"Not" in the brain and behavior.

Negation is key for cognition but has no physical basis, raising questions about its neural origins. A new study in PLOS Biology on the negation of scalar adjectives shows that negation acts in part by altering the response to the adjective it negates.

Phase-dependent word perception emerges from region-specific sensitivity to the statistics of language.

Neural oscillations reflect fluctuations in excitability, which biases the percept of ambiguous sensory input. Why this bias occurs is still not fully understood. We hypothesized that neural populations representing likely events are more sensitive, and thereby become active on earlier oscillatory phases, when the ensemble itself is less excitable. Perception of ambiguous input presented during less-excitable phases should therefore be biased toward frequent or predictable stimuli that have lower activation thresholds. Here, we show such a frequency bias in spoken word recognition using psychophysics, magnetoencephalography (MEG), and computational modelling. With MEG, we found a double dissociation, where the phase of oscillations in the superior temporal gyrus and medial temporal gyrus biased word-identification behavior based on phoneme and lexical frequencies, respectively. This finding was reproduced in a computational model. These results demonstrate that oscillations provide a temporal ordering of neural activity based on the sensitivity of separable neural populations.

Neural dynamics differentially encode phrases and sentences during spoken language comprehension.

Human language stands out in the natural world as a biological signal that uses a structured system to combine the meanings of small linguistic units (e.g., words) into larger constituents (e.g., phrases and sentences). However, the physical dynamics of speech (or sign) do not stand in a one-to-one relationship with the meanings listeners perceive. Instead, listeners infer meaning based on their knowledge of the language. The neural readouts of the perceptual and cognitive processes underlying these inferences are still poorly understood. In the present study, we used scalp electroencephalography (EEG) to compare the neural response to phrases (e.g., the red vase) and sentences (e.g., the vase is red), which were close in semantic meaning and had been synthesized to be physically indistinguishable. Differences in structure were well captured in the reorganization of neural phase responses in delta (approximately <2 Hz) and theta bands (approximately 2 to 7 Hz),and in power and power connectivity changes in the alpha band (approximately 7.5 to 13.5 Hz). Consistent with predictions from a computational model, sentences showed more power, more power connectivity, and more phase synchronization than phrases did. Theta-gamma phase-amplitude coupling occurred, but did not differ between the syntactic structures. Spectral-temporal response function (STRF) modeling revealed different encoding states for phrases and sentences, over and above the acoustically driven neural response. Our findings provide a comprehensive description of how the brain encodes and separates linguistic structures in the dynamics of neural responses. They imply that phase synchronization and strength of connectivity are readouts for the constituent structure of language. The results provide a novel basis for future neurophysiological research on linguistic structure representation in the brain, and, together with our simulations, support time-based binding as a mechanism of structure encoding in neural dynamics.

Delta-Band Neural Responses to Individual Words Are Modulated by Sentence Processing.

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 toward 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 ∼100 milliseconds in right frontal areas. We conclude that low-frequency responses to words are changed by sentential context. The results of this study show how the neural representation of words is affected by structural context and as such provide insight into how the brain instantiates compositionality in language.SIGNIFICANCE STATEMENT Human language is unprecedented in its combinatorial capacity: we are capable of producing and understanding sentences we have never heard before. Although the mechanisms underlying this capacity have been described in formal linguistics and cognitive science, how they are implemented in the brain remains to a large extent unknown. A large body of earlier work from the cognitive neuroscientific literature implies a role for delta-band neural activity in the representation of linguistic structure and meaning. In this work, we combine these insights and techniques with findings from psycholinguistics to show that meaning is more than the sum of its parts; the delta-band MEG signal differentially reflects lexical information inside and outside sentence structures.

Naturalistic Spoken Language Comprehension Is Supported by Alpha and Beta Oscillations.

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 ß oscillations are linked to the putative reactivation of content representations. Can the proposed functional role of α and ß 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 ß power from the dependency features. Results showed that dependency features predict α and ß 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 ß. Critically, α- and ß-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-ß responses, their potential functional dissociation remains to be elucidated. Overall, this study sheds light on the role of α and ß oscillations during naturalistic spoken language comprehension, providing evidence for the generalizability of these dynamics from perceptual to complex linguistic processes.SIGNIFICANCE STATEMENT It remains unclear whether the proposed functional role of α and ß oscillations in perceptual and motor function is generalizable to higher-level cognitive processes, such as spoken language comprehension. We found that syntactic features predict α and ß power in language-related regions beyond low-level linguistic features when listening to naturalistic speech in a known language. We offer experimental findings that integrate a neuroscientific framework on the role of brain oscillations as "building blocks" with spoken language comprehension. This supports the view of a domain-general role of oscillations across the hierarchy of cognitive functions, from low-level sensory operations to abstract linguistic processes.

Interdependence of "What" and "When" in the Brain.

From a brain's-eye-view, when a stimulus occurs and what it is are interrelated aspects of interpreting the perceptual world. Yet in practice, the putative perceptual inferences about sensory content and timing are often dichotomized and not investigated as an integrated process. We here argue that neural temporal dynamics can influence what is perceived, and in turn, stimulus content can influence the time at which perception is achieved. This computational principle results from the highly interdependent relationship of what and when in the environment. Both brain processes and perceptual events display strong temporal variability that is not always modeled; we argue that understanding-and, minimally, modeling-this temporal variability is key for theories of how the brain generates unified and consistent neural representations and that we ignore temporal variability in our analysis practice at the peril of both data interpretation and theory-building. Here, we review what and when interactions in the brain, demonstrate via simulations how temporal variability can result in misguided interpretations and conclusions, and outline how to integrate and synthesize what and when in theories and models of brain computation.

Delta-band Activity Underlies Referential Meaning Representation during Pronoun Resolution.

Human language offers a variety of ways to create meaning, one of which is referring to entities, objects, or events in the world. One such meaning maker is understanding to whom or to what a pronoun in a discourse refers to. To understand a pronoun, the brain must access matching entities or concepts that have been encoded in memory from previous linguistic context. Models of language processing propose that internally stored linguistic concepts, accessed via exogenous cues such as phonological input of a word, are represented as (a)synchronous activities across a population of neurons active at specific frequency bands. Converging evidence suggests that delta band activity (1-3 Hz) is involved in temporal and representational integration during sentence processing. Moreover, recent advances in the neurobiology of memory suggest that recollection engages neural dynamics similar to those which occurred during memory encoding. Integrating from these two research lines, we here tested the hypothesis that neural dynamic patterns, especially in delta frequency range, underlying referential meaning representation, would be reinstated during pronoun resolution. By leveraging neural decoding techniques (i.e., representational similarity analysis) on a magnetoencephalogram data set acquired during a naturalistic story-listening task, we provide evidence that delta-band activity underlies referential meaning representation. Our findings suggest that, during spoken language comprehension, endogenous linguistic representations such as referential concepts may be proactively retrieved and represented via activation of their underlying dynamic neural patterns.

Thorough assessment of the effectiveness of belimumab in a large Spanish multicenter cohort of systemic lupus erythematosus patients.

OBJECTIVES: To provide an overview on the current use of belimumab (BLM) in SLE patients in clinical practice and to examine its efficacy in terms of standardized outcomes, drug survival, as well as patient and safety profiles. METHODS: A longitudinal retrospective multicentre cohort including SLE patients treated with BLM at 18 Spanish centers. Data was collected upon initiation of BLM, at 6 and 12 months after initiation, and at the last recorded visit. Changes in SLEDAI-2K, the proportion of patients who achieved LLDAS and DORIS 2021, and number of flares were compared between visits. Changes in damage, glucocorticoids use and employment status pre-BLM and post-BLM were also assessed. RESULTS: A total of 324 patients were included with a mean follow-up of 3.8 (±2.7) years. LLDAS was attained by 45.8%, 62% and 71% of patients, and DORIS by 24%, 36.2% and 52.5% on successive visits, respectively. Twenty-seven-point two percent of patients were in DORIS ≥ 50% of the visits and a 46% in LLDAS-50. Flares and number of flares were significantly lower one year after treatment with BLM and no changes in damage accrual were observed. Mean (±SD) prednisone dose was significantly reduced over time, with 70 (24%) patients discontinuing GC. CONCLUSION: Our study not only demonstrates belimumab´s efficacy in attaining treat-to-target goals in SLE patients, but also confirms its GC-sparing effect, and its prevention of flares and organ damage accrual.

Stress degrades working memory-related frontostriatal circuit function.

Goal-directed behavior is dependent on neuronal activity in the prefrontal cortex (PFC) and extended frontostriatal circuitry. Stress and stress-related disorders are associated with impaired frontostriatal-dependent cognition. Our understanding of the neural mechanisms that underlie stress-related cognitive impairment is limited, with the majority of prior research focused on the PFC. To date, the actions of stress across cognition-related frontostriatal circuitry are unknown. To address this gap, the current studies examined the effects of acute noise-stress on the spiking activity of neurons and local field potential oscillatory activity within the dorsomedial PFC (dmPFC) and dorsomedial striatum (dmSTR) in rats engaged in a test of spatial working memory. Stress robustly suppressed responses of both dmPFC and dmSTR neurons strongly tuned to key task events (delay, reward). Additionally, stress strongly suppressed delay-related, but not reward-related, theta and alpha spectral power within, and synchrony between, the dmPFC and dmSTR. These observations provide the first demonstration that stress disrupts the neural coding and functional connectivity of key task events, particularly delay, within cognition-supporting dorsomedial frontostriatal circuitry. These results suggest that stress-related degradation of neural coding within both the PFC and striatum likely contributes to the cognition-impairing effects of stress.

Generation and Characterization of Mirikizumab, a Humanized Monoclonal Antibody Targeting the p19 Subunit of IL-23.

Interleukin (IL)-23 exists as a heterodimer consisting of p19 and p40 and is a key cytokine for promoting inflammatory responses in a variety of target organs. IL-23 plays a key role in the differentiation and maintenance of T helper 17 cells, and deregulation of IL-23 can result in autoimmune pathologies of the skin, lungs, and gut. This study describes the generation and characterization of mirikizumab (miri), a humanized IgG4 monoclonal antibody directed against the p19 subunit of IL-23. Miri binds human and cynomolgus monkey IL-23 with high affinity and binds rabbit IL-23 weakly but does not bind to rodent IL-23 or the other IL-23 family members IL-12, IL-27, or IL-35. Miri effectively inhibits the interaction of IL-23 with its receptor, and potently blocks IL-23-induced IL-17 production in cell-based assays while preserving the function of IL-12. In both local and systemic in vivo mouse models, miri blocked IL-23-induced keratin mRNA or IL-17 production, respectively. These data provide a comprehensive preclinical characterization of miri, for which efficacy and safety have been demonstrated in human clinical trials for psoriasis, ulcerative colitis, and Crohn's disease. SIGNIFICANCE STATEMENT: This article describes the generation and characterization of mirikizumab, a high affinity, neutralizing IgG4 variant monoclonal antibody that is under development for the treatment of ulcerative colitis and Crohn's disease. Neutralization of interleukin (IL)-23 is achieved by preventing the binding of IL-23 p19 subunit to the IL-23 receptor and does not affect the IL-12 pathway.

Inferring the nature of linguistic computations in the brain.

Sentences contain structure that determines their meaning beyond that of individual words. An influential study by Ding and colleagues (2016) used frequency tagging of phrases and sentences to show that the human brain is sensitive to structure by finding peaks of neural power at the rate at which structures were presented. Since then, there has been a rich debate on how to best explain this pattern of results with profound impact on the language sciences. Models that use hierarchical structure building, as well as models based on associative sequence processing, can predict the neural response, creating an inferential impasse as to which class of models explains the nature of the linguistic computations reflected in the neural readout. In the current manuscript, we discuss pitfalls and common fallacies seen in the conclusions drawn in the literature illustrated by various simulations. We conclude that inferring the neural operations of sentence processing based on these neural data, and any like it, alone, is insufficient. We discuss how to best evaluate models and how to approach the modeling of neural readouts to sentence processing in a manner that remains faithful to cognitive, neural, and linguistic principles.

Local Thyroid Hormone Action in Brain Development.

Proper brain development essentially depends on the timed availability of sufficient amounts of thyroid hormone (TH). This, in turn, necessitates a tightly regulated expression of TH signaling components such as TH transporters, deiodinases, and TH receptors in a brain region- and cell-specific manner from early developmental stages onwards. Abnormal TH levels during critical stages, as well as mutations in TH signaling components that alter the global and/or local thyroidal state, result in detrimental consequences for brain development and neurological functions that involve alterations in central neurotransmitter systems. Thus, the question as to how TH signaling is implicated in the development and maturation of different neurotransmitter and neuromodulator systems has gained increasing attention. In this review, we first summarize the current knowledge on the regulation of TH signaling components during brain development. We then present recent advances in our understanding on how altered TH signaling compromises the development of cortical glutamatergic neurons, inhibitory GABAergic interneurons, cholinergic and dopaminergic neurons. Thereby, we highlight novel mechanistic insights and point out open questions in this evolving research field.

Linguistic Structure and Meaning Organize Neural Oscillations into a Content-Specific Hierarchy.

Neural oscillations track linguistic information during speech comprehension (Ding et al., 2016; Keitel et al., 2018), and are known to be modulated by acoustic landmarks and speech intelligibility (Doelling et al., 2014; Zoefel and VanRullen, 2015). However, studies investigating linguistic tracking have either relied on non-naturalistic isochronous stimuli or failed to fully control for prosody. Therefore, it is still unclear whether low-frequency activity tracks linguistic structure during natural speech, where linguistic structure does not follow such a palpable temporal pattern. Here, we measured electroencephalography (EEG) and manipulated the presence of semantic and syntactic information apart from the timescale of their occurrence, while carefully controlling for the acoustic-prosodic and lexical-semantic information in the signal. EEG was recorded while 29 adult native speakers (22 women, 7 men) listened to naturally spoken Dutch sentences, jabberwocky controls with morphemes and sentential prosody, word lists with lexical content but no phrase structure, and backward acoustically matched controls. Mutual information (MI) analysis revealed sensitivity to linguistic content: MI was highest for sentences at the phrasal (0.8-1.1 Hz) and lexical (1.9-2.8 Hz) timescales, suggesting that the delta-band is modulated by lexically driven combinatorial processing beyond prosody, and that linguistic content (i.e., structure and meaning) organizes neural oscillations beyond the timescale and rhythmicity of the stimulus. This pattern is consistent with neurophysiologically inspired models of language comprehension (Martin, 2016, 2020; Martin and Doumas, 2017) where oscillations encode endogenously generated linguistic content over and above exogenous or stimulus-driven timing and rhythm information.SIGNIFICANCE STATEMENT Biological systems like the brain encode their environment not only by reacting in a series of stimulus-driven responses, but by combining stimulus-driven information with endogenous, internally generated, inferential knowledge and meaning. Understanding language from speech is the human benchmark for this. Much research focuses on the purely stimulus-driven response, but here, we focus on the goal of language behavior: conveying structure and meaning. To that end, we use naturalistic stimuli that contrast acoustic-prosodic and lexical-semantic information to show that, during spoken language comprehension, oscillatory modulations reflect computations related to inferring structure and meaning from the acoustic signal. Our experiment provides the first evidence to date that compositional structure and meaning organize the oscillatory response, above and beyond prosodic and lexical controls.

Nucleophilic catalysis of p-substituted aniline derivatives in acylhydrazone formation and exchange.

Hydrazone bond formation is a versatile reaction employed in several research fields. It is one of the most popular reversible reactions in dynamic combinatorial chemistry. Under physiological conditions, hydrazone exchange benefits from the addition of a nucleophilic catalyst. We report a mechanistic study and superior performance of electron-rich p-substituted aniline derivatives as catalysts for efficient hydrazone formation and exchange in both protic and aprotic solvents. Rigorous kinetic analyses demonstrate that imine formation with 3-hydroxy-4-nitrobenzaldehyde and aniline derivatives proceeds with unprecedented third-order kinetics in which the aldehyde consistently shows a partial order of two. Computational investigations provide insights into the mechanisms of these transformations.

Prefrontal Corticotropin-Releasing Factor (CRF) Neurons Act Locally to Modulate Frontostriatal Cognition and Circuit Function.

The PFC and extended frontostriatal circuitry support higher cognitive processes that guide goal-directed behavior. PFC-dependent cognitive dysfunction is a core feature of multiple psychiatric disorders. Unfortunately, a major limiting factor in the development of treatments for PFC cognitive dysfunction is our limited understanding of the neural mechanisms underlying PFC-dependent cognition. We recently demonstrated that activation of corticotropin-releasing factor (CRF) receptors in the caudal dorsomedial PFC (dmPFC) impairs higher cognitive function, as measured in a working memory task. Currently, there remains much unknown about CRF-dependent regulation of cognition, including the source of CRF for cognition-modulating receptors and the output pathways modulated by these receptors. To address these issues, the current studies used a viral vector-based approach to chemogenetically activate or inhibit PFC CRF neurons in working memory-tested male rats. Chemogenetic activation of caudal, but not rostral, dmPFC CRF neurons potently impaired working memory, whereas inhibition of these neurons improved working memory. Importantly, the cognition-impairing actions of PFC CRF neurons were dependent on local CRF receptors coupled to protein kinase A. Additional electrophysiological recordings demonstrated that chemogenetic activation of caudal dmPFC CRF neurons elicits a robust degradation of task-related coding properties of dmPFC pyramidal neurons and, to a lesser extent, medium spiny neurons in the dorsomedial striatum. Collectively, these results demonstrate that local CRF release within the caudal dmPFC impairs frontostriatal cognitive and circuit function and suggest that CRF may represent a potential target for treating frontostriatal cognitive dysfunction.SIGNIFICANCE STATEMENT The dorsomedial PFC and its striatal targets play a critical role in higher cognitive function. PFC-dependent cognitive dysfunction is associated with many psychiatric disorders. Although it has long-been known that corticotropin-releasing factor (CRF) neurons are prominent within the PFC, their role in cognition has remained unclear. Using a novel chemogenetic viral vector system, the present studies demonstrate that PFC CRF neurons impair working memory via activation of local PKA-coupled CRF receptors, an action associated with robust degradation in task-related frontostriatal neuronal coding. Conversely, suppression of constitutive PFC CRF activity improved working memory. Collectively, these studies provide novel insight into the neurobiology of cognition and suggest that CRF may represent a novel target for the treatment of cognitive dysfunction.

A Compositional Neural Architecture for Language.

Hierarchical structure and compositionality imbue human language with unparalleled expressive power and set it apart from other perception-action systems. However, neither formal nor neurobiological models account for how these defining computational properties might arise in a physiological system. I attempt to reconcile hierarchy and compositionality with principles from cell assembly computation in neuroscience; the result is an emerging theory of how the brain could convert distributed perceptual representations into hierarchical structures across multiple timescales while representing interpretable incremental stages of (de)compositional meaning. The model's architecture-a multidimensional coordinate system based on neurophysiological models of sensory processing-proposes that a manifold of neural trajectories encodes sensory, motor, and abstract linguistic states. Gain modulation, including inhibition, tunes the path in the manifold in accordance with behavior and is how latent structure is inferred. As a consequence, predictive information about upcoming sensory input during production and comprehension is available without a separate operation. The proposed processing mechanism is synthesized from current models of neural entrainment to speech, concepts from systems neuroscience and category theory, and a symbolic-connectionist computational model that uses time and rhythm to structure information. I build on evidence from cognitive neuroscience and computational modeling that suggests a formal and mechanistic alignment between structure building and neural oscillations, and moves toward unifying basic insights from linguistics and psycholinguistics with the currency of neural computation.

A mechanism for the cortical computation of hierarchical linguistic structure.

Biological systems often detect species-specific signals in the environment. In humans, speech and language are species-specific signals of fundamental biological importance. To detect the linguistic signal, human brains must form hierarchical representations from a sequence of perceptual inputs distributed in time. What mechanism underlies this ability? One hypothesis is that the brain repurposed an available neurobiological mechanism when hierarchical linguistic representation became an efficient solution to a computational problem posed to the organism. Under such an account, a single mechanism must have the capacity to perform multiple, functionally related computations, e.g., detect the linguistic signal and perform other cognitive functions, while, ideally, oscillating like the human brain. We show that a computational model of analogy, built for an entirely different purpose-learning relational reasoning-processes sentences, represents their meaning, and, crucially, exhibits oscillatory activation patterns resembling cortical signals elicited by the same stimuli. Such redundancy in the cortical and machine signals is indicative of formal and mechanistic alignment between representational structure building and "cortical" oscillations. By inductive inference, this synergy suggests that the cortical signal reflects structure generation, just as the machine signal does. A single mechanism-using time to encode information across a layered network-generates the kind of (de)compositional representational hierarchy that is crucial for human language and offers a mechanistic linking hypothesis between linguistic representation and cortical computation.

The LISA beamline at ESRF.

This contribution provides a description of LISA, the new Italian Collaborating Research Group beamline operative at the European Synchrotron Radiation Facility. A presentation of the instruments available and optical devices is given as well as the main X-ray parameters (flux, energy resolution, focal spot dimensions, etc.) and comparison with theoretical calculations. The beamline has been open to users since April 2018 and will be ready at the opening of the Extremely Brilliant Source in late-2020.

Novel Synthesis of Anhydrous and Hydroxylated CuF2 Nanoparticles and Their Potential for Lithium Ion Batteries.

Anhydrous nanoscopic CuF2 is synthesized from alkoxides Cu(OR)2 (R=Me, tBu) by their reaction either in pure liquid HF at -70 °C, or under solvothermal conditions at 150 °C using excess HF and THF as solvent. Depending on the synthesis method, nanoparticles of sizes between 10 and 100 nm are obtained. The compound is highly hygroscopic and forms different hydrolysis products under moist air, namely CuF2 ⋅2 H2 O, Cu2 (OH)F3 , and Cu(OH)F, of which only the latter is stable at room temperature. CuF2 exhibits an electrochemical plateau at a potential of ≈2.7 V when cycled versus Li in half cell Li-ion batteries, which is attributed to a non-reversible conversion mechanism. The cell capacity in the first cycle depends on the particle size, being 468 mAh g-1 for ≈8 nm crystallite diameter, and 353 mAh g-1 for ≈12 nm crystallite diameter, referred to CuF2 . However, such a high capacity cannot be sustained for several cycles and the capacity rapidly fades out. The cell voltage decreases to ≈2.0 V for CuF2 ⋅2 H2 O, Cu2 (OH)F3 , and Cu(OH)F. As all the compounds studied in this work show irreversible conversion reactions, it can be concluded that copper-based fluorides are unsuitable for Li-ion battery applications.