The Basal Ganglia and Cortex Implement Optimal Decision Making Between Alternative Actions

By Rafal Bogacz, Kevin N. Gurney. Neural Computation, 2007

431 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/b1ce756729139a23943551cf76ce4252c2fc44ed

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In Cognitive Neuroscience

Citations in the corpus

Neural computations associated with goal-directed choice. (2010, background): “The process terminates when the relative value action becomes sufficiently biased towards one of the choices [48,51–55].”
Neuronal Reward and Decision Signals: From Theories to Data. (2015, methodology): “The basal ganglia may be involved in two distinguishable aspects of decision-making, namely, the direct selection of options and the updating of option values through reinforcement learning (57).”
Multialternative drift-diffusion model predicts the relationship between visual fixations and choice in value-based decisions (2011, background): “Furthermore, the optimal statistical test associated with the case of multiple alternatives is unknown, and only approximations have been proposed (32, 33).”
Action understanding and active inference (2011, neutral): “Exactly the same sort of bias has been proposed for action selection by fronto-striatal loops (e.g. Bogacz and Gurney 2007; Frank et al. 2007; Hazy et al. 2007).”
Attractor and integrator networks in the brain (2021, background): “Neural winner-take-all networks can accurately and rapidly (in ⇠ log(N) time) make the best decision among N alternatives, even if the presented data are noisy (fluctuating over time around their means) [68, 64] and the number of options varies over orders of magnitude [64].”
Striatum and pre-SMA facilitate decision-making under time pressure (2008, background): “The key hypothesis that is shared by recent neuro-computational models of decisionmaking [8, 9, 10, 11, 12] is that when people have to make decisions under time pressure, the basal ganglia lessen their inhibitory control over the brain in a nonspecific fashion, thereby generally facilitating fast b”
Design for a working memory. (2009, methodology): “To optimize selection of a single response, Design for a Working Memory 59 inhibitory links are set up between the response alternatives in the task set (Bogacz & Gurney, 2008; Usher & McClelland, 2001).”
Methodological and empirical developments for the Ratcliff diffusion model of response times and accuracy (2009, background): “Moreover, recent work has started to connect the diffusion model to a range of findings from neuroscience, mainly through the analysis of single cell recordings in monkeys, but also through mathematical modelling (eg, Bogacz & Gurney, 2007 ; for reviews see Gold & Shadlen, 2007 ; Ratcliff & McKoon”
Subthalamic nucleus stimulation reverses mediofrontal influence over decision threshold (2011, background): “Cognitive systems involved in evaluating stimuli and adapting actions are known to be instantiated in cortico-striatal circuits, including mPFC and ST”
Cognitive bias as an indicator of animal emotion and welfare: Emerging evidence and underlying mechanisms (2009, background): “cortical basal ganglia structures (Redgrave et al., 1999; Bogacz and Gurney, 2007) which have the neural architecture required to implement action selection in this way (Redgrave et al.”
Probabilistic population codes for Bayesian decision making (2008, background): “This notion does not generalize easily to multiple directions (Bogacz and Gurney, 2007; McMillen and Holmes, 2006) and does not generalize at all to time- and trial-varying coherence.”
A tutorial on the free-energy framework for modelling perception and learning (2017, background): “Although it has been proposed that circuits within the basal ganglia can compute the normalization term in case of the discrete probability distributions (Bogacz & Gurney, 2007), computation of the normalization for continuous distributions involves evaluating the integral of Eq.”
Selection of cortical dynamics for motor behaviour by the basal ganglia (2015, background): “…competition between channels a cumulative dynamical process, similar of those described in neural-field modelling (Si 1977; Erlhagen and Schoner 2002), with the difference that competition within these CSNTC channels is based on disinhibition rather than excitation (Bogacz and Gurney 2007).”