Altered Associations Between Task Performance and Dorsolateral Prefrontal Cortex Activation During Cognitive Control in Schizophrenia.

BACKGROUND: Dysfunctional cognitive control processes are now well understood to be core features of schizophrenia (SZ). A body of work suggests that the dorsolateral prefrontal cortex (DLPFC) plays a critical role in explaining cognitive control disruptions in SZ. Here, we examined relationships between DLPFC activation and drift rate (DR), a model-based performance measure that combines reaction time and accuracy, in people with SZ and healthy control (HC) participants. METHODS: One hundred fifty-one people with recent-onset SZ spectrum disorders and 118 HC participants performed the AX-Continuous Performance Task during functional magnetic resonance imaging scanning. Proactive cognitive control-associated activation was extracted from left and right DLPFC regions of interest. Individual behavior was fit using a drift diffusion model, allowing DR to vary between task conditions. RESULTS: Behaviorally, people with SZ showed significantly lower DRs than HC participants, particularly during high proactive control trial types ("B" trials). Recapitulating previous findings, the SZ group also demonstrated reduced cognitive control-associated DLPFC activation compared with HC participants. Furthermore, significant group differences were also observed in the relationship between left and right DLPFC activation with DR, such that positive relationships between DR and activation were found in HC participants but not in people with SZ. CONCLUSIONS: These results suggest that DLPFC activation is less associated with cognitive control-related behavioral performance enhancements in SZ. Potential mechanisms and implications are discussed.

Altered Associations Between Motivated Performance and Frontostriatal Functional Connectivity During Reward Anticipation in Schizophrenia.

BACKGROUND AND HYPOTHESIS: The neuronal mechanisms that underlie deficits in effort cost computation in schizophrenia (SZ) are poorly understood. Given the role of frontostriatal circuits in valence-oriented motivation, we hypothesized that these circuits are either dysfunctional in SZ or do not appropriately predict behavior in SZ when task conditions are difficult and good performance is rewarded. STUDY DESIGN: A total of 52 people with recent onset SZ-spectrum disorders and 48 healthy controls (HCs) performed a 3T fMRI task with 2 valence conditions (rewarded vs neutral) and 2 difficulty conditions. Frontostriatal connectivity was extracted during the cue (anticipatory) phase. Individual behavior was fit using a drift-diffusion model, allowing the performance parameter, drift rate (DR), to vary between task conditions. Three models were examined: A group × condition model of DR, a group × condition model of connectivity, and a regression model of connectivity predicting DR depending on group and condition. STUDY RESULTS: DRs showed the expected positive correlation with accuracy and a negative association with reaction time. The SZ group showed a deficit in DR but did not differ in overall connectivity or show a valence-specific deficit in connectivity. Significant group × valence × difficulty interactions, however, were observed on the relationship between right dorsolateral prefrontal (DLPFC)-striatal connectivity and DR (DLPFC-Caudate: F = 10.92, PFDR = .004; DLPFC-Putamen: F = 5.14, PFDR = .048) driven by more positive relationships between DR and connectivity during cues for the difficult-rewarded condition in HCs compared to SZ. CONCLUSIONS: These findings suggest that frontostriatal connectivity is less predictive of performance in SZ when task difficulty is increased and a reward incentive is applied.

Attentional Guidance and Match Decisions Rely on Different Template Information During Visual Search.

When searching for a target object, we engage in a continuous "look-identify" cycle in which we use known features of the target to guide attention toward potential targets and then to decide whether the selected object is indeed the target. Target information in memory (the target template or attentional template) is typically characterized as having a single, fixed source. However, debate has recently emerged over whether flexibility in the target template is relational or optimal. On the basis of evidence from two experiments using college students (Ns = 30 and 70, respectively), we propose that initial guidance of attention uses a coarse relational code, but subsequent decisions use an optimal code. Our results offer a novel perspective that the precision of template information differs when guiding sensory selection and when making identity decisions during visual search.

Change point detection with multiple alternatives reveals parallel evaluation of the same stream of evidence along distinct timescales.

In order to behave appropriately in a rapidly changing world, individuals must be able to detect when changes occur in that environment. However, at any given moment, there are a multitude of potential changes of behavioral significance that could occur. Here we investigate how knowledge about the space of possible changes affects human change point detection. We used a stochastic auditory change point detection task that allowed model-free and model-based characterization of the decision process people employ. We found that subjects can simultaneously apply distinct timescales of evidence evaluation to the same stream of evidence when there are multiple types of changes possible. Informative cues that specified the nature of the change led to improved accuracy for change point detection through mechanisms involving both the timescales of evidence evaluation and adjustments of decision bounds. These results establish three important capacities of information processing for decision making that any proposed neural mechanism of evidence evaluation must be able to support: the ability to simultaneously employ multiple timescales of evidence evaluation, the ability to rapidly adjust those timescales, and the ability to modify the amount of information required to make a decision in the context of flexible timescales.

Timescales of Evidence Evaluation for Decision Making and Associated Confidence Judgments Are Adapted to Task Demands.

Decision making often involves choosing actions based on relevant evidence. This can benefit from focussing evidence evaluation on the timescale of greatest relevance based on the situation. Here, we use an auditory change detection task to determine how people adjust their timescale of evidence evaluation depending on task demands for detecting changes in their environment and assessing their internal confidence in those decisions. We confirm previous results that people adopt shorter timescales of evidence evaluation for detecting changes in contexts with shorter signal durations, while bolstering those results with model-free analyses not previously used and extending the results to the auditory domain. We also extend these results to show that in contexts with shorter signal durations, people also adopt correspondingly shorter timescales of evidence evaluation for assessing confidence in their decision about detecting a change. These results provide important insights into adaptability and flexible control of evidence evaluation for decision making.

Flexibility of Timescales of Evidence Evaluation for Decision Making.

To understand the neural mechanisms that support decision making, it is critical to characterize the timescale of evidence evaluation. Recent work has shown that subjects can adaptively adjust the timescale of evidence evaluation across blocks of trials depending on context [1]. However, it's currently unknown if adjustments to evidence evaluation occur online during deliberations based on a single stream of evidence. To examine this question, we employed a change-detection task in which subjects report their level of confidence in judging whether there has been a change in a stochastic auditory stimulus. Using a combination of psychophysical reverse correlation analyses and single-trial behavioral modeling, we compared the time period over which sensory information has leverage on detection report choices versus confidence. We demonstrate that the length of this period differs on separate sets of trials based on what's being reported. Surprisingly, confidence judgments on trials with no detection report are influenced by evidence occurring earlier than the time period of influence for detection reports. Our findings call into question models of decision formation involving static parameters that yield a singular timescale of evidence evaluation and instead suggest that the brain represents and utilizes multiple timescales of evidence evaluation during deliberation.

Causal contribution and dynamical encoding in the striatum during evidence accumulation.

A broad range of decision-making processes involve gradual accumulation of evidence over time, but the neural circuits responsible for this computation are not yet established. Recent data indicate that cortical regions that are prominently associated with accumulating evidence, such as the posterior parietal cortex and the frontal orienting fields, may not be directly involved in this computation. Which, then, are the regions involved? Regions that are directly involved in evidence accumulation should directly influence the accumulation-based decision-making behavior, have a graded neural encoding of accumulated evidence and contribute throughout the accumulation process. Here, we investigated the role of the anterior dorsal striatum (ADS) in a rodent auditory evidence accumulation task using a combination of behavioral, pharmacological, optogenetic, electrophysiological and computational approaches. We find that the ADS is the first brain region known to satisfy the three criteria. Thus, the ADS may be the first identified node in the network responsible for evidence accumulation.

Characterization of decision commitment rule alterations during an auditory change detection task.

A critical component of decision making is determining when to commit to a choice. This involves stopping rules that specify the requirements for decision commitment. Flexibility of decision stopping rules provides an important means of control over decision-making processes. In many situations, these stopping rules establish a balance between premature decisions and late decisions. In this study we use a novel change detection paradigm to examine how subjects control this balance when invoking different decision stopping rules. The task design allows us to estimate the temporal weighting of sensory information for the decisions, and we find that different stopping rules did not result in systematic differences in that weighting. We also find bidirectional post-error alterations of decision strategy that depend on the type of error and effectively reduce the probability of making consecutive mistakes of the same type. This is a generalization to change detection tasks of the widespread observation of unidirectional post-error slowing in forced-choice tasks. On the basis of these results, we suggest change detection tasks as a promising paradigm to study the neural mechanisms that support flexible control of decision rules.NEW & NOTEWORTHY Flexible decision stopping rules confer control over decision processes. Using an auditory change detection task, we found that alterations of decision stopping rules did not result in systematic changes in the temporal weighting of sensory information. We also found that post-error alterations of decision stopping rules depended on the type of mistake subjects make. These results provide guidance for understanding the neural mechanisms that control decision stopping rules, one of the critical components of decision making and behavioral flexibility.

Fronto-parietal Cortical Circuits Encode Accumulated Evidence with a Diversity of Timescales.

Decision-making in dynamic environments often involves accumulation of evidence, in which new information is used to update beliefs and select future actions. Using in vivo cellular resolution imaging in voluntarily head-restrained rats, we examined the responses of neurons in frontal and parietal cortices during a pulse-based accumulation of evidence task. Neurons exhibited activity that predicted the animal's upcoming choice, previous choice, and graded responses that reflected the strength of the accumulated evidence. The pulsatile nature of the stimuli enabled characterization of the responses of neurons to a single quantum (pulse) of evidence. Across the population, individual neurons displayed extensive heterogeneity in the dynamics of responses to pulses. The diversity of responses was sufficiently rich to form a temporal basis for accumulated evidence estimated from a latent variable model. These results suggest that heterogeneous, often transient sensory responses distributed across the fronto-parietal cortex may support working memory on behavioral timescales. VIDEO ABSTRACT.

Perceptual Decision Making in Rodents, Monkeys, and Humans.

Perceptual decision making is the process by which animals detect, discriminate, and categorize information from the senses. Over the past two decades, understanding how perceptual decisions are made has become a central theme in the neurosciences. Exceptional progress has been made by recording from single neurons in the cortex of the macaque monkey and using computational models from mathematical psychology to relate these neural data to behavior. More recently, however, the range of available techniques and paradigms has dramatically broadened, and researchers have begun to harness new approaches to explore how rodents and humans make perceptual decisions. The results have illustrated some striking convergences with findings from the monkey, but also raised new questions and provided new theoretical insights. In this review, we summarize key findings, and highlight open challenges, for understanding perceptual decision making in rodents, monkeys, and humans.

Neural underpinnings of the evidence accumulator.

Gradual accumulation of evidence favoring one or another choice is considered a core component of many different types of decisions, and has been the subject of many neurophysiological studies in non-human primates. But its neural circuit mechanisms remain mysterious. Investigating it in rodents has recently become possible, facilitating perturbation experiments to delineate the relevant causal circuit, as well as the application of other tools more readily available in rodents. In addition, advances in stimulus design and analysis have aided studying the relevant neural encoding. In complement to ongoing non-human primate studies, these newly available model systems and tools place the field at an exciting time that suggests that the dynamical circuit mechanisms underlying accumulation of evidence could soon be revealed.

Distinct effects of prefrontal and parietal cortex inactivations on an accumulation of evidence task in the rat.

Numerous brain regions have been shown to have neural correlates of gradually accumulating evidence for decision-making, but the causal roles of these regions in decisions driven by accumulation of evidence have yet to be determined. Here, in rats performing an auditory evidence accumulation task, we inactivated the frontal orienting fields (FOF) and posterior parietal cortex (PPC), two rat cortical regions that have neural correlates of accumulating evidence and that have been proposed as central to decision-making. We used a detailed model of the decision process to analyze the effect of inactivations. Inactivation of the FOF induced substantial performance impairments that were quantitatively best described as an impairment in the output pathway of an evidence accumulator with a long integration time constant (>240 ms). In contrast, we found a minimal role for PPC in decisions guided by accumulating auditory evidence, even while finding a strong role for PPC in internally-guided decisions.

Distinct relationships of parietal and prefrontal cortices to evidence accumulation.

Gradual accumulation of evidence is thought to be fundamental for decision-making, and its neural correlates have been found in several brain regions. Here we develop a generalizable method to measure tuning curves that specify the relationship between neural responses and mentally accumulated evidence, and apply it to distinguish the encoding of decision variables in posterior parietal cortex and prefrontal cortex (frontal orienting fields, FOF). We recorded the firing rates of neurons in posterior parietal cortex and FOF from rats performing a perceptual decision-making task. Classical analyses uncovered correlates of accumulating evidence, similar to previous observations in primates and also similar across the two regions. However, tuning curve assays revealed that while the posterior parietal cortex encodes a graded value of the accumulating evidence, the FOF has a more categorical encoding that indicates, throughout the trial, the decision provisionally favoured by the evidence accumulated so far. Contrary to current views, this suggests that premotor activity in the frontal cortex does not have a role in the accumulation process, but instead has a more categorical function, such as transforming accumulated evidence into a discrete choice. To probe causally the role of FOF activity, we optogenetically silenced it during different time points of the trial. Consistent with a role in committing to a categorical choice at the end of the evidence accumulation process, but not consistent with a role during the accumulation itself, a behavioural effect was observed only when FOF silencing occurred at the end of the perceptual stimulus. Our results place important constraints on the circuit logic of brain regions involved in decision-making.

Elapsed decision time affects the weighting of prior probability in a perceptual decision task.

Decisions are often based on a combination of new evidence with prior knowledge of the probable best choice. Optimal combination requires knowledge about the reliability of evidence, but in many realistic situations, this is unknown. Here we propose and test a novel theory: the brain exploits elapsed time during decision formation to combine sensory evidence with prior probability. Elapsed time is useful because (1) decisions that linger tend to arise from less reliable evidence, and (2) the expected accuracy at a given decision time depends on the reliability of the evidence gathered up to that point. These regularities allow the brain to combine prior information with sensory evidence by weighting the latter in accordance with reliability. To test this theory, we manipulated the prior probability of the rewarded choice while subjects performed a reaction-time discrimination of motion direction using a range of stimulus reliabilities that varied from trial to trial. The theory explains the effect of prior probability on choice and reaction time over a wide range of stimulus strengths. We found that prior probability was incorporated into the decision process as a dynamic bias signal that increases as a function of decision time. This bias signal depends on the speed-accuracy setting of human subjects, and it is reflected in the firing rates of neurons in the lateral intraparietal area (LIP) of rhesus monkeys performing this task.

Bounded integration in parietal cortex underlies decisions even when viewing duration is dictated by the environment.

Decisions about sensory stimuli are often based on an accumulation of evidence in time. When subjects control stimulus duration, the decision terminates when the accumulated evidence reaches a criterion level. Under many natural circumstances and in many laboratory settings, the environment, rather than the subject, controls the stimulus duration. In these settings, it is generally assumed that subjects commit to a choice at the end of the stimulus stream. Indeed, failure to benefit from the full stream of information is interpreted as a sign of imperfect accumulation or memory leak. Contrary to these assumptions, we show that monkeys performing a direction discrimination task commit to a choice when the accumulated evidence reaches a threshold level (or bound), sometimes long before the end of stimulus. This bounded accumulation of evidence is reflected in the activity of neurons in the lateral intraparietal cortex. Thus, the readout of visual cortex embraces a termination rule to limit processing even when potentially useful information is available.

Macaque V1 activity during natural vision: effects of natural scenes and saccades.

In the present study, we examined the way that scene complexity and saccades combine to sculpt the temporal response patterns of V1 neurons. To bridge the gap between conventional and free viewing experiments, we compared responses of neurons across four paradigms ranging from less to more natural. An optimal bar stimulus was either flashed into a receptive field (RF) or brought into it via saccade and was embedded in either a natural scene or a uniform gray background. Responses to a flashed bar tended to be higher with a uniform rather than natural background. The most novel result reported here is that responses evoked by stimuli brought into the RF via saccades were enhanced compared with the same stimuli flashed during steady fixation. No single factor appears to account entirely for this surprising effect, but there were small contributions from fixational saccades and residual activity carried over from the previous fixation. We also found a negative correlation with cells' response "history" in that a larger response on one fixation was associated with a lower response on the subsequent fixation. The effects of the natural background and saccades exhibited a significant nonlinear interaction with the suppressive effects of the natural background less for stimuli entering RFs with saccades. Together, these results suggest that even responses to standard optimal stimuli are difficult to predict under conditions similar to natural vision, and further demonstrate the importance of naturalistic experimental paradigms to the study of visual processing in V1.

Seizures and reduced life span in mice lacking the potassium channel subunit Kv1.2, but hypoexcitability and enlarged Kv1 currents in auditory neurons.

Genes Kcna1 and Kcna2 code for the voltage-dependent potassium channel subunits Kv1.1 and Kv1.2, which are coexpressed in large axons and commonly present within the same tetramers. Both contribute to the low-voltage-activated potassium current I Kv1, which powerfully limits excitability and facilitates temporally precise transmission of information, e.g., in auditory neurons of the medial nucleus of the trapezoid body (MNTB). Kcna1-null mice lacking Kv1.1 exhibited seizure susceptibility and hyperexcitability in axons and MNTB neurons, which also had reduced I Kv1. To explore whether a lack of Kv1.2 would cause a similar phenotype, we created and characterized Kcna2-null mice (-/-). The -/- mice exhibited increased seizure susceptibility compared with their +/+ and +/- littermates, as early as P14. The mRNA for Kv1.1 and Kv1.2 increased strongly in +/+ brain stems between P7 and P14, suggesting the increasing importance of these subunits for limiting excitability. Surprisingly, MNTB neurons in brain stem slices from -/- and +/- mice were hypoexcitable despite their Kcna2 deficit, and voltage-clamped -/- MNTB neurons had enlarged I Kv1. This contrasts strikingly with the Kcna1-null MNTB phenotype. Toxin block experiments on MNTB neurons suggested Kv1.2 was present in every +/+ Kv1 channel, about 60% of +/- Kv1 channels, and no -/- Kv1 channels. Kv1 channels lacking Kv1.2 activated at abnormally negative potentials, which may explain why MNTB neurons with larger proportions of such channels had larger I Kv1. If channel voltage dependence is determined by how many Kv1.2 subunits each contains, neurons might be able to fine-tune their excitability by adjusting the Kv1.1:Kv1.2 balance rather than altering Kv1 channel density.

Microstimulation of macaque area LIP affects decision-making in a motion discrimination task.

A central goal of cognitive neuroscience is to elucidate the neural mechanisms underlying decision-making. Recent physiological studies suggest that neurons in association areas may be involved in this process. To test this, we measured the effects of electrical microstimulation in the lateral intraparietal area (LIP) while monkeys performed a reaction-time motion discrimination task with a saccadic response. In each experiment, we identified a cluster of LIP cells with overlapping response fields (RFs) and sustained activity during memory-guided saccades. Microstimulation of this cluster caused an increase in the proportion of choices toward the RF of the stimulated neurons. Choices toward the stimulated RF were faster with microstimulation, while choices in the opposite direction were slower. Microstimulation never directly evoked saccades, nor did it change reaction times in a simple saccade task. These results demonstrate that the discharge of LIP neurons is causally related to decision formation in the discrimination task.