Search results for "Neural coding"
showing 7 items of 7 documents
A Basis Set of Elementary Operations Captures Recombination of Neocortical Cell Assemblies During Basal Conditions and Learning
2019
Cell assemblies — subgroups within neuronal networks — are believed to serve as functional entities underlying cognitive capabilities such as categorical perception or memory formation and storage. However, little is known about their long-term dynamics. Using chronic in vivo calcium imaging in the mouse auditory cortex, we find that cell assemblies undergo continuous recombination, even under behaviorally stable conditions. We identify a basis set of elementary operations capturing the dynamics of cell assemblies, which involve plasticity of both the stimulus tuning of particular assemblies as well as the cellular composition of an assembly. Auditory fear conditioning introduces biases in …
Single neuron binding properties and the magical number 7
2008
When we observe a scene, we can almost instantly recognize a familiar object or can quickly distinguish among objects differing by apparently minor details. Individual neurons in the medial temporal lobe of humans have been shown to be crucial for the recognition process, and they are selectively activated by different views of known individuals or objects. However, how single neurons could implement such a sparse and explicit code is unknown and almost impossible to investigate experimentally. Hippocampal CA1 pyramidal neurons could be instrumental in this process. Here, in an extensive series of simulations with realistic morphologies and active properties, we demonstrate how n radial (ob…
Discrimination of retinal images containing bright lesions using sparse coded features and SVM
2015
Diabetic Retinopathy (DR) is a chronic progressive disease of the retinal microvasculature which is among the major causes of vision loss in the world. The diagnosis of DR is based on the detection of retinal lesions such as microaneurysms, exudates and drusen in retinal images acquired by a fundus camera. However, bright lesions such as exudates and drusen share similar appearances while being signs of different diseases. Therefore, discriminating between different types of lesions is of interest for improving screening performances. In this paper, we propose to use sparse coding techniques for retinal images classification. In particular, we are interested in discriminating between retina…
Classification of Melanoma Lesions Using Sparse Coded Features and Random Forests
2016
International audience; Malignant melanoma is the most dangerous type of skin cancer, yet it is the most treatable kind of cancer, conditioned by its early diagnosis which is a challenging task for clinicians and dermatologists. In this regard, CAD systems based on machine learning and image processing techniques are developed to differentiate melanoma lesions from benign and dysplastic nevi using dermoscopic images. Generally, these frameworks are composed of sequential processes: pre-processing, segmentation, and classification. This architecture faces mainly two challenges: (i) each process is complex with the need to tune a set of parameters, and is specific to a given dataset; (ii) the…
Music and Action
2013
Music performance includes planning, initiation, execution, monitoring, and correction of actions. This makes music performance a valuable tool for the study of human action and its neural correlates. This chapter reports action-related processes evoked by the perception of actions, and processes of error correction during music performance. Neuroscientific studies showed that, during the perception of action, neural systems are active that are also active during the performance of such actions. This supports the "common coding principle" stating that the late stages of perception and the early stages of action share a common representational format (such as the same neural code). Studies o…
Working memory performance is tied to stimulus complexity
2021
1. Summary Working memory is the cognitive capability to maintain and process information over short periods. Recent behavioral and computational studies have shown that increased visual information of the presented stimulus material is associated with enhanced working memory performance. However, the underlying neural correlates of this association are unknown. To identify how stimuli of different visual information levels affect working memory performance, we conducted behavioral experiments and single unit recordings in the avian analog of the prefrontal cortex, the nidopallium caudolaterale (NCL). On the behavioral level, we confirmed that feature-rich complex stimuli demonstrated highe…
Topology Inference and Signal Representation Using Dictionary Learning
2019
This paper presents a Joint Graph Learning and Signal Representation algorithm, called JGLSR, for simultaneous topology learning and graph signal representation via a learned over-complete dictionary. The proposed algorithm alternates between three main steps: sparse coding, dictionary learning, and graph topology inference. We introduce the “transformed graph” which can be considered as a projected graph in the transform domain spanned by the dictionary atoms. Simulation results via synthetic and real data show that the proposed approach has a higher performance when compared to the well-known algorithms for joint undirected graph topology inference and signal representation, when there is…