Computational Models of Timing Mechanisms in the Cerebellar Granular Layer

A long-standing question in neuroscience is how the brain controls movement that requires precisely timed muscle activations. Studies using Pavlovian delay eyeblink conditioning provide good insight into this question. In delay eyeblink conditioning, which is believed to involve the cerebellum, a subject learns an interstimulus interval (ISI) between the onsets of a conditioned stimulus (CS) such as a tone and an unconditioned stimulus such as an airpuff to the eye. After a conditioning phase, the subject’s eyes automatically close or blink when the ISI time has passed after CS onset. This timing information is thought to be represented in some way in the cerebellum. Several computational models of the cerebellum have been proposed to explain the mechanisms of time representation, and they commonly point to the granular layer network. This article will review these computational models and discuss the possible computational power of the cerebellum

A Computational Mechanism for Unified Gain and Timing Control in the Cerebellum

Precise gain and timing control is the goal of cerebellar motor learning. Because the basic neural circuitry of the cerebellum is homogeneous throughout the cerebellar cortex, a single computational mechanism may be used for simultaneous gain and timing control. Although many computational models of the cerebellum have been proposed for either gain or timing control, few models have aimed to unify them. In this paper, we hypothesize that gain and timing control can be unified by learning of the complete waveform of the desired movement profile instructed by climbing fiber signals. To justify our hypothesis, we adopted a large-scale spiking network model of the cerebellum, which was originally developed for cerebellar timing mechanisms to explain the experimental data of Pavlovian delay eyeblink conditioning, to the gain adaptation of optokinetic response (OKR) eye movements. By conducting large-scale computer simulations, we could reproduce some features of OKR adaptation, such as the learning-related change of simple spike firing of model Purkinje cells and vestibular nuclear neurons, simulated gain increase, and frequency-dependent gain increase. These results suggest that the cerebellum may use a single computational mechanism to control gain and timing simultaneously

The origin of lumbar subcutaneous edema: two case reports

Since magnetic resonance imaging (MRI) is widely used to evaluate complaints of low back pain, there have been many reports of lumbar subcutaneous edema (LSE). However, the mechanism underlying its development is unknown. We herein report 2 cases that showed the reduction of LSE. These cases suggest details concerning the mechanism underlying the development of LSE. The first case was an obese 70-year-old woman with a history of chronic back pain due to lumbar canal stenosis. MRI revealed LSE extending from the level of the L2 vertebral body to the sacrum. However, LSE was reduced following weight loss due to a stomach ulcer. This case clearly indicated obesity as the cause of LSE. The second case was a nonobese 31-year-old woman with acute excruciating low back pain due to thoracolumbar fascia strain. LSE was observed at the level of the L3-L4 vertebral body. Two weeks later, her low back pain and LSE were reduced. This case suggests that the origin of LSE was impairment of the thoracolumbar fascia due to strain. We hypothesize that the mechanism underlying the development of LSE may be lymphatic or interstitial fluid pooling due to disturbance of the lumbar fascia

De Novo SCLC Transformation From KRAS G12C-Mutated Lung Adenocarcinoma With Excellent Response to Sotorasib: A Case Report

The transformation to SCLC is a known mechanism of resistance against molecularly targeted therapies. This study reports a patient with untreated lung adenocarcinoma, characterized by a KRAS G12C mutation, which transformed into SCLC before treatment. Both the adenocarcinoma and SCLC components were responsive to sotorasib