Cognitive Profiles in Neurotypical Individuals and Aphasia: A Comparative Study of Fluent and Non-Fluent Variants

INTRODUCTION

Cognition is a mental process in which the sensory input is “transformed, reduced, elaborated, stored, recovered, and used”. It encompasses five primary domains of cognition: “attention, memory, executive functions, language, and visuospatial skills”. Cognitive control contributes to a wide range of mental processes, including “working memory, semantic short-term memory, language comprehension, and language production”.^[1] Cognitive functions are affected due to an acquired neurological condition, disease process, or mental health disorder. Aphasia, an acquired language disorder due to a neurological condition, may occur alone or with other cognitive disorders based on the lesion areas, affected brain area, and mechanism of cerebral reorganisation.^[2] Both language production and comprehension are constrained by diminished cognitive control. In persons with aphasia (PWA), the communicative skills are often compromised by cognitive impairments in addition to linguistic deficits, and this relationship between cognition and language function is stronger in severe aphasic conditions.

Several studies support the link between cognitive performance and language outcomes in aphasia. In PWA, there was a significant correlation between Raven’s progressive matrices and better performance in naming and language comprehension tasks following therapy.^[3] Moreover, it was observed that individuals with aphasia performed worse than neurologically healthy individuals on cognitive control tasks, showing a clear association between cognitive control performance and overall language impairment. Cognitive control is reported to vary according to the aphasia type.^[4] The core deficit in fluent aphasia (FA) is impaired linguistic selection, leading to phonemic paraphasia, semantic errors, and circumlocutions.^[5] In contrast, the non-fluent aphasia (NFA) involves disrupted syntactic organisation due to impaired sequencing of syllables, words, and syntactic structures.^[6] These deficits in selection (in FA) and sequencing (in NFA) resemble the extra-linguistic process of cognitive control.^[5] Considering the distinct linguistic impairments in FA and NFA and the strong link between cognitive control and language deficits, it is crucial to examine whether cognitive control impacts language similarly across aphasia types.

Impairments in cognition significantly influence the rehabilitation outcomes of individuals with aphasia, affecting their ability to engage in and benefit from therapeutic interventions. While aphasia is traditionally viewed as a disorder of language processing, increasing attention over recent decades has been directed toward the cognitive abilities of PWA. This growing interest reflects the significance of investigating cognition in aphasia (FA and NFA). A deeper understanding of cognitive functions in PWA can inform the development, adaptation, and implementation of language rehabilitation approaches that integrate cognitive profiles, enhancing the effectiveness and long-term outcomes of intervention. Understanding the differences in cognition between FA and NFA is particularly important, as it can guide more targeted assessment and individualised treatment planning based on specific cognitive-linguistic needs. Therefore, the study aims to compare the cognitive profile of neurotypical individuals with persons with aphasia, including fluent and non-fluent aphasia.

MATERIAL AND METHODS

We conducted a comparative study to evaluate cognitive abilities in PWA and healthy controls. The participants were recruited using purposive sampling based on the availability and inclusion criteria. A total of 20 participants (10 FA and 10 NFA) following cerebrovascular accident were recruited for the study, and the control group consisted of 10 participants (neurotypical individuals [NTIs]) without aphasia and no history of any neurological conditions or psychiatric illness. Control participants were matched for age and sex of PWA. The demographic details of the participants are shown in Table 1. Inclusion criteria required participants to be native Tamil speakers, right-handed, and to have self-reported normal vision and hearing abilities. Monolinguals and bilinguals were included, but the L1 should be Tamil. The diagnosis of aphasia was made based on the administration of the Western Aphasia Battery-R^[7] with Tamil as the language of administration by a speech-language pathologist. The participant was made to sit comfortably, and the assessment was carried out in a quiet room with minimal distractions and adequate lighting. Based on WAB-R, the participants were classified as FA and NFA. The NFA group comprised individuals with Broca’s aphasia and transcortical motor aphasia, while the FA group included individuals with Wernicke’s aphasia, conduction aphasia, and anomic aphasia, as classified based on the WAB-R scores. The general health questionnaire (GHQ-12) was administered to NTIs to confirm the absence of any health-related problems. All the assessments were carried out by an experienced speech-language pathologist fluent in Tamil. The Addenbrooke’s Cognitive Examination-III (ACE-III) in Tamil^[8] was used in the current study to assess cognition in PWA. All the participants were conscious and alert during the assessment. They have undergone the language assessment, followed by a cognitive assessment by ACE-III. The domains of ACEIII were attention, memory, fluency, language, and visuospatial abilities. The cognitive assessment using ACE-III was administered with necessary adaptations to minimise language demands, such as using simplified instructions and allowing non-verbal or alternative response modes where appropriate. The rationale for selecting ACE-III to assess cognition is that it provides a comprehensive evaluation of multiple cognitive domains while incorporating both verbal and non-verbal components, making it suitable for examining the relationship between language and cognition in PWA. All assessments were conducted at least 3 months post-onset, ensuring that participants were in the chronic phase of recovery, thereby minimising the influence of spontaneous recovery on cognitive performance. The language and cognitive assessments were conducted in separate sessions with adequate rest intervals to minimise fatigue. The study was approved by the Ethical Committee for Bio-behavioural Research involving human subjects. Informed consent was obtained from the caregivers of all the participants by explaining the need and procedure of the study before initiating the assessment. They were assured of safety during testing and confidentiality regarding their details.

RESULTS

The objective of the present study is to profile the cognitive abilities of individuals with FA and NFA and to compare their cognitive abilities with those of NTIs. The results of the study are explained in three sections, with section A being the descriptive statistics of the performance of FA, NFA, and NTIs on ACE-III, as shown in Table 2. Section B explains the comparison of the ACE-III score on cognition between FA and NFA with NTIs, as shown in Table 3.

Section A: Performance on ACE-III by PWA and NTI

Table 2 presents the median and interquartile range (IQR) of ACE-III domain scores for NTIs, FA, and NFA participants. NTIs had the highest scores across all domains. Among aphasic participants, FA individuals generally scored higher than NFA in memory, language, fluency, and visuospatial domains, while NFA participants had slightly higher attention scores. Total ACE-III scores were highest in the control group, followed by participants in the FA and NFA groups.

DISCUSSION

The current study investigated the cognitive-linguistic profiles of individuals with FA and NFA and compared their performance to NTI using the ACE-III Tamil.^[8] This comprehensive tool assesses five core cognitive domains: attention, memory, fluency, language, and visuospatial abilities, allowing for a holistic view of cognitive performance. The findings demonstrated that individuals with aphasia exhibit significant impairments across all domains compared to those without aphasia, and that cognitive deficits in aphasia extend beyond the language domain, affecting multiple aspects of neuropsychological functioning.

Descriptive statistics revealed that the NTI group scored the highest across all ACE-III domains, which was expected given their intact cognitive-linguistic abilities. Among the aphasia subtypes, participants with FA showed higher scores in memory, fluency, language, and visuospatial abilities than those with NFA. However, NFA participants outperformed FA in the attention domain. These findings partially align with existing neuroimaging literature showing that FA is often associated with posterior temporal and temporoparietal lesions and is generally characterised by well-articulated but semantically empty speech, often with deficits in auditory comprehension and semantic memory.^[5] In contrast, NFA is typically linked to lesions in the left inferior frontal gyrus and anterior insula. It features agrammatic, effortful speech and relatively preserved comprehension, which may explain the comparatively higher attention scores in NFA, possibly reflecting preserved executive monitoring or task focus. Research evidence suggests that posterior temporal and temporoparietal regions are often compromised in FA, which plays a key role in attention and monitoring.^[9,10] Conversely dorsal attentional network is spared in NFA, allowing better performance on tasks requiring attention or executive function.^[11,12]

Statistical comparisons using the Kruskal-Wallis H test revealed significant differences between the three groups across all ACE-III domains. Follow-up post-hoc analyses using Mann-Whitney U tests with Bonferroni correction confirmed that NTI individuals significantly outperformed both FA and NFA participants in all cognitive domains. Interestingly, no statistically significant differences were observed between FA and NFA in any domain. This is an important finding, suggesting that while FA and NFA differ in language output characteristics, their overall cognitive impairment levels may be comparable. It supports the growing view that aphasia is a complex neurocognitive disorder involving deficits in both language and non-linguistic cognition.^[13,14] These results are supported by network-based models of aphasia, which state that language and cognition have overlapping neural substrates and that damage results in comparable levels of cognitive deficits in FA and NFA.^[15,16]

Particularly striking were the significant group differences in the language and memory domains, where NTI individuals demonstrated the most pronounced advantage. These findings are consistent with the central role of language and memory in aphasia. Language deficits are, by definition, the hallmark of aphasia, but verbal memory impairments are also widely reported.^[17] Impaired verbal working memory can interfere with lexical retrieval, sentence processing, and discourse organisation, critical components of fluent and meaningful communication. Working memory performance was a reliable predictor of language function in aphasia, further highlighting the cognitive-linguistic interplay,^[18] and the performance of working memory is reported to be the same between FA and NFA.^[19] Similarly, individuals with post-stroke aphasia often exhibit broader cognitive deficits, particularly in attention and memory, that correlate with language impairment severity, supporting the interdependence of cognitive and linguistic processing.^[20] Language deficits in aphasia are rarely isolated; instead, they reflect disruptions in complex language networks involving phonological, lexical, and syntactic processing. The shared impairment across subtypes in our study supports a network-based view of language processing and suggests that domain-specific interventions should be customised not only by aphasia type but also by the particular linguistic components affected.^[21]

Verbal fluency is a critical indicator of both linguistic and executive functioning, and our results demonstrated significant impairment in this domain among individuals with FA and NFA compared to NTIs. Despite their clinical distinctions, both aphasia types exhibited similarly reduced fluency scores, suggesting that verbal fluency tasks tap into broader cognitive processes such as working memory, cognitive flexibility, and semantic organisation. Verbal fluency is supported by a distributed network involving frontal and temporal regions, and lesions in these areas, as seen in various types of aphasia, can disrupt performance regardless of fluency classification.^[22] Visuospatial functioning was also significantly impaired in individuals with aphasia, particularly in those with NFA types. Visuospatial deficits frequently coexist with language impairments in post-stroke aphasia due to overlapping neural involvement, especially when lesions extend beyond classical language areas. These deficits can impact the patient’s ability to process written text, follow visual cues in communication, and engage with therapy materials.^[20]

In terms of clinical application, the results support the importance of comprehensive cognitive assessments in aphasia rehabilitation. While traditional assessments focus primarily on linguistic output, tools like the ACE-III provide valuable information about non-linguistic cognitive functions such as attention and visuospatial processing. These domains are particularly relevant in treatment planning, as deficits in attention or executive functioning can reduce a patient’s capacity to engage effectively in therapy or apply learned strategies in daily life.^[14] Moreover, understanding the full cognitive profile of individuals with aphasia allows clinicians to tailor intervention goals more precisely and apply compensatory strategies that accommodate individual cognitive strengths and weaknesses. Another notable implication is the lack of a significant difference between FA and NFA in ACE-III scores. This suggests that despite different linguistic presentations, the global cognitive burden may be similar. This aligns with earlier findings that overall cognitive reserve, rather than language subtype alone, may be a stronger predictor of functional outcomes post-stroke.^[23] Therefore, differentiating patients based solely on aphasia subtype may overlook important nuances in cognitive functioning that influence recovery trajectories.

CONCLUSION

The present study examined the cognitive profiles of individuals with FA and NFA compared to NTIs using the ACE-III in Tamil. Results revealed significant cognitive impairments across all domains: attention, memory, fluency, language, and visuospatial skills in FA and NFA groups relative to NTI. Although FA participants performed better in most domains compared to non-fluent PWA, no statistically significant differences emerged between the two aphasia subtypes, indicating a comparable level of overall cognitive impairment. These findings reinforce the concept that aphasia is not merely a language disorder but a broader neurocognitive condition. The use of comprehensive cognitive assessments is therefore essential in guiding personalised treatment plans. This integrated approach can facilitate more effective and targeted rehabilitation, ultimately improving long-term outcomes for individuals with aphasia.