{1520} revision 0 modified: 09-13-2020 02:00 gmt

PMID-15142952 Visual binding through reentrant connectivity and dynamic synchronization in a brain-based device

  • Controlled a robot with a complete (for the time) model of the occipital-inferotemporal visual pathway (V1 V2 V4 IT), auditory cortex, colliculus, 'value cortex'.
  • Synapses had a timing-dependent assoicative BCM learning rule
  • Robot had reflexes to orient toward preferred auditory stimuli
  • Subsequently, robot 'learned' to orient toward a preferred stimuli (e.g. one that caused orientation).
  • Visual stimuli were either diamonds or squares, either red or green.
    • Discrimination task could have been carried out by (it seems) one perceptron layer.
  • This was 16 years ago, and the results look quaint compared to the modern deep-learning revolution. That said, 'the binding problem' is imho still outstanding or at least interesting. Actual human perception is far more compositional than a deep CNN can support.