Evidence accumulation

A prevailing theory in goal-directed decision-making is that the brain accumulates evidence over time to make perceptual decisions. However, even after two decades of studies on evidence accumulation, it is still unclear how neuronal populations cooperate to dynamically represent decision variables. This is because of a lack of tools for gaining experimental control over variables of interest to test their relationship to behavior. To address this gap, we develop a state-space control framework to causally interact with decision-related latent variables. To expose decision variables to target

Global excitatory activity patterns across the dorsal cortex are reorganized when mice perform perceptual decision-making tasks that involve different underlying computations and vary in complexity. However, the circuit mechanisms enabling such large-scale activity reorganization remain unknown. An interesting possibility is that they depend on neuromodulatory input to the cortex. In particular, cholinergic neurons in the basal forebrain project widely across cortical areas while exhibiting topographical and functional heterogeneity. They are therefore well equipped to serve as an orchestrator

Animals readily make value-based decisions between discrete and static items, with decades of work elucidating neural circuits involved in such choices (Rangel et al., 2015). Much less is known about naturalistic decision-making contexts such as goal pursuit (e.g., hunting). Dynamic choices require determining the value of blending different goal-pursuit strategies, switching goals, and continuously monitoring the actions and goals most valuable (Yoo et al., 2021). Despite its prevalence, there is a lack of methods to identify continuous decision processes and thus a dearth of understanding th

…Mice first accumulate evidence to determine the predominant color of a random

Behavioural tasks requiring context-dependent selection and accumulation of noisy sensory evidence are a powerful tool to study flexible decision-making (Mante et al., 2013), and recent work revealed a surprisingly degree of variability in the underlying neural mechanisms across individual animals (Pagan et al., 2022). Here we study how this individual variability develops during learning in rats and recurrent neural networks (RNNs). First, we show that the number of hidden units in RNNs plays a crucial role in the resulting amount of variability across networks initialized with different rand

…into working memory and accumulating evidence before making a decision. How the DMS produces these behaviors is less understood than the DLS because, unlike habitual motor tasks used to study the DLS, tasks used to study the DMS require more management of internal mental states, an inherently unobservable process. In this work, we build a compu

Latent dynamical system (LDS) models have been widely used to characterize the dynamics of high-dimensional neural population activity. However, these models typically ignore the fact that the brain contains multiple cell types. This limits their ability to capture the functional roles of distinct cell classes, and thus to capture the effects of cell-specific optogenetic perturbations on neural activity and behavior. To address this gap, we introduce the "cell-type dynamical systems" (CTDS) model, which extends latent linear dynamical systems to contain distinct latent variables for each cell

…an EEG signature of motor-independent evidence accumulation (O'Connell, Dockree, & Kelly 2012), in an fMRI study. It involved a mental counting task assessing vi

Spatial summation in thermosensation refers to the integration of multiple sensory signals, resulting in the perception of a unique sensation. The relationship between stimulus size and perceived intensity is sub-additive, suggesting an influence of lateral inhibition, a process in which adjacent neurons inhibit each other. We investigated the role of spatial summation and lateral inhibition in thermosensation using computational modeling. We devised a perceptual decision-making task where thermal stimuli were applied to 16 participants' forearms, with temperatures increasing or decreasing fro

Decision models involving protracted temporal integration of sensory information are known to provide excellent fits to decision behaviour. However, despite the computational advantage in principle, several studies have suggested a limited role for extended integration in practice, variously finding that it is subjected to low bounds, applied over a short timeframe, or plausibly replaced by non-integration strategies such as extrema detection. Here, we probed the role of extended integration in a noiseless but difficult contrast comparison task with response choices made after viewing a long 1

…increased emphasis on gaze-driven evidence accumulation models, existing decision models underestimate or neglect the significance of mental imagery in decision-making. We aim to explore how gaze behavior and visual imagery interact, simulating mental states associated with potential outcomes during deliberation. Previous research has suggested the 'looking-at-nothing' phenomenon, a behavi

…(EEG), continuous bounded accumulation model, which, through adjustments to sensory criteria set on the evidence to be accumulated

…the neural mechanisms underpinning evidence accumulation in tasks where information is continuously available, but less is known about how humans make decisions based on temporally separate samples. Here, we ran two electroencephalography (EEG) experiments using a modified version of the standard Random Dot Kinematogram (RDK). In our tasks (N = 22, N = 21), two pulses of evidence were presented separated by "gaps" of vary

…due to elaborated post-decisional evidence processing. Here, we investigated the time-course of evidence processing under different speed pressures using time-resolved analysis of electroencephalographic (EEG) data. Forty participants performed a motion discrimination task under short and long response deadlines. Following the initial response, participants

During perceptual decision-making, neural circuits can accumulate decision evidence and maintain the choice in short-term memory until the motor response. Previous modelling work has proposed that recurrent circuit dynamics underlie these two processes and that N-methyl-D-aspartate receptors (NMDARs) are necessary for proper network function. Electrophysiological evidence indicates that circuits in the frontal cortex may carry out these computations but the role of NMDAR has not been systematically tested. We developed an auditory two-alternative delayed-choice (2ADC) task for head-fixed mice

Beliefs and expectations, also referred to as priors, shape how we perceive our environment. In a complex and ever-changing world, prior beliefs need to be flexibly and continuously integrated into sensory decision processes to guide adaptive behavior. Despite the advances in understanding the integration of priors in visual decisions at the computational and algorithmic levels, its neural mechanisms remain unclear. The goal of this study was to understand the neural dynamics involved in belief formation and updating. Here, we used high-density electroencephalogram recordings to constrain and

…across time in a process called evidence accumulation. This has been widely studied on various animals; however, in flies, the emphasis has primarily been centered on the subcellular integration mechanisms, overlooking the behavioral impacts and whole-brain neuronal dynamics.Here, we

The idea that evidence accumulation is the only crucial factor for decision making has been recently challenged. Even during simple visual tasks, both impulsivity/prudence and working memory (WM) may also play a crucial role in its dynamics. We wanted to investigate how a wide range of sequences of visual evidence and the presence of a time gap (located in between such sequences) would interact with participants’ impulsivity (measured with a personality scale) to bias WM and/or the prioritization of speed over accuracy. 34 human adults (65% females, aged 18-48) performed a version of the token

…benchmarks for how specific forms of evidence accumulation and decision rules can optimally balance quantities like decision speed and accuracy. These theories have recently been expanded to include adaptive components that are necessary for effective decision making in dynamic environments. However, these extensions remain incomplete, because they have focused primarily on how an unconstrained agent manages single, independent decisions [1]. In contrast, real-wo

Aggression, leading to the formation of social hierarchy, has an evolutionary role in reducing conflict and facilitating the allocation of limited resources. Previous studies in mice have identified the regions involved in the neural circuitry of aggression, yet the mechanisms leading to the emergence of aggressive behavior remain to be poorly understood. To analyze such mechanisms, we used a mouse chronic social conflict paradigm where multiple aggressive phenotypes were formed, for which we obtained behavioral readouts (134 mice) and whole-brain snapshots of neuronal activity (c-Fos; 54 mice

…We developed a novel GO/NO-GO evidence accumulation task that requires fast responses to hidden-state changes under varying uncertainty levels. The goal is to detect transitions between `safe' and `unsafe' states. In the

…trigger decisions once sufficient evidence is acquired for a choice. Models often describe single accumulation-to-bound processes, but organisms often decide in groups or accumulate multiple information streams. A better understanding of naturalistic decision making thus requires probing the neural computations and behaviors of evidence accumulation processes involving the integration of multiple information streams. Normative models of information-sharing in multi-ag

…making it tempting to fit evidence accumulation models as the go- and stop-racers. Prior research shows, however, that behavioral stop-signal evidence accumulation models have unrecoverable parameters. In this study, we explored whether neurocognitive models of response inhibition are recoverable from neural and behavioral stop-signal data, as it has been suggested

The brain makes decisions by accumulating evidence until there is enough to stop and choose. Neural mechanisms of evidence accumulation are well established in association cortex, but the site and mechanism of termination is unknown. Here, we elucidate a mechanism for termination by neurons in the primate superior colliculus. We recorded simultaneously from neurons in lateral intraparietal cortex (LIP) and the superior colliculus (SC) while monkeys made perceptual decisions, reported by eye-movements. Single-trial analyses revealed distinct dynamics: LIP tracked the accumulation of evidence on