Data for: Prediction in cultured cortical neural networks

Theory suggest that networks of neurons may predict their input.
Prediction may underlie most aspects of information processing, and is
believed to be involved in motor and cognitive control and decision
making. Retinal cells have been shown to be capable of predicting visual
stimuli, and there is some evidence for prediction of input in the visual
cortex and hippocampus. However, there is no proof that the ability to
predict is a generic feature of neural networks. We investigated whether
random in vitro neuronal networks can predict stimulation, and how
prediction is related to short and long-term memory. To answer these
questions we applied two different stimulation modalities. Focal
electrical stimulation has been shown to induce long term memory traces,
whereas global optogenetic stimulation did not. We used mutual information
to quantify how much activity recorded from these networks reduces the
uncertainty of upcoming stimuli (prediction) or recent past stimuli
(short-term memory).      Cortical
neural networks did predict future stimuli, with the majority of all
predictive information provided by the immediate network response to the
stimulus. Interestingly, prediction strongly depended on short-term memory
of recent sensory inputs during focal as well as global stimulation.
However, prediction required less short-term memory during focal
stimulation. Furthermore, the dependency on short-term memory decreased
during 20h of focal stimulation, when long-term connectivity changes were
induced. These changes are fundamental for long-term memory formation,
suggesting that besides short-term memory the formation of long-term
memory traces may play a role in efficient prediction.