Neurodegenerative diseases: molecular mechanisms and new strategies for neuroprotection

The term neurodegeneration defines numerous conditions that modify neuron’s normal functions in the human brain where is possible to observe a progressive and consistent neuronal loss. The mechanisms involved in neurodegenerative chronic and acute diseases evolution are not completely understood yet, however they share common characteristics such as misfolded proteins, oxidative stress, inflammation, excitotoxicity, and neuronal loss. Many studies have shown the frequency to develop neurodegenerative chronic diseases several years after an acute brain injury. In addition, many patients show, after a traumatic brain injury, motor and cognitive manifestations that are close to which are observed in neurodegenerative chronic patients. For this reason it is evident how is fundamental the concept of neuroprotection as a way to modulate the neurodegenerative processes evolution. Neuroinflammation, oxidative stress and the apoptotic process may be functional targets where operate to this end. Taking into account these considerations, the aim of the present study is to identify potential common pathogenetic pathways in neurodegenerative diseases using an integrated approach of preclinical studies. The goal is to delineate therapeutic strategies for the prevention of neuroinflammation, neurodegeneration and dysfunctions associated to Parkinson’s disease (PD) and cerebral ischemia. In the present study we used a murine model of PD treated with an isothiocyanate, 6-MSITC, able to quench ROS formation, restore the antioxidant GSH system, slow down the apoptotic neuronal death and counteract motor dysfunction induced by 6-OHDA. In the second study we utilized a transgenic mouse model knockout for CD36 receptor to investigate the inflammation involvement in a long term study of MCAo, which shows a better outcome after the damage induced. In conclusion, results in this study allow underlying the connection among these pathologies, and the importance of a neuroprotective strategy able to restore neurons activity where current drugs therapies have shown palliative but not healing abilities.

Deep learning for computer vision: a comparison between convolutional neural networks and hierarchical temporal memories on object recognition tasks

In recent years, Deep Learning techniques have shown to perform well on a large variety of problems both in Computer Vision and Natural Language Processing, reaching and often surpassing the state of the art on many tasks. The rise of deep learning is also revolutionizing the entire field of Machine Learning and Pattern Recognition pushing forward the concepts of automatic feature extraction and unsupervised learning in general. However, despite the strong success both in science and business, deep learning has its own limitations. It is often questioned if such techniques are only some kind of brute-force statistical approaches and if they can only work in the context of High Performance Computing with tons of data. Another important question is whether they are really biologically inspired, as claimed in certain cases, and if they can scale well in terms of "intelligence". The dissertation is focused on trying to answer these key questions in the context of Computer Vision and, in particular, Object Recognition, a task that has been heavily revolutionized by recent advances in the field. Practically speaking, these answers are based on an exhaustive comparison between two, very different, deep learning techniques on the aforementioned task: Convolutional Neural Network (CNN) and Hierarchical Temporal memory (HTM). They stand for two different approaches and points of view within the big hat of deep learning and are the best choices to understand and point out strengths and weaknesses of each of them. CNN is considered one of the most classic and powerful supervised methods used today in machine learning and pattern recognition, especially in object recognition. CNNs are well received and accepted by the scientific community and are already deployed in large corporation like Google and Facebook for solving face recognition and image auto-tagging problems. HTM, on the other hand, is known as a new emerging paradigm and a new meanly-unsupervised method, that is more biologically inspired. It tries to gain more insights from the computational neuroscience community in order to incorporate concepts like time, context and attention during the learning process which are typical of the human brain. In the end, the thesis is supposed to prove that in certain cases, with a lower quantity of data, HTM can outperform CNN.

Stimulus predictability reduces responses in primary visual cortex

In this functional magnetic resonance imaging study we tested whether the predictability of stimuli affects responses in primary visual cortex (V1). The results of this study indicate that visual stimuli evoke smaller responses in V1 when their onset or motion direction can be predicted from the dynamics of surrounding illusory motion. We conclude from this finding that the human brain anticipates forthcoming sensory input that allows predictable visual stimuli to be processed with less neural activation at early stages of cortical processing.

Elevated level of metabotropic glutamate receptor 2/3 in the prefrontal cortex in major depression

Clinical, postmortem and preclinical research strongly implicates dysregulation of glutamatergic neurotransmission in major depressive disorder (MDD). Recently, metabotropic glutamate receptors (mGluRs) have been proposed as attractive targets for the discovery of novel therapeutic approaches against depression. The aim of this study was to examine mGluR2/3 protein levels in the prefrontal cortex (PFC) from depressed subjects. In addition, to test whether antidepressants influence mGluR2/3 expression we also studied levels of mGluR2/3 in fluoxetine-treated monkeys. Postmortem human prefrontal samples containing Brodmann's area 10 (BA10) were obtained from 11 depressed and 11 psychiatrically healthy controls. Male rhesus monkeys were treated chronically with fluoxetine (dose escalated to 3mg/kg, p.o.; n=7) or placebo (n=6) for 39 weeks. The mGluR2/3 immunoreactivity was investigated using Western blot method. There was a robust (+67%) increase in the expression of the mGlu2/3 protein in the PFC of depressed subjects relative to healthy controls. The expression of mGlu2/3 was unchanged in the PFC of monkeys treated with fluoxetine. Our findings provide the first evidence that mGluR2/3 is elevated in the PFC in MDD. This observation is consistent with reports showing that mGluR2/3 antagonists exhibit antidepressant-like activity in animal models and demonstrates that these receptors are promising targets for the discovery of novel antidepressants.

Quantitative mapping of T2 using partial spoiling

Fast quantitative MRI has become an important tool for biochemical characterization of tissue beyond conventional T1, T2, and T2*-weighted imaging. As a result, steady-state free precession (SSFP) techniques have attracted increased interest, and several methods have been developed for rapid quantification of relaxation times using steady-state free precession. In this work, a new and fast approach for T2 mapping is introduced based on partial RF spoiling of nonbalanced steady-state free precession. The new T2 mapping technique is evaluated and optimized from simulations, and in vivo results are presented for human brain at 1.5 T and for human articular cartilage at 3.0 T. The range of T2 for gray and white matter was from 60 msec (for the corpus callosum) to 100 msec (for cortical gray matter). For cartilage, spatial variation in T2 was observed between deep (34 msec) and superficial (48 msec) layers, as well as between tibial (33 msec), femoral, (54 msec) and patellar (43 msec) cartilage. Excellent correspondence between T2 values derived from partially spoiled SSFP scans and the ones found with a reference multicontrast spin-echo technique is observed, corroborating the accuracy of the new method for proper T2 mapping. Finally, the feasibility of a fast high-resolution quantitative partially spoiled SSFP T2 scan is demonstrated at 7.0 T for human patellar cartilage.

LGI2 truncation causes a remitting focal epilepsy in dogs

One quadrillion synapses are laid in the first two years of postnatal construction of the human brain, which are then pruned until age 10 to 500 trillion synapses composing the final network. Genetic epilepsies are the most common neurological diseases with onset during pruning, affecting 0.5% of 2-10-year-old children, and these epilepsies are often characterized by spontaneous remission. We previously described a remitting epilepsy in the Lagotto romagnolo canine breed. Here, we identify the gene defect and affected neurochemical pathway. We reconstructed a large Lagotto pedigree of around 34 affected animals. Using genome-wide association in 11 discordant sib-pairs from this pedigree, we mapped the disease locus to a 1.7 Mb region of homozygosity in chromosome 3 where we identified a protein-truncating mutation in the Lgi2 gene, a homologue of the human epilepsy gene LGI1. We show that LGI2, like LGI1, is neuronally secreted and acts on metalloproteinase-lacking members of the ADAM family of neuronal receptors, which function in synapse remodeling, and that LGI2 truncation, like LGI1 truncations, prevents secretion and ADAM interaction. The resulting epilepsy onsets at around seven weeks (equivalent to human two years), and remits by four months (human eight years), versus onset after age eight in the majority of human patients with LGI1 mutations. Finally, we show that Lgi2 is expressed highly in the immediate post-natal period until halfway through pruning, unlike Lgi1, which is expressed in the latter part of pruning and beyond. LGI2 acts at least in part through the same ADAM receptors as LGI1, but earlier, ensuring electrical stability (absence of epilepsy) during pruning years, preceding this same function performed by LGI1 in later years. LGI2 should be considered a candidate gene for common remitting childhood epilepsies, and LGI2-to-LGI1 transition for mechanisms of childhood epilepsy remission.

Subcortical electrostimulation to identify network subserving motor control

Objectives: Recent anatomical-functional studies have transformed our understanding of cerebral motor control away from a hierarchical structure and toward parallel and interconnected specialized circuits. Subcortical electrical stimulation during awake surgery provides a unique opportunity to identify white matter tracts involved in motor control. For the first time, this study reports the findings on motor modulatory responses evoked by subcortical stimulation and investigates the cortico-subcortical connectivity of cerebral motor control. Experimental design: Twenty-one selected patients were operated while awake for frontal, insular, and parietal diffuse low-grade gliomas. Subcortical electrostimulation mapping was used to search for interference with voluntary movements. The corresponding stimulation sites were localized on brain schemas using the anterior and posterior commissures method. Principal observations: Subcortical negative motor responses were evoked in 20/21 patients, whereas acceleration of voluntary movements and positive motor responses were observed in three and five patients, respectively. The majority of the stimulation sites were detected rostral of the corticospinal tract near the vertical anterior-commissural line, and additional sites were seen in the frontal and parietal white matter. Conclusions: The diverse interferences with motor function resulting in inhibition and acceleration imply a modulatory influence of the detected fiber network. The subcortical stimulation sites were distributed veil-like, anterior to the primary motor fibers, suggesting descending pathways originating from premotor areas known for negative motor response characteristics. Further stimulation sites in the parietal white matter as well as in the anterior arm of the internal capsule indicate a large-scale fronto-parietal motor control network. Hum Brain Mapp, 2012. © 2012 Wiley Periodicals, Inc.

Marked global reduction in mGluR5 receptor binding in smokers and ex-smokers determined by [11C]ABP688 positron emission tomography

Nicotine addiction is a major public health problem, resulting in primary glutamatergic dysfunction. We measured the glutamate receptor binding in the human brain and provided direct evidence for the abnormal glutamate system in smokers. Because antagonism of the metabotropic glutamate receptor 5 (mGluR5) reduced nicotine self-administration in rats and mice, mGluR5 is suggested to be involved in nicotine addiction. mGluR5 receptor binding specifically to an allosteric site was observed by using positron emission tomography with [(11)C]ABP688. We found a marked global reduction (20.6%; P < 0.0001) in the mGluR5 distribution volume ratio (DVR) in the gray matter of 14 smokers. The most prominent reductions were found in the bilateral medial orbitofrontal cortex. Compared with 14 nonsmokers, 14 ex-smokers had global reductions in the average gray matter mGluR5 DVR (11.5%; P < 0.005), and there was a significant difference in average gray matter mGluR5 DVR between smokers and ex-smokers (9.2%; P < 0.01). Clinical variables reflecting current nicotine consumption, dependence and abstinence were not correlated with mGluR5 DVR. This decrease in mGluR5 receptor binding may be an adaptation to chronic increases in glutamate induced by chronic nicotine administration, and the decreased down-regulation seen in the ex-smokers could be due to incomplete recovery of the receptors, especially because the ex-smokers were abstinent for only 25 wk on average. These results encourage the development and testing of drugs against addiction that directly target the glutamatergic system.

Auditory motion direction encoding in auditory cortex and high-level visual cortex

The aim of this functional magnetic resonance imaging (fMRI) study was to identify human brain areas that are sensitive to the direction of auditory motion. Such directional sensitivity was assessed in a hypothesis-free manner by analyzing fMRI response patterns across the entire brain volume using a spherical-searchlight approach. In addition, we assessed directional sensitivity in three predefined brain areas that have been associated with auditory motion perception in previous neuroimaging studies. These were the primary auditory cortex, the planum temporale and the visual motion complex (hMT/V5+). Our whole-brain analysis revealed that the direction of sound-source movement could be decoded from fMRI response patterns in the right auditory cortex and in a high-level visual area located in the right lateral occipital cortex. Our region-of-interest-based analysis showed that the decoding of the direction of auditory motion was most reliable with activation patterns of the left and right planum temporale. Auditory motion direction could not be decoded from activation patterns in hMT/V5+. These findings provide further evidence for the planum temporale playing a central role in supporting auditory motion perception. In addition, our findings suggest a cross-modal transfer of directional information to high-level visual cortex in healthy humans.

Time course based artifact identification for independent components of resting-state FMRI

In functional magnetic resonance imaging (fMRI) coherent oscillations of the blood oxygen level-dependent (BOLD) signal can be detected. These arise when brain regions respond to external stimuli or are activated by tasks. The same networks have been characterized during wakeful rest when functional connectivity of the human brain is organized in generic resting-state networks (RSN). Alterations of RSN emerge as neurobiological markers of pathological conditions such as altered mental state. In single-subject fMRI data the coherent components can be identified by blind source separation of the pre-processed BOLD data using spatial independent component analysis (ICA) and related approaches. The resulting maps may represent physiological RSNs or may be due to various artifacts. In this methodological study, we propose a conceptually simple and fully automatic time course based filtering procedure to detect obvious artifacts in the ICA output for resting-state fMRI. The filter is trained on six and tested on 29 healthy subjects, yielding mean filter accuracy, sensitivity and specificity of 0.80, 0.82, and 0.75 in out-of-sample tests. To estimate the impact of clearly artifactual single-subject components on group resting-state studies we analyze unfiltered and filtered output with a second level ICA procedure. Although the automated filter does not reach performance values of visual analysis by human raters, we propose that resting-state compatible analysis of ICA time courses could be very useful to complement the existing map or task/event oriented artifact classification algorithms.

Different duration of at-risk mental state associated with neurofunctional abnormalities. A multimodal imaging study

Objectives: Neurofunctional alterations are correlates of vulnerability to psychosis, as well as of the disorder itself. How these abnormalities relate to different probabilities for later transition to psychosis is unclear. We investigated vulnerability- versus disease-related versus resilience biomarkers of psychosis during working memory (WM) processing in individuals with an at-risk mental state (ARMS). Experimental design: Patients with “first-episode psychosis” (FEP, n = 21), short-term ARMS (ARMS-ST, n = 17), long-term ARMS (ARMS-LT, n = 16), and healthy controls (HC, n = 20) were investigated with an n-back WM task. We examined functional magnetic resonance imaging (fMRI) and structural magnetic resonance imaging (sMRI) data in conjunction using biological parametric mapping (BPM) toolbox. Principal observations: There were no differences in accuracy, but the FEP and the ARMS-ST group had longer reaction times compared with the HC and the ARMS-LT group. With the 2-back > 0-back contrast, we found reduced functional activation in ARMS-ST and FEP compared with the HC group in parietal and middle frontal regions. Relative to ARMS-LT individuals, FEP patients showed decreased activation in the bilateral inferior frontal gyrus and insula, and in the left prefrontal cortex. Compared with the ARMS-LT, the ARMS-ST subjects showed reduced activation in the right inferior frontal gyrus and insula. Reduced insular and prefrontal activation was associated with gray matter volume reduction in the same area in the ARMS-LT group. Conclusions: These findings suggest that vulnerability to psychosis was associated with neurofunctional alterations in fronto-temporo-parietal networks in a WM task. Neurofunctional differences within the ARMS were related to different duration of the prodromal state and resilience factors

Orientation-selective functional magnetic resonance imaging adaptation in primary visual cortex revisited

The processing of orientations is at the core of our visual experience. Orientation selectivity in human visual cortex has been inferred from psychophysical experiments and more recently demonstrated with functional magnetic resonance imaging (fMRI). One method to identify orientation-selective responses is fMRI adaptation, in which two stimuli—either with the same or with different orientations—are presented successively. A region containing orientation-selective neurons should demonstrate an adapted response to the “same orientation” condition in contrast to the “different orientation” condition. So far, human primary visual cortex (V1) showed orientation-selective fMRI adaptation only in experimental designs using prolonged pre-adaptation periods (∼40 s) in combination with top-up stimuli that are thought to maintain the adapted level. This finding has led to the notion that orientation-selective short-term adaptation in V1 (but not V2 or V3) cannot be demonstrated using fMRI. The present study aimed at re-evaluating this question by testing three differently timed adaptation designs. With the use of a more sensitive analysis technique, we show robust orientation-selective fMRI adaptation in V1 evoked by a short-term adaptation design.

Motion standstill leads to activation of inferior parietal lobe

Previous studies on motion perception revealed motion-processing brain areas sensitive to changes in luminance and texture (low-level) and changes in salience (high-level). The present functional magnetic resonance imaging (fMRI) study focused on motion standstill. This phenomenon, occurring at fast presentation frequencies of visual moving objects that are perceived as static, has not been previously explored by neuroimaging techniques. Thirteen subjects were investigated while perceiving apparent motion at 4 Hz, at 30 Hz (motion standstill), isoluminant static and flickering stimuli, fixation cross, and blank screen, presented randomly and balanced for rapid event-related fMRI design. Blood oxygenation level-dependent (BOLD) signal in the occipito-temporal brain region MT/V5 increased during apparent motion perception. Here we could demonstrate that brain areas like the posterior part of the right inferior parietal lobule (IPL) demonstrated higher BOLD-signal during motion standstill. These findings suggest that the activation of higher-order motion areas is elicited by apparent motion at high presentation rates (motion standstill). We interpret this observation as a manifestation of an orienting reaction in IPL towards stimulus motion that might be detected but not resolved by other motion-processing areas (i.e., MT/V5).

How does spatial extent of fMRI datasets affect independent component analysis decomposition?

Spatial independent component analysis (sICA) of functional magnetic resonance imaging (fMRI) time series can generate meaningful activation maps and associated descriptive signals, which are useful to evaluate datasets of the entire brain or selected portions of it. Besides computational implications, variations in the input dataset combined with the multivariate nature of ICA may lead to different spatial or temporal readouts of brain activation phenomena. By reducing and increasing a volume of interest (VOI), we applied sICA to different datasets from real activation experiments with multislice acquisition and single or multiple sensory-motor task-induced blood oxygenation level-dependent (BOLD) signal sources with different spatial and temporal structure. Using receiver operating characteristics (ROC) methodology for accuracy evaluation and multiple regression analysis as benchmark, we compared sICA decompositions of reduced and increased VOI fMRI time-series containing auditory, motor and hemifield visual activation occurring separately or simultaneously in time. Both approaches yielded valid results; however, the results of the increased VOI approach were spatially more accurate compared to the results of the decreased VOI approach. This is consistent with the capability of sICA to take advantage of extended samples of statistical observations and suggests that sICA is more powerful with extended rather than reduced VOI datasets to delineate brain activity.