A toy model of the brain
B. Hoeneisen, F. Pasmay
Abstract
We have designed a toy brain and have written computer code that simulates it. This toy brain is flexible, modular, has hierarchical learning and recognition, has short and long term memory, is distributed (i.e. has no central control), is asynchronous, and includes parallel and series processing. We have simulated the neurons calculating their internal voltages as a function of time. We include in the simulation the ion pumps of the neurons, the synapses with glutamate or GABA neurotransmitters, and the delays of the action pulses in axons and dendrites. We have used known or plausible circuits of real brains. The toy brain reads books and learns languages using the Hebb mechanism. Finally, we have related the toy brain with what might be occurring in a real brain.
Create a lesson
Related papers
Learning Time-Varying Connectomes for Stable Behavior Across Development
Christof Fehrman, Jacob J. Morra, Eva A. Naumann
Synchronized Hearts, Desynchronized Brains: A Nonlinear Dynamics Perspective for Function and Failure
Irene Pellini, Simon Bauer, Seba Contreras et al.
Mind Control of LLMs via Closed-Loop Stimulation: Out-of-Distribution Robustness
Kasra Fallah, Rudramani Singha, Hannah Ghanei et al.
A minimal E/I circuit model explains differential recovery from amblyopia under TTX and reverse occlusion
Lawrence Udeigwe
When Model Complexity Matters in Cross-Subject Naturalistic fMRI Prediction
Junhao Zhao, Jacob Kang, Colin Kurniawan et al.
Fly Whiskers Meet LiDAR: Robust Navigation under Sensor Failure
Ali Mahzarnia, Homayoun Jamshidi