Hebbian Research Articles

Deep eutectic solvent-assisted synthesis of transition metal oxide and its integration into polymer matrix for supercapacitor

Transition metal oxide-based materials continue to attract increasing interest in energy and environmental applications due to their unique characteristics. However, their integration with polymers needs to be explored to achieve enhanced capacitance values. To address this issue, two step strategy is utilized wherein the first step involves preparation of a pristine transition metal oxide (Co3O4) is by a deep eutectic solvent (DES) consisting of choline chloride and hydrogen donor ethyelene glycol in the ratio of 2:1. In the second step the environmentally friendly high energy ball milling is utilized with strong mechanical forces producing desired poly-3-dodecyl thiophene (P3DDT)-wrapped cobalt oxide (Co3O4). The structural and morphological properties of the prepared Co3O4 and its composite (P3DDT-Co3O4) are determined by aid of X-ray diffraction (XRD) studies, Field emission scanning electron microscope (FESEM), and X-ray photoelectron spectroscopy (XPS). The synthesized Co3O4 exhibited petal-like morphology, whereas in P3DDT-Co3O4 the polymer appears to be completely wrapped on transition metal oxide. The electrochemical characteristics of electrodes were studied. The P3DDT-Co3O4 exhibited higher specific capacitance (294F/g) than pristine Co3O4 (174F/g) at a current density of 1 A/g and its retention capacity increased (96%) and then decreased (93%) over 5000 cycles in a three-electrode cell assembly. The lowest capacitance (136F/g) was obtained for P3DDT. Experimental results demonstrate that the design is suitable for upgrading favorably active electrochemical spots in Co3O4 during the incorporation of P3DDT by the ball-milling procedure, showing outstanding performance in energy-storage applications.

Realization of Multiple Synapse Plasticity by Coexistence of Volatile and Nonvolatile Characteristics of Interface Type Memristor.

Studies on neuromorphic computing systems are becoming increasingly important in the big-data-processing era as these systems are capable of energy-efficient parallel data processing and can overcome the present limitations owing to the von Neumann bottleneck. The Pt/WOx/ITO resistive random-access memory device can be used to implement versatile synapse functions because it possesses both volatile and nonvolatile characteristics. The gradual increase and decrease in the current of the Pt/WOx/ITO device with its uniform resistance state for endurance and retention enables additional synaptic applications that can be controlled using electric pulses. If the volatile and nonvolatile device properties are set through rehearsal and forgetting processes, the device can emulate various synaptic behaviors, such as potentiation and depression, paired-pulse facilitation, post-tetanic potentiation, image training, Hebbian learning rules, excitatory postsynaptic current, and Pavlov's test. Furthermore, reservoir computing can be implemented for applications such as pattern generation and recognition. This emphasizes the various applications of future neuromorphic devices, demonstrating the various favorable characteristics of pulse-enhanced Pt/WOx/ITO devices.

Dynamics of a Random Hopfield Neural Lattice Model with Adaptive Synapses and Delayed Hebbian Learning

Dynamics of a Random Hopfield Neural Lattice Model with Adaptive Synapses and Delayed Hebbian Learning

Recurrent neural networks that learn multi-step visual routines with reinforcement learning.

Many cognitive problems can be decomposed into series of subproblems that are solved sequentially by the brain. When subproblems are solved, relevant intermediate results need to be stored by neurons and propagated to the next subproblem, until the overarching goal has been completed. We will here consider visual tasks, which can be decomposed into sequences of elemental visual operations. Experimental evidence suggests that intermediate results of the elemental operations are stored in working memory as an enhancement of neural activity in the visual cortex. The focus of enhanced activity is then available for subsequent operations to act upon. The main question at stake is how the elemental operations and their sequencing can emerge in neural networks that are trained with only rewards, in a reinforcement learning setting. We here propose a new recurrent neural network architecture that can learn composite visual tasks that require the application of successive elemental operations. Specifically, we selected three tasks for which electrophysiological recordings of monkeys' visual cortex are available. To train the networks, we used RELEARNN, a biologically plausible four-factor Hebbian learning rule, which is local both in time and space. We report that networks learn elemental operations, such as contour grouping and visual search, and execute sequences of operations, solely based on the characteristics of the visual stimuli and the reward structure of a task. After training was completed, the activity of the units of the neural network elicited by behaviorally relevant image items was stronger than that elicited by irrelevant ones, just as has been observed in the visual cortex of monkeys solving the same tasks. Relevant information that needed to be exchanged between subroutines was maintained as a focus of enhanced activity and passed on to the subsequent subroutines. Our results demonstrate how a biologically plausible learning rule can train a recurrent neural network on multistep visual tasks.

Remapping and Reconnecting the Language Network after Stroke

Here, we review the literature on neurotypical individuals and individuals with post-stroke aphasia showing that right-hemisphere regions homologous to language network and other regions, like the right cerebellum, are activated in language tasks and support language even in healthy people. We propose that language recovery in post-stroke aphasia occurs largely by potentiating the right hemisphere network homologous to the language network and other networks that previously supported language to a lesser degree and by modulating connection strength between nodes of the right-hemisphere language network and undamaged nodes of the left-hemisphere language network. Based on this premise (supported by evidence we review), we propose that interventions should be aimed at potentiating the right-hemisphere language network through Hebbian learning or by augmenting connections between network nodes through neuroplasticity, such as non-invasive brain stimulation and perhaps modulation of neurotransmitters involved in neuroplasticity. We review aphasia treatment studies that have taken this approach. We conclude that further aphasia rehabilitation with this aim is justified.

Detecting material state changes in the nucleolus by label-free digital holographic microscopy.

Ribosome biogenesis is initiated in the nucleolus, a multiphase biomolecular condensate formed by liquid-liquid phase separation. The nucleolus is a powerful disease biomarker and stress biosensor whose morphology reflects function. Here we have used digital holographic microscopy (DHM), a label-free quantitative phase contrast microscopy technique, to detect nucleoli in adherent and suspension human cells. We trained convolutional neural networks to detect and quantify nucleoli automatically on DHM images. Holograms containing cell optical thickness information allowed us to define a novel index which we used to distinguish nucleoli whose material state had been modulated optogenetically by blue-light-induced protein aggregation. Nucleoli whose function had been impacted by drug treatment or depletion of ribosomal proteins could also be distinguished. We explored the potential of the technology to detect other natural and pathological condensates, such as those formed upon overexpression of a mutant form of huntingtin, ataxin-3, or TDP-43, and also other cell assemblies (lipid droplets). We conclude that DHM is a powerful tool for quantitatively characterizing nucleoli and other cell assemblies, including their material state, without any staining.

Defect chemistry engineering of Ga-doped garnet electrolyte with high stability for solid-state lithium metal batteries

Abstract Ga-doped Li7La3Zr2O12 (Ga-LLZO) has long been considered as a promising garnet-type electrolyte candidate for all-solid-state lithium metal batteries (ASSLBs) due to its high room temperature ionic conductivity. However, the typical synthesis of Ga-LLZO is usually accompanied by the formation of undesired LiGaO2 impurity phase that causes severe instability issue of electrolyte in contact with molten Li metal during half/full cells assembly. In this study, we show that by simply engineering the defect chemistry of Ga-LLZO, namely, the lithium deficiency level, LiGaO2 impurity phase is effectively inhibited in the final synthetic product. Consequently, defect chemistry engineered Ga-LLZO exhibits excellent electrochemical stability against lithium metal, while its high room temperature ionic conductivity (~1.9 × 10-3 S·cm-1) is well reserved. The assembled Li/Ga-LLZO/Li symmetric cell has a superior critical current density of 0.9 mA·cm-2, and cycles stably for 500 hours at a current density of 0.3 mA·cm-2. This research facilitates the potential commercial applications of high performance Ga-LLZO solid electrolyte in ASSLBs.

Designer peptide-DNA cytoskeletons regulate the function of synthetic cells.

The bottom-up engineering of artificial cells requires a reconfigurable cytoskeleton that can organize at distinct locations and dynamically modulate its structural and mechanical properties. Here, inspired by the vast array of actin-binding proteins and their ability to reversibly crosslink or bundle filaments, we have designed a library of peptide-DNA crosslinkers varying in length, valency and geometry. Peptide filaments conjoint through DNA hybridization give rise to tactoid-shaped bundles with tunable aspect ratios and mechanics. When confined in cell-sized water-in-oil droplets, the DNA crosslinker design guides the localization of cytoskeletal structures at the cortex or within the lumen of the synthetic cells. The tunable spatial arrangement regulates the passive diffusion of payloads within the droplets and complementary DNA handles allow for the reversible recruitment and release of payloads on and off the cytoskeleton. Heat-induced reconfiguration of peptide-DNA architectures triggers shape deformations of droplets, regulated by DNA melting temperatures. Altogether, the modular design of peptide-DNA architectures is a powerful strategy towards the bottom-up assembly of synthetic cells.

Progressive Circuit Hyperexcitability in Mouse Neocortical Slice Cultures with Increasing Duration of Activity Silencing.

Forebrain neurons deprived of activity become hyperactive when activity is restored. Rebound activity has been linked to spontaneous seizures in vivo following prolonged activity blockade. Here, we measured the time course of rebound activity and the contributing circuit mechanisms using calcium imaging, synaptic staining, and whole-cell patch clamp in organotypic slice cultures of mouse neocortex. Calcium imaging revealed hypersynchronous activity increasing in intensity with longer periods of deprivation. While activity partially recovered 3 d after slices were released from 5 d of deprivation, they were less able to recover after 10 d of deprivation. However, even after the longer period of deprivation, activity patterns eventually returned to baseline levels. The degree of deprivation-induced rebound was age-dependent, with the greatest effects occurring when silencing began in the second week. Pharmacological blockade of NMDA receptors indicated that hypersynchronous rebound activity did not require activation of Hebbian plasticity. In single-neuron recordings, input resistance roughly doubled with a concomitant increase in intrinsic excitability. Synaptic imaging of pre- and postsynaptic proteins revealed dramatic reductions in the number of presumptive synapses with a larger effect on inhibitory than excitatory synapses. Putative excitatory synapses colocalizing PSD-95 and Bassoon declined by 39 and 56% following 5 and 10 d of deprivation, but presumptive inhibitory synapses colocalizing gephyrin and VGAT declined by 55 and 73%, respectively. The results suggest that with prolonged deprivation, a progressive reduction in synapse number is accompanied by a shift in the balance between excitation and inhibition and increased cellular excitability.

An ultra energy-efficient hardware platform for neuromorphic computing enabled by 2D-TMD tunnel-FETs

Brain-like energy-efficient computing has remained elusive for neuromorphic (NM) circuits and hardware platform implementations despite decades of research. In this work we reveal the opportunity to significantly improve the energy efficiency of digital neuromorphic hardware by introducing NM circuits employing two-dimensional (2D) transition metal dichalcogenide (TMD) layered channel material-based tunnel-field-effect transistors (TFETs). Our novel leaky-integrate-fire (LIF) based digital NM circuit along with its Hebbian learning circuitry operates at a wide range of supply voltages, frequencies, and activity factors, enabling two orders of magnitude higher energy-efficient computing that is difficult to achieve with conventional material and/or device platforms, specifically the silicon-based 7 nm low-standby-power FinFET technology. Our innovative 2D-TFET based NM circuit paves the way toward brain-like energy-efficient computing that can unleash major transformations in future AI and data analytics platforms.

Cell-free Protein Synthesis System for Building Synthetic Cells.

The Cell-Free Protein Synthesis (CFPS) system has been widely employed to facilitate the bottom-up assembly of synthetic cells. It serves as the host for the core machinery of the Central Dogma, standing as an optimal chassis for the integration and assembly of diverse artificial cellular mimicry systems. Despite its frequent use in the fabrication of synthetic cells, establishing a tailored and robust CFPS system for a specific application remains a nontrivial challenge. In this methods paper, we present a comprehensive protocol for the CFPS system, routinely employed in constructing synthetic cells. This protocol encompasses key stages in the preparation of the CFPS system, including the cell extract, template preparation, and routine expression optimization utilizing a fluorescent reporter protein. Additionally, we show representative results by encapsulating the CFPS system within various micro-compartments, such as monolayer droplets, double-emulsion vesicles, and chambers situated atop supported lipid bilayers. Finally, we elucidate the critical steps and conditions necessary for the successful assembly of these CFPS systems in distinct environments. We expect that our approach will facilitate the establishment of good working practices among various laboratories within the continuously expanding synthetic cell community, thereby accelerating progress in the field of synthetic cell development.

Supramolecular Assembly in Live Cells Mapped by Real-Time Phasor-Fluorescence Lifetime Imaging.

The complex dynamics and transience of assembly pathways in living systems complicate the understanding of these molecular to nanoscale processes. Current technologies are unable to track the molecular events leading to the onset of assembly, where real-time information is imperative to correlate their rich biology. Using a chemically designed pro-assembling molecule, we map its transformation into nanofibers and their fusion with endosomes to form hollow fiber clusters. Tracked by phasor-fluorescence lifetime imaging (phasor-FLIM) in epithelial cells (L929, A549, MDA-MB 231) and correlative light-electron microscopy and tomography (CLEM), spatiotemporal splicing of the assembly events shows time-correlated metabolic dysfunction. The biological impact begins with assembly-induced endosomal disruption that reduces glucose transport into the cells, which, in turn, stymies mitochondrial respiration.

Biomarker-Driven DNA-Functionalized Colloidal Programmed Simultaneous Assembly and Disassembly in Cells.

Complex structures and devices, both natural and artificial, can often undergo assembly and disassembly. Assembly and disassembly allow multiple stimuli to initiate, for example, the assembly and disassembly of primary cilia under the control of E3 ubiquitin ligases and deubiquitinases. Although biology relies on such schemes, they are rarely available in materials science. Here, we demonstrate a DNA-functionalized colloidal Au response to endogenous biomarkers to trigger simultaneous assembly and disassembly techniques. Colloidal Au is initially inert because the starting DNA strands are paired and prehybridized. TK1 mRNA competes to bind one of the paired strands and release its complement. The released complement binds to the next colloidal Au to initiate assembly, and APE1 can shear the colloidal Au assembly binding site to initiate disassembly. Our strategy provides temporal and spatial logic control during colloidal Au assembly and disassembly, and this simultaneous assembly and disassembly process can be used for sequential detection and cellular imaging of two biomarkers, effectively reducing signal false-positive results and shortening detection time. This work highlights biomarker-controlled colloidal Au simultaneous assembly and disassembly in ways that are simple and versatile, with the potential to enrich the application scope of DNA nanotechnology and provide an idea for the application of precision medicine testing.

Porous Si/Ca-Si-O nanocomposite lithium storage materials by calciothermic reduction of Si with CaH2

Silicon monoxide (SiO)-based anode materials are one of the most intensively investigated class of materials for use as high-capacity anodes in lithium-ion batteries. However, their low initial Coulombic efficiency (ICE), resulting from the irreversible electrochemical reaction of the amorphous SiO2 (a-SiO2) phase in the SiO, restricts the wide-spread adoption of SiO-based anode materials in lithium-ion batteries. Pre-emptive formation of an irreversible phase that converts a-SiO2 to a non-reactive state with lithium prior to cell assembly has received much attention for enhancing ICE. However, this process has the drawback of not ensuring long-term cycle performance. Herein, the pre-emptive formation of irreversible phase combined with the high-energy mechanical milling (HEMM) process is proposed to simultaneously improve both the ICE and long-term cycle performance. The resulting porous Si/Ca-Si-O nanocomposite electrode exhibits an impressive ICE of 86.4 % and maintains 55 % of its capacity over 200 cycles. The key factor in the significant ICE improvement is the irreversible Ca-Si-O phase, which is formed by the calciothermic reduction of Si with CaH2. In addition, the microstructural changes induced by the HEMM process effectively mitigate the volume expansion of Si during cycling, resulting in improved long-term cycle stability.

Clathrin assemblies at a glance.

Clathrin assembles into honeycomb-like lattices at the plasma membrane but also on internal membranes, such as at the Golgi and tubular endosomes. Clathrin assemblies primarily regulate the intracellular trafficking of different cargoes, but clathrin also has non-endocytic functions in cell adhesion through interactions with specific integrins, contributes to intraluminal vesicle formation by forming flat bilayered coats on endosomes and even assembles on kinetochore k-fibers during mitosis. In this Cell Science at a Glance article and the accompanying poster, we review our current knowledge on the different types of canonical and non-canonical membrane-associated clathrin assemblies in mammalian cells, as observed by thin-section or platinum replica electron microscopy in various cell types, and discuss how the structural plasticity of clathrin contributes to its functional diversity.

Semaphorin 3A causes immune suppression by inducing cytoskeletal paralysis in tumour-specific CD8+ T cells

Semaphorin-3A (SEMA3A) functions as a chemorepulsive signal during development and can affect T cells by altering their filamentous actin (F-actin) cytoskeleton. The exact extent of these effects on tumour-specific T cells are not completely understood. Here we demonstrate that Neuropilin-1 (NRP1) and Plexin-A1 and Plexin-A4 are upregulated on stimulated CD8+ T cells, allowing tumour-derived SEMA3A to inhibit T cell migration and assembly of the immunological synapse. Deletion of NRP1 in both CD4+ and CD8+ T cells enhance CD8+ T-cell infiltration into tumours and restricted tumour growth in animal models. Conversely, over-expression of SEMA3A inhibit CD8+ T-cell infiltration. We further show that SEMA3A affects CD8+ T cell F-actin, leading to inhibition of immune synapse formation and motility. Examining a clear cell renal cell carcinoma patient cohort, we find that SEMA3A expression is associated with reduced survival, and that T-cells appear trapped in SEMA3A rich regions. Our study establishes SEMA3A as an inhibitor of effector CD8+ T cell tumour infiltration, suggesting that blocking NRP1 could improve T cell function in tumours.

Predictive coding with spiking neurons and feedforward gist signaling.

Predictive coding (PC) is an influential theory in neuroscience, which suggests the existence of a cortical architecture that is constantly generating and updating predictive representations of sensory inputs. Owing to its hierarchical and generative nature, PC has inspired many computational models of perception in the literature. However, the biological plausibility of existing models has not been sufficiently explored due to their use of artificial neurons that approximate neural activity with firing rates in the continuous time domain and propagate signals synchronously. Therefore, we developed a spiking neural network for predictive coding (SNN-PC), in which neurons communicate using event-driven and asynchronous spikes. Adopting the hierarchical structure and Hebbian learning algorithms from previous PC neural network models, SNN-PC introduces two novel features: (1) a fast feedforward sweep from the input to higher areas, which generates a spatially reduced and abstract representation of input (i.e., a neural code for the gist of a scene) and provides a neurobiological alternative to an arbitrary choice of priors; and (2) a separation of positive and negative error-computing neurons, which counters the biological implausibility of a bi-directional error neuron with a very high baseline firing rate. After training with the MNIST handwritten digit dataset, SNN-PC developed hierarchical internal representations and was able to reconstruct samples it had not seen during training. SNN-PC suggests biologically plausible mechanisms by which the brain may perform perceptual inference and learning in an unsupervised manner. In addition, it may be used in neuromorphic applications that can utilize its energy-efficient, event-driven, local learning, and parallel information processing nature.

Plasticity of Response Properties of Mouse Visual Cortex Neurons Induced by Optogenetic Tetanization In Vivo.

Heterosynaptic plasticity, along with Hebbian homosynaptic plasticity, is an important mechanism ensuring the stable operation of learning neuronal networks. However, whether heterosynaptic plasticity occurs in the whole brain in vivo, and what role(s) in brain function in vivo it could play, remains unclear. Here, we used an optogenetics approach to apply a model of intracellular tetanization, which was established and employed to study heterosynaptic plasticity in brain slices, to study the plasticity of response properties of neurons in the mouse visual cortex in vivo. We show that optogenetically evoked high-frequency bursts of action potentials (optogenetic tetanization) in the principal neurons of the visual cortex induce long-term changes in the responses to visual stimuli. Optogenetic tetanization had distinct effects on responses to different stimuli, as follows: responses to optimal and orthogonal orientations decreased, responses to null direction did not change, and responses to oblique orientations increased. As a result, direction selectivity of the neurons decreased and orientation tuning became broader. Since optogenetic tetanization was a postsynaptic protocol, applied in the absence of sensory stimulation, and, thus, without association of presynaptic activity with bursts of action potentials, the observed changes were mediated by mechanisms of heterosynaptic plasticity. We conclude that heterosynaptic plasticity can be induced in vivo and propose that it may play important homeostatic roles in operation of neural networks by helping to prevent runaway dynamics of responses to visual stimuli and to keep the tuning of neuronal responses within the range optimized for the encoding of multiple features in population activity.

Inhibiting presynaptic calcium channel motility in the auditory cortex suppresses synchronized input processing.

The emergent coherent population activity from thousands of stochastic neurons in the brain is believed to constitute a key neuronal mechanism for salient processing of external stimuli and its link to internal states like attention and perception. In the sensory cortex, functional cell assemblies are formed by recurrent excitation and inhibitory influences. The stochastic dynamics of each cell involved is largely orchestrated by presynaptic CAV2.1 voltage-gated calcium channels (VGCCs). Cav2.1 VGCCs initiate the release of neurotransmitters from the presynaptic compartment and are therefore able to add variability into synaptic transmission which can be partly explained by their mobile organization around docked vesicles. To investigate the relevance of Cav2.1 channel surface motility for the input processing in the primary auditory cortex (A1) in vivo, we make use of a new optogenetic system which allows for acute, reversable cross-linking Cav2.1 VGCCs via a photo-cross-linkable cryptochrome mutant, CRY2olig. In order to map neuronal activity across all cortical layers of the A1, we performed laminar current-source density (CSD) recordings with varying auditory stimulus sets in transgenic mice with a citrine tag on the N-terminus of the VGCCs. Clustering VGCCs suppresses overall sensory-evoked population activity, particularly when stimuli lead to a highly synchronized distribution of synaptic inputs. Our findings reveal the importance of membrane dynamics of presynaptic calcium channels for sensory encoding by dynamically adjusting network activity across a wide range of synaptic input strength.

A virtual thermometer for ultrahigh-temperature–pressure experiments in a large-volume press

Ultrahigh-temperature–pressure experiments are crucial for understanding the physical and chemical properties of matter. The recent development of boron-doped diamond (BDD) heaters has made such melting experiments possible in large-volume presses. However, estimates of temperatures above 2600 K and of the temperature distributions inside BDD heaters are not well constrained, owing to the lack of a suitable thermometer. Here, we establish a three-dimensional finite element model as a virtual thermometer to estimate the temperature and temperature field above 2600 K. The advantage of this virtual thermometer over those proposed in previous studies is that it considers both alternating and direct current heating modes, the actual sizes of cell assemblies after compression, the effects of the electrode, thermocouple and anvil, and the heat dissipation by the pressure-transmitting medium. The virtual thermometer reproduces the power–temperature relationships of ultrahigh-temperature–pressure experiments below 2600 K at press loads of 2.8–7.9 MN (∼19 to 28 GPa) within experimental uncertainties. The temperatures above 2600 K predicted by our virtual thermometer are within the uncertainty of those extrapolated from power–temperature relationships below 2600 K. Furthermore, our model shows that the temperature distribution inside a BDD heater (19–26 K/mm along the radial direction and <83 K/mm along the longitudinal direction) is more homogeneous than those inside conventional heaters such as graphite or LaCrO3 heaters (100–200 K/mm). Our study thus provides a reliable virtual thermometer for ultrahigh-temperature experiments using BDD heaters in Earth and material sciences.