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Issue In testing of a trained network
by Aditya Srivastava 10 Dec '24

10 Dec '24

I have built a nest model with a reverse stdp approach in which with time I'm trying to reduce the spikes in training data which is a normal bearing metal data and then during testing I'll try to test it on a anomalous data which should produce opposite results to that of training data so now firstly I made it in brian and it worked fine but here in nest after training the model when I have to test it then again the synaptic weights are changing which should not happen during testing. In brian I had put the learning rate as 0 thats why it was working fine but in Nest I am not able to find a way to test a model by freezing the weights. So I tried something which I'm not sure is the correct approach so can anyone please review this approach or if suggest a better approach for testing these kind of models. Also I want to mention one thing that with my current approach the weights are freezing but as I'm assigning input spikes from anomalous signal and start testing, the kernel is getting died which usually happens when there is a some issue in nest network. nest.ResetKernel() # Simulation parameters dt = 0.01 # Simulation time step in ms nest.SetKernelStatus({"resolution": dt}) N = 16 # Number of neurons gmax = 3 neuron_params = { "tau_m": 140.0, # Membrane time constant in ms "E_L": -70.6, # Resting potential (in mV) "V_th": -40.4, # Threshold potential (in mV) "V_reset": -70.6, # Reset potential (in mV) "V_m":0.0, } nest.CopyModel("stdp_synapse_hom", "stdp_synapse_exc", {"weight":gmax,"alpha":1,"Wmax":gmax, "tau_plus": 20.0,"lambda": -0.0005, "mu_minus": 0, "mu_plus": 0}) nest.CopyModel("stdp_synapse_hom", "stdp_synapse_inh", {"weight":-gmax/(N-1),"alpha":1,"Wmax":-gmax, "tau_plus": 20.0,"lambda": 0.005, "mu_minus": 0, "mu_plus": 0}) G_spike_gen = nest.Create("spike_generator", N) G_input = nest.Create("parrot_neuron", N) G_hidden = nest.Create("iaf_psc_delta", N,params=neuron_params) G_output = nest.Create("iaf_psc_delta", 1,params=neuron_params) S_in = nest.Connect(G_spike_gen, G_input, "one_to_one") # Connect input to hidden layer with excitatory STDP synapses S_exc = nest.Connect(G_input, G_hidden,"one_to_one",syn_spec = "stdp_synapse_exc") # Retrieve the neuron IDs for G_input and G_hidden input_ids = G_input.tolist() hidden_ids = G_hidden.tolist() # Get the existing excitatory connections and extract their source-target ID pairs exc_connections = nest.GetConnections(G_input, G_hidden) exc_connection_pairs = set(zip(exc_connections.get("source"), exc_connections.get("target"))) for i in input_ids: for h in hidden_ids: if (i, h) not in exc_connection_pairs: nc1 = nest.NodeCollection([i]) nc2 = nest.NodeCollection([h]) nest.Connect(nc1, nc2, syn_spec= "stdp_synapse_inh") S_out = nest.Connect(G_hidden, G_output,"all_to_all",syn_spec = {"weight": 40.4/N}) def train_net(signals, spike_tol=0): output_spike_recorder = nest.Create("spike_recorder") output_membrane_recorder = nest.Create("voltmeter", 1) nest.Connect(G_output, output_spike_recorder) # Record output layer spikes nest.Connect(output_membrane_recorder, G_output, "one_to_one") while True: recorder_for_epoch = nest.Create("spike_recorder") nest.Connect(G_output, recorder_for_epoch) for signal in signals: indices, times = process_signal(signal) # Get the indices and times offset = nest.GetKernelStatus()["biological_time"] for i in range(N): times_for_neuron = [t+offset for j,t in enumerate(times) if indices[j] == i] G_spike_gen[i].set(spike_times = times_for_neuron) nest.Simulate(len(signal)*(1/SAMPLE_RATE)*1000) output_spikes_num = len(recorder_for_epoch.get()["events"]["times"]) print("# of output spikes: " + str(output_spikes_num)) del recorder_for_epoch if output_spikes_num <= spike_tol: print("Training finished") break return output_membrane_recorder, output_spike_recorder def synapse_freeze(): conn = nest.GetConnections() sources = conn.get("source") targets = conn.get("target") weights = conn.get("weight") # Store as a list of tuples connections = list(zip(sources, targets, weights)) # Replace dynamic synapses with static synapses for s,t,w in connections: nc1 = nest.NodeCollection([s]) nc2 = nest.NodeCollection([t]) conn_t = nest.GetConnections(nc1,nc2) model=nest.GetConnections(nc1,nc2).get("synapse_model") if model=="stdp_synapse_exc": nest.Disconnect(nc1,nc2,syn_spec = {"synapse_model":"stdp_synapse_exc"}) nest.Connect(nc1,nc2,syn_spec = {"synapse_model":"static_synapse","weight":w}) if model=="stdp_synapse_inh": nest.Disconnect(nc1,nc2,syn_spec = {"synapse_model":"stdp_synapse_inh"}) nest.Connect(nc1,nc2,syn_spec = {"synapse_model":"static_synapse","weight":w}) print("Switched to static synapses with trained weights.") def inference(signal): output_spike_recorder_t = nest.Create("spike_recorder") output_membrane_recorder_t = nest.Create("voltmeter", 1) nest.Connect(G_output, output_spike_recorder_t) # Record output layer spikes nest.Connect(output_membrane_recorder_t, G_output, "one_to_one") indices, times = process_signal(signal) # Prepare test signal offset = nest.GetKernelStatus()["biological_time"] for i in range(N): times_for_neuron = [t+offset for j,t in enumerate(times) if indices[j] == i] G_spike_gen[i].set(spike_times = times_for_neuron) nest.Simulate(len(signal)*(1/SAMPLE_RATE)*1000) # Run simulation output_spikes_num = len(output_spike_recorder_t.get()["events"]["times"]) print("# of output spikes: " + str(output_spikes_num)) return output_membrane_recorder_t, output_spike_recorder_t

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Request for Assistance with Synaptic Weight Normalization
by Peter Mason 02 Dec '24

02 Dec '24

I am currently working on a project involving synaptic weight normalization using the guidelines provided in the NEST simulator documentation. I have implemented the normalization process; however, I encountered some questions that I would appreciate your insights on. 1. Normalization Value: I found that the normalization value for a neuron with approximately 190 synapses is around 420, which I do not fully understand. This looks like the total weight of the neuron synapses. Could you provide clarification on how the normalisation value is determined? 2. Simulation State Preservation: I would like to save and restore the state of synaptic weights to maintain the simulation's behaviour across sessions. Below is the pseudocode I intend to use: Save synaptic weights: w = array of current weights of neuron connections normalization_factor = sum of absolute weights if normalization_factor != 0: normalized_weights = w / normalization_factor save normalized_weights to file Load synaptic weights: read normalized_weights from file assign loaded weights back to connection I would like to know if you have any suggestions for improving this pseudocode or if there are best practices I should consider. Thank you for your time and assistance. I look forward to your response.

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Open NEST Developer Video Conference Monday December 2, at 11:30 CET (UTC+0100)
by Dennis Terhorst 02 Dec '24

02 Dec '24

Dear NEST Users & Developers! I would like to invite you to our next fortnightly Open NEST Developer Video Conference today *Monday December 2, at 11:30 CET (UTC+0100).* As usual, in the Project team round, a contact person of each team will give a short statement summarizing ongoing and planned work in the team and highlight cross-cutting points that need discussion among the teams. The remainder of the meeting we would go into a more in-depth discussion of topics that came up on the mailing list or that are suggested by the teams. Feel free to join the meeting also if it’s just to bring your own quick questions for direct discussion in the in-depth section. Agenda * Welcome * Review of NEST User Mailing List * Project team round * In-depth discussion The agenda for this meeting is also available online, see https://github.com/nest/nest-simulator/wiki/2024-12-02-Open-NEST-Developer-… <https://github.com/nest/nest-simulator/wiki/2024-12-02-Open-NEST-Developer-…> Today Jessica will be chairing the meeting. Cheers, Dennis Terhorst Log-in information We use a virtual conference room provided by DFN <https://www.dfn.de/en/> (Deutsches Forschungsnetz). You can use the web client to connect. We however encourage everyone to use a headset for better audio quality or even a proper video conferencing system (see below) or software when available. Web client * Visit https://conf.dfn.de/webapp/conference/97938800 <https://conf.dfn.de/webapp/conference/97938800> * Enter your name and allow your browser to use camera and microphone * The conference does not need a PIN to join, just click join and you’re in. In case you see a dfnconf logo and the phrase “Auf den Meetingveranstalter warten”, just be patient, the meeting host needs to join first (a voice will tell you). VC system/software How to log in with a video conferencing system, depends on you VC system or software. * Using the H.323 protocol (eg Polycom): |vc.dfn.net##97938800| or |194.95.240.2##97938800| * Using the SIP protocol:97938800@vc.dfn.de <mailto:97938800@vc.dfn.de> * By telephone: |+49-30-200-97938800| For those who do not have a video conference system or suitable software, Polycom provides a pretty good free app for iOS and Android, so you can join from your tablet (Polycom RealPresence Mobile, available from AppStore/PlayStore). Note that firewalls may interfere with videoconferencing in various and sometimes confusing ways. For more technical information on logging in from various VC systems, please see http://vcc.zih.tu-dresden.de/index.php?linkid=1.1.3.4 <http://vcc.zih.tu-dresden.de/index.php?linkid=1.1.3.4> -- Dipl.-Phys. Dennis Terhorst Coordinator Software Development Institute for Advanced Simulation (IAS-6) Computational and Systems Neuroscience & JARA-Institute Brain Structure-Function Relationships (INM-10) Institute of Neuroscience and Medicine Jülich Research Center, Member of the Helmholz Association 52425 Jülich, Germany http://www.csn.fz-juelich.de/ Phone +49 2461 61-85062 ---------------------------------------------------------------------- Forschungszentrum Jülich GmbH 52425 Jülich Sitz der Gesellschaft: Jülich Eingetragen im Handelsregister des Amtsgerichts Düren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Stefan Müller Geschäftsführung: Prof. Dr. Astrid Lambrecht (Vorsitzende), Karsten Beneke (stellv. Vorsitzender), Prof. Dr. Ir. Pieter Jansens ----------------------------------------------------------------------

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Open NEST Developer Video Conference Monday November 18, at 11:30 CET (UTC+0100)
by Dennis Terhorst 02 Dec '24

02 Dec '24

Dear NEST Users & Developers! I would like to invite you to our next fortnightly Open NEST Developer Video Conference today *Monday November 18, at 11:30 CET (UTC+0100).* As usual, in the Project team round, a contact person of each team will give a short statement summarizing ongoing and planned work in the team and highlight cross-cutting points that need discussion among the teams. The remainder of the meeting we would go into a more in-depth discussion of topics that came up on the mailing list or that are suggested by the teams. Feel free to join the meeting also if it’s just to bring your own quick questions for direct discussion in the in-depth section. Agenda * Welcome * Review of NEST User Mailing List * Project team round * In-depth discussion The agenda for this meeting is also available online, see https://github.com/nest/nest-simulator/wiki/2024-11-18-Open-NEST-Developer-… <https://github.com/nest/nest-simulator/wiki/2024-11-18-Open-NEST-Developer-…> Looking forward to seeing you soon! Cheers, Dennis Terhorst Log-in information We use a virtual conference room provided by DFN <https://www.dfn.de/en/> (Deutsches Forschungsnetz). You can use the web client to connect. We however encourage everyone to use a headset for better audio quality or even a proper video conferencing system (see below) or software when available. Web client * Visit https://conf.dfn.de/webapp/conference/97938800 <https://conf.dfn.de/webapp/conference/97938800> * Enter your name and allow your browser to use camera and microphone * The conference does not need a PIN to join, just click join and you’re in. In case you see a dfnconf logo and the phrase “Auf den Meetingveranstalter warten”, just be patient, the meeting host needs to join first (a voice will tell you). VC system/software How to log in with a video conferencing system, depends on you VC system or software. * Using the H.323 protocol (eg Polycom): |vc.dfn.net##97938800| or |194.95.240.2##97938800| * Using the SIP protocol:97938800@vc.dfn.de <mailto:97938800@vc.dfn.de> * By telephone: |+49-30-200-97938800| For those who do not have a video conference system or suitable software, Polycom provides a pretty good free app for iOS and Android, so you can join from your tablet (Polycom RealPresence Mobile, available from AppStore/PlayStore). Note that firewalls may interfere with videoconferencing in various and sometimes confusing ways. For more technical information on logging in from various VC systems, please see http://vcc.zih.tu-dresden.de/index.php?linkid=1.1.3.4 <http://vcc.zih.tu-dresden.de/index.php?linkid=1.1.3.4> -- Dipl.-Phys. Dennis Terhorst Coordinator Software Development Institute for Advanced Simulation (IAS-6) Computational and Systems Neuroscience & JARA-Institute Brain Structure-Function Relationships (INM-10) Institute of Neuroscience and Medicine Jülich Research Center, Member of the Helmholz Association 52425 Jülich, Germany http://www.csn.fz-juelich.de/ Phone +49 2461 61-85062 ---------------------------------------------------------------------- Forschungszentrum Jülich GmbH 52425 Jülich Sitz der Gesellschaft: Jülich Eingetragen im Handelsregister des Amtsgerichts Düren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Stefan Müller Geschäftsführung: Prof. Dr. Astrid Lambrecht (Vorsitzende), Karsten Beneke (stellv. Vorsitzender), Prof. Dr. Ir. Pieter Jansens ----------------------------------------------------------------------

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About Resonate and Fire Neuron Model?
by Thanh Binh To 02 Dec '24

02 Dec '24

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Generating and building code in NESTML
by Shavika Rastogi 25 Nov '24

25 Nov '24

Hello everyone, I am Shavika Rastogi, a PhD student at the International Centre for Neuromorphic Systems, Western Sydney University, Australia. I currently use NEST and NESTML to write and test any arbitrary neuron model. Before writing my own neuron model, I wanted to test neuron models already existing in NESTML. I am using NEST and NESTML using docker. I am running the Izhikevich tutorial available in the documentation ( https://nestml.readthedocs.io/en/latest/tutorials/izhikevich/nestml_izhikev…). As per this tutorial, we can generate and build code using the following statement : "module_name,neuron_model_name=NESTCodeGeneratorUtils.generate_code_for("izhikevich_solution.nestml")" When I am using this function, I get the following error : "AttributeError: 'NESTCodeGeneratorUtils' object has no attribute 'generate_code_for'" Does anyone know whether the generate_code_for() function exists in the NESTCodeGeneratorUtils package? If not, what could be the alternative function we can use for generating and building neuron models ? Thanks in advance. With Warm Regards Shavika Rastogi, Research Scholar (Dual Award PhD) International Centre for Neuromorphic Systems The MARCS Institute of Brain, Behaviour and Development Western Sydney University Sydney, Australia & Biocomputation Research Group University of Hertfordshire, UK

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Re: NESTML Dopa Synapse - Error during parsing
by Jona Scholz 15 Nov '24

15 Nov '24

Hello everyone, quick update on my problem: I was using the latest .nestml models from the main branch with NESTML version 8.0.0-rc3. There is a slight difference between these and apparently that caused it. It works now and I hope everyone has a great weekend. Kind regards, Jona

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NESTML Dopa Synapse - Error during parsing
by Jona Scholz 13 Nov '24

13 Nov '24

Dear NESTML enthusiasts, I'm trying to do the NESTML dopamine-modulated STDP synapse tutorial ( https://nestml.readthedocs.io/en/latest/tutorials/stdp_dopa_synapse/stdp_do…) and get an error during the first code generation (see bottom of the message). This is the line where it fails: NESTCodeGeneratorUtils.generate_code_for("../../../models/neurons/iaf_psc_delta_neuron.nestml", nestml_stdp_dopa_model, ...) I am running the tutorial notebook as is, except for a change in the neuron model path. I changed it like this: NESTCodeGeneratorUtils.generate_code_for("iaf_psc_delta_neuron.nestml", nestml_stdp_dopa_model, ...) With this model https://github.com/nest/nestml/blob/master/models/neurons/iaf_psc_delta_neu… in the same folder as the notebook. I am using NESTML version 8.0.0rc3 and Nest 3.8. If I only generate code for the neuron model everything is fine. module_name, neuron_model_name = NESTCodeGeneratorUtils.generate_code_for( "iaf_psc_delta_neuron.nestml") [100%] Built target nestml_24dea23d173448c9b2a52d4f6a232dbd_module_module Install the project... Additionally, in the SFA tutorial I am able to change the neuron model and run it without any problems ( https://nestml.readthedocs.io/en/latest/tutorials/spike_frequency_adaptatio… ). With all of that said, here is the error: [1,GLOBAL, INFO]: List of files that will be processed: [2,GLOBAL, INFO]: /home/jona/rstdp-gym/iaf_psc_delta_neuron.nestml [3,GLOBAL, INFO]: /home/jona/rstdp-gym/neuromodulated_stdp_synapse.nestml [4,GLOBAL, INFO]: Target platform code will be generated in directory: '/home/jona/rstdp-gym/target' [5,GLOBAL, INFO]: Target platform code will be installed in directory: '/tmp/nestml_target_8uqeeze7' -- N E S T -- Copyright (C) 2004 The NEST Initiative Version: 3.8.0 Built: Aug 27 2024 04:33:09 This program is provided AS IS and comes with NO WARRANTY. See the file LICENSE for details. Problems or suggestions? Visit https://www.nest-simulator.org Type 'nest.help()' to find out more about NEST. [6,GLOBAL, INFO]: The NEST Simulator version was automatically detected as: v3.8.0 [7,GLOBAL, INFO]: Given template root path is not an absolute path. Creating the absolute path with default templates directory '/home/jona/mambaforge/envs/neuro/lib/python3.11/site-packages/pynestml/codegeneration/resources_nest/point_neuron' [8,GLOBAL, INFO]: Given template root path is not an absolute path. Creating the absolute path with default templates directory '/home/jona/mambaforge/envs/neuro/lib/python3.11/site-packages/pynestml/codegeneration/resources_nest/point_neuron' [9,GLOBAL, INFO]: Given template root path is not an absolute path. Creating the absolute path with default templates directory '/home/jona/mambaforge/envs/neuro/lib/python3.11/site-packages/pynestml/codegeneration/resources_nest/point_neuron' [10,GLOBAL, INFO]: The NEST Simulator installation path was automatically detected as: /home/jona/mambaforge/envs/neuro [11,GLOBAL, INFO]: Start processing '/home/jona/rstdp-gym/iaf_psc_delta_neuron.nestml'! [13,GLOBAL, INFO]: Start processing '/home/jona/rstdp-gym/neuromodulated_stdp_synapse.nestml'! [14,GLOBAL, ERROR]: Error occurred during parsing: abort [15,iaf_psc_delta_neuron_nestml, WARNING, [43:0;85:0]]: Model 'iaf_psc_delta_neuron_nestml' contains errors. No code generated! line 37:13 mismatched input '(' expecting NEWLINE line 39:4 extraneous input 'onReceive' expecting {<EOF>, NEWLINE, 'model'} line 40:8 extraneous input ' ' expecting {<EOF>, NEWLINE, 'model'} line 40:4 extraneous input ' ' expecting {<EOF>, NEWLINE, 'model'} line 43:8 extraneous input ' ' expecting {<EOF>, NEWLINE, 'model'} line 46:8 extraneous input 'c' expecting {<EOF>, NEWLINE, 'model'} line 46:4 extraneous input ' ' expecting {<EOF>, NEWLINE, 'model'} line 49:8 extraneous input ' ' expecting {<EOF>, NEWLINE, 'model'} line 52:8 extraneous input 'c' expecting {<EOF>, NEWLINE, 'model'} line 55:8 extraneous input 'emit_spike' expecting {<EOF>, NEWLINE, 'model'} line 55:4 extraneous input ' ' expecting {<EOF>, NEWLINE, 'model'} line 59:8 extraneous input ' ' expecting {<EOF>, NEWLINE, 'model'} line 63:8 extraneous input 'w' expecting {<EOF>, NEWLINE, 'model'} line 64:8 extraneous input 'w' expecting {<EOF>, NEWLINE, 'model'} line 65:8 extraneous input 'c' expecting {<EOF>, NEWLINE, 'model'} line 66:8 extraneous input 'n' expecting {<EOF>, NEWLINE, 'model'} line 66:0 extraneous input '\n' expecting {<EOF>, NEWLINE, 'model'} Any help is appreciated. Kind regards, Jona

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Open NEST Developer Video Conference Monday November 4, at 11:30 CET (UTC+0100)
by Dennis Terhorst 04 Nov '24

04 Nov '24

Dear NEST Users & Developers! I would like to invite you to our next fortnightly Open NEST Developer Video Conference today *Monday November 4, at 11:30 CET (UTC+0100).* As usual, in the Project team round, a contact person of each team will give a short statement summarizing ongoing and planned work in the team and highlight cross-cutting points that need discussion among the teams. The remainder of the meeting we would go into a more in-depth discussion of topics that came up on the mailing list or that are suggested by the teams. Feel free to join the meeting also if it’s just to bring your own quick questions for direct discussion in the in-depth section. Agenda * Welcome * Review of NEST User Mailing List * Project team round * In-depth discussion The agenda for this meeting is also available online, see https://github.com/nest/nest-simulator/wiki/2024-11-04-Open-NEST-Developer-… <https://github.com/nest/nest-simulator/wiki/2024-11-04-Open-NEST-Developer-…> Looking forward to seeing you soon! Cheers, Dennis Terhorst Log-in information We use a virtual conference room provided by DFN <https://www.dfn.de/en/> (Deutsches Forschungsnetz). You can use the web client to connect. We however encourage everyone to use a headset for better audio quality or even a proper video conferencing system (see below) or software when available. Web client * Visit https://conf.dfn.de/webapp/conference/97938800 <https://conf.dfn.de/webapp/conference/97938800> * Enter your name and allow your browser to use camera and microphone * The conference does not need a PIN to join, just click join and you’re in. In case you see a dfnconf logo and the phrase “Auf den Meetingveranstalter warten”, just be patient, the meeting host needs to join first (a voice will tell you). VC system/software How to log in with a video conferencing system, depends on you VC system or software. * Using the H.323 protocol (eg Polycom): |vc.dfn.net##97938800| or |194.95.240.2##97938800| * Using the SIP protocol:97938800@vc.dfn.de <mailto:97938800@vc.dfn.de> * By telephone: |+49-30-200-97938800| For those who do not have a video conference system or suitable software, Polycom provides a pretty good free app for iOS and Android, so you can join from your tablet (Polycom RealPresence Mobile, available from AppStore/PlayStore). Note that firewalls may interfere with videoconferencing in various and sometimes confusing ways. For more technical information on logging in from various VC systems, please see http://vcc.zih.tu-dresden.de/index.php?linkid=1.1.3.4 <http://vcc.zih.tu-dresden.de/index.php?linkid=1.1.3.4> -- Dipl.-Phys. Dennis Terhorst Coordinator Software Development Institute for Advanced Simulation (IAS-6) Computational and Systems Neuroscience & JARA-Institute Brain Structure-Function Relationships (INM-10) Institute of Neuroscience and Medicine Jülich Research Center, Member of the Helmholz Association 52425 Jülich, Germany http://www.csn.fz-juelich.de/ Phone +49 2461 61-85062 ---------------------------------------------------------------------- Forschungszentrum Jülich GmbH 52425 Jülich Sitz der Gesellschaft: Jülich Eingetragen im Handelsregister des Amtsgerichts Düren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Stefan Müller Geschäftsführung: Prof. Dr. Astrid Lambrecht (Vorsitzende), Karsten Beneke (stellv. Vorsitzender), Prof. Dr. Ir. Pieter Jansens ----------------------------------------------------------------------

1 0

Simulation execution time for extended runs
by Peter Mason 01 Nov '24

01 Nov '24

The simulation of C.elegans now is implemented in a multi processing environment. The simulation of each individual object and various observation tools such as visualisation, matplotlib spike data plotting and configuration of the simulation parameters have their own process. An issue has arisen with only one object being simulated in that the execution 'time' for the constant 'simulation step time', increases with subsequent call to pynn.nest.Simulate(self.simulation_step). I presume nest continues the simulation from the previous iteration state. A crude plot suggests that the time increase is linear. Eventually the simulation stalls. I have a recorder connected to each of the 302 nodes and multiple recorders connected to some of the nodes. These use multiprocessor queues and a manged list to transfer data and as far as I can tell they do not overflow. I have disabled the recorders by not connecting them to the neurons and the phenomenon persists. It looks as if the issue is in the nest simulation. I have increased the process priority to -1. It does not help. Also does anyone know of the work of Ramin Hasani at Wien. He seems to have done the same thing and is now using 19 neurons to steer a car. How can I get a copy of the report of work done by him and his students? Peter Mason

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