851 resultados para dorsolateral prefrontal cortex
Resumo:
Our aim was to make a quantitative comparison of the response of the different visual cortical areas to selective stimulation of the two different cone-opponent pathways [long- and medium-wavelength (L/M)- and short-wavelength (S)-cone-opponent] and the achromatic pathway under equivalent conditions. The appropriate stimulus-contrast metric for the comparison of colour and achromatic sensitivity is unknown, however, and so a secondary aim was to investigate whether equivalent fMRI responses of each cortical area are predicted by stimulus contrast matched in multiples of detection threshold that approximately equates for visibility, or direct (cone) contrast matches in which psychophysical sensitivity is uncorrected. We found that the fMRI response across the two colour and achromatic pathways is not well predicted by threshold-scaled stimuli (perceptual visibility) but is better predicted by cone contrast, particularly for area V1. Our results show that the early visual areas (V1, V2, V3, VP and hV4) all have robust responses to colour. No area showed an overall colour preference, however, until anterior to V4 where we found a ventral occipital region that has a significant preference for chromatic stimuli, indicating a functional distinction from earlier areas. We found that all of these areas have a surprisingly strong response to S-cone stimuli, at least as great as the L/M response, suggesting a relative enhancement of the S-cone cortical signal. We also identified two areas (V3A and hMT+) with a significant preference for achromatic over chromatic stimuli, indicating a functional grouping into a dorsal pathway with a strong magnocellular input.
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A combined data matrix consisting of high performance liquid chromatography–diode array detector (HPLC–DAD) and inductively coupled plasma-mass spectrometry (ICP-MS) measurements of samples from the plant roots of the Cortex moutan (CM), produced much better classification and prediction results in comparison with those obtained from either of the individual data sets. The HPLC peaks (organic components) of the CM samples, and the ICP-MS measurements (trace metal elements) were investigated with the use of principal component analysis (PCA) and the linear discriminant analysis (LDA) methods of data analysis; essentially, qualitative results suggested that discrimination of the CM samples from three different provinces was possible with the combined matrix producing best results. Another three methods, K-nearest neighbor (KNN), back-propagation artificial neural network (BP-ANN) and least squares support vector machines (LS-SVM) were applied for the classification and prediction of the samples. Again, the combined data matrix analyzed by the KNN method produced best results (100% correct; prediction set data). Additionally, multiple linear regression (MLR) was utilized to explore any relationship between the organic constituents and the metal elements of the CM samples; the extracted linear regression equations showed that the essential metals as well as some metallic pollutants were related to the organic compounds on the basis of their concentrations
Resumo:
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.
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What can the statistical structure of natural images teach us about the human brain? Even though the visual cortex is one of the most studied parts of the brain, surprisingly little is known about how exactly images are processed to leave us with a coherent percept of the world around us, so we can recognize a friend or drive on a crowded street without any effort. By constructing probabilistic models of natural images, the goal of this thesis is to understand the structure of the stimulus that is the raison d etre for the visual system. Following the hypothesis that the optimal processing has to be matched to the structure of that stimulus, we attempt to derive computational principles, features that the visual system should compute, and properties that cells in the visual system should have. Starting from machine learning techniques such as principal component analysis and independent component analysis we construct a variety of sta- tistical models to discover structure in natural images that can be linked to receptive field properties of neurons in primary visual cortex such as simple and complex cells. We show that by representing images with phase invariant, complex cell-like units, a better statistical description of the vi- sual environment is obtained than with linear simple cell units, and that complex cell pooling can be learned by estimating both layers of a two-layer model of natural images. We investigate how a simplified model of the processing in the retina, where adaptation and contrast normalization take place, is connected to the nat- ural stimulus statistics. Analyzing the effect that retinal gain control has on later cortical processing, we propose a novel method to perform gain control in a data-driven way. Finally we show how models like those pre- sented here can be extended to capture whole visual scenes rather than just small image patches. By using a Markov random field approach we can model images of arbitrary size, while still being able to estimate the model parameters from the data.
Resumo:
Cation chloride cotransporters (CCCs) are critical for controlling intracellular chloride homeostasis. The CCC family is composed of four isoforms of K-Cl cotransporters (KCC1-4), two isoforms of Na-K-2Cl cotransporters (NKCC1-2), one Na-Cl cotransporter (NCC) and two the structurally related proteins with unknown function, CCC8 also known as cation-chloride cotransporter interaction protein, CIP, and CCC9. KCC2 is a neuron-specific isoform, which plays a prominent role in controlling the intracellular Cl- concentration in neurons and is responsible for producing the negative shift of GABAA responses from depolarizing to hyperpolarizing during neuronal maturation. In the present studies we first used in situ hybridization to examine the developmental expression patterns of the cation-chloride cotransporters KCC1-4 and NKCC1. We found that they display complementary expression patterns during embryonic brain development. Most interestingly, KCC2 expression in the embryonic central nervous system strictly follows neuronal maturation. In vitro data obtained from primary and organotypic neuronal cultures support this finding and revealed a temporal correlation between the expression of KCC2 and synaptogenesis. We found that KCC2 is highly expressed in filopodia and mature spines as well as dendritic shaft and investigated the role of KCC2 in spine formation by analyzing KCC2-/- neurons in vitro. Our studies revealed that KCC2 is a key factor in the maturation of dendritic spines. Interestingly, the effect of KCC2 in spine formation is not due to Cl- transport activity, but mediated through the interaction between KCC2 C-terminal and intracellular protein associated with cytoskeleton. The interacting protein we found is protein 4.1N by immunoprecipitation. Our results indicate a structural role for KCC2 in the development of functional glutamatergic synapses and suggest KCC2 as a synchronizer for the functional development of glutamatergic and GABAergic synapses in neuronal network. Studies on the regulatory mechanisms of KCC2 expression during development and plasticity revealed that synaptic activity of both the glutamatergic and GABAergic system is not required for up-regulation of KCC2 during development, whereas in acute mature hippocampal slices which undergo continuous synchronous activity induced by the absence of Mg2+ solution, KCC2 mRNA and protein expression were down-regulated in CA1 pyramidal neurons subsequently leading to a reduced capacity for neuronal Cl- extrusion. This effect is mediated by endogenous BDNF-TrkB down-stream cascades involving both Shc/FRS-2 and PLCγ-CREB signaling. BDNF mediated changes in KCC2 expression indicate that KCC2 is significantly involved in the complex mechanisms of neuronal plasticity during development and pathophysiological conditions.
Resumo:
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.
Resumo:
Background: Aims of the study were: (i) to characterise the clinical picture, immunological features and changes in brain morphology and function in patients with widespread unilateral pain and HSV-infections, and (ii) to analyse the prevalence, clinical symptoms and immunological predisposing factors of HSV-2 induced recurrent lymphocytic meningitis (RLM) in Southern Finland. Patients and methods: Patients for the studies were recruited from the Pain Clinic, and from the Department of Neurology, at Helsinki University Central Hospital. Plasma concentrations of IgM, IgA, IgG, and IgG1-4, and serum concentrations of C3, C4 were measured. Serological anti-HSV-1 and -2 antibody status was tested. C4 genotyping, HLA-A, HLA-B and HLA-DRB1 typing, MBL2 genotyping, and IgG1 and IgG3 allotyping (Gm) were performed. Clinical neurological examination, quantitative sensory testing, skin biopsy, and functional magnetic resonance imaging were also performed. Results: HSV probably has a role in the generation of a pathological pain state. Low serum IgG1 and IgG3 levels, made the patients vulnerable for recurring HSV infections. Both functional and structural changes were observed in the brain pain-processing areas in the patients: they had less pain-related activity in the insular cortices bilaterally, in the anterior cingular cortex (ACC), and in the thalamus, and the gray matter density was lower in the ACC, in the frontal and prefrontal cortices. In the meningitis studies it was shown that RLM is more common and less benign than previously reported, and that neuropathic pain is frequently present both during and after meningitis episodes. HLA-DRB1*01, HLA-B*27, and low IgG1 levels are predisposing factors for RLM. Conclusions: Patients are vulnerable to recurrent HSV infections because of subtle immunological abnormalities. HSV causes diverse clinical manifestations. First, the herpes simplex virus, or the inflammatory process triggered by it, may cause pathological widespread pain probably by activating glial cells in the CNS. In these patients, signs of alterations in the brain pain-processing areas can be demonstrated by functional brain imaging methods. Secondly, HSV-2 induced RLM is a rare complication of HSV-2 virus. The predisposing factors include low IgG1 subclass levels, HLA-DRB1*01 and HLA –B*27 genotypes. Neuropathic pain is frequently associated with RLM.
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The aim of this paper is to assess the heritability of cerebral cortex, based on measurements of grey matter (GM) thickness derived from structural MR images (sMRI). With data acquired from a large twin cohort (328 subjects), an automated method was used to estimate the cortical thickness, and EM-ICP surface registration algorithm was used to establish the correspondence of cortex across the population. An ACE model was then employed to compute the heritability of cortical thickness. Heritable cortical thickness measures various cortical regions, especially in frontal and parietal lobes, such as bilateral postcentral gyri, superior occipital gyri, superior parietal gyri, precuneus, the orbital part of the right frontal gyrus, right medial superior frontal gyrus, right middle occipital gyrus, right paracentral lobule, left precentral gyrus, and left dorsolateral superior frontal gyrus.
Resumo:
"The functional organization of auditory cortex (AC) is still poorly understood. Previous studies suggest segregation of auditory processing streams for spatial and nonspatial information located in the posterior and anterior AC, respectively (Rauschecker and Tian, 2000; Arnott et al., 2004; Lomber and Malhotra, 2008). Furthermore, previous studies have shown that active listening tasks strongly modulate AC activations (Petkov et al., 2004; Fritz et al., 2005; Polley et al., 2006). However, the task dependence of AC activations has not been systematically investigated. In the present study, we applied high-resolution functional magnetic resonance imaging of the AC and adjacent areas to compare activations during pitch discrimination and n-back pitch memory tasks that were varied parametrically in difficulty. We found that anterior AC activations were increased during discrimination but not during memory tasks, while activations in the inferior parietal lobule posterior to the AC were enhanced during memory tasks but not during discrimination. We also found that wide areas of the anterior AC and anterior insula were strongly deactivated during the pitch memory tasks. While these results are consistent with the proposition that the anterior and posterior AC belong to functionally separate auditory processing streams, our results show that this division is present also between tasks using spatially invariant sounds. Together, our results indicate that activations of human AC are strongly dependent on the characteristics of the behavioral task."
Resumo:
Shape and texture are both important properties of visual objects, but texture is relatively less understood. Here, we characterized neuronal responses to discrete textures in monkey inferotemporal (IT) cortex and asked whether they can explain classic findings in human texture perception. We focused on three classic findings on texture discrimination: 1) it can be easy or hard depending on the constituent elements; 2) it can have asymmetries, and 3) it is reduced for textures with randomly oriented elements. We recorded neuronal activity from monkey inferotemporal (IT) cortex and measured texture perception in humans for a variety of textures. Our main findings are as follows: 1) IT neurons show congruent selectivity for textures across array size; 2) textures that were easy for humans to discriminate also elicited distinct patterns of neuronal activity in monkey IT; 3) texture pairs with asymmetries in humans also exhibited asymmetric variation in firing rate across monkey IT; and 4) neuronal responses to randomly oriented textures were explained by an average of responses to homogeneous textures, which rendered them less discriminable. The reduction in discriminability of monkey IT neurons predicted the reduced discriminability in humans during texture discrimination. Taken together, our results suggest that texture perception in humans is likely based on neuronal representations similar to those in monkey IT.