antagonism

Spontaneous Emergence of Computation in Network Cascades

Neuronal network computation and computation by avalanche supporting networks are of interest to the fields of physics, computer science (computation theory as well as statistical or machine learning) and neuroscience. Here we show that computation of complex Boolean functions arises spontaneously in threshold networks as a function of connectivity and antagonism (inhibition), computed by logic automata (motifs) in the form of computational cascades. We explain the emergent inverse relationship between the computational complexity of the motifs and their rank-ordering by function probabilities due to motifs, and its relationship to symmetry in function space. We also show that the optimal fraction of inhibition observed here supports results in computational neuroscience, relating to optimal information processing.

Deep brain stimulation of the medial septum restores blood perfusion following pharmacologic NMDA antagonism in a region-dependent manner

Dopamine D3 receptor antagonism blocked the Akt/mTOR pathway downregulation in the dentate gyrus after the reinstatement of cocaine induced CPP evoked by physiological stress

Dopamine D3R antagonism facilitates the extinction of drug-seeking behaviours in opiate CPA model and is associated with decreased Iba1 levels in the medial prefrontal cortex

FENS Forum 2024