fMRI Evidence for a Dual Process Account of the Speed-Accuracy Tradeoff in Decision-Making

Background: The speed and accuracy of decision-making have a well-known trading relationship: hasty decisions are more prone to errors while careful, accurate judgments take more time. Despite the pervasiveness of this speed-accuracy tradeoff (SAT) in decision-making, its neural basis is still unknown. Methodology/Principal Findings: Using functional magnetic resonance imaging (fMRI) we show that emphasizing the speed of a perceptual decision at the expense of its accuracy lowers the amount of evidence-related activity in lateral prefrontal cortex. Moreover, this speed-accuracy difference in lateral prefrontal cortex activity correlates with the speedaccuracy difference in the decision criterion metric of signal detection theory. We also show that the same instructions increase baseline activity in a dorso-medial cortical area involved in the internal generation of actions. Conclusions/Significance: These findings suggest that the SAT is neurally implemented by modulating not only the amount of externally-derived sensory evidence used to make a decision, but also the internal urge to make a response. We propose that these processes combine to control the temporal dynamics of the speed-accuracy trade-off in decisionmaking

Integration of Sensory and Reward Information during Perceptual Decision-Making in Lateral Intraparietal Cortex (LIP) of the Macaque Monkey

Single neurons in cortical area LIP are known to carry information relevant to both sensory and value-based decisions that are reported by eye movements. It is not known, however, how sensory and value information are combined in LIP when individual decisions must be based on a combination of these variables. To investigate this issue, we conducted behavioral and electrophysiological experiments in rhesus monkeys during performance of a two-alternative, forced-choice discrimination of motion direction (sensory component). Monkeys reported each decision by making an eye movement to one of two visual targets associated with the two possible directions of motion. We introduced choice biases to the monkeys' decision process (value component) by randomly interleaving balanced reward conditions (equal reward value for the two choices) with unbalanced conditions (one alternative worth twice as much as the other). The monkeys' behavior, as well as that of most LIP neurons, reflected the influence of all relevant variables: the strength of the sensory information, the value of the target in the neuron's response field, and the value of the target outside the response field. Overall, detailed analysis and computer simulation reveal that our data are consistent with a two-stage drift diffusion model proposed by Diederich and Bussmeyer [1] for the effect of payoffs in the context of sensory discrimination tasks. Initial processing of payoff information strongly influences the starting point for the accumulation of sensory evidence, while exerting little if any effect on the rate of accumulation of sensory evidence

Streptozotocin, Type I Diabetes Severity and Bone

As many as 50% of adults with type I (T1) diabetes exhibit bone loss and are at increased risk for fractures. Therapeutic development to prevent bone loss and/or restore lost bone in T1 diabetic patients requires knowledge of the molecular mechanisms accounting for the bone pathology. Because cell culture models alone cannot fully address the systemic/metabolic complexity of T1 diabetes, animal models are critical. A variety of models exist including spontaneous and pharmacologically induced T1 diabetic rodents. In this paper, we discuss the streptozotocin (STZ)-induced T1 diabetic mouse model and examine dose-dependent effects on disease severity and bone. Five daily injections of either 40 or 60 mg/kg STZ induce bone pathologies similar to spontaneously diabetic mouse and rat models and to human T1 diabetic bone pathology. Specifically, bone volume, mineral apposition rate, and osteocalcin serum and tibia messenger RNA levels are decreased. In contrast, bone marrow adiposity and aP2 expression are increased with either dose. However, high-dose STZ caused a more rapid elevation of blood glucose levels and a greater magnitude of change in body mass, fat pad mass, and bone gene expression (osteocalcin, aP2). An increase in cathepsin K and in the ratio of RANKL/OPG was noted in high-dose STZ mice, suggesting the possibility that severe diabetes could increase osteoclast activity, something not seen with lower doses. This may contribute to some of the disparity between existing studies regarding the role of osteoclasts in diabetic bone pathology. Examination of kidney and liver toxicity indicate that the high STZ dose causes some liver inflammation. In summary, the multiple low-dose STZ mouse model exhibits a similar bone phenotype to spontaneous models, has low toxicity, and serves as a useful tool for examining mechanisms of T1 diabetic bone loss

Dynamic excitatory and inhibitory gain modulation can produce flexible, robust and optimal decision-making

<div><p>Behavioural and neurophysiological studies in primates have increasingly shown the involvement of urgency signals during the temporal integration of sensory evidence in perceptual decision-making. Neuronal correlates of such signals have been found in the parietal cortex, and in separate studies, demonstrated attention-induced gain modulation of both excitatory and inhibitory neurons. Although previous computational models of decision-making have incorporated gain modulation, their abstract forms do not permit an understanding of the contribution of inhibitory gain modulation. Thus, the effects of co-modulating both excitatory and inhibitory neuronal gains on decision-making dynamics and behavioural performance remain unclear. In this work, we incorporate time-dependent co-modulation of the gains of both excitatory and inhibitory neurons into our previous biologically based decision circuit model. We base our computational study in the context of two classic motion-discrimination tasks performed in animals. Our model shows that by simultaneously increasing the gains of both excitatory and inhibitory neurons, a variety of the observed dynamic neuronal firing activities can be replicated. In particular, the model can exhibit winner-take-all decision-making behaviour with higher firing rates and within a significantly more robust model parameter range. It also exhibits short-tailed reaction time distributions even when operating near a dynamical bifurcation point. The model further shows that neuronal gain modulation can compensate for weaker recurrent excitation in a decision neural circuit, and support decision formation and storage. Higher neuronal gain is also suggested in the more cognitively demanding reaction time than in the fixed delay version of the task. Using the exact temporal delays from the animal experiments, fast recruitment of gain co-modulation is shown to maximize reward rate, with a timescale that is surprisingly near the experimentally fitted value. Our work provides insights into the simultaneous and rapid modulation of excitatory and inhibitory neuronal gains, which enables flexible, robust, and optimal decision-making.</p></div