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Channel

Нейроинтерфейсы

@bci_ru

On this record: Topic · Observations · Channels linked by matching posts · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry

6,505subscribers

+129 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1001634978355
TypeChannel
Username@bci_ru
Descriptionнейроинтерфейсы (aka интерфейсы мозг-компьютер, BCI, BMI) • айтрекинг, глазоуправление • нейро, когно, психофизиология, HMI • BCI-related ML & DSP • https://bci.megmoscow.ru/ и МЭГ-центр • подробнее см. https://t.me/bci_ru/2
Created27 March 2022 — measured — cross-checked against a third-party dataset (ext.tg_channel)
First recorded6 August 2026
Last confirmed live9 November 2026
Measurements held25
Confirmed unchanged2 times, most recently 9 November 2026
On Telegramt.me/bci_ru

Topic

Science — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 12 September 2026 and assigned it the closest of 31 fixed categories, at 99% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and the other topics.

Observations

These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.

Content that also appears on other registered channels

Posts published here appear in near-verbatim form on 1 other registered channel. This entry also forms a group of 2 channels linked by matching posts. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.

Matching posts — open both and compare (1 of the pairs behind the counts below)
Posted firstThenOverlapGap
@neuronovosti/96826 Nov 2026, 15:14 UTC@bci_ru/6584 · this entry6 Nov 2026, 16:37 UTC1.0083 minutes
Channels this entry shares post bodies with, where at least one matching post pair has no forward credit between the two channels, or to a common source, recorded in our data
ChannelMatching postsText overlapTypical gapPublished first
@neuronovosti5 (5/5 hand-verifiable sample passed)1.0083 minutes@neuronovosti (5–0)

Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.

What this cannot establish

MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.

Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. 1 of the 1 matches recorded here fall after that date and carried no header when we read them. The rest predate reliable capture and are not evidence either way.

“Published first” means first in this corpus. We hold 46 comparable posts for this entry, running 26 July 2026 to 6 November 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.

The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.

  • Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
  • 'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
  • shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
  • Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).

Of the group of 2 channels, the one whose matching posts we hold earliest is @liftfeed. That is a statement about our reading window, not a claim of authorship.

Recorded under the key clone_copy, last confirmed 11 November 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.

Channels linked by matching posts

This channel is in a group of 2 registered channels linked by matching posts. Links are found by comparing text fingerprints across every channel on the register.

Which channel, if either, published first is deliberately not shown in this list. “First” could only mean first in our own crawl, which depends on how deep we happened to reach into each channel’s history, not on when the content was actually first posted. Our one hand-check read 45 of the highest-confidence flagged pairs against the live Telegram pages. In 18 of them the live page showed a “Forwarded from” credit that our database had no record of, so reading that pair as an unattributed copy was wrong; the check did not measure who published first. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Near-verbatim matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.

Growth

6,3736,5056,4396 August 2026 — 6,376 subscribers7 August 2026 — 6,373 subscribers10 August 2026 — 6,386 subscribers12 August 2026 — 6,385 subscribers16 August 2026 — 6,386 subscribers19 August 2026 — 6,392 subscribers22 August 2026 — 6,396 subscribers26 August 2026 — 6,403 subscribers29 August 2026 — 6,405 subscribers1 September 2026 — 6,414 subscribers5 September 2026 — 6,412 subscribers11 September 2026 — 6,413 subscribers14 September 2026 — 6,420 subscribers18 September 2026 — 6,426 subscribers27 September 2026 — 6,437 subscribers5 October 2026 — 6,449 subscribers12 October 2026 — 6,450 subscribers15 October 2026 — 6,456 subscribers18 October 2026 — 6,461 subscribers21 October 2026 — 6,466 subscribers24 October 2026 — 6,480 subscribers28 October 2026 — 6,487 subscribers30 October 2026 — 6,494 subscribers3 November 2026 — 6,504 subscribers6 November 2026 — 6,505 subscribers6 August 20266 November 2026
25 measurements spanning 92 days, net +129. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 6,353–6,525 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 25
Measured (UTC)SubscribersChange
6 Nov 2026, 17:556,505+1
3 Nov 2026, 09:306,504+10
30 Oct 2026, 23:006,494+7
28 Oct 2026, 02:076,487+7
24 Oct 2026, 19:186,480+14
21 Oct 2026, 15:086,466+5
18 Oct 2026, 15:506,461+5
15 Oct 2026, 18:266,456+6
12 Oct 2026, 13:316,450+1
5 Oct 2026, 13:376,449+12
27 Sept 2026, 09:566,437+11
18 Sept 2026, 11:016,426+6
14 Sept 2026, 13:406,420+7
11 Sept 2026, 04:366,413+1
5 Sept 2026, 21:016,412-2
1 Sept 2026, 11:346,414+9
29 Aug 2026, 05:346,405+2
26 Aug 2026, 05:036,403+7
22 Aug 2026, 23:436,396+4
19 Aug 2026, 22:526,392first reading

Engagement

51 posts held, back to 26 July 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 17 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
12.2%
avg views ÷ 6,505 subscribers
Avg views / post
797
22 posts measured
Reaction rate
0.976%
reactions ÷ views · ER floor
Posts in window
22
of 51 held

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.

What these figures were computed from
WindowRolling 30 days · latest post in window 6 November 2026
Posts held51 (26 July 2026 – 6 November 2026)
Views total17,524
Reactions total171
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken9 Nov 2026, 17:09 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.

What this channel posts

Photos
≈2,100
Videos
≈222
Links
≈4,500

Lifetime counters from Telegram’s own channel header, read 9 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.

Video runtime
6m 19s
Average length
2m 06s

Measured directly from 3 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.

Reaction mix

391 reactions across 48 posts, in 22 distinct kinds. The most used accounts for 35.3% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤13835.3%
👍10025.6%
🔥338.44%
❤‍🔥266.65%
😁225.63%
👎143.58%
😢143.58%
🤔71.79%
🤯71.79%
👌61.53%
😍41.02%
👨‍💻30.767%
🕊30.767%
🤝30.767%
👀20.512%
💯20.512%
🥴20.512%
✍10.256%
💘10.256%
🤡10.256%
2 further kinds20.512%

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 49 of the 51 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 399 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 51 most recent posts we hold, published 26 July 2026 to 6 November 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.

Recent posts

Telegram’s own ‘edited’ marker: 4 of 22 posts held from the last 30 days (18.2%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).

6 Nov 2026, 16:37 UTC466 views6 reactionsread 9 November 2026
Photo

Дорогие коллеги! Мы рады вам сообщить, что даты Volga Neuroscience Meeting 2027 определены! Будем ждать вас в Нижнем Новгороде с 5 по 9 июля 2027 года. Конференция пройдет в любимом загородном отеле "Чайка"🕊 Следите за актуальной информацией в канале📢

❤4👍2

Signed Sergei Shishkin

5 Nov 2026, 07:10 UTC616 views14 reactionsread 9 November 2026
Forwarded from @fmba_of_russiaPhoto

🇷🇺Единый контур развития российских биотехнологий: Пироговский университет передан в ведение ФМБА России Подписано распоряжение Правительства Российской Федерации N 3180-р от 3.11.2026 о передаче Федерального государственного автономного образовательного учреждения высшего образования «Национальный исследовательский медицинский университет имени Н.И. Пирогова (Пироговский университет)» в ведение Федерального медико-…

👎9👀2🔥2🤮1

Signed Sergei Shishkin

5 Nov 2026, 06:56 UTC544 views8 reactionsread 9 November 2026
Forwarded from @sensortechVideo

🧠ELVIS C изнутри: как всё устроено? Наша команда работает над созданием первого российского кохлеарного импланта ELVIS C. Технология поможет глухим и слабослышащим людям обрести возможность слышать. И сегодня руководитель проекта Дмитрий Равинский показывает ELVIS C изнутри и объясняет, из каких частей он состоит и за что отвечает каждая из них. 📹Все подробности в видео. Приятного просмотра! ❤️ А если у вас появя…

❤7👍1

Signed Sergei Shishkin

3 Nov 2026, 17:46 UTC681 views4 reactionsread 9 November 2026

7T fMRI + OPM MEG + foundational models -> возможно, действительно удастся что-то новое предсказывать о работе мозга, но ожидания явно завышенные: в пресс-релизе нет совершенно никаких намеков на новые идеи, одни лишь упования на грубую силу мощных новых технологий.

👍4

Signed Sergei Shishkin

3 Nov 2026, 17:35 UTC637 views11 reactionsread 9 November 2026
Forwarded from @blockchainRF

Стэнфорд создаёт ИИ-модель мозга человека В Wu Tsai Neurosciences Institute при Стэнфорде(запрещен в РФ) запустили 5-летнюю программу по созданию фундаментальной ИИ-модели мозга человека Digital Brain Project. Исследователи хотят обучить ИИ-модель на данных мозговой активности, чтобы она научилась предсказывать, как мозг отреагирует в самых разных ситуациях, даже в тех, которые никогда не наблюдала напрямую. Начну…

❤9👍2

Signed Sergei Shishkin

3 Nov 2026, 15:17 UTC589 views4 reactionsread 9 November 2026
Forwarded from @sector_szfPhoto

Друзья, в рамках очередного заседания семинара "Философия сознания: метафизика и когнитивные науки" продолжаем обсуждение методологических и мета-философских вопросов, находящихся на пересечении философии и когнитивной психологии. На очередной встрече, организованной научным сотрудником нашего сектора к.ф.н. Матвеем Сысоевым и профессором РАНХиГС, д.п.н. Владимиром Спиридоновым, обсудим на конкретном примере методол…

😍4

Signed Sergei Shishkin

2 Nov 2026, 17:11 UTC767 views4 reactionsread 9 November 2026
File

Это весьма интересные вопросы (причем статья по ссылке затрагивает, ес-но, более широкий спектр, чем пост). Но точные числа не могли не возбудить у меня некоторые сомнения, и Чат, подумав 14 секунд, их подтвердил. Причем история оказалась очень содержательной, и для желающих углубиться (не столько в числа, сколько в историю и вообще в тему) я прикладываю его ответ. А заканчивается его ответ такими словами (не бог ве…

❤4

Signed Sergei Shishkin

2 Nov 2026, 16:59 UTC630 views8 reactionsread 9 November 2026
Forwarded from @gulagdigital

А вот и новая статья от исследователей Лукоморья Почему ноукод/лоукод уже 70 лет не может победить? https://habr.com/ru/companies/lukit_ru/articles/1100404/ Когда-то Алан Кей писал, что нельзя создать систему, которая позволит рядовому пользователю создать программу наравне с профессионалом по той же причине, почему нельзя создать систему, которая уравнивает ребенка и взрослого при создании какой-то программы. У бо…

👍5🤔2🔥1

Signed Sergei Shishkin

2 Nov 2026, 15:29 UTC545 views4 reactionsread 9 November 2026
Forwarded from @liftfeed

А вот полная программа конференции Neuroscience 2026: сотни докладов, постеров (абстракты), удобно разбиты по дням, темам и направлениям. Отмечу, что начиная с 2025 структура программы обновилась, добавлены отдельно: Theme C: Neural Aging and Degeneration Theme D: Neuroimmunity, Neurovasculature, and Neural Injury ✍️ То есть Общество нейронаук (SfN) с недавних пор выделяет старение и нейроиммунитет как большие темы…

❤4

Signed Sergei Shishkin

2 Nov 2026, 09:06 UTC563 views5 reactionsread 9 November 2026
Forwarded from @brainstart_bioelectrichse

🚀 Мы уже начали, подключайтесь к трансляции по ссылке: https://youtube.com/live/Nl9tE8sNd5Q?feature=share

🔥5

Signed Sergei Shishkin

2 Nov 2026, 08:57 UTC565 views4 reactionsread 9 November 2026
Forwarded from @brainstart_bioelectrichsePhoto

Ура, все спикеры Международной онлайн-школы «Нейроинтерфейсы нового поколения: от нейрона до искусственного интеллекта и обратно» в сборе! 🥳 Знакомьтесь с докладчиками: 🇫🇷 Александр Грамфорт — Университет Париж-Сакле, Франция. «Декодирование электромиографических сигналов в инвариантных к пользователю системах высокоскоростного человеко-машинного взаимодействия»; 🇫🇷 Олеся Догонашева — Институт Пастера, Франция. «Рит…

❤4

Signed Sergei Shishkin

31 Oct 2026, 17:25 UTC796 views8 reactionsread 9 November 2026
File

Для сравнения - реальный soa: мгновенный пофонемный синтез речи с возможностью произвольного интонирования, разработанный в UC Davis. Звук генерируется не после попытки произнесения фразы, а немедленно - каждые 10 мс с минимальной задержкой! В результате пациент слышит произносимые слова точно так же, как их слышит здоровый человек (что очень важно для речи). Тут мышцы если и играют роль, то совсем небольшую. (Стать…

🔥6❤2

Signed Sergei Shishkin

Showing the 12 most recent of 51 posts we hold for @bci_ru. 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.

Forward network

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.

Mentions

Named by 6 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.

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.

Appears in Telegram’s recommendations for other channels

The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.

Все о блокчейн/мозге/space/WEB 3.0 в России и мире
@blockchainRF · 20,455
Telegram ranks this channel #40 of 97 here — alongside 96 others — read 27 September 2026
Дубынин о мозге 🧠
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Telegram ranks this channel #58 of 97 here — alongside 96 others — read 28 August 2026
Sci_Career
@sci_career · 30,649
Telegram ranks this channel #70 of 92 here — alongside 91 others — read 7 September 2026
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Telegram ranks this channel #71 of 95 here — alongside 94 others — read 12 September 2026
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Telegram ranks this channel #74 of 74 here — alongside 73 others — read 22 August 2026
Зоопарк из слоновой кости
@ivoryzoo · 32,048
Telegram ranks this channel #77 of 97 here — alongside 96 others — read 6 September 2026

This channel appears in 6 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.

Cite this entry

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 6 November 2026 — this entry's latest reading, not the date you are reading this.

“Нейроинтерфейсы” (@bci_ru), 6,505 subscribers as measured 6 November 2026. Telegram Register, tgregister.com/channel/bci_ru.

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.