Channel
@augmented_brain
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cross-platform identity · Cite this entry
6,044subscribers
-12 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
| Telegram ID | -1001546912681 |
|---|---|
| Type | Channel |
| Username | @augmented_brain |
| Created | 4 July 2021 — measured — cross-checked against a third-party dataset (ext.tg_channel) |
| First recorded | 6 August 2026 |
| Last confirmed live | 12 August 2026 |
| Measurements held | 4 |
| Confirmed unchanged | 1 time, most recently 12 August 2026 |
| On Telegram | t.me/augmented_brain |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 12 Aug 2026, 03:45 | 6,044 | +5 |
| 9 Aug 2026, 02:36 | 6,039 | -14 |
| 6 Aug 2026, 08:11 | 6,053 | -3 |
| 6 Aug 2026, 06:21 | 6,056 | first reading |
85 posts held, back to 4 August 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 9 pagesof Telegram’s post history, 20 posts per page.
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views— note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate. It is computed over the 55 of 85 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 12 August 2026 |
|---|---|
| Posts held | 85 (4 August 2026 – 12 August 2026) |
| Views total | 18,474 |
| Reactions total | 118 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 12 Aug 2026, 03:35 UTC |
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
Measured directly from 7 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
95 reactions across 40 posts, in 10 distinct kinds. The most used accounts for 33.7% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 32 | 33.7% | |
| 👍 | 31 | 32.6% | |
| 🔥 | 14 | 14.7% | |
| 🤔 | 6 | 6.32% | |
| 😁 | 5 | 5.26% | |
| 😱 | 2 | 2.11% | |
| 🤝 | 2 | 2.11% | |
| ✍ | 1 | 1.05% | |
| ❤🔥 | 1 | 1.05% | |
| 🙏 | 1 | 1.05% |
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 55 of the 85 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 118reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 85 most recent posts we hold, published 4 August 2026 to 12 August 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
От теоретической концепции к клинической практике: как брейн-сети и телемедицина объединяются в современную нейротехнологию В 2021 году мы с коллегами опубликовали главу в книге: «Усиление функций через объединение: брейн-сети и телемедицина» («Augmentation Through Interconnection: Brain-Nets and Telemedicine»). В то время концепция объединения нескольких головных мозгов в единую сеть и её интеграция с телемедицинс…
Вдохновляющая новость от Чада Бутона (Chad Bouton) об использовании нашей парадигмы межиндивидуального ИМК («Human Avatar») для совместной реабилитации! (Естественно, без упоминания нашей работы. Но так уж у них заведено.) Продемонстрированная его командой возможность двух людей делиться сенсорным опытом и помогать друг другу преодолевать двигательный дефицит — это важнейшая веха для нашей области. Кроме того, это…
❤1👍1
На конференции BCI Samara 2026 Сергей Шишкин представил доклад о барьерах на пути применения нейроинтерфейсной реабилитации после инсульта. Спикер отметил принципиальную разницу между биологической обратной связью и интерфейсами «мозг-компьютер», подчеркнув, что последние нацелены на совершение действия, а не просто смещение показателя. Несмотря на высокую популяризацию темы, технологию в клинической практике до си…
👍3
В этой работе ученые научили роботов понимать команды человека по направлению моргания: отделяя моргание левым глазом, правым или обоими сразу. Считывая сигналы мозга с помощью простейшей гарнитуры, разработанная программа показала высокую точность — это поможет создать удобные устройства управления для людей с ограниченными возможностями. https://link.springer.com/chapter/10.1007/978-3-032-11411-2_13
👍1
«Материализм и эмпириокритицизм» Ленина — 1 глава Ленин критикует Маха и Авенариуса, которые утверждают, что вещи — это лишь комплексы наших ощущений, а наука должна изучать связи между ними, а не реальный мир. Ленин доказывает, что это субъективный идеализм в духе Беркли, неизбежно ведущий к солипсизму. Все попытки махистов скрыть это несостоятельны: понятие нейтральных элементов распадается, как только мы признае…
Доклад Сергея Шишкина на конференции в Самаре Будет транскрипт, но пока идея использования квазидвижений, то есть инструкции не двигаться, для восстановления движений мне не показалась достаточно убедительной. Здесь, скорее, механический перенос этой темы на когорту инсультных больных. И, как обычно, все упирается в контрольную группу, которая в подобного рода исследованиях как правило отсутствует. Впрочем, все бу…
❤5
Коррекция платоновского пространства https://t.me/ArtemROganov/2506
Когда «нейроинженерия» сходит с рельсов: быстрый взгляд на сомнительное исследование равновесия. Познакомился с очередной свежей статьей в Journal of NeuroEngineering and Rehabilitation (JNER) под названием «Effects of balance training with electrical muscle stimulation on ankle joint muscle on sensory reweighting and motor strategy» («Влияние тренировки равновесия с электростимуляцией мышц голеностопного сустава на…
🤔1
Может ли человек оставаться невербальным до 11 лет, неграмотным до 18, а к 30 годам стать профессором Кембриджа? С нейробиологической точки зрения заявления Джейсона Ардэя с самого начала выглядели неправдоподобно. Тем не менее, несмотря на широкое освещение в международных СМИ, они были безоговорочно приняты Кембриджским университетом и коммерческими издательствами. Вот научный разбор того, почему заявленная Ардэе…
🔥2👍1😱1
Разработан новый гибкий и самовосстанавливающийся материал для «искусственных мышц» — диэлектрических актуаторов, способных сжиматься и растягиваться под действием электричества. Благодаря особой двухслойной структуре эти мышцы начинают работать на 30 вольтах — это в 10 раз ниже, чем у аналогов, при сохранении высокой деформации (более 130%). https://advanced.onlinelibrary.wiley.com/doi/10.1002/adma.202523659
👍1
From the series "Philosophical Parables" One day, Lenin died and ceased to exist. And suddenly, Ernst Mach appears to him and says, “Gedankenexperiment.” And at that moment, Lenin realized that this whole thing was some kind of prank. Since the objects of the objectively existing external world no longer existed, Lenin couldn't throw, say, a glass at Mach. So he decided to take a different approach. Lenin simply …
Is it just me, or have scientific abstracts turned into exercises in deciphering pure gibberish? Given the high reputation and declared quality of the Journal of NeuroEngineering and Rehabilitation (JNER), one expects rigorous clarity. Instead, reading the abstract of a recent paper by Charbonnier et al. ("Variable kinetic constraints in robotic assistance enhance learning of a complex motor skill") is a masterclass…
Showing the 12 most recent of 85 posts we hold for @augmented_brain. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Citation-graph rank — 36,565 of 1,160,990entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Republishes
Channels on the register whose posts this channel has forwarded.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Named by 14 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
Names
Channels on the register whose handles appear in this channel's posts.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
A Wikidata item names this Telegram handle as belonging to the entity it describes. This is Wikidata’s claim, not a verification made by this register — nobody here confirmed that the account is genuinely operated by the entity named. Wikidata content is CC0; every fact below is dated to when it was read from Wikidata, not to when the association was first made there.
| Label | Mikhail A. Lebedev |
|---|---|
| Description | russian neurophysiologist |
| X / Twitter | @LebedevMikhailA |
| Official site | https://sites.google.com/site/lebedevneuro/ |
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 12 August 2026 — this entry's latest reading, not the date you are reading this.
“Лебедев про мозг” (@augmented_brain), 6,044 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/augmented_brain.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.