Biology subjects

Kirsch, P.

Publications and source records attributed to Kirsch, P..

9 recordsLinked to original sources

bioRxiv2025

A Data-Driven Closed-Loop Control Approach to Drive NeuralState Transitions for Mechanistic Insight

Repetitive negative thinking (RNT) is a transdiagnostic risk factor for mood disorders, consistently associated with altered biological substrates, including functional connectivity in key brain networks. As a stable cognitive feature linked to vulnerability across disorders, RNT presents a compelling target for intervention. However, leveraging RNT as a modifiable mechanism requires a deeper understanding of its causal neural dynamics and how targeted modulation can induce adaptive change. We introduce a data-driven framework that combines dynamical system reconstruction (DSR) with model predictive control (MPC) to infer optimal control policies for transitions between resting and sad mood brain states from functional magnetic resonance imaging (fMRI) data. Using nonlinear generative DSR models trained on individuals with remitted major depressive disorder (rMDD) and matched healthy controls (HCs), we derive region-specific, state-dependent control strategies. We find that small brain regions (e.g., sgACC, NAcc) exhibit higher controllability, requiring less energy to drive state transitions. Critically, rMDD participants require less control energy than HCs to move into sad mood from rest and - unexpectedly - also to move back to rest, though the latter effect is spatially restricted. Despite comparable target attainment, rMDD participants remain closer to the sad mood distribution when returning to rest, indicating a residual negative-affect bias. Our data-driven analysis reveals elevated effective coupling in rMDD, most prominently toward (but not away from) the DLPFC. Across regions, greater coupling is associated with reduced control energy, suggesting that enhanced network influence facilitates more efficient state transitions. These results suggest dynamics in rMDD that facilitate entry into negative affect and hinders full disengagement without sustained input, highlighting closed-loop control as a tool for mechanistic insight and potentially for designing targeted neuromodulatory interventions in the future.

neuroscience↗

bioRxiv2025

Neural Convergence of Graded Belief and Binary Belief Uncertainty

Belief was defined by William James as "the psychological process or function of cognizing reality", and the recent philosophical literature has emphasized that there are two types of belief: categorical and graded. The relationship between these two belief types is complex, and it is often assumed that the degrees of graded belief reflect confidence. However, this claim has not yet been addressed empirically. In this functional magnetic resonance imaging study we let N=29 young healthy participants rate their graded belief in propositions from the conspiracy theory spectrum and estimated certainty scores from the ratings that we associated with brain activation during the presentation of the propositions. We found associations of uncertainty (i.e. negative associations with certainty scores) with brain activation in the dorsomedial prefrontal cortex, right dorsolateral prefrontal cortex, and posterior parietal cortex. The clusters in the dorsomedial and dorsolateral prefrontal cortex replicated prior associations with explicit ratings of uncertainty in binary belief decisions from a study on domain-general belief and the dorsomedial prefrontal cortex effect, localized in the anterior pre-supplementary motor area, corresponds to the concepts of Alexander Bain about the close relationship between belief and action and a central role of doubt in belief. Our results provide empirical evidence for a link between graded belief and uncertainty in human cognition and emphasize the role of doubt as a relevant process to take into account in concepts of graded belief. Highlights- Converging neural associations of graded belief levels and belief uncertainty - Conceptual replication of belief uncertainty associations with a modified procedure - Correspondence to classical concepts of belief by Alexander Bain and William James - Our results emphasize doubt as a relevant process in graded belief

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bioRxiv2023

Neural Correlates of Self-Referential Belief Processes

BackgroundBelief processing as well as self-referential processing have both been consistently associated with cortical midline structures. In addition, seminal neuroimaging papers have implicated cortical regions such as the vmPFC in general belief processing. However, the neural correlates of self-referential belief are yet to be investigated in functional magnetic resonance imaging (fMRI). MethodsIn this fMRI study, we presented 120 statements with trait adjectives as target words to N=27 young healthy participants and asked them to judge whether they believed that these trait adjectives applied to themselves, a self-chosen close person, or a public person (the German chancellor at that time). Participants subsequently rated how certain (0-100%) they were in their judgment. ResultsAs expected, self-referential processing evoked a large cluster in the vmPFC, ACC and dmPFC. For belief, we found an activated cluster in the vmPFC during statement presentation, which partly overlapped with the cluster for self-referential processing. The cluster for self-belief vs. disbelief was similar in location and size to the cluster for general belief processing and distinct from the cluster for self-referential processing. We also found dmPFC activation for uncertainty in belief evaluations. DiscussionWe successfully replicated vmPFC involvement in belief processing and found a common neural correlate for belief and self-belief in the vmPFC. The activation clusters for self-belief versus self-referential processing were distinct, implying distinct neural processes. This insight will prove relevant for investigations in clinical populations with aberrant (self-)belief processing. Furthermore, we replicated the role of the dmPFC in uncertainty, supporting a dual neural process model of belief and certainty.

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bioRxiv2023

Reactivation strength during cued recall is modulated by graph distance within cognitive maps

Declarative memory retrieval is thought to involve reinstatement of neuronal activity patterns elicited and encoded during a prior learning episode. Furthermore, it is suggested that two mechanisms operate during reinstatement, dependent on task demands: individual memory items can be reactivated simultaneously as a clustered occurrence or, alternatively, replayed sequentially as temporally separate instances. In the current study, participants learned associations between images that were embedded in a directed graph network and retained this information over a brief 8-minute consolidation period. During a subsequent cued recall session, participants retrieved the learned information while undergoing magnetoencephalographic (MEG) recording. Using a trained stimulus decoder, we found evidence for clustered reactivation of learned material. Reactivation strength of individual items during clustered reactivation decreased as a function of increasing graph distance, an ordering present solely for successful retrieval but not for retrieval failure. In line with previous research, we found evidence that sequential replay was dependent on retrieval performance and was most evident in low performers. The results provide evidence for distinct performance-dependent retrieval mechanisms with graded clustered reactivation emerging as a plausible mechanism to search within abstract cognitive maps.

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bioRxiv2022

Neural responses to instructed positive couple interaction: An fMRI study on compliment sharing

Love is probably the most fascinating feeling that a person ever experiences. However, little is known about what is happening in the brains of a romantic couple -the central and most salient relationship during adult age- while they are particularly tender and exchanging loving words with one another. To gain insight into nearly natural couple interaction, we collected data from N=84 individuals (including N=43 heterosexual couples) simultaneously in two functional magnetic resonance imaging scanners, while they sent and received compliments, i.e. short messages about what they liked about each other and their relationship. Activation patterns during compliment sharing in the individuals revealed a broad pattern of activated brain areas known to be involved in empathy and reward processing. Notably, the ventral striatum, including parts of the putamen, was activated particularly when selecting messages for the partner. This provides initial evidence that giving a verbal treat to a romantic partner seems to involve neural reward circuitry in the basal ganglia. These results can have important implications for the neurobiological mechanisms protecting and stabilizing romantic relationships, which build a highly relevant aspect of human life and health.

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bioRxiv2021

Brain-Wide Inferiority and Equivalence Tests in fMRI Group Analyses: Selected Applications

Null hypothesis significance testing is the major statistical procedure in the field of fMRI, but provides only a rather limited picture of the effects in a data set. When sample size and power is low relying only on strict significance testing may lead to a host of false negative findings. In contrast, with very large data sets virtually every voxel might become significant. It is thus desirable to complement significance testing with procedures like inferiority and equivalence tests that allow to formally compare effect sizes within and between data sets and offer novel approaches to obtain insight into fMRI data. The major component of these tests are estimates of standardized effect sizes and their confidence intervals. Here we show how Hedges g, the bias corrected version of Cohens d, and its confidence interval can be obtained from SPM t maps. We then demonstrate how these values can be used to evaluate whether non-significant effects are really statistically smaller than significant effects to obtain "regions of undecidability" within a data set, and to test for the replicability and lateralization of effects. This method allows the analysis of fMRI data beyond point estimates enabling researchers to take measurement uncertainty into account when interpreting their findings.

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bioRxiv2019

The genetic architecture of human brainstem structures and their involvement in common brain disorders

Brainstem regions support critical bodily functions, yet their genetic architectures and involvement in brain disorders remain understudied. Here, we examined volumes of brainstem structures using magnetic resonance imaging in 43,353 individuals. In 27,034 genotyped healthy participants, we identified 16 genetic loci associated with whole brainstem volume and 10, 23, 3, and 9 loci associated with volumes of the midbrain, pons, superior cerebellar peduncle, and medulla oblongata, respectively. These loci were mapped to 305 genes, including genes linked to brainstem development and common brain disorders. We detected genetic overlap between the brainstem volumes and eight psychiatric and neurological disorders. Using imaging data from 16,319 additional individuals, we observed differential volume alterations in schizophrenia, bipolar disorder, multiple sclerosis, mild cognitive impairment, dementia, and Parkinsons disease. Together, our results provide new insights into the genetic underpinnings of brainstem structures and support their involvement in common brain disorders.

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bioRxiv2019

Phantom limb pain intensity is associated with generalized hyperalgesia

After limb amputation, most amputees suffer from phantom limb pain (PLP). The mechanisms underlying this condition are complex and insufficiently understood. Altered somatosensory sensitivity (either heightened or lowered) might contribute to PLP. Recent studies have tested this assumption but mainly focused on the residual limb. However, altered somatosensation in PLP might be generalized. In this study, we applied quantitative sensory testing to 37 unilateral upper-limb amputees (23 with PLP, 14 without PLP) and 19 healthy controls. We assessed thresholds to heat pain (HPT), pressure pain (PPT), warmth detection (WDT), and two-point discrimination (2PDT) at the residual limb, a homologous point and the thenar of the intact limb, and both corners of the mouth. We did not find significant differences in any of the thresholds between the groups. However, higher PLP intensity was significantly related to lower HPT at all measured body sites except for the residual limb. At the residual limb, lower HPT were observed in more distal amputations and in amputees showing a higher degree of prosthesis use. Although WDT did by itself not significantly correlate with PLP intensity at any of the body sites, multiple regression analysis showed the highest multiple correlations with PLP intensity for a combination of high WDT and low HPT at the corners of the mouth. In this model, the combination of HPT and WDT shared 58% of the variance with PLP intensity. Other factors of potential importance, especially residual limb pain, were not significantly associated to any sensory threshold. We conclude that the intensity, but not the presence of PLP is positively associated with higher heat pain sensitivity. Since this association was observed at various, distributed body sites, we suggest that central mechanisms might be underlying such generalized hyperalgesia.

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bioRxiv2018

The dark side of the mean: brain structural heterogeneity in schizophrenia and its polygenic risk.

ImportanceBetween-subject variability in brain structure is determined by gene-environment interactions, possibly reflecting differential sensitivity to environmental and genetic perturbations. Magnetic resonance imaging (MRI) studies have revealed thinner cortices and smaller subcortical volumes in patients. However, such group-level comparisons may mask considerable within-group heterogeneity, which has largely remained unnoticed in the literature\n\nObjectiveTo compare brain structural variability between individuals with SZ and healthy controls (HC) and to test if respective variability reflects the polygenic risk for SZ (PRS) in HC.\n\nDesign, Setting, and ParticipantsWe compared MRI derived cortical thickness and subcortical volumes between 2,010 healthy controls and 1,151 patients with SZ across 16 cohorts. Secondly, we tested for associations between PRS and MRI features in 12,490 participants from UK Biobank.\n\nMain Outcomes and MeasuresWe modeled mean and dispersion effects of SZ and PRS using double generalized linear models. We performed vertex-wise analyses for thickness, and region-of-interest analysis for cortical, subcortical and hippocampal subfield volumes. Follow-up analyses included within-sample analysis, controlling for intracranial volume and population covariates, test of robustness of PRS threshold, and outlier removal.\n\nResultsCompared to controls, patients with SZ showed higher heterogeneity in cortical thickness, cortical and ventricle volumes, and hippocampal subfields. Higher PRS was associated with thinner frontal and temporal cortices, as well as smaller left CA2/3, but was not significantly associated with dispersion.\n\nConclusion and relevanceSZ is associated with substantial brain structural heterogeneity beyond the mean differences. These findings possibly reflect higher differential sensitivity to environmental and genetic perturbations in patients, supporting the heterogeneous nature of SZ. Higher PRS for SZ was associated with thinner fronto-temporal cortices and smaller subcortical volumes, but there were no significant associations with the heterogeneity in these measures, i.e. the variability among individuals with high PRS were comparable to the variability among individuals with low PRS. This suggests that brain variability in SZ results from interactions between environmental and genetic factors that are not captured by the PGR. Factors contributing to heterogeneity in fronto-temporal cortices and hippocampus are thus key to further our understanding of how genetic and environmental factors shape brain biology in SZ.\n\nKey PointsQuestion: Is schizophrenia and its polygenic risk associated with brain structural heterogeneity in addition to mean changes?\n\nFindings: In a sample of 1151 patients and 2010 controls, schizophrenia was associated with increased heterogeneity in fronto-temporal thickness, cortical, ventricle, and hippocampal volumes, besides robust reductions in mean estimates. In an independent sample of 12,490 controls, polygenic risk for schizophrenia was associated with thinner fronto-temporal cortices and smaller CA2/3 of the left hippocampus, but not with heterogeneity.\n\nMeaning: Schizophrenia is associated with increased inter-individual differences in brainstructure, possibly reflecting clinical heterogeneity, gene-environment interactions, or secondary disease factors.

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