A Probabilistic, Distributed, Recursive Mechanism for Decision-making in the Brain

Decision formation recruits many brain regions, but the procedure they jointly execute is unknown. Here we characterize its essential composition, using as a framework a novel recursive Bayesian algorithm that makes decisions based on spike-trains with the statistics of those in sensory cortex (MT). Using it to simulate the random-dot-motion task, we demonstrate it quantitatively replicates the choice behaviour of monkeys, whilst predicting losses of otherwise usable information from MT. Its architecture maps to the recurrent cortico-basal-ganglia-thalamo-cortical loops, whose components are all implicated in decision-making. We show that the dynamics of its mapped computations match those of neural activity in the sensorimotor cortex and striatum during decisions, and forecast those of basal ganglia output and thalamus. This also predicts which aspects of neural dynamics are and are not part of inference. Our single-equation algorithm is probabilistic, distributed, recursive, and parallel. Its success at capturing anatomy, behaviour, and electrophysiology suggests that the mechanism implemented by the brain has these same characteristics

The Neural Computations In The Caudate Nucleus For Reward-Biased Perceptual Decision-Making

Decision-making is a complex process in which our brain has to combine different sources of information, such as noisy sensory evidence and expected reward, in appropriate ways to obtain the outcome that satisfies the decision-maker. Despite various studies on perceptual decision-making and value-based decision making, it is still unclear how the brain combines sensory and reward information to make a complex decision. A prime candidate for mediating this process is the basal ganglia pathway. This pathway is known to make separate contributions to perceptual decisions based on the interpretation of uncertain sensory evidence and value-based decisions that select among outcome options. To begin to investigate what computations are performed by the brain, particularly in the basal ganglia, we trained monkeys to perform a reward-biased visual motion direction discrimination task and performed single-unit extracellular recordings in the caudate nucleus, the input station in the basal ganglia. Fitting the monkeys’ behaviors to a drift-diffusion model, we found that the monkeys used a rational heuristic to combine sensory and reward information. This heuristic is suboptimal but leads to good-enough outcomes. We also found that the monkeys’ reward biases were sensitive to the changes in the reward functions from session to session. This adaptive adjustment could be a possible reason underlying the individual variability in their decision strategies. By recording in the caudate nucleus, we found that it is involved in both the decision-formation and evaluation: before the monkey started accumulating sensory evidence, the caudate neurons represented the reward context that could be used to form a reward bias; during decision-formation, some caudate neurons jointly represented sensory evidence and reward information, which could facilitate the combining of sensory and reward information appropriately. After a decision is made, caudate nucleus represented both decision confidence and reward expectation, two evaluation-related quantities that influence the monkeys’ subsequent decision behaviors

The Origins of Self

The Origins of Self explores the role that selfhood plays in defining human society, and each human individual in that society. It considers the genetic and cultural origins of self, the role that self plays in socialisation and language, and the types of self we generate in our individual journeys to and through adulthood. Edwardes argues that other awareness is a relatively early evolutionary development, present throughout the primate clade and perhaps beyond, but self-awareness is a product of the sharing of social models, something only humans appear to do. The self of which we are aware is not something innate within us, it is a model of our self produced as a response to the models of us offered to us by other people. Edwardes proposes that human construction of selfhood involves seven different types of self. All but one of them are internally generated models, and the only non-model, the actual self, is completely hidden from conscious awareness. We rely on others to tell us about our self, and even to let us know we are a self

The Origins of Self: An Anthropological Perspective

The Origins of Self explores the role that selfhood plays in defining human society, and each human individual in that society. It considers the genetic and cultural origins of self, the role that self plays in socialisation and language, and the types of self we generate in our individual journeys to and through adulthood. Edwardes argues that other awareness is a relatively early evolutionary development, present throughout the primate clade and perhaps beyond, but self-awareness is a product of the sharing of social models, something only humans appear to do. The self of which we are aware is not something innate within us, it is a model of our self produced as a response to the models of us offered to us by other people. Edwardes proposes that human construction of selfhood involves seven different types of self. All but one of them are internally generated models, and the only non-model, the actual self, is completely hidden from conscious awareness. We rely on others to tell us about our self, and even to let us know we are a self. Developed in relation to a range of subject areas – linguistics, anthropology, genomics and cognition, as well as socio-cultural theory – The Origins of Self is of particular interest to students and researchers studying the origins of language, human origins in general, and the cognitive differences between human and other animal psychologies