Publications

Abstract

According to the language marker hypothesis language has provided homo sapiens with a rich symbolic system that plays a central role in interpreting signals delivered by our sensory apparatus, in shaping action goals, and in creating a powerful tool for reasoning and inferencing. This view provides an important correction on embodied accounts of language that reduce language to action, perception, emotion and mental simulation. The presence of a language system has, however, also important consequences for perception, action, emotion, and memory. Language stamps signals from perception, action, and emotional systems with rich cognitive markers that transform the role of these signals in the overall cognitive architecture of the human mind. This view does not deny that language is implemented by means of universal principles of neural organization. However, language creates the possibility to generate rich internal models of the world that are shaped and made accessible by the characteristics of a language system. This makes us less dependent on direct action-perception couplings and might even sometimes go at the expense of the veridicality of perception. In cognitive (neuro)science the pendulum has swung from language as the key to understand the organization of the human mind to the perspective that it is a byproduct of perception and action. It is time that it partly swings back again.

Abstract

EEG and eye-tracking provide complementary information when investigating language comprehension. Evidence that speech processing may be facilitated by speech prediction comes from the observation that a listener's eye gaze moves towards a referent before it is mentioned if the remainder of the spoken sentence is predictable. However, changes to the trajectory of anticipatory fixations could result from a change in prediction or an attention shift. Conversely, N400 amplitudes and concurrent spectral power provide information about the ease of word processing the moment the word is perceived. In a proof-of-principle investigation, we combined EEG and eye-tracking to study linguistic prediction in naturalistic, virtual environments. We observed increased processing, reflected in theta band power, either during verb processing - when the verb was predictive of the noun - or during noun processing - when the verb was not predictive of the noun. Alpha power was higher in response to the predictive verb and unpredictable nouns. We replicated typical effects of noun congruence but not predictability on the N400 in response to the noun. Thus, the rich visual context that accompanied speech in virtual reality influenced language processing compared to previous reports, where the visual context may have facilitated processing of unpredictable nouns. Finally, anticipatory fixations were predictive of spectral power during noun processing and the length of time fixating the target could be predicted by spectral power at verb onset, conditional on the object having been fixated. Overall, we show that combining EEG and eye-tracking provides a promising new method to answer novel research questions about the prediction of upcoming linguistic input, for example, regarding the role of extralinguistic cues in prediction during language comprehension.

Abstract

During listening, brain activity tracks the rhythmic structures of speech signals. Here, we directly dissociated the contribution of neural envelope tracking in the processing of speech acoustic cues from that related to linguistic processing. We examined the neural changes associated with the comprehension of Noise-Vocoded (NV) speech using magnetoencephalography (MEG). Participants listened to NV sentences in a 3-phase training paradigm: (1) pre-training, where NV stimuli were barely comprehended, (2) training with exposure of the original clear version of speech stimulus, and (3) post-training, where the same stimuli gained intelligibility from the training phase. Using this paradigm, we tested if the neural responses of a speech signal was modulated by its intelligibility without any change in its acoustic structure. To test the influence of spectral degradation on neural envelope tracking independently of training, participants listened to two types of NV sentences (4-band and 2-band NV speech), but were only trained to understand 4-band NV speech. Significant changes in neural tracking were observed in the delta range in relation to the acoustic degradation of speech. However, we failed to find a direct effect of intelligibility on the neural tracking of speech envelope in both theta and delta ranges, in both auditory regions-of-interest and whole-brain sensor-space analyses. This suggests that acoustics greatly influence the neural tracking response to speech envelope, and that caution needs to be taken when choosing the control signals for speech-brain tracking analyses, considering that a slight change in acoustic parameters can have strong effects on the neural tracking response.

Abstract

Affective behaviors enable social robots to not only establish better connections with humans but also serve as a tool for the robots to express their internal states. It has been well established that emotions are important to signal understanding in Human-Robot Interaction (HRI). This work aims to harness the power of Large Language Models (LLM) and proposes an approach to control the affective behavior of robots. By interpreting emotion appraisal as an Emotion Recognition in Conversation (ERC) tasks, we used GPT-3.5 to predict the emotion of a robot’s turn in real-time, using the dialogue history of the ongoing conversation. The robot signaled the predicted emotion using facial expressions. The model was evaluated in a within-subjects user study (N = 47) where the model-driven emotion generation was compared against conditions where the robot did not display any emotions and where it displayed incongruent emotions. The participants interacted with the robot by playing a card sorting game that was specifically designed to evoke emotions. The results indicated that the emotions were reliably generated by the LLM and the participants were able to perceive the robot’s emotions. It was found that the robot expressing congruent model-driven facial emotion expressions were perceived to be significantly more human-like, emotionally appropriate, and elicit a more positive impression. Participants also scored significantly better in the card sorting game when the robot displayed congruent facial expressions. From a technical perspective, the study shows that LLMs can be used to control the affective behavior of robots reliably in real-time. Additionally, our results could be used in devising novel human-robot interactions, making robots more effective in roles where emotional interaction is important, such as therapy, companionship, or customer service.

Abstract

Neuron models with explicit dendritic dynamics have shed light on mechanisms for coincidence detection, pathway selection and temporal filtering. However, it is still unclear which morphological and physiological features are required to capture these phenomena. In this work, we introduce the Tripod neuron model and propose a minimal structural reduction of the dendritic tree that is able to reproduce these computations. The Tripod is a three-compartment model consisting of two segregated passive dendrites and a somatic compartment modelled as an adaptive, exponential integrate-and-fire neuron. It incorporates dendritic geometry, membrane physiology and receptor dynamics as measured in human pyramidal cells. We characterize the response of the Tripod to glutamatergic and GABAergic inputs and identify parameters that support supra-linear integration, coincidence-detection and pathway-specific gating through shunting inhibition. Following NMDA spikes, the Tripod neuron generates plateau potentials whose duration depends on the dendritic length and the strength of synaptic input. When fitted with distal compartments, the Tripod encodes previous activity into a dendritic depolarized state. This dendritic memory allows the neuron to perform temporal binding, and we show that it solves transition and sequence detection tasks on which a single-compartment model fails. Thus, the Tripod can account for dendritic computations previously explained only with more detailed neuron models or neural networks. Due to its simplicity, the Tripod neuron can be used efficiently in simulations of larger cortical circuits.

Abstract

Changes in oscillatory brain dynamics can be studied by means of induced band power (IBP) analyses, which quantify event-related changes in amplitude of frequency-specific EEG rhythms. Such analyses capture EEG phenomena that are not part of traditional event-related potential measures. The present study investigated whether IBP changes in the δ, θ, and α frequency ranges are sensitive to syntactic violations in sentences. Subjects read sentences that either were correct or contained a syntactic violation. The violations were either grammatical gender agreement violations, where a prenominal adjective was not appropriately inflected for the head noun's gender, or number agreement violations, in which a plural quantifier was combined with a singular head noun. IBP changes of the concurrently measured EEG were computed in five frequency bands of 2-Hz width, individually adjusted on the basis of subjects' α peak, ranging approximately from 2 to 12 Hz. Words constituting a syntactic violation elicited larger increases in θ power than the same words in a correct sentence context, in an interval of 300–500 ms after word onset. Of all the frequency bands studied, this was true for the θ frequency band only. The scalp topography of this effect was different for different violations: following number violations a left-hemispheric dominance was found, whereas gender violations elicited a right-hemisphere dominance of the θ power increase. Possible interpretations of this effect are considered in closing.

Abstract

By analyzing event-related changes in induced band power in narrow frequency bands of the human electroencephalograph, the present paper explores a possible functional role of the alpha and theta rhythms during the processing of words and of sentences. The results show a phasic power increase in the theta frequency range, together with a phasic power decrease in the alpha frequency range, following the presentation of words in a sentence. These effects may be related to word processing, either lexical or in relation to sentence context. Most importantly, there is a slow and highly frequency-specific increase in theta power as a sentence unfolds, possibly related to the formation of an episodic memory trace, or to incremental verbal working memory load.

Abstract

The control of language use has in its simplest form perhaps been most intensively studied using the color–word Stroop task. The authors review chronometric and neuroimaging evidence on Stroop task performance to evaluate two prominent, implemented models of control in naming and reading: GRAIN and WEAVER++. Computer simulations are reported, which reveal that WEAVER++ offers a more satisfactory account of the data than GRAIN. In particular, we report WEAVER++ simulations of the BOLD response in anterior cingulate cortex during Stroop performance. Aspects of single-word production and perception in the Stroop task are discussed in relation to the wider problem of the control of language use.

Abstract

This paper presents electrophysiological evidence of an impairment in the on-line processing of word class information in patients with Broca’s aphasia with agrammatic comprehension. Event-related brain potentials (ERPs) were recorded from the scalp while Broca patients and non-aphasic control subjects read open- and closed-class words that appeared one at a time on a PC screen. Separate waveforms were computed for open- and closed-class words. The non-aphasic control subjects showed a modulation of an early left anterior negativity in the 210–325 ms as a function of vocabulary class (VC), and a late left anterior negative shift to closed-class words in the 400–700 ms epoch. An N400 effect was present in both control subjects and Broca patients. We have taken the early electrophysiological differences to reflect the first availability of word-category information from the mental lexicon. The late differences can be related to post-lexical processing. In contrast to the control subjects, the Broca patients showed no early VC effect and no late anterior shift to closed-class words. The results support the view that an incomplete and/or delayed availability of word-class information might be an important factor in Broca’s agrammatic comprehension.