The Electrophysiology of Resting State fMRI Networks

Traditional research in neuroscience has studied the topography of specific brain functions largely by presenting stimuli or imposing tasks and measuring evoked brain activity. This paradigm has dominated neuroscience for 50 years. Recently, investigations of brain activity in the resting state, most frequently using functional magnetic resonance imaging (fMRI), have revealed spontaneous correlations within widely distributed brain regions known as resting state networks (RSNs). Variability in RSNs across individuals has found to systematically relate to numerous diseases as well as differences in cognitive performance within specific domains. However, the relationship between spontaneous fMRI activity and the underlying neurophysiology is not well understood. This thesis aims to combine invasive electrophysiology and resting state fMRI in human subjects to better understand the nature of spontaneous brain activity. First, we establish an approach to precisely coregister intra-cranial electrodes to fMRI data (Chapter 2). We then created a novel machine learning approach to define resting state networks in individual subjects (Chapter 3). This approach is validated with cortical stimulation in clinical electrocorticography (ECoG) patients (Chapter 4). Spontaneous ECoG data are then analyzed with respect to fMRI time-series and fMRI-defined RSNs in order to illustrate novel ECoG correlates of fMRI for both local field potentials and band-limited power (BLP) envelopes (Chapter 5). In Chapter 6, we show that the spectral specificity of these resting state ECoG correlates link classic brain rhythms with large-scale functional domains. Finally, in Chapter 7 we show that the frequencies and topographies of spontaneous ECoG correlations specifically recapitulate the spectral and spatial structure of task responses within individual subjects

A comparison of resting state functional magnetic resonance imaging to invasive electrocortical stimulation for sensorimotor mapping in pediatric patients

Localizing neurologic function within the brain remains a significant challenge in clinical neurosurgery. Invasive mapping with direct electrocortical stimulation currently is the clinical gold standard but is impractical in young or cognitively delayed patients who are unable to reliably perform tasks. Resting state functional magnetic resonance imaging non-invasively identifies resting state networks without the need for task performance, hence, is well suited to pediatric patients. We compared sensorimotor network localization by resting state fMRI to cortical stimulation sensory and motor mapping in 16 pediatric patients aged 3.1 to 18.6 years. All had medically refractory epilepsy that required invasive electrographic monitoring and stimulation mapping. The resting state fMRI data were analyzed using a previously trained machine learning classifier that has previously been evaluated in adults. We report comparable functional localization by resting state fMRI compared to stimulation mapping. These results provide strong evidence for the utility of resting state functional imaging in the localization of sensorimotor cortex across a wide range of pediatric patients

On the role of the corpus callosum in interhemispheric functional connectivity in humans

Resting state functional connectivity is defined in terms of temporal correlations between physiologic signals, most commonly studied using functional magnetic resonance imaging. Major features of functional connectivity correspond to structural (axonal) connectivity. However, this relation is not one-to-one. Interhemispheric functional connectivity in relation to the corpus callosum presents a case in point. Specifically, several reports have documented nearly intact interhemispheric functional connectivity in individuals in whom the corpus callosum (the major commissure between the hemispheres) never develops. To investigate this question, we assessed functional connectivity before and after surgical section of the corpus callosum in 22 patients with medically refractory epilepsy. Section of the corpus callosum markedly reduced interhemispheric functional connectivity. This effect was more profound in multimodal associative areas in the frontal and parietal lobe than primary regions of sensorimotor and visual function. Moreover, no evidence of recovery was observed in a limited sample in which multiyear, longitudinal follow-up was obtained. Comparison of partial vs. complete callosotomy revealed several effects implying the existence of polysynaptic functional connectivity between remote brain regions. Thus, our results demonstrate that callosal as well as extracallosal anatomical connections play a role in the maintenance of interhemispheric functional connectivity

Individualized precision targeting of dorsal attention and default mode networks with rTMS in traumatic brain injury-associated depression

At the group level, antidepressant efficacy of rTMS targets is inversely related to their normative connectivity with subgenual anterior cingulate cortex (sgACC). Individualized connectivity may yield better targets, particularly in patients with neuropsychiatric disorders who may have aberrant connectivity. However, sgACC connectivity shows poor test-retest reliability at the individual level. Individualized resting-state network mapping (RSNM) can reliably map inter-individual variability in brain network organization. Thus, we sought to identify individualized RSNM-based rTMS targets that reliably target the sgACC connectivity profile. We used RSNM to identify network-based rTMS targets in 10 healthy controls and 13 individuals with traumatic brain injury-associated depression (TBI-D). These RSNM targets were compared with consensus structural targets and targets based on individualized anti-correlation with a group-mean-derived sgACC region ( sgACC-derived targets ). The TBI-D cohort was also randomized to receive active (n = 9) or sham (n = 4) rTMS to RSNM targets with 20 daily sessions of sequential high-frequency left-sided stimulation and low-frequency right-sided stimulation. We found that the group-mean sgACC connectivity profile was reliably estimated by individualized correlation with default mode network (DMN) and anti-correlation with dorsal attention network (DAN). Individualized RSNM targets were thus identified based on DAN anti-correlation and DMN correlation. These RSNM targets showed greater test-retest reliability than sgACC-derived targets. Counterintuitively, anti-correlation with the group-mean sgACC connectivity profile was also stronger and more reliable for RSNM-derived targets than for sgACC-derived targets. Improvement in depression after RSNM-targeted rTMS was predicted by target anti-correlation with the portions of sgACC. Active treatment also led to increased connectivity within and between the stimulation sites, the sgACC, and the DMN. Overall, these results suggest that RSNM may enable reliable individualized rTMS targeting, although further research is needed to determine whether this personalized approach can improve clinical outcomes

The Stakes in Bayh-Dole: Public Values Beyond the Pace of Innovation

Evaluation studies of the Bayh-Dole Act are generally concerned with the pace of innovation or the transgressions to the independence of research. While these concerns are important, I propose here to expand the range of public values considered in assessing Bayh-Dole and formulating future reforms. To this end, I first examine the changes in the terms of the Bayh-Dole debate and the drift in its design. Neoliberal ideas have had a definitive influence on U.S. innovation policy for the last thirty years, including legislation to strengthen patent protection. Moreover, the neoliberal policy agenda is articulated and justified in the interest of “competitiveness.” Rhetorically, this agenda equates competitiveness with economic growth and this with the public interest. Against that backdrop, I use Public Value Failure criteria to show that values such as political equality, transparency, and fairness in the distribution of the benefits of innovation, are worth considering to counter the “policy drift” of Bayh-Dole

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Listeria pathogenesis and molecular virulence determinants

The gram-positive bacterium Listeria monocytogenes is the causative agent of listeriosis, a highly fatal opportunistic foodborne infection. Pregnant women, neonates, the elderly, and debilitated or immunocompromised patients in general are predominantly affected, although the disease can also develop in normal individuals. Clinical manifestations of invasive listeriosis are usually severe and include abortion, sepsis, and meningoencephalitis. Listeriosis can also manifest as a febrile gastroenteritis syndrome. In addition to humans, L. monocytogenes affects many vertebrate species, including birds. Listeria ivanovii, a second pathogenic species of the genus, is specific for ruminants. Our current view of the pathophysiology of listeriosis derives largely from studies with the mouse infection model. Pathogenic listeriae enter the host primarily through the intestine. The liver is thought to be their first target organ after intestinal translocation. In the liver, listeriae actively multiply until the infection is controlled by a cell-mediated immune response. This initial, subclinical step of listeriosis is thought to be common due to the frequent presence of pathogenic L. monocytogenes in food. In normal indivuals, the continual exposure to listerial antigens probably contributes to the maintenance of anti-Listeria memory T cells. However, in debilitated and immunocompromised patients, the unrestricted proliferation of listeriae in the liver may result in prolonged low-level bacteremia, leading to invasion of the preferred secondary target organs (the brain and the gravid uterus) and to overt clinical disease. L. monocytogenes and L. ivanovii are facultative intracellular parasites able to survive in macrophages and to invade a variety of normally nonphagocytic cells, such as epithelial cells, hepatocytes, and endothelial cells. In all these cell types, pathogenic listeriae go through an intracellular life cycle involving early escape from the phagocytic vacuole, rapid intracytoplasmic multiplication, bacterially induced actin-based motility, and direct spread to neighboring cells, in which they reinitiate the cycle. In this way, listeriae disseminate in host tissues sheltered from the humoral arm of the immune system. Over the last 15 years, a number of virulence factors involved in key steps of this intracellular life cycle have been identified. This review describes in detail the molecular determinants of Listeria virulence and their mechanism of action and summarizes the current knowledge on the pathophysiology of listeriosis and the cell biology and host cell responses to Listeria infection. This article provides an updated perspective of the development of our understanding of Listeria pathogenesis from the first molecular genetic analyses of virulence mechanisms reported in 1985 until the start of the genomic era of Listeria research