Search results for "EURA"
showing 10 items of 3336 documents
Changing paradigm in mild traumatic brain injury research
2016
Traumatic brain injury (TBI) is a major cause of death and disability among young adults. Recent data show that TBI affects about 1.7 million people annually in the United States (Faul and Coronado, 2015). After TBI, the primary injury produces almost irreparable brain damage. However, recent experimental studies have shown evidence for dynamic brain repair following TBI because endogenous progenitor cells may play regenerative roles in response to injuries (McGinn and Povlishock, 2015). In surviving patients, what plays a critical role in the clinical prognosis is the subsequent secondary injury; without effective treat- ment, cascades that include glutamatergic excitotoxicity and calcium …
The on-line curvilinear component analysis (onCCA) for real-time data reduction
2015
Real time pattern recognition applications often deal with high dimensional data, which require a data reduction step which is only performed offline. However, this loses the possibility of adaption to a changing environment. This is also true for other applications different from pattern recognition, like data visualization for input inspection. Only linear projections, like the principal component analysis, can work in real time by using iterative algorithms while all known nonlinear techniques cannot be implemented in such a way and actually always work on the whole database at each epoch. Among these nonlinear tools, the Curvilinear Component Analysis (CCA), which is a non-convex techni…
Using Aerial Platforms in Predicting Water Quality Parameters from Hyperspectral Imaging Data with Deep Neural Networks
2020
In near future it is assumable that automated unmanned aerial platforms are coming more common. There are visions that transportation of different goods would be done with large planes, which can handle over 1000 kg payloads. While these planes are used for transportation they could similarly be used for remote sensing applications by adding sensors to the planes. Hyperspectral imagers are one this kind of sensor types. There is need for the efficient methods to interpret hyperspectral data to the wanted water quality parameters. In this work we survey the performance of neural networks in the prediction of water quality parameters from remotely sensed hyperspectral data in freshwater basin…
A Mutually Stimulating Loop Involving Emx2 and Canonical Wnt Signalling Specifically Promotes Expansion of Occipital Cortex and Hippocampus
2005
The correct size of the different areas composing the mature cerebral cortex depends on the proper early allocation of cortical progenitors to their distinctive areal fates, as well as on appropriate subsequent tuning of their area-specific proliferation--differentiation profiles. Whereas much is known about the genetics of the former process, the molecular mechanisms regulating proliferation and differentiation rates within distinctive cortical proto-areas are still largely obscure. Here we show that a mutual stimulating loop, involving Emx2 and canonical Wnt signalling, specifically promotes expansion of the occipito-hippocampal anlage. Collapse of this loop occurring in Emx2 2/2 mutants …
Neural networks with non-uniform embedding and explicit validation phase to assess Granger causality
2015
A challenging problem when studying a dynamical system is to find the interdependencies among its individual components. Several algorithms have been proposed to detect directed dynamical influences between time series. Two of the most used approaches are a model-free one (transfer entropy) and a model-based one (Granger causality). Several pitfalls are related to the presence or absence of assumptions in modeling the relevant features of the data. We tried to overcome those pitfalls using a neural network approach in which a model is built without any a priori assumptions. In this sense this method can be seen as a bridge between model-free and model-based approaches. The experiments perfo…
Semantic and action tool knowledge in the brain: Identifying common and distinct networks.
2021
Most cognitive models of apraxia assume that impaired tool use results from a deficit occurring at the conceptual level, which contains dedicated information about tool use, namely, semantic and action tool knowledge. Semantic tool knowledge contains information about the prototypical use of familiar tools, such as function (e.g., a hammer and a mallet share the same purpose) and associative relations (e.g., a hammer goes with a nail). Action tool knowledge contains information about how to manipulate tools, such as hand posture and kinematics. The present review aimed to better understand the neural correlates of action and semantic tool knowledge, by focusing on activation, stimulation an…
Dynamic Changes in the Neurogenic Potential in the Ventricular–Subventricular Zone of Common Marmoset during Postnatal Brain Development
2020
AbstractEven after birth, neuronal production continues in the ventricular–subventricular zone (V–SVZ) and hippocampus in many mammals. The immature new neurons (“neuroblasts”) migrate and then mature at their final destination. In humans, neuroblast production and migration toward the neocortex and the olfactory bulb (OB) occur actively only for a few months after birth and then sharply decline with age. However, the precise spatiotemporal profiles and fates of postnatally born neurons remain unclear due to methodological limitations. We previously found that common marmosets, small nonhuman primates, share many features of V–SVZ organization with humans. Here, using marmosets injected wit…
Modality-specific dysfunctional neural processing of social-abstract and non-social-concrete information in schizophrenia
2021
Highlights • Social/non-social information processing in three modalities was investigated in SZ. • SZ showed reduced activation for social information only in gesture modality. • Reduced activation in SZ was observed for non-social information only in speech. • Neural Neural processing in bimodal condition is not different between patients and controls.
Blocking NMDA-receptors in the pigeon's "prefrontal" caudal nidopallium impairs appetitive extinction learning in a sign-tracking paradigm
2015
Extinction learning provides the ability to flexibly adapt to new contingencies by learning to inhibit previously acquired associations in a context-dependent manner. The neural networks underlying extinction learning were mostly studied in rodents using fear extinction paradigms. To uncover invariant properties of the neural basis of extinction learning, we employ pigeons as a model system. Since the prefrontal cortex of mammals is a key structure for extinction learning, we assessed the role of N-methyl-D-aspartate receptors (NMDARs) in the nidopallium caudolaterale, the avian functional equivalent of mammalian prefrontal cortex. Since NMDARs in prefrontal cortex have been shown to be rel…
How functional coupling between the auditory cortex and the amygdala induces musical emotion: a single case study.
2013
Music is a sound structure of remarkable acoustical and temporal complexity. Although it cannot denote specific meaning, it is one of the most potent and universal stimuli for inducing mood. How the auditory and limbic systems interact, and whether this interaction is lateralized when feeling emotions related to music, remains unclear. We studied the functional correlation between the auditory cortex (AC) and amygdala (AMY) through intracerebral recordings from both hemispheres in a single patient while she listened attentively to musical excerpts, which we compared to passive listening of a sequence of pure tones. While the left primary and secondary auditory cortices (PAC and SAC) showed …