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Characterizing habit learning in the human brain at the individual and group levels: a multi-modal MRI study
No full textThe dual-process theory of action control postulates that there are two competitive and complementary mechanisms that control our behavior: a goal-directed system that executes deliberate actions, explicitly aimed toward a particular outcome, and a habitual system that autonomously execute well-learned actions, typically following an encounter with a previously associated cue. In line with the dual-process theory, animal studies have provided convincing evidence for dissociable neural mechanisms, mainly manifested in cortico-striatal regions, involved in goal-directed and habitual action control. While substantial progress has been made in characterizing the neural mechanism underlying habit learning in animals, we still lack knowledge on how habits are formed and maintained in the human brain. Thus far only one study, conducted more than a decade ago by Tricomi et al. (2009), has been able to induce habitual behavior in humans via extensive training. This study also implicated the posterior putamen in the process, using functional magnetic resonance imaging (fMRI). However, recent attempts to replicate the behavioral results of this study were not successful. This leaves the research of human habits, and particularly the research of their formation through extensive repetition, as well as their neural basis, limited and far behind the animal research in the field. This motivated us to (1) attempt to replicate the behavioral and imaging main findings of Tricomi et al., (2) identify further functional and microstructural neural modifications associated with habit formation and manifestation, and (3) investigate the relationships between functional and structural plasticity and individual differences in habit expression. To this end, in this registered report we used Tricomi et al.’s free-operant task along with multi-modal MRI methods in a well-powered sample (n=123). In this task participants’ sensitivity to outcome devaluation (an index of goal-directed/habitual action control) is tested following either short or extensive training. In contrast to our hypothesis, we were not able to demonstrate habit formation as a function of training duration nor were we able to relate any functional or microstructural plasticity in the putamen with individual habit expression. We found that a pattern of increased activations in the left head of caudate that reoccurred across each day’s training was associated with goal directed behavior and that increased processing of devalued cues in low-level visual regions was indicative of goal-directed behavior. In a follow-up exploratory analysis comparing habitual and goal-directed subgroups within each experimental group, we found that elevated activations in frontoparietal regions during early stages of training, as well as increased reactivity towards still-valued cues in somatosensory and superior parietal regions, were found in individuals that were more inclined to perform goal-directed behavior (compared with more habitual individuals). Taken together, regions commonly implicated in goal-directed behavior were most predictive of individual habit expression. Finally, we also found that differential patterns of training-related microstructural plasticity, as measured with diffusion MRI, in midbrain dopaminergic regions were associated with habit expression. This work provides new insights into the neural dynamics involved in individual habit formation/expression and encourages the development and testing of new, more sensitive, procedures for experimental habit induction in humans
Entanglement resolution of free Dirac fermions on a torus
No full textWhenever a system possesses a conserved charge, the density matrix splits into eigenspaces associated to the each symmetry sector and we can access the entanglement entropy in a given subspace, known as symmetry resolved entanglement (SRE). Here, we first evaluate the SRE for massless Dirac fermions in a system at finite temperature and size, i.e. on a torus. Then we add a massive term to the Dirac action and we treat it as a perturbation of the massless theory. The charge-dependent entropies turn out to be equally distributed among all the symmetry sectors at leading order. However, we find subleading corrections which depend both on the mass and on the boundary conditions along the torus. We also study the resolution of the fermionic negativity in terms of the charge imbalance between two subsystems. We show that also for this quantity, the presence of the mass alters the equipartition among the different imbalance sectors at subleading order
Water sorption isotherms and hysteresis of cement paste at moderately high temperature, up to 80 °C
No full textThe constitutive models of concrete often consider water desorption isotherms to be near-equilibrium and significantly affected by moderately high temperature, 40–80 °C, typically through microstructural changes. However literature data suggest that adsorption, not desorption, is near-equilibrium and moderate temperatures do not cause microstructural changes. This work supports the latter theory, through dynamic vapor sorption experiments on cement paste at 20–80 °C. Samples were pre-conditioned at 60% relative humidity and 20 °C, and isotherms were measured for several humidity ranges and testing rates. The results, corroborated by classical DFT simulations, indicate that adsorption is near-equilibrium and mostly unaffected by temperature, whereas desorption is out-of-equilibrium due to the ink-bottle effect at high humidity, and interlayer water at low humidity. Starting from the second cycle, desorption at higher temperatures features a shift of the cavitation pressure and overall a smaller hysteresis. A conceptual model of pore-specific temperature-dependent hysteresis is proposed to qualitatively explain the results
Benchtop and bedside validation of a low-cost programmable cortical stimulator in a testbed for bi-directional brain-computer-interface research
No full textIntroduction: Bi-directional brain-computer interfaces (BD-BCI) to restore movement and sensation must achieve concurrent operation of recording and decoding of motor commands from the brain and stimulating the brain with somatosensory feedback.
Methods: A custom programmable direct cortical stimulator (DCS) capable of eliciting artificial sensorimotor response was integrated into an embedded BCI system to form a safe, independent, wireless, and battery powered testbed to explore BD-BCI concepts at a low cost. The BD-BCI stimulator output was tested in phantom brain tissue by assessing its ability to deliver electrical stimulation equivalent to an FDA-approved commercial electrical cortical stimulator. Subsequently, the stimulator was tested in an epilepsy patient with subcortical electrocorticographic (ECoG) implants covering the sensorimotor cortex to assess its ability to elicit equivalent responses as the FDA-approved counterpart. Additional safety features (impedance monitoring, artifact mitigation, and passive and active charge balancing mechanisms) were also implemeneted and tested in phantom brain tissue. Finally, concurrent operation with interleaved stimulation and BCI decoding was tested in a phantom brain as a proof-of-concept operation of BD-BCI system.
Results: The benchtop prototype BD-BCI stimulator's basic output features (current amplitude, pulse frequency, pulse width, train duration) were validated by demonstrating the output-equivalency to an FDA-approved commercial cortical electrical stimulator (R² > 0.99). Charge-neutral stimulation was demonstrated with pulse-width modulation-based correction algorithm preventing steady state voltage deviation. Artifact mitigation achieved a 64.5% peak voltage reduction. Highly accurate impedance monitoring was achieved with R² > 0.99 between measured and actual impedance, which in-turn enabled accurate charge density monitoring. An online BCI decoding accuracy of 93.2% between instructional cues and decoded states was achieved while delivering interleaved stimulation. The brain stimulation mapping via ECoG grids in an epilepsy patient showed that the two stimulators elicit equivalent responses.
Significance: This study demonstrates clinical validation of a fully-programmable electrical stimulator, integrated into an embedded BCI system. This low-cost BD-BCI system is safe and readily applicable as a testbed for BD-BCI research. In particular, it provides an all-inclusive hardware platform that approximates the limitations in a near-future implantable BD-BCI. This successful benchtop/human validation of the programmable electrical stimulator in a BD-BCI system is a critical milestone toward fully-implantable BD-BCI systems
Light Alters the NH₃ vs N₂H₄ Product Profile in Iron-catalyzed Nitrogen Reduction via Dual Reactivity from an Iron Hydrazido (Fe=NNH₂) Intermediate
No full textWhereas synthetically catalyzed nitrogen reduction (N₂R) to produce ammonia is widely studied, catalysis to instead produce hydrazine (N₂H₄) has received less attention despite its considerable mechanistic interest. Herein, we disclose that irradiation of a tris(phosphine)borane (P₃ᴮ) Fe catalyst, P₃ᴮFe⁺, significantly alters its product profile to increase N₂H₄ versus NH₃; P₃ᴮFe⁺ is otherwise known to be highly selective for NH₃. We posit a key terminal hydrazido intermediate, P₃ᴮFe=NNH₂, as selectivity-determining. Whereas its singlet ground state undergoes protonation to liberate NH₃, a low-lying triplet excited state leads to reactivity at N_α and formation of N₂H₄. Associated electrochemical and spectroscopic studies establish that N₂H₄ lies along a unique product pathway; NH3 is not produced from N₂H₄. Our findings are distinct from the canonical mechanism for hydrazine formation, which proceeds via a diazene (HN=NH) intermediate and showcase light as a tool to tailor selectivity
TsOH-catalyzed acyl migration reaction of the Bz-group: innovative assembly of various building blocks for the synthesis of saccharides
No full textWe developed an efficient method to achieve the regioselective acyl migration of benzoyl ester. In all the cases, the reactions required only the commercially available organic acid catalyst TsOH·H₂O. This method enables the benzoyl group to migrate from secondary groups to primary hydroxyl groups, or from equatorial secondary hydroxyl groups to axial hydroxyl groups. The 1,2 or 1,3 acyl migration would potentially occur via five- and six-membered cyclic ortho acid intermediates. A wide range of orthogonally protected monosaccharides, which are useful intermediates for the synthesis of natural oligosaccharides, were synthesized. Finally, to demonstrate the utility of the method, a tetrasaccharide portion from a mycobacterial cell wall polysaccharide was assembled
Ab Initio Calculations of XUV Ground and Excited States for First-Row Transition Metal Oxides
No full textTransient X-ray spectroscopies have become ubiquitous in studying photoexcited dynamics in solar energy materials due to their sensitivity to carrier occupations and local chemical or structural dynamics. The interpretation of solid-state photoexcited dynamics, however, is complicated by the core–hole perturbation and the resulting many-body dynamics. Here, an ab initio, Bethe–Salpeter equation (BSE) approach is developed that can incorporate photoexcited state effects for solid-state materials. The extreme ultraviolet (XUV) absorption spectra for the ground, photoexcited, and thermally expanded states of first row transition metal oxides─TiO₂, α-Cr₂O₃, β-MnO₂, α-Fe₂O₃, Co₃O₄, NiO, CuO, and ZnO─are calculated to demonstrate the accuracy of this approach. The theory is used to decompose the core–valence excitons into the separate components of the X-ray transition Hamiltonian for each of the transition metal oxides investigated. The decomposition provides a physical intuition about the origins of XUV spectral features as well as how the spectra will change following photoexcitation. The method is easily generalized to other K, L, M, and N edges to provide a general approach for analyzing transient X-ray absorption or reflection data
Safer at school early alert: an observational study of wastewater and surface monitoring to detect COVID-19 in elementary schools
No full textBackground. Schools are high-risk settings for SARS-CoV-2 transmission, but necessary for children's educational and social-emotional wellbeing. Previous research suggests that wastewater monitoring can detect SARS-CoV-2 infections in controlled residential settings with high levels of accuracy. However, its effective accuracy, cost, and feasibility in non-residential community settings is unknown.
Methods. The objective of this study was to determine the effectiveness and accuracy of community-based passive wastewater and surface (environmental) surveillance to detect SARS-CoV-2 infection in neighborhood schools compared to weekly diagnostic (PCR) testing. We implemented an environmental surveillance system in nine elementary schools with 1700 regularly present staff and students in southern California. The system was validated from November 2020 to March 2021.
Findings. In 447 data collection days across the nine sites 89 individuals tested positive for COVID-19, and SARS-CoV-2 was detected in 374 surface samples and 133 wastewater samples. Ninety-three percent of identified cases were associated with an environmental sample (95% CI: 88%–98%); 67% were associated with a positive wastewater sample (95% CI: 57%–77%), and 40% were associated with a positive surface sample (95% CI: 29%–52%). The techniques we utilized allowed for near-complete genomic sequencing of wastewater and surface samples.
Interpretation. Passive environmental surveillance can detect the presence of COVID-19 cases in non-residential community school settings with a high degree of accuracy
Comprehensive evaluation of shotgun metagenomics, amplicon sequencing, and harmonization of these platforms for epidemiological studies
No full textIn a large cohort of 1,772 participants from the Hispanic Community Health Study/Study of Latinos with overlapping 16SV4 rRNA gene (bacterial amplicon), ITS1 (fungal amplicon), and shotgun sequencing data, we demonstrate that 16SV4 amplicon sequencing and shotgun metagenomics offer the same level of taxonomic accuracy for bacteria at the genus level even at shallow sequencing depths. In contrast, for fungal taxa, we did not observe meaningful agreements between shotgun and ITS1 amplicon results. Finally, we show that amplicon and shotgun data can be harmonized and pooled to yield larger microbiome datasets with excellent agreement (<1% effect size variance across three independent outcomes) using pooled amplicon/shotgun data compared to pure shotgun metagenomic analysis. Thus, there are multiple approaches to study the microbiome in epidemiological studies, and we provide a demonstration of a powerful pooling approach that will allow researchers to leverage the massive amount of amplicon sequencing data generated over the last two decades
Re-ViLM: Retrieval-Augmented Visual Language Model for Zero and Few-Shot Image Captioning
No full textAugmenting pretrained language models (LMs) with a vision encoder (e.g., Flamingo) has obtained state-of-the-art results in image-to-text generation. However, these models store all the knowledge within their parameters, thus often requiring enormous model parameters to model the abundant visual concepts and very rich textual descriptions. Additionally, they are inefficient in incorporating new data, requiring a computational-expensive fine-tuning process. In this work, we introduce a Retrieval-augmented Visual Language Model, Re-ViLM, built upon the Flamingo, that supports retrieving the relevant knowledge from the external database for zero and in-context few-shot image-to-text generations. By storing certain knowledge explicitly in the external database, our approach reduces the number of model parameters and can easily accommodate new data during evaluation by simply updating the database. We also construct an interleaved image and text data that facilitates in-context few-shot learning capabilities. We demonstrate that Re-ViLM significantly boosts performance for image-to-text generation tasks, especially for zero-shot and few-shot generation in out-of-domain settings with 4 times less parameters compared with baseline methods