Altered functional connectivity in mesial temporal lobe epilepsy.

Growing evidence of altered functional connectivity suggests that mesial temporal lobe epilepsy (mTLE) alters not only hippocampal networks, but also a number of resting state networks. These highly coherent, yet functionally distinct brain circuits interact dynamically with each other in order to mediate consciousness, memory, and attention. However, little is currently known about the modulation of these networks by epileptiform activity, such as interictal spikes and seizures. The objective of the study was to use simultaneous EEG-fMRI to investigate functional connectivity in three resting state networks: default mode network (DMN), salience network (SN), and dorsal attentional network (DAN) in patients with mTLE compared to a healthy cohort, and in relation to the onset of interictal spikes and the period immediately prior to the spikes. Compared to the healthy participants, mTLE patients showed significant alterations in functional connectivity of all three resting state networks, generally characterized by a lack of functional connectivity to prefrontal areas and increased connectivity to subcortical and posterior areas. Critically, prior to the onset of interictal spikes, compared to resting state, mTLE patients showed a lack of functional connectivity to the DMN and decreased synchronization within the SN and DAN, demonstrating alterations in functional coherence that may be responsible for the generation of epileptiform activity. Our findings demonstrate mTLE-related alterations of connectivity during the resting state as well as in relation to the onset of interictal spikes. These functional changes may underlie epilepsy-related cognitive abnormalities, because higher cognitive functions, such as memory or attention, rely heavily on the coordinated activity of all three resting state networks

A multimodal approach to the study of self and others’ awareness in prodromal to mild Alzheimer’s disease

Patients in the early stage of Alzheimer’s disease (AD) can manifest disorders of cognitive awareness such as a lack of/limited self-awareness of their own cognitive deficits (anosognosia) or as a reduction in the ability to be aware of others, i.e., social cognition; more specifically in the ability to recognise emotions or attribute mental states to others (also known as Theory of Mind, ToM). The present thesis intended to explain the behavioural, brain neuroanatomical, structural connectivity and resting-state functional relationship between the presence of multi-domain alterations of self-awareness/anosognosia and others awareness/social cognition to understand the cognitive and neural substrates that shape conscious awareness in early AD. Behavioural findings evidenced an association between the presence of anosognosia and reduced ToM. Individually, memory anosognosia was associated with memory proxies and total anosognosia with visuospatial abilities, while social cognition was associated with language, memory, attention and most importantly, executive functions. Neuroanatomical structural findings of non-memory and total anosognosia showed reduced grey matter volume in the anterior cingulate cortex (ACC), fusiform, lingual and precentral gyri. Conversely, ToM showed reduced grey matter volume also in the ACC, but reduction extended to encompass temporoparietal junction, orbitofrontal, superior temporal and cerebellar cortices. The ACC showed a statistical shared neural overlap between self-other awareness. At the functional level, both anosognosia and social cognition were associated with reduced internetwork connectivity between the default mode network (DMN) and the executive frontoparietal network (FPN), as well as higher connectivity between the DMN and the salience network, in which the insula seems to have an essential role. Subcortical contributions to large-scale network connectivity were also found. We propose that medial frontal executive mechanisms, such as those subserved by the ACC, might support awareness in the presence of an inherently damaged DMN in early-AD. Functional adaptive reorganisation of network dynamics might increase the strain to salient system hubs (ACC) by redirecting network traffic of executive resources to cope with the progressive decline of conscious awareness

Exploring the Neural Mechanisms of Physics Learning

This dissertation presents a series of neuroimaging investigations and achievements that strive to deepen and broaden our understanding of human problem solving and physics learning. Neuroscience conceives of dynamic relationships between behavior, experience, and brain structure and function, but how neural changes enable human learning across classroom instruction remains an open question. At the same time, physics is a challenging area of study in which introductory students regularly struggle to achieve success across university instruction. Research and initiatives in neuroeducation promise a new understanding into the interactions between biology and education, including the neural mechanisms of learning and development. These insights may be particularly useful in understanding how students learn, which is crucial for helping them succeed. Towards this end, we utilize methods in functional magnetic resonance imaging (fMRI), as informed by education theory, research, and practice, to investigate the neural mechanisms of problem solving and learning in students across semester-long University-level introductory physics learning environments. In the first study, we review and synthesize the neuroimaging problem solving literature and perform quantitative coordinate-based meta-analysis on 280 problem solving experiments to characterize the common and dissociable brain networks that underlie human problem solving across different representational contexts. Then, we describe the Understanding the Neural Mechanisms of Physics Learning project, which was designed to study functional brain changes associated with learning and problem solving in undergraduate physics students before and after a semester of introductory physics instruction. We present the development, facilitation, and data acquisition for this longitudinal data collection project. We then perform a sequence of fMRI analyses of these data and characterize the first-time observations of brain networks underlying physics problem solving in students after university physics instruction. We measure sustained and sequential brain activity and functional connectivity during physics problem solving, test brain-behavior relationships between accuracy, difficulty, strategy, and conceptualization of physics ideas, and describe differences in student physics-related brain function linked with dissociations in conceptual approach. The implications of these results to inform effective instructional practices are discussed. Then, we consider how classroom learning impacts the development of student brain function by examining changes in physics problem solving-related brain activity in students before and after they completed a semester-long Modeling Instruction physics course. Our results provide the first neurobiological evidence that physics learning environments drive the functional reorganization of large-scale brain networks in physics students. Through this collection of work, we demonstrate how neuroscience studies of learning can be grounded in educational theory and pedagogy, and provide deep insights into the neural mechanisms by which students learn physics

Language and thought are not the same thing: evidence from neuroimaging and neurological patients

Is thought possible without language? Individuals with global aphasia, who have almost no ability to understand or produce language, provide a powerful opportunity to find out. Surprisingly, despite their near-total loss of language, these individuals are nonetheless able to add and subtract, solve logic problems, think about another person's thoughts, appreciate music, and successfully navigate their environments. Further, neuroimaging studies show that healthy adults strongly engage the brain's language areas when they understand a sentence, but not when they perform other nonlinguistic tasks such as arithmetic, storing information in working memory, inhibiting prepotent responses, or listening to music. Together, these two complementary lines of evidence provide a clear answer: many aspects of thought engage distinct brain regions from, and do not depend on, language