Topic: decision making

Traditional work in the study of human reward-based learning involves designing an experimental task---often inspired by Reinforcement Learning (RL) theory---and fits a small set of computational models---often inspired by RL algorithms---to that dataset. For example, researchers often model human behavior on bandit tasks using variants of Q-learning. While this approach has been highly productive, leading to landmark discoveries such as the dopamine reward prediction error hypothesis, it also has limitations. This talk focuses on the lack of generalizability of such models: Even if they close

Neural computation is inextricably bound to decisions that must be made under time pressure and uncertainty. At the level of neural circuits, single neurons need to decide whether to spike. On longer timescales, the component circuitry needs to decide whether to reconfigure to store memories and adapt to novel situations. In this talk I will focus on two fun ideas in each of these contexts by showing how nonlinearities in neural components naturally form excitable switches that enable reliable decisions to be made in fluctuating environments. I will also issue propaganda that the kind of high

To understand subjective evaluation of an option, various disciplines have quantified the interaction between reward and effort during decision making, producing an estimate of economic utility, namely the subject ‘goodness’ of an option. However, those same variables that affect the utility of an option also influence the vigor (speed) of movements to acquire it. To better understand this, we have developed a mathematical framework demonstrating how utility can influence not only the choice of what to do, but also the speed of the movement follows. I will present results demonstrating that ex

Attractors play a key role in a wide range of processes including learning, memory, decision making and navigation. Due to recent innovations in recording methods, there is increasing evidence for the existence of attractor dynamics in the brain. Yet, our understanding of how these attractors emerge or disappear in a biological system is lacking. In vitro cultured cortical neurons have been used extensively as a realistic experimental tool to understand the underlying mechanisms in neuronal assemblies. One of the main characteristics of the activity of such networks are the spontaneous synchro

Integrating information is particularly crucial when decisions contain complex information. In decision neuroscience, it has been widely studied how overall decision value is encoded in the brain, but how information is integrated prior to encoding overall value remains largely unclear. Recently, our neuroimaging study has shown that the lateral frontopolar cortex (FPl), a uniquely well-developed region in the human brain, engaged specifically in complex choice but not in simple choice (Law et al., 2023). Aided by an artificial neural network, we found that FPl involved a parallel processing t

Decision making involves assessing potential options and their expected outcomes. In most laboratory studies, decision making is examined through perceptual discrimination tasks with constant net sensory information, and explained as an accumulation of evidence until a threshold is reached. However, natural behavior involves dynamic, intermittently presented perceptual information, necessitating the use of memory. A recent study indicates that, in such cases, decisions align better with an urgency mechanism, which combines sensory evidence from memory or perception with a growing urgency signa

The reciprocal connectivity of the nucleus reuniens (RE) of the ventral midline thalamus with the prefrontal cortex (PFC) and hippocampus (HC) is suggestive of the RE being a critical node within a large-scale brain network underlying spatial cognition. The RE activity has been implicated in navigation, decision making, and spatial memory consolidation. We have previously shown that the RE activity is critical for the retrieval of spatial memory. Yet, the network mechanisms of the RE contribution to the extended prefrontal-thalamo-hippocampal circuit remain to be explored. It has been suggeste