A few days ago I was on the phone with a family member, and the conversation drifted, the way these conversations do, to an old video tape. My older daughter was two and a half. She was on the floor with a wooden puzzle of the United States, and she was picking up each state and setting it down in its exact spot without hesitating. Nevada, there. Colorado, there. If you asked her the capital, she would tell you, in the small serious voice kids use when they already know they are right.

I could not do that today. I am not entirely sure I could do it the day I am writing this sentence.

That is not really a story about a smart toddler, although she was one. It is a story about how much a very young brain can hold, briefly and completely, and how much of that same knowledge quietly falls away as the brain grows into a life that no longer needs state capitals on demand. What she knew at two and a half did not disappear because it was unimportant. It disappeared because nobody needed her to keep carrying it forward. The tape, though, still carries it. Thirty-some years later, I can press play and get it back. That gap, between what a mind lets go of and what a piece of media holds onto, is the whole reason I am writing this.

What She Knew at Two and a Half

If I asked my older daughter today where Nevada is, she would get it right, probably without thinking. Ask her the capital, and I suspect there would be a pause, maybe a guess, maybe a shrug. That gap between geography and trivia is a pretty good stand-in for how memory actually works across a life: the shape of a thing survives long after the specific detail does not. We keep the map. We lose the footnotes.

My younger daughter, Hannah, would probably handle both questions without hesitation today (she even knows all the countries and their locations), but you already heard a bit about Hannah — Study with Hannah, about the sixty-two thousand study cards she built for herself in medical school. Different puzzle, same posture at the table, the same total absorption in getting something exactly right. What has changed between the toddler and the med student is not a child’s capacity to learn. What has changed is what we bothered to keep a record of, and whether that record is still readable when we go looking for it.

Berkeley, DEC, and the Machines That Wouldn’t Talk to Each Other

I have been thinking about this problem longer than I have had children. In the late 1980s I was in graduate school at Berkeley, building some of the earliest neural network methods anyone was using for protein structure prediction, work that was probably thirty years ahead of the field’s patience for it. None of that matters here except for one detail: the machines.

I started on old DEC systems and moved, over a few years, onto Silicon Graphics workstations. The two families of machines were different enough that moving anything between them (code, results, the tapes I had recorded my work onto) took real, deliberate effort. Nobody handed me a converter. I had to notice, ahead of time, that the platform I was standing on would not be the platform I would be standing on in five years, and that if I did not move my own work forward on my own schedule, I would eventually be locked out of it on somebody else’s schedule instead.

That was not foresight so much as an early, uncomfortable lesson, learned by hand, tape by tape, in a lab that had no particular reason to warn me about it. I moved source code and results off those machines more than once, onto whatever came next, well before I had hard evidence the old hardware was actually going away. It turned out to be the right call every single time. Ever since, I have treated “will I be able to read this in ten years” as a real engineering requirement for anything I actually care about keeping, not a nice-to-have I get around to eventually.

The Alexandria Fire, on a Budget

Here is the part almost everyone has lived through without ever quite naming it. Betamax. Video CDs. MiniDV. Blu-ray, which felt permanent for about a decade. Every one of those formats held real memories: someone’s wedding, someone’s Christmas morning, someone’s toddler doing a state puzzle. And every one of those formats has quietly become harder to play than the memory itself deserves. You can find a working deck in the Smithsonian Institute. You can probably find one on eBay if you are patient and willing to gamble on a stranger’s storage unit. You are not finding one on Amazon, and you are certainly not finding one at Walmart.

Workers interacting with papyrus scrolls housed on shelves and columns within the ancient Egyptian Library of Alexandria

That is a small, slow-motion version of the Library of Alexandria. Nothing burned. The scrolls are all technically still there, on tape, on disc, in a drawer in someone’s garage. What is gone is the ability to read them, which for practical purposes is the same thing as gone. It just happens quietly, one format transition at a time, spread out over decades instead of one bad afternoon in Egypt. Nobody registers it as loss, because nothing dramatic ever happens. The device you need just gets a little harder to find every year, until one day it is a museum piece, and by then the moment you would have wanted back is thirty years further from anyone’s reach than it ever needed to be.

In Silico, Not Just the Highlight Reel

Most of what we do save, we save selectively. We keep the wedding, not the argument in the car on the way to the wedding. We keep the graduation, not the ordinary Tuesday that actually made up most of a relationship. I understand the instinct. Nobody wants to relive the difficult parts on purpose, and curated memory has always been a kindness we do for ourselves.

But I think we are underinvesting in the unremarkable footage: the stuff that is not staged, the stuff that just happens to be running while a life is actually being lived. Not for anyone’s entertainment, and not to build an inventory for later monetization. I mean something closer to memorializing as much of a person’s real life as is reasonably possible, quietly and unobtrusively, without turning every family dinner into a production. Call it in silico memorialization, a phrase I keep coming back to: preserving people’s lives in digital form, ahead of a need you cannot yet name, rather than after you can. The specific detail worth keeping is rarely the one you would have predicted in advance. Nobody sets out to film “the last time we will all be in this kitchen together.” You only find out which recordings mattered after the fact, which is exactly the argument for keeping more of them than you think you need right now.

Built to Move, Not to Stay

This is also why I have put real effort into making sure the systems I build myself do not repeat the DEC-to-Silicon-Graphics problem for anyone else. Everything I put in the cloud now, I put there assuming the cloud is this decade’s format, not a permanent home. It needs to be able to leave cleanly whenever the next platform shows up, the same way my old research needed to leave a machine before that machine stopped being useful to anyone.

That thinking is a big part of why I built out ToastOurFriend, a place where you can create a circle around someone you want to celebrate (a friend, a mentor, a neighbor) and fill it with stories, photos, and voice memories while that person is still around to read them. I wrote more about the origin of that project, and why celebration should happen before someone is gone rather than after (Medium: https://medium.com/@smuskal/toast-our-friend-87dc344a3fb3; Substack: https://www.drstevenmuskal.com/p/toast-our-friend). The content in a circle belongs to the people in it, not to the platform. If ToastOurFriend is not the right home for it in five years, moving that circle somewhere else should be simple. I built it that way on purpose, because I have already lived through what happens when a format outlives its own hardware, and I would rather not do that to anyone’s memories a second time.

Where Things Go

There is a reason the puzzle in that old video has stuck with me all week, beyond the obvious cuteness of a two and a half year old rattling off capitals. A puzzle only works because every piece has exactly one place it belongs. My daughter knew, instantly and correctly, where each one went. That is a small, almost embarrassingly literal model for the actual argument here: the memories worth keeping need to keep landing in the right place, generation of media after generation of media, or they simply stop existing anywhere we can reach them.

Nobody does this migration for you automatically. The photo albums that got scanned onto a CD did not get themselves scanned again when CD drives started disappearing from laptops. Someone had to notice, ahead of the format’s expiration date, and move the content forward on purpose. That stopped being a technology problem a long time ago. It is a decision every family has to make, over and over, about what they are willing to carry forward and what they are willing to let the next quiet Alexandria fire take.

So here is the actual ask, buried under all the DEC machines and Betamax decks: go find the tape, the disc, the drive you have not opened in a decade, and move whatever is on it somewhere it can survive the next format change. Do it before you need a device you can only find at the Smithsonian. And if there is someone in your life worth celebrating while they can still see it, do not wait for the version of this essay that shows up at a memorial. Say it, film it, post it, now, while it can still land exactly where it is supposed to go.

Related reading: Study with Hannah · Toast Our Friend · ToastOurFriend.com

Related listening, with the daughters you just read about: Father-Daughter Face-Off, part one, with Lili · Father-Daughter Face-Off, part two, with Hannah: Medical Training Overseas · Homeownership, Healthcare, and AI, with Lili

Steven Muskal, Ph.D. is the CEO of Eidogen-Sertanty, Inc. — a drug discovery informatics company. He has spent four decades working at the intersection of computational biology, AI, and drug discovery. He writes about AI, health, and the intersection of biology and technology at stevenmuskal.com

For a couple mixes — these are from the recent July 3 gathering. Green River (Dan, Ron, Tim, Andrew) — “let me remember things I love.” And Ventura Highway (Ron, Andrew, Dan, TimL)

That Go There was originally published in Age of Awareness on Medium, where people are continuing the conversation by highlighting and responding to this story.

TL;DR

• One molecule, ketamine, is used as a painkiller, a dissociative sedative, a full anesthetic and a fast-acting antidepressant. Which one it becomes depends on how much reaches the brain, how fast, and what else is on board.
• Ketamine does not simply turn the brain down. In the human data it reviewed, cortex stays active and complex while communication between regions breaks down. I call this disconnection without silence.
• Think of an orchestra that keeps playing loudly but is no longer in sync. A volume meter (or a single anesthesia monitor number) cannot hear the difference. The shape of the activity can.
• My hypothesis (not a finding yet): ketamine changes the geometry of population activity, the “neural manifold” and the paths on it, in a way that depends on the whole exposure history, not only the current dose. None of the three sources I use measured this directly, so I state it as a testable prediction and propose a first experiment (Section 7).

1. Why one drug confuses so many people

Picture two rooms with the same average noise level. In one, an orchestra is playing a symphony. In the other, a crowd is shouting. A sound meter reads the same number in both. Any instrument that only measures how much noise is there will call them identical.

Medicine has this problem with ketamine. It is used for induction in trauma and shock, for pain relief at low doses, for dissociative sedation, for hard-to-treat status epilepticus, and, more recently, as a rapid antidepressant. Monitors built for GABA-type anesthetics such as propofol assume that deeper anesthesia means slower, quieter brain activity. Ketamine breaks that assumption: a patient can be unresponsive while the cortex stays busy, and the monitor index can stay high even though the patient is not truly “awake” (Sarasso et al., 2015; Vlisides et al., 2017).

This article asks one question: what changes about the organization of brain activity as ketamine exposure rises from analgesia to anesthesia, and what does that mean for how we model and monitor it?

Key terms in plain language

• NMDA receptor: a docking site for the neurotransmitter glutamate. It is slow and is thought to help sustain “top-down” signals. Ketamine blocks it.
• Interneuron: a local brain cell that mostly inhibits its neighbors, like a brake. Fast-spiking interneurons are especially influential brakes.
• Disinhibition: loosening a brake, so the cells it was holding back become more active.
• Neural manifold: thousands of neurons could fire in countless ways, but in practice they move together in a much smaller set of patterns. That smaller “surface” of allowed patterns is the manifold.
• Neural trajectory: the path the population traces over time on that surface.
• Persistent homology: a method from topology that detects the shape of data (clusters, loops, holes) and checks that the shape is not an artifact of how the data was simplified.
• Hidden Markov model (HMM): a model that infers which of several hidden “regimes” a system is in and how often it switches between them.
• Neural ODE: a neural network that learns the rule describing how a system’s state changes continuously in time.
• Effective concentration, c(t): the drug level at the site of action over time, as opposed to the dose written on the syringe.

2. What this article claims, and what it does not

This article integrates three sources: (1) a review applying predictive processing to ketamine’s antidepressant mechanism (citing work by Bottemanne and colleagues); (2) a preprint on ketamine in human dorsal forebrain organoids recorded with high-density microelectrode arrays; and (3) a review of ketamine across the dose-state continuum, covering EEG signatures and network dynamics. I add primary papers where I am confident of them, and I mark every place that still needs a primary citation.

Three limits shape everything below:

1. Pharmacokinetics. The sources describe dose, delivery mode and concentration but do not report absorption, distribution, metabolism or elimination parameters. I treat pharmacokinetics as the time course of exposure: its peak, plateau and decline.
2. Geometry is inferred. None of the sources measured manifold geometry under ketamine. Every manifold statement here is an inference from measured connectivity, oscillation and complexity data. Section 5 labels each one.
3. Evidence quality. One source is a bioRxiv preprint on organoids (which lack long-range brain architecture), and two are secondary reviews. See Section 8.

3. Exposure is a movie, not a number

The dose axis is informative but coarse. Reported dose bands depend on route, population and context, and they overlap. As a rough orientation from the dose-state review: very low doses (on the order of 0.1 to 0.5 mg/kg, intravenous, in the sources I used) produce analgesia and mild perceptual change; higher exposure produces dissociation, first from the surroundings, then from the body and self; higher again, behavioral unresponsiveness. The review is explicit that ketamine does not map each dose to a fixed signature.

The shape of exposure over time adds a second axis. The same total dose given as a bolus (a fast, high peak) or as a slow infusion (a steady plateau) leaves different EEG traces. Frontal theta power has been reported to rise after a bolus and fall during slow subanesthetic infusion, and the best-described anesthetic-dose pattern, the gamma burst, appears only at higher effect-site concentrations (Akeju et al., 2016; Vlisides et al., 2017). Context is a third axis: combined with propofol or volatile agents, ketamine can keep processed indices such as the bispectral index (BIS) elevated and can change the course of emergence, often with dreams or hallucinations.

So let c(t) be the effective concentration at the site of action. Two regimens can share the same cumulative dose yet differ in peak, rate of rise and plateau length, and the evidence says the brain responds to all three. Exposure must therefore be treated as a function of time.

Time matters on a longer scale too. The acute effect lasts as long as the drug acts, but antidepressant benefit appears within hours and can outlast it. In the organoid preprint, suppressed bursting returned after 24 hours in saline, but without restoring the original organization. The input is short; its consequences are not.

4. From receptor to circuit

4.1 Receptor and cell type

The primary action of ketamine is non-competitive blockade of the NMDA-type glutamate receptor. Its two mirror-image forms differ: esketamine (S-ketamine) binds the NMDA receptor with several-fold higher affinity than arketamine (R-ketamine), while the antidepressant role of arketamine and of ketamine metabolites remains debated (Zanos et al., 2016).

Because the same receptor sits on different cell types, the same block has different consequences in different places. One well-studied example is the prefrontal cortex. There, NMDA antagonists have been reported to reduce the firing of fast-spiking inhibitory interneurons while increasing the firing of pyramidal (excitatory) neurons and raising glutamate release (Moghaddam et al., 1997; Homayoun and Moghaddam, 2007). In plain terms: ketamine loosens a brake, so the cells it was restraining speed up. The released glutamate then acts at AMPA receptors, which carry fast excitation. The predictive-processing review stresses that this is a description of some circuits, not all.

At higher concentrations other targets are thought to contribute. Inhibition of HCN1 channels has been proposed as one contributor to ketamine’s hypnotic effect, supported by animal knockout work (Chen et al., 2009). It is a proposed contributor, not a settled explanation of unresponsiveness.

Two conclusions follow. First, ketamine does not silence the cortex; it disinhibits and reorganizes it. Second, the resulting disconnection comes from targeted disruption of particular synapses and cell types, not from a uniform change in excitability.

4.2 Circuit computation: predictions versus evidence

Predictive processing is a framework in which the brain constantly generates predictions, compares them with incoming evidence, and updates its internal model by the mismatch (the prediction error). Each side is weighted by precision, the brain’s estimate of how reliable it is. A simple illustration of the idea, not a result from the sources, is a precision-weighted average: the updated belief equals (π_p × prediction + π_s × evidence) divided by (π_p + π_s), where π_p and π_s are the precisions of prediction and evidence. A prediction held with very high precision resists contradicting evidence.

A proposed (relative, not strict) division of labor assigns NMDA receptors to sustaining top-down influence, through slow, recurrent and dendritic processes, and AMPA receptors to fast bottom-up signals and prediction errors. On this view, blocking NMDA while boosting AMPA-driven excitation weakens the sustained top-down influence while altering lower-level signals. The network becomes more active while its hierarchy of predictions and evidence becomes less stable. More activity is not better processing.

For depression, which some accounts describe as negative expectations held with excessive precision, the proposal is that ketamine temporarily loosens the dominance of learned predictions, creating a window in which new experience can revise them. It would not delete negative beliefs; it would make them revisable.

4.3 Oscillations, self-experience and delayed plasticity

Alpha activity (8 to 12 Hz) is linked to top-down regulation and gamma (above 30 Hz) to fast local processing. Ketamine can reduce alpha and increase gamma, consistent with weaker top-down signaling alongside stronger excitation. Mismatch negativity (the brain’s response to a violated regularity, which depends on NMDA function) offers a complementary probe (Umbricht et al., 2000). Neither measure is an exclusive marker of one computation, and the dose-state review adds that the same alpha and low-beta decrease has been tied both to dissociation and to ketamine used as an anesthetic adjunct, so these features seem to track drug effect and arousal more than dissociation itself.

The sense of self is a parallel case: bodily awareness depends on matching predicted sensory consequences against multisensory evidence, so degraded top-down signaling may produce depersonalization and altered body boundaries. Whether dissociation relates to antidepressant response is unsettled, with some studies finding an association and others not.

Finally, an acute change in inference cannot by itself explain benefits that outlast the drug. The proposed bridge is delayed synaptic plasticity involving BDNF and mTOR signaling (Li et al., 2010; Autry et al., 2011). This link remains a hypothesis for now.

5. The same pattern at two scales

5.1 Organoids: a fragmenting network

In dorsal forebrain organoids recorded with high-density microelectrode arrays, mean firing rates fell after ketamine but were not silenced. The reduction concentrated in a subset of burst-driving units the authors call the backbone, and population bursting was abolished. Functional connectivity, estimated with the spike time tiling coefficient, fell: fewer and weaker connections, loss of hub nodes (here, highly connected recorded units, not brain regions), and more clustering into dense communities. The network became more segregated and fragmented, a topology that favors isolated local activity over coordinated information flow. History mattered: after chronic exposure, re-exposure no longer silenced bursting (a form of tolerance), and during gradual dose escalation backbone units declined faster than other units. Bursting returned after 24 hours in saline, but with an altered structure and without full recovery of firing.

Note that ketamine did reduce some activity here. My claim isn’t that nothing goes down, but that integration falls much more than activity does.

5.2 Human EEG: active but disconnected

In the human literature reviewed, the aperiodic spectral slope stayed close to its waking value under ketamine while it steepened under propofol and xenon as consciousness was lost (Colombo et al., 2019). Signal complexity was preserved or increased: subanesthetic doses raised spontaneous complexity above the waking baseline (Schartner et al., 2017), and unresponsive participants under ketamine retained high complexity (Sarasso et al., 2015). Cortical metabolism rises while metabolic connectivity falls, thalamic activity can be preserved, and EEG studies show disrupted long-range and feedback-directed connectivity. Findings vary by dose and study, so these are general trends, not fixed laws.

5.3 What the two scales share

The preparations differ in important ways. Organoids lack the thalamocortical and long-range feedback architecture, and their bursting is a self-organized regime with no exact counterpart in intact cortex. What they share is more informative: in both, an index of activity and an index of integration come apart. Activity is reduced moderately in the organoid and maintained or elevated in the human cortex, whereas integration (edge weight and hubs in one, long-range and feedback connectivity in the other) falls markedly. That is the pattern I call disconnection without silence.

This has a practical consequence. Unresponsiveness under ketamine does not establish absence of experience; the reviewed work indexes external consciousness, and internal experience may remain disconnected in ways it does not capture. And because monitors were developed on GABAergic drugs, ketamine’s fast activity can keep processed indices high without any hypnosis, risking unnecessary escalation of co-administered agents. The dose-state review also reports that ketamine’s large-scale dynamics resemble those seen in PTSD and that its connectome-level signature aligns with that of serotonergic psychedelic states.

6. From measured facts to a geometric hypothesis

A population of N neurons lives in an N-dimensional space, but coordinated activity occupies a much smaller region: the manifold (Gallego et al., 2017). The path on it is the trajectory. If ketamine’s action lies in altered relationships among signals, not in a uniform change in amplitude, then amplitude-based measures are insensitive to it by construction, and measures of organization are the right instruments.

The table separates what was measured in the sources from what I infer. Every geometric row is an inference.

Two rows seem to pull in opposite directions: fragmentation suggests more independent degrees of freedom, while stabilization suggests fewer. They are reconciled if ketamine disconnects between populations while stabilizing dynamics within them, which predicts a manifold that is locally simple and globally disjoint. Persistent homology can test that prediction directly.

The organoid washout result, activity returning but organization not, is consistent with history dependence (hysteresis) in network structure, but a single 24-hour washout does not establish it.

7. A dose-conditioned model, and a first experiment

7.1 The model

Let z(t) be the latent state of the population, obtained by dimensionality reduction of recordings. The proposal is that its evolution follows a vector field that depends on exposure: the rate of change of z equals f(z, c(t)), where f is learned, for example with a neural ODE. In words: the drug does not push the brain to a fixed location; it changes the field of flow on the manifold, and the trajectory at any moment is the integral of that field over the exposure history. Because c(t) differs between a bolus and an infusion of equal total dose, the model predicts different trajectories.

A workable design follows the dose-state source: define a control manifold in awake participants, sample ketamine states across doses, and quantify divergence by subspace alignment, change in dimensionality and change in topology. Hidden Markov models identify latent regimes and test whether one regime transforms into another. Established EEG signatures (alpha reduction, gamma activity, slope, complexity) serve as independent validation, not training targets. Competing mechanisms (altered predictive influence, modified precision weighting, altered excitatory dynamics) should be compared as separate model variants.

7.2 The first experiment I would run

Question: at equal total dose, do bolus and infusion leave the brain on different paths?

Data: existing open EEG recordings of ketamine administration, or the datasets underlying the dose-state review, grouped by delivery mode.

Method: (1) reduce each recording to a low-dimensional latent state; (2) estimate flow and dimensionality per delivery mode; (3) compare modes with subspace alignment and persistent homology; (4) fit an HMM and compare regime occupancy and switching rates.

What would prove me wrong: if, after matching total dose, arousal and movement, bolus and infusion trajectories are not separable beyond between-subject variability, then history dependence is not supported by this data. If persistent homology shows the same topology across doses, the “locally simple, globally disjoint” prediction fails. Reporting that outcome would be a result, not a failure.

7.3 Why it could matter: a shape-aware monitor

If the geometric signatures turn out to be real, a monitor could track the position and flow of the brain in state space instead of a single index trained on GABAergic drugs, and in principle adjust delivery in a closed loop to keep a patient in a target region. That is a long-range idea, not a result, and it needs the validation above first.

8. Limitations

• Source base is thin. Two secondary reviews and one preprint. Preprints are not peer-reviewed (though we do trust them), and the organoid sample size and replication must be checked.
• Organoids are not brains. They lack thalamocortical and long-range feedback architecture, so similarities with human EEG are suggestive, not equivalent.
• No manifold data. The geometry is an inference. Everything in Section 6 labeled “inferred” is a prediction.
• Dose bands overlap and depend on route, population and co-administered drugs.
• Dissociation is not equal to antidepressant effect. The relationship is unsettled.
• Citations in progress. Primary papers are added where I am confident; the PTSD and psychedelic comparisons, the exact receptor-affinity ratio, and the BIS behavior under ketamine still need primary sources.

9. Conclusion

The three sources describe one phenomenon at three scales. At the receptor and cell level, use-dependent NMDA blockade with concentration-dependent consequences produces targeted disruption of coordination. At the network level, it appears as fragmentation, loss of hubs and disrupted long-range communication alongside preserved activity and complexity. At the level of function and experience, it appears as a shifted balance between prediction and evidence, with outcomes from analgesia and dissociation to unresponsiveness and, in the right setting, rapid relief from rigid negative inference.

Pharmacokinetics supplies the temporal structure that selects among these outcomes. Peak, rate and duration of exposure, together with co-administered drugs and history, shape which state the brain enters and how it recovers. The geometric language of manifolds and trajectories is a promising way to unify these facts: a dose-conditioned flow field that changes the shape of population activity, in which disconnection without silence, dependence on exposure history, and the dissociation of unresponsiveness from consciousness appear as properties of geometry, not anomalies.

I do not claim this is established. I claim it is a precise, falsifiable hypothesis, and that the right first step is the bolus-versus-infusion test in Section 7.2.

References

Primary papers below are ones I am confident exist as cited.

• Akeju, O., et al. (2016). Electroencephalogram signatures of ketamine anesthesia-induced unconsciousness. Clinical Neurophysiology.
• Autry, A. E., et al. (2011). NMDA receptor blockade at rest triggers rapid behavioural antidepressant responses. Nature.
• Chen, X., Shu, S., and Bayliss, D. A. (2009). HCN1 channel subunits are a molecular substrate for hypnotic actions of ketamine. Journal of Neuroscience.
• Colombo, M. A., et al. (2019). The spectral exponent of the resting EEG indexes the presence of consciousness during unresponsiveness induced by propofol, xenon, and ketamine. NeuroImage.
• Gallego, J. A., et al. (2017). Neural manifolds for the control of movement. Neuron.
• Homayoun, H., and Moghaddam, B. (2007). NMDA receptor hypofunction produces opposite effects on prefrontal cortex interneurons and pyramidal neurons. Journal of Neuroscience.
• Li, N., et al. (2010). mTOR-dependent synapse formation underlies the rapid antidepressant effects of NMDA antagonists. Science.
• Moghaddam, B., et al. (1997). Activation of glutamatergic neurotransmission by ketamine. Journal of Neuroscience.
• Sarasso, S., et al. (2015). Consciousness and complexity during unresponsiveness induced by propofol, xenon, and ketamine. Current Biology.
• Schartner, M. M., et al. (2017). Increased spontaneous MEG signal diversity for psychoactive doses of ketamine, LSD and psilocybin. Scientific Reports.
• Umbricht, D., et al. (2000). Ketamine-induced deficits in auditory and visual context-dependent processing in healthy volunteers. Archives of General Psychiatry.
• Vlisides, P. E., et al. (2017). Neurophysiologic correlates of ketamine sedation and anesthesia. Anesthesiology.
• Zanos, P., et al. (2016). NMDAR inhibition-independent antidepressant actions of ketamine metabolites. Nature.

Talking about how was this article written, I have read research papers and pre-prints first, then combining all the annotations i reserved, i combined them into one synthesis paper, which resulted in this article

Why the same-looking signal can conceal different dynamics — and how to test whether neural… was originally published in Age of Awareness on Medium, where people are continuing the conversation by highlighting and responding to this story.

For the last few weeks, I’ve been caring for my child’s service dog while they’re in hospital. I’ve taken over the handler duties — taking him for walks, having him stay with me at a home for families near the hospital and bringing him to visit her each day (with his service dog vest on).

What I’ve discovered is the significant amount of public interest, and even interference, service handlers face each and every time they leave the house. It is exhausting!

In case you don’t read this whole article (but I hope you do) here’s some simple advice of what not to do if you encounter a service dog and handler.

• Don’t pet any random dog — but especially one wearing a service dog vest
• Don’t make kissing noises, say here puppy or otherwise try to engage — these are working animals who need to focus on their job
• Don’t ask what the service dog is for — people have a right to keep their health details private
• Don’t ask the handler a million questions- what breed, how old, their name and more.

Best advice — treat the service dog like a mobility aid. You wouldn’t try to strike up a conversation about a wheelchair. Yes, I know the dog is cute, but he has an important job to do. And I need to stick to the training even when he’s not with his handler so he can continue to support them when they’re released.

Working animal

Before I go on my rant about my frustrating experiences (yes, a rant is coming), I need to be clear I’m talking about a fully licensed and trained service dog who serves a specific purpose(s). I’m not talking about a family pet that someone has slapped an Amazon vest on or an emotional support animal or therapy animal.

Rather, I’m talking about a highly trained dog who plays an important role in supporting his/her handler. In the province where I live, service dogs go through a rigorous process to be certified and are tested every two years to retain their certification. They carry government issued ID and have full public access rights.

They are not family pets (although when they’re off duty they’re definitely dogs). When you see a true service dog in action, there’s no doubt they’re at work, focused on their handler.

Unwanted conversations

Now on to my rant. As mentioned, these are working animals with an important job to do. What that job is varies from handler to handler, based on their specific needs. What is common is they need to stay focused. And many times, the handler is navigating a disability that also requires their focus.

This is why the unsolicited questions and conversations start to become annoying. While I appreciate that you have a dog at home, think the dog is cute or just want to say hi, each interaction adds up and takes valuable energy.

It’s funny — when my child is in their wheelchair, no one ever comes up and asks questions about where they got it, how long they’ve had it for, the make or model, or why they need it. Rather, they see a person in a wheelchair and just let them pass by.

A service dog is often a mobility aid (even when the handler doesn’t have mobility issues), helping a person navigate their surroundings, similar to a walker or wheelchair. While yes, they have fur and are cute, their job is no less important.

In the few weeks I’ve been caring for my child’s service dog, I have had hundreds of people stop and try to talk to me, asking their questions. Again, each interaction adds up, taking time and energy. All this while I’m rushing to meet the doctor, or while I’m on the verge of tears.

Admittedly I’ve started walking away from these interactions. Not out of rudeness but self-sustainability. I only have so many spoons in a day, and these “harmless” conversations can quickly deplete me of my spoons.

No touching!

This is my biggest irk — people who reach down to pet the dog in line ups or in elevators. This despite the vest that reads — Medical Alert Dog. IGNORE ME.

When I ask people to please not touch him as he’s working, I often get — but he’s so cute, I just couldn’t resist.

Here’s the thing about ANY dog. It’s never a good idea as a stranger to stick your hand in their face or touch them without asking. Dogs, even service dogs, can react negatively to unexpected touching.

Think about it. Imagine standing in a grocery store lineup and someone just started touching you. You’d likely be startled and may react negatively.

Again, this is just common sense with any dog. Period. Please keep your hands to yourself.

Personal information

Other questions I often get are — what’s he trained for and what’s the medical condition (often with guesses that include ableism language like you don’t look like you have a disability).

Depending on the day, and my patience level, I respond with anything from he’s a medical service dog or, when my spoons are depleted, a person’s medical condition is private information.

Again, I wouldn’t think of asking someone why they’re in a wheelchair. Same with a service dog — it’s not your business why someone needs a service animal. And if it’s a true service dog, fully trained, it’s likely supporting a number of conditions — which are often invisible.

I appreciate that people are curious. But imagine going through life with people asking you about your medical condition each and every day.

Privacy vs education

My final comment (as really, I could rant all day) is balancing privacy vs public education. When I posted about my experience on my Facebook page, someone commented that I shouldn’t be rude and kept walking but rather take the time to educate people about service dogs.

I get it. But really, is it the handler’s job to educate people on disability supports while trying to navigate life with a disability? Definitely not.

Again, let me stress how many times these interactions can happen in a day. To the point where I’ve completely lost count and have absolutely no problem ignoring people and continuing on my way. Otherwise, I could easily add an hour to my day just talking to strangers.

Going back to my spoons, and the spoons of service dog handlers, I need to preserve what limited spoons I have left for the tasks I need to complete vs using the spoons educating complete strangers.

This experience has definitely shown me that there needs to be more public education about service dogs, the various roles they play and the importance of giving them space — emotionally and physically. But is that the role of the person with the disability? Nope.

I will end my rant by saying I hope this has helped you think about service dogs, and their handlers, differently. If you do ask to pet their dog, bombard them with questions or make annoying kissing noises, now you’ll know why the handler simply walked away vs engaging with you. But I know if you’ve read this far, I expect you’re committed to learning and supporting these important working animals.

Please share what you’ve learned with others so service dog handlers can carry on with their day vs having to also be public educators.

Originally published at https://learnpatientadvocacy.com on November 3, 2026.

Curiosity Comes at a Cost: The Hidden Exhaustion of Being a Service Dog Handler — Learn Patient… was originally published in Age of Awareness on Medium, where people are continuing the conversation by highlighting and responding to this story.

Like everyone, I have occasional bouts with insomnia. In many cases it’s kitten-assisted insomnia; one of our four cats is a highly affectionate clouded calico called Bobsy who seems to think I need to be physically rescued from certain death every time I doze off. Marww? MAARW? MARRW!! MARWWW!!! continues until she finds a spot to perch on my shoulder, where she steals my warmz until I subconsciously roll over, when the process starts over again and i’m wide awake.

One of the things I do to fall asleep again is put something on the headphones that i’m super familiar with, that’s not so interesting that I’ll stay glued to it, but something that’s absolutely calming. A spaceflight documentary like The Farthest is a good one. (It’s great, I know it by heart and nothing terrible happens to a Teacher in Space). Another is 1965's Those Magnificent Men in Their Flying Machines a film which I have never in my entire life been awake for the final act, making it a guaranteed sleep aid. Or a re-listen to The Mignight Library of Baseball, which I dearly love, but which is so kind and gentle that after literal midnight I can doze off in the time it takes to play the top half of an inning.

Last night it was Tom Hanks narrating the story of WWII.

I know, it’s harrowing and horrible but also, by and large, a decent, if overly America-centered retelling of the worst thing humanity has ever done to itself. So far.

But it ticks all my boxes: A: Hanks’ voice is a pleasant, steady drone. B: I already know everything that happens, and have since I had the Time/Life book series delivered to me monthly for a few years as a kid in the late 1970s. C: It follows a very standard, predictable kabuki of basic cable talking scholars, none of whom say anything distractingly funny.

And so it was last night, with Bozzer (AKA Bobsy, Bobzer, Cheesecat, Morbier) in position, that I drifted off as Tom Hanks narrated the expensive failure of the Maginot Line to imagine that the Germans could simply use Belgium as a high-speed freeway and goose-step into Paris.

Pretty rarely, these audio tracks invade my REM sleep. And when it did last night, I began to notice things that were …off… in my dream images. US-style roadsigns in the tank-column invasion footage. Hitler walking toward the Eiffel Tower with the city not quite right, Paris looking a bit more like Nashville than it should have in 1940. Then the tower transformed into the loading area for a Belle Époque themed rollercoaster, which Hitler then rode, emotionless, rendered as though it were the product of prompts, with the unmoving light and clouds of a Grok-built construction timelapse.

Crap. I was dreaming in AI slop.

It’s certainly saying something that I’m more upset that I was dreaming in AI than I was about dreaming about Hitler, but here we are.

It went on for a few minutes more, with pretty much every scene of Parisians dealing with the Wehrmacht partying on the Boulevard St. Germain and Marshal Pétain collaborating in Vichy looking like a Donald Trump Truth Social meme. How could it have all happened so quickly, that the visual cues of the digital synthesis of a billion stolen images end up in the render farm of my own dreams? What manager do I complain to about that?

I am now having coffee, stewing about it, but also wondering; has technology been ruining our dreams since, say, the Industrial Revolution?

When I was very young, my mom and I used to talk about whether our dreams the previous night were in color or black and white. (Mom and I talked about dreams a lot when I was a kid, after this event.) She was in her 20s in the 1960s and it was her contention that most people dreamed in black and white, because she’d been talking about it with her classmates and friends for years. I (at 7) reported that I always dreamed in color, and it was proof, to her, that I was special. (I wasn’t.)

In fact, a lot of people then did report dreaming in black and white. For a while, dream researchers in the 20th century began to believe that black and white was sort of the default setting for human dreaming. But today, not only do the vast majority of people report that they dream in color, it’s understood by sleep researchers that people my mother’s age dreamed in black and white because the movies and television they grew up with trained them to dream in black and white.

Technology had ruined her dreams too!

Our dream brains, it seems, are frighteningly malleable. As a teen in Indiana, one of the worst jobs you could get to make decent money over the summer break was detassling corn. Machines mostly do this job now, but back then, the job entailed you and a few dozen of your high school classmates walking (or trudging) along mile-long rows of shoulder-height corn in the most blistering, humid, muddy and UV-danger-zone sunlight the solstice could muster, and yanking the glume-tipped upper part of each corn stalk off to de-sex it as the lower leaf-blades cut your forearms (can you blame them?) until you won a 30 minute break for a hot baloney-and-kraft-single sandwich and a cigarette. After which, you would repeat the process for several more rows, as the afternoon heat, Mr. Pibb and corn sweat turned the landscape and its featureless horizon surrealist.

By bedtime, the experience was most of the way to a dream anyway. And from the moment you closed your eyes, the corn would pass by. And pass by. Some nights it was the exclusive screening in the dream theater. By morning you’d already be exhausted for the next day’s mud fest. I imagine something similar happening to assembly line workers, or anyone with a repetitive relationship with the processes that fuel capitalism. It molds our subconscious.

As far as we can tell, folks in the middle ages dreamed, for the most part, about things they saw during the day; The hunt, the neighbors, the chickens, and the little horrors they encountered. There’s not a lot we can know about how they were rendered, but we do know we had, even before tech, a pretty strong ability to synthesize and combine our daily animal encounters into our night monsters. And when the smokestacks rose, they also monstered up in our dream theaters. So I shouldn’t be too surprised that I’ve fallen victim to this latest infection.

I just can’t believe it would happen so soon.

I dreamed in the visual language of AI slop last night and I’m pretty pissed about it, actually. was originally published in Age of Awareness on Medium, where people are continuing the conversation by highlighting and responding to this story.

I love the idea of doing a lot with very little, and I’m currently bringing that to life in my music studio.

All my students have a favourite song they’ve been dying to do, from the big Disney princess numbers, to rock, pop, jazz, classical, and everything in-between.

But these can be challenging to learn, especially when we’re reducing these big and usually complicated songs to just voice and piano. While the framework of a song remains the same, it can feel scarily unfamiliar, and without the vocal of the original singer it becomes challenging to sing by yourself, let alone make it your own.

What my students need is a way to develop the skills they need and boost their confidence so they feel ready to take on the challenge. And I think the best way to do this is by focusing on something small, without the noise — mentally, emotionally, and literally — of the big songs.

With this in mind, I’ve been writing a collection of small songs. They all use a range of just five or six notes, are only a few lines long, are beautiful to sing, and they allow us to focus on all of the technical and musical aspects of singing, as well as giving us the opportunity to be creative.

Constraints and creativity

I have always been intrigued by the idea that having constraints in place can encourage creativity. It might seem like the opposite should be true. That only five music notes should be an obstacle, a small picture frame a hindrance, a small room not enough space to really dance.

But what I see in my studio and in my own creative work is that having too much room to move, too many options, can induce a form of creative paralysis. How can I possibly know what to do next with so much from which to choose? How can I focus on one thing when there are so many other things demanding my attention?

What I’ve found, again and again, is that deliberately imposing constraints encourages learning and creativity.

In my studio, my small songs give us the opportunity to not just develop skills and knowledge, but also give ourselves permission to be creative in a way that can seem less possible with something much bigger.

Creative exploration

There’s an awful lot of creative exploring we can do with something small.

We make up harmonies for one person to sing while the other sings the melody. We play around with the rhythm and the chords playing underneath. We try different tempos (speed), different rhythms, and different levels of dynamics (loud and soft). We try different sounds and make up lyrics, and we improvise, creating new melodies based on the ones already there.

Because it’s small it feels less risky and, because there are so few notes from which to choose, the creative choices, while constrained, are also guaranteed to sound good.

And when we do return to something much bigger like one of those favourite songs, the difference in how a student approaches it is astounding. It’s not just in the musical choices they make, but in the level of confidence they have in their own ability to not just sing but also create.

Making creativity possible

As always, what works for music works for just about any other creative pursuit you can think of. This is because it’s in the tiny steps, the minutiae of whatever it is you’re creating, that so much creative growth can take place.

Try narrowing your focus and really going in deep. When you eventually broaden your scope again you’ll be amazed at how much stronger and more confident you feel in your ability to be creative and tackle creative challenges.

Kate’s Little Melody

Here’s an excerpt from one of my small songs, fresh from my brain to you:

I’m Kate Paine, and making creativity feel possible is what I do, in my music studio and beyond. Because what unlocks creativity in music unlocks it everywhere. I write about what it actually takes to make things. Curious? So am I!

Small songs was originally published in Age of Awareness on Medium, where people are continuing the conversation by highlighting and responding to this story.

There’s a sound that’s familiar to every single child who has ever spent time on a school playground.

It’s the na nah na nah nah chant beloved of kids everywhere across so many countries, used to express contempt, mockery, ridicule, or to rile up the other team.

And while it’s not exactly the same everywhere, kids in just about every country come up with something remarkably similar, as if we are hard-wired for it.

Long before they have any kind of formal music training, kids are spontaneously organising notes into repeated patterns and structures, and then playing around with these structures, all for fun. They’re manipulating musical relationships with no note names or theory, no understanding of why it works or how, and no thought for right or wrong outcomes.

Nothing but a reason to do it, of which there are plenty when you’re a kid.

Play by immersion

It’s nothing they’ve been taught by any adult or, should I say, nothing we’ve been taught by an adult, as we were all kids once, weren’t we?

And it’s not really from nothing, because we are immersed in sound and music from the moment we’re born. From the voices of our parents onwards we’re soaking in every sound, and also making our own.

As babies and toddlers we sing before we have words. We copy sounds and then do our own variations. When language starts to come we create melodies and songs with whatever words and sounds we like the sound of to be sung at home, on trains, in supermarkets, wherever the inspiration strikes, and often with movements to match.

By the time we’re standing in a school playground making up a chant we’re little experts at what our brains have naturally absorbed. We don’t need to analyse it or check that it’s right because sounds, rhythms, voices, and songs have become part of our internal world.

And throughout all of this process we play with it.

We don’t need to be told twice to experiment. We create elaborate games with no end. We see what happens when we do this and then that, pushing barriers to see how far we can go before they bend or break.

And throughout it all we continue to take in what’s around us, incorporating it into every game or experiment, an ongoing process of let’s see what happens next.

It’s fun, it’s play, it’s how we work out what we’re thinking and feeling and how we make sense of the world. And it’s also a perfect demonstration of creative growth in action.

Creative growth

Children have a relationship with creativity that is much less self-conscious than the one most adults have. They don’t think about it as something to be done or question their ability to do it. It’s simply one of the ways they interact with the world.

Kids are constantly encountering things they don’t yet understand, and one of the best ways to learn is to change things and see what happens. They transform, they combine, they improvise, and then they do it again and again, each time with new variations.

A box is a box is a…

A box, for example, can be not just a receptacle for other things but a spacecraft, a boat, a hat, a bed, a shop, whatever they dream up. Nor do they need the boundary between real and imaginary to stay in one place or to even be there at all. The box can be a spaceship and a box at the same time.

Kids are asking themselves, ‘what else could this box be?’ and this is a deeply creative question.

And as with the example of the chanting in the playground, none of this is happening in isolation. The kids singing in the playground have absorbed and processed enough for them to make the leap to begin creating their own music. The kids with the box have done the same. Now they can take that box and take one creative leap and then another, even if they don’t have a clear idea of where these leaps will have them land.

Play versus adult life

For many adults play is what we think happens before the real business of life starts.

As soon as we start school we start the process of actively separating childhood from adulthood. While it’s acceptable for kids to spend an hour building something that will be knocked down within minutes of completion, we’re likely to see it as a pointless task, it’s value difficult to determine in a world focused on being able to measure outcome.

Children in the playground can chant and sing with no thought to being in tune. Adults have a finely tuned internal and highly judgemental audience we carry with us everywhere. It’s a result of years of soaking up the insidious notion that there is no point opening your mouth to sing if the result is not going to be good.

Good and bad, valid and invalid, measurable and non-measurable, these are the markers we use to judge whether an activity is appropriate and whether we are fit to take part.

And it’s this self-judgement that I see all the time in my music studio.

Play by stealth

Before my new adult singing students even open their mouths for the first time they’re primed to expect themselves to fail to meet the benchmark they already have fixed in their heads.

The best foil for this, I have discovered, is play.

It’s the secret weapon that can take someone ashamed of the sound they think they will produce from feeling frozen to singing anyway. It’s the tactic that will see someone relax enough to take that first leap and then the second and so on.

It’s the game-changer that means someone afraid of making mistakes can start to see them not as the end of the world but instead simply part of the process, with the added bonus that you never know where they might take you.

But I don’t call it play.

It’s curiosity, experimentation, improvisation, making connections, and trying things out. It’s a bit of silliness where none was expected, a mistake that turns into a joke, a sudden moment of lightness that makes any thought of judgement disappear.

It’s just the two of us singing things in different ways, sometimes laughing while we do it. It’s repetition in such a way that it feels enough in itself. It’s breaking up something into such small portions that they seem inconsequential, and then having fun with them.

We pull things apart and put them together again, see what makes them work, see what we like and what we don’t. We clap and move and even dance sometimes, taking away that feeling that singing is only in our heads, which too often results in such a stiff body it’s no wonder the sound doesn’t want to come out.

Making creativity possible

Above all, it’s about making creativity possible, by introducing and nurturing the desire to see what happens, no matter the outcome.

What works in my music studio will work anywhere, because the principle applies no matter the context.

It’s exploration with the notion of a predetermined outcome and judgement removed, and it feels like learning and doing by stealth. It’s taking advantage of our brains in exactly the same way kids chanting in a playground are taking advantage of theirs, acting on instinct instead of to plan, seeing where something takes them.

In order to create something new, we need to be able to hold possibilities in our mind. We need the opportunity to absorb what’s going on around us, test the waters, dip a toe in and take it out again, and then feel emboldened to do it again, and again.

We need to play, in other words, like the kids in just about every playground chanting nah nah na nah nah.

And don’t forget that you were probably one of them, back in the day.

I’m Kate Paine, and making creativity feel possible is what I do, in my music studio and beyond. Because what unlocks creativity in music unlocks it everywhere. I write about what it actually takes to create things. Curious? So am I!

Return of the playground was originally published in Age of Awareness on Medium, where people are continuing the conversation by highlighting and responding to this story.

You wake up.

Before you’ve even decided how you feel, you’ve checked your phone.

A few notifications become a quick scroll. A quick scroll becomes forty minutes. Somehow, you’ve consumed dozens of videos, replied to nobody, learned almost nothing, and already feel mentally tired.

Then comes the guilt.

“Why can’t I just stop?”

We tend to treat this as a willpower problem.

But what if it isn’t?

What if your brain is simply doing exactly what evolution designed it to do?

The oldest technology in the room

The human brain wasn’t built for infinite information.

For hundreds of thousands of years, paying attention to something new was a survival advantage. A sudden movement in the bushes could be food. Or a predator. Either way, your brain rewarded curiosity.

Fast-forward to today.

That same curiosity is met with an endless feed designed to never end.

Instead of discovering one new thing every few hours, your brain encounters hundreds of novel stimuli in a single afternoon.

The system isn’t broken.

It’s overwhelmed.

Why scrolling feels impossible to stop

One of the biggest misconceptions online is that dopamine is simply the “pleasure chemical.”

It’s more accurate to think of dopamine as part of the brain’s motivation and learning systems.

Every swipe carries uncertainty.

Maybe the next post is funny.

Maybe it’s shocking.

Maybe it’s life-changing.

Maybe it’s nothing.

That unpredictability keeps us engaged. Our brains are naturally drawn toward uncertain rewards because, throughout human history, paying attention to uncertain opportunities often increased the chances of survival.

The problem is that today’s digital environments can deliver those opportunities far faster and more frequently than our brains evolved to handle.

The cost of constant stimulation

Many people describe the same experience.

Real life starts to feel…

…slower.

Reading becomes harder.

Silence becomes uncomfortable.

Waiting in line feels unbearable.

Not because we’ve become lazy.

Because our expectations of stimulation have quietly changed.

When every spare second is filled, ordinary moments can begin to feel strangely empty.

The surprising power of boredom

For years, we’ve treated boredom as something to eliminate.

But boredom may be one of the healthiest mental states we’ve lost.

Some psychological research suggests that stepping away from constant demands on attention allows different patterns of thinking to emerge — reflection, mind-wandering, creative problem-solving, and memory processing.

In other words, doing “nothing” isn’t always nothing.

Sometimes it’s where the brain catches up.

This isn’t about deleting your phone

Technology isn’t the enemy.

You’re probably reading this on a screen.

The goal isn’t to reject modern life.

It’s to understand it.

Once you understand why your brain responds the way it does, you stop blaming yourself for every distraction and start making changes that work with your biology instead of against it.

Understanding comes before change.

Why I wrote Touch Grass

I’m a 16-year-old student who became fascinated by a simple question:

Why does my generation feel so mentally overstimulated?

That curiosity led me down a rabbit hole of neuroscience, psychology, behavioral science, and evolutionary biology. Over the course of several months, I read more than 200 peer-reviewed studies trying to understand what the evidence actually says about attention, dopamine, boredom, loneliness, social connection, and life in the age of infinite scroll.

That research became my book:

Touch Grass: The Neuroscience of an Overstimulated Generation — A Field Guide to Your Own Mind in the Age of Infinite Scroll.

It’s not a book about abandoning technology or chasing another 30-day digital detox. It’s about understanding the brain you already have and why it reacts the way it does in a world that changes faster than evolution ever could.

If this article made you think differently about your own relationship with technology, I hope the book will help you explore the science even further.

After all, maybe “touch grass” was never an insult.

Maybe it was neuroscience.

Your Brain Is 300,000 Years Old. Your Smartphone Is 17. Something Had to Break. was originally published in Age of Awareness on Medium, where people are continuing the conversation by highlighting and responding to this story.