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Decision cost hypersensitivity underlies Huntington's disease apathy.
The neuropsychiatric syndrome of apathy is now recognized to be a common and disabling condition in Huntington's disease (HD). However, the mechanisms underlying it are poorly understood. One way to investigate apathy is to utilise a theoretical framework of normal motivated behaviour, to determine where breakdown has occurred in people with this behavioural disruption. A fundamental computation underlying motivated, goal-directed behaviour across species is weighing up the costs and rewards associated with actions. Here, we asked whether people with apathy are more sensitive to costs of actions (physical effort and time delay), less sensitive to rewarding outcomes, or both. Based on the unique anatomical substrates associated with HD pathology, we hypothesised that a general hypersensitivity to costs would underpin HD apathy. Genetically confirmed carriers of the expanded Huntingtin gene (premanifest to mild motor manifest disease (n=53) were compared to healthy controls (n = 38). Participants performed a physical effort-based decision-making task (Apple Gathering Task) and a delay discounting task (Money Choice Questionnaire). Choice data was analysed using linear regression and drift diffusion models that also accounted for the time taken to make decisions. Apathetic people with HD accepted fewer offers overall on the Apple Gathering Task, specifically driven by increased sensitivity to physical effort costs, and not explained by motor severity, mood, cognition, or medication. Drift diffusion modelling provided further evidence of effort hypersensitivity, with apathy associated with a faster drift rate towards rejecting offers as a function of varying effort. Increased delay sensitivity was also associated with apathy, both when analysing raw choice and also drift rate, where there was moderate evidence of HD apathy drifting faster towards the immediately available (low cost) option. Furthermore, the effort and delay sensitivity parameters from these tasks were positively correlated. The results demonstrate a clear mechanism for apathy in HD, cost hypersensitivity, which manifests in both the effort and time costs associated with actions towards rewarding goals. This suggests that HD pathology may cause a domain-general disruption of cost processing, which is distinct to apathy occurrence in other brain disorders, and may require different therapeutic approaches.
Analysis of the senescence-associated cell surfaceome reveals potential senotherapeutic targets.
The accumulation of senescent cells is thought to play a crucial role in aging-associated physiological decline and the pathogenesis of various age-related pathologies. Targeting senescence-associated cell surface molecules through immunotherapy emerges as a promising avenue for the selective removal of these cells. Despite its potential, a thorough characterization of senescence-specific surface proteins remains to be achieved. Our study addresses this gap by conducting an extensive analysis of the cell surface proteome, or "surfaceome", in senescent cells, spanning various senescence induction regimes and encompassing both murine and human cell types. Utilizing quantitative mass spectrometry, we investigated enriched cell surface proteins across eight distinct models of senescence. Our results uncover significant changes in surfaceome expression profiles during senescence, highlighting extensive modifications in cell mechanics and extracellular matrix remodeling. Our research also reveals substantive heterogeneity of senescence, predominantly influenced by cell type and senescence inducer. A key discovery of our study is the identification of four unique cell surface proteins with extracellular epitopes. These proteins are expressed in senescent cells, absent or present at low levels in their proliferating counterparts, and notably upregulated in tissues from aged mice and an Alzheimer's disease mouse model. These proteins stand out as promising candidates for senotherapeutic targeting, offering potential pathways for the detection and strategic targeting of senescent cell populations in aging and age-related diseases.
Glutamate dynamics and BOLD response during OCD symptom provocation in the lateral occipital cortex: A 7 Tesla fMRI-fMRS study.
Obsessive-compulsive disorder (OCD) is linked with dysfunction in frontal-striatal, fronto-limbic, and visual brain regions. Research using proton magnetic resonance spectroscopy (1H-MRS) suggests that altered neurometabolite levels, like glutamate, may contribute to this dysfunction. However, static neurometabolite levels in OCD patients have shown inconsistent results, likely due to previous studies' limited focus on neurometabolite dynamics. We employ functional MRS (fMRS) and functional magnetic resonance imaging (fMRI) to explore these dynamics and brain activation during OCD symptom provocation. We utilized a combined 7-tesla fMRI-fMRS setup to examine task-related BOLD response and glutamate changes in the lateral occipital cortex (LOC) of 30 OCD participants and 34 matched controls during an OCD-specific symptom provocation task. The study examined main effects and between-group differences in brain activation and glutamate levels during the task. A whole sample task-effects analysis on data meeting predefined quality criteria showed significant glutamate increases (n = 41 (22 OCD, 19 controls), mean change: 3.2 %, z = 3.75, p
Dataset factors associated with age-related changes in brain structure and function in neurodevelopmental conditions.
With brain structure and function undergoing complex changes throughout childhood and adolescence, age is a critical consideration in neuroimaging studies, particularly for those of individuals with neurodevelopmental conditions. However, despite the increasing use of large, consortium-based datasets to examine brain structure and function in neurotypical and neurodivergent populations, it is unclear whether age-related changes are consistent between datasets and whether inconsistencies related to differences in sample characteristics, such as demographics and phenotypic features, exist. To address this, we built models of age-related changes of brain structure (regional cortical thickness and regional surface area; N = 1218) and function (resting-state functional connectivity strength; N = 1254) in two neurodiverse datasets: the Province of Ontario Neurodevelopmental Network and the Healthy Brain Network. We examined whether deviations from these models differed between the datasets, and explored whether these deviations were associated with demographic and clinical variables. We found significant differences between the two datasets for measures of cortical surface area and functional connectivity strength throughout the brain. For regional measures of cortical surface area, the patterns of differences were associated with race/ethnicity, while for functional connectivity strength, positive associations were observed with head motion. Our findings highlight that patterns of age-related changes in the brain may be influenced by demographic and phenotypic characteristics, and thus future studies should consider these when examining or controlling for age effects in analyses.
Sex chromosomes and hormones independently influence healthy brain development but act similarly after cranial radiation.
The course of normal development and response to pathology are strongly influenced by biological sex. For instance, female childhood cancer survivors who have undergone cranial radiation therapy (CRT) tend to display more pronounced cognitive deficits than their male counterparts. Sex effects can be the result of sex chromosome complement (XX vs. XY) and/or gonadal hormone influence. The contributions of each can be separated using the four-core genotype mouse model (FCG), where sex chromosome complement and gonadal sex are decoupled. While studies of FCG mice have evaluated brain differences in adulthood, it is still unclear how sex chromosome and sex hormone effects emerge through development in both healthy and pathological contexts. Our study utilizes longitudinal MRI with the FCG model to investigate sex effects in healthy development and after CRT in wildtype and immune-modified Ccl2-knockout mice. Our findings in normally developing mice reveal a relatively prominent chromosome effect prepubertally, compared to sex hormone effects which largely emerge later. Spatially, sex chromosome and hormone influences were independent of one another. After CRT in Ccl2-knockout mice, both male chromosomes and male hormones similarly improved brain outcomes but did so more separately than in combination. Our findings highlight the crucial role of sex chromosomes in early development and identify roles for sex chromosomes and hormones after CRT-induced inflammation, highlighting the influences of biological sex in both normal brain development and pathology.
A Cognitive-Behavioral Model of Apathy in Parkinson's Disease.
Apathy is recognized to be a common, disabling syndrome that occurs across a range of psychiatric and neurological conditions, including Parkinson's disease. It can have a significant impact on quality of life, both for people affected and those around them. Currently, there are no established, evidence-based treatments for this debilitating syndrome. Assessment and treatment have been complicated by overlaps with depression and anhedonia, as well as a lack of understanding of the underlying mechanisms. Emerging lines of evidence conceptualize apathy as a reduction of motivation associated with disordered effort-based decision-making and dysfunction of distinct neural circuitry between the basal ganglia and medial prefrontal cortex. Here, we introduce a novel cognitive-behavioral framework that can inform a clinician's conceptualization and treatment of apathy, using cognitive-behavioral therapy (CBT) techniques. We focus on people with Parkinson's disease in our model, but our approach is transdiagnostic and can be applied to other conditions. It considers both individual targets for therapy as well as maintenance and intervention at a systemic level. The generalizability and parsimony of the framework provides a structured assessment and formulation of apathy, while also allowing clinicians to remain sensitive to other neuropsychiatric symptoms that can occur alongside apathy, such as depression and anxiety.
The influence of negative and affective symptoms on anhedonia self-report in schizophrenia.
BACKGROUND: Anhedonia, a symptom prevalent in schizophrenia patients, is thought to arise either within negative symptomatology or from secondary sources, such as depression. The common co-occurrence of these diseases complicates the assessment of anhedonia in schizophrenia. METHOD: In a sample of 40 outpatients with chronic schizophrenia, we explored both the validity of the Snaith-Hamilton Pleasure Scale (SHAPS) self-report for anhedonia assessment and those factors influenced its scoring. We assessed negative symptoms using the Brief Negative Symptom Scale (BNSS), depression symptoms using the Calgary Depression Scale for Schizophrenia (CDSS) and cognitive impairment using the Brief Assessment of Cognition in Schizophrenia (BACS), before exploring associations between these scales. RESULTS: The SHAPS was validated for use in schizophrenia. SHAPS scores were not associated with negative symptoms or cognitive impairment, but were linked to a single Depression symptom: Hopelessness (r = 0.52, p
Negative symptoms and cognitive impairment are associated with distinct motivational deficits in treatment resistant schizophrenia.
BACKGROUND: Motivational deficits are a central feature of the negative syndrome in schizophrenia. They have consistently been associated with reduced willingness to expend physical effort in return for monetary rewards on effort based decision making (EBDM) paradigms. Nevertheless, the mechanisms underlying such altered performance are not well characterised, and it remains unclear if they are driven purely by negative symptoms, or also in part by cognitive impairment, antipsychotic treatment or even positive symptoms. Here we investigated the impact of all these factors using a paradigm that has not previously been used to measure EBDM in schizophrenia. METHODS: Forty treatment resistant schizophrenia (TRS) patients on clozapine and matched controls (N = 80) completed a well validated EBDM task which offers monetary rewards in return for physical effort. Choice and reaction time data was analysed using logistic regressions, as well as Bayesian hierarchical drift diffusion modelling (HDDM). Behavioural parameters were compared between groups and their association with negative symptoms, cognitive function and serum clozapine levels were assessed. RESULTS: Overall, TRS patients accepted significantly less offers than controls during effort-based decision making, suggesting they were less motivated. They demonstrated reduced sensitivity to increasing rewards, but surprisingly were also less averse to increasing effort. Despite a positive correlation between negative symptoms and cognitive function in TRS, reward sensitivity was associated only with cognitive performance. In contrast, reduced effort aversion correlated with negative symptom severity. Clozapine levels and positive symptoms were not associated with either behavioural parameter. CONCLUSION: Motivational deficits in TRS are characterised by both diminished reward sensitivity and reduced effort aversion during EBDM. Cognitive dysfunction and negative symptom severity account for distinct aspects of these behavioural changes, despite positive associations between themselves. Overall, these findings demonstrate that negative symptoms and cognitive impairment have significant independent contributions to EBDM in TRS, thereby opening the possibility of individualised treatment targeting these mechanisms to improve motivation.
Dissociable effects of mild COVID-19 on short- and long-term memories.
Recent studies have highlighted the presence of cognitive deficits following COVID-19 that persist beyond acute infection, regardless of the initial disease severity. Impairments in short- and long-term memory are among the core deficits reported by patients and observed in objective tests of memory performance. We aimed to extend previous studies by examining performance in a task that allows us to directly compare and contrast memories at different timescales. More specifically, we assessed both short- and long-term memories for contextual-spatial associations encoded during a common session and probed at different durations using an equivalent task in non-hospitalized individuals recovering from mild COVID-19 compared to healthy controls. The approach equated all aspects of memory materials and response demands, isolating performance changes resulting only from memory timescales and thus allowing us to quantify the impact of COVID-19 on cognition. In addition to providing measures of accuracy and response times, the task also provided a sensitive continuous readout of the precision of memory representations, specifically by examining the resolution with which spatial locations were retained in memory. The results demonstrated selective impairment of long-term memory performance in individuals recovering from mild COVID-19 infection. Short-term memory performance remained comparable to healthy controls. Specifically, poor precision of long-term memory representations was demonstrated, which improved with days since diagnosis. No such relationship was observed for short-term memory performance. Our findings reveal a specific impairment to the precision of spatial-contextual long-term memory representations in individuals recovering from mild COVID-19 and demonstrate evidence of recovery in long-term memory over time. Further, the experimental design provides a carefully controlled and sensitive framework to assess memory across different durations with the potential to provide more detailed phenotyping of memory deficits associated with COVID-19 in general.
Causal role of a neural system for separating and selecting multidimensional social cognitive information.
People are multi-faceted, typically good at some things but bad at others, and a critical aspect of social judgement is the ability to focus on those traits relevant for the task at hand. However, it remains unknown how the brain supports such context-dependent social judgement. Here, we examine how people represent multidimensional individuals, and how the brain extracts relevant information and filters out irrelevant information when comparing individuals within a specific dimension. Using human fMRI, we identify distinct neural representations in dorsomedial prefrontal cortex (dmPFC) and anterior insula (AI) supporting separation and selection of information for context-dependent social judgement. Causal evaluation using non-invasive brain stimulation shows that AI disruption alters the impact of relevant information on social comparison, whereas dmPFC disruption only affects the impact of irrelevant information. This neural circuit is distinct from the one supporting integration across, as opposed to separation of, different features of a multidimensional cognitive space.
Exploration in 4-year-old children is guided by learning progress and novelty.
Humans are driven by an intrinsic motivation to learn, but the developmental origins of curiosity-driven exploration remain unclear. We investigated the computational principles guiding 4-year-old children's exploration during a touchscreen game (N = 102, F = 49, M = 53, primarily white and middle-class, data collected in the Netherlands from 2021-2023). Children guessed the location of characters that were hiding following predictable (yet noisy) patterns. Children could freely switch characters, which allowed us to quantify when they decided to explore something different and what they chose to explore. Bayesian modeling of their responses revealed that children selected activities that were more novel and offered greater learning progress (LP). Moreover, children's interest in making LP correlated with better learning performance. These findings highlight the importance of novelty and LP in guiding children's exploration.
The impact of COVID-19 on people with epilepsy: Global results from the coronavirus and epilepsy study.
OBJECTIVE: To characterize the experience of people with epilepsy and aligned healthcare workers (HCWs) during the first 18 months of the COVID-19 pandemic and compare experiences in high-income countries (HICs) with non-HICs. METHODS: Separate surveys for people with epilepsy and HCWs were distributed online in April 2020. Responses were collected to September 2021. Data were collected for COVID-19 infections, the effect of COVID-related restrictions, access to specialist help for epilepsy (people with epilepsy), and the impact of the pandemic on work productivity (HCWs). The frequency of responses for non-HICs and HICs were compared using non-parametric Chi-square tests. RESULTS: Two thousand one hundred and five individuals with epilepsy from 53 countries and 392 HCWs from 26 countries provided data. The same proportion of people with epilepsy in non-HICs and HICs reported COVID-19 infection (7%). Those in HICs were more likely to report that COVID-19 measures had affected their health (32% vs. 23%; p
Replay-triggered brain-wide activation in humans.
The consolidation of discrete experiences into a coherent narrative shapes the cognitive map, providing structured mental representations of our experiences. In this process, past memories are reactivated and replayed in sequence, fostering hippocampal-cortical dialogue. However, brain-wide engagement coinciding with sequential reactivation (or replay) of memories remains largely unexplored. In this study, employing simultaneous EEG-fMRI, we capture both the spatial and temporal dynamics of memory replay. We find that during mental simulation, past memories are replayed in fast sequences as detected via EEG. These transient replay events are associated with heightened fMRI activity in the hippocampus and medial prefrontal cortex. Replay occurrence strengthens functional connectivity between the hippocampus and the default mode network, a set of brain regions key to representing the cognitive map. On the other hand, when subjects are at rest following learning, memory reactivation of task-related items is stronger than that of pre-learning rest, and is also associated with heightened hippocampal activation and augmented hippocampal connectivity to the entorhinal cortex. Together, our findings highlight a distributed, brain-wide engagement associated with transient memory reactivation and its sequential replay.
Neural mechanisms of credit assignment for delayed outcomes during contingent learning.
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 (FPl). Our results indicate that FPl 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.
DISENTANGLEMENT WITH BIOLOGICAL CONSTRAINTS: A THEORY OF FUNCTIONAL CELL TYPES
Neurons in the brain are often finely tuned for specific task variables. Moreover, such disentangled representations are highly sought after in machine learning. Here we mathematically prove that simple biological constraints on neurons, namely nonnegativity and energy efficiency in both activity and weights, promote such sought after disentangled representations by enforcing neurons to become selective for single factors of task variation. We demonstrate these constraints lead to disentanglement in a variety of tasks and architectures, including variational autoencoders. We also use this theory to explain why the brain partitions its cells into distinct cell types such as grid and object-vector cells, and also explain when the brain instead entangles representations in response to entangled task factors. Overall, this work provides a mathematical understanding of why single neurons in the brain often represent single human-interpretable factors, and steps towards an understanding task structure shapes the structure of brain representation.
ACTIONABLE NEURAL REPRESENTATIONS: GRID CELLS FROM MINIMAL CONSTRAINTS
To afford flexible behaviour, the brain must build internal representations that mirror the structure of variables in the external world.For example, 2D space obeys rules: the same set of actions combine in the same way everywhere (step north, then south, and you won't have moved, wherever you start).We suggest the brain must represent this consistent meaning of actions across space, as it allows you to find new short-cuts and navigate in unfamiliar settings.We term this representation an 'actionable representation'.We formulate actionable representations using group and representation theory, and show that, when combined with biological and functional constraints-non-negative firing, bounded neural activity, and precise coding-multiple modules of hexagonal grid cells are the optimal representation of 2D space.We support this claim with intuition, analytic justification, and simulations.Our analytic results normatively explain a set of surprising grid cell phenomena, and make testable predictions for future experiments.Lastly, we highlight the generality of our approach beyond just understanding 2D space.Our work characterises a new principle for understanding and designing flexible internal representations: they should be actionable, allowing animals and machines to predict the consequences of their actions, rather than just encode.