Tag: Verbal working memory

Students with language disorders have difficulties that extend beyond language. There is an extensive research literature linking weaknesses in broader cognitive skills such as attention, processing speed, executive functioning, short term and working memory with language disorders (Leonard et al, 2007, 2013, Henry and Botting, 2017).

Short term and working memory have received particular attention. Whilst some studies have identified weaknesses in the nonverbal component, suggestive of domain-general impairments in this population, deficits in verbal short term memory (VSTM) and verbal working memory (VWM) have been more consistently reported, and found to be 2-3 times larger (Vugs et al, 2013). What’s more, poor performance on nonword repetition tasks, widely used to test VSTM, is even considered a clinical marker for Developmental Language Disorder (DLD) (Bishop et al, 2016).

VSTM and VWM are often used interchangeably, but VSTM might be more accurately considered a component of VWM. VSTM refers to the ability to hold information just heard in mind for a short period of time before it “decays” and has historically been thought of as a “storage space” with limited capacity. Indeed, most people are only able to keep three or four chunks of information in their heads at once (Montgomery et al, 2021).

Meanwhile, VWM involves manipulation as well as storage of information, and is increasingly being thought of more as a “mental workspace”. Others have spoken of VWM in terms of a set of cognitive processes that include sustained attention, inhibition of irrelevant information, and the ability to switch simultaneously between maintenance of stored information and processing new information (Marton et al, 2007, Leonard et al, 2013).

Various theories of working memory have been proposed in the past, one of the most influential being Baddeley and Hitch’s multicomponent model, made up of two passive storage systems: the “phonological loop” (or VSTM) and “visuo-spatial sketchpad”, as well as a “central executive” and “episodic buffer” (Baddeley and Hitch, 1974, Baddeley, 2000).

According to this, the phonological loop stores speech-based and verbal information (and could be considered what we refer to as VSTM). Whilst information typically fades away after a couple of seconds, it is possible to keep it in an active state for longer through silent repetition (such as when you repeat a phone number or code to yourself). The visuospatial sketchpad stores visual information in a similar fashion, whilst the central executive acts as the control centre, dividing and switching attention between different tasks. Meanwhile, the episodic buffer binds the information together, and acts as an interface between short and long-term memory.

VSTM and VWM are considered essential to learning in the classroom, from following lengthy instructions and understanding what’s going on in lessons, to keeping the steps of a task in mind and recalling the details of a story. Working memory has been found to be a more powerful predictor of academic achievement even than IQ (Alloway and Alloway, 2010). Students with poor VWM may appear inattentive, forgetful or careless, when really they are struggling to retain what was said.

VWM is also considered to be intrinsically linked to comprehension of complex sentences, since certain elements have to be kept in mind, and even moved around whilst the next part is processed. Long, complex sentences require more processing time than simple sentences, and are not as easily understood (e.g. Marton et al, 2007), suggesting that increased VWM capacity is required to understand such sentences. Montgomery et al (2009) argued that comprehension of both simple and complex grammar is a mentally demanding task for school age children with and without language disorders that requires significant working memory resources.

Other authors such as Balthazar and Scott (2023) have spoken at length about the various elements that can increase the processing “load” of a sentence. This includes the number of clauses, long distance dependencies (gaps), as well as (in English) anything that disrupts the subject-verb-object order such as passive constructions and post-modification of the noun phrase (see my post for more information).

Take the following example sentence given by Marilyn Nippold (2010) from a science text book: “organisms that eat living corals, such as the crown-of-thorns sea star, can greatly damage reefs”. In this sentence, post-modification of the noun “organisms” with the phrase “that eat living corals, such as the crown-of-thorns sea star” results in an extended gap between the main subject and verb. This whole phrase must then be stored in VSTM (or the phonological loop according to the Baddeley model) until the reader reaches the main action, “can greatly damage” and understands what the sentence is about.

For a student with a language disorder and limited VWM, this is likely to be challenging. Other studies have shown that adolescents with DLD do not understand complex sentences as well as their typically developing peers, despite similar performance for simple sentences (Montgomery et al, 2009). Some researchers have even gone so far as to argue that VWM difficulties, rather than poor language knowledge are the primary cause of receptive language difficulties in older students (Larson and McKinley, 2003).

However, recent research suggests that the reality may be more complex. Indeed, there is some evidence to suggest that complex sentences are processed in different ways by those with and without language disorders, with working memory playing an unequal role in each. In a large scale study of 117 children with DLD and 117 typically developing peers aged 7-11, Montgomery et al (2021) investigated how a range of measures were connected with comprehension of simple and more complex sentences.

They found that fluid reasoning and language knowledge residing in long-term memory (LTM) indirectly influenced comprehension of complex, non-canonical sentences in typically developing students. For those with DLD, on the other hand, controlled attention (an important facet of working memory), was more important (Montgomery et al, 2021).

On the back of this research, they came up with a new memory model, the GEM (Gillam-Evans-Montgomery) model, where VWM serves as a conduit for fluid reasoning, controlled attention and long-term language knowledge. They argued that listeners face the challenge of a rapid incoming stream of speech in different ways (Montgomery et al, 2021).

According to them, repeated experience with language allows most people to build up linguistic representations in long-term memory (LTM). Typically developing listeners are able to activate these patterns, some of which may take the form of multiword templates, to anticipate the types of words that are likely to come next, as well as to “chunk” the speech stream into noun phrases, verb phrases and even whole clauses. This information is then stored as chunks, reducing the demands on working memory capacity, before being reintegrated into a coherent whole (Montgomery et al, 2021).

They hypothesized that students with DLD may have weaker, or non-existent representations of certain grammatical structures. This means that they will be unable to segment the speech stream in the same way as their peers, resulting in word by word processing which places enormous pressure on an already overstretched VWM. Accordingly, sentence processing is much more effortful for those with language disorders (Montgomery et al, 2021).

This theory seems to be backed up by a review of the literature. Karavasilis et al (2023) found inconclusive evidence of a link between VSTM/ VWM and complex sentence comprehension in typically developing individuals. On the other hand, there was a consistent link between working memory and sentence comprehension in those with DLD. The authors concluded that, at least for children with DLD, a processing component is involved in comprehension of complex sentences.

According to Montgomery et al (2021), the solution is not to attempt to improve students’ VWMs (which, in any case, has had limited success), but rather, to support their language representations in long-term memory.

Notes

Alloway, Tracy Packiam, and Ross G. Alloway. “Investigating the Predictive Roles of Working Memory and IQ in Academic Attainment.” Journal of Experimental Child Psychology 106, no. 1 (May 2010): 20–29.

Baddeley, Alan D., and Graham J. Hitch. 1974. “Working Memory.” In The Psychology of Learning and Motivation: Advances in Research and Theory, edited by Gordon H. Bower, Vol. 8, 47–89. New York: Academic Press.

Baddeley, A.D. (2000). The episodic buffer: A new component of working memory? Trends in Cognitive Sciences, 4, 417-423.

Baddeley, Alan. 2003. “Working Memory: Looking Back and Looking Forward.” Nature Reviews Neuroscience 4, no. 10: 829–39.

Balthazar, Catherine H., and Cheryl M. Scott. “Sentences Are Key.” American Journal of Speech-Language Pathology 33, no. 2 (2023): 564–579.

Bishop DVM, Snowling MJ, Thompson PA, Greenhalgh T, CATALISE consortium (2016)

CATALISE: A Multinational and Multidisciplinary Delphi Consensus Study. Identifying Language Impairments in Children. PLoS ONE 11(7): e0158753. doi:10.1371/journal.pone.0158753

Haebig, Eileen, Christine Weber, Laurence B. Leonard, Patricia Deevy, and J. Bruce Tomblin. “Neural Patterns Elicited by Sentence Processing Uniquely Characterize Typical Development, SLI Recovery, and SLI Persistence.” Journal of Neurodevelopmental Disorders 9, no. 1 (2017): 22.

Henry, L. & Botting, N. (2017). Working memory and developmental language impairments. Child Language Teaching and Therapy, 33(1), pp. 19-32.

Karavasilis, Gavriil, K. Diakogiorgi, and D. Papadopoulou. 2023. “The Role of Working Memory in the Comprehension of Syntactically Complex Sentences in Children with and without Developmental Language Disorder: A Literature Review.” Psychology: The Journal of the Hellenic Psychological Society 28 (2): 205–222.

Larson, V.L. and McKinley, N.L. (2003) Communication solutions for older students. Thinking Pub. 

Leonard, Laurence B., Patricia Deevy, James W. Miller, Chrystal Rameela, Robert Schwartz, and J. Bruce Tomblin. “Speed of Processing, Working Memory, and Language Impairment in Children.” Journal of Speech, Language, and Hearing Research 50, no. 2 (April 2007): 408–428. 

Leonard, Laurence B., Patricia Deevy, Marc E. Fey, and Shelley L. Bredin-Oja. “Sentence Comprehension in Specific Language Impairment: A Task Designed to Distinguish between Cognitive Capacity and Syntactic Complexity.” Journal of Speech, Language, and Hearing Research 56, no. 2 (April 2013): 577-589.

Marton, Klara, Richard G. Schwartz, Lajos Farkas, and Valeriya Katsnelson. “Effect of Sentence Length and Complexity on Working Memory Performance in Hungarian Children with Specific Language Impairment: A Cross-Linguistic Comparison.” International Journal of Language & Communication Disorders 42, no. 6 (2007): 691–711.

McCauley, Stewart M., and Morten H. Christiansen. 2015. “Individual Differences in Chunking Ability Predict On-line Sentence Processing.” In Proceedings of the 37th Annual Conference of the Cognitive Science Society, edited by D. C. Noelle et al., 1550–1555. Austin, TX: Cognitive Science Society. 

Montgomery, James W., and Julia L. Evans. 2009. “Complex Sentence Comprehension and Working Memory in Children with Specific Language Impairment.” Journal of Speech, Language, and Hearing Research 52, no. 2 (April): 269-288.

Montgomery, James W., Ronald B. Gillam, and Julia L. Evans. “A New Memory Perspective on the Sentence Comprehension Deficits of School-Age Children With Developmental Language Disorder: Implications for Theory, Assessment, and Intervention.” Language, Speech, and Hearing Services in Schools 52, no. 2 (April 2021): 449–466.

Newman, Sharlene D., Evie Malaia, Roy Seo, and Hu Cheng. “The effect of individual differences in working memory capacity on sentence comprehension: an fMRI study.” Brain and Language 125, no. 3 (2013): 269-277.

Nippold, Marilyn A. 2010. “Back to School: Why the Speech-Language Pathologist Belongs in the Classroom.” Language, Speech, and Hearing Services in Schools 41 (4): 377–378.

Vugs, B., Cuperus, J., Hendriks, M., & Verhoeven, L. (2013). Visuospatial working memory in specific language impairment: A meta-analysis. Research in Developmental Disabilities, 34(9), 2596-2597.