Abstract

This paper presents a novel pathway-specific framework for metacognitive interventions in Alzheimer's Disease (AD), addressing the heterogeneity in treatment responses across the disease continuum. The framework integrates the Cognitive Awareness Model (CAM) with neurobiological correlates to categorize interventions according to three distinct anosognosia pathways: mnemonic (memory-based), executive (performance monitoring), and primary (metacognitive awareness). Through meta-analysis of six randomized controlled trials, this study identified differential effectiveness patterns across disease stages. Memory-focused interventions demonstrated robust efficacy in early stages but diminishing returns in advanced disease. Executive pathway interventions showed promising but stage-limited effectiveness, primarily benefiting those with Subjective Cognitive Decline (SCD) and Mild Cognitive Impairment (MCI). Interventions targeting the primary anosognosia pathway exhibited sustained effectiveness across the disease spectrum. This neurobiologically informed approach enables clinicians to select interventions based on preserved neural systems at specific disease stages, potentially optimizing treatment outcomes through personalized intervention pathways. Future research should explore biomarker-guided selection and evaluate long-term intervention sustainability.

Keywords: Alzheimer's disease, metacognition, anosognosia, neural pathways, cognitive intervention, personalized medicine, neuroplasticity, memory awareness 

Introduction

Metacognition, defined as “thinking about thinking,” consists of self-awareness (i.e., metacognitive knowledge) and self-regulation (i.e., metacognitive control) of cognitive processes (Fleur et al., 2021). Recently, with the projected global increase in dementia cases, there is growing interest in the clinical implications beyond cognitive decline itself (2024 Alzheimer’s Disease Facts and Figures, 2024). Despite growing research on metacognitive interventions for Alzheimer’s Disease (AD), we lack a systematic framework to determine which interventions are most effective for specific neural deficits across different disease stages (Hallam et al., 2020; Meunier-Duperray et al., 2025; Mondragón et al., 2019). The AD continuum is characterized by progressive neurodegeneration, but the onset of molecular changes foreshadowing gradual cognitive decline occurs when an individual is considered cognitively normal (Elvira-Hurtado et al., 2023).

The level of impairment in the AD pathophysiologic continuum, according to Jack Jr. et al. (2024), is organized into a six-stage numerical clinical staging scheme. Stage 1 reflects asymptomatic individuals with biomarker evidence of AD pathology. Stage 2, known as Subjective Cognitive Decline (SCD), is characterized by self-reported cognitive concerns without measurable impairment (Jack Jr. et al., 2024). Stage 3, or Mild Cognitive Impairment (MCI), marks an early stage of dementia in which cognitive changes exceed those expected from normal aging but do not yet meet the criteria for dementia (Anand & Schoo, 2025; Jack Jr. et al., 2024). Stages 4, 5, and 6 represent progressively severe forms of dementia, classified as mild, moderate, and severe dementia, respectively (Jack Jr. et al., 2024). These progressive stages of cognitive decline have significant implications for metacognitive function.

It is now well-established that anosognosia, or a lack of self-awareness due to impaired metacognition, has a causal effect on symptom progression and patient outcomes in the AD continuum (Andrade & Pacella, 2024). Metacognitive deficits may result in dangerous behaviors, diminished emotion recognition, compromised medical and everyday decision-making capacity, and substantially increased caregiver burden (Al-Aloucy et al., 2011; Cosentino et al., 2011; Garcia-Cordero et al., 2021; Starkstein et al., 2007). These cognitive and functional limitations, stemming from lack of insight, translate to substantial economic impact through increased healthcare utilization that could be mitigated through effective metacognitive interventions. However, the current state of research for patients with MCI or AD presents problems of heterogeneity, with mixed findings regarding the efficacy of metacognitive interventions aimed at slowing cognitive decline, enhancing self-awareness, and improving decision-making capacity (Sherman et al., 2017; Xu et al., 2021).

Current metacognitive interventions typically adopt a uniform approach across patients, failing to account for the differential deterioration of specific neural systems (Duara & Barker, 2022). This cognitive and pathological heterogeneity explains why interventions show variable effectiveness across patients and disease stages (Thomas et al., 2022). Without a framework that matches interventions to preserved neural pathways, clinicians lack clear guidance for selecting the most appropriate metacognitive strategies for individual patients. Considering the challenges in translating research into clinical practice, there is an urgent need for a revised theoretical framework to better understand differential intervention effectiveness.

Recent advances in neuroimaging and cognitive neuroscience offer promising directions for addressing this gap in understanding. A particularly relevant framework proposed by Salmon et al. (2024) delineates specific neural correlates of metacognitive deficits in AD. This neurobiologically informed approach provides a foundation for examining why certain interventions may be effective for some patients but not others based on the specific neural systems affected. The revised CAM with neural correlates effectively captures the relationship between neural deterioration patterns and clinical manifestations (Salmon et al., 2024). However, as acknowledged by the authors, a major limitation of their model is that cognitive processes are dependent on neural networks and cannot be fully explained by simple correlations relating function to brain regions (Salmon et al., 2024). Moreover, the model does not account for how different information is shared and integrated based on cortical regions (Salmon et al., 2024). Building on these neurobiological insights, a more targeted approach to metacognitive intervention is needed.

This paper presents a novel pathway-specific framework to categorize metacognitive interventions by their targeted neural correlates, enabling clinicians to select interventions based on preserved neural systems at specific disease stages. By mapping interventions to the three anosognosia types (i.e., mnemonic anosognosia, involving failure to update self-knowledge; executive anosognosia, involving impaired performance monitoring; and primary anosognosia, involving decline in metacognitive function), this paper offers a neurobiologically-informed approach to intervention selection that accounts for the differential deterioration of neural systems across the AD continuum (Tagai et al., 2020). Past studies show strong alignment between CAM anosognosia types and Salmon et al.’s (2024) neural correlates, which supports the need to examine metacognitive interventions in MCI and AD through pathway-specific lens (Bueichekú et al., 2024; Valera-Bermejo et al., 2020). With this renewed understanding, there is potential for optimizing intervention selection based on preserved neural systems.

This paper will be divided into two sections: a theoretical framework and meta-analysis. The primary objective of the theoretical framework is to synthesize existing research on deficits in memory-based metacognitive awareness in the AD continuum and the revised CAM with neural correlates to identify the neural mechanisms that mediate the three pathways of anosognosia. This theoretical framework will be applied in the second section of this paper to compare pathway-specific effectiveness based on disease progression. Secondary objectives of the meta-analysis include identifying which neural pathways remain responsive at different disease stages, refining theoretical understanding of metacognition in neurodegeneration, and, ultimately, establishing clinical guidelines for pathway-specific intervention selection. Finally, this paper will conclude by analyzing emerging patterns of differential effectiveness when comparing interventions across the three pathways and the pattern changes with disease progression to provide directions for future research. 

Theoretical Framework

This section establishes the neurobiological foundation for understanding metacognitive deficits in AD. By examining how specific neural systems mediate different aspects of self-awareness, this analytical framework categorizes metacognitive interventions based on their targeted neural pathways. This approach enables a more precise analysis of intervention effectiveness across disease stages and provides a rationale for tailoring interventions to preserved neural systems.

The Cognitive Awareness Model (CAM): Core Components

The Cognitive Awareness Model (CAM) developed by Agnew & Morris (1998) and refined by Morris & Mograbi (2013) provides the foundation for understanding metacognitive deficits in AD. The Personal Database (PDB), mediated by the middle temporal cortex (MTC), represents the repository of stored knowledge about oneself, including cognitive capabilities and limitations (Berlingeri et al., 2015; Salmon et al., 2024). Comparator Mechanisms (CMs) compare current experiences and performance with stored self-knowledge in the PDB, detecting discrepancies that signal cognitive change (Tondelli et al., 2024). The Metacognitive Awareness System (MAS) enables explicit awareness of cognitive abilities and limitations, allowing for conscious insight into one's condition (Tondelli et al., 2024).

Three Types of Anosognosia in the CAM

The revised CAM framework encompasses two levels of anosognosia: primary (higher metacognitive level) anosognosia due to direct MAS deficits and secondary (lower metacognitive level) mnemonic or executive anosognosia due to memory or executive impairment (Hannesdottir & Morris, 2007). The three types of anosognosia can be further distinguished by identifying dysfunction in specific neural mechanisms and components (Tagai et al., 2020). These classifications help explain the heterogeneity of awareness deficits observed in the AD continuum.

Primary anosognosia involves direct MAS dysfunction, where the systems responsible for receiving inputs from the PDB and CMs to produce feedback into consciousness about ability are compromised (Hannesdottir & Morris, 2007). Mnemonic anosognosia, a type of secondary anosognosia involving lower-level impairment, corresponds to a failure to update the PDB with novel memory information despite the successful detection of cognitive changes by the CMs (Tagai et al., 2020). In an episodic memory task, Berlingeri et al. (2015) demonstrated a positive relationship between the degree of anosognosia in AD patients and weaker functional connectivity between episodic memory systems to integrate semantic self-knowledge in the PDB with new information from the current metacognitive task. Whereas CM function is preserved in mnemonic anosognosia, executive anosognosia corresponds to impaired CMs, which fail to evaluate ongoing cognitive performance and cause a breakdown in error detection and performance monitoring (Morris & Mograbi, 2013).

The three anosognosia types present distinctly in clinical settings. Primary anosognosia manifests as a patient firmly denying memory problems despite obvious impairment (e.g., "My memory is perfect"). Mnemonic anosognosia presents as failure to update self-knowledge despite acknowledging individual incidents (e.g., "I forgot your name, but my memory has always been excellent"). Executive anosognosia appears as an inability to detect errors during tasks (e.g., "I'm doing great" while making multiple mistakes). These distinct presentations suggest different intervention targets across the disease continuum.

Neural Correlates of Anosognosia Types

Salmon et al. (2024) mapped these anosognosia types to specific neural systems, establishing a neurobiological basis for metacognitive deficits in AD, with each type corresponding to distinct brain regions and networks. Based on the three types of anosognosia in the CAM, this paper organizes metacognitive function into three neurocognitive pathways of self-awareness, each with specific neural substrates and cognitive processes. Figure 1 illustrates these pathways and their neural correlates.

Pathway 1: Metacognitive Awareness System (Primary Anosognosia)

This pathway primarily engages higher-level awareness associated with subjective conscious experience, metacognition, and social cognition (Huntley et al., 2021). The neural correlates include the ventromedial prefrontal cortex (vmPFC) for affective processing of self-relevant information, dorsomedial prefrontal cortex (dmPFC) for evaluation and decision-making of self-reflective and other-reflective processes, posterior cingulate cortex/precuneus (PCC/PCu) for retrieving and consulting autobiographical memory in self-reflective processes, temporoparietal junction (TPJ) for self-other distinction at the perceptual, action, and mental-state levels, and retrosplenial cortex (RSC) for translating between egocentric and allocentric perspectives (Maddock et al., 2001; Quesque & Brass, 2019; Salmon et al., 2024; van der Meer et al., 2010).

In cognitively normal healthy individuals, dmPFC and dorsal anterior cingulate cortex (dACC) activity reflects the need for change, allowing behavior adaption and updated internal models of the world (Clairis & Lopez-Persem, 2023). Global meta-processing also involves the rostral ventrolateral prefrontal cortex (rvlPFC) for introspection, awareness of competence, mentalizing, and self-judgment (Burgess & Wu, 2013). The anteromedial prefrontal cortex (amPFC) acts as a gating mechanism that controls the flow of information into conscious awareness, affecting metacognitive accuracy in memory retrieval (Baird et al., 2013).

The metacognitive awareness system pathway displays a distinct pattern of preservation or deterioration across disease stages. In MCI or AD, dysfunction results in decreased vmPFC-PCC/PCu functional connectivity, disrupting self-evaluation and monitoring, reduced activation of dmPFC correlating to greater anosognosia for current characteristics of personality traits, and TPJ dysfunction affecting self-representation (Dillen et al., 2017; Jedidi et al., 2014; Jobson et al., 2021; Lattanzio et al., 2021). Posterior dorsomedial prefrontal (pdmPF) involvement in attentional processing for perspective-taking is also compromised (Salmon et al., 2024). Interestingly, some aspects of this pathway may remain responsive to intervention even in later disease stages.

Pathway 2: Memory Processes (Mnemonic Anosognosia)

This pathway involves three core cognitive functions: episodic memory encoding and retrieval, autobiographical memory integration, and self-schema updating and maintenance. The neural correlates include the medial temporal lobe (mTL) for updating self-knowledge through memory recollection and consolidation and middle temporal cortex (MTC) for storing personal semantic information in the PDB (Brown et al., 2018; Dickerson & Eichenbaum, 2010; Rugg & Vilberg, 2013).

Dysfunction in the mnemonic anosognosia pathway manifests as decreased functional connectivity between the hippocampus and MTC, preventing the integration of episodic experiences into semantic knowledge (Park et al., 2017). Furthermore, greater mTL atrophy is correlated with worsened episodic performance, demonstrating impaired abilities to incorporate new experiences into semantic self-concepts (Chauveau et al., 2021). The GMS and AMS are affected, contributing to the persistence of outdated self-knowledge. Longitudinal studies have shown a pattern of progressive deterioration across the MCI-AD continuum, with this pathway often affected early in the disease process.

Pathway 3: Executive Processes (Executive Anosognosia)

This pathway involves executive functions critical for cognitive control, including performance monitoring, error detection, feedback processing, and the strategic regulation of attention and behavior (Friedman & Robbins, 2022). The neural correlates include the ventrolateral prefrontal cortex (vlPFC), which supports local monitoring of cognitive performance and flexible task-shifting, and the inferior parietal lobe (IPL), which contributes to the retrieval and selection of complex task-relevant information (Gray et al., 2020; Segal & Elkana, 2023). The intraparietal sulcus (IPS) is also implicated, which plays a role in supporting familiarity-based retrieval processes that may compensate for impairments in recollection-based memory retrieval (Hou et al., 2021; King et al., 2018).

Unlike memory processes, executive functions such as attention regulation, divided attention, and working memory show a unique and partially independent pattern of deterioration during disease progression, highlighting the importance of tracking executive dysfunction separately from episodic memory decline (Hoshi et al., 2022; Kirova et al., 2015). Recent MEG studies further support this dissociation by showing that executive dysfunction can emerge independently and early, even when memory is relatively preserved, and that network-level compensatory mechanisms may temporarily sustain cognitive performance (Hoshi et al., 2022). Fan et al. (2025) demonstrated that in individuals with MCI, executive dysfunction manifests as compensatory hyperactivation of the vlPFC and parietal lobes during monitoring and control tasks, such as the Stroop task. Although this overactivation initially helps maintain task accuracy despite slower response times, compensatory activation becomes progressively insufficient as cognitive demands increase, revealing emerging inefficiency in executive control systems (Fan et al., 2025).

Network Integration and Compensatory Mechanisms

While these pathways offer targeted intervention points, they do not operate in isolation. Instead, they interact dynamically within larger brain networks that provide compensatory relationships between pathways. One of the most prominent, the Default Mode Network (DMN), supports self-referential processing through the coordinated activity of the PCC, MPFC, and IPL (Davey et al., 2016). Dynamic causal modeling by Davey et al. (2016) further demonstrated that these regions form a core-self system within the DMN, interacting to sustain both resting-state self-representation and task-driven self-referential cognition. In parallel, the Central Executive Network (CEN), also known as the cognitive control network or executive control network, facilitates cognitive monitoring and regulatory control via the DLPFC and VLPFC (Mulders et al., 2015). In particular, a recent neurofeedback study by Y. Li et al. (2025) showed that the VLPFC plays a dynamic role in emotion regulation. Successful individual modulation of VLPFC activity predicts enhanced regulation outcomes, highlighting the prefrontal system’s adaptability and compensatory potential in early cognitive decline (Y. Li et al., 2025). Moreover, the Salience Network (SN), anchored in the anterior cingulate and ventral anterior insular cortices, plays a critical role in identifying and prioritizing salient internal and external stimuli (Seeley, 2019). Recent neuroimaging reviews highlight the SN’s function in dynamically allocating attention toward internally salient events (e.g., physiological or socioemotional pain) and externally salient cues (e.g., reward signals), coordinating network switching to facilitate adaptive behavioral responses (X. Li et al., 2024). Complementing these findings, Menon and Uddin (2010) demonstrated that the SN orchestrates rapid transitions between large-scale brain networks, optimizing attentional resources to support contextually appropriate, goal-directed behavior.

Consistent with models of brain network dynamics in psychopathology and healthy aging, individual differences in network vulnerability and compensatory mechanisms may explain differential responses to metacognitive interventions (Cabeza et al., 2018; Menon, 2011). As neural pathways deteriorate with aging (e.g., gray matter loss, white matter degradation, or reduced network specificity), the Scaffolding Theory of Aging and Cognition (STAC) model suggests that compensatory scaffolding promotes adaptive reorganization (Reuter-Lorenz & Park, 2014). The brain may engage compensatory scaffolding by recruiting alternative circuits, engaging bilateral activation, and increasing reliance on domain-general executive systems to preserve cognitive function (Reuter-Lorenz & Park, 2014). Similarly, network neuroscience studies show that following neural disruption, functional hyperconnectivity and reorganization through network hubs can temporarily preserve communication efficiency, although with potential long-term metabolic costs (Hillary & Grafman, 2017). This network perspective offers a more nuanced view than localized approaches, emphasizing that interventions must account for both pathway-specific changes and their integration within broader network dynamics (Bassett & Sporns, 2017; Petersen & Sporns, 2015).

This theoretical framework provides the foundation for the subsequent meta-analysis of metacognitive interventions. By categorizing interventions according to their primary targeted neurocognitive pathway, we can systematically evaluate their effectiveness across different stages of AD. This approach enables the identification of which neural mechanisms remain responsive to intervention at specific disease stages, determines optimal timing for different types of metacognitive interventions, develops principles for tailoring interventions to individual neural profiles, and establishes a neurobiologically informed approach to clinical decision-making. The following meta-analysis will examine evidence from 6 randomized controlled trials of metacognitive interventions, organizing them according to their primary pathway targets and analyzing differential effectiveness across the disease continuum.

Meta-Analysis

Methods

This meta-analysis followed the PRISMA guidelines for systematic reviews, with the selection process illustrated in Figure 2. A comprehensive search of the PubMed database was conducted in February 2025. A structured combination of metacognitive and Alzheimer's-related terms was used, combining metacognitive intervention terminology with Alzheimer's disease and related conditions. The specific search string employed was: (((metacognitive* intervention) OR (metacognitive* training) OR (metacognitive* skills training) OR (metamemory training) OR (metacognitive* strategy training) OR (self-monitoring training) OR (cognitive awareness training) OR (memory monitoring) OR (memory awareness)) AND (("Alzheimer Disease"[Mesh]) OR ("alzheimer s") OR (dementia) OR ("mild cognitive impairment") OR ("cognitive decline"))). The search was refined using “Randomized Controlled Trial,” “English,” and “Humans” filters, which yielded 145 initial results. The time frame for the search ranged from 1998 to the present, aligning with the timeline of the Cognitive Awareness Model development.

Six studies met the strict inclusion criteria for this meta-analysis. Only randomized controlled trials with interventions targeting metacognitive processes in MCI and AD populations were considered. Studies were required to have published outcome measures assessing metacognitive function to be considered for final analysis. Neural correlate assessment was evaluated when available. As depicted in Figure 2, non-intervention studies, studies with populations other than MCI or AD, studies featuring purely cognitive training without metacognitive components, and studies with insufficient outcome data were excluded. Furthermore, the six selected studies were assessed for methodological quality using reported sample size and power calculations, randomization and allocation concealment, blinding procedures where applicable, outcome measurement validity, follow-up duration and attrition rates where applicable, and analysis appropriateness. For studies including neural correlate data, the quality of neural correlate assessment was also evaluated where applicable.

Based on quality assessment, each metacognitive intervention was classified according to its primary neurocognitive pathway using the operational definitions established by Salmon et al. (2024). Rigorous criteria were employed to categorize interventions by their target mechanisms, the neural systems they engaged (either directly measured or theoretically implicated), the specific outcome measures related to the three pathways, and their mapping to CAM components and anosognosia types. This classification procedure was also applied to multi-component interventions, summarizing each study and its respective metacognitive intervention in Table 1.

For data extraction, each of the six studies was analyzed for participant characteristics (including age, education, and disease severity), intervention details (such as format, duration, frequency, and components), outcome measures (encompassing metacognitive, cognitive, and functional assessments), effect sizes (either extracted directly or calculated), and neural correlate findings when available. Table 1 presents this comprehensive extraction data. To enable cross-pathway effectiveness comparisons, effect sizes across studies were standardized using meta-analytic techniques where applicable and organized into subgroup analyses by disease stage and pathway. Table 2 summarizes qualitative synthesis results for these heterogeneous interventions.

Results

Interventions Targeting Memory Processes (Mnemonic Anosognosia)

Reminiscence-Based Intervention: Nakamura et al. (2016)

Nakamura et al. (2016) evaluated the efficacy of a Group Reminiscence Approach combined with Reality Orientation (GRA-RO) in improving cognitive and metacognitive outcomes among 94 older adults with MCI (mean age ~81). Participants were randomized into three groups: GRA-RO (n=39), Physical Activity (n=23), and Cognitive Training (n=32). The GRA-RO intervention involved weekly one-hour sessions over 12 weeks, supplemented by structured homework assignments focused on memory recall and self-reflection.

Compared to control groups, the GRA-RO group exhibited significantly greater improvements in self-awareness of memory deficits (χ² = 21.79, p < .001), autobiographical memory recall (F = 7.52, p = .001), Mini-Mental State Examination (MMSE) scores (F = 7.54, p = .009), and overall quality of life (F = 12.18, p = .002). The intervention primarily engaged neural systems implicated in autobiographical memory integration and personal semantic updating, including the mTL, MTC, and PCC/PCu.

Computerized Cognitive Training: Bahar-Fuchs et al. (2017)

Bahar-Fuchs et al. (2017) conducted a double-blind randomized controlled trial evaluating an individually-tailored, adaptive computerized cognitive training (CCT) program in 44 older adults with MCI, mood-related neuropsychiatric symptoms (MrNPS), or both (MCI+MrNPS). Participants underwent 8–12 weeks of home-based training (CCT: n=21; Active Control: n=23).

The CCT group demonstrated significant improvements in global cognition (d = .80 post-intervention; d = .79 at 3-month follow-up), composite learning and memory (d = .50 post-intervention; d = .83 at 3-month follow-up), and delayed memory (d = .92 at follow-up), with participants 7.4 times more likely to achieve clinically meaningful cognitive gains (≥0.5 SD) immediately post-intervention compared to controls. Benefits were maintained and, in some cases, further consolidated at 3 months. Individuals with MrNPS benefited comparably to those with MCI alone. The intervention primarily engaged neural systems involved in memory encoding, consolidation, and self-referential processing systems, including the mTL, MTC, and PCC/PCu.

Cognitive Stimulation Therapy: Bertrand et al. (2023)

Bertrand et al. (2023) conducted a pilot randomized controlled trial evaluating the effects of a Brazilian-adapted Cognitive Stimulation Therapy (CST-Brasil) on metacognitive awareness in 47 individuals with mild to moderate dementia (MMSE 10-24). Participants were randomized to CST (n=23) or treatment as usual (n=24). The intervention consisted of twice-weekly, 45-minute group sessions over 7 weeks. Awareness of cognitive abilities was assessed using the Assessment Scale of Psychosocial Impact of the Diagnosis of Dementia (ASPIDD).

Results showed significant improvements in awareness of cognitive deficits in the CST group (ηp² = .10, p = .012), with no significant changes in affective, social, or functional awareness domains. Enhanced engagement in structured cognitive activities was also observed. The intervention primarily engaged neural systems involved in episodic recall, self-schema maintenance, and memory integration, including the mTL, MTC, and PCC/PCu.

Interventions Targeting Executive Processes (Executive Anosognosia)

Attentional Control Training: Gagnon & Belleville (2012)

Gagnon and Belleville (2012) evaluated attentional control training in 24 older adults with MCI and executive deficits, randomized to Variable Priority (VP) training (n=12) or Fixed Priority (FP) control (n=12). The intervention involved six one-hour sessions of computer-based dual-task training over two weeks. VP training emphasized flexible attention shifting between visual detection and alpha-arithmetic tasks, supplemented by self-estimation and feedback after each block. FP training involved rote practice without shifting or feedback.

Results showed that the VP group achieved significantly greater improvements in dual-task performance (26% vs. 3.4% improvement; F(1,22) = 6.49, p < .05, η² = .23) and enhanced switching ability on executive function tasks (F(1,21) = 12.24, p < .01, η² = .37). General attention improved in both groups, but no far-transfer to self-reported functional measures was observed. The intervention primarily engaged neural systems supporting executive control and attentional flexibility, including the DLPFC, VLPFC, and IPL.

Meta-Cognitive Group Training: Rotenberg et al. (2024)

Rotenberg et al. (2024) evaluated the ASPIRE metacognitive group intervention in 264 older adults with SCD or MCI, randomized to ASPIRE (n=131) or Brain Education control (n=133). The 10-week ASPIRE program emphasized metacognitive strategy acquisition, individualized goal setting, self-efficacy building, and real-time feedback applied to personalized daily activities, while the control group received general cognitive health education without strategy training.

Results showed that ASPIRE participants improved performance in trained activities by 65.5%, but only 32.5% improvement was observed in untrained activities, similar to the control group (30.6%). No significant group differences were found for untrained activities, and no objective cognitive gains were detected. However, both groups reported improved subjective cognition, executive function, and self-efficacy. Subgroup analysis suggested greater benefits for participants with SCD compared to MCI. The intervention targeted neural systems supporting metacognitive and executive control, including the VLPFC, DLPFC, and the broader Executive Control Network.

Interventions Targeting Comparator and Metacognitive Mechanisms (Primary Anosognosia)

Mindfulness-Based Intervention: Larouche et al. (2019)

Larouche et al. (2019) conducted a randomized controlled trial to evaluate the effects of a Mindfulness-Based Intervention (MBI) in 45 older adults with amnestic Mild Cognitive Impairment (aMCI), assigning participants to either an MBI group (n = 23) or a Psychoeducation-Based Intervention (PBI) group (n = 22). Both groups participated in eight weekly sessions lasting 2.5 hours each. The MBI group received training based on Mindfulness-Based Stress Reduction and Mindfulness-Based Cognitive Therapy frameworks, incorporating meditation, group reflection, and structured home practice (averaging 140 minutes per week). In contrast, the PBI group received educational sessions about aging and cognition without mindfulness components.

Across both groups, significant improvements were observed in depressive symptoms (η²p = .09), anxiety symptoms (η²p = .11), and aging-related quality of life (η²p = .10). Mechanistically, increases in non-judgment and non-reaction facets of mindfulness predicted reductions in rumination and anxiety, whereas changes in the monitoring (i.e., observation) facet did not correlate with memory outcomes. Neurobiologically, the intervention primarily engaged regions implicated in self-referential processing and emotional regulation, including the VMPFC, DMPFC, and PCC/PCu.

Supporting Evidence from Multi-Component Interventions

Cognitive Stimulation Therapy (CST), as implemented by Bertrand et al. (2023), demonstrated significant improvements in awareness of cognitive abilities (ηp² = .10, p = .012) through group-based reflection and feedback activities. These changes occurred without corresponding increases in distress.

Similarly, the ASPIRE intervention by Rotenberg et al. (2024), which primarily targeted executive functions, was associated with improvements in metacognitive self-monitoring, reflected by increases in self-efficacy and self-reported satisfaction with cognitive functioning. The intervention produced stronger effects among participants with Subjective Cognitive Decline compared to those with Mild Cognitive Impairment (MCI), and greater gains were observed in trained activities (65.5% improvement) compared to untrained activities (32.5% improvement).

Discussion

The aim of the current review was to synthesize existing research on metacognitive deficits in AD through a pathway-specific lens and to evaluate the comparative effectiveness of interventions targeting these distinct neural pathways across the disease continuum. By mapping interventions to the three anosognosia types identified in the revised Cognitive Awareness Model (CAM)—mnemonic anosognosia, executive anosognosia, and primary anosognosia—this review sought to establish a neurobiologically-informed framework for intervention selection that accounts for the differential deterioration of neural systems in AD.

This meta-analysis revealed distinctive patterns of effectiveness among the three metacognitive pathways investigated, each showing variable responsiveness across the AD continuum. These findings suggest that intervention selection should be tailored to both the disease stage and preserved neural systems to maximize therapeutic outcomes.

Mnemonic Anosognosia Pathway: Robust Early Intervention Target

The mnemonic anosognosia pathway demonstrates the most comprehensive empirical support, particularly in early to moderate stages of cognitive decline. Interventions targeting memory processes, including reminiscence therapy, computerized cognitive training, and cognitive stimulation, consistently yield significant improvements in autobiographical memory recall (χ² = 21.79, p < .001), self-schema updating, and awareness of memory deficits (ηp² = .10, p = .012) (Bahar-Fuchs et al., 2017; Bertrand et al., 2023; Nakamura et al., 2016). The effectiveness of these interventions appears most pronounced when targeting autobiographical memory and personal narrative construction, suggesting that strengthening connections between episodic experiences and personal semantic knowledge represents a potent mechanism for enhancing metacognitive awareness. This pattern is consistent with the integrative framework proposed by Mograbi et al. (2021), highlighting that while episodic recollection deteriorates in AD, semantic aspects of the self often remain intact, providing a scaffold that can support interventions aimed at preserving self-awareness and narrative identity. By reinforcing these resilient components, memory-based interventions may mitigate awareness deficits and promote a more cohesive sense of self amid progressive cognitive decline.

The neural systems implicated in mnemonic anosognosia—mTL, MTC, and PCC/PCu— form an integrated circuit supporting both episodic memory consolidation and its integration into self-referential knowledge (Dickerson & Eichenbaum, 2010; Nejad et al., 2013). Within this network, the hippocampus binds event features, while the PCC/PCu contributes to the self-evaluative and autobiographical relevance of memory retrieval, processes crucial for recognizing memory impairment (Nejad et al., 2013). Biomarker studies suggest that computerized cognitive training can enhance hippocampal-PCC functional connectivity and mitigate PCC atrophy, providing neural support for interventions targeting mnemonic anosognosia (Hayashi et al., 2024). Human pathological studies show that during MCI, the hippocampus displays active neuroplasticity, including increased dendritic arborization in CA1 neurons and cholinergic sprouting, despite mounting tau pathology (Mufson et al., 2015). These remodeling processes likely sustain residual mnemonic updating mechanisms before irreversible degeneration. Effect sizes in this pathway range from moderate to large (d = 0.50 - 0.92), reflecting both intervention diversity and individual variability in cognitive reserve. This range corresponds to clinically meaningful cognitive gains, as reported by Bahar-Fuchs et al. (2017), where participants were 7.4 times more likely to achieve improvements of ≥0.5 SD compared to controls.

However, a notable limitation within this pathway is the relative absence of longitudinal follow-up data extending beyond 3 to 6 months post-intervention. As structural degeneration progresses, the sustainability of memory-based metacognitive improvements remains uncertain. Future research should prioritize long-term outcome assessment to determine whether these interventions merely delay awareness decline or fundamentally alter disease trajectory.

Executive Anosognosia Pathway: Promising but Stage-Limited Efficacy

Interventions targeting the executive anosognosia pathway demonstrate substantial efficacy in early disease stages but diminishing returns as neurodegeneration advances. Approaches such as attentional control training and metacognitive strategy instruction yield moderate to large improvements (η² = 0.23 - 0.37) in self-monitoring, performance regulation, and cognitive flexibility among individuals with MCI and SCD (Gagnon & and Belleville, 2012; Rotenberg et al., 2024). The variable priority attentional control intervention demonstrated particularly robust effects on dual-task performance (26% vs. 3.4% improvement; F(1,22) = 6.49, p < .05) and switching ability (F(1,21) = 12.24, p < .01).

The neural substrates of executive anosognosia, primarily the VLPFC, DLPFC, and broader attentional networks, show particular vulnerability to AD pathology, explaining the stage-dependent efficacy of these interventions. This meta-analysis indicates that executive pathway interventions yield diminishing returns beyond the MCI stage, likely reflecting progressive network degradation and reduced capacity for strategy engagement. Supporting this, Pu et al. (2025) demonstrated that task-evoked prefrontal functional connectivity, particularly within the DLPFC and VLPFC, progressively weakens from SCD to MCI, mirroring early network-level disruptions that compromise executive monitoring. Consistent with this, Naveed et al. (2024) showed that structural deterioration of the DLPFC and its associated white matter tracts directly impairs neuroplastic capacity, with reduced cortical thickness predicting diminished responsiveness to stimulation-based interventions in AD. This aligns with Fan et al.'s (2025) observations of compensatory prefrontal hyperactivation in early MCI that become progressively insufficient as the disease advances.

A key strength of executive anosognosia pathway interventions is their robust transfer to functional outcomes in early disease stages, particularly for tasks requiring error detection and strategy adaptation. Clinical trials of individualized cognitive rehabilitation further support this, demonstrating that goal-oriented interventions significantly improve functional outcomes in individuals with mild-to-moderate dementia while effects diminish as the disease progresses (Clare et al., 2019). Meta-analytic findings on cognitive interventions in MCI similarly show that multi-component and multidomain training can prompt moderate cognitive and functional gains in early stages, but compensatory scaffolding mechanisms become increasingly insufficient with advancing neuropathology (Sherman et al., 2017). Recent clinical studies show that interventions targeting executive self-monitoring and control—key aspects of executive anosognosia—produce sustained gains in cognitive flexibility and metacognitive regulation over six months, while standard cognitive exercises yield less durable effects (Bampa et al., 2024). However, their application in moderate to severe dementia appears limited, suggesting these approaches should be prioritized early in the disease trajectory when prefrontal systems retain sufficient functional integrity.

Primary Anosognosia Pathway: Sustained Therapeutic Window

Interventions targeting the primary anosognosia pathway exhibit the most consistent efficacy across the disease spectrum, from SCD through moderate dementia. This pathway primarily engages higher-level awareness associated with subjective conscious experience, metacognition, and social cognition (Huntley et al., 2021). Approaches such as mindfulness-based therapy, group-based metacognitive reflection, and cognitive stimulation with structured feedback demonstrate enduring benefits for self-awareness, emotional insight, and psychological resilience (Larouche et al., 2019).

The neural correlates implicated in this pathway include the vmPFC, dmPFC, PCC/PCu, and TPJ, which together support affective self-processing, evaluative self-monitoring, autobiographical retrieval, and self-other distinction. Early-stage AD preferentially affects these default mode network hubs, initiating a cascading network failure that begins with posterior DMN collapse and progressively burdens downstream executive and self-monitoring systems (Jones et al., 2016). Nevertheless, compensatory hyperconnectivity in regions such as the precuneus can temporarily sustain self-monitoring functions during mild cognitive impairment (Wang et al., 2019). This pattern of neural preservation explains why interventions targeting primary anosognosia exhibit a sustained therapeutic window, meaning a residual capacity for intervention responsiveness even as broader neurodegenerative processes advance. In cognitively normal individuals, dmPFC and dACC activity reflect the need for change, allowing behavior adaptation and updated internal models of the world (Clairis & Lopez-Persem, 2023).

The pattern of neural preservation in this pathway explains why primary anosognosia interventions remain effective even in later disease stages. Although MCI and AD are associated with decreased vmPFC-PCC/PCu functional connectivity disrupting self-evaluation and monitoring, reduced dmPFC activation correlating with greater anosognosia for personality traits, and TPJ dysfunction affecting self-representation, sufficient residual functional integrity remains to permit targeted intervention responses (Dillen et al., 2017; Jedidi et al., 2014; Jobson et al., 2021; Lattanzio et al., 2021). According to the CAM, primary anosognosia emerges when impairments in metacognitive awareness prevent conscious access to failures or deficits independent of real-time performance monitoring deficits (Morese et al., 2018; Morris & Mograbi, 2013). Neuroimaging findings further highlight that dysfunction within medial prefrontal regions, particularly ACC hypofunctionality, contributes to reduced self-awareness even when basic cognitive monitoring is preserved (Morese et al., 2018).

Effect sizes for these interventions show interesting domain specificity: emotional and psychosocial outcomes (anxiety reduction, depressive symptom amelioration, quality of life enhancement) demonstrate more robust and sustained improvements (η²p = 0.09 - 0.11) than changes in objective cognitive performance (Larouche et al., 2019). Importantly, Bertrand et al. (2016) emphasize that despite impairments in direct self-monitoring, many individuals with AD retain the ability to access awareness through indirect or perspective-taking strategies, supporting the notion that primary anosognosia interventions can successfully restore aspects of self-awareness even as cognitive deficits advance. Emerging evidence suggests that interventions enhancing metacognitive awareness, particularly those supporting emotional processing and self-evaluation, may produce sustained improvements in subjective well-being even as cognitive decline progresses (Bampa et al., 2024; Bertrand et al., 2016).

Integrating Network Perspectives with Pathway-Specific Approaches

This pathway-specific framework benefits from integration with broader network neuroscience perspectives. The observed differential effectiveness of interventions likely reflects not only pathway-specific vulnerabilities but also compensatory network dynamics articulated in the Scaffolding Theory of Aging and Cognition (STAC) (Reuter-Lorenz & Park, 2014). The Default Mode Network (DMN), Central Executive Network (CEN), and Salience Network (SN) provide compensatory relationships between pathways, potentially explaining why some individuals with similar clinical presentations respond differently to specific intervention approaches. Recent evidence from dynamic functional network connectivity studies shows that variability in triple-network dynamics distinguishes AD, MCI, and cognitively normal individuals, suggesting that individual differences in network engagement contribute to heterogeneity in cognitive outcomes (Meng et al., 2022). Structural compensation at both regional and global network levels has also been demonstrated, with mTL reorganization emerging early and whole-brain compensatory recruitment expanding with disease progression (Sheng et al., 2021). Furthermore, compensatory hyperactivation of executive and frontal networks in early AD has been shown to mask cognitive deficits, highlighting how resilience mechanisms can delay clinical symptom emergence despite underlying pathology (Torrealba et al., 2023). These findings underscore the importance of tailoring metacognitive interventions not only to affected pathways but also to the individual's remaining compensatory network capacity.

The Primary Anosognosia Pathway, in particular, shows strong connections to broader network dynamics. Global meta-processing engages the rvlPFC, a region shown to support introspection, awareness of competence, and self-evaluation (Burgess & Wu, 2013). Fleming et al. (2012) demonstrated that rvlPFC activity increases during self-monitoring tasks correlates with subjective confidence and predicting metacognitive accuracy across individuals, highlighting its key role in conscious performance monitoring. Complementing this, evidence from cognitive control research emphasizes that prefrontal subregions, including the rvlPFC and amPFC, are not isolated operators but dynamically coordinate goal-directed behavior by biasing internal representations and facilitating flexible integration across multiple cognitive networks (Friedman & Robbins, 2022). Specifically, the amPFC likely acts as a gating mechanism, regulating access to conscious awareness and influencing metacognitive fidelity in memory retrieval (Friedman & Robbins, 2022). Structural evidence further supports this integrative role: Weiller et al. (2025) identified the medial prefrontal cortex (MPFC) as a key hub within a "meta-loop" system, anatomically linking the medial and lateral brain networks responsible for internal self-reference, Theory of Mind, and flexible cognitive control. Disruption of this MPFC-centered hub architecture, particularly its convergence with ventral association tracts, compromises the integration of internal and external information streams, providing a neuroanatomical basis for the impaired metacognitive awareness observed in primary anosognosia (Weiller et al., 2025). Together, these prefrontal hubs serve as critical integrators across the default mode, salience, and executive control networks and may enable compensatory reorganization when specific pathways deteriorate.

Individual variability in the preservation of network hubs may partly account for heterogeneity in intervention outcomes. This aligns with findings that hub disruption severity in AD tracks progression even in preclinical stages and varies across individuals depending on the preservation of global network hubs (Tu et al., 2024). The PCC, a highly connected and metabolically active hub within the DMN, plays a crucial role in mediating the balance between internally and externally directed attention, conscious awareness, and arousal regulation (Leech & Sharp, 2014). For instance, the PCC acts as a critical convergence point between the mnemonic and primary anosognosia pathways, potentially explaining why interventions targeting autobiographical memory sometimes produce broader improvements in self-awareness. This role is reinforced by findings that self-related processes are primarily driven via PCC activity, which organizes self-representations and interfaces with broader conscious monitoring systems (Davey et al., 2016). Furthermore, emerging evidence suggests functional segregation within the PCC itself, with ventral PCC primarily supporting internally directed cognition and dorsal PCC regulating attentional metastability across networks, offering a potential mechanistic explanation for differential patterns of anosognosia and responsiveness to interventions targeting self-awareness (Leech & Sharp, 2014). Likewise, prefrontal hubs situated at the interface of executive control and metacognitive awareness pathways may enable compensatory processing when one system deteriorates. Notably, MPFC activity has been shown to regulate and moderate PCC-driven self-representations, functioning as a flexible ‘gateway’ that selects internal information streams for conscious self-awareness, a mechanism potentially critical for resilience to early network disruption (Davey et al., 2016).

This network perspective suggests that optimal intervention selection should consider not only primary pathway targets but also potential compensatory mechanisms. Emerging evidence from multimodal lifestyle-based interventions demonstrates that targeting multiple domains simultaneously, such as physical activity, cognitive training, and nutrition, can enhance cognitive resilience by leveraging preserved network dynamics (Soldevila-Domenech et al., 2025). Structured multimodal interventions with higher intensity and sustained adherence have been particularly associated with cognitive benefits, highlighting the importance of engaging compensatory systems rather than focusing narrowly on isolated deficits (Soldevila-Domenech et al., 2025). Multimodal interventions engaging multiple pathways simultaneously may prove particularly effective by leveraging preserved network dynamics to compensate for localized deficits.

Clinical Implications and Future Directions

Findings from this meta-analysis have direct implications for clinical practice and future research. First, stage-specific intervention selection is critical, as the optimal approach should evolve with disease progression. In the early stages (i.e., SCD or MCI), mnemonic and executive interventions yield substantial benefits. For example, the ASPIRE metacognitive group intervention demonstrated greater benefits for participants with SCD compared to those with MCI (Rotenberg et al., 2024). As the disease advances to mild-moderate dementia, comparator-focused approaches become increasingly important for maintaining psychological well-being and residual awareness, as evidenced by the effectiveness of CST in later stages (Bertrand et al., 2023). Second, personalized intervention pathways should address individual differences in neural vulnerability patterns. Cognitive assessment batteries should differentiate between mnemonic, executive, and primary anosognosia to guide intervention selection. This approach aligns with the differential deterioration patterns observed across the three pathways. Third, combined pathway approaches should be considered in future intervention designs. Multi-component interventions like CST demonstrate engagement across multiple pathways, with improvements in both cognitive awareness (ηp² = .10, p = .012) and social functioning, suggesting synergistic effects when addressing multiple metacognitive systems concurrently (Bertrand et al., 2023). Fourth, biomarker-guided intervention represents a promising frontier, as advances in neuroimaging and fluid biomarkers offer tools for precise pathway assessment. Research should explore whether biomarker profiles can predict differential intervention responsiveness across the three pathways, consistent with the neurobiological framework outlined by Salmon et al. (2024). Fifth, long-term efficacy assessment remains a critical research priority. Few studies extend beyond 3-month follow-up, limiting our understanding of intervention sustainability. Longitudinal studies tracking both cognitive and neural outcomes are needed to determine whether interventions delay awareness decline or fundamentally alter disease trajectory.

Methodological Considerations and Limitations

Several methodological considerations warrant attention when interpreting current findings. First, the heterogeneity of outcome measures across studies complicates the direct comparison of intervention effectiveness. Standardization of metacognitive assessment tools would facilitate more precise cross-study comparisons in future research. Second, the current pathway classification, while neurobiologically grounded, represents a simplification of complex and interconnected neural systems. Individual interventions likely engage multiple pathways to varying degrees, and future research should employ network analysis techniques to capture these nuanced effects more precisely. Third, individual differences in cognitive reserve, genetic factors, and comorbid pathologies may moderate intervention responsiveness in ways not fully captured by this pathway framework. Future studies should explore these potential moderating factors to refine intervention selection criteria. Finally, the evidence base remains limited by relatively small sample sizes, short follow-up periods (typically ≤3 months), and variable methodological quality across studies. Many trials lack active control conditions or employ inconsistent outcome measures, complicating cross-study comparisons. Larger, multi-center trials with longer follow-up periods and standardized assessment protocols are needed to establish definitive recommendations for clinical practice.

Conclusion

This pathway-specific analysis of metacognitive interventions in AD represents an important step toward more precise, neurobiologically informed treatment selection. By mapping interventions to specific neural systems and examining differential effectiveness across disease stages, this meta-analysis provides an empirical foundation for tailoring metacognitive approaches to individual needs and preserved capabilities.

The evidence suggests that mnemonic interventions offer robust benefits in early disease stages, executive interventions demonstrate stage-limited efficacy with diminishing returns in advanced disease, and interventions targeting the Primary Anosognosia Pathway (Metacognitive Awareness System) provide sustainable benefits across the disease spectrum. The latter is particularly noteworthy, as structures such as the vmPFC, dmPFC, PCC/PCu, and TPJ maintain sufficient functional capacity to respond to intervention even in moderate dementia.

Future research should build on this framework to develop personalized intervention protocols that target preserved neural systems while accounting for individual variability in disease presentation and progression. Promising directions include examining how global meta-processing mechanisms supported by the rvlPFC and amPFC can be leveraged to enhance metacognitive functions even when memory and executive systems show substantial deterioration. By integrating pathway-specific approaches with network neuroscience perspectives, clinicians and researchers can move toward more effective metacognitive interventions that enhance quality of life and functional independence across the Alzheimer's disease continuum.

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