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Abstract Failure to direct axon regeneration to appropriate targets is a major barrier to restoring function after nerve injury. Development of strategies that can direct targeted regeneration of neurons such as retinal ganglion cells (RGCs) are needed to delay or reverse blindness in diseases like glaucoma. Here, we demonstrate that a new class of asymmetric, charge balanced (ACB) waveforms are effective at directing RGC axon growth, in vitro, without compromising cell viability. Unlike previously proposed direct current (DC) stimulation approaches, charge neutrality of ACB waveforms ensures the safety of stimulation while asymmetry ensures its efficacy. Furthermore, we demonstrate the relative influence of pulse amplitude and pulse width on the overall effectiveness of stimulation. This work can serve as a practical guideline for the potential deployment of electrical stimulation as a treatment strategy for nerve injury. 

A major advance in understanding learning behavior stems from experiments showing that reward learning requires dopamine inputs to striatal neurons and arises from synaptic plasticity of cortico-striatal synapses. Numerous reinforcement learning models mimic this dopamine-dependent synaptic plasticity by using the reward prediction error, which resembles dopamine neuron firing, to learn the best action in response to a set of cues. Though these models can explain many facets of behavior, reproducing some types of goal-directed behavior, such as renewal and reversal, require additional model components. Here we present a reinforcement learning model, TD2Q, which better corresponds to the basal ganglia with two Q matrices, one representing direct pathway neurons (G) and another representing indirect pathway neurons (N). Unlike previous two-Q architectures, a novel and critical aspect of TD2Q is to update the G and N matrices utilizing the temporal difference reward prediction error. A best action is selected for N and G using a softmax with a reward-dependent adaptive exploration parameter, and then differences are resolved using a second selection step applied to the two action probabilities. The model is tested on a range of multi-step tasks including extinction, renewal, discrimination; switching reward probability learning; and sequence learning. Simulations show that TD2Q produces behaviors similar to rodents in choice and sequence learning tasks, and that use of the temporal difference reward prediction error is required to learn multi-step tasks. Blocking the update rule on the N matrix blocks discrimination learning, as observed experimentally. Performance in the sequence learning task is dramatically improved with two matrices. These results suggest that including additional aspects of basal ganglia physiology can improve the performance of reinforcement learning models, better reproduce animal behaviors, and provide insight as to the role of direct- and indirect-pathway striatal neurons.

 

Abstract The absorption by neutral hydrogen in the intergalactic medium (IGM) produces the Ly α forest in the spectra of quasars. The Ly α forest absorbers have a broad distribution of neutral hydrogen column density N H I and Doppler b parameter. The narrowest Ly α absorption lines (of lowest b ) with neutral hydrogen column density above ∼10 13 cm −2 are dominated by thermal broadening, which can be used to constrain the thermal state of the IGM. Here we constrain the temperature-density relation T = T 0 ( ρ / ρ ¯ ) γ − 1 of the IGM at 1.6 < z < 3.6 by using N H I and b parameters measured from 24 high-resolution and high-signal-to-noise quasar spectra and by employing an analytic model to model the N H I -dependent low- b cutoff in the b distribution. In each N H I bin, the b cutoff is estimated using two methods, one non-parametric method from computing the cumulative b distribution and a parametric method from fitting the full b distribution. We find that the IGM temperature T 0 at the mean gas density ρ ¯ shows a peak of ∼1.5 × 10 4 K at z ∼ 2.7–2.9. At redshift higher than this, the index γ approximately remains constant, and it starts to increase toward lower redshifts. The evolution in both parameters is in good agreement with constraints from completely different approaches, which signals that He ii reionization completes around z ∼ 3. 

The two Voyager spacecraft have now been immersed in the very local interstellar medium for several years. Both spacecraft carry a plasma wave instrument capable of detecting plasma waves that yield electron density through the determination of the electron plasma frequency. Recent observations by Voyager 1 show increases in density at shocks and pressure fronts that are commensurate with increases in the magnetic field at these structures. Voyager 1 has not observed electron plasma oscillations, thought to be a signature of a nearby shock, since 2019, although Voyager 2 continues to observe these as recently as 2022 November. Voyager 1 also detects a faint thermal emission at the electron plasma frequency that shows the evolution of the plasma density as Voyager moves deeper into the medium. Here, we show the most recent observations from both Voyagers showing the increasing densities in the region upstream of the heliopause. We also investigate the fate of solar transients as they move ever deeper into the interstellar medium.

 

Abstract Recent rapid thinning of West Antarctic ice shelves are believed to be caused by intrusions of warm deep water that induce basal melting and seaward meltwater export. This study uses data from three bottom-mounted mooring arrays to show seasonal variability and local forcing for the currents moving into and out of the Dotson ice shelf cavity. A southward flow of warm, salty water had maximum current velocities along the eastern channel slope, while northward outflows of freshened ice shelf meltwater spread at intermediate depth above the western slope. The inflow correlated with the local ocean surface stress curl. At the western slope, meltwater outflows followed the warm influx along the eastern slope with a ~2–3 month delay. Ocean circulation near Dotson Ice Shelf, affected by sea ice distribution and wind, appears to significantly control the inflow of warm water and subsequent ice shelf melting on seasonal time-scales. 

Interstellar neutral atoms propagating into the heliosphere experience charge exchange with the supersonic solar wind (SW) plasma, generating ions that are picked up by the SW. These pickup ions (PUIs) constitute ∼25% of the proton number density by the time they reach the heliospheric termination shock (HTS). Preferential acceleration of PUIs at the HTS leads to a suprathermal, kappa-like PUI distribution in the heliosheath, which may be further heated in the heliosheath by traveling shocks or pressure waves. In this study, we utilize a dynamic, 3D magnetohydrodynamic model of the heliosphere to show that dynamic heating of PUIs at the HTS and in the inner heliosheath (IHS), as well as a background source of energetic neutral atoms (ENAs) from outside the heliopause, can explain the heliospheric ENA signal observed by the Interstellar Boundary Explorer (IBEX) in the Voyager 2 direction. We show that the PUI heating process at the HTS is characterized by a polytropic index larger than 5/3, likely ranging betweenγ∼ 2.3 and 2.7, depending on the time in solar cycle 24 and SW conditions. The ENA fluxes at energies >1.5 keV show large-scale behavior in time with the solar cycle and SW dynamic pressure, whereas ENAs < 1.5 keV primarily exhibit random-like fluctuations associated with SW transients affecting the IHS. We find that ≲20% of the ENAs observed at ∼0.5–6 keV come from other sources, likely from outside the heliopause as secondary ENAs. This study offers the first model replication of the intensity and evolution of IBEX-Hi ENA observations from the outer heliosphere.

 

The Sun emits a stream of charged particles called the solar wind, which is the primary driver of space weather and geomagnetic disturbances. Modeling and observations complement each other to help us identify and understand the physical processes governing the solar wind dynamics on different scales. Numerical models of the solar wind have greatly improved in recent years with advances in computational infrastructure and by employing data-driven or data-assimilative approaches. Designed primarily for modeling the partially ionized space plasma using adaptive mesh refinement technique on Cartesian or spherical grids, the Multi-scale Fluid-kinetic Simulation Suite (MS-FLUKSS) is arguably one of the most sophisticated numerical codes for simulating the solar wind flow. To inform potential users and interested members of the space weather community, we present a brief summary of the current state of the solar wind models developed in the MS-FLUKSS framework, with an emphasis on the 3D heliospheric MHD models driven and constrained by remote/in situ observations and empirical coronal models such as the Wang-Sheeley-Arge model. We also discuss potential scientific and operational applications of our solar wind models on prediction of space weather (e.g., high speed streams, coronal mass ejections, and interplanetary shocks) throughout the solar system.