Reward positivity affects temporal interval production in a continuous timing task.

The neural circuits of reward processing and interval timing (including the perception and production of temporal intervals) are functionally intertwined, suggesting that it might be possible for momentary reward processing to influence subsequent timing behavior. Previous animal and human studies have mainly focused on the effect of reward on interval perception, whereas its impact on interval production is less clear. In this study, we examined whether feedback, as an example of performance-contingent reward, biases interval production.

The representation of priors and decisions in the human parietal cortex.

Animals actively sample their environment through orienting actions such as saccadic eye movements. Saccadic targets are selected based both on sensory evidence immediately preceding the saccade, and a "salience map" or prior built-up over multiple saccades. In the primate cortex, the selection of each individual saccade depends on competition between target-selective cells that ramp up their firing rate to saccade release.

A cognitive map for value-guided choice in ventromedial prefrontal cortex.

The prefrontal cortex is crucial for economic decision-making and representing the value of options. However, how such representations facilitate flexible decisions remains unknown. We reframe economic decision-making in prefrontal cortex in line with representations of structure within the medial temporal lobe because such cognitive map representations are known to facilitate flexible behaviour.

Quantifying decision-making in dynamic, continuously evolving environments.

During perceptual decision-making tasks, centroparietal electroencephalographic (EEG) potentials report an evidence accumulation-to-bound process that is time locked to trial onset. However, decisions in real-world environments are rarely confined to discrete trials; they instead unfold continuously, with accumulation of time-varying evidence being recency-weighted towards its immediate past. The neural mechanisms supporting recency-weighted continuous decision-making remain unclear.

The neural correlates of continuous feedback processing.

Feedback processing is commonly studied by analyzing the brain's response to discrete rather than continuous events. Such studies have led to the hypothesis that rapid phasic midbrain dopaminergic activity tracks reward prediction errors (RPEs), the effects of which are measurable at the scalp via electroencephalography (EEG). Although studies using continuous feedback are sparse, recent animal work suggests that moment-to-moment changes in reward are tracked by slowly ramping midbrain dopaminergic activity.

Temporal scaling of human scalp-recorded potentials.

Much of human behavior is governed by common processes that unfold over varying timescales. Standard event-related potential analysis assumes fixed-duration responses relative to experimental events. However, recent single-unit recordings in animals have revealed neural activity scales to span different durations during behaviors demanding flexible timing.

Novelty, uncertainty, and the looming horizon.

Novelty and uncertainty are powerful drivers of exploration that are often conflated. In this issue of Neuron, Cockburn and colleagues dissociate the two and report a key interaction: close to task termination, novel options appear much more attractive relative to uncertain options.

Task-level value affects trial-level reward processing.

Despite disagreement about how anterior cingulate cortex (ACC) supports decision making, a recent hypothesis suggests that activity in this region is best understood in the context of a task or series of tasks. One important task-level variable is average reward because it is both a known driver of effortful behaviour and an important determiner of the tasks in which we choose to engage. Here we asked how average task value affects reward-related ACC activity.

Behavioural and neural indices of perceptual decision-making in autistic children during visual motion tasks.

Many studies report atypical responses to sensory information in autistic individuals, yet it is not clear which stages of processing are affected, with little consideration given to decision-making processes. We combined diffusion modelling with high-density EEG to identify which processing stages differ between 50 autistic and 50 typically developing children aged 6-14 years during two visual motion tasks. Our pre-registered hypotheses were that autistic children would show task-dependent differences in sensory evidence accumulation, alongside a more cautious decision-making style and longer non-decision time across tasks.

Visual Motion and Decision-Making in Dyslexia: Reduced Accumulation of Sensory Evidence and Related Neural Dynamics.

Children with and without dyslexia differ in their behavioral responses to visual information, particularly when required to pool dynamic signals over space and time. Importantly, multiple processes contribute to behavioral responses. Here we investigated which processing stages are affected in children with dyslexia when performing visual motion processing tasks, by combining two methods that are sensitive to the dynamic processes leading to responses.

Adapting non-invasive human recordings along multiple task-axes shows unfolding of spontaneous and over-trained choice.

Choices rely on a transformation of sensory inputs into motor responses. Using invasive single neuron recordings, the evolution of a choice process has been tracked by projecting population neural responses into state spaces. Here, we develop an approach that allows us to recover similar trajectories on a millisecond timescale in non-invasive human recordings.

Frontal circuit specialisations for decision making.

There is widespread consensus that distributed circuits across prefrontal and anterior cingulate cortex (PFC/ACC) are critical for reward-based decision making. The circuit specialisations of these areas in primates were likely shaped by their foraging niche, in which decision making is typically sequential, attention-guided and temporally extended. Here, I argue that in humans and other primates, PFC/ACC circuits are functionally specialised in two ways.

A Diversity of Intrinsic Timescales Underlie Neural Computations.

Neural processing occurs across a range of temporal scales. To facilitate this, the brain uses fast-changing representations reflecting momentary sensory input alongside more temporally extended representations, which integrate across both short and long temporal windows. The temporal flexibility of these representations allows animals to behave adaptively.

A circuit mechanism for decision-making biases and NMDA receptor hypofunction.

Decision-making biases can be features of normal behaviour, or deficits underlying neuropsychiatric symptoms. We used behavioural psychophysics, spiking-circuit modelling and pharmacological manipulations to explore decision-making biases during evidence integration. Monkeys showed a pro-variance bias (PVB): a preference to choose options with more variable evidence.

Visual fixation patterns during economic choice reflect covert valuation processes that emerge with learning.

Visual fixations play a vital role in decision making. Recent studies have demonstrated that the longer subjects fixate an option, the more likely they are to choose it. However, the role of evaluating stimuli covertly (i.

Triple dissociation of attention and decision computations across prefrontal cortex.

Naturalistic decision-making typically involves sequential deployment of attention to choice alternatives to gather information before a decision is made. Attention filters how information enters decision circuits, thus implying that attentional control may shape how decision computations unfold. We recorded neuronal activity from three subregions of the prefrontal cortex (PFC) while monkeys performed an attention-guided decision-making task.

Neuroscience: Intracranial Recordings of Value.

The role of orbitofrontal cortex in value-based choice is well-established from animal research, but there are challenges in relating neurophysiological recordings from animals to equivalent data from humans: a new study bridges this gap.

Reconciling persistent and dynamic hypotheses of working memory coding in prefrontal cortex.

Competing accounts propose that working memory (WM) is subserved either by persistent activity in single neurons or by dynamic (time-varying) activity across a neural population. Here, we compare these hypotheses across four regions of prefrontal cortex (PFC) in an oculomotor-delayed-response task, where an intervening cue indicated the reward available for a correct saccade. WM representations were strongest in ventrolateral PFC neurons with higher intrinsic temporal stability (time-constant).

Spontaneous cortical activity transiently organises into frequency specific phase-coupling networks.

Frequency-specific oscillations and phase-coupling of neuronal populations are essential mechanisms for the coordination of activity between brain areas during cognitive tasks. Therefore, the ongoing activity ascribed to the different functional brain networks should also be able to reorganise and coordinate via similar mechanisms. We develop a novel method for identifying large-scale phase-coupled network dynamics and show that resting networks in magnetoencephalography are well characterised by visits to short-lived transient brain states, with spatially distinct patterns of oscillatory power and coherence in specific frequency bands.

Differential Valuation and Learning From Social and Nonsocial Cues in Borderline Personality Disorder.

Background: Volatile interpersonal relationships are a core feature of borderline personality disorder (BPD) and lead to devastating disruption of patients' personal and professional lives. Quantitative models of social decision making and learning hold promise for defining the underlying mechanisms of this problem. In this study, we tested BPD and control subject weighting of social versus nonsocial information and their learning about choices under stable and volatile conditions.

Correction: Approach-Induced Biases in Human Information Sampling.

[This corrects the article DOI: 10.1371/journal.pbio.

A distributed, hierarchical and recurrent framework for reward-based choice.

Many accounts of reward-based choice argue for distinct component processes that are serial and functionally localized. In this Opinion article, we argue for an alternative viewpoint, in which choices emerge from repeated computations that are distributed across many brain regions. We emphasize how several features of neuroanatomy may support the implementation of choice, including mutual inhibition in recurrent neural networks and the hierarchical organization of timescales for information processing across the cortex.

Approach-Induced Biases in Human Information Sampling.

Information sampling is often biased towards seeking evidence that confirms one's prior beliefs. Despite such biases being a pervasive feature of human behavior, their underlying causes remain unclear. Many accounts of these biases appeal to limitations of human hypothesis testing and cognition, de facto evoking notions of bounded rationality, but neglect more basic aspects of behavioral control.

Autocorrelation structure at rest predicts value correlates of single neurons during reward-guided choice.

Correlates of value are routinely observed in the prefrontal cortex (PFC) during reward-guided decision making. In previous work (Hunt et al., 2015), we argued that PFC correlates of chosen value are a consequence of varying rates of a dynamical evidence accumulation process.