1,862 research outputs found
Tracking dynamic interactions between structural and functional connectivity : a TMS/EEG-dMRI study
Transcranial magnetic stimulation (TMS) in combination with neuroimaging techniques allows to measure the effects of a direct perturbation of the brain. When coupled with high-density electroencephalography (TMS/hd-EEG), TMS pulses revealed electrophysiological signatures of different cortical modules in health and disease. However, the neural underpinnings of these signatures remain unclear. Here, by applying multimodal analyses of cortical response to TMS recordings and diffusion magnetic resonance imaging (dMRI) tractography, we investigated the relationship between functional and structural features of different cortical modules in a cohort of awake healthy volunteers. For each subject, we computed directed functional connectivity interactions between cortical areas from the source-reconstructed TMS/hd-EEG recordings and correlated them with the correspondent structural connectivity matrix extracted from dMRI tractography, in three different frequency bands (alpha, beta, gamma) and two sites of stimulation (left precuneus and left premotor). Each stimulated area appeared to mainly respond to TMS by being functionally elicited in specific frequency bands, that is, beta for precuneus and gamma for premotor. We also observed a temporary decrease in the whole-brain correlation between directed functional connectivity and structural connectivity after TMS in all frequency bands. Notably, when focusing on the stimulated areas only, we found that the structure-function correlation significantly increases over time in the premotor area controlateral to TMS. Our study points out the importance of taking into account the major role played by different cortical oscillations when investigating the mechanisms for integration and segregation of information in the human brain
Visual feedback alters force control and functional activity in the visuomotor network after stroke.
Modulating visual feedback may be a viable option to improve motor function after stroke, but the neurophysiological basis for this improvement is not clear. Visual gain can be manipulated by increasing or decreasing the spatial amplitude of an error signal. Here, we combined a unilateral visually guided grip force task with functional MRI to understand how changes in the gain of visual feedback alter brain activity in the chronic phase after stroke. Analyses focused on brain activation when force was produced by the most impaired hand of the stroke group as compared to the non-dominant hand of the control group. Our experiment produced three novel results. First, gain-related improvements in force control were associated with an increase in activity in many regions within the visuomotor network in both the stroke and control groups. These regions include the extrastriate visual cortex, inferior parietal lobule, ventral premotor cortex, cerebellum, and supplementary motor area. Second, the stroke group showed gain-related increases in activity in additional regions of lobules VI and VIIb of the ipsilateral cerebellum. Third, relative to the control group, the stroke group showed increased activity in the ipsilateral primary motor cortex, and activity in this region did not vary as a function of visual feedback gain. The visuomotor network, cerebellum, and ipsilateral primary motor cortex have each been targeted in rehabilitation interventions after stroke. Our observations provide new insight into the role these regions play in processing visual gain during a precisely controlled visuomotor task in the chronic phase after stroke
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The role of HG in the analysis of temporal iteration and interaural correlation
Development of Low-Frequency Repetitive Transcranial Magnetic Stimulation as a Tool to Modulate Visual Disorders: Insights from Neuroimaging
Repetitive transcranial magnetic stimulation (rTMS) has become a popular neuromodulation technique, increasingly employed to manage several neurological and psychological conditions. Despite its popular use, the underlying mechanisms of rTMS remain largely unknown, particularly at the visual cortex. Moreover, the application of rTMS to modulate visual-related disorders is under-investigated. The goal of the present research was to address these issues. I employ a multitude of neuroimaging techniques to gain further insight into neural mechanisms underlying low-frequency (1 Hz) rTMS to the visual cortex. In addition, I begin to develop and refine clinical low-frequency rTMS protocols applicable to visual disorders as an alternative therapy where other treatment options are unsuccessful or where there are simply no existing therapies. One such visual disorder that can benefit from rTMS treatment is the perception of visual hallucinations that can occur following visual pathway damage in otherwise cognitively healthy individuals. In Chapters 23, I investigate the potential of multiday low-frequency rTMS to the visual cortex to alleviate continuous and disruptive visual hallucinations consequent to occipital injury. Combining rTMS with magnetic resonance imaging techniques reveals functional and structural cortical changes that lead to the perception of visual hallucinations; and rTMS successfully attenuates these anomalous visual perceptions. In Chapters 45, I compare the effects of alternative doses of low-frequency rTMS to the visual cortex on neurotransmitter levels and intrinsic functional connectivity to gain insight into rTMS mechanisms and establish the most effective protocol. Differential dose-dependent effects are observed on neurotransmitter levels and functional connectivity that suggest the choice of protocol critically depends on the neurophysiological target. Collectively, this work provides a basic framework for the use of low-frequency rTMS and neuroimaging in clinical application for visual disorders
Age Differences in Vestibular Processing: Neural and Behavioral Evidence
The vestibular system is well known for its role in balance, but its mechanisms of action in this role are not well understood. My dissertation aims to provide a better understanding of vestibular brain function, its correlation with postural control, and its alteration with advancing age. This is an important topic considering that falls are the current leading cause of injuries in older adults in the U.S., and they have negative consequences on wellbeing and independence.
In this dissertation, I first review the conventional methods for studying vestibular function in the human brain, and I evaluate a novel MRI-compatible method, which relies on a pneumatic tapper. This approach successfully induces vestibular responses, while preventing the aversive effects of stimulation that are common in other approaches. Next, I assess age differences in brain responses to pneumatic vestibular stimulation, and find that older adults demonstrate less sensitivity to stimulation. Also, those with better postural control exhibit less deactivation of cross-modal sensory regions (e.g. visual and somatosensory cortices). This greater engagement of non-vestibular sensory regions in older adults with better balance could be a mechanism to compensate for inefficient vestibular processing. Consistent with this hypothesis, the relationship between postural control and deactivation of sensory regions was only evident in tasks of low difficulty (i.e. normal stance) in which compensatory neural recruitment might be most effective.
After assessing the brain responses to vestibular stimulation in terms of activation and deactivation, I examine connectivity of the vestibular cortex with other regions. This last experiment demonstrates that vestibular cortex connectivity increases in response to vestibular stimulation, and young adults exhibit greater connectivity relative to older adults. Also, connectivity predicts postural stability in high difficulty tasks for young adults, and in low difficulty tasks for older adults. Better balance in young adults is associated with less vestibular connectivity (i.e. they engaged vestibular cortex more selectively), whereas better balance in older adults is associated with higher connectivity (i.e. more recruitment of other sensory regions). These findings reinforce the conclusions from the second experiment, and provide more evidence in support of the compensation related utilization of neural circuits hypothesis (CRUNCH) of neural processing in older adults.PHDKines & Psychology PhDUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/145857/1/fnoohi_1.pd
Digital twin brain: a bridge between biological intelligence and artificial intelligence
In recent years, advances in neuroscience and artificial intelligence have
paved the way for unprecedented opportunities for understanding the complexity
of the brain and its emulation by computational systems. Cutting-edge
advancements in neuroscience research have revealed the intricate relationship
between brain structure and function, while the success of artificial neural
networks highlights the importance of network architecture. Now is the time to
bring them together to better unravel how intelligence emerges from the brain's
multiscale repositories. In this review, we propose the Digital Twin Brain
(DTB) as a transformative platform that bridges the gap between biological and
artificial intelligence. It consists of three core elements: the brain
structure that is fundamental to the twinning process, bottom-layer models to
generate brain functions, and its wide spectrum of applications. Crucially,
brain atlases provide a vital constraint, preserving the brain's network
organization within the DTB. Furthermore, we highlight open questions that
invite joint efforts from interdisciplinary fields and emphasize the
far-reaching implications of the DTB. The DTB can offer unprecedented insights
into the emergence of intelligence and neurological disorders, which holds
tremendous promise for advancing our understanding of both biological and
artificial intelligence, and ultimately propelling the development of
artificial general intelligence and facilitating precision mental healthcare
Action control in uncertain environments
A long-standing dichotomy in neuroscience pits automatic or reflexive drivers of behaviour against deliberate or reflective processes. In this thesis I explore how this concept applies to two stages of action control: decision-making and response inhibition. The first part of this thesis examines the decision-making process itself during which actions need to be selected that maximise rewards. Decisions arise through influences from model-free stimulus-response associations as well as model-based, goal-directed thought. Using a task that quantifies their respective contributions, I describe three studies that manipulate the balance of control between these two systems. I find that a pharmacological manipulation with levodopa increases model-based control without affecting model-free function; disruption of dorsolateral prefrontal cortex via magnetic stimulation disrupts model-based control; and direct current stimulation to the same prefrontal region has no effect on decision-making. I then examine how the intricate anatomy of frontostriatal circuits subserves reinforcement learning using functional, structural and diffusion magnetic resonance imaging (MRI). A second stage of action control discussed in this thesis is post-decision monitoring and adjustment of action. Specifically, I develop a response inhibition task that dissociates reactive, bottom-up inhibitory control from proactive, top-down forms of inhibition. Using functional MRI I show that, unlike the strong neural segregation in decision-making systems, neural mechanisms of reactive and proactive response inhibition overlap to a great extent in their frontostriatal circuitry. This leads to the hypothesis that neural decline, for 4 example in the context of ageing, might affect reactive and proactive control similarly. I test this in a large population study administered through a smartphone app. This shows that, against my prediction, reactive control reliably declines with age but proactive control shows no such decline. Furthermore, in line with data on gender differences in age-related neural degradation, reactive control in men declines faster with age than that of women
Methods and models for brain connectivity assessment across levels of consciousness
The human brain is one of the most complex and fascinating systems in nature. In the last decades, two events have boosted the investigation of its functional and structural properties. Firstly, the emergence of novel noninvasive neuroimaging modalities, which helped improving the spatial and temporal resolution of the data collected from in vivo human brains. Secondly, the development of advanced mathematical tools in network science and graph theory, which has recently translated into modeling the human brain as a network, giving rise to the area of research so called Brain Connectivity or Connectomics.
In brain network models, nodes correspond to gray-matter regions (based on functional or structural, atlas-based parcellations that constitute a partition), while links or edges correspond either to structural connections as modeled based on white matter fiber-tracts or to the functional coupling between brain regions by computing statistical dependencies between measured brain activity from different nodes.
Indeed, the network approach for studying the brain has several advantages:
1) it eases the study of collective behaviors and interactions between regions;
2) allows to map and study quantitative properties of its anatomical pathways;
3) gives measures to quantify integration and segregation of information processes in the brain, and the flow (i.e. the interacting dynamics) between different cortical and sub-cortical regions.
The main contribution of my PhD work was indeed to develop and implement new models and methods for brain connectivity assessment in the human brain, having as primary application the analysis of neuroimaging data coming from subjects at different levels of consciousness. I have here applied these methods to investigate changes in levels of consciousness, from normal wakefulness (healthy human brains) or drug-induced unconsciousness (i.e. anesthesia) to pathological (i.e. patients with disorders of consciousness)
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Distal Functional Connectivity of Known and Emerging Cortical Targets for Therapeutic Noninvasive Stimulation.
Noninvasive stimulation is an emerging modality for the treatment of psychiatric disorders, including addiction. A crucial element in effective cortical target selection is its distal influence. We approached this question by examining resting-state functional connectivity patterns in known and potential stimulation targets in 145 healthy adults. We compared connectivity patterns with distant regions of particular relevance in the development and maintenance of addiction. We used stringent Bonferroni-correction for multiple comparisons. We show how the anterior insula, dorsal anterior cingulate, and ventromedial prefrontal cortex had opposing functional connectivity with striatum compared to the dorsomedial prefrontal cortex. However, the dorsolateral prefrontal cortex, the currently preferred target, and the presupplementary motor area had strongest negative connections to amygdala and hippocampus. Our findings highlight differential and opposing influences as a function of cortical site, underscoring the relevance of careful cortical target selection dependent on the desired effect on subcortical structures. We show the relevance of dorsal anterior cingulate and ventromedial prefrontal cortex as emerging cortical targets, and further emphasize the anterior insula as a potential promising target in addiction treatment, given its strong connections to ventral striatum, putamen, and substantia nigra
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