Identification of Early Hippocampal Dynamics during Recognition Memory with Independent Component Analysis.

The hippocampus is generally considered to have relatively late involvement in recognition memory, its main electrophysiological signature being between 400 and 800 ms after stimulus onset. However, most electrophysiological studies have analyzed the hippocampus as a single responsive area, selecting only a single-site signal exhibiting the strongest effect in terms of amplitude. These classical approaches may not capture all the dynamics of this structure, hindering the contribution of other hippocampal sources that are not located in the vicinity of the selected site. We combined intracerebral electroencephalogram recordings from epileptic patients with independent component analysis during a recognition memory task involving the recognition of old and new images. We identified two sources with different responses emerging from the hippocampus: a fast one (maximal amplitude at ∼250 ms) that could not be directly identified from raw recordings and a latter one, peaking at ∼400 ms. The former component presented different amplitudes between old and new items in 6 out of 10 patients. The latter component had different delays for each condition, with a faster activation (∼290 ms after stimulus onset) for recognized items. We hypothesize that both sources represent two steps of hippocampal recognition memory, the faster reflecting the input from other structures and the latter the hippocampal internal processing. Recognized images evoking early activations would facilitate neural computation in the hippocampus, accelerating memory retrieval of complementary information. Overall, our results suggest that the hippocampal activity is composed of several sources with an early activation related to recognition memory.

Towards formal models of inhibitory mechanisms involved in motor imagery: a commentary on Bach et al. (2022).

A vast body of research suggests that the primary motor cortex is involved in motor imagery. This raises the issue of inhibition: how is it possible for motor imagery not to lead to motor execution? Bach et al. (Psychol Res Psychol Forschung. 10.1007/s00426-022-01773-w, 2022, this issue) suggest that the motor execution threshold may be "upregulated" during motor imagery to prevent execution. Alternatively, it has been proposed that, in parallel to excitatory mechanisms, inhibitory mechanisms may be actively suppressing motor output during motor imagery. These theories are verbal in nature, with well-known limitations. Here, we describe a toy-model of the inhibitory mechanisms thought to be at play during motor imagery to start disentangling predictions from competing hypotheses.

Distinct neural mechanisms support inner speaking and inner hearing.

Humans have the ability to mentally examine speech. This covert form of speech production is often accompanied by sensory (e.g., auditory) percepts. However, the cognitive and neural mechanisms that generate these percepts are still debated. According to a prominent proposal, inner speech has at least two distinct phenomenological components: inner speaking and inner hearing. We used transcranial magnetic stimulation to test whether these two phenomenologically distinct processes are supported by distinct neural mechanisms. We hypothesised that inner speaking relies more strongly on an online motor-to-sensory simulation that constructs a multisensory experience, whereas inner hearing relies more strongly on a memory-retrieval process, where the multisensory experience is reconstructed from stored motor-to-sensory associations. Accordingly, we predicted that the speech motor system will be involved more strongly during inner speaking than inner hearing. This would be revealed by modulations of TMS evoked responses at muscle level following stimulation of the lip primary motor cortex. Overall, data collected from 31 participants corroborated this prediction, showing that inner speaking increases the excitability of the primary motor cortex more than inner hearing. Moreover, this effect was more pronounced during the inner production of a syllable that strongly recruits the lips (vs. a syllable that recruits the lips to a lesser extent). These results are compatible with models assuming that the primary motor cortex is involved during inner speech and contribute to clarify the neural implementation of the fundamental ability of silently speaking in one's mind.

Studying memory processes at different levels with simultaneous depth and surface EEG recordings.

Investigating cognitive brain functions using non-invasive electrophysiology can be challenging due to the particularities of the task-related EEG activity, the depth of the activated brain areas, and the extent of the networks involved. Stereoelectroencephalographic (SEEG) investigations in patients with drug-resistant epilepsy offer an extraordinary opportunity to validate information derived from non-invasive recordings at macro-scales. The SEEG approach can provide brain activity with high spatial specificity during tasks that target specific cognitive processes (e.g., memory). Full validation is possible only when performing simultaneous scalp SEEG recordings, which allows recording signals in the exact same brain state. This is the approach we have taken in 12 subjects performing a visual memory task that requires the recognition of previously viewed objects. The intracranial signals on 965 contact pairs have been compared to 391 simultaneously recorded scalp signals at a regional and whole-brain level, using multivariate pattern analysis. The results show that the task conditions are best captured by intracranial sensors, despite the limited spatial coverage of SEEG electrodes, compared to the whole-brain non-invasive recordings. Applying beamformer source reconstruction or independent component analysis does not result in an improvement of the multivariate task decoding performance using surface sensor data. By analyzing a joint scalp and SEEG dataset, we investigated whether the two types of signals carry complementary information that might improve the machine-learning classifier performance. This joint analysis revealed that the results are driven by the modality exhibiting best individual performance, namely SEEG.

When words collide: Bayesian meta-analyses of distractor and target properties in the picture-word interference paradigm.

In the picture-word interference paradigm, participants name pictures while ignoring a written or spoken distractor word. Naming times to the pictures are slowed down by the presence of the distractor word. The present study investigates in detail the impact of distractor and target word properties on picture naming times, building on the seminal study by Miozzo and Caramazza. We report the results of several Bayesian meta-analyses based on 26 datasets. These analyses provide estimates of effect sizes and their precision for several variables and their interactions. They show the reliability of the distractor frequency effect on picture naming latencies (latencies decrease as the frequency of the distractor increases) and demonstrate for the first time the impact of distractor length, with longer naming latencies for trials with longer distractors. Moreover, distractor frequency interacts with target word frequency to predict picture naming latencies. The methodological and theoretical implications of these findings are discussed.

Inter-individual variability in dorsal stream dynamics during word production.

The current standard model of language production involves a sensorimotor dorsal stream connecting areas in the temporo-parietal junction with those in the inferior frontal gyrus and lateral premotor cortex. These regions have been linked to various aspects of word production such as phonological processing or articulatory programming, primarily through neuropsychological and functional imaging group studies. Most if not all the theoretical descriptions of this model imply that the same network should be identifiable across individual speakers. We tested this hypothesis by quantifying the variability of activation observed across individuals within each dorsal stream anatomical region. This estimate was based on electrical activity recorded directly from the cerebral cortex with millisecond accuracy in awake epileptic patients clinically implanted with intracerebral depth electrodes for pre-surgical diagnosis. Each region's activity was quantified using two different metrics-intra-cerebral evoked related potentials and high gamma activity-at the level of the group, the individual and the recording contact. The two metrics show simultaneous activation of parietal and frontal regions during a picture naming task, in line with models that posit interactive processing during word retrieval. They also reveal different levels of between-patient variability across brain regions, except in core auditory and motor regions. The independence and non-uniformity of cortical activity estimated through the two metrics push the current model towards sub-second and sub-region explorations focused on individualized language speech production. Several hypotheses are considered for this within-region heterogeneity.

Typing expertise in a large student population.

Typing has become a pervasive mode of language production worldwide, with keyboards fully integrated in a large part of many daily activities. The bulk of the literature on typing expertise concerns highly trained professional touch-typists, but contemporary typing skills mostly result from unconstrained sustained practice. We measured the typing performance of a large cohort of 1301 university students through an online platform and followed a preregistered plan to analyse performance distributions, practice factors, and cognitive variables. The results suggest that the standard model with a sharp distinction between novice and expert typists may be inaccurate to account for the performance of the current generation of young typists. More generally, this study shows how the mere frequent use of a new tool can lead to the incidental development of high expertise.

Magnetoencephalography can reveal deep brain network activities linked to memory processes.

Recording from deep neural structures such as hippocampus noninvasively and yet with high temporal resolution remains a major challenge for human neuroscience. Although it has been proposed that deep neuronal activity might be recordable during cognitive tasks using magnetoencephalography (MEG), this remains to be demonstrated as the contribution of deep structures to MEG recordings may be too small to be detected or might be eclipsed by the activity of large-scale neocortical networks. In the present study, we disentangled mesial activity and large-scale networks from the MEG signals thanks to blind source separation (BSS). We then validated the MEG BSS components using intracerebral EEG signals recorded simultaneously in patients during their presurgical evaluation of epilepsy. In the MEG signals obtained during a memory task involving the recognition of old and new images, we identified with BSS a putative mesial component, which was present in all patients and all control subjects. The time course of the component selectively correlated with stereo-electroencephalography signals recorded from hippocampus and rhinal cortex, thus confirming its mesial origin. This finding complements previous studies with epileptic activity and opens new possibilities for using MEG to study deep brain structures in cognition and in brain disorders.

An open-source toolbox for Multi-patient Intracranial EEG Analysis (MIA).

Intracranial EEG (iEEG) performed during the pre-surgical evaluation of refractory epilepsy provides a great opportunity to investigate the neurophysiology of human cognitive functions with exceptional spatial and temporal precisions. A difficulty of the iEEG approach for cognitive neuroscience, however, is the potential variability across patients in the anatomical location of implantations and in the functional responses therein recorded. In this context, we designed, implemented, and tested a user-friendly and efficient open-source toolbox for Multi-Patient Intracranial data Analysis (MIA), which can be used as standalone program or as a Brainstorm plugin. MIA helps analyzing event related iEEG signals while following good scientific practice recommendations, such as building reproducible analysis pipelines and applying robust statistics. The signals can be analyzed in the temporal and time-frequency domains, and the similarity of time courses across patients or contacts can be assessed within anatomical regions. MIA allows visualizing all these results in a variety of formats at every step of the analysis. Here, we present the toolbox architecture and illustrate the different steps and features of the analysis pipeline using a group dataset collected during a language task.

The Role of Motor Inhibition During Covert Speech Production.

Covert speech is accompanied by a subjective multisensory experience with auditory and kinaesthetic components. An influential hypothesis states that these sensory percepts result from a simulation of the corresponding motor action that relies on the same internal models recruited for the control of overt speech. This simulationist view raises the question of how it is possible to imagine speech without executing it. In this perspective, we discuss the possible role(s) played by motor inhibition during covert speech production. We suggest that considering covert speech as an inhibited form of overt speech maps naturally to the purported progressive internalization of overt speech during childhood. We further argue that the role of motor inhibition may differ widely across different forms of covert speech (e.g., condensed vs. expanded covert speech) and that considering this variety helps reconciling seemingly contradictory findings from the neuroimaging literature.

Avoiding gender ambiguous pronouns in French.

Across many languages, pronouns are the most frequently produced referring expressions. We examined whether and how speakers avoid referential ambiguity that arises when the gender of a pronoun is compatible with more than one entity in the context in French. Experiment 1 showed that speakers use fewer pronouns when human referents have the same gender than when they had different genders, but grammatical gender congruence between inanimate referents did not result in fewer pronouns. Experiment 2 showed that semantic similarity between non-human referents can enhance the likelihood that speakers avoid grammatical-gender ambiguous pronouns. Experiment 3 pitched grammatical gender ambiguity avoidance against the referents' competition in the non-linguistic context, showing that when speakers can base their pronoun choice on non-linguistic competition, they ignore the pronoun's grammatical gender ambiguity even when the referents are semantically related. The results thus indicated that speakers preferentially produce referring expressions based on non-linguistic information; they are more likely to be affected by the referents' non-linguistic similarity than by the linguistic ambiguity of a pronoun.

Functional Topography of Auditory Areas Derived From the Combination of Electrophysiological Recordings and Cortical Electrical Stimulation.

The posterior part of the superior temporal gyrus (STG) has long been known to be a crucial hub for auditory and language processing, at the crossroad of the functionally defined ventral and dorsal pathways. Anatomical studies have shown that this "auditory cortex" is composed of several cytoarchitectonic areas whose limits do not consistently match macro-anatomic landmarks like gyral and sulcal borders. The only method to record and accurately distinguish neuronal activity from the different auditory sub-fields of primary auditory cortex, located in the tip of Heschl and deeply buried in the Sylvian fissure, is to use stereotaxically implanted depth electrodes (Stereo-EEG) for pre-surgical evaluation of patients with epilepsy. In this prospective, we focused on how anatomo-functional delineation in Heschl's gyrus (HG), Planum Temporale (PT), the posterior part of the STG anterior to HG, the posterior superior temporal sulcus (STS), and the region at the parietal-temporal boundary commonly labeled "SPT" can be achieved using data from electrical cortical stimulation combined with electrophysiological recordings during listening to pure tones and syllables. We show the differences in functional roles between the primary and non-primary auditory areas, in the left and the right hemispheres. We discuss how these findings help understanding the auditory semiology of certain epileptic seizures and, more generally, the neural substrate of hemispheric specialization for language.

Cerebellar and Cortical Correlates of Internal and External Speech Error Monitoring.

An event-related functional magnetic resonance imaging study examined how speakers inspect their own speech for errors. Concretely, we sought to assess 1) the role of the temporal cortex in monitoring speech errors, linked with comprehension-based monitoring; 2) the involvement of the cerebellum in internal and external monitoring, linked with forward modeling; and 3) the role of the medial frontal cortex for internal monitoring, linked with conflict-based monitoring. In a word production task priming speech errors, we observed enhanced involvement of the right posterior cerebellum for trials that were correct, but on which participants were more likely to make a word as compared with a nonword error (contrast of internal monitoring). Furthermore, comparing errors to correct utterances (contrast of external monitoring), we observed increased activation of the same cerebellar region, of the superior medial cerebellum, and of regions in temporal and medial frontal cortex. The presence of the cerebellum for both internal and external monitoring indicates the use of forward modeling across the planning and articulation of speech. Dissociations across internal and external monitoring in temporal and medial frontal cortex indicate that monitoring of overt errors is more reliant on vocal feedback control.

Assessing model-based inferences in decision making with single-trial response time decomposition.

The latent psychological mechanisms involved in decision-making are often studied with quantitative models based on evidence accumulation processes. The most prolific example is arguably the drift-diffusion model (DDM). This framework has frequently shown good to very good quantitative fits, which has prompted its wide endorsement. However, fit quality alone does not establish the validity of a model's interpretation. Here, we formally assess the model's validity with a novel cross-validation approach based on the recording of muscular activities, which directly relate to the standard interpretation of various model parameters. Specifically, we recorded electromyographic activity along with response times (RTs), and used it to decompose every RT into 2 components: a premotor time (PMT) and motor time (MT). The latter interval, MT, can be directly linked to motor processes and hence to the nondecision parameter of DDM. In two canonical perceptual decision tasks, we manipulated stimulus strength, speed-accuracy trade-off, and response force and quantified their effects on PMT, MT, and RT. All 3 factors consistently affected MT. The DDM parameter for nondecision processes recovered the MT effects in most situations, with the exception of the fastest responses. The extent of the good fits and the scope of the mis-estimations that we observed allow drawing new limits of the interpretability of model parameters. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Contributions of electrophysiology for identifying cortical language systems in patients with epilepsy.

A crucial element of the surgical treatment of medically refractory epilepsy is to delineate cortical areas that must be spared in order to avoid clinically relevant neurological and neuropsychological deficits postoperatively. For each patient, this typically necessitates determining the language lateralization between hemispheres and language localization within hemisphere. Understanding cortical language systems is complicated by two primary challenges: the extent of the neural tissue involved and the substantial variability across individuals, especially in pathological populations. We review the contributions made through the study of electrophysiological activity to address these challenges. These contributions are based on the techniques of magnetoencephalography (MEG), intracerebral recordings, electrical-cortical stimulation (ECS), and the electrovideo analyses of seizures and their semiology. We highlight why no single modality alone is adequate to identify cortical language systems and suggest avenues for improving current practice.

On the Boundaries between Decision and Action: Effector-selective Lateralization of Beta-frequency Power Is Modulated by the Lexical Frequency of Printed Words.

Current computational and neuroscientific models of decision-making posit a discrete, serial processing distinction between upstream decisional stages and downstream processes of motor-response implementation. We investigated this framework in the context of two-alternative forced-choice tasks on linguistic stimuli, words and pseudowords. In two experiments, we assessed the impact of lexical frequency and action semantics on two effector-selective EEG indexes of motor-response activation: the lateralized readiness potential and the lateralization of beta-frequency power. This allowed us to track potentially continuous streams of processing progressively mapping the evaluation of linguistic stimuli onto corresponding response channels. Whereas action semantics showed no influence on EEG indexes of motor-response activation, lexical frequency affected the lateralization of response-locked beta-frequency power. We argue that these observations point toward a continuity between linguistic processing of word input stimuli and implementation of corresponding choice in terms of motor behavior. This interpretation challenges the commonly held assumption of a discrete processing distinction between decisional and motor-response processes in the context of decisions based on symbolic stimuli.

A description of verbal and gestural communication during postictal aphasia.

Patients suffering from drug-resistant temporal lobe epilepsy show substantial language deficits (i.e., anomia) during their seizures and in the postictal period (postictal aphasia). Verbal impairments observed during the postictal period may be studied to help localizing the epileptogenic zone. These explorations have been essentially based on simple tasks focused on speech, thus disregarding the multimodal nature of verbal communication, particularly the fact that, when speakers want to communicate, they often produce gestures of various kinds. Here, we propose an innovative procedure for testing postictal language and communication abilities, including the assessment of co-speech gestures. We provide a preliminary description of the changes induced on communication during postictal aphasia. We studied 21 seizures that induced postictal aphasia from 12 patients with drug-refractory epilepsy, including left temporal and left frontal seizures. The experimental task required patients to memorize a highly detailed picture and, briefly after, to describe what they had seen, thus eliciting a communicative meaningful monologue. This allowed comparing verbal communication in postictal and interictal conditions within the same individuals. Co-speech gestures were coded according to two categories: "Rhythmic" gestures, thought to be produced in support of speech building, and "illustrative" gestures, thought to be produced to complement the speech content. When postictal and interictal conditions were compared, there was decreased speech flow along with an increase of rhythmic gesture production at the expense of illustrative gesture production. The communication patterns did not differ significantly after temporal and frontal seizures, yet they were illustrated separately, owing to the clinical importance of the distinction, along with considerations of interindividual variability. A contrast between rhythmic and illustrative gestures production is congruent with previous literature in which rhythmic gestures have been linked to lexical retrieval processes. If confirmed in further studies, such evidence for a facilitative role of co-speech gestures in language difficulties could be put to use in the context of multimodal language therapies.

Multi-factor analysis in language production: Sequential sampling models mimic and extend regression results.

For multi-factor analyses of response times, descriptive models (e.g., linear regression) arguably constitute the dominant approach in psycholinguistics. In contrast empirical cognitive models (e.g., sequential sampling models, SSMs) may fit fewer factors simultaneously, but decompose the data into several dependent variables (a multivariate result), offering more information to analyze. While SSMs are notably popular in the behavioural sciences, they are not significantly developed in language production research. To contribute to the development of this modelling in language, we (i) examine SSMs as a measurement modelling approach for spoken word activation dynamics, and (ii) formally compare SSMs to the default method, regression. SSMs model response activation or selection mechanisms in time, and calculate how they are affected by conditions, persons, and items. While regression procedures also model condition effects, it is only in respect to the mean RT, and little work has been previously done to compare these approaches. Through analyses of two language production experiments, we show that SSMs reproduce regression predictors, and further extend these effects through a multivariate decomposition (cognitive parameters). We also examine a combined regression-SSM approach that is hierarchical Bayesian, which can jointly model more conditions than classic SSMs, and importantly, achieve by-item modelling with other conditions. In this analysis, we found that spoken words principally differed from one another by their activation rates and production times, but not their thresholds to be activated.

Cortical Dynamics of Semantic Priming and Interference during Word Production: An Intracerebral Study.

Language production requires that semantic representations are mapped to lexical representations on the basis of the ongoing context to select the appropriate words. This mapping is thought to generate two opposing phenomena, "semantic priming," where multiple word candidates are activated, and "interference," where these word activities are differentiated to make a goal-relevant selection. In previous neuroimaging and neurophysiological research, priming and interference have been associated to activity in regions of a left frontotemporal network. Most of such studies relied on recordings that either have high temporal or high spatial resolution, but not both. Here, we employed intracerebral EEG techniques to explore with both high resolutions, the neural activity associated with these phenomena. The data came from nine epileptic patients who were stereotactically implanted for presurgical diagnostics. They performed a cyclic picture-naming task contrasting semantically homogeneous and heterogeneous contexts. Of the 84 brain regions sampled, 39 showed task-evoked activity that was significant and consistent across two patients or more. In nine of these regions, activity was significantly modulated by the semantic manipulation. It was reduced for semantically homogeneous contexts (i.e., priming) in eight of these regions, located in the temporal ventral pathway as well as frontal areas. Conversely, it was increased only in the pre-SMA, notably at an early poststimulus temporal window (200-300 msec) and a preresponse temporal window (700-800 msec). These temporal effects respectively suggest the pre-SMA's role in initial conflict detection (e.g., increased response caution) and in preresponse control. Such roles of the pre-SMA are traditional from a history of neural evidence in simple perceptual tasks, yet are also consistent with recent cognitive lexicosemantic theories that highlight top-down processes in language production. Finally, although no significant semantic modulation was found in the ACC, future intracerebral EEG work should continue to inspect ACC with the pre-SMA.