The sodium-potassium pump controls the intrinsic firing of the cerebellar Purkinje neuron

In vitro, cerebellar Purkinje cells can intrinsically fire action potentials in a repeating trimodal or bimodal pattern. The trimodal pattern consists of tonic spiking, bursting, and quiescence. The bimodal pattern consists of tonic spiking and quiescence. It is unclear how these firing patterns are generated and what determines which firing pattern is selected. We have constructed a realistic biophysical Purkinje cell model that can replicate these patterns. In this model, Na+/K+ pump activity sets the Purkinje cell's operating mode. From rat cerebellar slices we present Purkinje whole cell recordings in the presence of ouabain, which irreversibly blocks the Na+/K+ pump. The model can replicate these recordings. We propose that Na+/K+ pump activity controls the intrinsic firing mode of cerbellar Purkinje cells

riverSedge Spring 1978 v.2 no.1

Gilbert Benton -- K. Wm. Eibell -- Errol Miller -- Laureen Ching -- Jessie T. Ellison -- Michael Moore -- Katharyn Machan Aal -- Gloria Hulk -- Marie Danti -- Daryl Scroggins -- Maeve Butler -- Melissa Cannon -- Emilie Glen -- L. S. Fallis -- Charles Fishman -- Bob Fauteux -- John Levin -- Barbara Crooker -- Ulf Goebel -- Jim Corder -- Louis McKee -- Donna Cobb Vogt -- Phillip Corwin.https://scholarworks.utrgv.edu/riversedge/1003/thumbnail.jp

Predicted action consequences are perceptually facilitated before cancellation

Models of action control suggest that predicted action outcomes are “cancelled” from perception, allowing agents to devote resources to more behaviorally relevant unexpected events. These models are supported by a range of findings demonstrating that expected consequences of action are perceived less intensely than unexpected events. A key assumption of these models is that the prediction is subtracted from the sensory input. This early subtraction allows preferential processing of unexpected events from the outset of movement, thereby promoting rapid initiation of corrective actions and updating of predictive models. We tested this assumption in three psychophysical experiments. Participants rated the intensity (brightness) of observed finger movements congruent or incongruent with their own movements at different timepoints after action. Across Experiments 1 and 2, evidence of cancellation—whereby congruent events appeared less bright than incongruent events—was only found 200 ms after action, whereas an opposite effect of brighter congruent percepts was observed in earlier time ranges (50 ms after action). Experiment 3 demonstrated that this interaction was not a result of response bias. These findings suggest that “cancellation” may not be the rapid process assumed in the literature, and that perception of predicted action outcomes is initially “facilitated.” We speculate that the representation of our environment may in fact be optimized via two opposing processes: The primary process facilitates perception of events consistent with predictions and thereby helps us to perceive what is more likely, but a later process aids the perception of any detected events generating prediction errors to assist model updating

Black Holes with Zero Mass

We consider the spacetimes corresponding to static Global Monopoles with interior boundaries corresponding to a Black Hole Horizon and analyze the behavior of the appropriate ADM mass as a function of the horizon radius r_H. We find that for small enough r_H, this mass is negative as in the case of the regular global monopoles, but that for large enough r_H the mass becomes positive encountering an intermediate value for which we have a Black Hole with zero ADM mass.Comment: 10 pages, 2 ps figures, REVTeX, some minor change

Finite-Size-Scaling at the Jamming Transition: Corrections to Scaling and the Correlation Length Critical Exponent

We carry out a finite size scaling analysis of the jamming transition in frictionless bi-disperse soft core disks in two dimensions. We consider two different jamming protocols: (i) quench from random initial positions, and (ii) quasistatic shearing. By considering the fraction of jammed states as a function of packing fraction for systems with different numbers of particles, we determine the spatial correlation length critical exponent $\nu\approx 1$, and show that corrections to scaling are crucial for analyzing the data. We show that earlier numerical results yielding $\nu<1$ are due to the improper neglect of these corrections.Comment: 5 pages, 4 figures -- slightly revised version as accepted for Phys. Rev. E Rapid Communication

Chaotic root-finding for a small class of polynomials

In this paper we present a new closed-form solution to a chaotic difference equation, $y_{n+1} = a_2 y_{n}^2 + a_1 y_{n} + a_0$ with coefficient $a_0 = (a_1 - 4)(a_1 + 2) / (4 a_2)$, and using this solution, show how corresponding exact roots to a special set of related polynomials of order $2^p, p \in \mathbb{N}$ with two independent parameters can be generated, for any $p$

Predictive Information: Status or Alert Information?

Previous research investigating the efficacy of predictive information for detecting and diagnosing aircraft system failures found that subjects like to have predictive information concerning when a parameter would reach an alert range. This research focused on where the predictive information should be located, whether the information should be more closely associated with the parameter information or with the alert information. Each subject saw 3 forms of predictive information: (1) none, (2) a predictive alert message, and (3) predictive information on the status display. Generally, subjects performed better and preferred to have predictive information available although the difference between status and alert predictive information was minimal. Overall, for detection and recalling what happened, status predictive information is best; however for diagnosis, alert predictive information holds a slight edge

Association between action kinematics and emotion perception across adolescence

Research with adults suggests that we interpret others’ internal states from kinematic cues, using models calibrated to our own action experiences. Changes in action production that occur during adolescence may therefore have implications for adolescents’ understanding of others. Here we examined whether, like adults, adolescents use velocity cues to determine others’ emotions, and whether any emotion perception differences would be those predicted based on differences in action production. We measured preferred walking velocity in groups of Early (11-12 years old), Middle (13-14 years old) and Late (16-18 years old) adolescents, and adults, and recorded their perception of happy, angry and sad ‘point-light walkers’. Preferred walking velocity decreased across age and ratings of emotional stimuli with manipulated velocity demonstrated that all groups used velocity cues to determine emotion. Importantly, the relative intensity ratings of different emotions also differed across development in a manner that was predicted based on the group differences in walking velocity. Further regression analyses demonstrated that emotion perception was predicted by own movement velocity, rather than age or pubertal stage per se. These results suggest that changes in action production across adolescence are indeed accompanied by corresponding changes in how emotions are perceived from velocity. These findings indicate the importance of examining differences in action production across development when interpreting differences in understanding of others

Awareness Modifies the Skill-Learning Benefits of Sleep

Behind every skilled movement lies months of practice. However, practice alone is not responsible for the acquisition of all skill; performance can improve between, not just within, practice sessions. An important principle shaping these offline improvements may be an individual's awareness of learning a new skill. New skills, such as a sequence of finger movements, can be learned unintentionally (with little awareness for the sequence, implicit learning) or intentionally (explicit learning). We measured skill in an implicit and explicit sequence-learning task before and after a 12 hr interval. This interval either did (8 p.m. to 8 a.m.) or did not (8 a.m. to 8 p.m.) include a period of sleep. Following explicit sequence learning, offline skill improvements were only observed when the 12 hr interval included sleep. This overnight improvement was correlated with the amount of NREM sleep. The same improvement could also be observed in the evening (with an interval from 8 p.m. to 8 p.m.), so it was not coupled to retesting at a particular time of day and cannot therefore be attributed to circadian factors. In contrast, in the implicit learning task, offline learning was observed regardless of whether the 12 hr interval did or did not contain a period of sleep. However, these improvements were not observed with only a 15 min interval between sessions. Therefore, the practice available within each session cannot account for these skill improvements. Instead, sufficient time is necessary for offline learning to occur. These results show a behavioral dissociation, based upon an individual's awareness for having learned a sequence of finger movements. Offline learning is sleep dependent for explicit skills but time dependent for implicit skills

Computational Efficiency of Frequency-- and Time--Domain Calculations of Extreme Mass--Ratio Binaries: Equatorial Orbits

Gravitational waveforms and fluxes from extreme mass--ratio inspirals can be computed using time--domain methods with accuracy that is fast approaching that of frequency--domain methods. We study in detail the computational efficiency of these methods for equatorial orbits of fast spinning Kerr black holes, and find the number of modes needed in either method --as functions of the orbital parameters-- in order to achieve a desired accuracy level. We then estimate the total computation time and argue that for high eccentricity orbits the time--domain approach is more efficient computationally. We suggest that in practice low--$m$ modes are computed using the frequency--domain approach, and high--$m$ modes are computed using the time--domain approach, where $m$ is the azimuthal mode number.Comment: 19 figures, 6 table