eLife: Study reveals pathological mechanisms of schizophrenia.

October 1, 2020 /--- -- A new study published in the journal eLife has developed a new type of computer "brain circuit" or artificial neural network that reflects the decision-making processes of the human brain and reveals changes in the circuits of people with mental illness.
the model reveals the underlying mechanism of impaired decision-making in patients with schizophrenia, a reduced molecular activity in the brain called the NDMA receptor.
these results provide a reference for the development of future treatments for neuropsyurological disorders.
(Photo: www.pixabay.com) "The main challenge in psychiatry research is how to link changes in the brain's synapses to cognitive processes that lead to conditions such as schizophrenia," explains lead author Dr Sean Cavanagh of the Institute of Neurology in London, UK.
model of the "brain circuit" can fill these gaps.
can predict neural activity and behavior by changing the circuit model at the synhap level, and then test it experimentally.
team built a model that simulates how the brain makes decisions.
type of decision they are interested in is one that involves merging multiple information.
, for example, when deciding where to go on holiday, we must combine information about many factors, including cost, weather and cultural experience.
, the team wanted to know if their computer models showed the same decision bias as healthy people in such choices, known as "variance bias."
describes how humans tend to have more choice of evidence.
researchers first set decision-making tasks for two macaques and recorded their behavior patterns.
showed the monkeys two series, each with eight bars, one on either side of the computer screen, which had to decide which side had a higher average height.
based on nearly 30,000 sets of information, the researchers looked at the timing of the evidence and the effects of variability on monkey selection.
found that, like humans, monkeys often prefer to choose options that differ more from evidence.
to explore the brain processes that form the basis of this preference, the team built a computer-based circuit model.
the model includes two groups of excitable nerve cells assigned to the right or left options.
two groups of neurons were also connected to inhibitory neurons, which counteracted and balanced the activity of excitable neurons.
, the researchers tested the circuit with the same decision-making tasks, and the results showed that the circuit was able to reproduce the same biases that monkeys used in decision-making (and in humans).
to understand how these decision-making processes are affected in neuropsychiasts such as schizophrenia, the team reduced the activity of synactic NMDA receptors connecting neurons in each excitable and inhibitory group.
found that decision performance in the model depended on the balance between excitation and inhibition, which in turn was affected by relative changes in NDMA subjects in both groups of neurons.
ketamine is known to block NDMA subjects, which in turn temporarily reproduce many symptoms of schizophrenia in healthy people.
to test whether the model's predictions were consistent with behavioral changes, the team studied the effects of ketamine on monkey decision-making.
although ketamine reduced the accuracy of the monkeys' decision-making, they retained the same forward bias.
in computer models, this change in decision-making behavior is consistent with changes in neuron activity.
together, suggesting that changes in decision-making behavior seen in schizophrenia and other diseases may be due to reduced NMDA subjectivity in excitatory neurons.
team hopes this insight could pave the way for the development of new therapies.
(bioon.com) Source: Computer model explains altered decision making in schizophrenia Original source: Sean Edward Cavanagh et al, A circuit mechanism for decision-making biases and NMDA receptor hypofunction, eLife (2020). DOI: 10.7554/eLife.53664.