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. 2026 Jul 16;6:106178. doi: 10.1016/j.bas.2026.106178

Decision-Making in Neurotrauma: a multidimensional model of cognitive and contextual factors influencing surgical judgment in the acute care setting

Andrés M Rubiano a,b,c,⁎, Laura M Loaiza-Cardona a, Wendy D González a, Wilco Peul d
PMCID: PMC13400409  PMID: 42502370

Abstract

Introduction

Surgical decision-making in acute neurotrauma settings is a cognitively complex process shaped by multiple factors beyond neuroimaging and clinical examination. Despite established evidence-based guidelines for traumatic brain injury (TBI) management, significant variability in surgical practice persists globally. Understanding the cognitive and contextual determinants of surgical judgment is essential for improving outcomes and neurosurgical education.

Research question

What cognitive and contextual factors shape surgical decision-making in neurotrauma, and how can a hippocampal–prefrontal cortex model informs strategies to improve judgment and reduce practice variability?

Material and methods

This narrative review integrates knowledge from cognitive neuroscience, surgical decision-making research, and clinical neurotrauma management. We apply a validated algorithmic model based on hippocampal–prefrontal cortex (PFC) interaction to neurosurgical TBI decision-making, analyzing both information sources available to the surgeon and surgeon-specific contextual modulators shaping the final clinical judgment.

Results

Surgical decisions in neurotrauma are influenced by two factor categories: (1) hippocampal inputs (clinical experience, published evidence, guidelines, expert consensus, bioethical considerations, neuromonitoring data, and neuroimaging), each carrying variable cognitive bias; and (2) PFC modulators (risk–benefit analysis, emotional state, work environment, fatigue, and level of training), which determine how information is weighted and transformed into action. Evidence-based protocols provide structured decision anchors, but their implementation remains subject to the surgeon's interpretive and contextual filters.

Discussion and conclusion

A multidimensional, neuroscience-informed model of surgical decision-making in neurotrauma has practical implications for training, quality improvement, and decision-support tool development. Recognizing cognitive biases, incorporating objective neuromonitoring data, and standardizing decision frameworks are key strategies for optimizing surgical outcomes in TBI.

Keywords: Traumatic brain injury, Decision making, Cognitive bias, Neuromonitoring, Prefrontal cortex, Neurotrauma

Highlights

  • •

    Neurotrauma surgical decisions involve hippocampal inputs and PFC modulators.

  • •

    Ten cognitive biases are identified with clinical examples and mitigation strategies.

  • •

    Non-invasive neuromonitoring adds objective physiological data to reduce decision bias.

  • •

    BTF guidelines and CREVICE protocol serve as structured decision anchors.

  • •

    Model has implications for training, quality improvement, and decision-support tools.

1. Introduction

Traumatic brain injury (TBI) remains one of the leading causes of death and disability worldwide, with an annual global incidence exceeding 27 million cases and a disproportionate burden in low- and middle-income countries (LMICs) compared to high-income countries (GBD, 2016, 2019). In the acute management of moderate-to-severe TBI, fast surgical decision-making is a time-critical process that can be the determining factor between survival and death, or between meaningful recovery and permanent disability.

Despite the availability of evidence-based surgical guidelines (most notably those published by the Brain Trauma Foundation (BTF) in 2016 (Carney et al., 2017)) considerable variability in surgical practice persists across institutions and countries. This variability suggests that the decision to operate, or not, and the selection of the appropriate procedure, is not solely determined by the available clinical evidence, but is profoundly influenced by a complex array of cognitive, emotional, and contextual factors intrinsic to the surgeon, his or her training background and the surgical environment (Richburg et al., 2023).

The neuroscience of decision-making has advanced significantly in recent decades. Seminal models, such as the algorithmic model proposed by Saberi and colleagues (Saberi et al., 2019), describe decision-making as a sequential, iterative interaction between the hippocampus (which retrieves and stores prior knowledge) and the prefrontal cortex (PFC), which integrates this information with current constraints, emotional state, and cost-benefit calculations to generate a behavioral plan. Applying this framework to the context of surgical treatment of neurotrauma offers a novel and clinically relevant perspective on the origins of variability in surgical judgment, partly responsible for the international practice variation in trauma surgery for cases like acute subdural hematomas, decompressive craniectomy and intracerebral hematomas (Yue et al., 2013, 2024; Maas et al., 2015; Singh et al., 2026).

The objective of this review is to describe and analyze the multidimensional factors that influence surgical decision-making in neurotrauma, using the hippocampal–Pre-Frontal Cortex (PFC) model of treating neurosurgeons as an organizing theoretical framework. We identify the principal information sources available to the neurosurgeon (hippocampal inputs) and the surgeon-specific modulators (PFC factors) that shape the final clinical decision. We also briefly discuss the role of evidence-based protocols as structured decision anchors, and the emerging contribution of multimodal neuromonitoring to enhance decision precision. Finally, we explore the implications of this model for neurosurgical education, cognitive debiasing, and the development of clinical decision-support tools in resource-limited settings.

2. A neuroscience framework for surgical decision-making

Decision-making is a fundamental cognitive function that depends on the coordinated interaction of multiple brain regions. The hippocampus, a key structure of the medial temporal lobe, encodes, stores, and retrieves episodic and semantic memories, forming the substrate of prior knowledge from which decisions are informed. The prefrontal cortex, particularly the orbitofrontal and dorsolateral regions, integrates this retrieved knowledge with current environmental inputs, emotional valence, anticipated reward, and executive control to generate goal-directed plans (Saberi et al., 2019; Miller and Cohen, 2001).

The algorithmic model proposed by Saberi et al. describes this process as a sequential cycle: (1) initial sensory stimuli excite hippocampal neuronal networks, generating a primary information state; (2) a secondary set of stimuli reaches the hippocampus, and both converge as input to the PFC; (3) the PFC determines what additional information is required and retrieves it from hippocampal memory; (4) the PFC then executes a model predictive control (MPC) process (evaluating constraints, optimizing cost functions, and predicting outcomes) to arrive at a final decision (Saberi et al., 2019).

This model has powerful implications for execution of acute surgical procedures in neurotrauma. During decision-making, while the patient is assessed at the Emergency Room and in the operating room, the neurosurgeon's hippocampus functions as a dynamic repository of all prior learning: past surgical cases, read literature, attended courses, and absorbed guidelines. The PFC then filters, weighs, and acts upon this repository in real time, under the influence of immediate cognitive and emotional pressures. The quality of the final surgical decision is therefore a function of both the quality of the information stored and the integrity of the PFC's integrative and regulatory process (Richburg et al., 2023; Miller and Cohen, 2001; Anaya González et al., 1944; Bechara et al., 2000). It is unknown to neuroscience and scientific philosophy where in the brain moral deliberation about a meaningful future life is located and possibly by the opinion of the authors this is suppressed in the critical situations of stress and in particular during fast decision making during life threatening acute disease like severe TBI.

Kahneman's dual-process theory of cognition offers a complementary lens: System 1 thinking is fast, intuitive, and heuristic-driven (often dominating in emergency neurotrauma scenarios) while System 2 thinking is deliberate, analytical, and more resistant to cognitive bias (O'Brien, 2012). Expert neurosurgeons develop metacognitive skills that allow them to recognize when to slow down and shift from intuitive to analytical reasoning, a competency described by Moulton et al. as "slowing down when you should" (Moulton et al., 2007).

Fig. 1 provides a schematic representation of this dual-process model adapted to the neurotrauma surgical context, illustrating the parallel streams of hippocampal information inputs and PFC contextual modulators that converge on the decision process.

Fig. 1.

Fig. 1

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Dual-process model of surgical decision-making in neurotrauma, adapted from Saberi et al. (Saberi et al., 2019). Hippocampal inputs provide the information substrate; prefrontal cortex modulators shape how information is weighted and acted upon. Abbreviations: BOOTStraP = Beyond One Option for Treatment of Traumatic Brain Injury: A Stratified Protocol; BTF = Brain Trauma Foundation; CREVICE = Consensus-based management protocol; CT = Computed Tomography; ICP = Intracranial Pressure; MRI = Magnetic resonance imaging; ONSD = optic nerve sheath diameter; PFC = Prefrontal cortex; PTCD = transcranial Doppler; SIBICC = Seattle International Severe Traumatic Brain Injury Consensus Conference.

3. Information sources in surgical decision-making: hippocampal inputs

The information available to the neurosurgeon at the time of a clinical decision constitutes the content of the hippocampal repository. These inputs vary substantially in their objectivity, the degree of interpretive bias they introduce, and their capacity to be systematically filtered and validated. At least seven distinct categories of hippocampal inputs can be identified in neurotrauma.

3.1. Clinical experience

Personal clinical experience, whether positive or negative, constitutes the most immediate and intuitively weighted source of surgical knowledge. Experienced surgeons possess a rich library of mental models derived from hundreds or thousands of cases. However, experience-based knowledge is systematically biased by availability heuristics (overweighting vivid or recent outcomes), outcome bias (attributing good outcomes to the chosen strategy regardless of confounders), and confirmation bias (seeking information that validates prior decisions) (Richburg et al., 2023; Croskerry, 2002; Marewski and Gigerenzer, 2012; Little and Wu, 2022). In neurotraumatology, a junior surgeon who has observed cases of spontaneous hematoma resolution during his/her training may systematically underestimate the need for surgical intervention in borderline cases. And in the other way around (s)he might overestimate the added value of wide hemi-craniectomy and subdural and intracerebral hematoma removal on future quality of life in a “nearly braindead” patient with a very low Glasgow Coma Score and bilateral wide nonresponsive pupils.

3.2. Unfiltered literature

Access to scientific literature is essential, but unfiltered reading introduces the risk of incorporating premature, methodologically weak, or non-reproducible findings into clinical practice. In the era of information overload, the cognitive effort required to critically appraise each study is enormous, and surgeons unfortunately frequently rely on secondary sources (review articles by non-experts, editorials, social media summaries of non-experienced doctors) that may propagate selective or distorted interpretations of primary evidence (Croskerry, 2002; Little and Wu, 2022).

3.3. Evidence-based guidelines/protocols

Filtered, critically appraised guidelines or protocols (such as the BTF Guidelines (Carney et al., 2017; Hawryluk et al., 2020; Bell et al., 2026) and the CREVICE (Consensus-based management protocol for TBI based on imaging and clinical examination) (Chesnut et al., 2020a) and BOOTStraP (Beyond One Option for Treatment of Traumatic Brain Injury: A Stratified Protocol)) protocols (Rubiano et al., 2020, 2026)) represent the highest scientific quality hippocampal inputs in terms of systematic bias control. These guidelines synthesize the best available evidence and provide structured decision frameworks. However, their implementation is not automatic: guidelines need to be remembered, retrieved accurately, and applied without interpretive distortion. Furthermore, guidelines are necessarily lagging instruments; they codify the evidence available at the time of their development and cannot fully address the complexity and heterogeneity of individual patients.

3.4. Expert consensus

Expert consensus recommendations (such as those produced by the Seattle International Severe TBI Consensus Conference (SIBICC) (Chesnut et al., 2020b; Hawryluk et al., 2019), The World Society of Emergency Surgery (WSES) (Picetti et al., 2019, 2023) and The Brussels consensus for non-invasive intracranial pressure (ICP) monitoring (B-ICONIC) (Robba et al., 2025)) provide valuable clinical guidance when randomized trial evidence is insufficient. However, consensus inherently carries the collective biases of the participating experts, whose views may reflect the practice patterns of high-resource academic centers and may not be directly transferable to LMICs with different patient populations and resource constraints.

3.5. Bioethical and contextual considerations

The availability of resources (intensive care unit beds, intracranial pressure monitoring systems, surgical instruments, trained nursing staff) constitutes a bioethical input that fundamentally shapes surgical decision-making in many neurotrauma environments. As a critical component guiding the surgical decision area, the four core biomedical ethical principles (Herissone and-Kelly, 2011) must be explicitly considered. Autonomy upholds the patient's or surrogate's right to informed decision-making within the realistic limits of what can be offered. Beneficence requires an honest appraisal of whether surgery can be supported by the postoperative care needed to achieve a meaningful outcome. Non-maleficence extends beyond operative risk to include the foreseeable harm of care that cannot be safely delivered after the procedure. Justice demands fair allocation of scarce resources among patients with competing needs, recognizing that scarcity itself is a morally relevant clinical variable.

In resource-limited settings, the decision not to operate may reflect not only the absence of a surgical indication, but the absence of the infrastructure to safely manage the postsurgical patient, needing intensive- and subsequent high care, physically available rehabilitation medicine and neuropsychology guidance. These contextual inputs are legitimate and must be explicitly incorporated into decision frameworks designed for global use.

3.6. Non-invasive neuromonitoring

Emerging non-invasive tools (including optic nerve sheath diameter (ONSD) measurement by ultrasound, automated pupillometry, transcranial Doppler (TCD) assessment of cerebrovascular autoregulation, and non-invasive ICP waveform analysis) provide relatively objective, real-time physiological data that can anchor the surgical decision in the immediate clinical state of the patient (Rubiano et al., 2022; Cucciolini et al., 2023). When ONSD is elevated (>6 mm) and TCD demonstrates a pattern consistent with critically elevated cerebrovascular resistance, the likelihood of clinically significant intracranial hypertension is high, regardless of CT scan findings alone (Robba et al., 2025; Alali et al., 2019).

3.7. Neuroimaging

Computed tomography (CT) scanning remains the cornerstone of acute TBI diagnosis and surgical planning. CT provides objective anatomical data of the primary injury (lesion volume, midline shift, cisternal effacement, Marshall classification) but is subject to significant interobserver variability in interpretation and does not capture real-time physiological changes. Furthermore, isolated reliance on CT-based decision criteria fails to account for the dynamic nature of TBI pathophysiology, where clinically significant lesion progression can occur within hours of the initial scan (Carney et al., 2017; Chesnut et al., 2020a).

4. Prefrontal cortex modulators: surgeon-specific factors

Beyond the information substrate, the final surgical decision is shaped by a set of surgeon-specific factors that modulate how the individual (neuro)surgeon's PFC processes, weights, and acts upon the available information (Bechara et al., 2000). These modulators can promote or impair optimal decision-making and are rarely addressed in formal surgical training programs.

4.1. Risk–benefit analysis

The surgeon's instantaneous cognitive appraisal of the balance between the surgical risks (hemorrhage, infection, neurological deficit, death) and the expected benefit (ICP reduction, hematoma evacuation, survival probability and neurological improvement) is the primary output of the PFC's cost-function optimization process (Saberi et al., 2019). This analysis is affected by the surgeon's prior experience with similar risk profiles, the patient's clinical trajectory, and the perceived probability of each outcome, all of which are subject to cognitive distortions. This situation especially affects junior surgeons with bias associated with previous expositions of different decision-makers during his residency training. As an example, if penetrating TBI patients were consistently managed medically for most of their instructors during his training program, the junior surgeon will show a decision trend of being surgically non-aggressive in these types of cases, while scientific literature shows benefit of surgery and intensive care treatment (Bell et al., 2026).

4.2. Emotional state and interpersonal dynamics

The surgeon's emotional state at the time of the decision (including time of the day or night, anxiety, stress, empathy fatigue, or grief following a poor recent outcome) can significantly modulate decision quality. Interactions with the patient's family, who may express strong preferences or emotional pressure, add an additional layer of cognitive load that can trigger emotional override of analytical reasoning (Croskerry, 2002; Marewski and Gigerenzer, 2012; Little and Wu, 2022). Equally, the dynamics within the surgical team (hierarchy, communication quality, psychological safety) influence the quality of collaborative decision-making in the operating room.

4.3. Fatigue and circadian effects

Physical fatigue and circadian disruption are well-documented impairments of surgical performance. Studies have demonstrated degraded surgical skill, increased error rates, and altered risk tolerance in sleep-deprived surgeons (O'Brien, 2012; Moulton et al., 2007). In neurotrauma, where emergencies frequently occur during night-time hours, the combination of time pressure, high-stakes decision-making, and physiological fatigue creates conditions that are highly vulnerable to system-1 cognitive errors, including premature closure, anchoring on the first available diagnosis, and underestimation of operative risk.

4.4. Level of training and self-efficacy

The surgeon's level of training (both formal neurosurgical training and specific neurotrauma experience) directly conditions the richness of the hippocampal repository and the PFC's capacity to generate accurate mental simulations of operative scenarios. Trainees and surgeons practicing in settings without dedicated neurotrauma expertise may face similar clinical presentations with a substantially impoverished knowledge base, increasing reliance on heuristic shortcuts and the risk of systematic errors (Moulton et al., 2007).

4.5. Work environment and institutional culture

Institutional factors (including the availability and reliability of surgical and anesthesiologic infrastructure, medicolegal climate, administrative pressures, and the prevailing culture of risk tolerance within the department) shape the normative frame within which individual decisions are made. In environments where surgical conservatism is institutionally rewarded, surgeons may systematically under-treat surgically amenable lesions; the inverse dynamic may lead to overtreatment and unnecessary operative risk.

5. Evidence-based protocols as decision anchors

Structured decision protocols represent an attempt to systematize the hippocampal input process, reducing the variability introduced by individual experiential bias and cognitive shortcuts. In this context, two frameworks deserve mention for their relevance in global neurotrauma practice.

The BTF Guidelines for the Surgical Management of TBI (Bullock et al., 2006; Carney et al., 2017) provide consensus-based indications for evacuation of epidural hematomas (>30 cc), acute subdural hematomas (>1 cm thickness or midline shift >5 mm), intracerebral hematomas (>50 cc with progressive deterioration), and posterior fossa lesions with fourth-ventricle obliteration (Carney et al., 2017; Hawryluk et al., 2020). These indications serve as validated anchors within the decision process, reducing the likelihood of both over- and under-treatment in the first hours after injury.

The CREVICE protocol (Chesnut et al., 2020a), validated in Latin American patient populations (Alali et al., 2019), extends this framework to patients without invasive ICP monitoring (the majority of TBI patients in LMICs). By identifying major and minor criteria for suspected intracranial hypertension (compressed cisterns, midline shift >5 mm, motor GCS ≤4, pupillary asymmetry), CREVICE provides a structured, accessible decision tool that demonstrated 98% sensitivity for ICP >25 mmHg. These protocols, however, do not eliminate the PFC modulators described above; they serve to structure and constrain the hippocampal input, while the PFC's integration of contextual factors retains a decisive role in the ultimate clinical action.

The most relevant cognitive biases affecting decision-making in neurotrauma are summarized in Table 1.

Table 1.

Cognitive biases prevalent in neurotrauma surgical decision-making: definition, clinical example, and mitigation strategy.

Cognitive bias Definition Clinical example Mitigation strategy
Anchoring bias Over-reliance on initial information with insufficient updating as new data emerge. Relying solely on the admission CT, failing to account for lesion progression in subsequent hours. Repeat CT upon neurological deterioration. Use continuous non-invasive neuromonitoring (ONSD, TCD, pupillometry) as a dynamic complement to static imaging.
Confirmation bias Seeking or interpreting information to confirm pre-existing hypotheses while disregarding contradictory evidence. Ordering monitoring only after deciding the patient is deteriorating, rather than using data as an independent input. Acquire neuromonitoring data before clinical formulation. Actively seek contradictory data. Involve a second observer in borderline cases.
Overconfidence bias Overestimating one's diagnostic accuracy or ability to predict surgical outcomes. Underestimating lesion complexity based on prior similar cases, omitting systematic assessment of the full injury pattern. Apply BTF guidelines and CREVICE protocol regardless of perceived familiarity. Review adverse outcomes. Foster a culture of second opinion.
Availability bias Overweighting scenarios that are easily recalled due to recency or emotional salience. After a recent adverse outcome, overestimating operative risk in borderline cases and defaulting to conservative management. Separate decisions from the emotional impact of recent cases. Use population-level data and guidelines as a counterweight to vivid memories.
Premature closure Stopping diagnostic reasoning at the first plausible explanation without exploring alternatives. Attributing deterioration solely to the identified hematoma without considering diffuse axonal injury, contusional evolution, or metabolic causes. Use structured checklists. Review all intracranial compartments and systemic parameters systematically before concluding.
Omission bias Preferring inaction over intervention due to fear of harm, even when evidence supports surgery. Withholding decompressive surgery in a patient meeting established criteria, due to disproportionate concern about complications. Apply BTF indications rigorously. Explicitly distinguish the risk of action from the risk of inaction. Document reasoning.
Authority bias Uncritical acceptance of a senior clinician's opinion without independent evidence appraisal. A junior surgeon accepts the attending's conservative approach despite escalating monitoring parameters, failing to communicate data supporting re-evaluation. Foster psychological safety and assertive communication. Establish escalation protocols triggered by objective monitoring thresholds.
Outcome bias Judging decision quality by the final outcome rather than the reasoning process at the time of decision. Judging the decision not to operate as correct because the patient survived, without recognizing that the reasoning was suboptimal. Separate process from outcome evaluation. Use structured case review based on process criteria, not results.
Framing effect Susceptibility to how information is presented rather than its objective content. Making different decisions depending on whether the family frames the situation as "do everything" vs. "accept the natural course," despite identical clinical data. Reformulate the problem using objective parameters before deciding. Use structured bioethical protocols for family communication.
Decision fatigue Deterioration of decision quality after prolonged consecutive decision-making or sleep deprivation. During a prolonged call, defaulting to conservative management regardless of findings, reflecting impaired executive function rather than deliberate judgment. Implement fatigue management policies. Use structured protocols to reduce cognitive load. Recognize fatigue as a patient safety risk.
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BTF Brain Trauma Foundation; CREVICE Consensus-based management protocol for traumatic brain injury based on imaging and clinical examination; CT computed tomography; ONSD optic nerve sheath diameter; TCD transcranial Doppler.

6. Integrating neuromonitoring to enhance decision precision

A critical challenge in neurotrauma decision-making is the disconnect between the relatively static information provided by CT neuroimaging and the dynamic physiological trajectory of the injured brain and its threatening factors, progressive by nature of hematoma- and oedema development. ICP monitoring (whether invasive (intraparenchymal probes, external ventricular drains) or non-invasive (ONSD, TCD-based assessment, automated pupillometry and non-invasive ICP monitoring)) introduces a time-resolved, objective physiological dimension that can substantially refine the surgical decision process (Robba et al., 2025; Rubiano et al., 2022; Cucciolini et al., 2023). From the perspective of the decision-making model, multimodal neuromonitoring data constitutes a uniquely valuable hippocampal input because it is objective, continuous, and carries a low interpretive bias compared to CT-based criteria or clinical examination findings. The ICP waveform, for example, provides information not only about the absolute pressure value, but about the state of intracranial compliance: a P2 > P1 morphology signals the approach of the exponential portion of the pressure–volume curve, indicating critically reduced compensatory reserve, even when absolute ICP values remain below the classical treatment threshold of 20–22 mmHg (Godoy et al., 2023).

The SIBICC consensus (Chesnut et al., 2020b; Hawryluk et al., 2019), B-ICONIC consensus (Robba et al., 2025) and the proposed model of the Intracranial Compartmental Syndrome (Godoy et al., 2023) integrate ICP monitoring with brain tissue oxygenation (PtiO2) and other neuromonitoring modalities into tiered treatment algorithms, providing structured triggers for escalation to surgical intervention. When non-invasive monitoring confirms elevated ONSD, pathological TCD waveform patterns or pulsatility index in TCD, altered Neurological Pupil Index (NPi) in automated pupillometry and an abnormal ICP waveform morphology, the convergence of multiple independent indicators reduces the likelihood that any individual parameter reflects a false-positive and strengthens the cognitive basis for the surgical decision.

7. Implications for neurosurgical training and quality improvement

The multidimensional model of surgical decision-making presented here has several actionable implications for neurosurgical education and quality improvement in neurotrauma care.

First, neurosurgical training programs should explicitly address the cognitive and personal intuitive factors that influence surgical judgment, including the nature and sources of cognitive bias, the impact of emotional and physical state on decision quality, and strategies for cognitive debiasing (Croskerry, 2002). Simulation-based training offers an opportunity to practice decision-making in high-fidelity scenarios while receiving structured feedback on both the process and outcome of clinical judgments (Moulton et al., 2007).

Second, the systematic adoption of structured decision protocols (including the BTF surgical guidelines, the CREVICE protocol, and SIBICC-based management algorithms) reduces the hippocampal input variance and provides a shared cognitive framework that facilitates communication and accountability within surgical teams. Mobile clinical decision support applications (such as the NeuroMind application (Kubben, 2012; Kubben, 2017)based on the BTF guidelines (Carney et al., 2017)) make these frameworks accessible at the point of care.

Third, the integration of non-invasive neuromonitoring into routine TBI assessment (B-ICONIC consensus) (achievable even in resource-limited settings), adds an objective, low-bias physiological input to the decision process that can partially compensate for limitations in expertise, training, or guideline implementation. This is of relevance in LMIC's, where the majority of TBI cases are managed in hospitals without access to invasive ICP monitoring.

Finally, institutional culture and work environment (identified as significant PFC modulators in this model), should be the target of systematic quality improvement interventions, including fatigue management policies, psychological safety frameworks for surgical teams, and structured multidisciplinary case review for neurotrauma outcomes.

8. Conclusions

Surgical decision-making in acute settings of severe neurotrauma is a cognitively complex process shaped by the dynamic interaction between the information available to the neurosurgeon and a constellation of surgeon-specific emotional, physical, and contextual modulators. Applying the hippocampal–PFC model of decision neuroscience to this clinical context reveals that the quality of the surgical decision depends not only on the knowledge base and the evidence-based framework employed, but on the degree to which cognitive biases and surgeon-specific contextual factors are recognized, managed, and mitigated. Evidence-based surgical protocols provide valuable anchors within this process, reducing variability and establishing shared decision standards. The integration of objective neuromonitoring data adds a uniquely low-bias physiological dimension that enhances decision precision, particularly in resource-limited settings. Future directions in this field should include the prospective validation of cognitive and contextual modulators as predictors of surgical decision quality, the development and evaluation of cognitive debiasing interventions in neurosurgical training, and the design of adaptive clinical decision-support tools informed by the multidimensional model described here. Understanding and improving the cognitive substrate of surgical judgment in neurotrauma is not merely a theoretical exercise; it is a direct pathway to reducing preventable morbidity and mortality in one of the most time-critical domains of clinical medicine.

Author contributions

AMR and WP: conceptualization, writing original draft, review and editing. LMLC and WGT: writing, review and editing. All authors read and approved of the final manuscript.

Ethics approval

Not applicable.

Funding

This research received no external funding.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Contributor Information

Andrés M. Rubiano, Email: rubianoam@outlook.com.

Laura M. Loaiza-Cardona, Email: loaiza.laura.meditechf@outlook.com.

Wendy D. González, Email: gonzalez.wendy.meditechf@outlook.com.

Wilco Peul, Email: wcpeul@lumc.nl.

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