Connectionists: Transient subnetwork selection: a new paradigm to replace connectionism?

[Grossberg, Stephen]

Dear Danko,

Thanks very much for sharing your latest article with the connectionists list.

In it, you kindly mention my own work in several places. Thanks very much!

However, the statements that you make about it are not correct.

My Magnum Opus

Conscious Mind, Resonant Brain: How Each Brain Makes a Mind

https://www.amazon.com/Conscious-Mind-Resonant-Brain-Makes/dp/0190070552

provides a self-contained and non-technical overview of many aspects of my work in which these problems
do not occur. I can provide examples if you would like, but will here focus on just one topic:

Your email mentions the importance of metabotropic receptors and suggest that they represent "a new paradigm as an alternative to connectionism...we think with those proteins".

Metabotropic glutamate receptors (mGluR) have played an important role in our work about how our brains learn since our
Journal of Neuroscience article in 1996 on this topic:

Fiala, J.C., Grossberg, S., and Bullock, D. (1996). Metabotropic glutamate receptor activation in cerebellar Purkinje cells
as substrate for adaptive timing of the classically conditioned eye blink response. Journal of Neuroscience, 16, 3760-3774.
https://sites.bu.edu/steveg/files/2016/06/FiaGroBul1996JouNeuroscience.pdf

Later work modeled how they play a role in many other brain regions to regulate multiple types of behaviors. For example:

Grossberg, S. and Merrill, J.W.L. (1992). A neural network model of adaptively timed reinforcement learning and hippocampal dynamics.
Cognitive Brain Research, 1, 3-38.
https://sites.bu.edu/steveg/files/2016/06/GroMer1992CogRes.pdf

Grossberg, S. and Merrill, J.W.L. (l996). The hippocampus and cerebellum in adaptively timed learning, recognition, and movement.
Journal of Cognitive Neuroscience, 8, 257-277.
https://sites.bu.edu/steveg/files/2016/06/GroMer96.pdf

Brown, J., Bullock, D., and Grossberg, S. (1999). How the basal ganglia use parallel excitatory and inhibitory learning pathways
to selectively respond to unexpected rewarding cues. Journal of Neuroscience, 19, 10502-10511.
https://sites.bu.edu/steveg/files/2016/06/BroBulGro99.pdf

Grossberg, S., and Vladusich, T. (2010). How do children learn to follow gaze, share joint attention, imitate their teachers, and use tools
during social interactions? Neural Networks, 23, 940-965.
https://sites.bu.edu/steveg/files/2016/06/GrossbergVladusichNN2010.pdf

Franklin, D. J., and Grossberg, S. (2017). A neural model of normal and abnormal learning and memory consolidation:
Adaptively timed conditioning, hippocampus, amnesia, neurotrophins, and consciousness.
Cognitive, Affective, and Behavioral Neuroscience, 17, 24-76.
https://link.springer.com/article/10.3758/s13415-016-0463-y

I hope that you find these references useful in your own work, and welcome any comments or questions that you may have about
these results.

Best wishes,

Steve



Stephen Grossberg
sites.bu.edu/steveg



________________________________
From: Connectionists <connectionists-bounces at mailman.srv.cs.cmu.edu> on behalf of Danko Nikolic <danko.nikolic at gmail.com>
Sent: Tuesday, January 31, 2023 12:43 PM
To: Post Connectionists <connectionists at mailman.srv.cs.cmu.edu>
Subject: Connectionists: Transient subnetwork selection: a new paradigm to replace connectionism?

Dear all,

I am happy to announce that my paper, the draft of which has been discussed on this list, has yesterday finally been published after a peer review.

This is probably the most important paper I have done in my career so far.

To remind you, the paper proposes a new paradigm as an alternative to connectionism. To understand the mind, synapses are not so important any more. Instead, critical are some other types of proteins on the neural membrane. These proteins have the capability to transiently select subnetworks that will be functional in the next few seconds or minutes. The paradigm proposes that cognition emerges from those transient subnetwork selections (and not from network computations of the classical, the so-called connectionist paradigm). The proteins in question are metabotropic receptors and G protein-gated ion channels. Simply put, we think with those proteins. A result of a thought is a new state of network pathways, not the activity of neurons.

I would like to thank the list for many of the comments that I received and that helped me improve the manuscript. For example, very useful was the information on the learning algorithms able to learn the n-bit parity problem (aka, generalized XOR), which I used to illustrate the scaling problems of deep learning. This made my supplementary materials much better.

The paper can be downloaded without a paywall for 50 days, here:
https://authors.elsevier.com/a/1gVvg5Fq7aXeir

The new version of the paper is much better than the original draft. It has more information, clearer explanations and improved structure.

I hope the paper inspires people to investigate possibilities beyond connectionism both for understanding the brain and for building AI.

For myself, I would love to build an AI based on these principles.

Thanks a lot.

Danko


Dr. Danko Nikolić
www.danko-nikolic.com<http://www.danko-nikolic.com>
https://www.linkedin.com/in/danko-nikolic/
-- I wonder, how is the brain able to generate insight? --
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