Brain activation during string playing

This chapter attempts to integrate data from both functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) to elucidate the activation of the cortical areas in musical performance for both execution and imagination of music during string playing. In both fMRI and EEG experiments, playing the music was compared with imagining the music. This allowed separation of the areas mainly involved in motor execution from those involved in imagining, planning, and working memory, thus differentiating musical from purely motor areas.

BRAIN ACTIVATION AND CONNECTIVITY IN NON-DISABLED MULTIPLE SCLEROSIS PATIENTS

Multiple sclerosis (MS) is the most common demyelinating disease affecting the central nervous system. There is no cure for MS and current therapies have limited efficacy. While the majority of individuals with MS develop significant clinical disability, a subset experiences a disease course with minimal impairment even in the presence of significant apparent tissue damage on magnetic resonance imaging (MRI). The current studies combined functional MRI and diffusion tensor imaging (DTI) to elucidate brain mechanisms associated with lack of clinical disability in patients with MS. Recent evidence has implicated cortical reorganization as a mechanism to limit the clinical manifestation of the disease. Functional MRI was used to test the hypothesis that non-disabled MS patients (Expanded Disability Status Scale ≤ 1.5) show increased recruitment of cognitive control regions (dorsolateral prefrontal and anterior cingulate cortex) while performing sensory, motor and cognitive tasks. Compared to matched healthy controls, patients increased activation of cognitive control brain regions when performing non-dominant hand movements and the 2-back working memory task. Using dynamic causal modeling, we tested whether increased cognitive control recruitment is associated with alterations in connectivity in the working memory functional network. Patients exhibited similar network connectivity to that of control subjects when performing working memory tasks. We subsequently investigated the integrity of major white matter tracts to assess structural connectivity and its relation to activation and functional integration of the cognitive control system. Patients showed substantial alterations in callosal, inferior and posterior white matter tracts and less pronounced involvement of the corticospinal tracts and superior longitudinal fasciculi (SLF). Decreased structural integrity within the right SLF in patients was associated with decreased performance, and decreased activation and connectivity of the cognitive control system when performing working memory tasks. These studies suggest that patient with MS without clinical disability increase cognitive control system recruitment across functional domains and rely on preserved functional and structural connectivity of brain regions associated with this network. Moreover, the current studies show the usefulness of combining brain activation data from functional MRI and structural connectivity data from DTI to improve our understanding of brain adaptation mechanisms to neurological disease.

Asymptotic theory of time varying networks with memory and heterogeneous activation pattern

In this thesis work we develop a new generative model of social networks belonging to the family of Time Varying Networks. The importance of correctly modelling the mechanisms shaping the growth of a network and the dynamics of the edges activation and inactivation are of central importance in network science. Indeed, by means of generative models that mimic the real-world dynamics of contacts in social networks it is possible to forecast the outcome of an epidemic process, optimize the immunization campaign or optimally spread an information among individuals. This task can now be tackled taking advantage of the recent availability of large-scale, high-quality and time-resolved datasets. This wealth of digital data has allowed to deepen our understanding of the structure and properties of many real-world networks. Moreover, the empirical evidence of a temporal dimension in networks prompted the switch of paradigm from a static representation of graphs to a time varying one. In this work we exploit the Activity-Driven paradigm (a modeling tool belonging to the family of Time-Varying-Networks) to develop a general dynamical model that encodes fundamental mechanism shaping the social networks' topology and its temporal structure: social capital allocation and burstiness. The former accounts for the fact that individuals does not randomly invest their time and social interactions but they rather allocate it toward already known nodes of the network. The latter accounts for the heavy-tailed distributions of the inter-event time in social networks. We then empirically measure the properties of these two mechanisms from seven real-world datasets and develop a data-driven model, analytically solving it. We then check the results against numerical simulations and test our predictions with real-world datasets, finding a good agreement between the two. Moreover, we find and characterize a non-trivial interplay between burstiness and social capital allocation in the parameters phase space. Finally, we present a novel approach to the development of a complete generative model of Time-Varying-Networks. This model is inspired by the Kaufman's adjacent possible theory and is based on a generalized version of the Polya's urn. Remarkably, most of the complex and heterogeneous feature of real-world social networks are naturally reproduced by this dynamical model, together with many high-order topological properties (clustering coefficient, community structure etc.).

Changes in brain activation during working memory and facial recognition tasks in patients with bipolar disorder with Lamotrigine monotherapy

Verbal working memory and emotional self-regulation are impaired in Bipolar Disorder (BD). Our aim was to investigate the effect of Lamotrigine (LTG), which is effective in the clinical management of BD, on the neural circuits subserving working memory and emotional processing. Functional Magnetic Resonance Imaging data from 12 stable BD patients was used to detect LTG-induced changes as the differences in brain activity between drug-free and post-LTG monotherapy conditions during a verbal working memory (N-back sequential letter task) and an angry facial affect recognition task. For both tasks, LGT monotherapy compared to baseline was associated with increased activation mostly within the prefrontal cortex and cingulate gyrus, in regions normally engaged in verbal working memory and emotional processing. Therefore, LTG monotherapy in BD patients may enhance cortical function within neural circuits involved in memory and emotional self-regulation. © 2007 Elsevier B.V. and ECNP.

No gender differences in brain activation during the N-back task:An fMRI study in healthy individuals

Gender differences have been well established in verbal and spatial abilities but few studies have examined if these differences also extend into the domain of working memory in terms of behavioural differences and brain activation. The conclusions that can be drawn from these studies are not clear cut but suggest that even though gender differences might not be apparent from behavioural measures, the underlying neural substrate associated with working memory might be different in men and women. Previous research suggests activation in a network of frontal and parietal regions during working memory tasks. This study aimed to investigate gender differences in patterns of brain activation during a verbal version of the N-back working memory task, which incorporates the effects of increased demands on working memory. A total of 50 healthy subjects, aged 18 to 58 years, that were equally split by gender were recruited matched for age, levels of education and ethnicity. All subjects underwent functional magnetic resonance imaging. We found that men and women performed equally well in terms of accuracy and response times, while using similar brain regions to the same degree. Our observations indicate that verbal working memory is not affected by gender at the behavioural or neural level, and support the findings of a recent meta-analysis by Hyde ([2005]: Sex Roles 53:717-725) that gender differences are generally smaller than intra-gender differences in many cognitive domains. © 2009 Wiley-Liss, Inc.

Principal Component Analysis and Assessment of Language Network Activation Patterns in Pediatric Epilepsy

This dissertation establishes a novel data-driven method to identify language network activation patterns in pediatric epilepsy through the use of the Principal Component Analysis (PCA) on functional magnetic resonance imaging (fMRI). A total of 122 subjects’ data sets from five different hospitals were included in the study through a web-based repository site designed here at FIU. Research was conducted to evaluate different classification and clustering techniques in identifying hidden activation patterns and their associations with meaningful clinical variables. The results were assessed through agreement analysis with the conventional methods of lateralization index (LI) and visual rating. What is unique in this approach is the new mechanism designed for projecting language network patterns in the PCA-based decisional space. Synthetic activation maps were randomly generated from real data sets to uniquely establish nonlinear decision functions (NDF) which are then used to classify any new fMRI activation map into typical or atypical. The best nonlinear classifier was obtained on a 4D space with a complexity (nonlinearity) degree of 7. Based on the significant association of language dominance and intensities with the top eigenvectors of the PCA decisional space, a new algorithm was deployed to delineate primary cluster members without intensity normalization. In this case, three distinct activations patterns (groups) were identified (averaged kappa with rating 0.65, with LI 0.76) and were characterized by the regions of: 1) the left inferior frontal Gyrus (IFG) and left superior temporal gyrus (STG), considered typical for the language task; 2) the IFG, left mesial frontal lobe, right cerebellum regions, representing a variant left dominant pattern by higher activation; and 3) the right homologues of the first pattern in Broca's and Wernicke's language areas. Interestingly, group 2 was found to reflect a different language compensation mechanism than reorganization. Its high intensity activation suggests a possible remote effect on the right hemisphere focus on traditionally left-lateralized functions. In retrospect, this data-driven method provides new insights into mechanisms for brain compensation/reorganization and neural plasticity in pediatric epilepsy.

Understanding the abnormal brain activity in epilepsy as a potential predictor of the onset of an epileptic seizure

The Brain Research Institute (BRI) uses various types of indirect measurements, including EEG and fMRI, to understand and assess brain activity and function. As well as the recovery of generic information about brain function, research also focuses on the utilisation of such data and understanding to study the initiation, dynamics, spread and suppression of epileptic seizures. To assist with the future focussing of this aspect of their research, the BRI asked the MISG 2010 participants to examine how the available EEG and fMRI data and current knowledge about epilepsy should be analysed and interpreted to yield an enhanced understanding about brain activity occurring before, at commencement of, during, and after a seizure. Though the deliberations of the study group were wide ranging in terms of the related matters considered and discussed, considerable progress was made with the following three aspects. (1) The science behind brain activity investigations depends crucially on the quality of the analysis and interpretation of, as well as the recovery of information from, EEG and fMRI measurements. A number of specific methodologies were discussed and formalised, including independent component analysis, principal component analysis, profile monitoring and change point analysis (hidden Markov modelling, time series analysis, discontinuity identification). (2) Even though EEG measurements accurately and very sensitively record the onset of an epileptic event or seizure, they are, from the perspective of understanding the internal initiation and localisation, of limited utility. They only record neuronal activity in the cortical (surface layer) neurons of the brain, which is a direct reflection of the type of electrical activity they have been designed to record. Because fMRI records, through the monitoring of blood flow activity, the location of localised brain activity within the brain, the possibility of combining fMRI measurements with EEG, as a joint inversion activity, was discussed and examined in detail. (3) A major goal for the BRI is to improve understanding about ``when'' (at what time) an epileptic seizure actually commenced before it is identified on an eeg recording, ``where'' the source of this initiation is located in the brain, and ``what'' is the initiator. Because of the general agreement in the literature that, in one way or another, epileptic events and seizures represent abnormal synchronisations of localised and/or global brain activity the modelling of synchronisations was examined in some detail. References C. M. Michel, G. Thut, S. Morand, A. Khateb, A. J. Pegna, R. Grave de Peralta, S. Gonzalez, M. Seeck and T. Landis, Electric source imaging of human brain functions, Brain Res. 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Meditation training increases brain efficiency in an attention task

Meditation is a mental training, which involves attention and the ability to maintain focus on a particular object. In this study we have applied a specific attentional task to simply measure the performance of the participants with different levels of meditation experience, rather than evaluating meditation practice per se or task performance during meditation. Our objective was to evaluate the performance of regular meditators and non-meditators during an fMRI adapted Stroop Word-Colour Task (SWCT), which requires attention and impulse control, using a block design paradigm. We selected 20 right-handed regular meditators and 19 non-meditators matched for age, years of education and gender. Participants had to choose the colour (red, blue or green) of single words presented visually in three conditions: congruent, neutral and incongruent. Non-meditators showed greater activity than meditators in the right medial frontal, middle temporal, precentral and postcentral gyri and the lentiform nucleus during the incongruent conditions. No regions were more activated in meditators relative to non-meditators in the same comparison. Non-meditators showed an increased pattern of brain activation relative to regular meditators under the same behavioural performance level. This suggests that meditation training improves efficiency, possibly via improved sustained attention and impulse control. (C) 2011 Elsevier Inc. All rights reserved.

Pattern and timing of the coronary sinus activation to guide rapid diagnosis of atrial tachycardia after atrial fibrillation ablation

BACKGROUND Atrial tachycardias (AT) during or after ablation of atrial fibrillation frequently pose a diagnostic challenge. We hypothesized that both the patterns and the timing of coronary sinus (CS) activation could facilitate AT mapping. METHODS AND RESULTS A total of 140 consecutive postpersistent atrial fibrillation ablation patients with sustained AT were investigated by conventional mapping. CS activation pattern was defined as chevron or reverse chevron when the activations recorded on both the proximal and the distal CS dipoles were latest or earliest, respectively. The local activation of mid-CS was timed with reference to Ppeak-Ppeak (P-P) interval in lead V1. A ratio, mid-CS activation time to AT cycle length, was computed. Of 223 diagnosed ATs, 124 were macroreentrant (56%) and 99 were centrifugal (44%). When CS activation was chevron/reverse chevron (n=44; 20%), macroreentries were mostly roof dependent. With reference to P-P interval, mid-CS activation timing showed specific consistency for peritricuspid and perimitral AT. Proximal to distal CS activation pattern and mid-CS activation at 50% to 70% of the P-P interval (n=30; 13%) diagnosed peritricuspid AT with 81% sensitivity and 89% specificity. Distal to proximal CS activation and mid-CS activation at 10% to 40% of the P-P interval (n=44; 20%) diagnosed perimitral AT with 88% sensitivity and 75% specificity. CONCLUSIONS The analysis of the patterns and timing of CS activation provides a rapid stratification of most likely macroreentrant ATs and points toward the likely origin of centrifugal ATs. It can be included in a stepwise diagnostic approach to rapidly select the most critical mapping maneuvers.

Pattern of neuronal activity associated with conscious and unconscious processing of visual signals

Following striate cortex damage in monkeys and humans there can be residual function mediated by parallel visual pathways. In humans this can sometimes be associated with a “feeling” that something has happened, especially with rapid movement or abrupt onset. For less transient events, discriminative performance may still be well above chance even when the subject reports no conscious awareness of the stimulus. In a previous study we examined parameters that yield good residual visual performance in the “blind” hemifield of a subject with unilateral damage to the primary visual cortex. With appropriate parameters we demonstrated good discriminative performance, both with and without conscious awareness of a visual event. These observations raise the possibility of imaging the brain activity generated in the “aware” and the “unaware” modes, with matched levels of discrimination performance, and hence of revealing patterns of brain activation associated with visual awareness. The intact hemifield also allows a comparison with normal vision. Here we report the results of a functional magnetic resonance imaging study on the same subject carried out under aware and unaware stimulus conditions. The results point to a shift in the pattern of activity from neocortex in the aware mode, to subcortical structures in the unaware mode. In the aware mode prestriate and dorsolateral prefrontal cortices (area 46) are active. In the unaware mode the superior colliculus is active, together with medial and orbital prefrontal cortical sites.

Decoding Spontaneous Emotional States in the Human Brain.

Pattern classification of human brain activity provides unique insight into the neural underpinnings of diverse mental states. These multivariate tools have recently been used within the field of affective neuroscience to classify distributed patterns of brain activation evoked during emotion induction procedures. Here we assess whether neural models developed to discriminate among distinct emotion categories exhibit predictive validity in the absence of exteroceptive emotional stimulation. In two experiments, we show that spontaneous fluctuations in human resting-state brain activity can be decoded into categories of experience delineating unique emotional states that exhibit spatiotemporal coherence, covary with individual differences in mood and personality traits, and predict on-line, self-reported feelings. These findings validate objective, brain-based models of emotion and show how emotional states dynamically emerge from the activity of separable neural systems.

Collagen-induced activation of the Mr. 72,000 type IV collagenase in normal and malignant human fibroblastoid cells

Although the Mr. 72,000 type IV collagenase (matrix metalloproteinase 2) has been implicated in a variety of normal and pathogenic processes, its activation mechanism in vivo is unclear. We have found that fibroblasts from normal and neoplastic human breast, as well as the sarcomatous human Hs578T and HT1080 cell lines, activate endogenous matrix metalloprotease 2 when cultured on type I collagen gels, but not on plastic, fibronectin, collagen IV, gelatin, matrigel, or basement membrane-like HR9 cell matrix. This activation is monitored by the zymographic detection of Mr 59,000 and/or Mr 62,000 species, requires 2-3 days of culture on vitrogen to manifest, is cycloheximide inhibitable, and correlates with an arborized morphology. A similar activation pattern was seen in these cells in response to Concanavalin A but not transforming growth factor β or 12-O-tetradecanoylphorbol-13-acetate. The interstitial matrix may thus play an important role in regulating matrix degradation in vivo.

Functional magnetic resonance brain imaging of executive cognitive performance in young first-episode schizophrenia patients and age-matched long-term cannabis users

Converging evidence from epidemiological, clinical and neuropsychological research suggests a link between cannabis use and increased risk of psychosis. Long-term cannabis use has also been related to deficit-like “negative” symptoms and cognitive impairment that resemble some of the clinical and cognitive features of schizophrenia. The current functional brain imaging study investigated the impact of a history of heavy cannabis use on impaired executive function in first-episode schizophrenia patients. Whilst performing the Tower of London task in a magnetic resonance imaging scanner, event-related blood oxygenation level-dependent (BOLD) brain activation was compared between four age and gender-matched groups: 12 first-episode schizophrenia patients; 17 long-term cannabis users; seven cannabis using first-episode schizophrenia patients; and 17 healthy control subjects. BOLD activation was assessed as a function of increasing task difficulty within and between groups as well as the main effects of cannabis use and the diagnosis of schizophrenia. Cannabis users and non-drug using first-episode schizophrenia patients exhibited equivalently reduced dorsolateral prefrontal activation in response to task difficulty. A trend towards additional prefrontal and left superior parietal cortical activation deficits was observed in cannabis-using first-episode schizophrenia patients while a history of cannabis use accounted for increased activation in the visual cortex. Cannabis users and schizophrenia patients fail to adequately activate the dorsolateral prefrontal cortex, thus pointing to a common working memory impairment which is particularly evident in cannabis-using first-episode schizophrenia patients. A history of heavy cannabis use, on the other hand, accounted for increased primary visual processing, suggesting compensatory imagery processing of the task.

Functional brain maps of Tower of London performance : a positron emission tomography and functional magnetic resonance imaging study

Regional cerebral blood flow (rCBF) and blood oxygenation level-dependent (BOLD) contrasts represent different physiological measures of brain activation. The present study aimed to compare two functional brain imaging techniques (functional magnetic resonance imaging versus [15O] positron emission tomography) when using Tower of London (TOL) problems as the activation task. A categorical analysis (task versus baseline) revealed a significant BOLD increase bilaterally for the dorsolateral prefrontal and inferior parietal cortex and for the cerebellum. A parametric haemodynamic response model (or regression analysis) confirmed a task-difficulty-dependent increase of BOLD and rCBF for the cerebellum and the left dorsolateral prefrontal cortex. In line with previous studies, a task-difficulty-dependent increase of left-hemispheric rCBF was also detected for the premotor cortex, cingulate, precuneus, and globus pallidus. These results imply consistency across the two neuroimaging modalities, particularly for the assessment of prefrontal brain function when using a parametric TOL adaptation.

A generalised deficit can account for problems in facial emotion recognition in schizophrenia

Neuroimaging research has shown localised brain activation to different facial expressions. This, along with the finding that schizophrenia patients perform poorly in their recognition of negative emotions, has raised the suggestion that patients display an emotion specific impairment. We propose that this asymmetry in performance reflects task difficulty gradations, rather than aberrant processing in neural pathways subserving recognition of specific emotions. A neural network model is presented, which classifies facial expressions on the basis of measurements derived from human faces. After training, the network showed an accuracy pattern closely resembling that of healthy subjects. Lesioning of the network led to an overall decrease in the network’s discriminant capacity, with the greatest accuracy decrease to fear, disgust and anger stimuli. This implies that the differential pattern of impairment in schizophrenia patients can be explained without having to postulate impairment of specific processing modules for negative emotion recognition.