Dynamics of contour, object and face processing in the human visual cortex

The neural basis of visual perception can be understood only when the sequence of cortical activity underlying successful recognition is known. The early steps in this processing chain, from retina to the primary visual cortex, are highly local, and the perception of more complex shapes requires integration of the local information. In Study I of this thesis, the progression from local to global visual analysis was assessed by recording cortical magnetoencephalographic (MEG) responses to arrays of elements that either did or did not form global contours. The results demonstrated two spatially and temporally distinct stages of processing: The first, emerging 70 ms after stimulus onset around the calcarine sulcus, was sensitive to local features only, whereas the second, starting at 130 ms across the occipital and posterior parietal cortices, reflected the global configuration. To explore the links between cortical activity and visual recognition, Studies II III presented subjects with recognition tasks of varying levels of difficulty. The occipito-temporal responses from 150 ms onwards were closely linked to recognition performance, in contrast to the 100-ms mid-occipital responses. The averaged responses increased gradually as a function of recognition performance, and further analysis (Study III) showed the single response strengths to be graded as well. Study IV addressed the attention dependence of the different processing stages: Occipito-temporal responses peaking around 150 ms depended on the content of the visual field (faces vs. houses), whereas the later and more sustained activity was strongly modulated by the observers attention. Hemodynamic responses paralleled the pattern of the more sustained electrophysiological responses. Study V assessed the temporal processing capacity of the human object recognition system. Above sufficient luminance, contrast and size of the object, the processing speed was not limited by such low-level factors. Taken together, these studies demonstrate several distinct stages in the cortical activation sequence underlying the object recognition chain, reflecting the level of feature integration, difficulty of recognition, and direction of attention.

Neural stem cell characteristics affected by oncogenic pathways and in a human motoneuron disease

Neural stem cell characteristics affected by oncogenic pathways and in a human motoneuron disease Stem cells provide the self-renewing cell pool for developing or regenerating organs. The mechanisms underlying the decisions of a stem or progenitor cell to either self-renew and maintain multipotentiality or alternatively to differentiate are incompletely understood. In this thesis work, I have approached this question by investigating the role of the proto-oncogene Myc in the regulatory functions of neural progenitor cell (NPC) self-renewal, proliferation and differentiation. By using a retroviral transduction technique to create overexpression models in embryonic NPCs cultured as neurospheres, I show that activated levels of Myc increase NPC self-renewal. Furthermore, several mechanisms that regulate the activity of Myc were identified. Myc induced self-renewal is signalled through binding to the transcription factor Miz-1 as shown by the inhibited capacity of a Myc mutant (MycV394D), deficient in binding to Miz-1, to increase self-renewal in NPCs. Furthermore, overexpression of the newly identified proto-oncogene CIP2A recapitulates the effects of Myc overexpression in NPCs. Also the expression levels and in vivo expression patterns of Myc and CIP2A were linked together. CIP2A stabilizes Myc protein levels in several cancer types by inhibiting its degradation and our results suggest the same function for CIP2A in NPCs. Our results also support the conception of self-renewal and proliferation being two separately regulated cellular functions. Finally, I suggest that Myc regulates NPC self-renewal by influencing the way stem and progenitor cells react to the environmental cues that normally dictate the cellular identity of tissues containing self-renewing cells. Neurosphere cultures were also utilised in order to characterise functional defects in a human disease. Neural stem cell cultures obtained post-mortem from foetuses of lethal congenital contracture syndrome (LCCS) were used to reveal possible cell autonomous differentiation defects of patient NPCs. However, LCCS derived NPCs were able to differentiate normally in vitro although several transcriptional differences were identified by using microarray analysis. Proliferation rate of the patient NPCs was also increased as compared to NPCs of age-matched control foetuses.

Automatic Lameness Detection in a Milking Robot : Instrumentation, measurement software, algorithms for data analysis and a neural network model

The aim of this thesis is to develop a fully automatic lameness detection system that operates in a milking robot. The instrumentation, measurement software, algorithms for data analysis and a neural network model for lameness detection were developed. Automatic milking has become a common practice in dairy husbandry, and in the year 2006 about 4000 farms worldwide used over 6000 milking robots. There is a worldwide movement with the objective of fully automating every process from feeding to milking. Increase in automation is a consequence of increasing farm sizes, the demand for more efficient production and the growth of labour costs. As the level of automation increases, the time that the cattle keeper uses for monitoring animals often decreases. This has created a need for systems for automatically monitoring the health of farm animals. The popularity of milking robots also offers a new and unique possibility to monitor animals in a single confined space up to four times daily. Lameness is a crucial welfare issue in the modern dairy industry. Limb disorders cause serious welfare, health and economic problems especially in loose housing of cattle. Lameness causes losses in milk production and leads to early culling of animals. These costs could be reduced with early identification and treatment. At present, only a few methods for automatically detecting lameness have been developed, and the most common methods used for lameness detection and assessment are various visual locomotion scoring systems. The problem with locomotion scoring is that it needs experience to be conducted properly, it is labour intensive as an on-farm method and the results are subjective. A four balance system for measuring the leg load distribution of dairy cows during milking in order to detect lameness was developed and set up in the University of Helsinki Research farm Suitia. The leg weights of 73 cows were successfully recorded during almost 10,000 robotic milkings over a period of 5 months. The cows were locomotion scored weekly, and the lame cows were inspected clinically for hoof lesions. Unsuccessful measurements, caused by cows standing outside the balances, were removed from the data with a special algorithm, and the mean leg loads and the number of kicks during milking was calculated. In order to develop an expert system to automatically detect lameness cases, a model was needed. A probabilistic neural network (PNN) classifier model was chosen for the task. The data was divided in two parts and 5,074 measurements from 37 cows were used to train the model. The operation of the model was evaluated for its ability to detect lameness in the validating dataset, which had 4,868 measurements from 36 cows. The model was able to classify 96% of the measurements correctly as sound or lame cows, and 100% of the lameness cases in the validation data were identified. The number of measurements causing false alarms was 1.1%. The developed model has the potential to be used for on-farm decision support and can be used in a real-time lameness monitoring system.

N-syndecan and HB-GAM in neural migration and differentiation : Modulation of growth factor activity in brain

The juvenile sea squirt wanders through the sea searching for a suitable rock or hunk of coral to cling to and make its home for life. For this task it has a rudimentary nervous system. When it finds its spot and takes root, it doesn't need its brain any more so it eats it. It's rather like getting tenure. Daniel C. Dennett (from Consciousness Explained, 1991) The little sea squirt needs its brain for a task that is very simple and short. When the task is completed, the sea squirt starts a new life in a vegetative state, after having a nourishing meal. The little brain is more tightly structured than our massive primate brains. The number of neurons is exact, no leeway in neural proliferation is tolerated. Each neuroblast migrates exactly to the correct position, and only a certain number of connections with the right companions is allowed. In comparison, growth of a mammalian brain is a merry mess. The reason is obvious: Squirt brain needs to perform only a few, predictable functions, before becoming waste. The more mobile and complex mammals engage their brains in tasks requiring quick adaptation and plasticity in a constantly changing environment. Although the regulation of nervous system development varies between species, many regulatory elements remain the same. For example, all multicellular animals possess a collection of proteoglycans (PG); proteins with attached, complex sugar chains called glycosaminoglycans (GAG). In development, PGs participate in the organization of the animal body, like in the construction of parts of the nervous system. The PGs capture water with their GAG chains, forming a biochemically active gel at the surface of the cell, and in the extracellular matrix (ECM). In the nervous system, this gel traps inside it different molecules: growth factors and ECM-associated proteins. They regulate the proliferation of neural stem cells (NSC), guide the migration of neurons, and coordinate the formation of neuronal connections. In this work I have followed the role of two molecules contributing to the complexity of mammalian brain development. N-syndecan is a transmembrane heparan sulfate proteoglycan (HSPG) with cell signaling functions. Heparin-binding growth-associated molecule (HB-GAM) is an ECM-associated protein with high expression in the perinatal nervous system, and high affinity to HS and heparin. N-syndecan is a receptor for several growth factors and for HB-GAM. HB-GAM induces specific signaling via N-syndecan, activating c-Src, calcium/calmodulin-dependent serine protein kinase (CASK) and cortactin. By studying the gene knockouts of HB-GAM and N-syndecan in mice, I have found that HB-GAM and N-syndecan are involved as a receptor-ligand-pair in neural migration and differentiation. HB-GAM competes with the growth factors fibriblast growth factor (FGF)-2 and heparin-binding epidermal growth factor (HB-EGF) in HS-binding, causing NSCs to stop proliferation and to differentiate, and affects HB-EGF-induced EGF receptor (EGFR) signaling in neural cells during migration. N-syndecan signaling affects the motility of young neurons, by boosting EGFR-mediated cell migration. In addition, these two receptors form a complex at the surface of the neurons, probably creating a motility-regulating structure.

Differentiation of neural stem cells in fragile X syndrome

Multipotent stem cells can self-renew and give rise to multiple cell types. One type of mammalian multipotent stem cells are neural stem cells (NSC)s, which can generate neurons, astrocytes and oligodendrocytes. NSCs are likely involved in learning and memory, but their exact role in cognitive function in the developing and adult brain is unclear. We have studied properties of NSCs in fragile X syndrome (FXS), which is the most common form of inherited mental retardation. FXS is caused by the lack of functional fragile X mental retardation protein (FMRP). FMRP is involved in the regulation of postsynaptic protein synthesis in a group I metabotropic glutamate receptor 5 (mGluR5)-dependent manner. In the absence of functional FMRP, the formation of functional synapses is impaired in the forebrain which results in alterations in synaptic plasticity. In our studies, we found that FMRP-deficient NSCs generated more neurons and less glia than control NSCs. The newborn neurons derived from FMRP-deficient NSCs showed an abnormally immature morphology. Furthermore, FMRP-deficient NSCs exhibited aberrant oscillatory Ca2+ responses to glutamate, which were specifically abolished by an antagonist of the mGluR5 receptor. The data suggested alterations in glutamatergic differentiation of FMRP-deficient NSCs and were further supported by an accumulation of cells committed to glutamatergic lineage in the subventricular zone of the embryonic Fmr1-knockout (Fmr1-KO) neocortex. Postnatally, the aberrant cells likely contributed to abnormal formation of the neocortex. The findings suggested a defect in the differentiation of distinct glutamatergic mGluR5 responsive cells in the absence of functional FMRP. Furthermore, we found that in the early postnatal Fmr1-KO mouse brain, the expression of mRNA for regulator of G-protein signalling-4 (RGS4) was decreased which was in line with disturbed G-protein signalling in NSCs lacking FMRP. Brain derived neurotrophic factor (BDNF) promotes neuronal differentiation of NSCs as the absence of FMRP was shown to do. This led us to study the effect of impaired BDNF/TrkB receptor signaling on NSCs by overexpression of TrkB.T1 receptor isoform. We showed that changes in the relative expression levels of the full-length and truncated TrkB isoforms influenced the replication capacity of NSCs. After the differentiation, the overexpression of TrkB.T1 increased neuronal turnover. To summarize, FMRP and TrkB signaling are involved in normal differentiation of NSCs in the developing brain. Since NSCs might have potential for therapeutic interventions in a variety of neurological disorders, our findings may be useful in the design of pharmacological interventions in neurological disorders of learning and memory.

From neural stem cells to precursors : Molecular regulation of self-renewal and differentiation

Stem cells are responsible for tissue turnover throughout lifespan. Only highly controlled specific environment, the stem cell niche , can sustain undifferentiated stem cell-pool. The balance between maintenance and differentiation is crucial for individual s health: uncontrolled stem cell self-renewal or proliferation can lead to hyperplasia and mutations that further provoke malignant transformation of the cells. On the other hand, uninhibited differentiation may result in diminished stem cell population, which is unable to maintain tissue turnover. The mechanisms that control the switch from maintenance to differentiation in stem cells are not well known. The same mechanisms that direct the self-renewal and proliferation in normal stem cells are likely to be also involved in maintenance of cancer stem cell . Cancer stem cells exhibit stem cell like properties such as self-renewal- and differentiation capacity and they can also regenerate the tumor tissue. In this thesis, I have investigated the effect of classical oncogenes E6/E7 and c-Myc, tumor suppressors p53 and retinoblastoma (pRb) family, and vascular endothelial growth factor (VEGF) subfamily and glial cell line-derived neurothropic factor (GDNF) family ligands on behavior of embryonic neural stem cells (NSCs) and progenitors. The study includes also the characterization of cytoskeletal tumor suppressor neurofibromatosis 2 (NF2) protein merlin and ezrin-radixin-moesin (ERM) protein ezrin expression in neural progenitors cells and their progeny. This study reveals some potential mechanisms regarding to NSCs maintenance. In summary, the studied molecules are able to shift the balance either towards stem cell maintenance or differentiation; tumor suppressor p53 represses whereas E6/E7 oncogenes and c-Myc increase the proportion of self-renewing and proliferating NSCs or progenitors. The data suggests that active MEK-ERK signaling is critical for self-renewal of normal and oncogene expressing NSCs. In addition, the results indicate that expression of cytoskeletal tumor suppressor merlin and ERM protein ezrin in central nervous system (CNS) tissue and progenitors indicates their role in cell differentiation. Furthermore, the data suggests that VEGF-C a factor involved in lymphatic system development, angiogenesis, neovascularization and metastasis but also in maintenance of some neural populations in brain is a novel thropic factor for progenitors in early sympathetic nervous system (SNS). It seems that VEGF-C dose dependently through ERK-pathway supports the proliferation and survival of early sympathetic progenitor cells, and the effect is comparable to that of GDNF family ligands.

Functional imaging of peripheral vision and dorsal stream function in the human cerebral cortex

Visual information processing in brain proceeds in both serial and parallel fashion throughout various functionally distinct hierarchically organised cortical areas. Feedforward signals from retina and hierarchically lower cortical levels are the major activators of visual neurons, but top-down and feedback signals from higher level cortical areas have a modulating effect on neural processing. My work concentrates on visual encoding in hierarchically low level cortical visual areas in human brain and examines neural processing especially in cortical representation of visual field periphery. I use magnetoencephalography and functional magnetic resonance imaging to measure neuromagnetic and hemodynamic responses during visual stimulation and oculomotor and cognitive tasks from healthy volunteers. My thesis comprises six publications. Visual cortex forms a great challenge for modeling of neuromagnetic sources. My work shows that a priori information of source locations are needed for modeling of neuromagnetic sources in visual cortex. In addition, my work examines other potential confounding factors in vision studies such as light scatter inside the eye which may result in erroneous responses in cortex outside the representation of stimulated region, and eye movements and attention. I mapped cortical representations of peripheral visual field and identified a putative human homologue of functional area V6 of the macaque in the posterior bank of parieto-occipital sulcus. My work shows that human V6 activates during eye-movements and that it responds to visual motion at short latencies. These findings suggest that human V6, like its monkey homologue, is related to fast processing of visual stimuli and visually guided movements. I demonstrate that peripheral vision is functionally related to eye-movements and connected to rapid stream of functional areas that process visual motion. In addition, my work shows two different forms of top-down modulation of neural processing in the hierachically lowest cortical levels; one that is related to dorsal stream activation and may reflect motor processing or resetting signals that prepare visual cortex for change in the environment and another local signal enhancement at the attended region that reflects local feed-back signal and may perceptionally increase the stimulus saliency.

Search for the Higgs Boson Using Neural Networks in Events with Missing Energy and b-Quark Jets in pp̅ Collisions at √s=1.96 TeV

We report on a search for the standard model Higgs boson produced in association with a $W$ or $Z$ boson in $p\bar{p}$ collisions at $\sqrt{s} = 1.96$ TeV recorded by the CDF II experiment at the Tevatron in a data sample corresponding to an integrated luminosity of 2.1 fb$^{-1}$. We consider events which have no identified charged leptons, an imbalance in transverse momentum, and two or three jets where at least one jet is consistent with originating from the decay of a $b$ hadron. We find good agreement between data and predictions. We place 95% confidence level upper limits on the production cross section for several Higgs boson masses ranging from 110$\gevm$ to 150$\gevm$. For a mass of 115$\gevm$ the observed (expected) limit is 6.9 (5.6) times the standard model prediction.