Slow transients and attractor neural dynamics of decision-making Recently, neurophysiologists have recorded from nerve cells in the brains of monkeys performing simple decision tasks. These studies have begun to reveal how neurons accumulate information in favor or against choice options in a deliberate decision process, eventually leading to a categorical response. In this talk, I will present a biophysically-based recurrent neural network model of decision making, and show that this model accounts for salient observations from a monkey experiment on perceptual decisions. This model suggests a circuit mechanism for decision-making that can be described theoretically in terms of stochastic attractor dynamical systems