Hofstra Horizons Research

Cognitive and Language Neurophysiological Indices for Early-Stage Alzheimer’s Disease

Susan M. DeMetropolis, MA, CCC-SLP, Instructor of Speech-Language-Hearing Sciences, Hofstra University
Speech-Language-Hearing Sciences Programs

How does the mind represent meaning of words or morphemes, and how does it combine these to represent the meaning of phrases and sentences? How does lexical access change as an individual ages and in neurodegenerative diseases, such as in Alzheimer’s disease?

Alzheimer’s disease (AD) is a degenerative brain disorder defined by neocortical atrophy, neuron and synapse loss and senile plaque, and neurofibrillary tangles in the hippocampus and in the association areas of the frontal, temporal, and parietal lobes (Hyman et al., 1984; Terry et al., 1991). One of the more common symptoms of AD is the progressive deterioration of cognitive functions, specifically language impairments.

The most common clinical manifestation of AD is impairment in episodic memory, which is learning and recalling specific facts from a spatiotemporal context, such as knowing you ate a banana for breakfast. Episodic memory and attentional deficits have been the focus of research with AD. There have been fewer studies on semantic memory, i.e., knowing objects, facts, concepts, words, and meaning (Tulving, 1983). An example of semantic memory would be knowing that a banana is yellow, that it grows on trees, and that you peel and eat it.

As a speech-language pathologist, I know how we assess and treat individuals with different types of dementia, including Alzheimer’s disease. We are not the ones to diagnose the disease, but many times, we assist in making a clinical profile of cognitive and language strengths and weaknesses for these patients. As clinicians, we use paper-pen tests that ask “wh” questions, as well as repetition tasks, confrontation naming, description, following commands, and drawing figures (i.e., clock, bucket, and kite). In a study I did for the American Speech-Language-Hearing Association (ASHA) in 2014, I compared lexical access of verbs vs. nouns with healthy older adults and those with early-stage AD. I used a standardized language and cognitive battery used by speech-language pathologists called the Arizona Battery for Communication in Dementia (ABCD) (Bayles & Tomoeda, 1993) and the criterion-referenced Northwestern Naming Battery (Thompson & Weintraub, 2014). The results of my study indicated that there was no difference in naming noun pictures (e.g., apple); however, there were differences with naming transitive verbs vs. intransitive verbs, in which it was more challenging for the individuals with AD to name transitive verbs (i.e., an object associated with the action; “stirring” which uses the object of a spoon). I also found differences on a linguistic expression subtest of the ABCD in which healthy individuals were descriptive in their responses with functions-verbs, descriptions-adjectives, and categorical-noun information. The individuals with AD responded with more functions and categorical information, and lacked the descriptive information.

As a clinical researcher, I decided to take these behavioral results further and find out more of what is happening in the semantic system of someone with a neurodegenerative disease such as AD at both the neural and behavioral level. A central question with the semantic system is whether the semantic system is progressively degrading, or is it that individuals cannot easily access their semantic system? This storage vs. access question has been debated from different theoretical perspectives, and further research will inform us on how to best navigate the semantic systems for speech and language/cognition therapy for many of the patients we assess and treat.

Figure 1: Set-up for EEG with electrodes on scalp and EEG reading on external computer  with experiment playing in front of the participant.

I designed a dissertation study that uses both behavioral and electrophysiological measures to gain more information on how the semantic system is breaking down in individuals with AD. I am using healthy adults as controls so that we can get more insight on differential diagnoses for typical aging processes and how we can differentiate these pathologies, such as in AD. Word retrieval problems are an indication of how aging affects older adults’ semantic processing. This is a common complaint as healthy elderly age and for individuals in the early stage of AD and their family members. As the baby boomer generation continues to age, this research is important to advance the specific changes we might observe in the semantic system, and thus, will affect the way we communicate with others.

My current research study involves using the cognitive screening Mini-Mental State Examination (MMSE) (Folstein, Folstein, & McHugh, 1975), the ABCD standardized test for overall cognitive and language skills and verification of the stage of AD, and the Pyramids and Palm Tree Test (Howard & Patterson, 1992), which is a standardized test that determines how a person can retrieve semantic information from pictures vs. words. A full hearing test is done in collaboration with the AuD students (consortium with St. John’s, Hofstra, and Adelphi) to rule out any hearing impairments for participation in the EEG part. The EEG portion involves a noninvasive net of 128 electrodes being placed on participants’ scalps. Participants look at a computer screen for a semantic priming task of pictures (black-white line drawings) and hear a consonant-vowel-consonant (CVC) word (e.g., hot, food, rake) in which the words are divided into 25 congruent descriptions/adjectives (e.g., picture: whale; word: “big”); 25 incongruent descriptions/adjectives (e.g., picture: razor; word: “dull”); 25 congruent functions/verbs (e.g., picture: boy swinging bat; word: “hit”); 25 incongruent functions/verbs (e.g., picture: boy throwing snowball; word: “fall”); 25 congruent categories/nouns (e.g., picture: hamburger; word: “food”), and 25 incongruent categories/nouns (e.g., picture: pumpkin; word: “job”).

Figure 2: Semantic experiment with sentences in which one word is congruent and one word is incongruent.The N400 is a component of time-locked EEG signals known as event-related potentials (ERPs). It is a negative-going deflection that peaks around 400 milliseconds post-stimulus onset, a lthough it can extend from 250 to 500 ms, and is typically maximal over centro-parietal electrode sites.
Retrieved from: https://www.researchgate.net/publication/273063386_Event-related_Potentials_ERPs_in_Second_Language_Research_A_Brief_Introduction_to_the_Technique_a_Selected_Review_and_an_Invitation_to_Reconsider_Critical_Periods_in_L2/figures?lo=1scalp-for-an-eeg-electroencephalogram

In addition to behavioral research, semantic priming has been examined using EEG markers such as event-related potentials (ERPs). ERPs are a nonintrusive measure of electrical brain activity that provides continuous information about the sequence and timing of brain activity. ERPs are time-locked to the onset of a stimulus or response and are characterized by voltage peaks and troughs that vary in size, timing, or scalp distribution with changes in stimulus, response, and cognitive processing parameters (Schwartz et al., 2003).

I am looking at the N400, first described in 1980 (Kutas & Hillyard, 1980). The N400 is a large effect seen in response to words and final words in sentences that are anomalous; it is much smaller or not present in congruent sentence completions as a function of their predictability, or how expected the words are within a given context (Kutas & Hillyard, 1984). The N400 is useful in assessing how semantic analysis is affected by typical aging and by neurological disorders, such as AD.

In clinical practice, semantic deficits are detected by naming or semantic fluency tasks that require conscious retrieval of semantic information through explicit tasks (Rogers & Friedman, 2008). Marques (2007) suggested that conceptual relations need to be studied through tasks that consider the common features of objects (e.g., visual, auditory, tactile, spatial).

Figure 3: Dissection of the N400 component.
Retrieved from: https://www.nrc-cnrc.gc.ca/eng/achievements/highlights/2005/brain_activity.html

This research is designed to give clinicians and researchers semantic information to better design assessment tools and therapy programs that could better assist individuals with
AD with their semantic memory skills for communication. The electrophysiological testing provides more neural information on timing and activation location to give us more insight into the sensitivity of behavioral testing in our clinical practice.

Figure 4: Multiple brain regions are involved in memory encoding. Processing conceptual networks that share few common features is more demanding than processing those with a greater number of features, such as concepts at the superordinate level (e.g., animals). Analysis of the associative network in semantic memory shows that semantic impairment in AD reflects the segregation of concepts (Caputi et al., 2016).
Retrieved from: http://slideplayer.com/slide/4395156/14/images/31/Figure+17.8+Encoding,+Consolidation,
+and+Retrieval+of+Declarative+Memories.jpg

References

  • Bayles, K. A., & Tomoeda, C. K. (1993). Arizona battery for communication disorders of dementia. Austin, TX: PRO-ED.
  • Caputi, N., Di Giacomo, D., Aloisio, F., & Passafiume, D. (2016). Deterioration of semantic associative relationships in mild cognitive impairment and Alzheimer disease. Applied Neuropsychology: Adult, 23(3), 186-195.
  • Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). “Mini-mental state.” A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12, 189-198.
  • Howard, D., & Patterson, K. (1992). Pyramids and palm trees: A test of semantic access from pictures and words. Bury St. Edmunds: Thames Valley Test Company.
  • Hyman, B. T., Van Hoesen, G. W., Damasio, A. R., & Barnes, C. L. (1984). Alzheimer’s disease: Cell-specific pathology isolates the hippocampal formation. Science, 225, 1168-1170.
  • Katzman, R. (1991). Physical basis of cognitive alterations in Alzheimer’s disease: Synapse loss is the major correlate of cognitive impairment. Annals of Neurology, 30, 572-580.
  • Kutas, M., & Hillyard, S. A. (1980). Reading senseless sentences: Brain potentials reflect semantic incongruity. Science, 207, 203-205.
  • Kutas, M., & Hillyard, S. A. (1984). Brain potentials during reading reflect word expectancy and semantic association. Nature, 307, 161-163.
  • Marques, J. F. (2007). The general/specific breakdown of semantic memory and the nature of superordinate knowledge: Insights from superordinate and basic-level feature norms. Cognitive Neuropsychology, 24, 879-903.
  • Rogers, S. L., & Friedman, R. B. (2008). The underlying mechanisms of semantic memory loss in Alzheimer’s disease and semantic dementia. Neuropsychologia, 46, 12-21.
  • Terry, R. D., & Katzman, R. (1983). Senile dementia of the Alzheimer type. Annals of Neurology, 14, 497-506.
  • Terry, R. D., Masliah, E., Salmon, D. P., Butters, N., DeTeresa, R. Hill, R. Hansen, L. A., & Thompson, C., & Weintraub, S. (2014). The Northwestern Battery. Evanston, IL.
  • Tulving, E. (1983). Elements of episodic memory. Oxford: Clarendon.

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