Primary Progressive Aphasia is a heterogeneous neurodegenerative disorder, characterized by a primary decline in language functions (Mesulam, 1982). Patients with PPA are usually categorized into one of the three distinct variants: semantic (svPPA), nonfluent (nfvPPA) and logopenic (lvPPA). Each variant is associated with diverse neuropsychological profiles, distinct regions of brain atrophy, even diverse pathologies (Gorno-Tempini et al., 2008). Specifically, while svPPA and nfvPPA are primarily caused by tauopathies, the most common underlying pathology for lvPPA is Alzheimer’s disease (AD). The dissociation of lvPPA from the other two variants has also been highlighted in the literature as a challenge to define and diagnose lvPPA compared to the other two variants (Keator et al., 2019, Mesulam et al., 2012, Neophytou et al., 2019, Themistocleous et al., 2021, Wilson et al., 2009). A recent study has also shown that atrophy in lvPPA follows two distinct neural pathways, which could be associated with the heterogeneity in the clinical presentation of this population (Mandelli et al., 2023). On the other hand, a recent meta-analysis suggests that lvPPA is a rather consistent syndrome (Conca et al., 2022). The ongoing debate around this population suggests that further research is required to understand the underlying cognitive deficits , which can then be leveraged to design efficient treatment protocols (Rising and Beeson, 2020).

According to the consensus criteria by Gorno-Tempini et al. (2011), lvPPA is primarily characterized by impaired single-word retrieval as well as impaired repetition of phrases and sentences. Particular emphasis has also been given to phonological working memory impairments in this population (Gorno-Tempini et al., 2008), with research showing an association between their phonological working memory impairments and their sentence repetition deficits (Arslan et al., 2022, Beales et al., 2019, Macoir et al., 2024). The proper functioning of the phonological working memory is argued to support verbal learning, since the temporary storage of verbal information mediates the creation of long-term memory records (Baddeley et al., 1998). Evidence in support of this hypothesis comes from studies with children with developmental language disorders who show poor single-word repetition skills - due, for example, to a faster than usual decay of the phonological traces - but with intact phonological perception abilities (Gathercole and Baddeley, 1989, Gathercole and Baddeley, 1990). Supporting evidence also comes from studies on foreign language learning in older healthy adults where phonological similarity of learned words shows an effect on vocabulary learning (Papagno et al., 1991, Papagno and Vallar, 1992). Seminal case studies of patients with phonological working memory impairments also corroborate this hypothesis by showing severe long-term phonological learning deficits in the context of adequate learning in tasks that do not heavily rely on phonological working memory processes (Baddeley, 1993, Baddeley et al., 1988, Trojano and Grossi, 1995). Finally, research in language learning treatment in aphasia has also provided supporting evidence for a relationship between phonological working memory skills and the success of learning treatments (for a review see: Peñaloza et al., 2022).

Given the prominence of phonological working memory impairment in lvPPA (Gorno-Tempini et al., 2008), one would expect then that verbal learning abilities in this population would be widely studied. However, very few studies have investigated the verbal learning abilities of these individuals so far. These few relevant studies have grouped lvPPA together with other PPA variants, which prevents us from clearly characterizing the verbal learning abilities in lvPPA. Nonetheless, these studies still report impaired learning abilities across PPA individuals, particularly as indexed by verbal effortless learning and verbal delayed retrieval (Kielb et al., 2016, Weintraub et al., 2013). To the best of our knowledge, there are no investigations focusing on the verbal learning abilities of lvPPA specifically (i.e., in isolation from the other PPA variants) and how that relates to their neurophysiological profile.

With respect to cortical atrophy, PPA is characterized by greater left than right hemisphere atrophy - as expected by a primarily language disorder (Gorno-Tempini et al., 2011, Mesulam, 1982). In lvPPA, the major areas of atrophy are temporo-parietal areas, specifically the left temporoparietal junction areas, the posterior temporal gyrus, the supramarginal and angular gyri, as well as the inferior parietal lobule (Conca et al., 2022, Gorno-Tempini et al., 2011, Gorno-Tempini et al., 2008, Mandelli et al., 2023, Rohrer et al., 2013). Atrophy in these regions has shown associations with the various behavioral symptoms of lvPPA (Breining et al., 2022, Leyton et al., 2012, Lukic et al., 2019, Win et al., 2017), with a recent study showing that naming and repetition performance in lvPPA are associated with atrophy in two distinct brain networks (Mandelli et al., 2023). The naming-related network, centered around the angular gyrus, was shown to spread along the posterior components of the Default Mode Network (DMN) – a network previously implicated in AD. The repetition-related network, centered around the perisylvian language region, encompassed areas of the speech perception network. Thus, disruptions of these two distinct functional brain networks are believed to explain the core language symptoms in lvPPA and the heterogeneity that it is often observed in this population.

While the cognitive and neuroimaging profile of lvPPA has been extensively studied, electrophysiological studies in PPA are quite scarce. In particular, the few electrophysiological studies that include lvPPA so far suggest that electrophysiological data can be extremely useful both for the differential diagnosis of PPA variants, including the challenging lvPPA (Cecchetti et al., 2024, Chriskos et al., 2025, Moral-Rubio et al., 2021, Quinn et al., 2025, Ranasinghe et al., 2017), as well as for understanding behavioral changes in this population (Dial et al., 2021, Utianski et al., 2019). Particularly relevant to the current study are recent studies in lvPPA that highlight the increased delta power density across the brain, increased left posterior theta power density and decreased alpha and beta band activity in posterior regions compared to healthy controls, both in resting state electroencephalography (EEG) (Cecchetti et al., 2024, Quinn et al., 2025), as well as in resting state magnetoencephalography (MEG) (Kielar et al., 2019, Ranasinghe et al., 2017).

A similar electrophysiological profile during resting-state has also been reported for a variety of neurological populations, such as AD, which is the primary underlying pathology in lvPPA (Babiloni et al., 2007, Babiloni et al., 2013, Caso et al., 2012, Huang et al., 2000, Kwak, 2006 - for a review see also: Jafari et al., 2020), for nfvPPA, which is primarily characterized by frontotemporal lobar degeneration (FTLD) tauopathy (Kielar et al., 2019, Quinn et al., 2025), as well as in post-stroke aphasia (Arheix-Parras et al., 2023, Hensel et al., 2004, Kamada et al., 1997, Spironelli and Angrilli, 2009). However, in svPPA, which is primarily characterized by another type of FTLD pathology, TDP-43, no increases in lower frequency bands have been observed (Lindau et al., 2003, Quinn et al., 2025). With respect to higher frequency bands (alpha and beta), contradictory findings have been reported, with some studies showing decreases (Kielar et al., 2022, Lindau et al., 2003) and a recent study showing increases (Quinn et al., 2025). Therefore, while increased slow-band activity and increased high-band activity is often perceived as indicative of neurological damage, this pattern is not ubiquitous across neurological conditions. The extent to which the underlying pathology relates to discrepancies in the observed changes of electrophysiological activity remains an open question, which requires investigations based on confirmed pathological profiles across populations.

The few studies on the electrophysiological profiles of lvPPA either made no associations with the behavioral profiles of this population (Cecchetti et al., 2024), or used task-related EEG recordings (Dial et al., 2021). While task-based EEG might provide more targeted information as to the electrophysiological activity that supports a given behavior, there are important limitations to such paradigms. A considerable constraint is that valid interpretation of task-based EEG recordings requires relatively high accuracy on the task in hand. Along the same line, task-based EEG paradigms usually require relatively long recordings to collect a large number of trials to be able to average activity over. In the context of impaired population research these goals are not always easy to achieve. Therefore, resting-state EEG holds an advantage over task-based EEG paradigms in patient-oriented studies. Additionally, in the context of neurodegenerative disorders, it is important to be able to test and re-test people without worrying about potential learning effects. A deeper understanding of the information that resting-stage EEG signal holds can be very beneficial for tracking disease progression, while circumventing this concern. To understand the information that resting-stage EEG signal holds, we need to investigate the relationship of resting-state electrophysiological activity with behavior, which, to the best of our knowledge, no prior studies have done in lvPPA. Given the evidence of altered resting-state EEG patterns in this group across frequency bands, it is important to try and understand how their overall electrophysiological profile relates to their behavioral profile - in this case, their verbal learning impairments. In turn, this could lead to the development of new, more targeted intervention protocols. For example, this line of research provides important insights as to what frequency bands we should target in future neuromodulation treatment studies for lvPPA, especially if the neuromodulation treatment is coupled with verbal learning treatment.

The present study is a preliminary investigation to understand how the electrophysiological profile of lvPPA individuals relates to their behavioral profile. Specifically, we wanted to know if and how EEG measurements relate to verbal learning abilities in lvPPA. To achieve this, we used short (three-minute) EEG recordings from only eight channels to record resting-state activity and investigated their relationship to learning scores from a single task. The use of a small number of electrodes has great advantages when studying clinical populations as it facilitates data collection, while it also makes it a viable option for researchers and clinicians with limited resources. Learning abilities were measured using the Sum of Trials score from the Rey Auditory Verbal Learning Test (RAVLT) (Rey, 1958). A plethora of previous studies have highlighted the usefulness of RAVLT scores in the study of neurodegenerative disorders, and of AD in particular. RAVLT scores have been successfully used in the past for the early diagnosis of AD (Estévez-González et al., 2003) and in differentiating AD from other disorders (Ricci et al., 2012, Schoenberg et al., 2006). On the other hand, RAVLT scores have also been found to be predictable based on MRI data in AD, specifically, with respect to the integrity of the angular gyrus (Moradi et al., 2017). These neural associations with the RAVLT scores are in accordance with previous work utilizing various other measurements of learning (for a review see: Jeong et al., 2015). RAVLT scores have also been used to differentiate lvPPA individuals with respect to the severity of their neurocognitive deficits (Owens et al., 2018). Despite the interest in RAVLT scores in AD and its clinical variants, to the best of our knowledge, no prior studies have investigated how RAVLT scores relate to the electrophysiological profiles of these populations. Thus, the current investigation aimed to understand if resting-state EEG activity is related to the verbal learning abilities in lvPPA, as measured using RAVLT Sum of Trials scores. Unveiling such a relationship could be rather informative for future studies on lvPPA diagnosis and treatment, particularly in the context of neuromodulation.