Executive functions predict verbal fluency scores in healthy participants

Abstract

While there is a clear link between impairments of executive functions (EFs), i.e. cognitive control mechanisms that facilitate goal-directed behavior, and speech problems, it is so far unclear exactly which of the complex subdomains of EFs most strongly contribute to speech performance, as measured by verbal fluency (VF) tasks. Furthermore, the impact of intra-individual variability is largely unknown. This study on healthy participants (n = 235) shows that the use of a relevance vector machine approach allows for the prediction of VF performance from EF scores. Based on a comprehensive set of EF scores, results identified cognitive flexibility and inhibition as well as processing speed as strongest predictors for VF performance, but also highlighted a modulatory influence of fluctuating hormone levels. These findings demonstrate that speech production performance is strongly linked to specific EF subdomains, but they also suggest that inter-individual differences should be taken into account. Executive functions (EFs) refer to a set of cognitive processes that allow for goal-directed behavior through the regulation of various cognitive subprocesses. Since EFs permeate behavior, they also impact daily activities as well as social and personal development, including school or job success 1. The importance and pervasiveness of EFs has led different fields of study to investigate these control mechanisms with the goal of differentiating the various subdomains of EFs. This, in turn, has resulted in a number of different conceptualizations based on different approaches, all attempting to subdivide EFs into different domains. While a consensus does not yet exist about how exactly to subdivide and name EFs, there is general agreement that there are three core EFs: (1) cognitive flexibility, (2) working memory and (3) inhibition 1 (but see Karr et al. 2,3). Higher-order EFs, such as reasoning, planning and problem solving, are then built on the basis of these subdomains. The various sub-domains of EFs have been shown to be impaired in a number of neurological and psychiatric diseases, such as attention-deficit/hyperactivity disorder (ADHD) 4 , Parkinson's disease 5 , depression 6 and schizophrenia 7. Different diseases present their own typical EF deficits and clinical diagnosis attempts to assess the specific patterns of the disease. For example, in the case of Parkinson's disease, patients suffer from difficulties in dual-tasking which is reflected in the deficient combination of memorizing and manipulation of thoughts and tasks 8 but also in impaired speech characterized by semantic paraphasias and reduced word fluency due to a lack of EFs 5,9. To assess these symptoms different test batteries have been developed. These batteries, which include tests tapping into the different EF sub-domains, are used for neuropsychological assessment in both clinical settings and lab-based environments. Commonly used batteries are the Delis-Kaplan Executive Function System (D-KEFS) and the Vienna Test System, both of which offer a w...

Comprehensive verbal fluency features predict executive function performance

“…In both analyses, variables which are not directly linked to EF performance but rather represent overall processing speed or reaction times, were predicted significantly. Similar findings were reported in our previous study predicting VF sum scores from EF tests variables 96 . The relationship of processing speed and sVF performance is also reported in other studies 83 , 97 .…”

Age-dependent contribution of domain-general networks to semantic cognition

“…Hence, these regions may not be language-specific but appear to strongly contribute to a task that requires goal-directed controlled access to semantic memory while monitoring the verbal articulation of words that match the semantic categories. Further support for the contribution of executive functions to semantic fluency stems from behavioral studies that associated cognitive flexibility, inhibition, working memory, and attention with a successful performance (Aita et al, 2018; Amunts et al, 2020; Gordon et al, 2018). Although activations in regions of the MDN have been reported by studies on semantic fluency repeatedly (Heinzel et al, 2013; Nagels et al, 2012; Whitney et al, 2009), to our knowledge, this is the first investigation that related them to a cognitive control network in an integrative manner (in the direct comparison of language and cognitive control networks).…”

Performance on verbal fluency tasks depends on the given category/letter: Preliminary data from a multivariable analysis

“…Studies report ambiguous results regarding the relationship between core EFs (i.e., working memory, inhibitory control, and cognitive flexibility) and VF performance (Amunts et al 2020).…”

“…Therefore, Aita et al (2018) incorporated various measures of EFs including fluid reasoning, working memory, shifting, and updating, while using the same methodology for both PF and SF tasks as Whiteside et al The findings of these two studies were not consistent, since Aita et al showed that multiple aspects of EFs were significantly related to both PF and SF. Regarding cognitive flexibility, Amunts et al (2020) pointed to significant relation between multiple tests of cognitive flexibility (i.e., WCST and TMT) and VF performance (animals, jobs). Importantly, this study used a time span of 2 minutes, while other studies mentioned here used 60 seconds, which is more common.…”