But now there are now two kinds of “nothing”. With green light, the “feedback replay” doesn't need to do anything. If we simply turn the replay device off, it “can’t” do anything. According to theories that depend on causality (e.g. IIT), the two kinds of nothing are fundamentally different.
26.05.2025 10:13 — 👍 3 🔁 0 💬 1 📌 0
A computational functionalist must decide:
Does consciousness require dynamic flexibility and counterfactuals?
Or is a perfect replay, mechanical and unresponsive, still enough?
26.05.2025 10:13 — 👍 1 🔁 0 💬 1 📌 0
So we ask: is consciousness just the path the system did take, or does it require the paths it could have taken?
26.05.2025 10:13 — 👍 2 🔁 0 💬 1 📌 0
In Turing terms: for the same input, the same state transitions occur. But if you change the input (e.g. shine red light), things break. Some states become unreachable. The program is intact but functionally inert. It can’t see colours anymore. Except arguably green - or can it?
26.05.2025 10:13 — 👍 0 🔁 0 💬 1 📌 0
For congruent input (here, the original green light), no corrections are needed. The replay “does nothing”. Everything flows causally just as before. Same input drives the same neurons to have the same activity for the same reasons. If the original system was conscious, should the re-run be, too?
26.05.2025 10:13 — 👍 0 🔁 0 💬 1 📌 0
Back to the new thought experiment extension, where we add a twist: “feedback replay”. Like how patch clamping a cell works, the system now monitors the activity of neurons, only intervening if needed.
26.05.2025 10:13 — 👍 0 🔁 0 💬 1 📌 0
Could the head be feeling something? Is it still computation?
26.05.2025 10:13 — 👍 0 🔁 0 💬 1 📌 0
In the original thought exp, we imagined “forward replay”. Here, the transition function (the program) is ignored, which amounts to a “dancing head”. This feels like a degenerate computation (Unfolding argument? doi.org/10.1016/j.co...).
26.05.2025 10:13 — 👍 0 🔁 0 💬 1 📌 0
A standard Turing Machine cartoon showing the "green states" that the algorithm uses to compute green, and "red states" that are only necessary for seeing red. Additionally, a recording device recording 4 values, the current state, the state transition, what the head writes, and how the head moves (s, t, w, m), for each step.
To analyze this, we model it with a Universal Turing Machine. Input: “green light.” The machine follows its transition rules and outputs “experience of green.” Each step we record 4 values, the current state, the state transition, what the head writes, and how the head moves (s, t, w, m).
26.05.2025 10:13 — 👍 1 🔁 0 💬 1 📌 0
So: is the replayed system still conscious? If everything unfolds the same way, does the conscious experience remain?
26.05.2025 10:13 — 👍 0 🔁 0 💬 1 📌 0
Then we replay it back into the same neurons. The system behaves identically. No intervention needed. So: is the replayed system still conscious? If everything unfolds the same way, does the conscious experience remain?
26.05.2025 10:13 — 👍 0 🔁 0 💬 1 📌 0
We record the entire sequence of what happens when “seeing green”. Then we replay it back into the same simulated neurons. If computational functionalist is right, this drives the “right” brain activity for a 1st-person experience.
26.05.2025 10:13 — 👍 0 🔁 0 💬 1 📌 0
Now, imagine a person looking at a green light. If the computational functionalist is right, the correct brain simulation algorithm doesn't just process green, it experiences green. Here, we start by assuming some deterministic algorithm can simulate all crucial brain activity.
26.05.2025 10:13 — 👍 0 🔁 0 💬 1 📌 0
@Penn Prof, deep learning, brains, #causality, rigor, http://neuromatch.io, Transdisciplinary optimist, Dad, Loves outdoors, 🦖 , c4r.io
Firstgen postdoc at USYD | Bit of physics and neuroscience 🔬 | I make very ordinary science papers; please, whatever you do, don't read them 📖
How brain neural nets do computations; we aim to understand differences in brain wiring, using lasers and neuro-AI.
Lab head, NIH. Prev: policy for democracypolicy.network. Pers views only.
neuro posts: #neuroscience /🧪
M3CS | A unique interdisciplinary centre at Monash University. Through research and education, we explore consciousness, mindfulness, and our connection to each other and the planet.
Learn more: http://monash.edu/m3cs
Algorithms for survival. Investigating the computing architecture of the mind and brain at its limits. 🧠
Lab account for science only.
https://www.caian.uni-bonn.de/en
Chair, Department of Computational Biomedicine at Cedars-Sinai Medical Center in Los Angeles. Director, Center for Artificial Intelligence Research & Education. Atari enthusiast. Retrocomputing. Maker.
Neuroscientist, music- and cat lover, drummer and bass fan, based at Heidelberg University
Brain science. Layer-specific 7T fMRI. Predictive Mind. Multi-scale Neuroscience. Based at Centre for Cognitive Neuroimaging (CCNi), and Imaging centre of Excellence (ICE), University of Glasgow.. So, how does the brain work?
https://muckli.psy.gla.ac.uk/
Interested in learning, predictive processing, memory, and brain development. PI of the Lifespan Cognitive and Brain Development (LISCO) Lab at Goethe University Frankfurt, Germany
Leslie A. Geddes Assistant Professor of Biomedical Engineering,
Weldon School of Biomedical Engineering, Purdue University, WL, IN
Interested in anything Nano and anything Neuro
https://nanoneurotech.com/
just trying to say true and-or kind things
Biologist, neuroscientist, interested in memory and what the brain makes of the world. Also, a mum, but less of that here.
Computational neuroscience and connectomics
Neuroscientist, jazz guitarist, father, neurologist, and co-organizer of the Jazz Artist in Residence program at the Zuckerman Institute @Columbia University. I think about thought—what it is and how it arises—through the neuroscience of decision-making.
Headed by Lucia Melloni @ae.mpg.de @ruhr-uni-bochum.de @nyu.edu.
We care about the brain, consciousness, cognition, & work actively towards a better science culture. This account is jointly run by lab members.
🧠 computational neuroscience | neurophenomenology 2.0? 🤖
Science Writer, Kempner Institute for the study of Natural and Artificial Intelligence at Harvard University
(views here are my own)
Professor at Cornell BME. Studying the neurobiology of psychiatric #drugs including #ketamine and #psychedelics.
https://alexkwanlab.org
UCLA Associate Professor, PhD Researcher of brains 🧠 (development, stem cells, neuroinflammation, autism, sensory processing, brain injury & repair)
Teacher of Neuroanatomy, Neurophilosophy (consciousness, cognitive science), & Stem Cell Biology
Neuroscientist, in theory. Studying sleep and navigation in 🧠s and 💻s.
Assistant Professor at Yale Neuroscience, Wu Tsai Institute.
An emergent property of a few billion neurons, their interactions with each other and the world over ~1 century.
Psychologist and neuroscientist at UCL https://metacoglab.org
Author, Know Thyself (2021) https://metacoglab.org/book
Dad and assistant to the Diplomat