arxiv: 2605.00465 · v1 · submitted 2026-05-01 · 🧬 q-bio.NC

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Intrinsic Brain Networks Underlying the Experience and Expression of Subclinical Anxiety

Shruti Kinger , Mrinmoy Chakrabarty

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Pith reviewed 2026-05-09 15:14 UTC · model grok-4.3

classification 🧬 q-bio.NC

keywords subclinical anxietyresting-state functional connectivityintrinsic brain networksanterior cingulate cortexinsulahippocampustwo-system frameworkthreat anticipation

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The pith

Subclinical anxiety's behavioral, physiological, and subjective facets map onto partially dissociable intrinsic brain networks observable at rest.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper examines whether the behavioral, physiological, and subjective components of subclinical anxiety are supported by distinct intrinsic brain networks during rest, guided by the two-system framework. In a sample of 47 young adults, participants completed a threat anticipation task and self-report measures, which were then correlated with resting-state functional connectivity between specific regions of interest. Behavioral vigilance under uncertain threat linked to stronger anterior cingulate cortex-insula connectivity, physiological arousal to anterior cingulate-orbitofrontal cortex connectivity, and subjective anxiety severity to hippocampus-insula connectivity, with these patterns surviving sequential correction. The results extend earlier task-based findings by showing that these anxiety dimensions can be differentiated in resting-state data alone. This separation implies that the components may be tracked independently in the brain even without active threat processing.

Core claim

The study reports that higher subclinical anxiety levels were associated with faster behavioral responses under temporally uncertain threat, but not with changes in skin conductance response. At the neural level, three specific resting-state functional connectivity patterns emerged after correction: behavioral modulation tied to anterior cingulate cortex-insula connectivity, physiological modulation tied to anterior cingulate cortex-orbitofrontal cortex connectivity, and subjective anxiety tied to hippocampus-insula connectivity. The authors conclude that these findings demonstrate partially dissociable yet overlapping intrinsic networks for the different facets of subclinical anxiety, and a

What carries the argument

Region-of-interest resting-state functional connectivity (rsFC) analysis between anterior cingulate cortex, insula, orbitofrontal cortex, and hippocampus, correlated with separate behavioral, physiological, and subjective anxiety measures.

If this is right

The three anxiety components can be tracked independently through resting-state scans without requiring an active threat task.
Early neural markers for subclinical anxiety may be identifiable via these distinct connectivity patterns.
Interventions could potentially target one facet of anxiety without necessarily affecting the others if the networks are dissociable.
Prior task-based observations of anxiety network differences generalize to intrinsic connectivity at rest.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

If these resting-state patterns hold, then large-scale population screening for anxiety risk could rely on brief resting scans rather than lengthy behavioral tasks.
The partial overlap among networks suggests that some individuals might show mixed anxiety profiles where one component dominates due to stronger specific connections.
Testing whether these same connectivity differences appear in diagnosed clinical anxiety samples would clarify if the subclinical patterns scale to disorder-level expression.

Load-bearing premise

The assumption that the specific connectivity patterns observed in this modest sample directly and specifically support the distinct expression of each anxiety component rather than reflecting general individual differences or other unrelated factors.

What would settle it

A larger replication study finding that none of the three reported rsFC patterns remain significantly associated with their corresponding anxiety component after family-wise error correction.

Figures

Figures reproduced from arXiv: 2605.00465 by Mrinmoy Chakrabarty, Shruti Kinger.

**Figure 1.** Figure 1: Experiment Design. (A–D) Each trial began with a fixation cross, followed by a cue indicating condition (X = Threat; O = Safety) presented for 2 s. Hints were presented below the cue to indicate the type of condition (ut = Uncertain Threat; us = Uncertain Safety; ct = Certain Threat; cs = Certain Safety). The cue was followed by an anticipation window lasting 4-6 s pseudorandomly, during which integers wer… view at source ↗

**Figure 2.** Figure 2: Association between anxiety and behavioural response (A-D). Each marker represents one participant, and the trend line represents the least square regression line for A) Uncertain Threat, B) Uncertain Safety, C) Certain Threat, and D) Certain Safety. *p < 0.05 for Uncertain Threat view at source ↗

**Figure 3.** Figure 3: Association between anxiety-modulated behavioural responses and rsFC. (A) Regions from Julich Brain Atlas were visualised using the BrainNet Viewer toolbox (Xia et al., view at source ↗

**Figure 4.** Figure 4: Association between anxiety-modulated physiological response and rsFC. (A) Regions sourced from Julich Brain Atlas were visualised using the BrainNet Viewer toolbox view at source ↗

**Figure 5.** Figure 5: Association between subjective experience of anxiety and rsFC. (A) view at source ↗

read the original abstract

Anxiety includes behavioural, physiological, and subjective components that do not always align, and it remains unclear whether these dimensions are supported by distinct intrinsic brain networks. Guided by the two-system framework, we tested whether resting-state functional connectivity (rsFC) differentiates these components in subclinical anxiety. Forty-seven young adults spanning a range of subclinical anxiety levels completed a threat anticipation task measuring behavioral responses (reaction time) and physiological arousal (skin conductance), along with the NIH Fear-Affect self-report of anxiety severity. These measures were related to rsFC using region-of-interest analyses. Higher subclinical anxiety was associated with faster responses under temporally uncertain threat, consistent with increased vigilance, while no association was found with physiological arousal. At the neural level, three connectivity patterns emerged and remained significant after sequential family-wise error correction. Behavioural responses modulated by subclinical anxiety were linked to stronger connectivity between the anterior cingulate cortex (ACC) and insula. Physiological modulation was associated with connectivity between the ACC and orbitofrontal cortex (OFC). Subjective anxiety was associated with increased connectivity between the hippocampus and insula. Additional connections were observed but did not survive stricter correction. Overall, the findings indicate that behavioural, physiological, and subjective aspects of subclinical anxiety map onto partially dissociable but overlapping intrinsic brain networks, extending prior task-based results to resting-state connectivity and informing future work on early neural markers of anxiety.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Desk Editor's Note private letter to a colleague

The paper reports three rsFC patterns tied to behavioral, physiological, and subjective subclinical anxiety in n=47, but small sample and targeted ROI correlations leave the dissociations under-supported.

read the letter

The core finding is that in young adults with subclinical anxiety, faster behavioral responses under uncertain threat link to stronger ACC-insula connectivity, physiological arousal links to ACC-OFC connectivity, and self-reported anxiety links to hippocampus-insula connectivity. These three survived sequential FWE correction in ROI analyses of resting-state data, extending some prior task-based work on anxiety components to intrinsic networks. The two-system framework guides the hypotheses, and using reaction time, skin conductance, and the NIH Fear-Affect scale together is a reasonable way to capture the different dimensions. That part is straightforward and adds a resting-state angle that was not already in the cited literature. The sample spans a range of subclinical levels, which fits the goal of looking at early markers rather than clinical cases. The soft spots are mostly around scale and specificity. With only 47 participants, correlational neuroimaging results like these are often noisy, and the abstract gives no power analysis, effect sizes, or robustness checks such as split-half reliability. Sequential FWE helps but does not fully address the risk that the patterns reflect shared variance or unmeasured traits instead of clean dissociations. The ROI pairs are pre-selected, so broader network exploration or whole-brain checks are missing. Everything stays associative, which is fine for the stated aims but limits how far the mapping claim can go without further controls. This is the kind of paper that fits a reading group focused on anxiety neuroscience or resting-state biomarkers in non-clinical samples. A colleague working on component-specific interventions or early neural signatures might pull a couple of the connectivity ideas for discussion, though they would want the full methods and stats first. I would send it to peer review. The question is worth asking and the design is clear enough to review, but it needs more detail on power, exclusions, and alternative explanations before it can stand on its own.

Referee Report

4 major / 2 minor

Summary. The manuscript reports an empirical study of 47 young adults spanning subclinical anxiety levels. Participants completed a threat anticipation task (measuring reaction time and skin conductance), the NIH Fear-Affect self-report, and resting-state fMRI. ROI-based rsFC analyses identified three connectivity patterns surviving sequential family-wise error correction: ACC-insula linked to behavioral responses (faster RT under uncertain threat), ACC-OFC linked to physiological modulation, and hippocampus-insula linked to subjective anxiety. The central claim is that behavioral, physiological, and subjective components of subclinical anxiety map onto partially dissociable but overlapping intrinsic brain networks, extending task-based findings to rsFC.

Significance. If the reported patterns prove reliable, the work would provide correlational evidence that distinct anxiety dimensions are supported by specific rsFC profiles at rest, potentially informing neural marker development for subclinical anxiety. The design is straightforward and avoids circularity, but the modest sample and targeted ROI approach limit claims of specificity and generalizability.

major comments (4)

[Methods] Methods: The sample comprises n=47 participants, yet no a priori power analysis, effect-size justification, or minimum detectable correlation is reported. This is load-bearing for the dissociation claim because the three surviving patterns after sequential FWE correction could reflect under-powered detection rather than true partial dissociability.
[Results] Results: No correlation coefficients, confidence intervals, or effect sizes are provided for the anxiety-rsFC associations, nor are robustness checks (split-half stability, bootstrap, or leave-one-out) described. Without these metrics, the reliability of the ACC-insula, ACC-OFC, and hippocampus-insula patterns cannot be assessed.
[Statistical analysis] Statistical analysis: The sequential FWE procedure is invoked but the total number of ROI-pair tests, the exact sequencing rule, and whether all possible connections among the selected ROIs were considered are not stated. This detail is required to evaluate whether the correction adequately protects the three reported dissociations.
[Results] Results: The abstract notes no direct association between subclinical anxiety and physiological arousal, yet reports that 'physiological modulation' correlates with ACC-OFC connectivity. The operational definition of 'modulation' versus the direct arousal measure must be clarified to substantiate the claimed dissociation.

minor comments (2)

[Abstract] Abstract: The sentence linking physiological modulation to ACC-OFC connectivity should be rephrased for consistency with the earlier statement of no association with physiological arousal.
[Discussion] Discussion: A brief paragraph on generalizability from a young-adult subclinical cohort to clinical anxiety populations would strengthen the limitations section.

Simulated Author's Rebuttal

4 responses · 0 unresolved

We thank the referee for their thoughtful and constructive comments, which have helped us improve the clarity and rigor of the manuscript. We address each major comment point by point below, providing explanations and indicating revisions made to the manuscript.

read point-by-point responses

Referee: Methods: The sample comprises n=47 participants, yet no a priori power analysis, effect-size justification, or minimum detectable correlation is reported. This is load-bearing for the dissociation claim because the three surviving patterns after sequential FWE correction could reflect under-powered detection rather than true partial dissociability.

Authors: We agree that an a priori power analysis would have been valuable for interpreting the strength of the dissociation claim. The sample size of 47 was determined based on feasibility for fMRI data collection and alignment with sample sizes in prior rsFC studies of anxiety (typically 40-60 participants). No pre-study power calculation was performed as the work was exploratory. In the revision, we have added a post-hoc power analysis using the observed effect sizes for the reported correlations, along with a minimum detectable correlation estimate given our sample and alpha level. We have also expanded the Discussion to explicitly address limitations in statistical power and the need for replication in larger samples, while noting that the survival of three patterns under sequential FWE correction provides some evidence against pure under-powering. revision: partial
Referee: Results: No correlation coefficients, confidence intervals, or effect sizes are provided for the anxiety-rsFC associations, nor are robustness checks (split-half stability, bootstrap, or leave-one-out) described. Without these metrics, the reliability of the ACC-insula, ACC-OFC, and hippocampus-insula patterns cannot be assessed.

Authors: We apologize for the omission of these quantitative details in the original submission. The revised Results section now includes Pearson correlation coefficients (r), 95% confidence intervals, and effect sizes (r-squared) for each of the three reported associations. We have additionally performed and reported split-half reliability analyses (randomly splitting the sample and verifying consistency of the connectivity patterns) and bootstrap resampling (1,000 iterations) to assess stability. These checks indicate reasonable robustness for the surviving connections, and the updated manuscript presents these metrics transparently. revision: yes
Referee: Statistical analysis: The sequential FWE procedure is invoked but the total number of ROI-pair tests, the exact sequencing rule, and whether all possible connections among the selected ROIs were considered are not stated. This detail is required to evaluate whether the correction adequately protects the three reported dissociations.

Authors: We have revised the Statistical Analysis subsection of the Methods to provide complete transparency. The ROIs analyzed were the ACC, insula, OFC, and hippocampus, yielding a total of 6 possible pairwise connections, all of which were tested. The sequential FWE correction followed the standard procedure of ordering p-values from smallest to largest and applying adjusted thresholds sequentially (alpha divided by remaining tests at each step). We now explicitly state the total number of tests performed (6) and confirm that the correction was applied across all tested connections among the selected ROIs, supporting the validity of the three surviving dissociations. revision: yes
Referee: Results: The abstract notes no direct association between subclinical anxiety and physiological arousal, yet reports that 'physiological modulation' correlates with ACC-OFC connectivity. The operational definition of 'modulation' versus the direct arousal measure must be clarified to substantiate the claimed dissociation.

Authors: We appreciate this observation and have clarified the terminology throughout the revised abstract, Results, and Discussion. The 'direct association' refers to the non-significant correlation between overall NIH Fear-Affect anxiety scores and mean skin conductance response (SCR) levels averaged across the entire task. 'Physiological modulation' is defined as the anxiety-related variation in SCR specifically during the threat anticipation task (i.e., the interaction between subclinical anxiety levels and task conditions such as temporal uncertainty on SCR amplitude). This task-specific modulation correlates with ACC-OFC connectivity, distinct from the overall arousal measure. The revision explicitly defines both terms and explains how this distinction supports the partial dissociation among anxiety components. revision: yes

Circularity Check

0 steps flagged

No circularity: purely empirical correlational study with no derivations or self-referential steps

full rationale

The paper reports statistical associations between task-derived behavioral/physiological scores, self-report measures, and resting-state functional connectivity in a sample of 47 participants using predefined ROI pairs and sequential FWE correction. No equations, fitted parameters, predictions, or derivations are present that could reduce any result to its inputs by construction. No self-citation chains, uniqueness theorems, or ansatzes are invoked as load-bearing premises. The central claims are observational mappings of anxiety components onto rsFC patterns, which remain independent of the input data by standard empirical standards.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The study is observational and relies on established fMRI analysis methods and psychological assessment tools without introducing new free parameters, axioms beyond standard statistical assumptions, or invented entities.

axioms (2)

domain assumption Standard assumptions underlying resting-state functional connectivity computation, including BOLD signal stationarity during rest periods.
Implicit in all rsFC analyses described.
domain assumption The threat anticipation task and skin conductance response validly index behavioral and physiological components of anxiety.
Used to relate individual differences to rsFC.

pith-pipeline@v0.9.0 · 5546 in / 1293 out tokens · 53510 ms · 2026-05-09T15:14:32.188478+00:00 · methodology

discussion (0)

Reference graph

Works this paper leans on

2 extracted references · 2 canonical work pages

[1]

mental” back in “mental disorders

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[2]

J Affect Disord 367:815–822

https://doi.org/10.1038/s41467-025-61706-0 Zhong Q, Niu L, Chen K, Lee TMC, Zhang R (2024) Prevalence and risk of subthreshold anxiety developing into threshold anxiety disorder in the general population. J Affect Disord 367:815–822. Zhong W, Katkov M, Tsodyks M (2025) Synaptic Theory of Chunking in Working Memory. Available at: http://arxiv.org/abs/2408....

work page doi:10.1038/s41467-025-61706-0 2024