@article {65115,
	title = {Effective dimensionality reduction for visualizing neural dynamics by laplacian eigenmaps.},
	journal = {Neural Computation},
	volume = {31},
	year = {2019},
	month = {2019 Jul},
	pages = {1356-1379},
	abstract = {<p>With the development of neural recording technology, it has become possible to collect activities from hundreds or even thousands of neurons simultaneously. Visualization of neural population dynamics can help neuroscientists analyze large-scale neural activities efficiently. In this letter, Laplacian eigenmaps is applied to this task for the first time, and the experimental results show that the proposed method significantly outperforms the commonly used methods. This finding was confirmed by the systematic evaluation using nonhuman primate data, which contained the complex dynamics well suited for testing. According to our results, Laplacian eigenmaps is better than the other methods in various ways and can clearly visualize interesting biological phenomena related to neural dynamics.</p>
},
	issn = {1530-888X},
	doi = {10.1162/neco_a_01203},
	author = {Sun, G and Zhang, S and Zhang, Y and Xu, K and Zhang, Q and Zhao, T and Zheng, X}
}
@article {4982,
	title = {The concepts of {\textquoteright}sameness{\textquoteright} and {\textquoteright}difference{\textquoteright} in an insect.},
	journal = {Nature},
	volume = {410},
	year = {2001},
	month = {2001 Apr 19},
	pages = {930-3},
	abstract = {<p>Insects process and learn information flexibly to adapt to their environment. The honeybee Apis mellifera constitutes a traditional model for studying learning and memory at behavioural, cellular and molecular levels. Earlier studies focused on elementary associative and non-associative forms of learning determined by either olfactory conditioning of the proboscis extension reflex or the learning of visual stimuli in an operant context. However, research has indicated that bees are capable of cognitive performances that were thought to occur only in some vertebrate species. For example, honeybees can interpolate visual information, exhibit associative recall, categorize visual information and learn contextual information. Here we show that honeybees can form {\textquoteright}sameness{\textquoteright} and {\textquoteright}difference{\textquoteright} concepts. They learn to solve {\textquoteright}delayed matching-to-sample{\textquoteright} tasks, in which they are required to respond to a matching stimulus, and {\textquoteright}delayed non-matching-to-sample{\textquoteright} tasks, in which they are required to respond to a different stimulus; they can also transfer the learned rules to new stimuli of the same or a different sensory modality. Thus, not only can bees learn specific objects and their physical parameters, but they can also master abstract inter-relationships, such as sameness and difference.</p>
},
	keywords = {Animals, Bees, Color, Discrimination Learning, Maze Learning, Odors},
	issn = {0028-0836},
	doi = {10.1038/35073582},
	author = {Giurfa, M and Zhang, S and Jenett, A and Menzel, R and Srinivasan, M V}
}
