The argument is not that all decisions require long integration times but that those that do permit insights that are otherwise difficult

to attain. To support a neural correlate of a DV, we must at least try to (1) distinguish the response from a sensory response, (2) distinguish it from a motor plan reflecting only the outcome of the decision, and (3) demonstrate a correspondence with the decision process. To achieve these we need more than tests of whether mean responses are different under choice A versus B. We would like to reconcile quantitatively see more the neural response with the DV inferred from a rich analysis of behavior: error rates, reaction time means and distributions, confidence ratings. We say try because there are reasons we do not expect complete satisfaction on any of these criteria. For example the motor system might reflect the DV (Gold and Shadlen, 2000, Selen et al., 2012, Song and Nakayama, 2008, Song and Nakayama, 2009 and Spivey et al., 2005), and noisy sensory responses often bear a weak relationship to choice (Britten et al., 1996, Nienborg and Cumming, 2009, Parker and Newsome, 1998, Uka and DeAngelis, 2004, Celebrini and Newsome, 1994 and Cook and Maunsell, 2002). Nonetheless, for the case of motion learn more bearing on a choice target in the response fields of LIP neurons, the correspondence to a DV seems reasonably compelling. Box

3 summarizes some of the principles that have arisen from a narrow line of investigation. We would like to think that such principles will apply more generally to many types of decisions, including those of humans MYO10 (Kayser et al., 2010, Donner et al., 2009, Heekeren et al., 2004, O’Connell et al., 2012 and Philiastides and Sajda, 2007), and to other cognitive functions that bear no obvious connection to decision making. Of course, many principles are yet to be discovered, and even those that seem solid are not understood at the refined circuit level that will be required to reap the benefits of this knowledge

in medicine. From here on, we will branch outward, beginning with other types of perceptual decisions, then decisions that are not about perception, and on to aspects of cognition that do not at first glance appear to have anything to do with decision making but that may benefit from this perspective. The neurobiology of decision making has exposed features of computation and neural processing that may be viewed as principles of cognitive neuroscience. Flexibility in time. The process is not tied reflexively to immediate changes in the environment or to the real time demands of motor control. Visual neuroscience was poised to contribute to the neurobiology of decision making because of a confluence of progress in psychophysics (Graham, 1989), quantitative reconciliation of signal and noise in the retina (Barlow et al.