We have examined the effects of current and conductance noise in a single-neuron model which can generate a variety of physiologically important impulse patterns. Current noise enters the membrane equation directly while conductance noise is propagated through the activation variables. Additive Gaussian white noise which is implemented as conductance noise appears in the voltage equations as an additive and a multiplicative term. Moreover, the originally white noise is turned into colored noise. The noise correlation time is a function of the system's control parameters which may explain the different effects of current and conductance noise in different dynamic states. We have found the most significant, qualitative differences between different noise implementations in a pacemaker-like, tonic firing regime at the transition to chaotic burst discharges. This reflects a dynamic state of high physiological relevance.
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http://dx.doi.org/10.1016/j.mbs.2008.03.007 | DOI Listing |
Learn Mem
January 2025
Department of Psychology, University of California, Los Angeles, Los Angeles, California 90095, USA
Early life trauma has been shown to facilitate habitual behavior, which may predispose individuals toward perpetuating maladaptive behaviors. However, previous investigations did not account for other traumatic childhood experiences like racial/ethnic discrimination exposure, nor have they examined the interaction of trauma and habits on real-world adverse outcomes. To examine these effects, we recruited 96 young adults (20.
View Article and Find Full Text PDFJ Neurosci
January 2025
Université Paris Cité, CNRS, Integrative Neuroscience and Cognition Center, F-75006 Paris, France.
Attention is key to perception and human behavior, and evidence shows that it periodically samples sensory information (<20Hz). However, this view has been recently challenged due to methodological concerns and gaps in our understanding of the function and mechanism of rhythmic attention. Here we used an intensive ∼22-hour psychophysical protocol combined with reverse correlation analyses to infer the neural representation underlying these rhythms.
View Article and Find Full Text PDFSLAS Discov
January 2025
The Hormel Institute, University of Minnesota, Austin, MN 55912. Electronic address:
Metabolic reprogramming of purine biosynthesis is a hallmark of cancer metabolism and represents a critical vulnerability. The enzyme phosphoribosylformylglycinamidine synthase (PFAS) catalyzes the fourth step in de novo purine biosynthesis and has been demonstrated to be prognostic for survival of liver cancer. Despite the importance of this protein as a drug target, there are no known specific inhibitors of PFAS activity.
View Article and Find Full Text PDFJ Gastrointest Surg
January 2025
Ariadne Labs, Brigham and Women's Hospital, Harvard. T.H. School of Public Health, Boston, MA, 02115; Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114; Mongan Institute Center for Aging and Serious Illness, Massachusetts General Hospital, Boston, MA, 02114. Electronic address:
Background: Ostomy education and support is instrumental in surgical recovery and adaptation. We aimed to evaluate 1) challenges faced by fecal ostomy patients with colorectal cancer and 2) resources necessary for recovery.
Methods: We recruited patients 21-90 days after scheduled fecal ostomy surgery for locally advanced or metastatic colorectal cancer from a single, tertiary academic center.
Comput Med Imaging Graph
January 2025
CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China; National Key Laboratory of Kidney Diseases, Beijing 100853, China. Electronic address:
In clinical optical molecular imaging, the need for real-time high frame rates and low excitation doses to ensure patient safety inherently increases susceptibility to detection noise. Faced with the challenge of image degradation caused by severe noise, image denoising is essential for mitigating the trade-off between acquisition cost and image quality. However, prevailing deep learning methods exhibit uncontrollable and suboptimal performance with limited interpretability, primarily due to neglecting underlying physical model and frequency information.
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