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  6. Circuits Constructed From Identified Aplysia Neurons Exhibit Multiple Patterns Of Persistent Activity

Circuits constructed from identified Aplysia neurons exhibit multiple patterns of persistent activity

D Kleinfeld1, F Raccuia-Behling, H J Chiel

  • 1Solid State and Quantum Physics Research Department, AT&T Bell Laboratories, Murray Hill, New Jersey 07974.

Biophysical Journal|April 1, 1990

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Summary

Two-neuron circuits in Aplysia demonstrate bistable activity, switching between states with external input. This research explores neuronal network models and control mechanisms in neural circuits.

Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Cellular Neuroscience

Background:

  • Neuronal circuits exhibit persistent activity crucial for memory and decision-making.
  • Understanding the fundamental properties of bistable neuronal networks is essential for deciphering complex neural computations.

Purpose of the Study:

  • To investigate the conditions under which simple neuronal circuits can generate bistable activity.
  • To analyze how feedback connections and individual neuron properties contribute to network stability.
  • To explore the potential for external inputs to control these bistable states.

Main Methods:

  • Construction and in vitro analysis of two-neuron circuits using identified neurons from Aplysia abdominal ganglion.
  • Coculturing specific neuron pairs (L10-LUQ with inhibitory connections, L7-L12 with excitatory connections).
  • Recording and analysis of neuronal firing patterns and network output states under varying injected currents.

Main Results:

  • Both circuits exhibited two stable patterns of persistent activity (bistability), switchable by brief external input.
  • Inhibitory L10-LUQ circuit showed alternating activity states, while excitatory L7-L12 circuit showed quiescent and continuously firing states.
  • Bistability depended on neuronal nonlinearities and feedback, with a defined range of background currents for stability.

Conclusions:

  • Simple two-neuron circuits can replicate bistable output states hypothesized for larger neuronal populations.
  • The findings provide insights into how in vivo circuits generate stable activity patterns and how higher centers may exert control.
  • This work validates theoretical models of neuronal network dynamics using experimental preparations.

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