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We ubiquitously seek information to make better decisions. Particularly in the modern age, when more information is available at our fingertips than ever, the information we choose to collect determines the quality of our decisions. Decision neuroscience has long adopted empirical approaches where the information available to decision-makers is fully controlled by the researchers, leaving neural mechanisms of information seeking less understood. Although information seeking has long been studied in the context of the exploration-exploitation trade-off, recent studies have widened the scope to investigate more overt information seeking in a way distinct from other decision processes. Insights gained from these studies, accumulated over the last few years, raise the possibility that information seeking is driven by the reward system signaling the subjective value of information. In this piece, we review findings from the recent studies, highlighting the conceptual and empirical relationships between distinct literatures, and discuss future research directions necessary to establish a more comprehensive understanding of how individuals seek information as a part of value-based decision-making. Information seeking is an integral, yet often overlooked aspect of value-based decision-making. Kobayashi and Kable review recent findings on the neural mechanisms of information seeking, highlighting an emerging hypothesis that the reward system represents the subjective value of information. [ABSTRACT FROM AUTHOR]

Adversarial collaboration has been championed as the gold standard for resolving scientific disputes but has gained relatively limited traction in neuroscience and allied fields. In this perspective, we argue that adversarial collaborative research has been stymied by an overly restrictive concern with the falsification of scientific theories. We advocate instead for a more expansive view that frames adversarial collaboration in terms of Bayesian belief updating, model comparison, and evidence accumulation. This framework broadens the scope of adversarial collaboration to accommodate a wide range of informative (but not necessarily definitive) studies while affording the requisite formal tools to guide experimental design and data analysis in the adversarial setting. We provide worked examples that demonstrate how these tools can be deployed to score theoretical models in terms of a common metric of evidence, thereby furnishing a means of tracking the amount of empirical support garnered by competing theories over time. Corcoran et al. present a Bayesian treatment of adversarial collaboration that operationalizes competing theoretical hypotheses as generative models. This approach enables the evaluation of alternative theories in terms of the evidential support their models garner across (potentially disparate) experimental settings. [ABSTRACT FROM AUTHOR]

Arousal and motivation interact to profoundly influence behavior. For example, experience tells us that we have some capacity to control our arousal when appropriately motivated, such as staying awake while driving a motor vehicle. However, little is known about how arousal and motivation jointly influence decision computations, including if and how animals, such as rodents, adapt their arousal state to their needs. Here, we developed and show results from an auditory, feature-based, sustained-attention task with intermittently shifting task utility. We use pupil size to estimate arousal across a wide range of states and apply tailored signal-detection theoretic, hazard function, and accumulation-to-bound modeling approaches in a large cohort of mice. We find that pupil-linked arousal and task utility both have major impacts on multiple aspects of task performance. Although substantial arousal fluctuations persist across utility conditions, mice partially stabilize their arousal near an intermediate and optimal level when task utility is high. Behavioral analyses show that multiple elements of behavior improve during high task utility and that arousal influences some, but not all, of them. Specifically, arousal influences the likelihood and timescale of sensory evidence accumulation but not the quantity of evidence accumulated per time step while attending. In sum, the results establish specific decision-computational signatures of arousal, motivation, and their interaction in attention. So doing, we provide an experimental and analysis framework for studying arousal self-regulation in neurotypical brains and in diseases such as attention-deficit/hyperactivity disorder. [Display omitted] • Mice increase their attentional intensity when task utility is high • Moderate arousal is optimal for sustained feature-based attention • Stabilizing arousal near optimality partly mediates the utility effect on attention • New modeling approaches strongly implicate stochastic signal neglect de Gee et al. monitor pupil-linked arousal and behavioral performance of mice in a feature-based, sustained-attention task with intermittently shifting task utility. A suite of new survival analysis and diffusion-based decision models show that arousal and utility have major, partially intersecting impacts on multiple aspects of choice behavior. [ABSTRACT FROM AUTHOR]

Cognitive models of interval timing can be formulated as an accumulation-to-bound process. 1–5 However, the physiological manifestation of such processes has not yet been identified. We used electroencephalography (EEG) to measure the neural responses of participants while they performed a temporal bisection task in which they were requested to categorize the duration of visual stimuli as short or long. 6 We found that the stimulus-offset and response-locked activity depends on both stimulus duration and the participants' decision. To relate this activity to the underlying cognitive processes, we used a drift-diffusion model. 7 The model includes a noisy accumulator starting with the stimulus onset and a decision threshold. According to the model, a stimulus duration will be categorized as "long" if the accumulator reaches the threshold during stimulus presentation. Otherwise, it will be categorized as "short." We found that at the offset of stimulus presentation, an EEG response marks the distance of the accumulator from the threshold. Therefore, this model offers an accurate description of our behavioral data as well as the EEG response using the same two model parameters. We then replicated this finding in an identical experiment conducted in the tactile domain. We also extended this finding to two different temporal ranges (sub- and supra-second). Taken together, the work provides a new way to study the cognitive processes underlying temporal decisions, using a combination of behavior, EEG, and modeling. [Display omitted] • Neural responses to stimuli offsets depend on their duration and participants' decision • These responses reflect subjective decisions even for identical durations • A computational model captures behavioral performance and predicts physiology • This finding generalizes to vision and touch as well as to different time ranges Ofir and Landau show that the EEG response to stimuli offsets in a temporal categorization task reflect their duration and participants' decisions. The responses match the distance to bound in a drift-diffusion model and generalize across sensory modalities and time ranges. The work provides a new way to study the cognitive processes underlying temporal decisions. [ABSTRACT FROM AUTHOR]

Neural network computations are usually assumed to emerge from patterns of fast electrical activity. Challenging this view, we show that a male fly's decision to persist in mating hinges on a biochemical computation that enables processing over minutes to hours. Each neuron in a recurrent network contains slightly different internal molecular estimates of mating progress. Protein kinase A (PKA) activity contrasts this internal measurement with input from the other neurons to represent accumulated evidence that the goal of the network has been achieved. When consensus is reached, PKA pushes the network toward a large-scale and synchronized burst of calcium influx that we call an eruption. Eruptions transform continuous deliberation within the network into an all-or-nothing output, after which the male will no longer sacrifice his life to continue mating. Here, biochemical activity, invisible to most large-scale recording techniques, is the key computational currency directing behavior and motivational state. • CaMKII measures time by delaying the Corazonin network eruption • Network-level evidence about time accumulates to threshold as cAMP/PKA signaling • A synchronized eruption reports suprathreshold evidence to downstream circuitry • Erupting networks can accumulate and evaluate information over seconds to hours Thornquist, Pitsch et al. describe the eruption: a neural network mechanism that transforms continuous and distributed inputs into discrete, consensus output. The eruption is a network-wide influx of calcium triggered by suprathreshold accumulation of cAMP/PKA signaling. The Corazonin eruption triggers motivational and behavioral changes once an evidence threshold is reached. [ABSTRACT FROM AUTHOR]

Neural activity throughout the cortex is correlated with perceptual decisions, but inactivation studies suggest that only a small number of areas are necessary for these behaviors. Here we show that the number of required cortical areas and their dynamics vary across related tasks with different cognitive computations. In a visually guided virtual T-maze task, bilateral inactivation of only a few dorsal cortical regions impaired performance. In contrast, in tasks requiring evidence accumulation and/or post-stimulus memory, performance was impaired by inactivation of widespread cortical areas with diverse patterns of behavioral deficits across areas and tasks. Wide-field imaging revealed widespread ramps of Ca2+ activity during the accumulation and visually guided tasks. Additionally, during accumulation, different regions had more diverse activity profiles, leading to reduced inter-area correlations. Using a modular recurrent neural network model trained to perform analogous tasks, we argue that differences in computational strategies alone could explain these findings. • Mice navigated in virtual reality while performing one of three related tasks • All dorsal cortex contributed to memory-dependent but not visually guided navigation • Higher task demands induced decorrelation of whole-cortex Ca2+ activity patterns • A modular RNN model suggested that differences in computations can explain results Pinto et al. show that more complex perceptual decisions engage more diverse and spatially distributed computations across the cortex than simpler decisions, even when sensory stimuli and motor output are held constant. [ABSTRACT FROM AUTHOR]

When a behavior repeatedly fails to achieve its goal, animals often give up and become passive, which can be strategic for preserving energy or regrouping between attempts. It is unknown how the brain identifies behavioral failures and mediates this behavioral-state switch. In larval zebrafish swimming in virtual reality, visual feedback can be withheld so that swim attempts fail to trigger expected visual flow. After tens of seconds of such motor futility, animals became passive for similar durations. Whole-brain calcium imaging revealed noradrenergic neurons that responded specifically to failed swim attempts and radial astrocytes whose calcium levels accumulated with increasing numbers of failed attempts. Using cell ablation and optogenetic or chemogenetic activation, we found that noradrenergic neurons progressively activated brainstem radial astrocytes, which then suppressed swimming. Thus, radial astrocytes perform a computation critical for behavior: they accumulate evidence that current actions are ineffective and consequently drive changes in behavioral states. • Zebrafish "give up" after swim attempts repeatedly fail to generate movement • Whole-brain imaging reveals noradrenergic neurons that encode swim failures • Radial astrocytes accumulate the noradrenergic failure signal and trigger passivity • Glia accumulate evidence that actions are futile, then switch behavioral state Whole-brain imaging in virtual-reality-immersed zebrafish reveals that failed swim attempts are detected by noradrenergic neurons, which drive glial cells that accumulate calcium until they trigger the suppression of further futile attempts. [ABSTRACT FROM AUTHOR]

Behaviors in which primates collect externally generated streams of sensory evidence, such as judgment of random dot motion direction, are explained by a bounded integration decision model. Does this model extend to rodents, and does it account for behavior in which the motor system generates evidence through interactions with the environment? In this study, rats palpated surfaces to identify the texture before them, showing marked trial-to-trial variability in the number of touches prior to expressing their choice. By high-speed video, we tracked whisker kinematic features and characterized how they encoded the contacted texture. Next, we quantified the evidence for each candidate texture transmitted on each touch by the specified whisker kinematic features. The instant of choice was well fit by modeling the brain as an integrator that gives the greatest weight to vibrissal evidence on first touch and exponentially less weight to evidence on successive touches; according to this model, the rat makes a decision when the accumulated quantity of evidence for one texture reaches a boundary. In summary, evidence appears to be accumulated within the brain until sufficient to support a well-grounded choice. These findings extend the framework of bounded sensory integration from primates to rodents and from passively received evidence to evidence that is actively generated by the sensorimotor system. • In a texture identification task, rats make variable numbers of touches per trial • Whisker kinematics—shape, motion, angle—form the texture-encoding evidence • Rats make a choice when primacy-weighted touch-by-touch evidence reaches a boundary • Akin to primate decision making, rats' choices are governed by bounded integration Faced with uncertain sensory inputs, primates integrate evidence over time to a decision boundary. Zuo and Diamond ask whether rats' employ bounded integration as they generate tactile evidence to identify texture. On each trial, rats accumulate vibrissal signals across touches; they make a decision when the integrated quantity reaches a boundary. [ABSTRACT FROM AUTHOR]

Recent work demonstrated that when a rat palpates a surface to identify its texture, signals generated by whisker kinematics are integrated by the brain, one touch at a time, until the accumulated evidence supports a well-grounded choice. The framework of decision making through bounded integration, previously attributed to primates, thus extends to rodents. In the present study, we ask whether vibrissal somatosensory cortex (vS1 and vS2) functions as the integrator of incoming evidence or, alternatively, as a relay of evidence to a downstream integrator. Rats carried out 1–6 touches per trial to discriminate among candidate textures. We calculated the evidence for each texture, per touch, carried by the firing rates of sets of neurons in vS1 and vS2. The quantity of information within vS1 and vS2 did not grow progressively; instead, the decision was accounted for by modeling a downstream integrator that accumulated packets of vS1 and vS2 texture information until the total quantity of evidence for one texture reached a boundary. In this behavioral task, vibrissal somatosensory cortex appears to act as a sensory relay. Bounded integration is likely to take place in regions targeted by somatosensory cortex. • Rats identify textures by carrying out 1–6 vibrissal touches per trial • Somatosensory cortical firing encodes vibrissal kinematics one touch at a time • Somatosensory cortex relays packets of texture evidence to a downstream integrator • Choice is triggered when the evidence across touches is integrated to a boundary When a rat palpates a surface to identify texture, vibrissal kinematic evidence is integrated by the brain one touch at a time. In this study, Zuo and Diamond find that vibrissal somatosensory cortex (vS1 and vS2) acts as a touch-by-touch distributor of evidence to a downstream integrator, where accumulation to a boundary triggers the decision. [ABSTRACT FROM AUTHOR]