A study of animal action segmentation algorithms across supervised, unsupervised, and semi-supervised learning paradigms [0.03%]
跨监督、非监督和半监督学习范式的动物行为分割算法研究
Ari Blau,Evan S Schaffer,Neeli Mishra et al.
Ari Blau et al.
Action segmentation of behavioral videos is the process of labeling each frame as belonging to one or more discrete classes, and is a crucial component of many studies that investigate animal behavior. A wide range of algorithms exist to au...
Expressive architectures enhance interpretability of dynamics-based neural population models [0.03%]
表达性架构增强了基于动态的神经群体模型的可解释性
Andrew R Sedler,Christopher Versteeg,Chethan Pandarinath
Andrew R Sedler
Artificial neural networks that can recover latent dynamics from recorded neural activity may provide a powerful avenue for identifying and interpreting the dynamical motifs underlying biological computation. Given that neural variance alon...
Mark A Kramer
Mark A Kramer
While brain rhythms appear fundamental to brain function, why brain rhythms consistently organize into the small set of discrete frequency bands observed remains unknown. Here we propose that rhythms separated by factors of the golden ratio...
Elaine Tring,Dario L Ringach
Elaine Tring
In cat visual cortex, the response of a neural population to the linear combination of two sinusoidal gratings (a plaid) can be well approximated by a weighted sum of the population responses to the individual gratings - a property we refer...
How do we generalize? [0.03%]
我们如何做到举一反三？
Jessica Elizabeth Taylor,Aurelio Cortese,Helen C Barron et al.
Jessica Elizabeth Taylor et al.
Humans and animals are able to generalize or transfer information from previous experience so that they can behave appropriately in novel situations. What mechanisms-computations, representations, and neural systems-give rise to this remark...
Sensitivity and specificity of a Bayesian single trial analysis for time varying neural signals [0.03%]
基于贝叶斯单试验分析的时间变化神经信号的敏感性和特异性
Jeff T Mohl,Valeria C Caruso,Surya T Tokdar et al.
Jeff T Mohl et al.
We recently reported the existence of fluctuations in neural signals that may permit neurons to code multiple simultaneous stimuli sequentially across time [1]. This required deploying a novel statistical approach to permit investigation of...
Predicting Goal-directed Attention Control Using Inverse-Reinforcement Learning [0.03%]
基于逆向强化学习预测目标导向注意力控制
Gregory J Zelinsky,Yupei Chen,Seoyoung Ahn et al.
Gregory J Zelinsky et al.
Understanding how goals control behavior is a question ripe for interrogation by new methods from machine learning. These methods require large and labeled datasets to train models. To annotate a large-scale image dataset with observed sear...
Application of the hierarchical bootstrap to multi-level data in neuroscience [0.03%]
层次自助法在神经科学中的应用
Varun Saravanan,Gordon J Berman,Samuel J Sober
Varun Saravanan
A common feature in many neuroscience datasets is the presence of hierarchical data structures, most commonly recording the activity of multiple neurons in multiple animals across multiple trials. Accordingly, the measurements constituting ...
Performance of normative and approximate evidence accumulation on the dynamic clicks task [0.03%]
规范性和近似证据积累在动态点击任务中的表现
Adrian E Radillo,Alan Veliz-Cuba,Krešimir Josić et al.
Adrian E Radillo et al.
The aim of a number of psychophysics tasks is to uncover how mammals make decisions in a world that is in flux. Here we examine the characteristics of ideal and near-ideal observers in a task of this type. We ask when and how performance de...
Characterizing the nonlinear structure of shared variability in cortical neuron populations using latent variable models [0.03%]
利用潜变量模型刻画皮层神经元群体共享变化中的非线性结构
Matthew R Whiteway,Karolina Socha,Vincent Bonin et al.
Matthew R Whiteway et al.
Sensory neurons often have variable responses to repeated presentations of the same stimulus, which can significantly degrade the stimulus information contained in those responses. This information can in principle be preserved if variabili...