<div dir="ltr"><div>Dear Steve,</div><div><br></div><div>Thank you for your email. I have a hard time seeing the relevance of those papers for my present work. There are thousands of papers on metabotropic receptors. However, here I put emphasis on their work in combination with G protein-gated ion channels. Do you have some papers about this combination: MRs and GPGICs working together to ensure transient subnetwork selection? </div><div><br></div><div>If you do and if they fit into the paradigm, I will of course gladly cite them in my next paper.</div><div><br></div><div>Thanks,</div><div><br></div><div>Danko</div><br clear="all"><div><div dir="ltr" class="gmail_signature" data-smartmail="gmail_signature"><div dir="ltr">Dr. Danko Nikolić<br><a href="http://www.danko-nikolic.com" target="_blank">www.danko-nikolic.com</a><br><a href="https://www.linkedin.com/in/danko-nikolic/" target="_blank">https://www.linkedin.com/in/danko-nikolic/</a><div><span style="color:rgb(34,34,34)">-- I wonder, how is the brain able to generate insight? --</span><br></div></div></div></div><br></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Wed, Feb 1, 2023 at 5:24 PM Grossberg, Stephen <<a href="mailto:steve@bu.edu">steve@bu.edu</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div class="msg-7746209270876013617">




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Dear Danko,</div>
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Thanks very much for sharing your latest article with the connectionists list.</div>
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In it, you kindly mention my own work in several places. Thanks very much!</div>
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However, the statements that you make about it are not correct.</div>
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My Magnum Opus </div>
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<b>Conscious Mind, Resonant Brain: How Each Brain Makes a Mind</b></div>
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<a href="https://www.amazon.com/Conscious-Mind-Resonant-Brain-Makes/dp/0190070552" id="m_1020288630203777692LPlnk468083" target="_blank">https://www.amazon.com/Conscious-Mind-Resonant-Brain-Makes/dp/0190070552</a><br>
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provides a self-contained and non-technical overview of many aspects of my work in which these problems</div>
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do not occur. I can provide examples if you would like, but will here focus on just one topic:</div>
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Your email mentions the importance of metabotropic receptors and suggest that they represent "<span style="font-size:18pt;background-color:rgb(255,255,255);display:inline">a new paradigm as an alternative to connectionism...</span><span style="font-size:18pt;background-color:rgb(255,255,255);display:inline">we
 think with those proteins".</span></div>
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<span style="font-size:18pt;background-color:rgb(255,255,255);display:inline"><b>Metabotropic glutamate receptors (mGluR)</b> have played an important role in our work about how our brains learn since our </span></div>
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<span style="font-size:18pt;background-color:rgb(255,255,255);display:inline"><i>Journal of Neuroscience</i> article </span><span style="font-size:18pt">in 1996 on this topic:</span></div>
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<span style="font-size:18pt;background-color:rgb(255,255,255);display:inline"><span style="font-size:18pt;text-align:left;background-color:rgb(255,255,255);display:inline">Fiala, J.C.,
 Grossberg, S., and Bullock, D. (1996). Metabotropic glutamate receptor activation in cerebellar Purkinje cells </span></span></div>
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<span style="font-size:18pt;background-color:rgb(255,255,255);display:inline"><span style="font-size:18pt;text-align:left;background-color:rgb(255,255,255);display:inline">as substrate
 for adaptive timing of the classically conditioned eye blink response.</span><span style="color:rgb(85,85,85);font-family:Capita;font-size:18px;text-align:left;background-color:rgb(255,255,255);display:inline"><span style="font-family:Arial,Helvetica,sans-serif;font-size:18pt;color:rgb(0,0,0);background-color:rgb(255,255,255)"> </span></span><span style="font-size:18pt;background-color:rgb(255,255,255)"><em style="box-sizing:border-box;text-align:left;background-color:rgb(255,255,255)">Journal
 of Neuroscience</em></span><span style="font-size:18pt;text-align:left;background-color:rgb(255,255,255);display:inline">,</span><span style="color:rgb(85,85,85);font-family:Capita;font-size:18px;text-align:left;background-color:rgb(255,255,255);display:inline"><span style="font-family:Arial,Helvetica,sans-serif;font-size:18pt;color:rgb(0,0,0);background-color:rgb(255,255,255)"> </span></span><span style="font-size:18pt;background-color:rgb(255,255,255)"><strong style="box-sizing:border-box;font-weight:bold;text-align:left;background-color:rgb(255,255,255)">16</strong></span><span style="font-size:18pt;text-align:left;background-color:rgb(255,255,255);display:inline">,
 3760-3774.</span><span style="color:rgb(85,85,85);font-family:Capita;font-size:18px;text-align:left;background-color:rgb(255,255,255);display:inline"><span style="font-family:Arial,Helvetica,sans-serif;font-size:18pt;color:rgb(0,0,0);background-color:rgb(255,255,255)"> </span></span><br>
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<a href="https://sites.bu.edu/steveg/files/2016/06/FiaGroBul1996JouNeuroscience.pdf" id="m_1020288630203777692LPNoLPOWALinkPreview" target="_blank">https://sites.bu.edu/steveg/files/2016/06/FiaGroBul1996JouNeuroscience.pdf</a><br>
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Later work modeled how they play a role in many other brain regions to regulate multiple types of behaviors. For example:</div>
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<span style="font-size:18pt;text-align:left;background-color:rgba(0,0,0,0);display:inline">Grossberg, S. and Merrill, J.W.L. (1992). A neural network model of adaptively timed reinforcement learning and hippocampal dynamics.</span><span style="color:rgb(85,85,85);font-family:Capita;font-size:18px;text-align:left;background-color:rgb(255,255,255);display:inline"><span style="font-family:Arial,Helvetica,sans-serif;font-size:18pt;color:rgb(0,0,0);background-color:rgba(0,0,0,0)"> </span></span></div>
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<span style="font-size:18pt;background-color:rgba(0,0,0,0)"><em style="box-sizing:border-box;text-align:left;background-color:rgba(0,0,0,0)">Cognitive Brain Research</em></span><span style="font-size:18pt;text-align:left;background-color:rgba(0,0,0,0);display:inline">,</span><span style="color:rgb(85,85,85);font-family:Capita;font-size:18px;text-align:left;background-color:rgb(255,255,255);display:inline"><span style="font-family:Arial,Helvetica,sans-serif;font-size:18pt;color:rgb(0,0,0);background-color:rgba(0,0,0,0)"> </span></span><span style="font-size:18pt;background-color:rgba(0,0,0,0)"><strong style="box-sizing:border-box;font-weight:bold;text-align:left;background-color:rgba(0,0,0,0)">1</strong></span><span style="font-size:18pt;text-align:left;background-color:rgba(0,0,0,0);display:inline">,
 3-38.</span><span style="color:rgb(85,85,85);font-family:Capita;font-size:18px;text-align:left;background-color:rgb(255,255,255);display:inline"><span style="font-family:Arial,Helvetica,sans-serif;font-size:18pt;color:rgb(0,0,0);background-color:rgba(0,0,0,0)"> </span></span><br>
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<span style="color:rgb(85,85,85);font-family:Capita;font-size:18px;text-align:left;background-color:rgb(255,255,255);display:inline"><span style="font-family:Arial,Helvetica,sans-serif;font-size:18pt;color:rgb(0,0,0);background-color:rgba(0,0,0,0)"><a href="https://sites.bu.edu/steveg/files/2016/06/GroMer1992CogRes.pdf" id="m_1020288630203777692LPlnk289312" target="_blank">https://sites.bu.edu/steveg/files/2016/06/GroMer1992CogRes.pdf</a><br>
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<span style="font-size:18pt;text-align:left;background-color:rgba(0,0,0,0);display:inline">Grossberg, S. and Merrill, J.W.L. (l996). The hippocampus and cerebellum in adaptively timed learning, recognition, and movement.</span><span style="color:rgb(85,85,85);font-family:Capita;font-size:18px;text-align:left;background-color:rgb(255,255,255);display:inline"><span style="font-family:Arial,Helvetica,sans-serif;font-size:18pt;color:rgb(0,0,0);background-color:rgba(0,0,0,0)"> </span></span></div>
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<span style="font-size:18pt;background-color:rgba(0,0,0,0)"><em style="box-sizing:border-box;text-align:left;background-color:rgba(0,0,0,0)">Journal of Cognitive Neuroscience,</em></span><span style="color:rgb(85,85,85);font-family:Capita;font-size:18px;text-align:left;background-color:rgb(255,255,255);display:inline"><span style="font-family:Arial,Helvetica,sans-serif;font-size:18pt;color:rgb(0,0,0);background-color:rgba(0,0,0,0)"> </span></span><span style="font-size:18pt;background-color:rgba(0,0,0,0)"><strong style="box-sizing:border-box;font-weight:bold;text-align:left;background-color:rgba(0,0,0,0)">8</strong></span><span style="font-size:18pt;text-align:left;background-color:rgba(0,0,0,0);display:inline">,
 257-277.</span><span style="color:rgb(85,85,85);font-family:Capita;font-size:18px;text-align:left;background-color:rgb(255,255,255);display:inline"><span style="font-family:Arial,Helvetica,sans-serif;font-size:18pt;color:rgb(0,0,0);background-color:rgba(0,0,0,0)"> </span></span><br>
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<span style="color:rgb(85,85,85);font-family:Capita;font-size:18px;text-align:left;background-color:rgb(255,255,255);display:inline"><span style="font-family:Arial,Helvetica,sans-serif;font-size:18pt;color:rgb(0,0,0);background-color:rgba(0,0,0,0)"><a href="https://sites.bu.edu/steveg/files/2016/06/GroMer96.pdf" id="m_1020288630203777692LPlnk374537" target="_blank">https://sites.bu.edu/steveg/files/2016/06/GroMer96.pdf</a><br>
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<span style="font-size:18pt;text-align:left;background-color:rgba(0,0,0,0);display:inline">Brown, J., Bullock, D., and Grossberg, S. (1999). How the basal ganglia use parallel excitatory and inhibitory learning pathways </span></div>
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<span style="font-size:18pt;text-align:left;background-color:rgba(0,0,0,0);display:inline">to selectively respond to unexpected rewarding cues.</span><span style="color:rgb(85,85,85);font-family:Capita;font-size:18px;text-align:left;background-color:rgb(255,255,255);display:inline"><span style="font-family:Arial,Helvetica,sans-serif;font-size:18pt;color:rgb(0,0,0);background-color:rgba(0,0,0,0)"> </span></span><span style="font-size:18pt;background-color:rgba(0,0,0,0)"><em style="box-sizing:border-box;text-align:left;background-color:rgba(0,0,0,0)">Journal
 of Neuroscience,</em></span><span style="color:rgb(85,85,85);font-family:Capita;font-size:18px;text-align:left;background-color:rgb(255,255,255);display:inline"><span style="font-family:Arial,Helvetica,sans-serif;font-size:18pt;color:rgb(0,0,0);background-color:rgba(0,0,0,0)"> </span></span><span style="font-size:18pt;background-color:rgba(0,0,0,0)"><strong style="box-sizing:border-box;font-weight:bold;text-align:left;background-color:rgba(0,0,0,0)">19</strong></span><span style="font-size:18pt;text-align:left;background-color:rgba(0,0,0,0);display:inline">,
 10502-10511.</span></div>
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<span style="color:rgb(85,85,85);font-family:Capita;font-size:18px;text-align:left;background-color:rgb(255,255,255);display:inline"><span style="font-family:Arial,Helvetica,sans-serif;font-size:18pt;color:rgb(0,0,0);background-color:rgba(0,0,0,0)"><a href="https://sites.bu.edu/steveg/files/2016/06/BroBulGro99.pdf" id="m_1020288630203777692LPlnk888600" target="_blank">https://sites.bu.edu/steveg/files/2016/06/BroBulGro99.pdf</a></span></span></div>
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<span style="color:rgb(85,85,85);font-family:Capita;font-size:18px;text-align:left;background-color:rgb(255,255,255);display:inline"><span style="font-family:Arial,Helvetica,sans-serif;font-size:18pt;color:rgb(0,0,0);background-color:rgba(0,0,0,0)"><span style="font-size:18pt;background-color:rgba(0,0,0,0);display:inline">Grossberg,
 S., and Vladusich, T. (2010). How do children learn to follow gaze, share joint attention, imitate their teachers, and use tools </span></span></span></div>
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<span style="color:rgb(85,85,85);font-family:Capita;font-size:18px;text-align:left;background-color:rgb(255,255,255);display:inline"><span style="font-family:Arial,Helvetica,sans-serif;font-size:18pt;color:rgb(0,0,0);background-color:rgba(0,0,0,0)"><span style="font-size:18pt;background-color:rgba(0,0,0,0);display:inline">during
 social interactions?</span><span style="color:rgb(85,85,85);font-family:Capita;font-size:18px;background-color:rgb(255,255,255);display:inline"><span style="font-family:Arial,Helvetica,sans-serif;font-size:18pt;color:rgb(0,0,0);background-color:rgba(0,0,0,0)"> </span></span><span style="font-size:18pt;background-color:rgba(0,0,0,0)"><em style="box-sizing:border-box;background-color:rgba(0,0,0,0)">Neural
 Networks</em></span><span style="font-size:18pt;background-color:rgba(0,0,0,0);display:inline">,</span><span style="color:rgb(85,85,85);font-family:Capita;font-size:18px;background-color:rgb(255,255,255);display:inline"><span style="font-family:Arial,Helvetica,sans-serif;font-size:18pt;color:rgb(0,0,0);background-color:rgba(0,0,0,0)"> </span></span><span style="font-size:18pt;background-color:rgba(0,0,0,0)"><strong style="box-sizing:border-box;font-weight:bold;background-color:rgba(0,0,0,0)">23</strong></span><span style="font-size:18pt;background-color:rgba(0,0,0,0);display:inline">,
 940-965.</span><span style="color:rgb(85,85,85);font-family:Capita;font-size:18px;background-color:rgb(255,255,255);display:inline"><span style="font-family:Arial,Helvetica,sans-serif;font-size:18pt;color:rgb(0,0,0);background-color:rgba(0,0,0,0)"> </span></span><br>
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 D. J., and Grossberg, S. (2017). A neural model of normal and abnormal learning and memory consolidation: </span></span></span></div>
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 timed conditioning, hippocampus, amnesia, neurotrophins, and consciousness.</span><span style="color:rgb(85,85,85);font-family:Capita;font-size:18px;background-color:rgb(255,255,255);display:inline"><span style="font-family:Arial,Helvetica,sans-serif;font-size:18pt;color:rgb(0,0,0);background-color:rgba(0,0,0,0)"> </span></span></span></span></div>
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<span style="color:rgb(85,85,85);font-family:Capita;font-size:18px;text-align:left;background-color:rgb(255,255,255);display:inline"><span style="font-family:Arial,Helvetica,sans-serif;font-size:18pt;color:rgb(0,0,0);background-color:rgba(0,0,0,0)"><span style="font-size:18pt;background-color:rgba(0,0,0,0)"><em style="box-sizing:border-box;background-color:rgba(0,0,0,0)">Cognitive,
 Affective, and Behavioral Neuroscience</em></span><span style="font-size:18pt;background-color:rgba(0,0,0,0);display:inline">, 17, 24-76.</span><br>
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<span style="color:rgb(85,85,85);font-family:Capita;font-size:18px;text-align:left;background-color:rgb(255,255,255);display:inline"><span style="font-family:Arial,Helvetica,sans-serif;font-size:18pt;color:rgb(0,0,0);background-color:rgba(0,0,0,0)"><span style="font-size:18pt;background-color:rgba(0,0,0,0);display:inline"><a href="https://link.springer.com/article/10.3758/s13415-016-0463-y" id="m_1020288630203777692LPNoLPOWALinkPreview_2" target="_blank">https://link.springer.com/article/10.3758/s13415-016-0463-y</a><br>
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I hope that you find these references useful in your own work, and welcome any comments or questions that you may have about</div>
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these results.</div>
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Best wishes,</div>
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Steve</div>
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<div id="m_1020288630203777692divRplyFwdMsg" dir="ltr"><font face="Calibri, sans-serif" color="#000000" style="font-size:11pt"><b>From:</b> Connectionists <<a href="mailto:connectionists-bounces@mailman.srv.cs.cmu.edu" target="_blank">connectionists-bounces@mailman.srv.cs.cmu.edu</a>> on behalf of Danko Nikolic <<a href="mailto:danko.nikolic@gmail.com" target="_blank">danko.nikolic@gmail.com</a>><br>
<b>Sent:</b> Tuesday, January 31, 2023 12:43 PM<br>
<b>To:</b> Post Connectionists <<a href="mailto:connectionists@mailman.srv.cs.cmu.edu" target="_blank">connectionists@mailman.srv.cs.cmu.edu</a>><br>
<b>Subject:</b> Connectionists: Transient subnetwork selection: a new paradigm to replace connectionism?</font>
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<div>Dear all,</div>
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<div>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. </div>
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<div>This is probably the most important paper I have done in my career so far.</div>
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<div>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.</div>
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<div>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. </div>
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<div>The paper can be downloaded without a paywall for 50 days, here:</div>
<a href="https://authors.elsevier.com/a/1gVvg5Fq7aXeir" target="_blank">https://authors.elsevier.com/a/1gVvg5Fq7aXeir</a>
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<div>The new version of the paper is much better than the original draft. It has more information, clearer explanations and improved structure.</div>
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<div>I hope the paper inspires people to investigate possibilities beyond connectionism both for understanding the brain and for building AI.</div>
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<div>For myself, I would love to build an AI based on these principles.</div>
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<div>Thanks a lot.</div>
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<div>Danko</div>
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<div dir="ltr">Dr. Danko Nikolić<br>
<a href="http://www.danko-nikolic.com" target="_blank">www.danko-nikolic.com</a><br>
<a href="https://www.linkedin.com/in/danko-nikolic/" target="_blank">https://www.linkedin.com/in/danko-nikolic/</a>
<div><span style="color:rgb(34,34,34)">-- I wonder, how is the brain able to generate insight? --</span><br>
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