Search results for "Neural"

Learning to Navigate in the Gaussian Mixture Surface

2021

In the last years, deep learning models have achieved remarkable generalization capability on computer vision tasks, obtaining excellent results in fine-grained classification problems. Sophisticated approaches based-on discriminative feature learning via patches have been proposed in the literature, boosting the model performances and achieving the state-of-the-art over well-known datasets. Cross-Entropy (CE) loss function is commonly used to enhance the discriminative power of the deep learned features, encouraging the separability between the classes. However, observing the activation map generated by these models in the hidden layer, we realize that many image regions with low discrimin…

Sudden sensorineural hearing loss as prodromal symptom of anterior inferior cerebellar artery infarction.

2011

Sudden sensorineural hearing loss is a clinical condition characterized by a sudden onset of unilateral or bilateral hearing loss. In recent years sudden deafness has been frequently described in association with anterior inferior cerebellar artery (AICA) infarction generally presenting along with other brainstem and cerebellar signs such as ataxia, dysmetria and peripheral facial palsy. The authors report a rare clinical case of a 53-year-old man who suddenly developed hearing loss and tinnitus without any brainstem or cerebellar signs. Computed tomography of his brain was normal, and the audiological results localized the lesion causing deafness to the inner ear. Surprisingly, magnetic re…

Deficient Interhemispheric Connectivity Underlies Movement Irregularities in Parkinson’s Disease

2021

Background: Movement execution is impaired in patients with Parkinson’s disease. Evolving neurodegeneration leads to altered connectivity between distinct regions of the brain and altered activity at interconnected areas. How connectivity alterations influence complex movements like drawing spirals in Parkinson’s disease patients remains largely unexplored. Objective: We investigated whether deteriorations in interregional connectivity relate to impaired execution of drawing. Methods: Twenty-nine patients and 31 age-matched healthy control participants drew spirals with both hands on a digital graphics tablet, and the regularity of drawing execution was evaluated by sample entropy. We recor…

Bipolar disorder: A neural network perspective on a disorder of emotion and motivation

2013

Bipolar disorder (BD) is a severe, chronic disease with a heritability of 60-80%. BD is frequently misdiagnosed due to phenomenological overlap with other psychopathologies, an important issue that calls for the identification of biological and psychological vulnerability and disease markers. Altered structural and functional connectivity, mainly between limbic and prefrontal brain areas, have been proposed to underlie emotional and motivational dysregulation in BD and might represent relevant vulnerability and disease markers. In the present laboratory review we discuss functional and structural neuroimaging findings on emotional and motivational dysregulation from our research group in BD…

Fear Network Unresponsiveness in Women with Anorexia Nervosa

2018

Expectation of sensory stimulation modulates brain activation during visual motion stimulation.

2005

The differential effects of visual hemifield motion stimulation during fixation of a stationary target were compared under two conditions: fixation straight ahead without any further instructions and fixation straight ahead with attention shifted to the "dark hemifield." Data from nine right-handed volunteers revealed that striate and extrastriate right hemispheric visual areas exhibited larger activations during left hemifield motion stimulation when attention was shifted to the right dark hemifield. Montreal Neurological Institute (MNI) coordinates (26, -98, -4) of the additional clusters activated in the latter condition corresponded best to the kinetic occipital region, which is known t…

Stably BDNF-GFP expressing embryonic stem cells exhibit a BDNF release-dependent enhancement of neuronal differentiation

2013

Brain-derived neurotrophic factor (BDNF) is known to be a crucial regulator of neuronal survival and synaptic plasticity in the mammalian brain. Furthermore, BDNF positively influences differentiation of embryonic neural precursors as well as of neural stem cells from adult neurogenic niches. To study the impact of cell-released BDNF on neural differentiation of embryonic stem cells (ESCs), which represent an attractive source for cell transplantation studies, we have generated BDNF-GFP overexpressing mouse ESC clones by knock-in technology. After neural differentiation in vitro, we observed that BDNF-GFP overexpressing ESC clones gave rise to an increased number of neurons as compared to c…

The CB1 cannabinoid receptor signals striatal neuroprotection via a PI3K/Akt/mTORC1/BDNF pathway

2015

The CB1 cannabinoid receptor, the main molecular target of endocannabinoids and cannabis active components, is the most abundant G protein-coupled receptor in the mammalian brain. In particular, the CB1 receptor is highly expressed in the basal ganglia, mostly on terminals of medium-sized spiny neurons, where it plays a key neuromodulatory function. The CB1 receptor also confers neuroprotection in various experimental models of striatal damage. However, the assessment of the physiological relevance and therapeutic potential of the CB1 receptor in basal ganglia-related diseases is hampered, at least in part, by the lack of knowledge of the precise mechanism of CB1 receptor neuroprotective ac…

Dissimilarity Application for Medical Imaging Classification

2005

In the traditional way of learning from examples of objects the classifiers are built in a feature space. However, alternative ways can be found by constructing decision rules on dissimilarity (distance) representations. In such a recognition process a new object is described by its distances to (a subset of) die training samples. The use of the dissimilarities is especially of interest when features are difficult to obtain or when they have a little discriminative power. Purpose of this work is the development of an automatic classification system which could be useful for radiologists in the investigation of breast cancer. The software has been designed in the framework of the MAGIC-5 col…

To Assess the Validity of the Transfer Function Method: A Neural Model for the Optimal Choice of Conduction Transfer Functions

2010

This paper presents a new mathematical approach applied to the Conduction Transfer Functions (CTFs) of a multilayered wall to predict the reliability of building simula- tions based upon them. Such a procedure can be used to develop a decision support system that identifies the best condition to calculate the best CTFs set. This is a critical point at the core of ASHRAE calculation methodology founded on the Transfer Function Method (TFM). To evaluate the perfor- mance of different CTFs sets, the authors built a large amount of data, subsequently employed to train a Neural Network Classifier (NNC) able to predict the reliability of a simulation without performing it. For this purpose all th…