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Related Experiment Video

Updated: Feb 26, 2026

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Connecting the Brain to Itself through an Emulation.

Mijail D Serruya1

  • 1Neurology, Thomas Jefferson UniversityPhiladelphia, PA, United States.

Frontiers in Neuroscience
|July 18, 2017
PubMed
Summary
This summary is machine-generated.

Pilot clinical trials explore augmenting human cognition using brain-computer interfaces. These trials test external modules for whole brain emulation, aiming to restore function and advance artificial intelligence.

Keywords:
artificial intelligencebrain machine interfacebrain-computer interface (BCI)medical devicesneuroprostheticsorganoidwhole brain emulation

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Area of Science:

  • Neuroscience
  • Artificial Intelligence
  • Biomedical Engineering

Background:

  • Chronic recording and stimulation of neural ensembles offer new possibilities for understanding and augmenting cognition.
  • Existing technologies allow for real-time processing of neural activity and stimulation feedback.

Purpose of the Study:

  • To investigate the potential of external modules for whole brain emulation to expand cognitive substrates.
  • To explore the use of machine learning and bedside testing to identify neural tuning properties and causal effects on perception and behavior.

Main Methods:

  • Pilot clinical trials involving human patients with implanted neural recording and stimulation devices.
  • Development of intermediate external modules (software, VLSI, biological tissue) for real-time neural data processing and stimulation.
  • Application of machine learning algorithms and classic cognitive tasks to identify ensemble tuning and test module architectures.

Main Results:

  • Demonstrated feasibility of closed-loop brain-computer interface pilot clinical trials.
  • Identified methods for rapidly assessing neural ensemble properties and the impact of external modules.
  • Showcased potential for whole brain emulation to augment neural function and compensate for neurological deficits.

Conclusions:

  • Closed-loop brain-computer interfaces and whole brain emulation can advance artificial intelligence development.
  • These technologies offer novel therapeutic strategies for restoring independence in individuals with neurological conditions.
  • Future research can focus on optimizing module architectures and synaptic weight updates for enhanced neural augmentation.