Biology subjects

Fleming, S. M.

Publications and source records attributed to Fleming, S. M..

18 recordsLinked to original sources

bioRxiv2026

Goals shape human confidence

Confidence guides our decisions: it determines when we commit to a choice, gather more information, or change our minds. Prominent models treat confidence as a readout of the evidence in support of a decision: given the same evidence, a similar confidence level should follow, regardless of what the decision-maker is trying to achieve. Here we show instead that confidence formation is relative to the goals of the decision-maker. Across value-based and perceptual decisions in different sensory modalities, we manipulated the behavioural goal, requiring participants to select the option with either the most or the least evidence. Reversing the goal reversed the relationship between evidence and confidence: biases previously considered fixed features of a confidence computation, such as the positive evidence bias (PEB), followed the goal rather than the stimulus. We developed a new computational model, GOAL (Goal-Oriented Asymmetric Likelihood), in which evidence is weighted according to its relevance for the current goal, and validated it in behavioural and physiological (pupillometry) experiments. Our findings support a new account of metacognition in which confidence is constructed relative to the goals of the decision-maker, prioritising goal-supportive evidence.

neuroscience↗

bioRxiv2026

Preserved self-other integration during social decision making among individuals with elevated autistic traits

Autistic people can find social interactions difficult to navigate, traditionally attributed to difficulties in taking others perspectives. However, we have a limited understanding of how autistic people integrate self and other information efficiently during social decision-making. We conducted four highly powered experiments (total N = 1,621) to determine whether autistic traits affect two aspects of self-other integration during social decision making: self-bias and social basis function use. Using Bayesian analyses, we found strong support for the absence of a relationship between autistic traits and either aspect of social decision making, even after controlling for potential confounds (BF01 = 32.13 for self-bias, BF01 = 7.04 for social basis function use). Our results indicate that variations along autistic traits do not impact how people prioritise self-relevant information (self-bias) or utilize compressed social patterns of interaction (social basis function use) to guide their decisions about oneself and other people. These findings nuance the conceptualisation of social-cognitive processes across autistic traits while highlighting the need for large samples to validate null effects.

neuroscience↗

bioRxiv2025

Quantifying Rhythmic and Arrhythmic Components of Brain Activity

Brain activity comprises both rhythmic (periodic) and arrhythmic (aperiodic) components. These signal elements vary across healthy aging, and disease, and may make distinct contributions to conscious perception. Despite pioneering techniques to parameterize rhythmic and arrhythmic neural components based on power spectra, the methodology for quantifying rhythmic activity remains in its infancy. Previous work has relied on parametric estimates of rhythmic power extracted from specparam, or estimates of rhythmic power obtained after detrending neural spectra. Variation in analytical choices for isolating brain rhythms from background arrhythmic activity makes interpreting findings across studies difficult. Whether these current approaches can accurately recover the independent contribution of these neural signal elements remains to be established. Here, using simulation and parameter recovery approaches, we show that power estimates obtained from detrended spectra conflate these two neurophysiological components, yielding spurious correlations between spectral model parameters. In contrast, modelled rhythmic power obtained from specparam, which detrends the power spectra and parametrizes brain rhythms, independently recovers the rhythmic and arrhythmic components in simulated neural time series, minimising spurious relationships. We validate these methods using resting-state recordings from a large cohort. Based on our findings, we recommend modelled rhythmic power estimates from specparam for the robust independent quantification of rhythmic and arrhythmic signal components for cognitive neuroscience.

neuroscience↗

bioRxiv2024

Creating something out of nothing: Symbolic and non-symbolic representations of numerical zero in the human brain

Representing the quantity zero as a symbolic concept is considered a unique achievement of abstract human thought. Despite considerable progress in understanding the neural code supporting natural numbers, how numerical zero is encoded in the human brain remains unknown. We find that both non-symbolic empty sets (the absence of dots on a screen) and symbolic zero ( 0) occupy ordinal positions along graded neural number lines within posterior association cortex. Neural representations of zero are partly independent of numerical format, exhibiting distance effects with countable numerosities in the opposing (symbolic or non-symbolic) format. Our results show that format-invariant neural magnitude codes extend to judgements of numerical zero and help motivate theoretical accounts in which representations of symbolic zero are grounded in more basic representations of sensory absences.

neuroscience↗

bioRxiv2022

Identifying Content-Invariant Neural Signatures of Phenomenal Magnitude

Some conscious experiences are more vivid than others. Although perceptual vividness is a key component of human consciousness, how variation in this magnitude property is registered by the human brain is unknown. A striking feature of magnitudes in other psychological domains, such as number or reward, is the existence of neural magnitude codes that are independent from sensory contents. To test whether perceptual vividness similarly covaries with neural codes that are invariant to sensory content, we reanalysed existing MEG and fMRI data from two distinct studies, quantifying perceptual vividness via subjective ratings of awareness and visibility. Using representational similarity and decoding analyses, we find evidence for the existence of content-invariant neural codes for perceptual vividness distributed across visual, parietal, and frontal cortices. Our findings are consistent with a hypothesis that the subjective vividness of conscious experience is supported by neural signatures similar to magnitude codes in other cognitive domains. Significance StatementThe vividness of conscious experience varies across different stimuli and contexts. Despite being a fundamental feature of conscious awareness, exactly how perceptual vividness is encoded in the human brain remains unclear. Neural codes underpinning magnitude in reward and numerosity domains have been shown to be unchanging as stimulus identity varies. Here, we test whether components of neural activity covarying with the magnitude of perceptual vividness are similarly independent of perceptual content in analyses of MEG and fMRI data. We find dynamic, content-invariant neural signatures of vividness in visual, parietal, and frontal cortices. Our findings introduce the surprising notion that neural signatures of conscious experience might follow similar coding principles to those found for magnitude properties of entirely different cognitive domains.

neuroscience↗

bioRxiv2022

Re-evaluating frontopolar and temporoparietal contributions to detection and discrimination confidence

Previously, we identified a subset of regions where the relation between decision confidence and univariate fMRI activity was quadratic, with stronger activation for both high and low compared to intermediate levels of confidence. We further showed that, in a subset of these regions, this quadratic modulation appeared only for confidence in detection decisions about the presence or absence of a stimulus, and not for confidence in discrimination decisions about stimulus identity (Mazor, Friston & Fleming, 2021). Here, in a pre-registered follow-up experiment, we sought to replicate our original findings and identify the origins of putative detection-specific confidence signals by introducing a novel asymmetric-discrimination condition: a discrimination task with the signal-detection properties of a detection task. This task required discriminating two alternatives (two different grating tilts) but was engineered such that the distribution of perceptual evidence was asymmetric, just as in yes/no detection. We successfully replicated the quadratic modulation of subjective confidence in prefrontal, parietal and temporal cortices. However, in contrast to our original report, this quadratic effect was similar in detection and discrimination responses, but stronger in the novel asymmetric-discrimination condition. We interpret our findings as weighing against the detection-specificity of confidence signatures and speculate about possible alternative origins of a quadratic modulation of decision confidence.

neuroscience↗

bioRxiv2021

Dissociating the neural correlates of subjective visibility from those of decision confidence

A key goal of consciousness science is identifying neural signatures of being aware vs. unaware of simple stimuli. This is often investigated in the context of near-threshold detection, with reports of stimulus awareness being linked to heightened activation in a frontoparietal network. However, due to reports of stimulus presence typically being associated with higher confidence than reports of stimulus absence, these results could be explained by frontoparietal regions encoding stimulus visibility, decision confidence or both. In an exploratory analysis, we leverage fMRI data from 35 human participants (20 females) to disentangle these possibilities. We first show that, whereas stimulus identity was best decoded from the visual cortex, stimulus visibility (presence vs. absence) was best decoded from prefrontal regions. To control for effects of confidence, we then selectively sampled trials prior to decoding to equalize confidence distributions between absence and presence responses. This analysis revealed striking differences in the neural correlates of subjective visibility in prefrontal cortex regions of interest, depending on whether or not differences in confidence were controlled for. We interpret our findings as highlighting the importance of controlling for metacognitive aspects of the decision process in the search for neural correlates of visual awareness. Significance statementWhile much has been learned over the past two decades about the neural basis of visual awareness, the role of the prefrontal cortex remains a topic of debate. By applying decoding analyses to functional brain imaging data, we show that prefrontal representations of subjective visibility are contaminated by neural correlates of decision confidence. We propose a new analysis method to control for these metacognitive aspects of awareness reports, and use it to reveal confidence-independent correlates of perceptual judgments in a subset of prefrontal areas.

neuroscience↗

bioRxiv2021

Neurocomputational mechanisms of confidence in self and others

Computing confidence in ones own and others decisions is crucial for success in many social situations. While there has been substantial progress in our understanding of confidence in oneself, little is known about how we form confidence about others. Here, we address this question by asking subjects undergoing fMRI to place bets on perceptual decisions made by themselves or one of three other players of varying ability. We show that subjects compute confidence in another players decisions by combining distinct estimates of player ability and decision difficulty - allowing them to predict that a good player may get a difficult decision wrong and that a bad player may get an easy decision right. We find that this computation is supported by an interaction between brain systems traditionally implicated in decision-making (LIP) and theory of mind (TPJ, dmPFC). These results reveal a neurocomputational interplay between self- and other-related processes during social cognition.

neuroscience↗

bioRxiv2021

Metacognitive Computations for Information Search: Confidence in Control

The metacognitive sense of confidence can play a critical role in regulating decisionmaking. In particular, a lack of confidence can justify the explicit, potentially costly, instrumental acquisition of extra information that might resolve the underlying uncertainty. Recent work has suggested a statistically sophisticated tapestry behind the information governing both the making and monitoring of choices. Here, we extend this tapestry to reveal extra richness in the use of confidence for controlling information seeking. We thereby highlight how different models of metacognition can generate diverse relationships between action, confidence, and information search. More broadly, our work shows how crucial it can be to treat metacognitive monitoring and control together.

neuroscience↗

bioRxiv2020

Explaining distortions in metacognition with an attractor network model of decision uncertainty

Metacognition is the ability to reflect on, and evaluate, our cognition and behaviour. Distortions in metacognition are common in mental health disorders, though the neural underpinnings of such dysfunction are unknown. One reason for this is that models of key components of metacognition, such as decision confidence, are generally specified at an algorithmic or process level. While such models can be used to relate brain function to psychopathology, they are difficult to map to a neurobiological mechanism. Here, we develop a biologically-plausible model of decision uncertainty in an attempt to bridge this gap. We first relate the models uncertainty in perceptual decisions to standard metrics of metacognition, namely mean confidence level (bias) and the accuracy of metacognitive judgments (sensitivity). We show that dissociable shifts in metacognition are associated with isolated disturbances at higher-order levels of a circuit associated with self-monitoring, akin to neuropsychological findings that highlight the detrimental effect of prefrontal brain lesions on metacognitive performance. Notably, we are able to account for empirical confidence judgements by fitting the parameters of our biophysical model to first-order performance data, specifically choice and response times. Lastly, in a reanalysis of existing data we show that self-reported mental health symptoms relate to disturbances in an uncertainty-monitoring component of the network. By bridging a gap between a biologically-plausible model of confidence formation and observed disturbances of metacognition in mental health disorders we provide a first step towards mapping theoretical constructs of metacognition onto dynamical models of decision uncertainty. In doing so, we provide a computational framework for modelling metacognitive performance in settings where access to explicit confidence reports is not possible. Author SummaryIn this work, we use a biologically-plausible model of decision uncertainty to show that shifts in metacognition are associated with disturbances in the interaction between decision-making and higher-order uncertainty-monitoring networks. Specifically, we show that stronger uncertainty modulation is associated with decreased metacognitive bias, sensitivity, and efficiency, with no effect on perceptual sensitivity. Our approach not only enables inferences about uncertainty modulation (and, in turn, these facets of metacognition) from fits to first-order performance data alone - but also provides a first step towards relating dynamical models of decision-making to metacognition. We also relate our models uncertainty modulation to psychopathology, and show that it can offer an implicit, low-dimensional marker of metacognitive (dys)function - opening the door to richer analysis of the interaction between metacognitive performance and psychopathology from first-order performance data.

neuroscience↗

bioRxiv2020

Confirmation bias is adaptive when coupled with self-awareness

Biases in the consideration of evidence can reduce the chances of consensus between people with different viewpoints. While such altered information processing typically leads to detrimental performance in laboratory tasks, the ubiquitous nature of confirmation bias makes it unlikely that selective information processing is universally harmful. Here we suggest that confirmation bias is adaptive to the extent that agents have good metacognition, allowing them to downweight contradictory information when correct but still able to seek new information when they realise they are wrong. Using simulation-based modelling, we explore how the adaptiveness of holding a confirmation bias depends on such metacognitive insight. We find that the behavioural consequences of selective information processing are systematically affected by agents introspective abilities. Strikingly, we find that selective information processing can even improve decision-making when compared to unbiased evidence accumulation, as long as it is accompanied by good metacognition. These results further suggest that interventions which boost peoples metacognition might be efficient in alleviating the negative effects of selective information processing on issues such as political polarisation.

neuroscience↗

bioRxiv2020

The Filter Detection Task for measurement of breathing-related interoception and metacognition

The study of the brains processing of sensory inputs from within the body ( interoception) has been gaining rapid popularity in neuroscience, where interoceptive disturbances are thought to exist across a wide range of chronic physiological and psychological conditions. Here we present a task and analysis procedure to quantify specific dimensions of breathing-related interoception, including interoceptive sensitivity (accuracy), decision bias, metacognitive bias, and metacognitive performance. Two major developments address some of the challenges presented by low trial numbers in interoceptive experiments: (i) a novel adaptive algorithm to maintain task performance at 70-75% accuracy; (ii) an extended hierarchical metacognitive model to estimate regression parameters linking metacognitive performance to relevant (e.g. clinical) variables. We demonstrate the utility of the task and analysis developments, using both simulated data and three empirical datasets. This methodology represents an important step towards accurately quantifying interoceptive dimensions from a simple experimental procedure that is compatible with clinical settings.

neuroscience↗

bioRxiv2020

Private-public mappings in human prefrontal cortex

A core feature of human cognition is an ability to separate private states of mind - what we think or believe - from public actions - what we say or do. This ability is central to navigating social interactions in which different contexts often require different mappings between private states and public actions in order to minimise conflict and facilitate communication. Here we investigated how the human brain supports private-public mappings, using an interactive task which required subjects to adapt how they communicated their confidence about a perceptual decision to the social context. Univariate and multivariate analysis of fMRI data revealed that a private-public distinction is reflected in a medial-lateral division of prefrontal cortex - with lateral frontal pole (FPl) supporting the context-dependent mapping from a private sense of confidence to a public report. The concept of private-public mappings provides a promising framework for understanding flexible social behaviour.

neuroscience↗

bioRxiv2020

Developmental exposure to the organochlorine pesticide dieldrin causes male-specific exacerbation of α-synuclein-preformed fibril-induced toxicity and motor deficits

Human and animal studies have shown that exposure to the organochlorine pesticide dieldrin is associated with increased risk of Parkinsons disease (PD). Previous work showed that developmental dieldrin exposure increased neuronal susceptibility to MPTP toxicity in male C57BL/6 mice, possibly via changes in dopamine (DA) packaging and turnover. However, the relevance of the MPTP model to PD pathophysiology has been questioned. We therefore studied dieldrin-induced neurotoxicity in the -synuclein (-syn)-preformed fibril (PFF) model, which better reflects the -syn pathology and toxicity observed in PD pathogenesis. Specifically, we used a "two-hit" model to determine whether developmental dieldrin exposure increases susceptibility to -syn PFF-induced synucleinopathy. Dams were fed either dieldrin (0.3 mg/kg, every 3-4 days) or vehicle corn oil starting 1 month prior to breeding and continuing through weaning of pups at postnatal day 22. At 12 weeks of age, male and female offspring received intrastriatal PFF or control saline injections. Consistent with the male-specific increased susceptibility to MPTP, our results demonstrate that developmental dieldrin exposure exacerbates PFF-induced toxicity in male mice only. Specifically, in male offspring, dieldrin exacerbated PFF-induced motor deficits on the challenging beam and increased DA turnover in the striatum 6 months after PFF injection. However, male offspring showed neither exacerbation of phosphorylated -syn (pSyn) aggregation in the substantia nigra (SN) at 1 or 2 months post-PFF injection, nor exacerbation of PFF-induced TH and NeuN loss in the SN 6 months post-PFF injection. Collectively, these data indicate that developmental dieldrin exposure produces a male-specific increase in neuronal vulnerability to synucleinopathy. This sex-specific result is consistent with both previous work in the MPTP model, our previously reported sex-specific effects of this exposure paradigm on the male and female epigenome, and the higher prevalence and more severe course of PD in males. The novel two-hit environmental toxicant/PFF exposure paradigm established in this project can be used to explore the mechanisms by which other PD-related exposures alter neuronal vulnerability to synucleinopathy in sporadic PD. HighlightsO_LIDevelopmental dieldrin exposure increases -syn-PFF-induced motor deficits C_LIO_LIDevelopmental dieldrin exposure increases PFF-induced deficits in DA handling C_LIO_LIDevelopmental dieldrin exposure does not affect PFF-induced loss of nigral neurons C_LIO_LIThis is a novel paradigm modeling how environmental factors increase risk of PD C_LIO_LIFemale mice show PFF-induced pathology, but no PFF-induced motor deficits. C_LI

neuroscience↗

bioRxiv2019

Distinct neural contributions to metacognition for detecting (but not discriminating) visual stimuli

Being confident in whether a stimulus is present or absent (a detection judgment) is qualitatively distinct from being confident in the identity of that stimulus (a discrimination judgment). In particular, in detection, evidence can only be available for the presence, not the absence, of a target object. This asymmetry suggests that higher-order cognitive and neural processes may be required for confidence in detection, and more specifically, in judgments about absence. In a within-subject, pre-registered and performance-matched fMRI design, we observed quadratic confidence effects in frontopolar cortex for detection but not discrimination. Furthermore, in the right temporoparietal junction, confidence effects were enhanced for judgments of target absence compared to judgments of target presence. We interpret these findings as reflecting qualitative differences between the neural basis of metacognitive evaluation of detection and discrimination, potentially in line with counterfactual or higher-order models of confidence formation in detection.

neuroscience↗

bioRxiv2018

Dissociating decision confidence from evidence reliability in the human brain

Our confidence in a choice and the evidence pertaining to a choice appear to be inseparable. An emerging computational consensus is, however, that the brain should maintain separate estimates of these quantities for adaptive behavioural control. Here we devised a psychophysical task to decouple confidence in a perceptual decision from both the reliability of sensory evidence and the relation of such evidence with respect to a choice boundary. Using human fMRI, we found that an area in medial prefrontal cortex (perigenual anterior cingulate cortex, pgACC) tracked expected performance, an aggregate signature of decision confidence, whereas neural areas previously proposed to encode decision confidence instead tracked sensory reliability (posterior parietal cortex and ventral striatum) or boundary distance (pre-supplementary motor area). Supporting that information encoded by pgACC is central to a subjective sense of decision confidence, we show that pgACC activity does not simply co-vary with expected performance but is also linked to within-subject and between-subject variation in explicit confidence estimates. Our study is consistent with the proposal that the brain maintains choice-dependent and choice-independent estimates of certainty, and sheds light on why dysfunctional confidence often emerges following prefrontal lesions and/or degeneration.\n\nSignificance StatementRecent computational models propose that our sense of confidence in a choice reflects an estimate of the probability that the choice is correct. However, it has proven difficult to experimentally separate decision confidence from its component parts, such as our certainty about perceptual evidence or choice requirements. Here we devised a task to dissociate these quantities and isolate a distinct encoding of decision confidence in the medial prefrontal cortex of the human brain. We show that activity in this area not only tracks expected performance on a task but is also related to both within-subject and between-subject variation in a subjective sense of confidence. Our study illuminates why dysfunctional confidence often emerges following damage to prefrontal cortex.

neuroscience↗

bioRxiv2017

Ahr and Cyp1a2 genotypes both affect susceptibility to motor deficits following gestational and lactational exposure to polychlorinated biphenyls

Polychlorinated biphenyls (PCBs) are persistent organic pollutants known to cause adverse health effects and linked to neurological deficits in both human and animal studies. Children born to exposed mothers are at highest risk of learning and memory and motor deficits. We developed a mouse model that mimics human variation in the aryl hydrocarbon receptor and cytochrome P450 1A2 (CYP1A2) to determine if genetic variation increases susceptibility to developmental PCB exposure. In our previous studies, we found that high-affinity AhrbCyp1a2(-/-) and poor-affinity AhrdCyp1a2(-/-) knockout mice were most susceptible to learning and memory deficits following developmental PCB exposure compared with AhrbCyp1a2(+/+) wild type mice (C57BL/6J strain). Our follow-up studies focused on motor deficits, because human studies have identified PCBs as a potential risk factor for Parkinsons disease. Dams were treated with an environmentally relevant PCB mixture at gestational day 10 and postnatal day 5. We used a motor battery that included tests of nigrostriatal function as well as cerebellar function, because PCBs deplete thyroid hormone, which is essential to normal cerebellar development. There was a significant effect of PCB treatment in the rotarod test with impaired performance in all three genotypes, but decreased motor learning as well in the two Cyp1a2(-/-) knockout lines. Interestingly, we found a main effect of genotype with corn oil-treated control Cyp1a2(-/-) mice performing significantly worse than Cyp1a2(+/+) wild type mice. In contrast, we found that PCB-treated high-affinity Ahrb mice were most susceptible to disruption of nigrostriatal function with the greatest deficits in AhrbCyp1a2(-/-) mice. We conclude that differences in both genes affect susceptibility to motor deficits following developmental PCB exposure.

pharmacology and toxicology↗

bioRxiv2017

Domain-Specific Patterns of Activity Support Metacognition in Human Prefrontal Cortex

AO_SCPLOWBSTRACTC_SCPLOWMetacognition is the capacity to evaluate the success of ones own cognitive processes in various domains, e.g. memory and perception. It remains controversial whether metacognition relies on a domain-general resource that is applied to different tasks, or whether self-evaluative processes are domain-specific. Here we directly investigated this issue by examining the neural substrates engaged when metacognitive judgments were made by human participants during perceptual and memory tasks matched for stimulus and performance characteristics. By comparing patterns of functional magnetic resonance imaging (fMRI) activity while subjects evaluated their performance, we revealed both domain-specific and domain-general metacognitive representations. Multi-voxel activity patterns in anterior prefrontal cortex predicted levels of confidence in a domain-specific fashion, whereas domain-general signals predicting confidence and accuracy were found in a widespread network in the frontal and posterior midline. The demonstration of domain-specific metacognitive representations suggests the presence of a content-rich mechanism available to introspection and cognitive control.\n\nSO_SCPLOWIGNIFICANCEC_SCPLOW O_SCPLOWSTATEMENTC_SCPLOWWe use human neuroimaging to investigate processes supporting memory and perceptual metacognition. It remains controversial whether metacognition relies on a global resource that is applied to different tasks, or whether self-evaluative processes are specific to particular tasks. Using multivariate decoding methods, we provide evidence that perceptual- and memory-specific metacognitive representations cortex co-exist with generic confidence signals. Our findings reconcile previously conflicting results on the domain-specificity/generality of metacognition, and lay the groundwork for a mechanistic understanding of metacognitive judgments.

neuroscience↗