Neurobiological Causal Models of Language Processing.

The language faculty is physically realized in the neurobiological infrastructure of the human brain. Despite significant efforts, an integrated understanding of this system remains a formidable challenge. What is missing from most theoretical accounts is a specification of the neural mechanisms that implement language function. Computational models that have been put forward generally lack an explicit neurobiological foundation. We propose a neurobiologically informed causal modeling approach which offers a framework for how to bridge this gap. A neurobiological causal model is a mechanistic description of language processing that is grounded in, and constrained by, the characteristics of the neurobiological substrate. It intends to model the generators of language behavior at the level of implementational causality. We describe key features and neurobiological component parts from which causal models can be built and provide guidelines on how to implement them in model simulations. Then we outline how this approach can shed new light on the core computational machinery for language, the long-term storage of words in the mental lexicon and combinatorial processing in sentence comprehension. In contrast to cognitive theories of behavior, causal models are formulated in the "machine language" of neurobiology which is universal to human cognition. We argue that neurobiological causal modeling should be pursued in addition to existing approaches. Eventually, this approach will allow us to develop an explicit computational neurobiology of language.

Cerebral Blood Flow Assessed with Phase-contrast Magnetic Resonance Imaging during Blood Pressure Changes with Noradrenaline and Labetalol: A Trial in Healthy Volunteers.

BACKGROUND: Adequate cerebral perfusion is central during general anesthesia. However, perfusion is not readily measured bedside. Clinicians currently rely mainly on mean arterial pressure (MAP) as a surrogate, even though the relationship between blood pressure and cerebral blood flow is not well understood. The aim of this study was to apply phase-contrast magnetic resonance imaging to characterize blood flow responses in healthy volunteers to commonly used pharmacologic agents that increase or decrease arterial blood pressure. METHODS: Eighteen healthy volunteers aged 30 to 50 yr were investigated with phase-contrast magnetic resonance imaging. Intra-arterial blood pressure monitoring was used. First, intravenous noradrenaline was administered to a target MAP of 20% above baseline. After a wash-out period, intravenous labetalol was given to a target MAP of 15% below baseline. Cerebral blood flow was measured using phase-contrast magnetic resonance imaging and defined as the sum of flow in the internal carotid arteries and vertebral arteries. Cardiac output (CO) was defined as the flow in the ascending aorta. RESULTS: Baseline median cerebral blood flow was 772 ml/min (interquartile range, 674 to 871), and CO was 5,874 ml/min (5,199 to 6,355). The median dose of noradrenaline was 0.17 µg · kg-1 · h-1 (0.14 to 0.22). During noradrenaline infusion, cerebral blood flow decreased to 705 ml/min (606 to 748; P = 0.001), and CO decreased to 4,995 ml/min (4,705 to 5,635; P = 0.01). A median dose of labetalol was 120 mg (118 to 150). After labetalol boluses, cerebral blood flow was unchanged at 769 ml/min (734 to 900; P = 0.68). CO increased to 6,413 ml/min (6,056 to 7,464; P = 0.03). CONCLUSIONS: In healthy, awake subjects, increasing MAP using intravenous noradrenaline decreased cerebral blood flow and CO. These data do not support inducing hypertension with noradrenaline to increase cerebral blood flow. Cerebral blood flow was unchanged when decreasing MAP using labetalol.

Formal language hierarchy reflects different levels of cognitive complexity.

Formal language hierarchy describes levels of increasing syntactic complexity (adjacent dependencies, nonadjacent nested, nonadjacent crossed) of which the transcription into a hierarchy of cognitive complexity remains under debate. The cognitive foundations of formal language hierarchy have been contradicted by two types of evidence: First, adjacent dependencies are not easier to learn compared to nonadjacent; second, crossed nonadjacent dependencies may be easier than nested. However, studies providing these findings may have engaged confounds: Repetition monitoring strategies may have accounted for participants' high performance in nonadjacent dependencies, and linguistic experience may have accounted for the advantage of crossed dependencies. We conducted two artificial grammar learning experiments where we addressed these confounds by manipulating reliance on repetition monitoring and by testing participants inexperienced with crossed dependencies. Results showed relevant differences in learning adjacent versus nonadjacent dependencies and advantages of nested over crossed, suggesting that formal language hierarchy may indeed translate into a hierarchy of cognitive complexity. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The Tripod neuron: a minimal structural reduction of the dendritic tree.

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. KEY POINTS: We present a neuron model, called the Tripod, with two segregated dendritic branches that are connected to an axosomatic compartment. Each branch implements inhibitory GABAergic and excitatory glutamatergic synaptic transmission, including voltage-gated NMDA receptors. Dendrites are modelled on relevant geometric and physiological parameters measured in human pyramidal cells. The neuron reproduces classical dendritic computations, such as coincidence detection and pathway selection via shunting inhibition, that are beyond the scope of point-neuron models. Under some conditions, dendritic NMDA spikes cause plateau potentials, and we show that they provide a form of short-term memory which is useful for sequence recognition. The dendritic structure of the Tripod neuron is sufficiently simple to be integrated into efficient network simulations and studied in a broad functional context.

Selective-Area Epitaxy of InGaAsP Buffer Multilayer for In-Plane InAs Nanowire Integration.

In order to use III-V compound semiconductors as active channel materials in advanced electronic and quantum devices, it is important to achieve a good epitaxial growth on silicon substrates. As a first step toward this, we report on the selective-area growth of GaP/InGaP/InP/InAsP buffer layer nanotemplates on GaP substrates which are closely lattice-matched to silicon, suitable for the integration of in-plane InAs nanowires. Scanning electron microscopy reveals a perfect surface selectivity and uniform layer growth inside 150 and 200 nm large SiO2 mask openings. Compositional and structural characterization of the optimized structure performed by transmission electron microscopy shows the evolution of the major facet planes and allows a strain distribution analysis. Chemically uniform layers with well-defined heterointerfaces are obtained, and the topmost InAs layer is free from any dislocation. Our study demonstrates that a growth sequence of thin layers with progressively increasing lattice parameters is effective to efficiently relax the strain and eventually obtain high quality in-plane InAs nanowires on large lattice-mismatched substrates.

Integration of Topological Insulator Josephson Junctions in Superconducting Qubit Circuits.

The integration of semiconductor Josephson junctions (JJs) in superconducting quantum circuits provides a versatile platform for hybrid qubits and offers a powerful way to probe exotic quasiparticle excitations. Recent proposals for using circuit quantum electrodynamics (cQED) to detect topological superconductivity motivate the integration of novel topological materials in such circuits. Here, we report on the realization of superconducting transmon qubits implemented with (Bi0.06Sb0.94)2Te3 topological insulator (TI) JJs using ultrahigh vacuum fabrication techniques. Microwave losses on our substrates, which host monolithically integrated hardmasks used for the selective area growth of TI nanostructures, imply microsecond limits to relaxation times and, thus, their compatibility with strong-coupling cQED. We use the cavity-qubit interaction to show that the Josephson energy of TI-based transmons scales with their JJ dimensions and demonstrate qubit control as well as temporal quantum coherence. Our results pave the way for advanced investigations of topological materials in both novel Josephson and topological qubits.

Supramodal Sentence Processing in the Human Brain: fMRI Evidence for the Influence of Syntactic Complexity in More Than 200 Participants.

This study investigated two questions. One is: To what degree is sentence processing beyond single words independent of the input modality (speech vs. reading)? The second question is: Which parts of the network recruited by both modalities is sensitive to syntactic complexity? These questions were investigated by having more than 200 participants read or listen to well-formed sentences or series of unconnected words. A largely left-hemisphere frontotemporoparietal network was found to be supramodal in nature, i.e., independent of input modality. In addition, the left inferior frontal gyrus (LIFG) and the left posterior middle temporal gyrus (LpMTG) were most clearly associated with left-branching complexity. The left anterior temporal lobe showed the greatest sensitivity to sentences that differed in right-branching complexity. Moreover, activity in LIFG and LpMTG increased from sentence onset to end, in parallel with an increase of the left-branching complexity. While LIFG, bilateral anterior temporal lobe, posterior MTG, and left inferior parietal lobe all contribute to the supramodal unification processes, the results suggest that these regions differ in their respective contributions to syntactic complexity related processing. The consequences of these findings for neurobiological models of language processing are discussed.

Distinguishing Syntactic Operations in the Brain: Dependency and Phrase-Structure Parsing.

Finding the structure of a sentence-the way its words hold together to convey meaning-is a fundamental step in language comprehension. Several brain regions, including the left inferior frontal gyrus, the left posterior superior temporal gyrus, and the left anterior temporal pole, are supposed to support this operation. The exact role of these areas is nonetheless still debated. In this paper we investigate the hypothesis that different brain regions could be sensitive to different kinds of syntactic computations. We compare the fit of phrase-structure and dependency structure descriptors to activity in brain areas using fMRI. Our results show a division between areas with regard to the type of structure computed, with the left anterior temporal pole and left inferior frontal gyrus favouring dependency structures and left posterior superior temporal gyrus favouring phrase structures.

Destructive Little-Parks Effect in a Full-Shell Nanowire-Based Transmon.

A semiconductor transmon with an epitaxial Al shell fully surrounding an InAs nanowire core is investigated in the low E_{J}/E_{C} regime. Little-Parks oscillations as a function of flux along the hybrid wire axis are destructive, creating lobes of reentrant superconductivity separated by a metallic state at a half quantum of applied flux. In the first lobe, phase winding around the shell can induce topological superconductivity in the core. Coherent qubit operation is observed in both the zeroth and first lobes. Splitting of parity bands by coherent single-electron coupling across the junction is not resolved beyond line broadening, placing a bound on Majorana coupling, E_{M}/h<10 MHz, much smaller than the Josephson coupling E_{J}/h∼4.7 GHz.

Neuronal spike-rate adaptation supports working memory in language processing.

Language processing involves the ability to store and integrate pieces of information in working memory over short periods of time. According to the dominant view, information is maintained through sustained, elevated neural activity. Other work has argued that short-term synaptic facilitation can serve as a substrate of memory. Here we propose an account where memory is supported by intrinsic plasticity that downregulates neuronal firing rates. Single neuron responses are dependent on experience, and we show through simulations that these adaptive changes in excitability provide memory on timescales ranging from milliseconds to seconds. On this account, spiking activity writes information into coupled dynamic variables that control adaptation and move at slower timescales than the membrane potential. From these variables, information is continuously read back into the active membrane state for processing. This neuronal memory mechanism does not rely on persistent activity, excitatory feedback, or synaptic plasticity for storage. Instead, information is maintained in adaptive conductances that reduce firing rates and can be accessed directly without cued retrieval. Memory span is systematically related to both the time constant of adaptation and baseline levels of neuronal excitability. Interference effects within memory arise when adaptation is long lasting. We demonstrate that this mechanism is sensitive to context and serial order which makes it suitable for temporal integration in sequence processing within the language domain. We also show that it enables the binding of linguistic features over time within dynamic memory registers. This work provides a step toward a computational neurobiology of language.

Superconducting gatemon qubit based on a proximitized two-dimensional electron gas.

The coherent tunnelling of Cooper pairs across Josephson junctions (JJs) generates a nonlinear inductance that is used extensively in quantum information processors based on superconducting circuits, from setting qubit transition frequencies1 and interqubit coupling strengths2 to the gain of parametric amplifiers3 for quantum-limited readout. The inductance is either set by tailoring the metal oxide dimensions of single JJs, or magnetically tuned by parallelizing multiple JJs in superconducting quantum interference devices with local current-biased flux lines. JJs based on superconductor-semiconductor hybrids represent a tantalizing all-electric alternative. The gatemon is a recently developed transmon variant that employs locally gated nanowire superconductor-semiconductor JJs for qubit control4,5. Here we go beyond proof-of-concept and demonstrate that semiconducting channels etched from a wafer-scale two-dimensional electron gas (2DEG) are a suitable platform for building a scalable gatemon-based quantum computer. We show that 2DEG gatemons meet the requirements6 by performing voltage-controlled single qubit rotations and two-qubit swap operations. We measure qubit coherence times up to ~2 µs, limited by dielectric loss in the 2DEG substrate.

Implicit sequence learning is preserved in dyslexic children.

This study investigates the implicit sequence learning abilities of dyslexic children using an artificial grammar learning task with an extended exposure period. Twenty children with developmental dyslexia participated in the study and were matched with two control groups-one matched for age and other for reading skills. During 3 days, all participants performed an acquisition task, where they were exposed to colored geometrical forms sequences with an underlying grammatical structure. On the last day, after the acquisition task, participants were tested in a grammaticality classification task. Implicit sequence learning was present in dyslexic children, as well as in both control groups, and no differences between groups were observed. These results suggest that implicit learning deficits per se cannot explain the characteristic reading difficulties of the dyslexics.

Modality effects in implicit artificial grammar learning: An EEG study.

Recently, it has been proposed that sequence learning engages a combination of modality-specific operating networks and modality-independent computational principles. In the present study, we compared the behavioural and EEG outcomes of implicit artificial grammar learning in the visual vs. auditory modality. We controlled for the influence of surface characteristics of sequences (Associative Chunk Strength), thus focusing on the strictly structural aspects of sequence learning, and we adapted the paradigms to compensate for known frailties of the visual modality compared to audition (temporal presentation, fast presentation rate). The behavioural outcomes were similar across modalities. Favouring the idea of modality-specificity, ERPs in response to grammar violations differed in topography and latency (earlier and more anterior component in the visual modality), and ERPs in response to surface features emerged only in the auditory modality. In favour of modality-independence, we observed three common functional properties in the late ERPs of the two grammars: both were free of interactions between structural and surface influences, both were more extended in a grammaticality classification test than in a preference classification test, and both correlated positively and strongly with theta event-related-synchronization during baseline testing. Our findings support the idea of modality-specificity combined with modality-independence, and suggest that memory for visual vs. auditory sequences may largely contribute to cross-modal differences.

Broca's region: A causal role in implicit processing of grammars with crossed non-adjacent dependencies.

Non-adjacent dependencies are challenging for the language learning machinery and are acquired later than adjacent dependencies. In this transcranial magnetic stimulation (TMS) study, we show that participants successfully discriminated between grammatical and non-grammatical sequences after having implicitly acquired an artificial language with crossed non-adjacent dependencies. Subsequent to transcranial magnetic stimulation of Broca's region, discrimination was impaired compared to when a language-irrelevant control region (vertex) was stimulated. These results support the view that Broca's region is engaged in structured sequence processing and extend previous functional neuroimaging results on artificial grammar learning (AGL) in two directions: first, the results establish that Broca's region is a causal component in the processing of non-adjacent dependencies, and second, they show that implicit processing of non-adjacent dependencies engages Broca's region. Since patients with lesions in Broca's region do not always show grammatical processing difficulties, the result that Broca's region is causally linked to processing of non-adjacent dependencies is a step towards clarification of the exact nature of syntactic deficits caused by lesions or perturbation to Broca's region. Our findings are consistent with previous results and support a role for Broca's region in general structured sequence processing, rather than a specific role for the processing of hierarchically organized sentence structure.

Eye movements in implicit artificial grammar learning.

Artificial grammar learning (AGL) has been probed with forced-choice behavioral tests (active tests). Recent attempts to probe the outcomes of learning (implicitly acquired knowledge) with eye-movement responses (passive tests) have shown null results. However, these latter studies have not tested for sensitivity effects, for example, increased eye movements on a printed violation. In this study, we tested for sensitivity effects in AGL tests with (Experiment 1) and without (Experiment 2) concurrent active tests (preference- and grammaticality classification) in an eye-tracking experiment. Eye movements discriminated between sequence types in passive tests and more so in active tests. The eye-movement profile did not differ between preference and grammaticality classification, and it resembled sensitivity effects commonly observed in natural syntax processing. Our findings show that the outcomes of implicit structured sequence learning can be characterized in eye tracking. More specifically, whole trial measures (dwell time, number of fixations) showed robust AGL effects, whereas first-pass measures (first-fixation duration) did not. Furthermore, our findings strengthen the link between artificial and natural syntax processing, and they shed light on the factors that determine performance differences in preference and grammaticality classification tests. (PsycINFO Database Record

The effects of ordinal load on incidental temporal learning.

How can we grasp the temporal structure of events? A few studies have indicated that representations of temporal structure are acquired when there is an intention to learn, but not when learning is incidental. Response-to-stimulus intervals, uncorrelated temporal structures, unpredictable ordinal information, and lack of metrical organization have been pointed out as key obstacles to incidental temporal learning, but the literature includes piecemeal demonstrations of learning under all these circumstances. We suggest that the unacknowledged effects of ordinal load may help reconcile these conflicting findings, ordinal load referring to the cost of identifying the sequence of events (e.g., tones, locations) where a temporal pattern is embedded. In a first experiment, we manipulated ordinal load into simple and complex levels. Participants learned ordinal-simple sequences, despite their uncorrelated temporal structure and lack of metrical organization. They did not learn ordinal-complex sequences, even though there were no response-to-stimulus intervals nor unpredictable ordinal information. In a second experiment, we probed learning of ordinal-complex sequences with strong metrical organization, and again there was no learning. We conclude that ordinal load is a key obstacle to incidental temporal learning. Further analyses showed that the effect of ordinal load is to mask the expression of temporal knowledge, rather than to prevent learning.

Disentangling stimulus plausibility and contextual congruency: Electro-physiological evidence for differential cognitive dynamics.

Expectancy mechanisms are routinely used by the cognitive system in stimulus processing and in anticipation of appropriate responses. Electrophysiology research has documented negative shifts of brain activity when expectancies are violated within a local stimulus context (e.g., reading an implausible word in a sentence) or more globally between consecutive stimuli (e.g., a narrative of images with an incongruent end). In this EEG study, we examine the interaction between expectancies operating at the level of stimulus plausibility and at more global level of contextual congruency to provide evidence for, or against, a disassociation of the underlying processing mechanisms. We asked participants to verify the congruency of pairs of cross-modal stimuli (a sentence and a scene), which varied in plausibility. ANOVAs on ERP amplitudes in selected windows of interest show that congruency violation has longer-lasting (from 100 to 500ms) and more widespread effects than plausibility violation (from 200 to 400ms). We also observed critical interactions between these factors, whereby incongruent and implausible pairs elicited stronger negative shifts than their congruent counterpart, both early on (100-200ms) and between 400-500ms. Our results suggest that the integration mechanisms are sensitive to both global and local effects of expectancy in a modality independent manner. Overall, we provide novel insights into the interdependence of expectancy during meaning integration of cross-modal stimuli in a verification task.

The P600 in Implicit Artificial Grammar Learning.

The suitability of the artificial grammar learning (AGL) paradigm to capture relevant aspects of the acquisition of linguistic structures has been empirically tested in a number of EEG studies. Some have shown a syntax-related P600 component, but it has not been ruled out that the AGL P600 effect is a response to surface features (e.g., subsequence familiarity) rather than the underlying syntax structure. Therefore, in this study, we controlled for the surface characteristics of the test sequences (associative chunk strength) and recorded the EEG before (baseline preference classification) and after (preference and grammaticality classification) exposure to a grammar. After exposure, a typical, centroparietal P600 effect was elicited by grammatical violations and not by unfamiliar subsequences, suggesting that the AGL P600 effect signals a response to structural irregularities. Moreover, preference and grammaticality classification showed a qualitatively similar ERP profile, strengthening the idea that the implicit structural mere-exposure paradigm in combination with preference classification is a suitable alternative to the traditional grammaticality classification test.

When the Eyes No Longer Lead: Familiarity and Length Effects on Eye-Voice Span.

During oral reading, the eyes tend to be ahead of the voice (eye-voice span, EVS). It has been hypothesized that the extent to which this happens depends on the automaticity of reading processes, namely on the speed of print-to-sound conversion. We tested whether EVS is affected by another automaticity component - immunity from interference. To that end, we manipulated word familiarity (high-frequency, low-frequency, and pseudowords, PW) and word length as proxies of immunity from interference, and we used linear mixed effects models to measure the effects of both variables on the time interval at which readers do parallel processing by gazing at word N + 1 while not having articulated word N yet (offset EVS). Parallel processing was enhanced by automaticity, as shown by familiarity × length interactions on offset EVS, and it was impeded by lack of automaticity, as shown by the transformation of offset EVS into voice-eye span (voice ahead of the offset of the eyes) in PWs. The relation between parallel processing and automaticity was strengthened by the fact that offset EVS predicted reading velocity. Our findings contribute to understand how the offset EVS, an index that is obtained in oral reading, may tap into different components of automaticity that underlie reading ability, oral or silent. In addition, we compared the duration of the offset EVS with the average reference duration of stages in word production, and we saw that the offset EVS may accommodate for more than the articulatory programming stage of word N.

Visual naming deficits in dyslexia: An ERP investigation of different processing domains.

Naming speed deficits are well documented in developmental dyslexia, expressed by slower naming times and more errors in response to familiar items. Here we used event-related potentials (ERPs) to examine at what processing level the deficits in dyslexia emerge during a discrete-naming task. Dyslexic and skilled adult control readers performed a primed object-naming task, in which the relationship between the prime and the target was manipulated along perceptual, semantic and phonological dimensions. A 3×2 design that crossed Relationship Type (Visual, Phonemic Onset, and Semantic) with Relatedness (Related and Unrelated) was used. An attenuated N/P190 - indexing early visual processing - and N300 - which index late visual processing - was observed to pictures preceded by perceptually related (vs. unrelated) primes in the control but not in the dyslexic group. These findings suggest suboptimal processing in early stages of object processing in dyslexia, when integration and mapping of perceptual information to a more form-specific percept in memory take place. On the other hand, both groups showed an N400 effect associated with semantically related pictures (vs. unrelated), taken to reflect intact integration of semantic similarities in both dyslexic and control readers. We also found an electrophysiological effect of phonological priming in the N400 range - that is, an attenuated N400 to objects preceded by phonemic related primes vs. unrelated - while it showed a more widespread distributed and more pronounced over the right hemisphere in the dyslexics. Topographic differences between groups might have originated from a word form encoding process with different characteristics in dyslexics compared to control readers.