Harris, co-author of the study.

The functional data acquired under the conditions of placebo and psilocybin were then combined with data from diffusion magnetic resonance imaging (dMRI) capturing brain structure by describing the anatomical connections between the different brain regions; and with data on the density of serotonin receptors estimated by positron emission tomography (PET).

The integration of neuronal and neurotransmitter systems at whole-brain level is important to fully explain the effects of psilocybin on brain activity.


Interest in research into the effects of psilocybin has increased significantly in recent years due to its
promising therapeutic effects in neuropsychiatric disorders such as depression, anxiety and addiction.


As explained by by Deco and Cruzat, co-authors of the work, “the computational simulations performed in this study revealed that the integration of neuronal and neurotransmitter systems at the whole-brain level is important to fully explain the effects of psilocybin on brain activity, specifically through the stimulation of serotonin receptors 5 -HT2A, involved in psychoactive modulation.”

Overall, the remarkable flexibility of human brain function depends crucially on the bidirectional dynamic participation of neuronal and neurotransmission systems. According to the authors, this new approach provides a better and deeper understanding of the effects of psilocybin on the brain and may lead to the development of new treatments for neuropsychiatric diseases such as depression, anxiety and addiction.

 
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thegreenhand

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That's a really cool article. Certainly a key gap in our neuroscientific knowledge. Lots of talk about computational systems and lot's of talk about biochemical systems but not a lot of talk on how those biochemical systems interface with the computational systems. Thanks for the find!
 

MountainTrails

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That's a really cool article. Certainly a key gap in our neuroscientific knowledge. Lots of talk about computational systems and lot's of talk about biochemical systems but not a lot of talk on how those biochemical systems interface with the computational systems. Thanks for the find!

Yeah, always hard, especially given the necessarily narrow focus of most researchers.

I sat through a talk by Christos Papadimitriou once where he presented some ideas/work that I consider in that intersection area. Take a look at this paper on something called "assemblies." They take kind of a bottom-up approach and look at how small groups of neurons work together as computational engines. I thought it was interesting stuff.
 

thegreenhand

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Yeah, always hard, especially given the necessarily narrow focus of most researchers.

I sat through a talk by Christos Papadimitriou once where he presented some ideas/work that I consider in that intersection area. Take a look at this paper on something called "assemblies." They take kind of a bottom-up approach and look at how small groups of neurons work together as computational engines. I thought it was interesting stuff.
Oh sweet I’ll read through that for sure. Maybe after my finals week ends next week though lol. Computational neuro fascinates me but right now my task is learning all the mathematics necessary to understand it
 

mr peabody

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Brain morphology may help explain differing psilocybin experiences

by Barb Bauer | Psychedelic Science Review | 17 April 2020

Understanding brain morphology differences may prove essential for creating effective psychedelic drug formulations.

Scientists have some understanding of the receptor mechanisms involved in the psychedelic experience. The current theory is that the binding of an agonist or partial agonist to the serotonin 5-HT2A receptor elicits a psychedelic effect via signaling pathways. Some experts hypothesize that the 5-HT2C receptor may also be involved.

The general effects of psilocybin (actually, its active metabolite psilocin) are documented, and they cover a range of emotional, cognitive, and perceptual changes. Set and setting (aka context) is known to play a critical role in the subjective effects of psychedelics. Despite this understanding, there is still considerable unexplained variability in the individual experience from ingesting psilocybin.

Now, research is showing that the morphology of certain parts of the brain may be a predictor of the magnitude of the psychedelic experience from psilocybin.

In February 2020, a research team, including Franz Vollenweider, published a randomized, double-blind, placebo-controlled study in Biomedicines. In this study, the authors built on previous research supporting the hypothesis that “Individual brain morphology measures can be used to predict various pharmacological challenges and behavior.” Specifically, the team measured the thickness of areas in the cingulate cortex of people’s brains and compared it to their subjective ratings from ingesting psilocybin.

Study design

The study recruited 55 people from local universities (33 men and 22 women) with a mean age of 25 years. They were randomly divided into three groups. The low and high dose groups received 0.16 mg/kg and 0.215 mg/kg psilocybin, respectively, in two sessions at least ten days apart. The control group received maltose as a placebo.

One hour after each psilocybin dose, the participants underwent a magnetic resonance imaging (MRI) of their brain. The areas of the brain the researchers measured the thickness of were in the right hemisphere. They were the rostral anterior cingulate, caudal anterior cingulate, and the posterior cingulate (Figure 1). The authors stated that they chose these areas because they have a high expression of 5-HT2A receptors compared to other regions of the limbic system. For the control area, they chose a part of the right hemisphere called the post central, where there is low expression of 5-HT2A receptors.


Figure 1: Schematic showing the brain regions used in the analyses. (A) Right hemisphere cingulate cortex region used in primary analyses. Dark purple = rostral anterior cingulate; medium purple = caudal anterior cingulate; light purple = posterior cingulate. (B) Red = right hemisphere post central region used as the control region analysis.

The Five-Dimensional Altered State of Consciousness (5D-ASC) questionnaire was administered to each participant six hours after each dose. Of the 11 sub-scales measured in the 5D-ASC, the researchers focused on the data from four of them: experience of unity, spiritual experience, blissful state, and insightfulness.

Results

The data revealed that there were no significant differences in the four 5D-ASC sub-scale ratings based on dose. The authors theorized this might be because the doses reflected the high and low ends of the medium dose range for psilocybin based on the literature. They recognized two doses being a strength of the study, but also a limitation because they were not sufficiently different to detect any dose effects. Therefore, the authors then looked at all the data together, regardless of the dose.

Analyzing the data in this way, the researchers observed that the thickness of the right hemisphere rostral anterior cingulate predicted ratings for the four 5D-ASC sub-scales (i.e., the thicker the region, the higher the person’s subjective experience ratings). Conversely, the thickness of the caudal and posterior cingulate areas was not predictive of the sub-scale ratings. The authors noted that these results correlate with previous studies in the literature.

The authors stated, “This is the first study to evaluate brain morphology as a predictor of the emotional subjective experience of psilocybin in healthy controls.” They hypothesized from the data that,

"...morphology metrics such as cortical thickness may reflect differences in brain substrates that mediate drug effects. Investigating the relationship between psilocybin modulation and cingulate structure could provide insight into mechanisms underlying psilocybin’s profound emotional effects and provides a theoretical framework for brain-based predictors of 5HT2A psychedelic modulation."

 
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MountainTrails

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Oh sweet I’ll read through that for sure. Maybe after my finals week ends next week though lol. Computational neuro fascinates me but right now my task is learning all the mathematics necessary to understand it

Good luck on your finals.

Don't get psyched out by the math in papers you read. A lot of the time it's there to support verbal conclusions (showing the work). Glean what you can and move on.
 
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