The Ease of Language Understanding (ELU) model: theoretical, empirical, and clinical advances

Abstract

Working memory is important for online language processing during conversation. We use it to maintain relevant information, to inhibit or ignore irrelevant information, and to attend to conversation selectively. Working memory helps us to keep track of and actively participate in conversation, including taking turns and following the gist. This paper examines the Ease of Language Understanding model (i.e., the ELU model, Rönnberg, 2003; Rönnberg et al., 2008) in light of new behavioral and neural findings concerning the role of working memory capacity (WMC) in uni-modal and bimodal language processing. The new ELU model is a meaning prediction system that depends on phonological and semantic interactions in rapid implicit and slower explicit processing mechanisms that both depend on WMC albeit in different ways. It is based on findings that address the relationship between WMC and (a) early attention processes in listening to speech, (b) signal processing in hearing aids and its effects on short-term memory, (c) inhibition of speech maskers and its effect on episodic long-term memory, (d) the effects of hearing impairment on episodic and semantic long-term memory, and finally, (e) listening effort. New predictions and clinical implications are outlined. Comparisons with other WMC and speech perception models are made.

Predictive processing increases intelligibility of acoustically distorted speech: Behavioral and neural correlates

“…According to this interpretation, the impact of memory in speech comprehension progressively increases when the quality of the acoustic signal decreases, until at the extreme forms of distortion, speech comprehension becomes a cued memory task. Related ideas have been presented in the Ease of Language Understanding (ELU) model that describes how and when working memory is involved in disambiguating acoustically distorted speech, and how it interacts with long‐term memory (LTM) during this process (Baddeley, 2000; Rönnberg, Rudner, Lunner, & Zekveld, 2010; Rönnberg et al., 2013; Rudner & Rönnberg, 2008). This model suggests that in easy listening conditions, sensory information matches with the corresponding syllabic phonological representation in semantic LTM, resulting in rapid memory retrieval.…”

How do the medial olivocochlear efferents influence the biomechanics of the outer hair cells and thereby the cochlear amplifier? Simulation results

“…It is well known today that higher cognitive processes can modulate the auditory periphery via descending pathways and control what auditory information reaches the brain cortices [10,11,13]. In the presented work, the effect of biomechanical changes, induced by MOC efferents, on the gain of the cochlear amplifier was investigated by means of a physiologically-based model.…”

“…It becomes more complex as the sound-induced signals ascend toward more central parts of the auditory system and brain cortices [2,11]. Over six decades ago Rasmussen discovered the olivocochlear efferents, fiber projections that descend from the superior olivary complex in the brainstem toward the inner ear [9].…”

“…Over six decades ago Rasmussen discovered the olivocochlear efferents, fiber projections that descend from the superior olivary complex in the brainstem toward the inner ear [9]. It is well known today that hearing involves various ascending (afferent) and descending (efferent) pathways interacting with each other on different levels [10,11,13].…”

PyVDT: A PsychoPy-Based Visual Sequence Detection Task

“…The association between working memory and speech perception first reported by Knutson et al [8] is central to the Ease of Language Understanding (ELU) model [12]. Rönnberg et al [12] theorize that working memory is beneficial to speech perception in difficult listening conditions (i.e., background noise), since -according to the ELU model -working memory helps maintain relevant information while inhibiting irrelevant information.…”