Understanding language-elicited EEG data by predicting it from a fine-tuned language model

Electroencephalography (EEG) recordings of brain activity taken while participants read or listen to language are widely used within the cognitive neuroscience and psycholinguistics communities as a tool to study language comprehension. Several time-locked stereotyped EEG responses to word-presentations -- known collectively as event-related potentials (ERPs) -- are thought to be markers for semantic or syntactic processes that take place during comprehension. However, the characterization of each individual ERP in terms of what features of a stream of language trigger the response remains controversial. Improving this characterization would make ERPs a more useful tool for studying language comprehension. We take a step towards better understanding the ERPs by fine-tuning a language model to predict them. This new approach to analysis shows for the first time that all of the ERPs are predictable from embeddings of a stream of language. Prior work has only found two of the ERPs to be predictable. In addition to this analysis, we examine which ERPs benefit from sharing parameters during joint training. We find that two pairs of ERPs previously identified in the literature as being related to each other benefit from joint training, while several other pairs of ERPs that benefit from joint training are suggestive of potential relationships. Extensions of this analysis that further examine what kinds of information in the model embeddings relate to each ERP have the potential to elucidate the processes involved in human language comprehension.Comment: To appear in Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistic

Nonlinear denoising of transient signals with application to event related potentials

We present a new wavelet based method for the denoising of {\it event related potentials} ERPs), employing techniques recently developed for the paradigm of deterministic chaotic systems. The denoising scheme has been constructed to be appropriate for short and transient time sequences using circular state space embedding. Its effectiveness was successfully tested on simulated signals as well as on ERPs recorded from within a human brain. The method enables the study of individual ERPs against strong ongoing brain electrical activity.Comment: 16 pages, Postscript, 6 figures, Physica D in pres

Characterization of spatio-temporal epidural event-related potentials for mouse models of psychiatric disorders.

Distinctive features in sensory event-related potentials (ERPs) are endophenotypic biomarkers of psychiatric disorders, widely studied using electroencephalographic (EEG) methods in humans and model animals. Despite the popularity and unique significance of the mouse as a model species in basic research, existing EEG methods applicable to mice are far less powerful than those available for humans and large animals. We developed a new method for multi-channel epidural ERP characterization in behaving mice with high precision, reliability and convenience and report an application to time-domain ERP feature characterization of the Sp4 hypomorphic mouse model for schizophrenia. Compared to previous methods, our spatio-temporal ERP measurement robustly improved the resolving power of key signatures characteristic of the disease model. The high performance and low cost of this technique makes it suitable for high-throughput behavioral and pharmacological studies

The development and neural basis of referential gaze perception

Infants are sensitive to the referential information conveyed by others’ eye gaze, which could be one of the developmental foundations of theory of mind. To investigate the neural correlates of gaze–object relations, we recorded ERPs from adults and 9-month-old infants while they watched scenes containing gaze shifts either towards or away from the location of a preceding object. In adults, object-incongruent gaze shifts elicited enhanced ERP amplitudes over the occipito-temporal area (N330). In infants, a similar posterior ERP component (N290) was greater for object-incongruent gaze shifts, which suggests that by the age of 9 months infants encode referential information of gaze in a similar way to adults. In addition, in infants we observed an early frontal ERP component (anterior N200), which showed higher amplitude in response to the perception of object-congruent gaze shifts. This component may reflect fast-track processing of socially relevant information, such as the detection of communicative or informative situations, and could form a developmental foundation for attention sharing, social learning and theory of mind

The pain matrix reloaded: a salience detection system for the body

Neuroimaging and neurophysiological studies have shown that nociceptive stimuli elia salience detection system for the bodycit responses in an extensive cortical network including somatosensory, insular and cingulate areas, as well as frontal and parietal areas. This network, often referred to as the "pain matrix", is viewed as representing the activity by which the intensity and unpleasantness of the perception elicited by a nociceptive stimulus are represented. However, recent experiments have reported (i) that pain intensity can be dissociated from the magnitude of responses in the "pain matrix", (ii) that the responses in the "pain matrix" are strongly influenced by the context within which the nociceptive stimuli appear, and (iii) that non-nociceptive stimuli can elicit cortical responses with a spatial configuration similar to that of the "pain matrix". For these reasons, we propose an alternative view of the functional significance of this cortical network, in which it reflects a system involved in detecting, orienting attention towards, and reacting to the occurrence of salient sensory events. This cortical network might represent a basic mechanism through which significant events for the body's integrity are detected, regardless of the sensory channel through which these events are conveyed. This function would involve the construction of a multimodal cortical representation of the body and nearby space. Under the assumption that this network acts as a defensive system signaling potentially damaging threats for the body, emphasis is no longer on the quality of the sensation elicited by noxious stimuli but on the action prompted by the occurrence of potential threats

A new method to detect event-related potentials based on Pearson\u2019s correlation

Event-related potentials (ERPs) are widely used in brain-computer interface applications and in neuroscience. Normal EEG activity is rich in background noise, and therefore, in order to detect ERPs, it is usually necessary to take the average from multiple trials to reduce the effects of this noise. The noise produced by EEG activity itself is not correlated with the ERP waveform and so, by calculating the average, the noise is decreased by a factor inversely proportional to the square root of N, where N is the number of averaged epochs. This is the easiest strategy currently used to detect ERPs, which is based on calculating the average of all ERP\u2019s waveform, these waveforms being time- and phase-locked. In this paper, a new method called GW6 is proposed, which calculates the ERP using a mathematical method based only on Pearson\u2019s correlation. The result is a graph with the same time resolution as the classical ERP and which shows only positive peaks representing the increase\u2014in consonance with the stimuli\u2014in EEG signal correlation over all channels. This new method is also useful for selectively identifying and highlighting some hidden components of the ERP response that are not phase-locked, and that are usually hidden in the standard and simple method based on the averaging of all the epochs. These hidden components seem to be caused by variations (between each successive stimulus) of the ERP\u2019s inherent phase latency period (jitter), although the same stimulus across all EEG channels produces a reasonably constant phase. For this reason, this new method could be very helpful to investigate these hidden components of the ERP response and to develop applications for scientific and medical purposes. Moreover, this new method is more resistant to EEG artifacts than the standard calculations of the average and could be very useful in research and neurology. The method we are proposing can be directly used in the form of a process written in the well-known Matlab programming language and can be easily and quickly written in any other software language

The feedback correct-related positivity : sensitivity of the event-related brain potential to unexpected positive feedback

The N200 and the feedback error-related negativity (fERN) are two components of the event-related brain potential (ERP) that share similar scalp distributions, time courses, morphologies, and functional dependencies, which raises the question as to whether they are actually the same phenomenon. To investigate this issue, we recorded the ERP from participants engaged in two tasks that independently elicited the N200 and fERN. Our results indicate that they are, in fact, the same ERP component and further suggest that positive feedback elicits a positive-going deflection in the time range of the fERN. Taken together, these results indicate that negative feedback elicits a common N200 and that modulation of fERN amplitude results from the superposition on correct trials of a positive-going deflection that we term the feedback correct-related positivity

Name agreement in picture naming: An ERP study

Name agreement is the extent to which different people agree on a name for a particular picture. Previous studies have found that it takes longer to name low name agreement pictures than high name agreement pictures. To examine the effect of name agreement in the online process of picture naming, we compared event-related potentials (ERPs) recorded whilst 19 healthy, native English speakers silently named pictures which had either high or low name agreement. A series of ERP components was examined: P1 approximately 120ms from picture onset, N1 around 170ms, P2 around 220ms, N2 around 290ms, and P3 around 400ms. Additionally, a late time window from 800 to 900ms was considered. Name agreement had an early effect, starting at P1 and possibly resulting from uncertainty of picture identity, and continuing into N2, possibly resulting from alternative names for pictures. These results support the idea that name agreement affects two consecutive processes: first, object recognition, and second, lexical selection and/or phonological encoding