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Record W4412141723 · doi:10.3389/fnbeh.2025.1544997

The neuroexistentialism of social connectedness and loneliness

2025· article· en· W4412141723 on OpenAlexafffund
Jamshid Faraji, Gerlinde A. S. Metz

Bibliographic record

VenueFrontiers in Behavioral Neuroscience · 2025
Typearticle
Languageen
FieldPsychology
TopicDeath Anxiety and Social Exclusion
Canadian institutionsUniversity of Lethbridge
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLonelinessSocial connectednessPsychologySocial psychology

Abstract

fetched live from OpenAlex

Social isolation and loneliness have been subject to extensive investigation and discussion by both modern neuroscience and existentialist philosophy. Neuroexistentialism, though controversial, examines how neuroscientific findings inform human existential concerns. In the present discussion, we argue that (1) in the absence of meaningful attributes, typically provided by relationships with objects and others, social isolation and loneliness lead an individual to a pervasive fear of being or the perception of “ being-in-the-empty-world” which resembles an existential horror of loneliness; and (2) the pervasiveness of these influences justifies the ubiquity of cerebral responses to both objective and subjective prolonged social disengagement in humans. We also contend that current neuroscientific models of social behaviors, especially within social neuroscience, need to avoid self-affirmative and tautological notions to explain the originality of social connections in human life. By adopting a more integrative and critical approach, these models can better address the complex interplay between social disengagement and their neurological correlates known as the “ social brain .” This can be accomplished through the establishment of a novel conceptual framework in modern neuroscience to remodel the triad of brain, solitary mind, and society.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.402
Threshold uncertainty score0.328

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.354
Teacher spread0.331 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

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