A decision is a deliberative process that leads to a commitment to a categorical proposition or plan of action. For example, a jury takes time to weigh evidence for alternative interpretations before settling on a verdict. Studies of decision-making in such varied fields as psychology, economics, statistics, political- and computer science must consider the flexible and nuanced way that information bears on the choices that agents make. In neuroscience, the study of decision-making opens a window on the neural basis of many other higher cognitive capacities which also use information in a contingent fashion and in a flexible time frame — free from the immediacy of sensory events or the need to control a body in real time.
Recent experiments have begun to expose the neural mechanisms that underlie simple forms of decision-making, in particular those in which a choice must be made based on evidence acquired through the senses. The decisions that arise in these tasks can be thought of as a form of statistical inference: what is the (unknown) state of the world, given the noisy data provided by the sensory systems? Our experiments focus mainly on tasks involving vision and eye movements. Here, the noisy data are action potentials from neurons in the visual cortex, and the choices are made through eye movements to “answer” targets. Progress in visual and oculomotor neuroscience in nonhuman primates over the past half-century has led to the identification of candidate neurons which are well placed to evaluate evidence and convert it to a verdict and plan of action.
We have discovered that many neurons in the parietal and prefrontal association cortex of the monkey accumulate evidence as a function of time. Their activity (spike rate) represents the integral of the stream of evidence in favor of a hypothesis and against its alternative(s). When these spike rates reach a critical level, the decision terminates. These neurons thus signal several quantities: the quality of the evidence, the decision that is made on the basis of this evidence (right or wrong), and the amount of time it takes to reach this decision. These signals are neither purely motor nor purely sensory. Instead, they represent an evolving mental process that contains features of reasoning and deliberation.
The neural computations exposed by these studies explain the tradeoff between the speed and accuracy of many decisions. Interestingly, these same computations were anticipated by Alan Turing in his code-breaking work during World War II, and they were developed by Abraham Wald into the field of Sequential Analysis. Besides its mathematical elegance and strategic importance, this computational mechanism may be essential for higher brain function. If so, the principles revealed by the study of decision- making may one day lead to new treatments for neurological disorders affecting our most cherished cognitive abilities.