2,692 research outputs found
An approach for identifying brainstem dopaminergic pathways using resting state functional MRI.
Here, we present an approach for identifying brainstem dopaminergic pathways using resting state functional MRI. In a group of healthy individuals, we searched for significant functional connectivity between dopamine-rich midbrain areas (substantia nigra; ventral tegmental area) and a striatal region (caudate) that was modulated by both a pharmacological challenge (the administration of the dopaminergic agonist bromocriptine) and a dopamine-sensitive cognitive trait (an individual's working memory capacity). A significant inverted-U shaped connectivity pattern was found in a subset of midbrain-striatal connections, demonstrating that resting state fMRI data is sufficiently powerful to identify brainstem neuromodulatory brain networks
Altered Resting State Cortico-Striatal Connectivity in Mild to Moderate Stage Parkinson's Disease
Parkinson's disease (PD) is a progressive neurodegenerative disorder that is characterized by dopamine depletion in the striatum. One consistent pathophysiological hallmark of PD is an increase in spontaneous oscillatory activity in the basal ganglia thalamocortical networks. We evaluated these effects using resting state functional connectivity MRI in mild to moderate stage Parkinson's patients on and off l-DOPA and age-matched controls using six different striatal seed regions. We observed an overall increase in the strength of cortico-striatal functional connectivity in PD patients off l-DOPA compared to controls. This enhanced connectivity was down-regulated by l-DOPA as shown by an overall decrease in connectivity strength, particularly within motor cortical regions. We also performed a frequency content analysis of the BOLD signal time course extracted from the six striatal seed regions. PD off l-DOPA exhibited increased power in the frequency band 0.02–0.05 Hz compared to controls and to PD on l-DOPA. The l-DOPA associated decrease in the power of this frequency range modulated the l-DOPA associated decrease in connectivity strength between striatal seeds and the thalamus. In addition, the l-DOPA associated decrease in power in this frequency band correlated with the l-DOPA associated improvement in cognitive performance. Our results demonstrate that PD and l-DOPA modulate striatal resting state BOLD signal oscillations and cortico-striatal network coherence
Acute modulation of brain connectivity in Parkinson disease after automatic mechanical peripheral stimulation: A pilot study
The present study shows the results of a double-blind sham-controlled pilot trial to test whether measurable stimulus-specific functional connectivity changes exist after Automatic Mechanical Peripheral Stimulation (AMPS) in patients with idiopathic Parkinson Disease.Eleven patients (6 women and 5 men) with idiopathic Parkinson Disease underwent brain fMRI immediately before and after sham or effective AMPS. Resting state Functional Connectivity (RSFC) was assessed using the seed-ROI based analysis. Seed ROIs were positioned on basal ganglia, on primary sensory-motor cortices, on the supplementary motor areas and on the cerebellum. Individual differences for pre- and post-effective AMPS and pre- and post-sham condition were obtained and first entered in respective one-sample t-test analyses, to evaluate the mean effect of condition.Effective AMPS, but not sham stimulation, induced increase of RSFC of the sensory motor cortex, nucleus striatum and cerebellum. Secondly, individual differences for both conditions were entered into paired group t-test analysis to rule out sub-threshold effects of sham stimulation, which showed stronger connectivity of the striatum nucleus with the right lateral occipital cortex and the cuneal cortex (max Z score 3.12) and with the right anterior temporal lobe (max Z score 3.42) and of the cerebellum with the right lateral occipital cortex and the right cerebellar cortex (max Z score 3.79).Our results suggest that effective AMPS acutely increases RSFC of brain regions involved in visuo-spatial and sensory-motor integration.This study provides Class II evidence that automatic mechanical peripheral stimulation is effective in modulating brain functional connectivity of patients with Parkinson Disease at rest.Clinical Trials.gov NCT01815281
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The role of HG in the analysis of temporal iteration and interaural correlation
Intrinsic functional brain networks in health and disease
6 Introduction
 6
 6.1
 Imaging
 cognitive
 processes
 with
 functional
 magnetic
 resonance
 imaging
 7
 6.2
 Imaging
 the
 brain’s
 resting
 state
 8
 6.3
 Intrinsic
 connectivity
 networks
 in
 the
 resting
 state
 9
 6.4
 Investigating
 modulations
 and
 plasticity
 of
 intrinsic
 connectivity
 networks
 12 7 Paper
 1:
 Towards
 discovery
 science
 of
 human
 brain
 function
 (PNAS
 2010)
 14 8 Paper
 2:
 Repeated
 pain
 induces
 adaptations
 of
 intrinsic
 brain
 activity
 to
 reflect
 past
 and
 predict future pain
 (Neuroimage
 2011)
 30 9 Paper
 3:
 Intrinsic
 network
 connectivity
 reflects
 consistency
 of
 synesthetic
 experience
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Brain network mechanisms in learning behavior
The study of learning has been a central focus of psychology and neuroscience since their inception. Cognitive neuroscience’s traditional approach to understanding learn-ing has been to decompose it into discrete cognitive processes with separable and localized underlying neural systems. While this focus on modular cognitive functions for individual brain areas has led to considerable progress, there is increasing evidence that much of learn-ing behavior relies on overlapping cognitive and neural systems, which may be harder to disentangle than previously envisioned. This is not surprising, as the processes underlying learning must involve widespread integration of information from sensory, affective, and motor sources. The standard tools of cognitive neuroscience limit our ability to describe processes that rely on widespread coordination of brain activity. To understand learning, it will be necessary to characterize dynamic co-activation at the circuit level.
In this dissertation, I present three studies that seek to describe the roles of distrib-uted brain networks in learning. I begin by giving an overview of our current understand-ing of multiple forms of learning, describing the neural and computational mechanisms thought to underlie incremental feedback-based learning and flexible episodic memory. I will focus in particular on the difficulties in separating these processes at the cognitive level and in localizing them to individual regions at the neural level. I will then describe recent findings that have begun to characterize the brain’s large-scale network structure, emphasiz-ing the potential roles that distributed networks could play in understanding learning and cognition more generally. I will end the introduction by reviewing current attempts to char-acterize the dynamics of large-scale brain networks, which will be essential for providing a mechanistic link to learning behavior.
Chapter 2 is a study demonstrating that intrinsic connectivity between the hippo-campus and the ventromedial prefrontal cortex, as well as between these regions and dis-tributed brain networks, is related to individual differences in the transfer of learning on a sensory preconditioning task. The hippocampus and ventromedial prefrontal cortex have both been shown to be involved in this type of learning, and this study represents an early attempt to link connectivity between individual regions and broader networks to learning processes.
Chapter 3 is a study that takes advantage of recent developments in mathematical modeling of temporal networks to demonstrate a relationship between large-scale network dynamics and reinforcement learning within individuals. This study shows that the flexibil-ity of network connectivity in the striatum is related to learning performance over time, as well as to individual differences in parameters estimated from computational models of re-inforcement learning. Notably, connectivity between the striatum and visual as well as or-bitofrontal regions increased over the course of the task, which is consistent with an inte-grative role for the region in learning value-based associations. Network flexibility in a dis-tinct set of regions is associated with episodic memory for object images presented during the learning task.
Chapter 4 examines the role of dopamine, a neurotransmitter strongly linked to val-ue updating in reinforcement learning, in the dynamic network changes occurring during learning. Patients with Parkinson’s disease, who experience a loss of dopaminergic neu-rons in the substantia nigra, performed a reversal-learning task while undergoing functional magnetic resonance imaging. Patients were scanned on and off of a dopamine precursor medication (levodopa) in a within-subject design in order to examine the impact of dopa-mine on brain network dynamics during learning. The reversal provided an experimental manipulation of dynamic connectivity, and patients on medication showed greater modula-tion of striatal-cortical connectivity. Similar results were found in a number of regions re-ceiving midbrain projections including the prefrontal cortex and medial temporal lobe. This study indicates that dopamine inputs from the midbrain modulate large-scale network dy-namics during learning, providing a direct link between reinforcement learning theories of value updating and network neuroscience accounts of dynamic connectivity.
Together, these results indicate that large-scale networks play a critical role in multi-ple forms of learning behavior. Each highlights the potential importance of understanding dynamic routing and integration of information across large-scale circuits for our concep-tion of learning and other cognitive processes. Understanding the when, where, and how of this information flow in the brain may provide an alternative or compliment to traditional theories of distinct learning systems. These studies also illustrate challenges in integrating this perspective with established theories in cognitive neuroscience. Chapter 5 will situate the studies in a broader discussion of how brain activity relates to cognition in general, while pointing out current roadblocks and potential ways forward for a cognitive network neuroscience of learning
L-Dopa modulates functional connectivity in striatal cognitive and motor networks: A double-blind placebo-controlled study
Functional connectivity (FC) analyses of resting-state fMRI data allow for the mapping of large-scale functional networks, and provide a novel means of examining the impact of dopaminergic challenge. Here, using a double-blind, placebo-controlled design, we examined the effect of L-dopa, a dopamine precursor, on striatal resting-state FC in 19 healthy young adults. We examined the FC of 6 striatal regions of interest (ROIs) previously shown to elicit networks known to be associated with motivational, cognitive and motor subdivisions of the caudate and putamen (Di Martino et al., 2008). In addition to replicating the previously demonstrated patterns of striatal FC, we observed robust effects of L-dopa. Specifically, L-dopa increased FC in motor pathways connecting the putamen ROIs with the cerebellum and brainstem. Although L-dopa also increased FC between the inferior ventral striatum and ventrolateral prefrontal cortex, it disrupted ventral striatal and dorsal caudate FC with the default mode network. These alterations in FC are consistent with studies that have demonstrated dopaminergic modulation of cognitive and motor striatal networks in healthy participants. Recent studies have demonstrated altered resting state FC in several conditions believed to be characterized by abnormal dopaminergic neurotransmission. Our findings suggest that the application of similar experimental pharmacological manipulations in such populations may further our understanding of the role of dopaminergic neurotransmission in those conditions
Altered corticostriatal functional connectivity in obsessive-compulsive disorder
Context: neurobiological models of obsessive-compulsive disorder (OCD) emphasize disturbances in the function and connectivity of brain corticostriatal networks, or 'loops.' Although neuroimaging studies of patients have supported this network model of OCD, very few have applied measurements that are sensitive to brain connectivity features. Objective: using resting-state functional magnetic resonance imaging, we tested the hypothesis that OCD is associated with disturbances in the functional connectivity of primarily ventral corticostriatal regions, measured from coherent spontaneous fluctuations in the blood oxygenation level-dependent (BOLD) signal. Design: case-control cross-sectional study. Setting: hospital referral OCD unit and magnetic resonance imaging facility. Participants: a total of 21 patients with OCD (10 men, 11 women) and 21 healthy control subjects matched for age, sex, and estimated intelligence. Main outcome measures: voxelwise statistical parametric maps testing the strength of functional connectivity of 4 striatal seed regions of interest (dorsal caudate nucleus, ventral caudate/nucleus accumbens, dorsal putamen, and ventral putamen) with remaining brain areas. Results: for both groups, there was a clear distinction in the pattern of cortical connectivity of dorsal and ventral striatal regions, consistent with the notion of segregated motor, associative, and limbic corticostriatal networks. Between groups, patients with OCD had significantly increased functional connectivity along a ventral corticostriatal axis, implicating the orbitofrontal cortex and surrounding areas. The specific strength of connectivity between the ventral caudate/nucleus accumbens and the anterior orbitofrontal cortex predicted patients' overall symptom severity (r(2) = 0.57; P < .001). Additionally, patients with OCD showed evidence of reduced functional connectivity of the dorsal striatum and lateral prefrontal cortex, and of the ventral striatum with the region of the midbrain ventral tegmental area. Conclusions: this study directly supports the hypothesis that OCD is associated with functional alterations of brain corticostriatal networks. Specifically, our findings emphasize abnormal and heightened functional connectivity of ventrolimbic corticostriatal regions in patients with OCD
Auditory Hallucinations and the Brain’s Resting-State Networks: Findings and Methodological Observations
In recent years, there has been increasing interest in the potential for alterations to the brain’s resting-state networks (RSNs) to explain various kinds of psychopathology. RSNs provide an intriguing new explanatory framework for hallucinations, which can occur in different modalities and population groups, but which remain poorly understood. This collaboration from the International Consortium on Hallucination Research (ICHR) reports on the evidence linking resting-state alterations to auditory hallucinations (AH) and provides a critical appraisal of the methodological approaches used in this area. In the report, we describe findings from resting connectivity fMRI in AH (in schizophrenia and nonclinical individuals) and compare them with findings from neurophysiological research, structural MRI, and research on visual hallucinations (VH). In AH, various studies show resting connectivity differences in left-hemisphere auditory and language regions, as well as atypical interaction of the default mode network and RSNs linked to cognitive control and salience. As the latter are also evident in studies of VH, this points to a domain-general mechanism for hallucinations alongside modality-specific changes to RSNs in different sensory regions. However, we also observed high methodological heterogeneity in the current literature, affecting the ability to make clear comparisons between studies. To address this, we provide some methodological recommendations and options for future research on the resting state and hallucinations
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