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

Abstract

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-basalganglia-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. Author SummaryDecision-making is central to cognition. Abnormally-formed decisions characterize disorders like over-eating, Parkinson's and Huntington's diseases, OCD, addiction, and compulsive gambling. Yet, a unified account of decisionmaking has, hitherto, remained elusive. Here we show the essential composition of the brain's decision mechanism by matching experimental data from monkeys making decisions, to the knowable function of a novel statistical inference algorithm. Our algorithm maps onto the large-scale architecture of decision circuits in the primate brain, replicating the monkeys' choice behaviour and the dynamics of the neural activity that accompany it. Validated in this way, our algorithm establishes a basic framework for understanding the mechanistic ingredients of decisionmaking in the brain, and thereby, a basic platform for understanding how pathologies arise from abnormal function.

Cognitive capacity limits are remediated by practice-induced plasticity between the Putamen and Pre-Supplementary Motor Area

“…We sought to understand how multitasking demands modulate underlying network dynamics, and how practice changes this network to reduce multitasking costs. We asked whether multitasking demands modulated connectivity within a frontal-parietal cortical network, as has been previously assumed (Dux et al 2006;Marti, King, and Dehaene 2015;Marois and Ivanoff 2005;Sigman and Dehaene 2008;Erickson et al 2007;Hesselmann, Flandin, and Dehaene 2011;Tombu et al 2011;Jiang 2004;Watanabe and Funahashi 2014) , or whether multitasking modulates the striatal-cortical connections recently implicated as critical in single sensorimotor decision making tasks (Caballero, Humphries, and Gurney 2018;Yartsev et al 2018;Badre and Nee 2018) . Specifically, having previously identified that practice-related improvements correlate with activity changes in the pre-SMA, the IPS and the putamen (Garner and Dux 2015) , we applied DCM to ask how multitasking modulates connectivity between these regions.…”

“…We probed the network dynamics underlying multitasking limitations, and asked whether they stem from information processing limitations in the previously hypothesised frontal-parietal network (Watanabe andFunahashi 2014, 2018;Garner and Dux 2015;Marti, King, and Dehaene 2015) , or whether they were better characterised as stemming from limits in a striatal-cortical network, as suggested by models probing the neural mechanisms underlying single sensorimotor task performance (Caballero, Humphries, and Gurney 2018;Bornstein and Daw 2011;Joel, Niv, and Ruppin 2002) . Using an implementation of DCM, we found evidence that multitasking demands motivate increased rates of information sharing between the putamen and cortical sites, suggesting that performance decrements are due to a limit in the rate at which the putamen can excite appropriate cortical stimulus-response representations.…”

“…We sought to understand how multitasking demands modulate underlying network dynamics, and how practice changes this network to reduce multitasking costs. We adjudicated between previously hypothesised models posing that multitasking demands modulate connectivity within 1) a frontal-parietal cortical network (Dux et al 2006 (Caballero, Humphries, and Gurney 2018;Yartsev et al 2018;Badre and Nee 2018) . We demonstrate evidence in keeping with the latter.…”

“…Despite recent advances, our understanding of the network dynamics that drive multitasking costs and the influence of practice remains unknown. Furthermore, although recent work has focused on understanding cortical contributions to multitasking limitations, multiple theoretical models implicate striatal-cortical circuits as important neurophysiological substrates for the performance of single sensorimotor decisions (Caballero, Humphries, and Gurney 2018;Bornstein and Daw 2011;Joel, Niv, and Ruppin 2002) , the formation of stimulus-response representations in frontal-parietal cortex (Hélie, Ell, and Ashby 2015; Ashby, Turner, and Horvitz 2010) , and performance of both effortful and habitual sensorimotor tasks (Yin and Knowlton 2006;Graybiel and Grafton 2015;Jahanshahi et al 2015) . This suggests that a complete account of cognitive limitations and their practice-induced attenuation also requires interrogation into the contribution of striatal-cortical circuits.…”

The Origins of Self

“…Recursion is not, as Wilhelm von Humboldt (1836Humboldt ( [1999, 91) says (and Chomsky is fond of quoting), 'infinite employment of finite means', 2 it is constrained by the capacities of the human brain, which are not as amazing or unusual as we often pretend. Caballero et al (2018) raise an important issue about infinitely recursive iteration: cognition is about decision points. At some time in the process, the formulation of an idea must result in a formed idea; and this cannot happen without a stop-marker on the iterative recursion formulating the idea.…”