Beyond the limitations of any imaginable mechanism: Large language models and psycholinguistics.

Large language models (LLMs) are not detailed models of human linguistic processing. They are, however, extremely successful at their primary task: Providing a model for language. For this reason LLMs are important in psycholinguistics: They are useful as a practical tool, as an illustrative comparative, and philosophically, as a basis for recasting the relationship between language and thought.

Reward conditioning may not have an effect on category-specific memory.

Behavioural tagging facilitates the temporary storage of seemingly insignificant episodic events, which may later become salient and enhanced in memory. Human behavioural studies have demonstrated selective memory enhancement for neutral stimuli from one category when this category is subsequently paired with reward. Although this phenomenon has implications for the role of reward conditioning on emotional and adaptive memory, its generalisability is underexplored. We conducted four experiments to investigate whether pairing items from a semantic category, animals or objects, with high or low rewards resulted in preferential memory for the high-reward category. Three of these experiments also aimed to replicate the category-specific retrospective enhancement effect reported by Patil et al. and two explored the corresponding prospective memory effect. None of our experiments showed consistent evidence for an effect of reward on category-specific memory enhancement, despite employing the same reward paradigm and incidental encoding protocol as in the original study. Consequently, we found no evidence for category-specific retrospective or prospective enhancement effects. Our experiments were conducted online which is an equally relevant method for assessing behavioural phenomenon as the in-person studies conducted by Patil et al. Overall, our results question the generalisability of previously reported category-specific memory enhancement effects due to reward.

The neural ingredients for a language of thought are available.

The classical notion of a 'language of thought' (LoT), advanced prominently by the philosopher Jerry Fodor, is an influential position in cognitive science whereby the mental representations underpinning thought are considered to be compositional and productive, enabling the construction of new complex thoughts from more primitive symbolic concepts. LoT theory has been challenged because a neural implementation has been deemed implausible. We disagree. Examples of critical computational ingredients needed for a neural implementation of a LoT have in fact been demonstrated, in particular in the hippocampal spatial navigation system of rodents. Here, we show that cell types found in spatial navigation (border cells, object cells, head-direction cells, etc.) provide key types of representation and computation required for the LoT, underscoring its neurobiological viability.

Illustrations of interactions needed when investigating sleep using a type of AM-PM PM-AM design.

Sleep has long been thought of and promoted to be beneficial for memory. Some claims that sleep aids memory have been made in the absence of a critical interaction. This condition is necessary when using a commonly-used experimental design (a type of AM-PM PM-AM design). We propose that a sleep effect exists only if there is an interaction between groups (experimental and time-of-day controls) and the time of test or study (morning and evening). We show different patterns of results that would and would not support a sleep effect with empirical and model-generated data from recognition memory experiments and hypothetical data. While we use these data to make our point, our suggestions apply to any memory and non-memory-related investigation (e.g., emotional memory, false memory susceptibility, language learning, problem-solving). Testing for and finding the proper interaction will add to the evidence that sleep boosts performance.

What neural oscillations can and cannot do for syntactic structure building.

Understanding what someone says requires relating words in a sentence to one another as instructed by the grammatical rules of a language. In recent years, the neurophysiological basis for this process has become a prominent topic of discussion in cognitive neuroscience. Current proposals about the neural mechanisms of syntactic structure building converge on a key role for neural oscillations in this process, but they differ in terms of the exact function that is assigned to them. In this Perspective, we discuss two proposed functions for neural oscillations - chunking and multiscale information integration - and evaluate their merits and limitations taking into account a fundamentally hierarchical nature of syntactic representations in natural languages. We highlight insights that provide a tangible starting point for a neurocognitive model of syntactic structure building.

Syllable-Initial Phonemes Affect Neural Entrainment to Consonant-Vowel Syllables.

Neural entrainment to speech appears to rely on syllabic features, especially those pertaining to the acoustic envelope of the stimuli. It has been proposed that the neural tracking of speech depends on the phoneme features. In the present electroencephalography experiment, we examined data from 25 participants to investigate neural entrainment to near-isochronous stimuli comprising syllables beginning with different phonemes. We measured the inter-trial phase coherence of neural responses to these stimuli and assessed the relationship between this coherence and acoustic properties of the stimuli designed to quantify their "edginess." We found that entrainment was different across different classes of the syllable-initial phoneme and that entrainment depended on the amount of "edge" in the sound envelope. In particular, the best edge marker and predictor of entrainment was the latency of the maximum derivative of each syllable.

Frequency tagging of syntactic structure or lexical properties; a registered MEG study.

A traditional view on sentence comprehension holds that the listener parses linguistic input using hierarchical syntactic rules. Recently, physiological evidence for such a claim has been provided by Ding et al.'s (2016) MEG study that demonstrated, using a frequency-tagging paradigm, that regularly occurring syntactic constituents were spontaneously tracked by listeners. Even more recently, this study's results have been challenged as artifactual by Frank and Yang (2018) who successfully re-created Ding's results using a distributional semantic vector model that relied exclusively on lexical information and did not appeal to any hierarchical syntactic representations. The current MEG study was designed to dissociate the two interpretations of Ding et al.'s results. Taking advantage of the morphological richness of Russian, we constructed two types of sentences of different syntactic structure; critically, this was achieved by manipulating a single affix on one of the words while all other lexical roots and affixes in the sentence were kept the same. In Experiment 1, we successfully verified the intuition that due to almost complete lexical overlap the two types of sentences should yield the same activity pattern according to Frank and Yang's (2018) lexico-semantic model. In Experiment 2, we recorded Russian listeners' MEG activity while they listened to the two types of sentences. Contradicting the hierarchical syntactic account and consistent with the lexico-semantic one, we observed no difference across the conditions in the way participants tracked the stimuli properties. Corroborated by other recent evidence, our findings show that peaks interpreted by Ding et al. as reflecting higher-level syntactic constituency may stem from non-syntactic factors.

A large-scale brain network mechanism for increased seizure propensity in Alzheimer's disease.

People with Alzheimer's disease (AD) are 6-10 times more likely to develop seizures than the healthy aging population. Leading hypotheses largely consider hyperexcitability of local cortical tissue as primarily responsible for increased seizure prevalence in AD. However, in the general population of people with epilepsy, large-scale brain network organization additionally plays a role in determining seizure likelihood and phenotype. Here, we propose that alterations to large-scale brain network organization seen in AD may contribute to increased seizure likelihood. To test this hypothesis, we combine computational modelling with electrophysiological data using an approach that has proved informative in clinical epilepsy cohorts without AD. EEG was recorded from 21 people with probable AD and 26 healthy controls. At the time of EEG acquisition, all participants were free from seizures. Whole brain functional connectivity derived from source-reconstructed EEG recordings was used to build subject-specific brain network models of seizure transitions. As cortical tissue excitability was increased in the simulations, AD simulations were more likely to transition into seizures than simulations from healthy controls, suggesting an increased group-level probability of developing seizures at a future time for AD participants. We subsequently used the model to assess seizure propensity of different regions across the cortex. We found the most important regions for seizure generation were those typically burdened by amyloid-beta at the early stages of AD, as previously reported by in-vivo and post-mortem staging of amyloid plaques. Analysis of these spatial distributions also give potential insight into mechanisms of increased susceptibility to generalized (as opposed to focal) seizures in AD vs controls. This research suggests avenues for future studies testing patients with seizures, e.g. co-morbid AD/epilepsy patients, and comparisons with PET and MRI scans to relate regional seizure propensity with AD pathologies.

Grammatical category and the neural processing of phrases.

The interlocking roles of lexical, syntactic and semantic processing in language comprehension has been the subject of longstanding debate. Recently, the cortical response to a frequency-tagged linguistic stimulus has been shown to track the rate of phrase and sentence, as well as syllable, presentation. This could be interpreted as evidence for the hierarchical processing of speech, or as a response to the repetition of grammatical category. To examine the extent to which hierarchical structure plays a role in language processing we recorded EEG from human participants as they listen to isochronous streams of monosyllabic words. Comparing responses to sequences in which grammatical category is strictly alternating and chosen such that two-word phrases can be grammatically constructed-cold food loud room-or is absent-rough give ill tell-showed cortical entrainment at the two-word phrase rate was only present in the grammatical condition. Thus, grammatical category repetition alone does not yield entertainment at higher level than a word. On the other hand, cortical entrainment was reduced for the mixed-phrase condition that contained two-word phrases but no grammatical category repetition-that word send less-which is not what would be expected if the measured entrainment reflected purely abstract hierarchical syntactic units. Our results support a model in which word-level grammatical category information is required to build larger units.

Impact of Induced Moods, Sensation Seeking, and Emotional Contagion on Economic Decisions Under Risk.

In addition to probabilities of monetary gains and losses, personality traits, socio-economic factors, and specific contexts such as emotions and framing influence financial risk taking. Here, we investigated the effects of joyful, neutral, and sad mood states on participants' risk-taking behaviour in a simple task with safe and risky options. We also analysed the effect of framing on risk taking. In different trials, a safe option was framed in terms of either financial gains or losses. Moreover, we investigated the effects of emotional contagion and sensation-seeking personality traits on risk taking in this task. We did not observe a significant effect of induced moods on risk taking. Sad mood resulted in a slight non-significant trend of risk aversion compared to a neutral mood. Our results partially replicate previous findings regarding the presence of the framing effect. As a novel finding, we observed that participants with a low emotional contagion score demonstrated increased risk aversion during a sad mood and a similar trend at the edge of significance was present in high sensation seekers. Overall, our results highlight the importance of taking into account personality traits of experimental participants in financial risk-taking studies.

EEG microstate complexity for aiding early diagnosis of Alzheimer's disease.

The dynamics of the resting brain exhibit transitions between a small number of discrete networks, each remaining stable for tens to hundreds of milliseconds. These functional microstates are thought to be the building blocks of spontaneous consciousness. The electroencephalogram (EEG) is a useful tool for imaging microstates, and EEG microstate analysis can potentially give insight into altered brain dynamics underpinning cognitive impairment in disorders such as Alzheimer's disease (AD). Since EEG is non-invasive and relatively inexpensive, EEG microstates have the potential to be useful clinical tools for aiding early diagnosis of AD. In this study, EEG was collected from two independent cohorts of probable AD and cognitively healthy control participants, and a cohort of mild cognitive impairment (MCI) patients with four-year clinical follow-up. The microstate associated with the frontoparietal working-memory/attention network was altered in AD due to parietal inactivation. Using a novel measure of complexity, we found microstate transitioning was slower and less complex in AD. When combined with a spectral EEG measure, microstate complexity could classify AD with sensitivity and specificity > 80%, which was tested on an independent cohort, and could predict progression from MCI to AD in a small preliminary test cohort of 11 participants. EEG microstates therefore have potential to be a non-invasive functional biomarker of AD.

Fast Periodic Visual Stimulation indexes preserved semantic memory in healthy ageing.

Behavioural studies investigating the preservation of semantic memory in healthy ageing have reported mixed findings. One suggested reason for this discrepancy is that the processes underpinning lexical access to semantic knowledge may be sensitive to ageing. It is therefore necessary to assess semantic memory utilising tasks that are not explicitly linguistic. In this study, a fast periodic visual stimulation (FPVS) paradigm coupled with EEG was used to assess the ability of younger and older adults to automatically distinguish between images by their semantic category. Participants were presented with a 6 Hz stream of images drawn from one semantic category except every fifth image (occurring at a rate of 1.2 Hz) which was drawn from an alternate semantic category. For both younger and older adults, results demonstrate successful and comparable semantic categorisation. This was detectable at the individual level for 71% and 72% of older and younger adults, respectively. Given the rapid presentation rate and absence of explicit instruction to categorise images, the task is unlikely to utilise linguistic strategies and suggests the maintenance of semantic memory in healthy ageing. Moreover, this study utilised mobile EEG equipment and short presentation times that would be suitable for practical application outside a research setting.

Fragments Along the Way: Minimalism as an Account of Some Stages in First Language Acquisition.

We discuss two instances in which the minimalist model of syntax offers a potential account of children's linguistic behavior: the Merge analysis of phrase structure and the analysis of pronominal structures and other long distance dependencies. In each case, we need to understand the relationship between performance mechanisms (the mechanisms for language production and comprehension) and the syntax on which these mechanisms draw.

A 'no' with a trace of 'yes': A mouse-tracking study of negative sentence processing.

There is strong evidence that comprehenders can parse sentences in an incremental fashion. However, when the sentence contains a negation, the evidence is less clear. Previous work has shown that increasing the pragmatic felicity of a negative sentence reduces or eliminates any processing overhead relative to affirmative sentences. However, in previous work felicity has gone hand-in-hand with the predictability of critical material in a sentence. In three experiments reported here, we presented equally felicitous sentences with critical material of varying predictability (operationalised as the number of possible completions) to test whether this might be a critical factor determining the ease with which partial sentences containing a negation are interpreted. Participants completed a truth-value judgement task (Experiment 1) or a sentence completion task (Experiments 2 and 3) after viewing a visual environment that provided the context for a test sentence, which could differ in truth value (in Experiment 1 only), polarity (affirmative or negative), and number of possible completions (one, two, or three). In all three experiments, we recorded response times and accuracy, but also response dynamics via participants' computer mouse trajectories, allowing us to test specific hypotheses about the time course of comprehension. Across all experiments, in conditions with one or two possible targets, we observed consistent detrimental effects of negative polarity, suggesting that the difficulty in processing negation cannot be reduced to effects relating to predictability or pragmatic felicity. We discuss this finding in relation to incremental and two-stage models of processing and outline a new account of the processing difficulty arising from negation in terms of a conflict between what is locally activated on the basis of individual words and phrases and the global meaning of a negative sentence.

Dissociable effects of prediction and integration during language comprehension: evidence from a large-scale study using brain potentials.

Composing sentence meaning is easier for predictable words than for unpredictable words. Are predictable words genuinely predicted, or simply more plausible and therefore easier to integrate with sentence context? We addressed this persistent and fundamental question using data from a recent, large-scale (n = 334) replication study, by investigating the effects of word predictability and sentence plausibility on the N400, the brain's electrophysiological index of semantic processing. A spatio-temporally fine-grained mixed-effect multiple regression analysis revealed overlapping effects of predictability and plausibility on the N400, albeit with distinct spatio-temporal profiles. Our results challenge the view that the predictability-dependent N400 reflects the effects of either prediction or integration, and suggest that semantic facilitation of predictable words arises from a cascade of processes that activate and integrate word meaning with context into a sentence-level meaning. This article is part of the theme issue 'Towards mechanistic models of meaning composition'.

Network substrates of cognitive impairment in Alzheimer's Disease.

OBJECTIVES: Functional and structural disconnection of the brain is a prevailing hypothesis to explain cognitive impairment in Alzheimer's Disease (AD). We aim to understand the link between alterations to networks and cognitive impairment using functional connectivity analysis and modelling. METHODS: EEG was recorded from 21 AD patients and 26 controls, mapped into source space using eLORETA, and functional connectivity was calculated using phase locking factor. The mini-mental state exam (MMSE) was used to assess cognitive impairment. A computational model was used to uncover mechanisms of altered functional connectivity. RESULTS: Small-worldness (SW) of functional networks decreased in AD and was positively correlated with MMSE score and the language sub-score. Reduced SW was a result of increased path lengths, predominantly localized to the temporal lobes. Combining observed differences in local oscillation frequency with reduced temporal lobe effective connectivity in the model could account for observed functional network differences. CONCLUSIONS: Temporal lobe disconnection plays a key role in cognitive impairment in AD. SIGNIFICANCE: We combine electrophysiology, neuropsychological scores, and computational modelling to provide novel insight into the relationships between the disconnection hypothesis and cognitive decline in AD.