Can training neural language models on a curriculum with developmentally plausible data improve alignment with human reading behavior?

The use of neural language models to model human behavior has met with mixed success. While some work has found that the surprisal estimates from these models can be used to predict a wide range of human neural and behavioral responses, other work studying more complex syntactic phenomena has found that these surprisal estimates generate incorrect behavioral predictions. This paper explores the extent to which the misalignment between empirical and model-predicted behavior can be minimized by training models on more developmentally plausible data, such as in the BabyLM Challenge. We trained teacher language models on the BabyLM "strict-small" dataset and used sentence level surprisal estimates from these teacher models to create a curriculum. We found tentative evidence that our curriculum made it easier for models to acquire linguistic knowledge from the training data: on the subset of tasks in the BabyLM challenge suite evaluating models' grammatical knowledge of English, models first trained on the BabyLM data curriculum and then on a few randomly ordered training epochs performed slightly better than models trained on randomly ordered epochs alone. This improved linguistic knowledge acquisition did not result in better alignment with human reading behavior, however: models trained on the BabyLM dataset (with or without a curriculum) generated predictions that were as misaligned with human behavior as models trained on larger less curated datasets. This suggests that training on developmentally plausible datasets alone is likely insufficient to generate language models capable of accurately predicting human language processing.Comment: To appear in the proceedings of BabyLM shared task CoNLL 202

Repetitive transcranial magnetic stimulation for treatment of limb spasticity following multiple sclerosis: a systematic review and meta-analysis

Pilot trials have suggested that repetitive transcranial magnetic stimulation (rTMS) may reduce limb spasticity in multiple sclerosis (MS). We carried out the current meta-analysis to synthesize currently available evidence regarding such correlation. Up to November 2022, five international electronic databases (Cochrane CENTRAL, PubMed, Embase, Web of Science, and CINAHL) and four Chinese electronic databases (CBM, CNKI, WanFang Data, and VIP) were systematically searched to identify randomized trials comparing active rTMS and sham stimulation in patients with MS-related spasticity. Two reviewers independently selected studies and extracted data on study design, quality, clinical outcomes, and time points measured. The primary outcome was clinical spasticity relief after intervention. Secondary outcomes included spasticity at the follow-up visit 2 weeks later and post-treatment fatigue. Of 831 titles found, we included 8 studies (181 participants) in the quantitative analysis. Pooled analyses showed that rTMS therapy was associated with significant spasticity relief in the early post-intervention period [standardized mean differences (SMD): -0.67; 95%CI: -1.12 to -0.21], but there was insufficient evidence for rTMS in reducing spasticity at the follow-up visit 2 weeks later (SMD: -0.17; 95%CI: -0.52 to 0.17) and fatigue (SMD: -0.26; 95%CI: -0.84 to 0.31). This evidence supports the recommendations to treat MS-related spasticity with rTMS, but underlines the need for further large randomized trials

Burning Cold: Involvement of TRPA1 in Noxious Cold Sensation

Soon after its discovery ten years ago, the ion channel TRPA1 was proposed as a sensor of noxious cold. Evidence for its activation by painfully cold temperatures (below ~15° C) has been mixed, however. Some groups found that cold elicits a nonselective conductance in cells expressing TRPA1; others found no activation, or argued that activation is an indirect effect of elevated $Ca^{ 2+}$ . Sensory cells from the trigeminal and dorsal root ganglia that are activated by cold were sometimes correlated with those cells expressing TRPA1; other times not. Mice lacking TRPA1 showed behavioral defi cits for some assays of painful cold sensation, but not others. New evidence tends to support direct activation of TRPA1 by cold, and the slow and relatively weak activation of TRPA1 by cold helps reconcile some confl icting studies

TrpA1 Regulates Thermal Nociception in Drosophila

Pain is a significant medical concern and represents a major unmet clinical need. The ability to perceive and react to tissue-damaging stimuli is essential in order to maintain bodily integrity in the face of environmental danger. To prevent damage the systems that detect noxious stimuli are therefore under strict evolutionary pressure. We developed a high-throughput behavioral method to identify genes contributing to thermal nociception in the fruit fly and have reported a large-scale screen that identified the Ca2+ channel straightjacket (stj) as a conserved regulator of thermal nociception. Here we present the minimal anatomical and neuronal requirements for Drosophila to avoid noxious heat in our novel behavioral paradigm. Bioinformatics analysis of our whole genome data set revealed 23 genes implicated in Ca2+ signaling that are required for noxious heat avoidance. One of these genes, the conserved thermoreceptor TrpA1, was confirmed as a bona fide “pain” gene in both adult and larval fly nociception paradigms. The nociceptive function of TrpA1 required expression within the Drosophila nervous system, specifically within nociceptive multi-dendritic (MD) sensory neurons. Therefore, our analysis identifies the channel TRPA1 as a conserved regulator of nociception

Regulation of Energy Stores and Feeding by Neuronal and Peripheral CREB Activity in Drosophila

The cAMP-responsive transcription factor CREB functions in adipose tissue and liver to regulate glycogen and lipid metabolism in mammals. While Drosophila has a homolog of mammalian CREB, dCREB2, its role in energy metabolism is not fully understood. Using tissue-specific expression of a dominant-negative form of CREB (DN-CREB), we have examined the effect of blocking CREB activity in neurons and in the fat body, the primary energy storage depot with functions of adipose tissue and the liver in flies, on energy balance, stress resistance and feeding behavior. We found that disruption of CREB function in neurons reduced glycogen and lipid stores and increased sensitivity to starvation. Expression of DN-CREB in the fat body also reduced glycogen levels, while it did not affect starvation sensitivity, presumably due to increased lipid levels in these flies. Interestingly, blocking CREB activity in the fat body increased food intake. These flies did not show a significant change in overall body size, suggesting that disruption of CREB activity in the fat body caused an obese-like phenotype. Using a transgenic CRE-luciferase reporter, we further demonstrated that disruption of the adipokinetic hormone receptor, which is functionally related to mammalian glucagon and β-adrenergic signaling, in the fat body reduced CRE-mediated transcription in flies. This study demonstrates that CREB activity in either neuronal or peripheral tissues regulates energy balance in Drosophila, and that the key signaling pathway regulating CREB activity in peripheral tissue is evolutionarily conserved

Analysis of Adhesion Molecules and Basement Membrane Contributions to Synaptic Adhesion at the Drosophila Embryonic NMJ

Synapse formation and maintenance crucially underlie brain function in health and disease. Both processes are believed to depend on cell adhesion molecules (CAMs). Many different classes of CAMs localise to synapses, including cadherins, protocadherins, neuroligins, neurexins, integrins, and immunoglobulin adhesion proteins, and further contributions come from the extracellular matrix and its receptors. Most of these factors have been scrutinised by loss-of-function analyses in animal models. However, which adhesion factors establish the essential physical links across synaptic clefts and allow the assembly of synaptic machineries at the contact site in vivo is still unclear. To investigate these key questions, we have used the neuromuscular junction (NMJ) of Drosophila embryos as a genetically amenable model synapse. Our ultrastructural analyses of NMJs lacking different classes of CAMs revealed that loss of all neurexins, all classical cadherins or all glutamate receptors, as well as combinations between these or with a Laminin deficiency, failed to reveal structural phenotypes. These results are compatible with a view that these CAMs might have no structural role at this model synapse. However, we consider it far more likely that they operate in a redundant or well buffered context. We propose a model based on a multi-adaptor principle to explain this phenomenon. Furthermore, we report a new CAM-independent adhesion mechanism that involves the basement membranes (BM) covering neuromuscular terminals. Thus, motorneuronal terminals show strong partial detachment of the junction when BM-to-cell surface attachment is impaired by removing Laminin A, or when BMs lose their structural integrity upon loss of type IV collagens. We conclude that BMs are essential to tie embryonic motorneuronal terminals to the muscle surface, lending CAM-independent structural support to their adhesion. Therefore, future developmental studies of these synaptic junctions in Drosophila need to consider the important contribution made by BM-dependent mechanisms, in addition to CAM-dependent adhesion

Observation of the Rare Decay of the η Meson to Four Muons

A search for the rare η→μ+μ−μ+μ− double-Dalitz decay is performed using a sample of proton-proton collisions, collected by the CMS experiment at the CERN LHC with high-rate muon triggers during 2017 and 2018 and corresponding to an integrated luminosity of 101  fb−1. A signal having a statistical significance well in excess of 5 standard deviations is observed. Using the η→μ+μ− decay as normalization, the branching fraction B(η→μ+μ−μ+μ−)=[5.0±0.8(stat)±0.7(syst)±0.7(B2μ)]×10−9 is measured, where the last term is the uncertainty in the normalization channel branching fraction. This work achieves an improved precision of over 5 orders of magnitude compared to previous results, leading to the first measurement of this branching fraction, which is found to agree with theoretical predictions

Performance of the local reconstruction algorithms for the CMS hadron calorimeter with Run 2 data

A description is presented of the algorithms used to reconstruct energy deposited in the CMS hadron calorimeter during Run 2 (2015–2018) of the LHC. During Run 2, the characteristic bunch-crossing spacing for proton-proton collisions was 25 ns, which resulted in overlapping signals from adjacent crossings. The energy corresponding to a particular bunch crossing of interest is estimated using the known pulse shapes of energy depositions in the calorimeter, which are measured as functions of both energy and time. A variety of algorithms were developed to mitigate the effects of adjacent bunch crossings on local energy reconstruction in the hadron calorimeter in Run 2, and their performance is compared