Publications

Abstract

Since the cognitive revolution, language and action have been compared as cognitive systems, with cross-domain convergent views recently gaining renewed interest in biology, neuroscience, and cognitive science. Language and action are both combinatorial systems whose mode of combination has been argued to be hierarchical, combining elements into constituents of increasingly larger size. This structural similarity has led to the suggestion that they rely on shared cognitive and neural resources. In this article, we compare the conceptual and formal properties of hierarchy in language and action using set theory. We show that the strong compositionality of language requires a particular formalism, a magma, to describe the algebraic structure corresponding to the set of hierarchical structures underlying sentences. When this formalism is applied to actions, it appears to be both too strong and too weak. To overcome these limitations, which are related to the weak compositionality and sequential nature of action structures, we formalize the algebraic structure corresponding to the set of actions as a trace monoid. We aim to capture the different system properties of language and action in terms of the distinction between hierarchical sets and hierarchical sequences and discuss the implications for the way both systems could be represented in the brain.

Abstract

In the cognitive, computational, and neuro-sciences, practitioners often reason about what computational models represent or learn, as well as what algorithm is instantiated. The putative goal of such reasoning is to generalize claims about the model in question, to claims about the mind and brain, and the neurocognitive capacities of those systems. Such inference is often based on a model’s performance on a task, and whether that performance approximates human behavior or brain activity. Here we demonstrate how such argumentation problematizes the relationship between models and their targets; we place emphasis on artificial neural networks (ANNs), though any theory-brain relationship that falls into the same schema of reasoning is at risk. In this paper, we model inferences from ANNs to brains and back within a formal framework — metatheoretical calculus — in order to initiate a dialogue on both how models are broadly understood and used, and on how to best formally characterize them and their functions. To these ends, we express claims from the published record about models’ successes and failures in first-order logic. Our proposed formalization describes the decision-making processes enacted by scientists to adjudicate over theories. We demonstrate that formalizing the argumentation in the literature can uncover potential deep issues about how theory is related to phenomena. We discuss what this means broadly for research in cognitive science, neuroscience, and psychology; what it means for models when they lose the ability to mediate between theory and data in a meaningful way; and what this means for the metatheoretical calculus our fields deploy when performing high-level scientific inference.

Abstract

To understand language, we need to recognize words and combine them into phrases and sentences. During this process, responses to the words themselves are changed. In a step towards understanding how the brain builds sentence structure, the present study concerns the neural readout of this adaptation. We ask whether low-frequency neural readouts associated with words change as a function of being in a sentence. To this end, we analyzed an MEG dataset by Schoffelen et al. (2019) of 102 human participants (51 women) listening to sentences and word lists, the latter lacking any syntactic structure and combinatorial meaning. Using temporal response functions and a cumulative model-fitting approach, we disentangled delta- and theta-band responses to lexical information (word frequency), from responses to sensory- and distributional variables. The results suggest that delta-band responses to words are affected by sentence context in time and space, over and above entropy and surprisal. In both conditions, the word frequency response spanned left temporal and posterior frontal areas; however, the response appeared later in word lists than in sentences. In addition, sentence context determined whether inferior frontal areas were responsive to lexical information. In the theta band, the amplitude was larger in the word list condition around 100 milliseconds in right frontal areas. We conclude that low-frequency responses to words are changed by sentential context. The results of this study speak to how the neural representation of words is affected by structural context, and as such provide insight into how the brain instantiates compositionality in language.

Abstract

When we comprehend language from speech, the phase of the neural response aligns with particular features of the speech input, resulting in a phenomenon referred to as neural tracking. In recent years, a large body of work has demonstrated the tracking of the acoustic envelope and abstract linguistic units at the phoneme and word levels, and beyond. However, the degree to which speech tracking is driven by acoustic edges of the signal, or by internally-generated linguistic units, or by the interplay of both, remains contentious. In this study, we used naturalistic story-listening to investigate (1) whether phoneme-level features are tracked over and above acoustic edges, (2) whether word entropy, which can reflect sentence- and discourse-level constraints, impacted the encoding of acoustic and phoneme-level features, and (3) whether the tracking of acoustic edges was enhanced or suppressed during comprehension of a first language (Dutch) compared to a statistically familiar but uncomprehended language (French). We first show that encoding models with phoneme-level linguistic features, in addition to acoustic features, uncovered an increased neural tracking response; this signal was further amplified in a comprehended language, putatively reflecting the transformation of acoustic features into internally generated phoneme-level representations. Phonemes were tracked more strongly in a comprehended language, suggesting that language comprehension functions as a neural filter over acoustic edges of the speech signal as it transforms sensory signals into abstract linguistic units. We then show that word entropy enhances neural tracking of both acoustic and phonemic features when sentence- and discourse-context are less constraining. When language was not comprehended, acoustic features, but not phonemic ones, were more strongly modulated, but in contrast, when a native language is comprehended, phoneme features are more strongly modulated. Taken together, our findings highlight the flexible modulation of acoustic, and phonemic features by sentence and discourse-level constraint in language comprehension, and document the neural transformation from speech perception to language comprehension, consistent with an account of language processing as a neural filter from sensory to abstract representations.

Abstract

Brain oscillations are prevalent in all species and are involved in numerous perceptual operations. α oscillations are thought to facilitate processing through the inhibition of task-irrelevant networks, while β oscillations are linked to the putative reactivation of content representations. Can the proposed functional role of α and β oscillations be generalized from low-level operations to higher-level cognitive processes? Here we address this question focusing on naturalistic spoken language comprehension. Twenty-two (18 female) Dutch native speakers listened to stories in Dutch and French while MEG was recorded. We used dependency parsing to identify three dependency states at each word: the number of (1) newly opened dependencies, (2) dependencies that remained open, and (3) resolved dependencies. We then constructed forward models to predict α and β power from the dependency features. Results showed that dependency features predict α and β power in language-related regions beyond low-level linguistic features. Left temporal, fundamental language regions are involved in language comprehension in α, while frontal and parietal, higher-order language regions, and motor regions are involved in β. Critically, α- and β-band dynamics seem to subserve language comprehension tapping into syntactic structure building and semantic composition by providing low-level mechanistic operations for inhibition and reactivation processes. Because of the temporal similarity of the α-β responses, their potential functional dissociation remains to be elucidated. Overall, this study sheds light on the role of α and β oscillations during naturalistic spoken language comprehension, providing evidence for the generalizability of these dynamics from perceptual to complex linguistic processes.

Abstract

In psycholinguistic studies using error rates as a response measure, response times (RT) are most often analyzed independently of the error rate, although it is widely recognized that they are related. In this paper we present a mixed effects logistic regression model for the error rate that uses RT as a trial-level fixed- and random-effect regression input. Production data from a translation–recall experiment are analyzed as an example. Several model comparisons reveal that RT improves the fit of the regression model for the error rate. Two simulation studies then show how the mixed effects regression model can identify individual participants for whom (a) faster responses are more accurate, (b) faster responses are less accurate, or (c) there is no relation between speed and accuracy. These results show that this type of model can serve as a useful adjunct to traditional techniques, allowing psycholinguistic researchers to examine more closely the relationship between RT and accuracy in individual subjects and better account for the variability which may be present, as well as a preliminary step to more advanced RT–accuracy modeling.

Abstract

The animacy distinction is deeply rooted in the language faculty. A key example is differential object marking, the phenomenon where animate sentential objects receive specific marking. We used event-related potentials to examine the neural processing consequences of case-marking violations on animate and inanimate direct objects in Spanish. Inanimate objects with incorrect prepositional case marker ‘a’ (‘al suelo’) elicited a P600 effect compared to unmarked objects, consistent with previous literature. However, animate objects without the required prepositional case marker (‘el obispo’) only elicited an N400 effect compared to marked objects. This novel finding, an exclusive N400 modulation by a straightforward grammatical rule violation, does not follow from extant neurocognitive models of sentence processing, and mirrors unexpected “semantic P600” effects for thematically problematic sentences. These results may reflect animacy asymmetry in competition for argument prominence: following the article, thematic interpretation difficulties are elicited only by unexpectedly animate objects.

Abstract

Two experiments examined the nature of the phonological representations used during visual word recognition. We tested whether a minimality constraint (R. Frost, 1998) limits the complexity of early representations to a simple string of phonemes. Alternatively, readers might activate elaborated representations that include prosodic syllable information before lexical access. In a modified lexical decision task (Experiment 1), words were preceded by parafoveal previews that were congruent with a target's initial syllable as well as previews that contained 1 letter more or less than the initial syllable. Lexical decision times were faster in the syllable congruent conditions than in the incongruent conditions. In Experiment 2, we recorded brain electrical potentials (electroencephalograms) during single word reading in a masked priming paradigm. The event-related potential waveform elicited in the syllable congruent condition was more positive 250-350 ms posttarget compared with the waveform elicited in the syllable incongruent condition. In combination, these experiments demonstrate that readers process prosodic syllable information early in visual word recognition in English. They offer further evidence that skilled readers routinely activate elaborated, speechlike phonological representations during silent reading. (PsycINFO Database Record (c) 2016 APA, all rights reserved)

Abstract

Interpreting a verb-phrase ellipsis (VP ellipsis) requires accessing an antecedent in memory, and then integrating a representation of this antecedent into the local context. We investigated the online interpretation of VP ellipsis in an eye-tracking experiment and four speed–accuracy tradeoff experiments. To investigate whether the antecedent for a VP ellipsis is accessed with a search or direct-access retrieval process, Experiments 1 and 2 measured the effect of the distance between an ellipsis and its antecedent on the speed and accuracy of comprehension. Accuracy was lower with longer distances, indicating that interpolated material reduced the quality of retrieved information about the antecedent. However, contra a search process, distance did not affect the speed of interpreting ellipsis. This pattern suggests that antecedent representations are content-addressable and retrieved with a direct-access process. To determine whether interpreting ellipsis involves copying antecedent information into the ellipsis site, Experiments 3–5 manipulated the length and complexity of the antecedent. Some types of antecedent complexity lowered accuracy, notably, the number of discourse entities in the antecedent. However, neither antecedent length nor complexity affected the speed of interpreting the ellipsis. This pattern is inconsistent with a copy operation, and it suggests that ellipsis interpretation may involve a pointer to extant structures in memory.