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Contingency management (CM) is notably successful as a substance use disorder treatment and is most effective when targeting monosubstance use. Evidence suggests the effects of CM exceed predictions based on the value of the incentives delivered for monosubstance abstinence. In this systematic review, we examine common variations of CM interventions applied to a single substance to determine what factors may contribute to the larger effect. Our results show that CM produced moderate to large effect sizes when single drugs were targeted, with stable effects over time. We also found that interventions targeting cocaine abstinence overwhelmingly outperformed their predicted effect, whereas interventions for smoking cessation did not. Thus, incentives alone may not account for the success of CM, at least when applied to stimulant use disorder. We propose other potential sources of the effect including social reinforcement and the specific parameters of the reinforcement schedule., (© 2024 Society for the Experimental Analysis of Behavior (SEAB).)

Background and Hypothesis: Cognitive control deficits are prominent in individuals with psychotic psychopathology. Studies providing evidence for deficits in proactive control generally examine average performance and not variation across trials for individuals-potentially obscuring detection of essential contributors to cognitive control. Here, we leverage intertrial variability through drift-diffusion models (DDMs) aiming to identify key contributors to cognitive control deficits in psychosis., Study Design: People with psychosis (PwP; N = 122), their first-degree biological relatives (N = 78), and controls (N = 50) each completed 120 trials of the dot pattern expectancy (DPX) cognitive control task. We fit full hierarchical DDMs to response and reaction time (RT) data for individual trials and then used classification models to compare the DDM parameters with conventional measures of proactive and reactive control., Study Results: PwP demonstrated slower drift rates on proactive control trials suggesting less efficient use of cue information. Both PwP and relatives showed protracted nondecision times to infrequent trial sequences suggesting slowed perceptual processing. Classification analyses indicated that DDM parameters differentiated between the groups better than conventional measures and identified drift rates during proactive control, nondecision time during reactive control, and cue bias as most important. DDM parameters were associated with real-world functioning and schizotypal traits., Conclusions: Modeling of trial-level data revealed that slow evidence accumulation and longer preparatory periods are the strongest contributors to cognitive control deficits in psychotic psychopathology. This pattern of atypical responding during the DPX is consistent with shallow basins in attractor dynamic models that reflect difficulties in maintaining state representations, possibly mediated by excess neural excitation or poor connectivity., (Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center 2024.)

Behavior in naturalistic scenarios occurs in diverse environments. Adaptive strategies rely on multiple neural circuits and competing decision systems. However, past studies of rodent decision making have largely measured behavior in simple environments. To fill this gap, we recorded neural ensembles from hippocampus (HC), dorsolateral striatum (DLS), and dorsomedial prefrontal cortex (dmPFC) while rats foraged for food under changing rules in environments with varying topological complexity. Environmental complexity increased behavioral variability, lengthened HC nonlocal sequences, and modulated action caching. We found contrasting representations between DLS and HC, supporting a competition between decision systems. dmPFC activity was indicative of setting this balance, in particular predicting the extent of HC non-local coding. Inactivating mPFC impaired short-term behavioral adaptation and produced long-term deficits in balancing decision systems. Our findings reveal the dynamic nature of decision-making systems and how environmental complexity modulates their engagement with implications for behavior in naturalistic environments., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Nucleus accumbens dopamine signaling is an important neural substrate for decision-making. Dominant theories generally discretize and homogenize decision-making, when it is in fact a continuous process, with evaluation and re-evaluation components that extend beyond simple outcome prediction into consideration of past and future value. Extensive work has examined mesolimbic dopamine in the context of reward prediction error, but major gaps persist in our understanding of how dopamine regulates volitional and self-guided decision-making. Moreover, there is little consideration of individual differences in value processing that may shape how dopamine regulates decision-making. Here, using an economic foraging task in mice, we found that dopamine dynamics in the nucleus accumbens core reflected decision confidence during evaluation of decisions, as well as both past and future value during re-evaluation and change-of-mind. Optogenetic manipulations of mesolimbic dopamine release selectively altered evaluation and re-evaluation of decisions in mice whose dopamine dynamics and behavior reflected future value., Competing Interests: Competing interests Authors declare that they have no competing interests.

Across systems, higher-order interactions between components govern emergent dynamics. Here we tested whether contextual threat memory retrieval in mice relies on higher-order interactions between dorsal CA1 hippocampal neurons requiring learning-induced dendritic spine plasticity. We compared population-level Ca2 + transients as wild-type mice (with intact learning-induced spine plasticity and memory) and amnestic mice (TgCRND8 mice with high levels of amyloid-β and deficits in learning-induced spine plasticity and memory) were tested for memory. Using machine-learning classifiers with different capacities to use input data with complex interactions, our findings indicate complex neuronal interactions in the memory representation of wild-type, but not amnestic, mice. Moreover, a peptide that partially restored learning-induced spine plasticity also restored the statistical complexity of the memory representation and memory behavior in Tg mice. These findings provide a previously missing bridge between levels of analysis in memory research, linking receptors, spines, higher-order neuronal dynamics and behavior., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Dysfunction in learning and motivational systems are thought to contribute to addictive behaviours. Previous models have suggested that dopaminergic roles in learning and motivation could produce addictive behaviours through pharmacological manipulations that provide excess dopaminergic signalling towards these learning and motivational systems. Redish (2004) suggested a role based on dopaminergic signals of value prediction error, while (Zhang et al., 2009) suggested a role based on dopaminergic signals of motivation. However, both models present significant limitations. They do not explain the reduced sensitivity to drug-related costs/negative consequences, the increased impulsivity generally found in people with a substance use disorder, craving behaviours, and non-pharmacological dependence, all of which are key hallmarks of addictive behaviours. Here, we propose a novel mathematical definition of salience, that combines aspects of dopamine's role in both learning and motivation within the reinforcement learning framework. Using a single parameter regime, we simulated addictive behaviours that the (Zhang et al., 2009; Redish, 2004) models also produce but we went further in simulating the downweighting of drug-related negative prediction-errors, steeper delay discounting of drug rewards, craving behaviours and aspects of behavioural/non-pharmacological addictions. The current salience model builds on our recently proposed conceptual theory that salience modulates internal representation updating and may contribute to addictive behaviours by producing misaligned internal representations (Kalhan et al., 2021). Critically, our current mathematical model of salience argues that the seemingly disparate learning and motivational aspects of dopaminergic functioning may interact through a salience mechanism that modulates internal representation updating., Competing Interests: Declaration of competing interest None declared., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Rats demonstrate a preference for smaller, immediate rewards over larger, delayed ones, a phenomenon known as delay-discounting (DD). Behavior arises from the interaction of multiple decision-making systems, and the medial prefrontal cortex (mPFC) has been identified as a central component in the mediation between these decision systems. To investigate the role of the prelimbic (PL) subregion of mPFC on decision strategy interaction, we compared two cohorts of rats (ChR2-opsin-expressing 'Active' and opsin-absent 'Control') on a spatial delay-discounting task while delivering in-vivo light stimulation into PL at the choice point of select trials. By analyzing the overall delay-adjustment along with deliberative and procedural behavioral strategy markers, our study revealed differences in the decision strategies used between the active and control animals despite both groups showing similar valuations. Control animals developed the expected shift from deliberative to procedural decision strategy on this task (indicated by reaching delay-stability, particularly during late-session laps); however, active-virus animals repeatedly over-adjusted around their preferred delay throughout the entire session, suggesting a significant deficit in procedural decision-making on this task. Active animals showed a significant decrease in proportion of vicarious trial and error events (VTE, a behavior correlated with deliberative processes) on delay adjustment laps relative to control animals. This points to a more nuanced role for VTE, not just in executing deliberation, but in shifting from deliberative to procedural processes. This opto-induced change in VTE was especially pronounced for late-session adjustment laps. We found no other session-by-session or lap-by-lap effects, leaving a particular role for PL in the long-term development of procedural strategies on this task., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)

The world is overabundant with feature-rich information obscuring the latent causes of experience. How do people approximate the complexities of the external world with simplified internal representations that generalize to novel examples or situations? Theories suggest that internal representations could be determined by decision boundaries that discriminate between alternatives, or by distance measurements against prototypes and individual exemplars. Each provide advantages and drawbacks for generalization. We therefore developed theoretical models that leverage both discriminative and distance components to form internal representations via action-reward feedback. We then developed three latent-state learning tasks to test how humans use goal-oriented discrimination attention and prototypes/exemplar representations. The majority of participants attended to both goal-relevant discriminative features and the covariance of features within a prototype. A minority of participants relied only on the discriminative feature. Behaviour of all participants could be captured by parameterizing a model combining prototype representations with goal-oriented discriminative attention., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

In recent years, the field of neuroscience has gone through rapid experimental advances and a significant increase in the use of quantitative and computational methods. This growth has created a need for clearer analyses of the theory and modeling approaches used in the field. This issue is particularly complex in neuroscience because the field studies phenomena that cross a wide range of scales and often require consideration at varying degrees of abstraction, from precise biophysical interactions to the computations they implement. We argue that a pragmatic perspective of science, in which descriptive, mechanistic, and normative models and theories each play a distinct role in defining and bridging levels of abstraction, will facilitate neuroscientific practice. This analysis leads to methodological suggestions, including selecting a level of abstraction that is appropriate for a given problem, identifying transfer functions to connect models and data, and the use of models themselves as a form of experiment., (Copyright © 2023 the authors.)

Decision-making involves multiple cognitive processes requiring different aspects of information about the situation at hand. The rodent medial prefrontal cortex (mPFC) has been hypothesized to be central to these abilities. Functional studies have sought to link specific processes to specific anatomical subregions, but past studies of mPFC have yielded controversial results, leaving the precise nature of mPFC function unclear. To settle this debate, we recorded from the full dorso-ventral extent of mPFC in each of 8 rats, as they performed a complex economic decision task. These data revealed four distinct functional domains within mPFC that closely mirrored anatomically identified subregions, including novel evidence to divide prelimbic cortex into dorsal and ventral components. We found that dorsal aspects of mPFC (ACC, dPL) were more involved in processing information about active decisions, while ventral aspects (vPL, IL) were more engaged in motivational factors., Competing Interests: GD, AR No competing interests declared, (© 2023, Diehl and Redish.)

Sunk cost sensitivity describes escalating decision commitment with increased spent resources. On neuroeconomic foraging tasks, mice, rats, and humans show similar escalations from sunk costs while quitting an ongoing countdown to reward. In a new analysis taken across computationally parallel foraging tasks across species and laboratories, we find that these behaviors primarily occur on choices that are economically inconsistent with the subject's other choices, and that they reflect not only the time spent, but also the time remaining, suggesting that these are change-of-mind re-evaluation processes. Using a recently proposed change-of-mind drift-diffusion model, we find that the sunk cost sensitivity in this model arises from decision-processes that directly take into account the time spent (costs sunk). Applying these new insights to experimental data, we find that sensitivity to sunk costs during re-evaluation decisions depends on the information provided to the subject about the time spent and the time remaining., (© 2022. The Author(s).)

Etiopathogenic models for psychosis spectrum illnesses are converging on a number of key processes, such as the influence of specific genes on the synthesis of proteins important in synaptic functioning, alterations in how neurons respond to synaptic inputs and engage in synaptic pruning, and microcircuit dysfunction that leads to more global cortical information processing vulnerabilities. Disruptions in prefrontal operations then accumulate and propagate over time, interacting with environmental factors, developmental processes, and homeostatic mechanisms, eventually resulting in symptoms of psychosis and disability. However, there are 4 key features of psychosis spectrum illnesses that are of primary clinical relevance but have been difficult to assimilate into a single model and have thus far received little direct attention: 1) the bidirectionality of the causal influences for the emergence of psychosis, 2) the catastrophic clinical threshold seen in first episodes of psychosis and why it is irreversible in some individuals, 3) observed biotypes that are neurophysiologically distinct but clinically both convergent and divergent, and 4) a reconciliation of the role of striatal dopaminergic dysfunction with models of prefrontal cortical state instability. In this selective review, we briefly describe these 4 hallmark features and we argue that theoretically driven computational perspectives making use of both algorithmic and neurophysiologic models are needed to reduce this complexity and variability of psychosis spectrum illnesses in a principled manner., (Copyright © 2022. Published by Elsevier Inc.)

We propose a new conceptual framework (computational validity) for translation across species and populations based on the computational similarity between the information processing underlying parallel tasks. Translating between species depends not on the superficial similarity of the tasks presented, but rather on the computational similarity of the strategies and mechanisms that underlie those behaviours. Computational validity goes beyond construct validity by directly addressing questions of information processing. Computational validity interacts with circuit validity as computation depends on circuits, but similar computations could be accomplished by different circuits. Because different individuals may use different computations to accomplish a given task, computational validity suggests that behaviour should be understood through the subject's point of view; thus, behaviour should be characterized on an individual level rather than a task level. Tasks can constrain the computational algorithms available to a subject and the observed subtleties of that behaviour can provide information about the computations used by each individual. Computational validity has especially high relevance for the study of psychiatric disorders, given the new views of psychiatry as identifying and mediating information processing dysfunctions that may show high inter-individual variability, as well as for animal models investigating aspects of human psychiatric disorders. This article is part of the theme issue 'Systems neuroscience through the lens of evolutionary theory'.

Purpose of Review: Despite decades of research, knowledge of the mechanisms maintaining anorexia nervosa (AN) remains incomplete and clearly effective treatments elusive. Novel theoretical frameworks are needed to advance mechanistic and treatment research for this disorder. Here, we argue the utility of engaging a novel lens that differs from existing perspectives in psychiatry. Specifically, we argue the necessity of expanding beyond two historically common perspectives: (1) the descriptive perspective: the tendency to define mechanisms on the basis of surface characteristics and (2) the deficit perspective: the tendency to search for mechanisms associated with under-functioning of decision-making abilities and related circuity, rather than problems of over-functioning, in psychiatric disorders., Recent Findings: Computational psychiatry can provide a novel framework for understanding AN because this approach emphasizes the role of computational misalignments (rather than absolute deficits or excesses) between decision-making strategies and environmental demands as the key factors promoting psychiatric illnesses. Informed by this approach, we argue that AN can be understood as a disorder of excess goal pursuit, maintained by over-engagement, rather than disengagement, of executive functioning strategies and circuits. Emerging evidence suggests that this same computational imbalance may constitute an under-investigated phenotype presenting transdiagnostically across psychiatric disorders. A variety of computational models can be used to further elucidate excess goal pursuit in AN. Most traditional psychiatric treatments do not target excess goal pursuit or associated neurocognitive mechanisms. Thus, targeting at the level of computational dysfunction may provide a new avenue for enhancing treatment for AN and related disorders., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

The hippocampus and medial prefrontal cortex (mPFC) interact during a myriad of cognitive processes including decision-making and long-term memory consolidation. Exactly how the mPFC and hippocampus interact during goal-directed decision-making remains to be fully elucidated. During periods of rest, bursts of high-frequency oscillations, termed sharp-wave ripple (SWR), appear in the local field potential. Impairing SWRs on the maze or during post-learning rest can interfere with memory-guided decision-making and memory consolidation. We hypothesize that the hippocampus and mPFC bidirectionally interact during SWRs to support memory consolidation and decision-making. Rats were trained on the neuroeconomic spatial decision-making task, Restaurant Row, to make serial stay-skip decisions where the amount of effort (delay to reward) varied upon entry to each restaurant. Hippocampal cells and SWRs were recorded in rats with the mPFC transduced with inhibitory DREADDs. We found that disrupting the mPFC impaired consolidating SWRs in the hippocampus. Hippocampal SWR rates depended on the internalized value of the reward (derived from individual flavor preferences), a parameter important in decision-making, and disrupting the mPFC changed this relationship. Additionally, we found a dissociation between SWRs that occurred while rats were on the maze dependent upon whether those SWRs occurred while the rat was anticipating food reward or during post-reward consumption., (© 2021 Wiley Periodicals LLC.)

The dorsolateral striatum (DLS) is involved in learning and executing procedural actions. Cell ensembles in the DLS, but not the dorsomedial striatum (DMS), exhibit a burst of firing at the start of a well-learned action sequence ("task-bracketing"). However, it is currently unclear what information is contained in these bursts. Some theories suggest that these bursts should represent the procedural action sequence itself (that they should be about future action chains), whereas others suggest that they should contain representations of the current state of the world, taking into account primarily past information. In addition, the DLS local field potential shows transient bursts of power in the 50 Hz range (γ50) around the time a learned action sequence is initiated. However, it is currently unknown how bursts of activity in DLS cell ensembles and bursts of γ50 power in the DLS local field potential are related to each other. We found that DLS bursts at lap initiation in rats represented recently experienced reward locations more than future procedural actions, indicating that task-initiation DLS bursts contain primarily retrospective, rather than prospective, information to guide procedural actions. Furthermore, representations of past reward locations increased during periods of increased γ50 power in the DLS. There was no evidence of task-initiation bursts, increased γ50 power, or retrospective reward location information in the neighboring dorsomedial striatum. These data support a role for the DLS in model-free theories of procedural decision-making over planned action-chain theories, suggesting that procedural actions derive from representations of the current and recent past. SIGNIFICANCE STATEMENT While it is well-established that the dorsolateral striatum (DLS) plays a critical role in procedural decision-making, open questions remain about the kinds of representations contained in DLS ensemble activity that guide procedural actions. We found that DLS, but not DMS, cell ensembles contained nonlocal representations of past reward locations that appear moments before task-initiation DLS bursts. These retrospective representations were temporally linked to a rise in γ50 power that also preceded the characteristic DLS burst at task-initiation. These results support models of procedural decision-making based on associations between available actions and the current state of the world over models based on planning over action-chains., (Copyright © 2021 the authors.)

Many foraging experiments have found that subjects are suboptimal in foraging tasks, waiting out delays longer than they should given the reward structure of the environment. Additionally, theories of decision-making suggest that actions arise from interactions between multiple decision-making systems and that these systems should depend on the availability of information about the future. To explore suboptimal behavior on foraging tasks and how varying the amount of future information changed behavior, we ran rats on two matching neuroeconomic foraging tasks, Known Delay (KD) and Randomized Delay (RD), with the only difference between them being the certainty of the cost of future opportunities. Rats' decision-making strategies differed significantly based on the amount of future certainty. Rats on both tasks still showed suboptimality in decision-making through a sensitivity to sunk costs; however, rats on KD showed significantly less sensitivity to sunk costs than rats on RD. Additionally, on neither task did the rats account for travel and postreward lingering times as heavily as prereward foraging times providing evidence problematic for the Marginal Value Theorem model of foraging behavior. This suggests that while future certainty reduced decision-making errors, more complex decision-making processes unaffected by future certainty were involved and likely produced these decision-making errors within subjects on these foraging tasks. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Decisions made by mammals and birds are often temporally extended. They require planning and sampling of decision-relevant information. Our understanding of such decision-making remains in its infancy compared with simpler, forced-choice paradigms. However, recent advances in algorithms supporting planning and information search provide a lens through which we can explain neural and behavioral data in these tasks. We review these advances to obtain a clearer understanding for why planning and curiosity originated in certain species but not others; how activity in the medial temporal lobe, prefrontal and cingulate cortices may support these behaviors; and how planning and information search may complement each other as means to improve future action selection., (© 2021. Springer Nature America, Inc.)

Adapting to the changing environment is a key component of optimal decision-making. Internal-models that accurately represent and selectively update from behaviorally relevant/salient stimuli may facilitate adaptive behaviors. Anterior cingulate cortex (ACC) and dopaminergic systems may produce these adaptive internal-models through selective updates from behaviorally relevant stimuli. Dysfunction of ACC and dopaminergic systems could therefore produce misaligned internal-models where updates are disproportionate to the salience of the cues. An aspect of addictive-like behaviors is reduced adaptation and, ACC and dopaminergic systems typically exhibit dysfunction in drug-dependents. We argue that ACC and dopaminergic dysfunction in dependents may produce misaligned internal-models such that drug-related stimuli are misattributed with a higher salience compared to non-drug related stimuli. Hence, drug-related rewarding stimuli generate over-weighted updates to the internal-model, while negative feedback and non-drug related rewarding stimuli generate down-weighted updates. This misaligned internal-model may therefore incorrectly reinforce maladaptive drug-related behaviors. We use the proposed framework to discuss ways behavior may be made more adaptive and how the framework may be supported or falsified experimentally., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Poor context integration, the process of incorporating both previous and current information in decision making, is a cognitive symptom of schizophrenia. The maintenance of the contextual information has been shown to be sensitive to changes in excitation-inhibition (EI) balance. Many regions of the brain are sensitive to EI imbalances, however, so it is unknown how systemic manipulations affect the specific regions that are important to context integration. We constructed a multi-structure, biophysically-realistic agent that could perform context-integration as is assessed by the dot pattern expectancy task. The agent included a perceptual network, a memory network, and a decision making system and was capable of successfully performing the dot pattern expectancy task. Systemic manipulation of the agent's EI balance produced localized dysfunction of the memory structure, which resulted in schizophrenia-like deficits at context integration. When the agent's pyramidal cells were less excitatory, the agent fixated upon the cue and initiated responding later than the default agent, which were like the deficits one would predict that individuals on the autistic spectrum would make. This modelling suggests that it may be possible to parse between different types of context integration deficits by adding distractors to context integration tasks and by closely examining a participant's reaction times., Competing Interests: The authors have declared that no competing interests exist.

Multimodal approaches combining cognitive behavioral therapies (CBT) with non-invasive brain stimulation (NIBS) hold promise for improving the treatment of neuropsychiatric disorders. As this is a relatively new approach, it is a critical time to identify guiding principles and methodological considerations to enhance research rigor. In the current paper, we argue for a principled approach to CBT and NIBS pairings based on synergistic activation of neural circuits and identify key considerations about CBT that may influence pairing with NIBS. Careful consideration of brain-state interactions and CBT-related nuances will increase the potential for these combinations to be positively synergistic., Competing Interests: CC and SJ are investigators on National Institute of Mental Health-funded SBIR grants awarded to Posit Science [R43MH121209 (CC), R43MH124542 (CC and SJ)]. SJ has been an investigator in multisite autism treatment trials by Roche and on an autism advisory board for Roche. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Conelea, Jacob, Redish and Ramsay.)

In the WebSurf task, humans forage for videos paying costs in terms of wait times on a time-limited task. A variant of the task in which demands during the wait time were manipulated revealed the role of attention in susceptibility to sunk costs. Consistent with parallel tasks in rodents, previous studies have found that humans (undergraduates measured in lab) preferred shorter delays, but waited longer for more preferred videos, suggesting that they were treating the delays economically. In an Amazon Mechanical Turk (mTurk) sample, we replicated these predicted economic behaviors for a majority of participants. In the lab, participants showed susceptibility to sunk costs in this task, basing their decisions in part on time they have already waited, which we also observed in the subset of the mTurk sample that behaved economically. In another version of the task, we added an attention check to the wait phase of the delay. While that attention check further increased the proportion of subjects with predicted economic behaviors, it also removed the susceptibility to sunk costs. These findings have important implications for understanding how cognitive processes, such as the deployment of attention, are key to driving re-evaluation and susceptibility to sunk costs., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Kazinka, MacDonald and Redish.)

A frequent assumption in value-based decision-making tasks is that agents make decisions based on the feature dimension that reward probabilities vary on. However, in complex, multidimensional environments, stimuli can vary on multiple dimensions at once, meaning that the feature deserving the most credit for outcomes is not always obvious. As a result, individuals may vary in the strategies used to sample stimuli across dimensions, and these strategies may have an unrecognized influence on decision-making. Sex is a proxy for multiple genetic and endocrine influences on behavior, including how environments are sampled. In this study, we examined the strategies adopted by female and male mice as they learned the value of stimuli that varied in both image and location in a visually cued two-armed bandit, allowing two possible dimensions to learn about. Female mice acquired the correct image-value associations more quickly than male mice, preferring a fundamentally different strategy. Female mice were more likely to constrain their decision-space early in learning by preferentially sampling one location over which images varied. Conversely, male mice were more likely to be inconsistent, changing their choice frequently and responding to the immediate experience of stochastic rewards. Individual strategies were related to sex-biased changes in neuronal activation in early learning. Together, we find that in mice, sex is associated with divergent strategies for sampling and learning about the world, revealing substantial unrecognized variability in the approaches implemented during value-based decision making., Competing Interests: Declaration of Interests The authors declare no competing interests., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Mammalian decision-making is mediated by the interaction of multiple, neurally and computationally separable decision systems. Having multiple systems requires a mechanism to manage conflict and converge onto the selection of singular actions. A long history of evidence has pointed to the prefrontal cortex as a central component in processing the interactions between distinct decision systems and resolving conflicts among them. In this chapter we review four theories of how that interaction might occur and identify how the medial prefrontal cortex in the rodent may be involved in each theory. We then present experimental predictions implied by the neurobiological data in the context of each theory as a starting point for future investigation of medial prefrontal cortex and decision-making., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Deliberation is thought to involve the internal simulation of the outcomes of candidate actions, the valuation of those outcomes, and the selection of the actions with the highest expected value. While it is known that deliberation involves prefrontal cortical areas, specifically the dorsomedial prefrontal cortex (dmPFC), as well as the hippocampus (HPC) and other brain regions, how these areas process prospective information and select actions is not well understood. We recorded simultaneously from ensembles in dmPFC and CA1 of dorsal HPC in rats during performance of a spatial contingency switching task, and examined the relationships between spatial and reward encoding in these two areas during deliberation at the choice point. We found that CA1 and dmPFC represented either goal locations or the current position simultaneously, but that when goal locations were encoded, HPC and dmPFC did not always represent the same goal location. Ensemble activity in dmPFC predicted when HPC would represent goal locations, but on a broad timescale on the order of seconds. Also, reward encoding in dmPFC increased during hippocampal theta cycles where CA1 ensembles represented the goal location. These results suggest that dmPFC and HPC share prospective information during deliberation, that dmPFC may influence whether HPC represents prospective information, and that information recalled about goal locations by HPC may be integrated into dmPFC reward representations on fast timescales., (© 2020 Wiley Periodicals LLC.)

Background: The causal biology underlying schizophrenia is not well understood, but it is likely to involve a malfunction in how neurons adjust synaptic connections in response to patterns of activity in networks. We examined statistical dependencies between neural signals at the cell, local circuit, and distributed network levels in prefrontal and parietal cortices of monkeys performing a variant of the AX continuous performance task paradigm. We then quantified changes in the pattern of neural interactions across levels of scale following NMDA receptor (NMDAR) blockade and related these changes to a pattern of cognitive control errors closely matching the performance of patients with schizophrenia., Methods: We recorded the spiking activity of 1762 neurons along with local field potentials at multiple electrode sites in prefrontal and parietal cortices concurrently, and we generated binary time series indicating the presence or absence of spikes in single neurons or local field potential power above or below a threshold. We then applied causal discovery analysis to the time series to detect statistical dependencies between the signals (causal interactions) and compared the pattern of these interactions before and after NMDAR blockade., Results: Global blockade of NMDAR produced distinctive and frequently opposite changes in neural interactions at the cell, local circuit, and network levels in prefrontal and parietal cortices. Cognitive control errors were associated with decreased interactions at the cell level and with opposite changes at the network level in prefrontal and parietal cortices., Conclusions: NMDAR synaptic deficits change causal interactions between neural signals at different levels of scale that correlate with schizophrenia-like deficits in cognitive control., (Copyright © 2020 Society of Biological Psychiatry. All rights reserved.)

Dorsomedial prefrontal cortex (dmPFC) and hippocampus (HPC) are thought to play complementary roles in a spatial working memory and decision-making network, where spatial information from HPC informs representations in dmPFC, and contextual information from dmPFC biases how HPC recalls that information. We recorded simultaneously from neural ensembles in rodent dmPFC and HPC as rats performed a rule-switching task, and found that ensembles in dmPFC and HPC simultaneously encoded task contingencies and other time-varying information. While ensembles in HPC transitioned to represent new contingencies at the same time as rats updated their strategies to be consistent with the new contingency, dmPFC ensembles transitioned earlier. Neural representations of other time-varying information also changed faster in dmPFC than in HPC. Our results suggest that HPC and dmPFC represent contingencies while simultaneously representing other information which changes over time, and that this contextual information is integrated into hippocampal representations more slowly than in dmPFC., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Humans have a remarkable capacity to mentally project themselves far ahead in time. This ability, which entails the mental simulation of events, is thought to be fundamental to deliberative decision making, as it allows us to search through and evaluate possible choices. Many decisions that humans make are foraging decisions, in which one must decide whether an available offer is worth taking, when compared to unknown future possibilities (i.e., the background). Using a translational decision-making paradigm designed to reveal decision preferences in rats, we found that humans engaged in deliberation when making foraging decisions. A key feature of this task is that preferences (and thus, value) are revealed as a function of serial choices. Like rats, humans also took longer to respond when faced with difficult decisions near their preference boundary, which was associated with prefrontal and hippocampal activation, exemplifying cross-species parallels in deliberation. Furthermore, we found that voxels within the visual cortices encoded neural representations of the available possibilities specifically following regret-inducing experiences, in which the subject had previously rejected a good offer only to encounter a low-valued offer on the subsequent trial.

Whether fear or anxiety is expressed is thought to depend on an animal's proximity to threat. In general, fear is elicited when threat is proximal, while anxiety is a response to threat that is distal and uncertain. This threat gradient model suggests that fear and anxiety involve non-overlapping neural circuitry, yet few behavioral paradigms exist that elicit both states. We studied avoid-approach conflict in rats that were behaving in a predator-inhabited foraging arena task that involved tangible threat and reward incentives. In the task, rats exhibited a variety of both fearful and anxious behaviors corresponding to proximal and distal threat, respectively. We then administered ethanol or diazepam to the rats in order to study how anxiolytics affected these fear and anxiety behaviors. We discovered that both ethanol and diazepam attenuated proximal-threat fear-like behaviors. Furthermore, we found that diazepam, but not ethanol, increased distal-threat anxiety-like behavior but also made rats less risk-averse. Finally, we describe how decisional conflict can be modeled as a partially observable Markov decision process and characterize a potential relationship between anxious behavior, diazepam's ability to suppress hippocampal theta oscillations, and hippocampal representations of the future.

Current theories of deliberative decision making suggest that deliberative decisions arise from imagined simulations that require interactions between the prefrontal cortex and hippocampus. In rodent navigation experiments, hippocampal theta sequences advance from the location of the rat ahead to the subsequent goal. To examine the role of the medial prefrontal cortex (mPFC) on the hippocampus, we disrupted the mPFC with DREADDs (designer receptors exclusively activated by designer drugs). Using the Restaurant Row foraging task, we found that mPFC disruption resulted in decreased vicarious trial and error behavior, reduced the number of theta sequences, and impaired theta sequences in hippocampus. mPFC disruption led to larger changes in the initiation of the hippocampal theta sequences that represent the current location of the rat rather than to the later portions that represent the future outcomes. These data suggest that the mPFC likely provides an important component to the initiation of deliberative sequences and provides support for an episodic-future thinking, working memory interpretation of deliberation. NEW & NOTEWORTHY The medial prefrontal cortex (mPFC) and hippocampus interact during deliberative decision making. Disruption of the mPFC impaired hippocampal processes, including the local and nonlocal representations of space along each theta cycle and the initiation of hippocampal theta sequences, while sparing place cell firing characteristics and phase precession. mPFC disruption reduced the deliberative behavioral process vicarious trial and error and improved economic behaviors on this task.

A fundamental feature of addiction is continued use despite high-cost losses. One possible driver of this feature is a dissociation between reward pursuit and reward valuation. To test for this dissociation, we employed a foraging paradigm with real-time delays and video rewards. Subjects made stay/skip choices on risky and non-risky offers; risky losses were operationalized as receipt of the longer delay after accepting a risky deal. We found that reward likability following risky losses predicted reward pursuit (i.e., subsequent choices), while there was no effect on reward valuation or reward pursuit in the absence of such losses. Individuals with high trait externalizing, who may be vulnerable to addiction, showed a dissociation between these phenomena: they liked videos more after risky losses but showed no decrease in choosing to stay on subsequent risky offers. This suggests that the inability to learn from mistakes is a potential component of risk for addiction.

An engineer's viewpoint on psychiatry asks: What are the failure modes that underlie psychiatric dysfunction? And: How can we modify the system? Psychiatry has made great strides in understanding and treating disorders using biology; however, failure modes and modification access points can also exist extrinsically in environmental interactions. The network analysis suggested by Borsboom et al. in the target article provides a new viewpoint that should be incorporated into current theoretical constructs, not placed in opposition to them.

[This corrects the article DOI: 10.3389/fnint.2018.00030.].

The decision to apply to a PhD-granting graduate program is both exciting and daunting. Understanding what graduate programs look for in an applicant will increase the chance of successful admission into a PhD program. It is also helpful for an applicant to understand what graduate training will look like once they matriculate into a PhD program to ensure they select programs that will help them reach their career objectives. This article focuses specifically on PhD programs in neuroscience, and while we use our program, the Graduate Program in Neuroscience at the University of Minnesota, as an example, most of what we describe is applicable to biomedical graduate programs generally. In order to ensure that our description of graduate programs is typical of neuroscience graduate programs generally, we surveyed the online websites of 52 neuroscience graduate programs around the U. S. and include our observations here. We will examine what graduate schools look for in an applicant, what to expect once admitted into a PhD graduate program, and the potential outcomes for those who successfully complete their PhD in neuroscience.

Addiction is considered to be a neurobiological disorder of learning and memory because addiction is capable of producing lasting changes in the brain. Recovering addicts chronically struggle with making poor decisions that ultimately lead to relapse, suggesting a view of addiction also as a neurobiological disorder of decision-making information processing. How the brain makes decisions depends on how decision-making processes access information stored as memories in the brain. Advancements in circuit-dissection tools and recent theories in neuroeconomics suggest that neurally dissociable valuation processes access distinct memories differently, and thus are uniquely susceptible as the brain changes during addiction. If addiction is to be considered a neurobiological disorder of memory, and thus decision-making, the heterogeneity with which information is both stored and processed must be taken into account in addiction studies. Addiction etiology can vary widely from person to person. We propose that addiction is not a single disease, nor simply a disorder of learning and memory, but rather a collection of symptoms of heterogeneous neurobiological diseases of distinct circuit-computation-specific decision-making processes., (© 2018 Sweis et al.; Published by Cold Spring Harbor Laboratory Press.)

Current theories suggest that decision-making arises from multiple, competing action-selection systems. Rodent studies dissociate deliberation and procedural behavior, and find a transition from procedural to deliberative behavior with experience. However, it remains unknown how this transition from deliberative to procedural control evolves within single trials, or within blocks of repeated choices. We adapted for rats a two-step task which has been used to dissociate model-based from model-free decisions in humans. We found that a mixture of model-based and model-free algorithms was more likely to explain rat choice strategies on the task than either model-based or model-free algorithms alone. This task contained two choices per trial, which provides a more complex and non-discrete per-trial choice structure. This task structure enabled us to evaluate how deliberative and procedural behavior evolved within-trial and within blocks of repeated choice sequences. We found that vicarious trial and error (VTE), a behavioral correlate of deliberation in rodents, was correlated between the two choice points on a given lap. We also found that behavioral stereotypy, a correlate of procedural automation, increased with the number of repeated choices. While VTE at the first choice point decreased [corrected] with the number of repeated choices, VTE at the second choice point did not, and only increased after unexpected transitions within the task. This suggests that deliberation at the beginning of trials may correspond to changes in choice patterns, while mid-trial deliberation may correspond to an interruption of a procedural process.

Sunk costs are irrecoverable investments that should not influence decisions, because decisions should be made on the basis of expected future consequences. Both human and nonhuman animals can show sensitivity to sunk costs, but reports from across species are inconsistent. In a temporal context, a sensitivity to sunk costs arises when an individual resists ending an activity, even if it seems unproductive, because of the time already invested. In two parallel foraging tasks that we designed, we found that mice, rats, and humans show similar sensitivities to sunk costs in their decision-making. Unexpectedly, sensitivity to time invested accrued only after an initial decision had been made. These findings suggest that sensitivity to temporal sunk costs lies in a vulnerability distinct from deliberation processes and that this distinction is present across species., (Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

The nucleus accumbens shell (NAcSh) is involved in reward valuation. Excitatory projections from infralimbic cortex (IL) to NAcSh undergo synaptic remodeling in rodent models of addiction and enable the extinction of disadvantageous behaviors. However, how the strength of synaptic transmission of the IL-NAcSh circuit affects decision-making information processing and reward valuation remains unknown, particularly because these processes can conflict within a given trial and particularly given recent data suggesting that decisions arise from separable information-processing algorithms. The approach of many neuromodulation studies is to disrupt information flow during on-going behaviors; however, this limits the interpretation of endogenous encoding of computational processes. Furthermore, many studies are limited by the use of simple behavioral tests of value which are unable to dissociate neurally distinct decision-making algorithms. We optogenetically altered the strength of synaptic transmission between glutamatergic IL-NAcSh projections in mice trained on a neuroeconomic task capable of separating multiple valuation processes. We found that induction of long-term depression in these synapses produced lasting changes in foraging processes without disrupting deliberative processes. Mice displayed inflated reevaluations to stay when deciding whether to abandon continued reward-seeking investments but displayed no changes during initial commitment decisions. We also developed an ensemble-level measure of circuit-specific plasticity that revealed individual differences in foraging valuation tendencies. Our results demonstrate that alterations in projection-specific synaptic strength between the IL and the NAcSh are capable of augmenting self-control economic valuations within a particular decision-making modality and suggest that the valuation mechanisms for these multiple decision-making modalities arise from different circuits., Competing Interests: The authors declare no conflict of interest.

Neuroeconomic theories propose changes in decision making drive relapse in recovering drug addicts, resulting in continued drug use despite stated wishes not to. Such conflict is thought to arise from multiple valuation systems dependent on separable neural components, yet many neurobiology of addiction studies employ only simple tests of value. Here, we tested in mice how prolonged abstinence from different drugs affects behavior in a neuroeconomic foraging task that reveals multiple tests of value. Abstinence from repeated cocaine and morphine disrupts separable decision-making processes. Cocaine alters deliberation-like behavior prior to choosing a preferred though economically unfavorable offer, while morphine disrupts re-evaluations after rapid initial decisions. These findings suggest that different drugs have long-lasting effects precipitating distinct decision-making vulnerabilities. Our approach can guide future refinement of decision-making behavioral paradigms and highlights how grossly similar behavioral maladaptations may mask multiple underlying, parallel, and dissociable processes that treatments for addiction could potentially target.

Regret can be defined as the subjective experience of recognizing that one has made a mistake and that a better alternative could have been selected. The experience of regret is thought to carry negative utility. This typically takes two distinct forms: augmenting immediate postregret valuations to make up for losses, and augmenting long-term changes in decision-making strategies to avoid future instances of regret altogether. While the short-term changes in valuation have been studied in human psychology, economics, neuroscience, and even recently in nonhuman-primate and rodent neurophysiology, the latter long-term process has received far less attention, with no reports of regret avoidance in nonhuman decision-making paradigms. We trained 31 mice in a novel variant of the Restaurant Row economic decision-making task, in which mice make decisions of whether to spend time from a limited budget to achieve food rewards of varying costs (delays). Importantly, we tested mice longitudinally for 70 consecutive days, during which the task provided their only source of food. Thus, decision strategies were interdependent across both trials and days. We separated principal commitment decisions from secondary reevaluation decisions across space and time and found evidence for regret-like behaviors following change-of-mind decisions that corrected prior economically disadvantageous choices. Immediately following change-of-mind events, subsequent decisions appeared to make up for lost effort by altering willingness to wait, decision speed, and pellet consumption speed, consistent with past reports of regret in rodents. As mice were exposed to an increasingly reward-scarce environment, we found they adapted and refined distinct economic decision-making strategies over the course of weeks to maximize reinforcement rate. However, we also found that even without changes in reinforcement rate, mice transitioned from an early strategy rooted in foraging to a strategy rooted in deliberation and planning that prevented future regret-inducing change-of-mind episodes from occurring. These data suggest that mice are learning to avoid future regret, independent of and separate from reinforcement rate maximization., Competing Interests: The authors have declared that no competing interests exist.

Competing Interests: The authors declare no conflict of interest.