Decision-making mechanisms in the brain

Behavioral, neurophysiological, and theoretical studies are converging to a common theory of decision-making that assumes an underlying diffusion process which integrates both the accumulation of perceptual and cognitive evidence for making the decision and motor choice in one unifying neural network. In particular, neuronal activity in the ventral premotor cortex (VPC) is related to decision-making while trained monkeys compare two mechanical vibrations applied sequentially to the tip of a finger to report which of the two stimuli have the higher frequency (Romo et al. 2004, Neuron 41: 165). In particular, neurons were found whose response depended only on the difference between the two applied frequencies, the sign of that difference being the determining factor for correct task performance. We describe an integrate-and-fire attractor model with realistic synaptic dynamics including AMPA, NMDA and GABA synapses which can reproduce the decision-making related response selectivity of VPC neurons during the comparison period of the task. Populations of neurons for each decision in the biased competition attractor receive a bias input that depends on the firing rates of neurons in the VPC that code for the two vibrotactile frequencies. It was found that if the connectivity parameters of the network are tuned, using mean-field techniques, so that the network has two possible stable stationary final attractors respectively related to the two possible decisions, then the firing rate of the neurons in whichever attractor wins reflects the sign of the difference in the frequencies being compared but not the absolute frequencies. Thus Weber's law for frequency comparison is not encoded by the firing rate of the neurons in these attractors. An analysis of the nonstationary evolution of the dynamics of the network model shows that Weber's law is implemented in the probability of transition from the initial spontaneous firing state to one of the two possible attractor states. In this way, statistical fluctuations due to finite size noise produced by the spiking dynamics play a crucial role in the decision-making process.