Repetitive transcranial magnetic stimulation improve tinnitus in normal hearing patients: a double-blind controlled, clinical and neuroimaging outcome study

Background and purpose: Tinnitus is a frequent disorder which is very difficult to treat and there is compelling evidence that tinnitus is associated with functional alterations in the central nervous system. Targeted modulation of tinnitus-related cortical activity has been proposed as a promising new treatment approach. We aimed to investigate both immediate and long-term effects of low frequency (1 Hz) repetitive transcranial magnetic stimulation (rTMS) in patients with tinnitus and normal hearing. Methods: Using a parallel design, 20 patients were randomized to receive either active or placebo stimulation over the left temporoparietal cortex for five consecutive days. Treatment results were assessed by using the Tinnitus Handicap Inventory. Ethyl cysteinate dimmer-single photon emission computed tomography (SPECT) imaging was performed before and 14 days after rTMS. Results: After active rTMS there was significant improvement of the tinnitus score as compared to sham rTMS for up to 6 months after stimulation. SPECT measurements demonstrated a reduction of metabolic activity in the inferior left temporal lobe after active rTMS. Conclusion: These results support the potential of rTMS as a new therapeutic tool for the treatment of chronic tinnitus, by demonstrating a significant reduction of tinnitus complaints over a period of at least 6 months and significant reduction of neural activity in the inferior temporal cortex, despite the stimulation applied on the superior temporal cortex.

Depression in Parkinson`s disease: Convergence from voxel-based morphometry and functional magnetic resonance imaging in the limbic thalamus

Depression is the most frequent psychiatric disorder in Parkinson`s disease (PD). Although evidence Suggests that depression in PD is related to the degenerative process that underlies the disease, further studies are necessary to better understand the neural basis of depression in this population of patients. In order to investigate neuronal alterations underlying the depression in PD, we studied thirty-six patients with idiopathic PD. Twenty of these patients had the diagnosis of major depression disorder and sixteen did not. The two groups were matched for PD motor severity according to Unified Parkinson Disease Rating Scale (UPDRS). First we conducted a functional magnetic resonance imaging (fMRI) using an event-related parametric emotional perception paradigm with test retest design. Our results showed decreased activation in the left mediodorsal (MD) thalamus and in medial prefrontall cortex in PD patients with depression compared to those without depression. Based upon these results and the increased neuron count in MD thalamus found in previous studies, we conducted a region of interest (ROI) guided voxel-based morphometry (VBM) study comparing the thalamic volume. Our results showed an increased volume in mediodorsal thalamic nuclei bilaterally. Converging morphological changes and functional emotional processing in mediodorsal thalamus highlight the importance of limbic thalamus in PD depression. In addition this data supports the link between neurodegenerative alterations and mood regulation. (C) 2009 Elsevier Inc. All rights reserved.

Improved detection of incipient vascular changes by a biotechnological platform combining post mortem MRI in situ with neuropathology

The histopathological counterpart of white matter hyperintensities is a matter of debate. Methodological and ethical limitations have prevented this question to be elucidated. We want to introduce a protocol applying state-of-the-art methods in order to solve fundamental questions regarding the neuroimaging-neuropathological uncertainties comprising the most common white matter hyperintensities [WMHs] seen in aging. By this protocol, the correlation between signal features in in situ, post mortem MRI-derived methods, including DTI and MTR and quantitative and qualitative histopathology can be investigated. We are mainly interested in determining the precise neuroanatomical substrate of incipient WMHs. A major issue in this protocol is the exact co-registration of small lesion in a tridimensional coordinate system that compensates tissue deformations after histological processing. The protocol is based on four principles: post mortem MRI in situ performed in a short post mortem interval, minimal brain deformation during processing, thick serial histological sections and computer-assisted 3D reconstruction of the histological sections. This protocol will greatly facilitate a systematic study of the location, pathogenesis, clinical impact, prognosis and prevention of WMHs. (C) 2009 Elsevier B.V. All rights reserved.

Hyperdopaminergia and NMDA Receptor Hypofunction Disrupt Neural Phase Signaling

Neural phase signaling has gained attention as a putative coding mechanism through which the brain binds the activity of neurons across distributed brain areas to generate thoughts, percepts, and behaviors. Neural phase signaling has been shown to play a role in various cognitive processes, and it has been suggested that altered phase signaling may play a role in mediating the cognitive deficits observed across neuropsychiatric illness. Here, we investigated neural phase signaling in two mouse models of cognitive dysfunction: mice with genetically induced hyperdopaminergia [dopamine transporter knock-out (DAT-KO) mice] and mice with genetically induced NMDA receptor hypofunction [NMDA receptor subunit-1 knockdown (NR1-KD) mice]. Cognitive function in these mice was assessed using a radial-arm maze task, and local field potentials were recorded from dorsal hippocampus and prefrontal cortex as DAT-KO mice, NR1-KD mice, and their littermate controls engaged in behavioral exploration. Our results demonstrate that both DAT-KO and NR1-KD mice display deficits in spatial cognitive performance. Moreover, we show that persistent hyperdopaminergia alters interstructural phase signaling, whereas NMDA receptor hypofunction alters interstructural and intrastructural phase signaling. These results demonstrate that dopamine and NMDA receptor dependent glutamate signaling play a critical role in coordinating neural phase signaling, and encourage further studies to investigate the role that deficits in phase signaling play in mediating cognitive dysfunction.

Evaluating SVM and MLDA in the extraction of discriminant regions for mental state prediction

Pattern recognition methods have been successfully applied in several functional neuroimaging studies. These methods can be used to infer cognitive states, so-called brain decoding. Using such approaches, it is possible to predict the mental state of a subject or a stimulus class by analyzing the spatial distribution of neural responses. In addition it is possible to identify the regions of the brain containing the information that underlies the classification. The Support Vector Machine (SVM) is one of the most popular methods used to carry out this type of analysis. The aim of the current study is the evaluation of SVM and Maximum uncertainty Linear Discrimination Analysis (MLDA) in extracting the voxels containing discriminative information for the prediction of mental states. The comparison has been carried out using fMRI data from 41 healthy control subjects who participated in two experiments, one involving visual-auditory stimulation and the other based on bimanual fingertapping sequences. The results suggest that MLDA uses significantly more voxels containing discriminative information (related to different experimental conditions) to classify the data. On the other hand, SVM is more parsimonious and uses less voxels to achieve similar classification accuracies. In conclusion, MLDA is mostly focused on extracting all discriminative information available, while SVM extracts the information which is sufficient for classification. (C) 2009 Elsevier Inc. All rights reserved.

An fMRI Normative Database for Connectivity Networks Using One-Class Support Vector Machines

The application of functional magnetic resonance imaging (fMRI) in neuroscience studies has increased enormously in the last decade. Although primarily used to map brain regions activated by specific stimuli, many studies have shown that fMRI can also be useful in identifying interactions between brain regions (functional and effective connectivity). Despite the widespread use of fMRI as a research tool, clinical applications of brain connectivity as studied by fMRI are not well established. One possible explanation is the lack of normal pattern, and intersubject variability-two variables that are still largely uncharacterized in most patient populations of interest. In the current study, we combine the identification of functional connectivity networks extracted by using Spearman partial correlation with the use of a one-class support vector machine in order construct a normative database. An application of this approach is illustrated using an fMRI dataset of 43 healthy Subjects performing a visual working memory task. In addition, the relationships between the results obtained and behavioral data are explored. Hum Brain Mapp 30:1068-1076, 2009. (C) 2008 Wiley-Liss. Inc.

Hyperplane navigation: A method to set individual scores in fMRI group datasets

Recent studies have demonstrated that spatial patterns of fMRI BOLD activity distribution over the brain may be used to classify different groups or mental states. These studies are based on the application of advanced pattern recognition approaches and multivariate statistical classifiers. Most published articles in this field are focused on improving the accuracy rates and many approaches have been proposed to accomplish this task. Nevertheless, a point inherent to most machine learning methods (and still relatively unexplored in neuroimaging) is how the discriminative information can be used to characterize groups and their differences. In this work, we introduce the Maximum Uncertainty Linear Discrimination Analysis (MLDA) and show how it can be applied to infer groups` patterns by discriminant hyperplane navigation. In addition, we show that it naturally defines a behavioral score, i.e., an index quantifying the distance between the states of a subject from predefined groups. We validate and illustrate this approach using a motor block design fMRI experiment data with 35 subjects. (C) 2008 Elsevier Inc. All rights reserved.

Movement-related potentials in Parkinson's disease - Motor imagery and movement preparation

Movement-related potentials (MRPs) associated with voluntary movements reflect cortical activity associated with processes Of movement preparation and movement execution. Early-stage pre-movement activity is reduced in amplitude in Parkinson's disease. However it is unclear whether this neurophysiological deficit relates to preparatory or execution-related activity, since previous studies have not been able to separate different functional components of MRPs. Motor imagery is thought to involve mainly processes of movement preparation, with reduced involvement of end-stage movement execution-related processes. Therefore, MRP components relating to movement preparation and execution may be examined separately by comparing MRPs associated with imagined and actual movements. In this study, MRPs were recorded from 14 subjects with Parkinson's disease and 10 age-matched control subjects while they performed a sequential button-pressing task, and while they imagined performance of the same task. Early-stage pre-movement activity was present in both Parkinson's disease patients and control subjects when they imagined movement, but was reduced in amplitude compared with that for actual movement. Movement execution-related components, arising predominantly from the primary motor cortex, were relatively unaffected in Parkinson's disease subjects. However motor preparatory processes, probably involving the supplementary motor area, were reduced in amplitude overall and abnormally prolonged, Indicating impaired termination following the motor response. Further this impaired termination of preparatory-phase activity was observed only in patients with more severe parkinsonian symptoms, and not in early-stage Parkinson's disease.

Expression of vitamin D receptor mRNA in the hippocampal formation of rats submitted to a model of temporal lobe epilepsy induced by pilocarpine

Vitamin D (VD), is a steroid hormone with multiple functions in the central nervous system (CNS), producing numerous physiological effects mediated by its receptor (VDR). Clinical and experimental studies have shown a link between VD dysfunction and epilepsy. Along these lines, the purpose of our work was to analyze the relative expression of VDR mRNA in the hippocampal formation of rats during the three periods of pilocarpine-induced epilepsy. Male Wistar rats were divided into five groups: (1) control group; rats that received saline 0.9%, i.p. and were killed 7 days after its administration (CTRL, n = 8), (2) SE group; rats that received pilocarpine and were killed 4 h after SE (SE, n = 8), (3) Silent group-7 days; rats that received pilocarpine and were killed 7 days after SE (SIL 7d, n = 8), (4) Silent group-14 days; rats that received pilocarpine and were killed 14 days after SE (SIL 14d, n = 8), (5) Chronic group; rats that received pilocarpine and were killed 60 days after the first spontaneous seizure, (chronic, n = 8). The relative expression of VDR mRNA was determined by real-time PCR. Our results showed an increase of the relative expression of VDR mRNA in the SIL 7 days, SIL 14 days and Chronic groups, respectively (0.060 +/- 0.024; 0.052 +/- 0.035; 0.085 +/- 0.055) when compared with the CTRL and SE groups (0.019 +/- 0.017; 0.019 +/- 0.025). These data suggest the VDR as a possible candidate participating in the epileptogenesis process of the pilocarpine model of epilepsy. (C) 2008 Elsevier Inc. All rights reserved.

The impact of functional connectivity changes on support vector machines mapping of fMRI data

Functional magnetic resonance imaging (fMRI) is currently one of the most widely used methods for studying human brain function in vivo. Although many different approaches to fMRI analysis are available, the most widely used methods employ so called ""mass-univariate"" modeling of responses in a voxel-by-voxel fashion to construct activation maps. However, it is well known that many brain processes involve networks of interacting regions and for this reason multivariate analyses might seem to be attractive alternatives to univariate approaches. The current paper focuses on one multivariate application of statistical learning theory: the statistical discrimination maps (SDM) based on support vector machine, and seeks to establish some possible interpretations when the results differ from univariate `approaches. In fact, when there are changes not only on the activation level of two conditions but also on functional connectivity, SDM seems more informative. We addressed this question using both simulations and applications to real data. We have shown that the combined use of univariate approaches and SDM yields significant new insights into brain activations not available using univariate methods alone. In the application to a visual working memory fMRI data, we demonstrated that the interaction among brain regions play a role in SDM`s power to detect discriminative voxels. (C) 2008 Elsevier B.V. All rights reserved.

Baseline hippocampal theta oscillation speeds correlate with rate of operant task acquisition

Many lines of evidence indicate that theta rhythm, a prominent neural oscillatory mode found in the mammalian hippocampus, plays a key role in the acquisition, processing, and retrieval of memories. However, a predictive neurophysiological feature of the baseline theta rhythm that correlates with the learning rate across different animals has yet to be identified. Here we show that the mean theta rhythm speed observed during baseline periods of immobility has a strong positive correlation with the rate at which rats learn an operant task. This relationship is observed across rats, during both quiet waking (r=0.82; p<0.01) and paradoxical sleep (r=0.83; p<0.01), suggesting that the basal theta frequency relates to basic neurological processes that are important in the acquisition of operant behavior. (c) 2008 Elsevier B.V. All rights reserved.

Egr transcription factors in the nervous system

The Egr proteins, Egr-1, Egr-2, Egr-3 and Egr-4, are closely related members of a subclass of immediate early gene-encoded, inducible transcription factors. They share a highly homologous DNA-binding domain which recognises an identical DNA response element. In addition, they have several less-well conserved structural features in common. As immediate early proteins, the Egr transcription factors are rapidly induced by diverse extracellular stimuli within the nervous system in a discretely controlled manner. The basal expression of the Egr proteins in the developing and adult rat brain and the induction of Egr proteins by neurotransmitter analogue stimulation, physiological mimetic and brain injury paradigms is reviewed. We review evidence indicating that Egr proteins are subject to tight differential control through diverse mechanisms at several levels of regulation. These include transcriptional, translational and posttranslational (including glycosylation, phosphorylation and redox) mechanisms and protein-protein interaction. Ultimately the differentially co-ordinated Egr response may lead to discrete effects on target gene expression. Some of the known target genes of Egr proteins and functions of the Egr proteins in different cell types are also highlighted. Future directions for research into the control and function of the different Egr proteins are also explored. (C) 1997 Elsevier Science Ltd.