Single Neuron Computation: From Dynamical System to Feature Detector
نویسندگان
چکیده
منابع مشابه
Single Neuron Computation: From Dynamical System to Feature Detector
White noise methods are a powerful tool for characterizing the computation performed by neural systems. These methods allow one to identify the feature or features that a neural system extracts from a complex input and to determine how these features are combined to drive the system's spiking response. These methods have also been applied to characterize the input-output relations of single neu...
متن کاملSingle neuron dynamics and computation.
At the single neuron level, information processing involves the transformation of input spike trains into an appropriate output spike train. Building upon the classical view of a neuron as a threshold device, models have been developed in recent years that take into account the diverse electrophysiological make-up of neurons and accurately describe their input-output relations. Here, we review ...
متن کاملstability and attraction domains of traffic equilibria in day-to-day dynamical system formulation
در این پژوهش مسئله واگذاری ترافیک را از دید سیستم های دینامیکی فرمول بندی می کنیم.فرض کرده ایم که همه فاکتورهای وابسته در طول زمان ثابت باشند و تعادل کاربر را از طریق فرایند منظم روزبه روز پیگیری کنیم.دینامیک ترافیک توسط یک نگاشت بازگشتی نشان داده می شود که تکامل سیستم در طول زمان را نشان می دهد.پایداری تعادل و دامنه جذب را توسط مطالعه ویژگی های توپولوژیکی تکامل سیستم تجزیه و تحلیل می کنیم.پاید...
Single-neuron criticality optimizes analog dendritic computation
Active dendritic branchlets enable the propagation of dendritic spikes, whose computational functions remain an open question. Here we propose a concrete function to the active channels in large dendritic trees. Modelling the input-output response of large active dendritic arbors subjected to complex spatio-temporal inputs and exhibiting non-stereotyped dendritic spikes, we find that the dendri...
متن کاملFSSD: Feature Fusion Single Shot Multibox Detector
SSD (Single Shot Multibox Detetor) is one of the best object detection algorithms with both high accuracy and fast speed. However, SSD’s feature pyramid detection method makes it hard to fuse the features from different scales. In this paper, we proposed FSSD (Feature Fusion Single Shot Multibox Detector), an enhanced SSD with a novel and lightweight feature fusion module which can improve the ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Neural Computation
سال: 2007
ISSN: 0899-7667,1530-888X
DOI: 10.1162/neco.2007.19.12.3133