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Recent studies suggest that synaptic lysophosphatidic acids (LPAs) augment glutamate-dependent cortical excitability and sensory information processing in mice and humans via presynaptic LPAR2 activation. Here, we studied the consequences of LPAR2 deletion or antagonism on various aspects of cognition using a set of behavioral and electrophysiological analyses. Hippocampal neuronal network activity was decreased in middle-aged LPAR2−/− mice, whereas hippocampal long-term potentiation (LTP) was increased suggesting cognitive advantages of LPAR2−/− mice. In line with the lower excitability, RNAseq studies revealed reduced transcription of neuronal activity markers in the dentate gyrus of the hippocampus in naïve LPAR2−/− mice, including ARC, FOS, FOSB, NR4A, NPAS4 and EGR2. LPAR2−/− mice behaved similarly to wild-type controls in maze tests of spatial or social learning and memory but showed faster and accurate responses in a 5-choice serial reaction touchscreen task requiring high attention and fast spatial discrimination. In IntelliCage learning experiments, LPAR2−/− were less active during daytime but normally active at night, and showed higher accuracy and attention to LED cues during active times. Overall, they maintained equal or superior licking success with fewer trials. Pharmacological block of the LPAR2 receptor recapitulated the LPAR2−/− phenotype, which was characterized by economic corner usage, stronger daytime resting behavior and higher proportions of correct trials. We conclude that LPAR2 stabilizes neuronal network excitability upon aging and allows for more efficient use of resting periods, better memory consolidation and better performance in tasks requiring high selective attention. Therapeutic LPAR2 antagonism may alleviate aging-associated cognitive dysfunctions.
Pitch peaks tend to be higher at the beginning of longer than shorter sentences (e.g., ‘A farmer is pulling donkeys’ vs ‘A farmer is pulling a donkey and goat’), whereas pitch valleys at the ends of sentences are rather constant for a given speaker. These data seem to imply that speakers avoid dropping their voice pitch too low by planning the height of sentence-initial pitch peaks prior to speaking. However, the length effect on sentence-initial pitch peaks appears to vary across different types of sentences, speakers and languages. Therefore, the notion that speakers plan sentence intonation in advance due to the limitations in low voice pitch leaves part of the data unexplained. Consequently, this study suggests a complementary cognitive account of length-dependent pitch scaling. In particular, it proposes that the sentence-initial pitch raise in long sentences is related to high demands on mental resources during the early stages of sentence planning. To tap into the cognitive underpinnings of planning sentence intonation, this study adopts the methodology of recording eye movements during a picture description task, as the eye movements are the established approximation of the real-time planning processes. Measures of voice pitch (Fundamental Frequency) and incrementality (eye movements) are used to examine the relationship between (verbal) working memory (WM), incrementality of sentence planning and the height of sentence-initial pitch peaks.
Highlights
• A big dataset reveals age-related alterations in EEG biomarkers and cognition.
• Prominent decline of individual alpha peak frequency primarily in temporal lobes.
• A positive association between individual alpha peak frequency and working memory.
• Absence of age-related alpha power decline when controlling for 1/f decay of the PSD.
• Alpha power is negatively associated with the speed of processing in elderly sample.
Abstract
While many structural and biochemical changes in the brain have previously been associated with older age, findings concerning functional properties of neuronal networks, as reflected in their electrophysiological signatures, remain rather controversial. These discrepancies might arise due to several reasons, including diverse factors determining general spectral slowing in the alpha frequency range as well as amplitude mixing between the rhythmic and non-rhythmic parameters. We used a large dataset (N = 1703, mean age 70) to comprehensively investigate age-related alterations in multiple EEG biomarkers taking into account rhythmic and non-rhythmic activity and their individual contributions to cognitive performance. While we found strong evidence for an individual alpha peak frequency (IAF) decline in older age, we did not observe a significant relationship between theta power and age while controlling for IAF. Not only did IAF decline with age, but it was also positively associated with interference resolution in a working memory task primarily in the right and left temporal lobes suggesting its functional role in information sampling. Critically, we did not detect a significant relationship between alpha power and age when controlling for the 1/f spectral slope, while the latter one showed age-related alterations. These findings thus suggest that the entanglement of IAF slowing and power in the theta frequency range, as well as 1/f slope and alpha power measures, might explain inconsistencies reported previously in the literature. Finally, despite the absence of age-related alterations, alpha power was negatively associated with the speed of processing in the right frontal lobe while 1/f slope showed no consistent relationship to cognitive performance. Our results thus demonstrate that multiple electrophysiological features, as well as their interplay, should be considered for the comprehensive assessment of association between age, neuronal activity, and cognitive performance.