Biology subjects

Koban, L.

Publications and source records attributed to Koban, L..

12 recordsLinked to original sources

bioRxiv2026

A brain signature of vaping cue-elicited craving

E-cigarette use among young adults has grown rapidly, raising concerns about nicotine dependence and motivating a better understanding of the neurobiology of vaping. We used a cue-induced craving fMRI paradigm to develop and evaluate a brain signature of vaping cue-elicited craving, and to compare it with smoking- and food-craving signatures developed using the same analytic pipeline. Using LASSO-PCR with leave-one-subject-out cross-validation, we identified a distributed pattern of brain activity that reliably predicted normative vaping craving from an independent sample (hereafter, normative craving). The vaping-craving signature was also substantially distinct from smoking- and food-craving signatures, both spatially and functionally, and showed specificity relative to previously established craving signatures. Moreover, greater signature expression was associated with greater e-cigarette dependence severity and showed a positive, though modest, prospective association with daily puff counts over four weeks, demonstrating the signature's behavioral and clinical relevance. Together, these findings establish a cross-validated brain signature of vaping cue-elicited craving, demonstrate its differentiation from other craving-related neural patterns, and link its expression to e-cigarette dependence and real-world use. More broadly, they support the potential of this framework for developing reproducible neural markers of craving.

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bioRxiv2026

Hippocampus mediates conceptual generalization of pain modulation

Pain is strongly influenced by expectations and learning from previous experience, such as in classical conditioning. Conditioned responses and expectations can generalize to perceptually and conceptually related cues, but how generalization influences pain experience and the neurobiological processing of pain remains unclear. We used fMRI and multilevel mediation analyses to address this question. Thirty-six human participants first learned to associate two visual cues from distinct conceptual categories (e.g., animals vs. vehicles) with high or low levels of heat pain. In a subsequent phase, they were presented with novel cues (images, drawings, or words) not previously paired with pain, but which shared the conceptual category of the initial pain-predictive cues. Participants who developed explicit expectations during learning reported greater pain in response to stimuli conceptually related to high- vs. low-pain cues (generalization stimuli), demonstrating generalization of cue influences on pain. This effect was mediated by increased pain-related activity to generalization stimuli in the hippocampus, which correlated with individual differences in cue-evoked expectations. A broader network, including areas of the default mode network and striatum, also contributed to conceptual generalization of pain modulation, while threat-related regions such as the amygdala responded to generalization stimuli but did not mediate effects on pain ratings. These findings extend our understanding of expectancy-driven pain modulation by showing how conceptual processes can influence pain and its neurobiological substrates, offering new insight into placebo effects and maladaptive learning in chronic pain.

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bioRxiv2025

Brain neuromarkers predict self- and other-related mentalizing across adult, clinical, and developmental samples

Human social interactions rely on the ability to reflect on ones own and others internal states and traits--a process known as mentalizing. Impaired or altered mentalizing is a hallmark of multiple psychiatric and neurodevelopmental conditions. Yet, replicable and easily testable brain markers of mentalizing have so far been lacking. Here, we apply an interpretable machine learning approach to multiple datasets (total N=390) to train and validate fMRI brain signatures that predict i) mentalizing about the self, ii) mentalizing about another person, and iii) both types of mentalizing. Self-mentalizing and other-mentalizing classifiers had positive weights in anterior/medial and posterior/lateral brain areas, respectively, with accuracy rates of 82% and 77% for out-of-sample prediction. The classifier trained across both types of mentalizing showed 98% predictive accuracy and separated (mental) attributional from factual inferences. Classifier patterns revealed better self/other separation in healthy adults compared to individuals with schizophrenia and with increasing age in adolescence. Together, our findings reveal consistent and separable neural patterns subserving trait-based mentalizing about self and others--present at least from the age of adolescence and functionally altered in severe neuropsychiatric disorders. These mentalizing signatures hold promise as candidate neuromarkers of social-cognitive processes in different contexts and clinical conditions. Author NoteThis work was funded by a Starting Grant from the European Research Council (ERC, 101041087) to LKo, a German Academic Exchange Service (DAAD) doctoral grant and a Network of European Neuroscience Schools (NENS) exchange fellowship to DA, an R01 grant from the U.S. National Institutes of Mental Health (R01MH125414-01) to JAH and DAS, a Junior Leader Fellowship from "la Caixa" Foundation (LCF/BQ/PR22/11920017) to PFC, a Consolidator Grant from the European Research Council (ERC, 648082) to LKr, R37, R01 support from the U.S. National Institutes of Mental Health (R37MH076136 to TDW, MH116026 to TDW and L. Chang [PI], R01EB026549 to TDW and M. Lindquist [MPIs]), an NIMH grant (P50MH094258-01A1) to R. Adolphs, and a CIC Brain and Mental Health Chair from the Neurodis foundation to AT. LvdM acknowledges a European Science Foundation EURYI grant (044035001) that funded her doctoral studies (PI: A. Aleman). Views and opinions expressed are however those of the authors only and do not necessarily reflect those of the European Union or the European Research Council. Neither the European Union nor the granting authority can be held responsible for them. The funders had no role in study design, data analysis, manuscript preparation, or publication decisions.

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bioRxiv2024

A structural MRI marker predicts individual differences in impulsivity and classifies patients with behavioral-variant frontotemporal dementia from matched controls

Impulsive decision-making is a symptom across many neuropsychiatric and neurological disorders. Yet, it is still unknown whether impulsivity can be predicted based on individual differences in brain structure. Here, we used machine-learning to develop a structural MRI signature of impulsivity, tested its validity in several independent samples, and assessed its diagnostic value in patients with behavioral variant frontotemporal dementia (bvFTD)--a neurodegenerative disease characterized by high impulsivity. The resulting whole-brain grey matter density pattern--the Structural Impulsivity Signature (SIS)--showed a good prediction-outcome correlation of r=0.35 (out-of-sample, p=0.0028) in the training sample of healthy adults (N=117) and significantly predicted individual differences in impulsivity in four other, independent studies (total N=626), including healthy and clinical participants with neuropsychiatric and neurological conditions. Further, the SIS separated bvFTD patients from controls with high accuracy (81% correct, p=0.002) and predicted impulsivity-related symptom severity among patients. The spatial distribution of weights in the SIS brain pattern highlights the key role of brain regions associated with affective processing in impulsivity. Together, these results provide evidence for a new structural neuromarker of individual differences in impulsivity that can be easily applied to new samples. Future studies can further assess its predictive value towards better prevention, diagnosis and treatment of mental disorders associated with impulsivity symptoms.

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bioRxiv2024

High delay discounting relates to core symptoms and to pulvinar atrophy in frontotemporal dementia

Behavioural variant frontotemporal dementia (bvFTD) is a neurodegenerative disorder characterized by behavioural changes and atrophy in brain regions important for decision-making. Computations such as trading off between larger later (LL) and smaller sooner (SS) rewards -- called delay discounting in behavioural economics -- might be heavily impaired by bvFTD. In this cross-sectional study, our objectives were to investigate (1) whether bvFTD patients show higher delay discounting than healthy controls, (2) whether this maladaptive discounting correlates with impulsivity-related bvFTD symptoms, and (3) in which brain regions atrophy is related to bvFTDs steeper discounting. BvFTD patients (N=24) and matched controls (N=18) performed two delay discounting tasks: one with monetary rewards and one with food rewards. We compared discount rates (log(k)) in bvFTD patients and controls and tested their correlations with symptoms. We used participants structural MRI data and applied whole-brain mediation analyses to investigate brain structures mediating the effect of bvFTD on delay discounting. For both monetary and food rewards, delay discounting was significantly higher in bvFTD patients than in healthy controls. BvFTD patients higher discounting of both money and food was associated with their greater disinhibition and eating behaviour changes. Whole-brain mediation analyses revealed that (1) several brain regions (left thalamic pulvinar, left parahippocampal cortex, right temporal lobe) were predictive of steeper discounting of both money and food and (2) grey matter density in these brain regions, including most prominently the medial pulvinar, mediated the effect of bvFTD on discounting. The impulsive preference for sooner rewards captured by delay discounting might constitute a common mechanism of the behavioural symptoms of inhibition deficit and eating behaviour changes in bvFTD. Future studies could further investigate the potential role of medial pulvinar structural modifications as a transdiagnostic marker and a therapeutic target of impulsivity troubles.

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bioRxiv2023

Listen to yourself: How motivational interviewing shifts food choices and craving-related brain responses to healthier options

Changing ones habits is challenging. Motivational interviewing (MI) has been proposed as a communication-based approach to overcome this challenge. Here, we tested how change and sustain talk suggestions, elicited by MI, influenced value-based dietary decision-making and responses of a recently developed neurobiological craving signature (NCS) in female adults. We found that following change talk, compared to sustain talk, participants food choices and activity in the ventromedial prefrontal cortex were more driven by the healthiness and less by the tastiness of food. These findings were paralleled by lower NCS responses to tasty food after change compared to sustain talk. Further, following change talk, participants body mass indices moderated the NCS decoding of healthy and tasty food choices. These results show that MI can shift value-based decision-making and reduce craving-related brain marker responses to highly palatable food items. The findings contribute to a better understanding of behavioral change interventions toward healthier eating.

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bioRxiv2023

Odor imagery but not perception drives risk for food cue reactivity and increased adiposity

Mental imagery has been proposed to play a critical role in the amplification of cravings. Here we tested whether olfactory imagery drives food cue reactivity strength to promote adiposity in 45 healthy individuals. We measured odor perception, odor imagery ability, and food cue reactivity using self-report, perceptual testing, and neuroimaging. Adiposity was assessed at baseline and one year later. Brain responses to real and imagined odors were analyzed with univariate and multivariate decoding methods to identify pattern-based olfactory codes. We found that the accuracy of decoding imagined, but not real, odor quality correlated with a perceptual measure of odor imagery ability and with greater adiposity changes. This latter relationship was mediated by cue-potentiated craving and intake. Collectively, these findings establish odor imagery ability as a risk factor for weight gain and more specifically as a mechanism by which exposure to food cues promotes craving and overeating.

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bioRxiv2021

Effect sizes and test-retest reliability of the fMRI-based Neurologic Pain Signature

Identifying biomarkers that predict mental states with large effect sizes and high test-retest reliability is a growing priority for fMRI research. We examined a well-established multivariate brain measure that tracks pain induced by nociceptive input, the Neurologic Pain Signature (NPS). In N = 295 participants across eight studies, NPS responses showed a very large effect size in predicting within-person single-trial pain reports (d = 1.45) and medium effect size in predicting individual differences in pain reports (d = 0.49). The NPS showed excellent shortterm (within-day) test-retest reliability (ICC = 0.84, with average 69.5 trials/person). Reliability scaled with the number of trials within-person, with [≥]60 trials required for excellent test-retest reliability. Reliability was tested in two additional studies across 5-day (N = 29, ICC = 0.74, 30 trials/person) and 1-month (N = 40, ICC = 0.46, 5 trials/person) test-retest intervals. The combination of strong within-person correlations and only modest between-person correlations between the NPS and pain reports indicate that the two measures have different sources of between-person variance. The NPS is not a surrogate for individual differences in pain reports but can serve as a reliable measure of pain-related physiology and mechanistic target for interventions. Significance statementCurrent efforts towards translating brain biomarkers require identifying brain measures that can strongly and reliably predict outcomes of interest. We systematically examined the performance of a well-established brain activity pattern, the Neurological Pain Signature (NPS), in a large and diverse sample of participants. The NPS showed excellent reliability, and the reliability scaled with the number of trials within-person. The NPS responses showed strong correlations with pain reports at the within-person level but only modest correlations at the between-person level. The findings suggest that the NPS is not a surrogate for individual differences in pain reports but can serve as a reliable measure of a pain-related physiological target. Author NoteThis project was supported by grants R01MH076136 (T.D.W.), R01DA046064, R01EB026549, and R01DA035484. Elizabeth A. Reynolds Losin was supported by a Mentored Research Scientist Development award from National Institute On Drug Abuse of the National Institutes of Health (K01DA045735). Lauren Y. Atlas was supported in part by funding from the Intramural Research Program of the National Center for Complementary and Integrative Health. Yoni K. Ashar was supported by NCATS Grant # TL1-TR-002386. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Code for all analyses and figures is available at https://github.com/XiaochunHan/NPS_measurement_properties. Data for all analyses and figures is available at https://osf.io/v9px7/.

neuroscience↗

bioRxiv2021

An fMRI-based brain marker predicts individual differences in delay discounting

Individual differences in impatience--how much we discount future compared to immediate rewards--are associated with general life outcomes and related to substance use, psychiatric diseases, and obesity. Here, we use machine-learning on fMRI activity during an intertemporal choice task to develop a brain marker of individual differences in delay discounting. Study 1 (N=110) was used as a training and cross-validation set, resulting in significant prediction accuracy (r = 0.49) and suggesting an interplay between brain regions associated with affect, value, and cognitive control. The validity of the brain marker was replicated in an independent data set (Study 2, N=145, r = 0.45). In both studies, responses of the marker significantly differed between overweight and lean individuals. This pattern is a first step towards a generalizable neuromarker of delay discounting and a potentially transdiagnostic phenotype, which can be used as a brain-based target measure in future studies.

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bioRxiv2020

Evoked pain intensity representation is distributed across brain systems: A multistudy mega-analysis

Information is coded in the brain at different scales for different phenomena: locally, distributed across regions and networks, and globally. For pain, the scale of representation is controversial. Although generally believed to be an integrated cognitive and sensory phenomenon implicating diverse brain systems, quantitative characterizations of which regions and networks are sufficient to represent pain are lacking. In this meta-analysis (or mega-analysis) using data from 289 participants across 10 studies, we use model comparison combined with multivariate predictive models to investigate the spatial scale and location of acute pain representation. We compare models based on (a) a single most pain-predictive module, either previously identified elementary regions or a single best large-scale cortical resting-state network module; (b) selected cortical-subcortical systems related to evoked pain in prior literature ( multi-system models); and (c) a model spanning the full brain. We estimate the accuracy of pain intensity predictions using cross validation (7 studies) and subsequently validate in three independent holdout studies. All spatial scales convey information about pain intensity, but distributed, multi-system models better characterize pain representations than any individual region or network (e.g. multisystem models explain >20% more of individual subject pain ratings than the best elementary region). Full brain models showed no predictive advantage over multi-system models. These findings quantify the extent that representation of evoked pain experience is distributed across multiple cortical and subcortical systems, show that pain representation is not circumscribed by any elementary region or conical network, and provide a blueprint for identifying the spatial scale of information in other domains. Significance StatementWe define modular, multisystem and global views of brain function, use multivariate fMRI decoding to characterize pain representations at each level, and provide evidence for a multisystem representation of evoked pain. We further show that local views necessarily exclude important components of pain representation, while a global full brain representation is superfluous, even though both are viable frameworks for representing pain. These findings quantitatively juxtapose and reconcile divergent conclusions from evoked pain studies within a generalized neuroscientific framework, and provide a blueprint for investigating representational architecture for diverse brain processes.

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bioRxiv2019

A generalizable multivariate brain pattern for interpersonal guilt

Feeling guilty when we have wronged another is a crucial aspect of prosociality, but its neurobiological bases are elusive. Although multivariate patterns of brain activity show promise for developing brain measures linked to specific emotions, it is less clear whether brain activity can be trained to detect more complex social emotional states such as guilt. Here, we identified a distributed Guilt-Related Brain Signature (GRBS) across two independent neuroimaging datasets that used interpersonal interactions to evoke guilt. This signature discriminated conditions associated with interpersonal guilt from closely matched control conditions in a cross-validated training sample (N = 24; Chinese population) and in an independent test sample (N = 19; Swiss population). However, it did not respond to observed or experienced pain, or recalled guilt. Moreover, the GRBS only exhibited weak spatial similarity with other brain signatures of social affective processes, further indicating the specificity of the brain state it represents. These findings provide a step towards developing biological markers of social emotions, which could serve as important tools to investigate guilt-related brain processes in both healthy and clinical populations.

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bioRxiv2018

Multiple brain networks mediating stimulus-pain relationships in humans

The brain transforms nociceptive input into a complex pain experience comprised of sensory, affective, motivational, and cognitive components. However, it is still unclear how pain arises from nociceptive input, and which brain networks coordinate to generate pain experiences. We introduce a new high-dimensional mediation analysis technique to estimate distributed, network-level patterns mediating the relationship between stimulus intensity and pain. In a large-scale analysis of functional magnetic resonance imaging data (N=284), we identify both traditional mediators in somatosensory brain regions and additional mediators located in prefrontal, midbrain, striatal, and default-mode regions unrelated to nociception in standard analyses. The whole brain mediators are specific for pain vs. aversive sounds and are organized in five functional networks. Brain mediators explain 32% more within-subject variance of single-trial pain ratings than previous brain-based models. Our results provide a new, broader view of the networks underlying pain experience, as well as distinct targets for interventions.

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