Exploring the Influence of Energy Constraints on Liquid State Machines

Biological organisms operate under severe energy constraints but are still the most powerful computational systems that we know of. In contrast, modern AI algorithms are generally implemented on power-hungry hardware resources such as GPUs, limiting their use at the edge. This work explores the application of biologically-inspired energy constraints to spiking neural networks to better understand their effects on network dynamics and learning and to gain insight into the creation of more energy-efficient AI. Energy constraints are modeled by abstracting the role of astrocytes in metabolizing glucose and regulating the activity-driven distribution of ATP molecules to “pools” of neurons and synapses. First, energy constraints are applied to the fixed recurrent part (a.k.a. reservoir) of liquid state machines (LSM)—a type of recurrent spiking neural network—in order to analyze their effects on both the network’s computational performance and ability to learn. Energy constraints were observed to have a significant influence on the dynamics of the network based on metrics such as Lyapunov exponent and separation ratio. In several cases the energy constraints also led to an increase in the LSM’s classification accuracy (up to 6.17\% improvement over baseline) when applied to two time series classification tasks: epileptic seizure detection and gait recognition. This improvement in classification accuracy was also typically correlated with the LSM separation metric (Pearson correlation coefficient of 0.9 for seizure detection task). However, the increased classification accuracy was generally not observed in LSMs with sparse connectivity, highlighting the role of energy constrains in sparsifying the LSM’s spike activity, which could lead to real-world energy savings in hardware implementations. In addition to the fixed LSM reservoir, the impact of energy constraints was also explored in the context of unsupervised learning with spike-timing dependent plasticity (STDP). It was observed that energy constraints can have the effect of decreasing the magnitude of the update of synaptic weights by up to 72.4\%, on average, depending on factors such as the energy cost of neuron spikes and energy pool regeneration rate. Energy constraints under certain conditions were also seen to modify which input frequencies the synapses respond to, tending to attenuate or eliminate weight updates from high frequency inputs. The effects of neuronal energy constraints on STDP learning were also studied at the network level to determine their effects on classification task performance. The final part of this work attempts to co-optimize an LSM’s energy consumption and performance through reinforcement learning. A proximal policy optimization (PPO) agent is introduced into the LSM reservoir to control the level of neuronal spiking. This was done by allowing it to modify individual energy constraint parameters. The agent is rewarded based on the separation of the reservoir and additionally rewarded for the reduction of reservoir energy consumption

Introduction to Special Section on Microcosms in Ice: The Biogeochemistry of Cryoconite Holes

Cryoconite holes are small, water filled, cylindrical melt-holes on glacial ice surface. Cryoconite, \u27cold dust,\u27 refers to the thin layer of sediment at the hole bottom. The holes form from surficial sediment patches that absorbs more solar radiation than the surrounding ice and which preferentially melt into the glacier forming a cylindrical water-filled hole. These holes form on the ice-covered, as opposed to snow covered, parts of glaciers world-wide, wherever there is sufficient energy for melting. Biogeochemically, cryoconite holes are interesting because the sediment is inncoculated with biologic material, a fraction of which thrives in the cryoconite environment of near-freezing waters and limited nutrient supply. The holes are thus oases for microbial life and biologically mediated chemical reactions on otherwise relatively inert glacier surfaces. Examining the chemical evolution of waters in cryoconite holes, showing how biogeochemical processes in cryoconite holes lead to increasing concentrations of dissolved organic carbon over time, which in may enhance adsorption of solar radiation by the water, aiding the development of deeper holes. If this is true, it suggests that there are a number of complex interactions between the biology, chemistry and biology of cryoconite holes, which act in concert to maintain life on glacier surfaces

The arctic circle boundary and the Airy process

We prove that the, appropriately rescaled, boundary of the north polar region in the Aztec diamond converges to the Airy process. The proof uses certain determinantal point processes given by the extended Krawtchouk kernel. We also prove a version of Propp's conjecture concerning the structure of the tiling at the center of the Aztec diamond.Comment: Published at http://dx.doi.org/10.1214/009117904000000937 in the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org

Glaciers in Equilibrium, McMurdo Dry Valleys, Antarctica

The McMurdo Dry Valleys are a cold, dry polar desert and the alpine glaciers therein exhibit small annual and seasonal mass balances, ofte

Distributed modeling of ablation (1996–2011) and climate sensitivity on the glaciers of Taylor Valley, Antarctica

The McMurdo Dry Valleys of Antarctica host the coldest and driest ecosystem on Earth, which is acutely sensitive to the availability of water coming from glacial runoff. We modeled the spatial variability in ablation and assessed climate sensitivity of the glacier ablation zones using 16 years of meteorological and surface mass-balance observations collected in Taylor Valley. Sublimation was the primary form of mass loss over much of the ablation zones, except for near the termini where melt, primarily below the surface, dominated. Microclimates in ~10 m scale topographic basins generated melt rates up to ten times higher than over smooth glacier surfaces. In contrast, the vertical terminal cliffs on the glaciers can have higher or lower melt rates than the horizontal surfaces due to differences in incoming solar radiation. The model systematically underpredicted ablation for the final 5 years studied, possibly due to an increase of windblown sediment. Surface mass-balance sensitivity to temperature was ~−0.02 m w.e. K−1, which is among the smallest magnitudes observed globally. We also identified a high sensitivity to ice albedo, with a decrease of 0.02 having similar effects as a 1 K increase in temperature, and a complex sensitivity to wind speed

Distributed Modeling of Ablation (1996–2011) and Climate Sensitivity on the Glaciers of Taylor Valley, Antarctica

The McMurdo Dry Valleys of Antarctica host the coldest and driest ecosystem on Earth, which is acutely sensitive to the availability of water coming from glacial runoff. We modeled the spatial variability in ablation and assessed climate sensitivity of the glacier ablation zones using 16 years of meteorological and surface mass-balance observations collected in Taylor Valley. Sublimation was the primary form of mass loss over much of the ablation zones, except for near the termini where melt, primarily below the surface, dominated. Microclimates in ~10 m scale topographic basins generated melt rates up to ten times higher than over smooth glacier surfaces. In contrast, the vertical terminal cliffs on the glaciers can have higher or lower melt rates than the horizontal surfaces due to differences in incoming solar radiation. The model systematically underpredicted ablation for the final 5 years studied, possibly due to an increase of windblown sediment. Surface mass-balance sensitivity to temperature was ~−0.02 m w.e. K−1, which is among the smallest magnitudes observed globally. We also identified a high sensitivity to ice albedo, with a decrease of 0.02 having similar effects as a 1 K increase in temperature, and a complex sensitivity to wind speed

Impact and Signatures of Deglaciation on the Cryosphere, Landscape, and Habitability of Earth and Mars

Science questions can help bridge Astrobiology and Earth Science disciples around the theme of planetary deglaciation

Brief communication: Recent estimates of glacier mass loss for western North America from laser altimetry

Glaciers in western North American outside of Alaska are often overlooked in global studies because their potential to contribute to changes in sea level is small. Nonetheless, these glaciers represent important sources of freshwater, especially during times of drought. Differencing recent ICESat-2 data from a digital elevation model derived from a combination of synthetic aperture radar data (TerraSAR-X/TanDEM-X), we find that over the period 2013–2020, glaciers in western North America lost mass at a rate of 12:3+3:5 Gt yr-1. This rate is comparable to the rate of mass loss (11:71:0 Gt yr1) for the period 2018– 2022 calculated through trend analysis using ICESat-2 and Global Ecosystems Dynamics Investigation (GEDI) data