The Effects of Neurocognitive Aging on Sentence Processing

Across the lifespan, successful language comprehension is crucial for continued participation in everyday life. The success of language comprehension relies on the intact functioning of both language-specific processes as well as domain-general cognitive processes that support language comprehension in general. This two-sided nature of successful language comprehension may contribute to the two diverging observations in healthy aging: the preservation and the decline of language comprehension on both the cognitive and the neural level. To date, our understanding of these two competing facets is incomplete and unclear. While greater language experience comes with increasing age, most domain-general cognitive functions, like verbal working memory, decline in healthy aging. The here presented thesis shows that when the electrophysiological network relevant for verbal working memory is already compromised at rest, language comprehension declines in older adults. Moreover, it could be shown that, as verbal working memory capacity declines with age, resources may be- come insufficient to successfully encode language-specific information into memory, yielding language comprehension difficulties in old age. Age differences in the electrophysiological dynamics underlying sentence encoding indicate that the encoding of detailed information may increasingly be inhibited throughout the lifespan, possibly to avoid overloading the verbal working memory. However, limitations in verbal working memory could be attenuated by the use of language-specific constraints. That is, semantic and syntactic constraints can be used to establish relations between words which reduces the memory load from individual word information to information about word group. Here, it was found that older adults do not benefit from the use of syntactic constraints as much as younger adults while the benefit of using semantic constraints was comparable across age. Overall, the here presented thesis suggests that previous findings on language comprehension in healthy aging are not contradictory but rather converge on a simultaneous combination of selective preservation and decline of various language-specific processes, burdened by domain-general neurocognitive aging

Age differences in encoding-related alpha power reflect sentence comprehension difficulties

When sentence processing taxes verbal working memory, comprehension difficulties arise. This is specifically the case when processing resources decline with advancing adult age. Such decline likely affects the encoding of sentences into working memory, which constitutes the basis for successful comprehension. To assess age differences in encoding-related electrophysiological activity, we recorded the electroencephalogram from three age groups (24, 43, and 65 years). Using an auditory sentence comprehension task, age differences in encoding-related oscillatory power were examined with respect to the accuracy of the given response. That is, the difference in oscillatory power between correctly and incorrectly encoded sentences, yielding subsequent memory effects (SME), was compared across age groups. Across age groups, we observed an age-related SME inversion in the alpha band from a power decrease in younger adults to a power increase in older adults. We suggest that this SME inversion underlies age-related comprehension difficulties. With alpha being commonly linked to inhibitory processes, this shift may reflect a change in the cortical inhibition–disinhibition balance. A cortical disinhibition may imply enriched sentence encoding in younger adults. In contrast, resource limitations in older adults may necessitate an increase in cortical inhibition during sentence encoding to avoid an information overload. Overall, our findings tentatively suggest that age-related comprehension difficulties are associated with alterations to the electrophysiological dynamics subserving general higher cognitive functions

Event-related responses reflect chunk boundaries in natural speech

Chunking language has been proposed to be vital for comprehension enabling the extraction of meaning from a continuous stream of speech. However, neurocognitive mechanisms of chunking are poorly understood. The present study investigated neural correlates of chunk boundaries intuitively identified by listeners in natural speech drawn from linguistic corpora using magneto-and electroencephalography (MEEG). In a behavioral experiment, subjects marked chunk boundaries in the excerpts intuitively, which revealed highly consistent chunk boundary markings across the subjects. We next recorded brain activity to investigate whether chunk boundaries with high and medium agreement rates elicit distinct evoked responses compared to non-boundaries. Pauses placed at chunk boundaries elicited a closure positive shift with the sources over bilateral auditory cortices. In contrast, pauses placed within a chunk were perceived as interruptions and elicited a biphasic emitted potential with sources located in the bilateral primary and non-primary auditory areas with right-hemispheric dominance, and in the right inferior frontal cortex. Furthermore, pauses placed at stronger boundaries elicited earlier and more prominent activation over the left hemisphere suggesting that brain responses to chunk boundaries of natural speech can be modulated by the relative strength of different linguistic cues, such as syntactic structure and prosody.Peer reviewe

Acoustically driven cortical delta oscillations underpin prosodic chunking

Oscillation-based models of speech perception postulate a cortical computational principle by which decoding is performed within a window structure derived by a segmentation process. Segmentation of syllable-size chunks is realized by a theta oscillator. We provide evidence for an analogous role of a delta oscillator in the segmentation of phrase-sized chunks. We recorded Magnetoencephalography (MEG) in humans, while participants performed a target identification task. Random-digit strings, with phrase-long chunks of two digits, were presented at chunk rates of 1.8 Hz or 2.6 Hz, inside or outside the delta frequency band (defined here to be 0.5 - 2 Hz). Strong periodicities were elicited by chunk rates inside of delta in superior, middle temporal areas and speech-motor integration areas. Periodicities were diminished or absent for chunk rates outside delta, in line with behavioral performance. Our findings show that prosodic chunking of phrase-sized acoustic segments is correlated with acoustic-driven delta oscillations, expressing anatomically specific patterns of neuronal periodicities

Oscillatory delta and theta frequencies differentially support multiple items encoding to optimize memory performance during the digit span task

The human brain has limited storage capacity often challenging the encoding and recall of a long series of multiple items. Different encoding strategies are therefore employed to optimize performance in memory processes such as chunking where particular items are ‘grouped’ to reduce the number of items to store artificially. Additionally, related to the position of an item within a series, there is a tendency to remember the first and last items on the list better than the middle ones, which calls the “serial position effect”. Although relatively well-established in behavioral research, the neuronal mechanisms underlying such encoding strategies and memory effects remain poorly understood. Here, we used event-related EEG oscillation analyses to unravel the neuronal substrates of serial encoding strategies and effects during the behaviorally controlled execution of the digit span task. We recorded EEG in forty-four healthy young-adult participants during a backward digit span (ds) task with two difficulty levels (i.e., 3-ds and 5-ds). Participants were asked to recall the digits in reverse order after the presentation of each set. We analyzed the pattern of event-related delta and theta oscillatory power in the time-frequency domain over fronto-central and parieto-occipital areas during the item (digit) list encoding, focusing on how these oscillatory responses changed with each subsequent digit being encoded in the series. Results showed that the development of event-related delta power evoked by digits in each series matched the ‘serial position curve’, with higher delta power being present during the first, and especially last, digits as compared to digits presented in the middle of a set, for both difficulty levels. Event-related theta power, in contrast, rather resembled a neural correlate of a chunking pattern where, during the 5-ds encoding, a clear change in event-related theta occurred around the third/fourth positions, with decreasing power values for later digits. This suggests that different oscillatory mechanisms linked to different frequency bands may code for the different encoding strategies and effects in serial item presentation. Furthermore, recall-EEG correlations suggested that participants with higher fronto-central delta responses during digit encoding showed also higher recall scores. The here presented findings contribute to our understanding of the neural oscillatory mechanisms underlying multiple item encoding, directly informing recent efforts towards memory enhancement through targeted oscillation-based neuromodulation.Türkiye Bilimsel ve Teknolojik Araştırma Kurum

Linguistic structure and meaning organize neural oscillations into a content-specific hierarchy

Neural oscillations track linguistic information during speech comprehension (e.g., Ding et al., 2016; Keitel et al., 2018), and are known to be modulated by acoustic landmarks and speech intelligibility (e.g., Doelling et al., 2014; Zoefel & VanRullen, 2015). However, studies investigating linguistic tracking have either relied on non-naturalistic isochronous stimuli or failed to fully control for prosody. Therefore, it is still unclear whether low frequency activity tracks linguistic structure during natural speech, where linguistic structure does not follow such a palpable temporal pattern. Here, we measured electroencephalography (EEG) and manipulated the presence of semantic and syntactic information apart from the timescale of their occurrence, while carefully controlling for the acoustic-prosodic and lexical-semantic information in the signal. EEG was recorded while 29 adult native speakers (22 women, 7 men) listened to naturally-spoken Dutch sentences, jabberwocky controls with morphemes and sentential prosody, word lists with lexical content but no phrase structure, and backwards acoustically-matched controls. Mutual information (MI) analysis revealed sensitivity to linguistic content: MI was highest for sentences at the phrasal (0.8-1.1 Hz) and lexical timescale (1.9-2.8 Hz), suggesting that the delta-band is modulated by lexically-driven combinatorial processing beyond prosody, and that linguistic content (i.e., structure and meaning) organizes neural oscillations beyond the timescale and rhythmicity of the stimulus. This pattern is consistent with neurophysiologically inspired models of language comprehension (Martin, 2016, 2020; Martin & Doumas, 2017) where oscillations encode endogenously generated linguistic content over and above exogenous or stimulus-driven timing and rhythm information

Testing Low-Frequency Neural Activity in Sentence Understanding

Human language has the unique characteristic where we can create infinite and novel phrases or sentences; this stems from the ability of composition, which allows us to combine smaller units into bigger meaningful units. Composition involves us following syntactic rules stored in memory and building well-formed structures incrementally. Research has shown that neural circuits can be associated with cognitive faculties such as memory and language and there is evidence indicating where and when the neural indices of the processing of composition are. However, it is not yet clear "how" neural circuits actually implement compositional processes. This dissertation aims to probe "how" composition of meaning is represented by neural circuits by investigating the role of low-frequency neural activity in carrying out composition. Neuroelectric signals were recorded with Electroencephalography (EEG) to examine the functional interpretation of low-frequency neural activity in the so-called delta band of 0.5 to 3 Hz. Activities in this band have been associated with the processing of syntactic structures (Ding et al. 2016). First, whether these activities are indeed associated with hierarchy remains under debate. This dissertation uses a novel condition in which the same words are presented, but their order is changed to remove the syntactic structure. Only entrainment with syllables was found in this "reversed" condition, supporting the hypothesis that neural activities in the delta band entrain to abstract syntactic structures. Second, we test the timing for language users to combine words and comprehend sentences. How comprehension correlates with this low-frequency neural activity and whether it represents endogenous neural response or evoked response remains unclear. This dissertation manipulates the length of syllables and regularity between syllables to test the hypotheses. The results support the view that this neural activity reflects endogenous response and suggest that it reflects top-down processing. Third, what semantic information modulates this low-frequency neural activity is unknown. This dissertation examines several semantic variables typically associated with different aspects of semantic processing. The stimuli are created by varying the statistical association between words, world knowledge, and the conceptual results of semantic composition. The current results suggest that low-frequency neural activity is not driven by semantic processing. Based on the above findings, we propose that neural activities in the delta band reflect top-down predictive processing that involves syntactic information directly but not semantic information.PHDLinguisticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169907/1/chiawenl_1.pd

Language dysfunction in schizophrenia: Assessing neural tracking to characterize the underlying disorder(s)?

Deficits in language production and comprehension are characteristic of schizophrenia. To date, it remains unclear whether these deficits arise from dysfunctional linguistic knowledge, or dysfunctional predictions derived from the linguistic context. Alternatively, the deficits could be a result of dysfunctional neural tracking of auditory information resulting in decreased auditory information fidelity and even distorted information. Here, we discuss possible ways for clinical neuroscientists to employ neural tracking methodology to independently characterize deficiencies on the auditory–sensory and abstract linguistic levels. This might lead to a mechanistic understanding of the deficits underlying language related disorder(s) in schizophrenia. We propose to combine naturalistic stimulation, measures of speech–brain synchronization, and computational modeling of abstract linguistic knowledge and predictions. These independent but likely interacting assessments may be exploited for an objective and differential diagnosis of schizophrenia, as well as a better understanding of the disorder on the functional level—illustrating the potential of neural tracking methodology as translational tool in a range of psychotic populations