Using temporally delayed linear modeling (TDLM) and magnetoencephalography (MEG), we investigated whether items associated with an underlying graph structure are replayed during a post-learning resting state. In these same data, we previously provided evidence for replay during online (non-rest) memory retrieval. Despite successful decoding of brain activity during a localizer task, and contrary to predictions, we found no evidence for replay during a post-learning resting state. To better understand this, we performed a hybrid simulation analysis in which we inserted synthetic replay events into a control resting state recorded prior to the actual experiment. This simulation revealed that replay detection using our current pipeline requires an extremely high replay density to reach significance (>1 replay sequence per second, with ‘replay’ defined as a sequence of reactivations within a certain time lag). Furthermore, when scaling the number of replay events with a behavioral measure, we were unable to induce a strong correlation between sequenceness and this measure. We infer that even if replay was present at plausible rates in our resting state dataset, we would lack statistical power to detect it with TDLM. Finally, contrasting our novel hybrid simulation to existing purely synthetic simulations indicated that the latter approaches overestimate the sensitivity of TDLM. We discuss approaches that might optimize the analytic methodology, including identifying boundary conditions under which TDLM can be expected to detect replay. We conclude that solving these methodological constraints will be crucial for optimizing the non-invasive measurement of human replay using MEG.

Spontaneous memory replay during sleep is crucial for cognition but challenging to capture because distinct sleep rhythms hinder the generalization of wake-trained electroencephalogram (EEG) decoders. To address this, we developed the Sleep Interpreter (SI), which uses neural contrastive learning to isolate shared semantic content from background rhythms. We collected a dataset of 135 participants undergoing targeted reactivation of 15 semantic categories, yielding approximately 1,000 h of overnight sleep and 400 h of wake EEG. During non-rapid eye movement (NREM) sleep, SI achieved high decoding accuracy for cue-evoked semantic responses, with accuracy peaking during slow oscillation and spindle coupling at 40.02% top-1 accuracy on unseen participants (chance 6.7%). We demonstrated SI generalizability in two independent nap experiments involving targeted and spontaneous reactivation, where decoded reactivations correlated with post-sleep memory performance. Finally, we implemented SI for real-time sleep staging and stage-specific NREM and REM decoding. The dataset and codebase are shared as open resources for future clinical applications.

BACKGROUND:Alcohol use disorder (AUD) is a major contributor to global disability and mortality. Cross-sectional studies have linked AUD to reduced cognitive control and heightened risky decision-making. However, the temporal direction of these effects remains unknown: are cognitive-behavioral alterations a consequence or a precursor of changes in drinking? METHODS:We deployed a battery of smartphone-based, gamified tasks in a one-year longitudinal ecological momentary assessment study of N=603 participants diagnosed with mostly mild to moderate AUD. Tasks measured cognitive control (working memory, response inhibition) and decision-making (risk-taking, information sampling). Participants completed tasks monthly and reported alcohol consumption every two days. RESULTS:We found that monthly fluctuations in aspects of decision-making predicted subsequent consumption. Specifically, participants shifted to higher monthly alcohol consumption when their risk-taking was higher in a mixed gambling context and lower in a loss context in the preceding month. Further, when information sampling biases decreased, participants consumed more alcohol in the subsequent month. This temporal direction-that within-subject fluctuations in task outcomes preceded changes in monthly drinking-was specific, was not observed vice versa and survived correction for autocorrelation in drinking, indicating risky decision-making as a precursor of subsequent drinking. Fluctuations in cognitive control and risk-taking in a win context were not associated with fluctuations in drinking. DISCUSSION:Our findings offer novel insights into the cognitive-behavioral forces driving changes in alcohol consumption in AUD: specific decision-making alterations precede changes in consumption. These findings suggest that smartphone-based gamified tasks show promise to identify periods of heightened risk paving the way for mechanism-based, real-time interventions in AUD.

INTRODUCTION:We examined whether locus coeruleus (LC) contrast, an indirect proxy for neuronal density and structural health, was related to delayed episodic memory in healthy older adults (OAs) and those with mild cognitive impairment (MCI) and its association with encoding-related brain activity, controlling for emotional salience. METHODS:Participants (27 younger adults, 26 OAs, and 24 MCI) memorized emotional and neutral images during functional magnetic resonance imaging (MRI). Delayed memory was tested after 4 h and compared to immediate memory. LC contrast was measured via LC-sensitive MRI. RESULTS:Memory was lower, independent of delay or emotional valence, and LC contrast was more strongly reduced in those with MCI compared to OAs. In OAs, LC contrast correlated with delayed memory and was mildly associated with LC activity during successful encoding. All groups remembered emotional images better than neutral ones, though memory was greatly impaired in those with MCI. DISCUSSION:LC contrast was associated with lower brain activity during encoding and emotional salience processing. Its relationship to delayed memory was evident in those with MCI.

Biases in information gathering are common in the general population and reach pathological extremes in paralysing indecisiveness, as in obsessive–compulsive disorder (OCD). Here we adopt a new perspective on information gathering and demonstrate an information integration bias whereby there is over-weighting of most recent information via evidence strength updates (ΔES). In a crowd-sourced sample (N = 5,237), we find that a reduced ΔES weighting drives indecisiveness along an obsessive–compulsive spectrum. We replicate this attenuated ΔES weighting in a second lab-based study (N = 105) that includes a transdiagnostic obsessive–compulsive spectrum encompassing OCD and generalized anxiety patients. Using magnetoencephalography (MEG), we trace ΔES signals to a late neural signal peaking at ~920 ms. Critically, highly obsessive–compulsive participants, across diagnoses, show an attenuated neural ΔES signal in mediofrontal areas, while other decision-relevant processes remain intact. Our findings establish biased information weighting as a driver of information gathering, where attenuated ΔES is linked to indecisiveness across an obsessive–compulsive spectrum. This research finds a strong recency bias in information gathering, attenuated in those on the OCD spectrum—a possible mechanism for indecisiveness. Behavioural and MEG data show reduced evidence updating in high-OC individuals.

INTRODUCTION:Pupil dilation (PD) can be easily measured and reflects responses to subjectively salient or cognitively demanding events. It therefore holds promise as a cognitive marker, especially for individuals with mild cognitive impairment (MCI) or other neurodegenerative conditions with restricted abilities to respond in cognitive assessments. METHODS:We assessed PD during two tasks, an oddball task for investigating attentional allocation and a Simon task, which additionally allows for investigating cognitive effort in younger adults (YAs), older adults (OAs), and patients with MCI. RESULTS:PD is a useful marker for investigating attention and cognitive effort in MCI, as suggested by elevated PD to salient stimuli in particular of individuals with better attentional control in MCI patients, as well as YAs and OAs. DISCUSSION:Measurement of PD may serve as an easy-to-administer measure to assess changes in cognitive function in healthy aging and MCI.

Language provides the most revealing window into the ways humans structure conceptual knowledge within cognitive maps. Harnessing this information has been difficult, given the challenge of reliably mapping words to mental concepts. Artificial Intelligence large language models (LLMs) now offer unprecedented opportunities to revisit this challenge. LLMs represent words and phrases as high-dimensional numerical vectors that encode vast semantic knowledge. To harness this potential for cognitive science, we introduce VECTOR, a computational framework that aligns LLM representations with human cognitive map organisation. VECTOR casts a participant's verbal reports as a geometric trajectory through a cognitive map representation, revealing how thoughts flow from one idea to the next. Applying VECTOR to narratives generated by 1,100 participants, we show these trajectories have cognitively meaningful properties that predict paralinguistic behaviour (response times) and real-world communication patterns. We suggest our approach opens new avenues for understanding how humans dynamically organise and navigate conceptual knowledge in naturalistic settings.

The Locus Coeruleus (LC) is prominently affected by neuronal loss in the earliest stages of Alzheimer’s disease (AD). Assessing LC integrity can serve as an important early biomarker for assessing AD progression. Neuromelanin (NM) accumulates in LC neurons and NM imaging has therefore been proposed as a means of imaging the LC. As signal intensity is taken as a proxy for cell density, a quantitative imaging approach of the LC, which is less variable across sites and time is desirable. The present study used a multi-parameter mapping (MPM) protocol optimized for LC imaging to compare weighted and quantitative maps in healthy younger, healthy older adults and individuals with AD. Structural MRI data was acquired in a group of 26 healthy young adults, 26 healthy older adults and 26 individuals with Alzheimer’s disease. Three sets of T1-weighted, MT-weighted, and PD-weighted images yielded quantitative maps (R1, MTsat, PD, and R2*) in each individual within one scan session. Qualitative and quantitative methods were used to assess weighted and quantitative maps for LC imaging across groups. Qualitatively, LC visibility was higher in weighted images. The LC was also apparent in R1 maps, but less clearly visible in MTsat and R2* maps (Figure 1). LC contrast ratio (with pons as reference), was reduced in Alzheimer’s disease compared to younger adults as detected by MTw scans ( p = .001) and to older adults as detected by T1w ( p <.001), MTw ( p <.001), and PDw scans ( p = .007). No group differences were detected in quantitative maps, suggesting less sensitivity to pick up typical LC integrity reductions. PD maps could not be reliably estimated in the modified setup of the MPMs. Although among the quantitative maps LC was most visible in R1 images, our findings indicate that R1 maps capture the LC signal intensity less well as compared to non-quantitative LC imaging, as suggested by a qualitative assessment of LC visibility and inability to detect known group differences. Further research should improve sensitivity of quantitative maps for LC assessment by combining sequences capturing different aspects of LC tissue properties.

Humans often make irrational decisions when facing uncertain or aversive future events despite careful deliberation. How we make choices, including irrational ones, has been the object of extensive study both behaviourally and neurally and is the focus of influential behavioural economic theories. Yet, little is known about how these (irrational) decisions are carved out in the brain. Here, using magnetoencephalography (MEG), we show that the construction and outcome evaluation of irrational decisions involves rapid, sequential state reactivation, or "replay.". During deliberation, we show that forward replay is biased towards choice options with more negative and uncertain outcomes, with this bias further amplified immediately preceding irrational choice. Likewise, post-decision evaluation relates to replay in a choice-dependent manner. Following irrational choices, relief-like signals were evident as stronger backward replay of worse counterfactual options, while after rational decisions, regret-like signals appeared as stronger backward replay of better counterfactual options. Together, these findings suggest that neural replay shapes both the formation and reflection of irrational decisions, and poise replay as a candidate mechanism underlying pervasive decision biases in humans. ### Competing Interest Statement The authors have declared no competing interest.

Maladaptive responses to uncertainty, including excessive risk seeking or avoidance, are linked to a range of mental disorders. One expression of these is a provariance bias (PVB), i.e., risk-seeking manifests as a preference for choosing options with higher variances/uncertainty. Using a magnitude learning task, we show that individual differences in PVB are explained by a model that includes asymmetric learning rates, allowing differential learning from positive prediction errors (PPEs) and negative prediction errors (NPEs). Using high-resolution 7T functional MRI (fMRI), we identify distinct neural responses to PPEs and NPEs in value-sensitive regions, including habenula (Hb), ventral tegmental area (VTA), nucleus accumbens (NAcc), and ventral medial prefrontal cortex (vmPFC) in humans. Notably, prediction error signals in NAcc and vmPFC were boosted for high variance options. NPEs responses in NAcc were associated with a negative bias in learning rates that was linked to the strength of Hb-VTA negative functional coupling during NPE encoding, with a mediation analysis revealing this coupling influenced NAcc responses to NPEs via an impact on learning rate bias. Our findings implicate Hb-VTA functional coupling in the emergence of risk preferences during learning, with implications for psychopathology.

Memory decline, which is especially prevalent in Alzheimer’s disease (AD), has been studied via fMRI, primarily focusing on the prefrontal cortex and hippocampus. However, emerging evidence suggests that the brainstem, alongside various midbrain regions, is an initial target for pathological processes like hyperphosphorylated TAU protein accumulation. Among these, the locus coeruleus, a noradrenergic nucleus in the pons, projects to critical midbrain areas supporting memory encoding. Hence, our study aimed to investigate BOLD task activations in AD relevant to memory, while focusing on differences in responses to emotional versus neutral stimuli in the brainstem and midbrain. Using event-related fMRI, 53 subjects (28 healthy older adults, 25 with mild cognitive impairment (MCI)) (see table 1) underwent an incidental recognition memory task involving emotional and neutral images. Memory tests followed immediately, and 4 hours after encoding. Group differences in brain activations for remembered versus not remembered images using the study template were examined. Results revealed a trend for greater activation in the left caudate nucleus in older adults, compared to those with MCI, when subsequently remembered items were compared with not remembered ones (small volume correction (SVC), cluster level p FWE-corr = 0.08). Similarly, a significant increased activation was observed in the locus coeruleus (SVC, cluster level p FWE-corr = 0.018). However, after adjusting for group and individual differences in LC integrity and global grey matter volume (GMV), no significant differences persisted, suggesting that structural changes contribute significantly to differences in LC activation between healthy controls and MCI participants (see Figures 1 and 2). In conclusion, our findings underscore the caudate nucleus’s role in memory encoding for healthy older adults versus those with MCI. A decline in LC function in MCI appears related to a decline in LC integrity. These insights contribute to understanding memory mechanisms in healthy aging versus MCI. Future studies are needed to explore potential neural memory compensatory processes in MCI.

Individuals experiencing symptoms of anxiety and depression have been shown to exhibit persistent underconfidence. The origin of such metacognitive biases presents a puzzle, given that individuals should be able to learn appropriate levels of confidence from observing their own performance. In two large general population samples (N = 230 and N = 278), we measure both “local” confidence in individual task instances and “global” confidence as longer run self-performance estimates while manipulating external feedback. Global confidence is sensitive to both local confidence and feedback valence – more frequent positive (negative) feedback increases (respectively decreases) global confidence, with asymmetries in feedback also leading to shifts in affective self-beliefs. Notably, however, global confidence exhibits reduced sensitivity to instances of higher local confidence in individuals with greater subclinical anxious-depression symptomatology, despite sensitivity to feedback valence remaining intact. Our finding of blunted sensitivity to increases in local confidence offers a mechanistic basis for how persistent underconfidence is maintained in the face of intact performance.

Locus coeruleus (LC) is a primary source of noradrenalin in the brain and plays a complex role in human behavior. In healthy aging and Alzheimer’s disease (AD), LC cell loss has been linked to a decline in overall cognitive function. This study aimed to explore age- and AD-related differences in a proxy measure of LC activity. Using pupil dilation (PD) as a non-exclusive proxy measure of the LC-NE system activity, we examined whether pupillometric recordings during cognitive tasks are possible in early AD and whether they reveal differences in attentional modulation in aging and AD. 37 subjects (14 healthy OA and 23 individuals with AD) completed an auditory and visual oddball task to assess attentional modulation; 62 subjects (22 healthy YA, 20 healthy OA, and 20 individuals with AD) completed a Simon task to assess attention and cognitive control. LC integrity was assessed using neuromelanin-sensitive MRI. A larger PD response for oddball compared to standard stimuli was observed, with no difference between OA and AD participants. In the visual task, greater PD correlated with faster reaction times (RTs) for hits in both groups, indicating the interindividual differences in PD can reflect heightened attentional involvement in aging and AD. Similarly, a consistent Simon effect, i.e., lower accuracy and longer RTs for incongruent trials, was observed in all groups, suggesting cognitive effort in discriminating between congruences. PD was higher for incongruent than congruent trials across all age groups, yet YA exhibited a less pronounced Simon effect, indicating age-related differences in attentional resource allocation with a potentially larger need in OA and AD for attentional control on incongruent stimuli. In YA, slower RTs correlated with smaller PD in incongruent trials. YA and AD individuals with a stronger Simon effect in PD showed faster processing for incongruent trials and better performance for congruent trials, respectively. Using PD as a measure of attentional allocation and effort during cognitive control is possible in AD. Moreover, it allows for the assessment of interindividual differences in the extent of attentional modulation in AD. Assessing PD could be a useful tool for distinguishing between healthy aging and early AD.

Receiving affirmation, whether from ourselves or others, is crucial for interpersonal relationships and goes awry in mental disorders. Meaningful evaluations emerge during interactions, where people can support or let each other down. However, such dynamics are difficult to understand comprehensively without quantitative theory and modeling. Here, we implemented an interactive decision-making game wherein two real-life participants evaluated, i.e. graded their approval, for themselves and their play partner. Young adult participants interacted in a multi-level version of the iterated prisoner’s dilemma. Crucially, each participant did not interact with the other directly, but instructed an avatar to do so on their behalf. This allowed increased experimental control while preserving considerable ecological validity. We tested computational models of participants’ evaluations of self and other, based on their beliefs about the quality of their decisions. However such models were less successful than a novel class of models, where self- and other- evaluations depended directly on the combination of self- and other- outcomes. The winning models suggested that for a given participant, evaluation of the self is proportional to how much one’s partner benefits, and vice versa. We found marked self-positivity bias, especially in dyads where neither partner cooperated. This was consistent with attributional theory, negatively evaluating others rather than the self for adverse outcomes. Between participants, self-positivity bias was explained by a reduced weight of one’s partner’s benefits for self-evaluation, hinting that the negative outcome subject to external attribution was the partner’s, rather than one’s own, poor returns. Preliminary analysis also suggested that a reduced sensitivity to others’ outcomes was associated, in this context when participants may have both cooperative and competitive motives, with reduced earnings for the self. The proposed computational model provides a concise and novel account of self-serving bias in evaluations, clearly observed during interactions.

INTRODUCTION We examined whether the decline of delayed episodic memory in old age and MCI is related to structural integrity of the locus coeruleus (LC). We also tested whether LC integrity was associated with encoding-related brain activity, controlling for emotional salience. METHODS Participants (28 young adults, 28 older adults, 25 MCI) memorized emotional and neutral images during fMRI. Delayed memory was tested four hours later and compared to immediate memory. LC integrity was measured with a neuromelanin-sensitive sequence. RESULTS MCI showed overall memory decline, independent of delay or emotional valence, and reduced LC integrity compared to older adults. Across participants, LC integrity correlated with delayed memory, but did not explain performance within OA or MCI. LC integrity was associated with lower activity related to encoding success and emotional salience. Groups remembered emotional better than neutral images, though memory was greatly impaired in MCI, matching with their reduce LC integrity. DISCUSSION LC integrity was associated with lower brain activity during encoding and emotional salience processing, no clear relationship with delayed memory performance was observed in MCI. ### Competing Interest Statement The authors have declared no competing interest. Wellcome Trust, 203147/Z/16/Z

Adaptive behavior in complex environments critically relies on the ability to appropriately link specific choices or actions to their outcomes. However, the neural mechanisms that support the ability to credit only those past choices believed to have caused the observed outcomes remain unclear. Here, we leverage multivariate pattern analyses of functional magnetic resonance imaging (fMRI) data and an adaptive learning task to shed light on the underlying neural mechanisms of such specific credit assignment. We find that the lateral orbitofrontal cortex (lOFC) and hippocampus (HC) code for the causal choice identity when credit needs to be assigned for choices that are separated from outcomes by a long delay, even when this delayed transition is punctuated by interim decisions. Further, we show when interim decisions must be made, learning is additionally supported by lateral frontopolar cortex (lFPC). Our results indicate that lFPC holds previous causal choices in a "pending" state until a relevant outcome is observed, and the fidelity of these representations predicts the fidelity of subsequent causal choice representations in lOFC and HC during credit assignment. Together, these results highlight the importance of the timely reinstatement of specific causes in lOFC and HC in learning choice-outcome relationships when delays and choices intervene, a critical component of real-world learning and decision making.

In decision-making, the likelihood of outcomes is often partly unknown, a form of uncertainty known as ambiguity. Previous studies report that people tend to be averse to ambiguity. However, existing models of decision making under uncertainty fail to explain why people will sometimes show an actual preference for ambiguity, particularly in contexts where reward appears unlikely. Likewise, models of ambiguity do not provide predictions regarding decisions under risk, wherein reward probabilities are explicit. Here we apply a model wherein ambiguity attitudes hinge on a Bayesian average over prior beliefs about reward probabilities, where priors correspond to alternative latent causes governing the distribution of reward. By postulating that all gambles inherently embody a degree of ambiguity, our approach can seamlessly integrate decisions made under both risk and ambiguity. We provide empirical support for predictions of this model in two behavioural experiments. Firstly, as predicted by our model, we show that ambiguity attitude seamlessly transitions from ambiguity seeking at low reward probabilities to ambiguity aversion at higher reward probabilities. Secondly, the model accounts for an empirical observation of non-linear probability weighting for both risky and ambiguous choices. Our approach highlights a continuum between risk and ambiguity, providing an integrated framework for interpreting decision-making under uncertainty.

The hippocampal-entorhinal system uses cognitive maps to represent spatial knowledge and other types of relational information. However, objects can often be characterized by different types of relations simultaneously. How does the hippocampal formation handle the embedding of stimuli in multiple relational structures that differ vastly in their mode and timescale of acquisition? Does the hippocampal formation integrate different stimulus dimensions into one conjunctive map or is each dimension represented in a parallel map? Here, we reanalyzed human functional magnetic resonance imaging data from Garvert et al. (2017) that had previously revealed a map in the hippocampal formation coding for a newly learnt transition structure. Using functional magnetic resonance imaging adaptation analysis, we found that the degree of representational similarity in the bilateral hippocampus also decreased as a function of the semantic distance between presented objects. Importantly, while both map-like structures localized to the hippocampal formation, the semantic map was located in more posterior regions of the hippocampal formation than the transition structure and thus anatomically distinct. This finding supports the idea that the hippocampal-entorhinal system forms parallel cognitive maps that reflect the embedding of objects in diverse relational structures.

Psychological therapies are among the most effective treatments for common mental health problems—however, we still know relatively little about how exactly they improve symptoms. Here, we demonstrate the power of combining theory with computational methods to parse effects of different components of cognitive-behavioral therapies onto underlying mechanisms. Specifically, we present data from a series of randomized-controlled experiments testing the effects of brief components of behavioral and cognitive therapies on different cognitive processes, using well-validated behavioral measures and associated computational models. A goal setting intervention, based on behavioral activation therapy activities, reliably and selectively reduced sensitivity to effort when deciding how to act to gain reward. By contrast, a cognitive restructuring intervention, based on cognitive therapy materials, reliably and selectively reduced the tendency to attribute negative everyday events to self-related causes. The effects of each intervention were specific to these respective measures. Our approach provides a basis for beginning to understand how different elements of common psychotherapy programs may work.

Comprehensible communication is critical for social functioning and well-being. In psychopathology, incoherent discourse is assumed to reflect disorganized thinking, which is classically linked to psychotic disorders. However, people do not express everything that comes to mind, rendering inferences from discourse to the underlying structure of thought challenging. Indeed, a range of psychopathologies are linked to self-reported disorganized thinking in the absence of language output incoherence. Here we combine natural language processing and computational modeling of free association to detail the relationship between disorganized thinking and language (in)coherence in a large sample of participants varying across different dimensions of psychopathology. Our approach allowed us to differentiate between disorganized thinking, disinhibited thought expression and deliberate creativity. We find evidence for both under-regulated and over-regulated disorganized thinking, which relate to two specific dimensions of psychopathology: self-reported eccentricity and suspiciousness. Broadly, these results underscore the theoretical progress afforded by analyzing latent dimensions underlying behavior and psychopathology.