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Control de la población neuronal a través de la síntesis de imágenes profundas

Pouya Bashivan1, Kohitij Kar2, James J DiCarlo2

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Los investigadores utilizaron redes neuronales artificiales (ANN) para controlar la actividad neuronal en el cerebro de los primates

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Área de la Ciencia:

  • La neurociencia
  • Inteligencia artificial
  • Neurociencia computacional

Sus antecedentes:

  • Las redes neuronales artificiales profundas (ANN) son modelos avanzados de la corriente visual ventral del cerebro de los primates.
  • Los modelos actuales ofrecen una alta precisión en la simulación del procesamiento visual.

Objetivo del estudio:

  • Investigar el potencial de las ANN para el control no invasivo de la actividad neuronal.
  • Explorar la aplicación de la síntesis de imágenes impulsada por ANN para la manipulación neuronal precisa.

Principales métodos:

  • Utilizó un enfoque de síntesis de imágenes impulsado por una red neuronal artificial (ANN).
  • Se aplican patrones de energía luminosa (imágenes) a las retinas de los primates.
  • Se dirigió a sitios neuronales V4 específicos y sus poblaciones.

Principales resultados:

  • Se logró un control predecible de la actividad de picos en sitios neuronales V4 específicos.
  • Se demostró un control independiente sin precedentes de las poblaciones neuronales V4, incluidas las con campos receptivos superpuestos.
  • Mostró la capacidad de empujar la actividad neuronal más allá de los niveles naturales.

Conclusiones:

  • El conocimiento de las ANN se puede utilizar para establecer de manera no invasiva los estados cerebrales deseados a nivel neuronal.
  • Los modelos ANN más precisos podrían conducir a un control aún más fino de la actividad neuronal.
  • Este enfoque ofrece un nuevo método para comprender y potencialmente modular la función cerebral.