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Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
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Neurons, the fundamental units of the brain and nervous system, communicate through complex electrochemical signals that underpin all cognitive and bodily functions. This communication is primarily facilitated by a process involving the generation and propagation of an action potential along the axon of the neuron. When the internal electrical charge of a neuron surpasses a certain threshold, an action potential is triggered. This rapid change in voltage travels swiftly along the axon to the...
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Synaptic integration mainly includes the summation of graded potentials. Graded potentials, regardless of their type, cause subtle alterations in membrane voltage, resulting in either depolarization or hyperpolarization. These incremental changes, when combined or summed, can propel the neuron toward its threshold. Consider, for example, a membrane experiencing a +15 mV shift, causing it to depolarize from -70 mV to -55 mV. In this scenario, graded potentials govern the membrane's ability to...
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A synapse is a specialized structure where two neurons connect, allowing them to pass an electrical or chemical signal to another neuron. It is the point of communication between neurons. The term "synapse" is derived from the Greek word "synapsis," which means "conjunction." The entire process of neural communication revolves around the synapse. When activated, a neuron releases chemicals known as neurotransmitters into the synapse. These neurotransmitters cross the synapse and bind to...
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Interlinked switch circuits of biological intelligence.

Raktim Mukherjee1, Saptarshi Sinha1, Gary D Luker2

  • 1Department of Cellular and Molecular Medicine, University of California, San Diego, CA, 92093, USA.

Trends in Biochemical Sciences
|February 10, 2024
PubMed
Summary

Eukaryotic cells adapt to scarcity using a two-GTPase circuit, suggesting biological intelligence mirrors artificial deep reinforcement learning (RL) principles in uncertain environments.

Keywords:
Ras superfamily GTPase switchesbiological feedbackepidermal growth factor receptor (EGFR)guanine nucleotide-exchange modulators (GEMs)reinforcement learningtrimeric GTPase switches

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Area of Science:

  • Cellular biology
  • Computational neuroscience
  • Artificial intelligence

Background:

  • Eukaryotic cells possess sophisticated network architectures enabling learning and adaptation.
  • Understanding these biological networks is crucial for deciphering cellular intelligence.
  • Recent research highlights specific molecular circuits involved in cellular responses.

Purpose of the Study:

  • To investigate the network architectures underlying eukaryotic cell adaptation.
  • To explore the parallels between biological intelligence in cells and artificial intelligence.
  • To determine if cells function as deep reinforcement learning (RL) agents.

Main Methods:

  • Analysis of a specific two-GTPase circuit in eukaryotic cells.
  • Comparative study of biological and artificial intelligence design principles.
  • Modeling cellular behavior within uncertain environmental conditions.

Main Results:

  • A two-GTPase circuit was identified as a key mechanism for cells to overcome growth factor scarcity.
  • Evidence suggests that biological and artificial intelligence share fundamental design principles.
  • Cells exhibit characteristics consistent with deep reinforcement learning (RL) agents operating in uncertain environments.

Conclusions:

  • The identified two-GTPase circuit is critical for cellular adaptation to resource scarcity.
  • Cells demonstrate intelligent behavior analogous to artificial reinforcement learning systems.
  • This research supports the view of cells as sophisticated RL agents navigating environmental uncertainty.