Effective connectivity at synaptic level in humans: a review and future prospects

Gürcan, Önder

doi:10.1007/s00422-014-0619-1

“…A much smaller number of fMRI studies have assessed effective connectivity (EC) between brain regions–the causal influence that functional activity in a source region exerts over functional activity in a target region ( Friston, 2011 ; Friston et al, 2013 ). EC fundamentally differs from FC as it focuses on more complex and asymmetric relationships between brain regions ( Horwitz et al, 2005 ; Stevens, 2009 ; Friston, 2011 ; Gürcan, 2014 ). These relationships may be either excitatory or inhibitory in nature ( Wilson and Cowan, 1972 ; Tagamets and Horwitz, 1998 ; Horwitz et al, 2005 ).…”

Section: Introductionmentioning

confidence: 99%

Brain effective connectivity and functional connectivity as markers of lifespan vascular exposures in middle-aged adults: The Bogalusa Heart Study

Chuang

¹

,

Ramakrishnapillai

²

,

Madden

³

et al. 2023

Front. Aging Neurosci.

1

0

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IntroductionEffective connectivity (EC), the causal influence that functional activity in a source brain location exerts over functional activity in a target brain location, has the potential to provide different information about brain network dynamics than functional connectivity (FC), which quantifies activity synchrony between locations. However, head-to-head comparisons between EC and FC from either task-based or resting-state functional MRI (fMRI) data are rare, especially in terms of how they associate with salient aspects of brain health.MethodsIn this study, 100 cognitively-healthy participants in the Bogalusa Heart Study aged 54.2 ± 4.3years completed Stroop task-based fMRI, resting-state fMRI. EC and FC among 24 regions of interest (ROIs) previously identified as involved in Stroop task execution (EC-task and FC-task) and among 33 default mode network ROIs (EC-rest and FC-rest) were calculated from task-based and resting-state fMRI using deep stacking networks and Pearson correlation. The EC and FC measures were thresholded to generate directed and undirected graphs, from which standard graph metrics were calculated. Linear regression models related graph metrics to demographic, cardiometabolic risk factors, and cognitive function measures.ResultsWomen and whites (compared to men and African Americans) had better EC-task metrics, and better EC-task metrics associated with lower blood pressure, white matter hyperintensity volume, and higher vocabulary score (maximum value of p = 0.043). Women had better FC-task metrics, and better FC-task metrics associated with APOE-ε4 3–3 genotype and better hemoglobin-A1c, white matter hyperintensity volume and digit span backwards score (maximum value of p = 0.047). Better EC rest metrics associated with lower age, non-drinker status, and better BMI, white matter hyperintensity volume, logical memory II total score, and word reading score (maximum value of p = 0.044). Women and non-drinkers had better FC-rest metrics (value of p = 0.004).DiscussionIn a diverse, cognitively healthy, middle-aged community sample, EC and FC based graph metrics from task-based fMRI data, and EC based graph metrics from resting-state fMRI data, were associated with recognized indicators of brain health in differing ways. Future studies of brain health should consider taking both task-based and resting-state fMRI scans and measuring both EC and FC analyses to get a more complete picture of functional networks relevant to brain health.

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“…Mammalian central neural networks are complex systems in which nanoscopic synaptic specializations precisely connect mesoscopic local circuit elements enabling the bottom-up emergence of behavior 1 . Understanding the cellular and circuit-level generation of such behavior therefore requires a detailed knowledge of synaptic architectures and phenotypes across multiple scales.…”

Section: Introductionmentioning

confidence: 99%

SEQUIN Multiscale Imaging of Mammalian Central Synapses Reveals Loss of Synaptic Connectivity Resulting from Diffuse Traumatic Brain Injury

Sauerbeck

¹

,

Gangolli

²

,

Reitz

³

et al. 2020

Neuron

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The complex microconnectivity of the mammalian brain underlies its computational abilities, and its vulnerability to injury and disease. It has been challenging to illuminate the features of this synaptic network due in part to the small size and exceptionally dense packing of its elements. Here we describe a rapid and accessible super-resolution imaging and image analysis workflow-SEQUIN-that identifies, quantifies, and characterizes central synapses in animal models and in humans, enabling automated volumetric imaging of mesoscale synaptic networks without the laborious production of large histological arrays. Using SEQUIN, we identify delayed cortical synapse loss resulting from diffuse traumatic brain injury. Similar synapse loss is observed in an Alzheimer disease model, where SEQUIN mesoscale mapping of excitatory synapses across the hippocampus identifies region-specific synaptic vulnerability to neurodegeneration. These results establish a novel, easily implemented and robust nano-to-mesoscale synapse quantification and molecular characterization method. They furthermore identify a mechanistic link-synaptopathy-between Alzheimer neurodegeneration and its bestestablished epigenetic risk factor, brain trauma.

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SEQUIN multiscale imaging of mammalian central synapses reveals loss of synaptic microconnectivity resulting from diffuse traumatic brain injury

Sauerbeck

¹

,

Gangolli

²

,

Reitz

³

et al. 2019

Preprint

0

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The complex microconnectivity of the mammalian brain underlies its computational abilities, and its vulnerability to injury and disease. It has been challenging to illuminate the features of this synaptic network due in part to the small size and exceptionally dense packing of its elements. Here we describe a rapid and accessible super-resolution imaging and image analysis workflow-SEQUIN-that identifies, quantifies, and characterizes central synapses in animal models and in humans, enabling automated volumetric imaging of mesoscale synaptic networks without the laborious production of large histological arrays. Using SEQUIN, we identify delayed cortical synapse loss resulting from diffuse traumatic brain injury. Similar synapse loss is observed in an Alzheimer disease model, where SEQUIN mesoscale mapping of excitatory synapses across the hippocampus identifies region-specific synaptic vulnerability to neurodegeneration. These results establish a novel, easily implemented and robust nano-to-mesoscale synapse quantification and molecular characterization method. They furthermore identify a mechanistic link-synaptopathy-between Alzheimer neurodegeneration and its bestestablished epigenetic risk factor, brain trauma.

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Effective connectivity at synaptic level in humans: a review and future prospects

Cited by 6 publications

References 109 publications

Brain effective connectivity and functional connectivity as markers of lifespan vascular exposures in middle-aged adults: The Bogalusa Heart Study

Brain effective connectivity and functional connectivity as markers of lifespan vascular exposures in middle-aged adults: The Bogalusa Heart Study

SEQUIN Multiscale Imaging of Mammalian Central Synapses Reveals Loss of Synaptic Connectivity Resulting from Diffuse Traumatic Brain Injury

SEQUIN multiscale imaging of mammalian central synapses reveals loss of synaptic microconnectivity resulting from diffuse traumatic brain injury

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