scholarly journals A Whole-Brain Connectivity Map of VTA and SNc Glutamatergic and GABAergic Neurons in Mice

2021 ◽  
Vol 15 ◽  
Author(s):  
Sile An ◽  
Xiangning Li ◽  
Lei Deng ◽  
Peilin Zhao ◽  
Zhangheng Ding ◽  
...  
Keyword(s):  
Brain Connectivity ◽  
Dorsal Striatum ◽  
Brain Regions ◽  
Gabaergic Neurons ◽  
Substantia Nigra Pars Compacta ◽  
Hypothalamic Area ◽  
Whole Brain ◽  
Glutamatergic Neurons ◽  
Brain Functions ◽  
Cell Type Specific

The glutamatergic and GABAergic neurons in the ventral tegmental area (VTA) and substantia nigra pars compacta (SNc) mediated diverse brain functions. However, their whole-brain neural connectivity has not been comprehensively mapped. Here we used the virus tracers to characterize the whole-brain inputs and outputs of glutamatergic and GABAergic neurons in VTA and SNc. We found that these neurons received similar inputs from upstream brain regions, but some quantitative differences were also observed. Neocortex and dorsal striatum provided a greater share of input to VTA glutamatergic neurons. Periaqueductal gray and lateral hypothalamic area preferentially innervated VTA GABAergic neurons. Specifically, superior colliculus provided the largest input to SNc glutamatergic neurons. Compared to input patterns, the output patterns of glutamatergic and GABAergic neurons in the VTA and SNc showed significant preference to different brain regions. Our results laid the anatomical foundation for understanding the functions of cell-type-specific neurons in VTA and SNc.

scholarly journals Whole-brain connectivity atlas of glutamatergic and GABAergic neurons in mouse dorsal and median raphe nucleus

2020 ◽  
Author(s):  
Zhengchao Xu ◽  
Zhao Feng ◽  
Meng-Ting Zhao ◽  
Qingtao Sun ◽  
Lei Deng ◽  
...  
Keyword(s):  
Brain Connectivity ◽  
Brain Regions ◽  
Gabaergic Neurons ◽  
Raphe Nucleus ◽  
Brain Atlas ◽  
Median Raphe ◽  
Median Raphe Nucleus ◽  
Whole Brain ◽  
Lateral Habenula ◽  
Median Raphé

The dorsal raphe nucleus (DR) and median raphe nucleus (MR) contain populations of glutamatergic and GABAergic neurons regulating diverse behavioral functions. Their whole-brain input-output circuits remain incompletely understood. We used viral tracing combined with fluorescence micro-optical sectioning tomography to generate a comprehensive whole-brain atlas of inputs and outputs of glutamatergic and GABAergic neurons in the DR and MR. We discovered that these neurons receive inputs from similar upstream brain regions. The glutamatergic and GABAergic neurons in the same raphe nucleus have divergent projection patterns with differences in critical brain regions. Specifically, MR glutamatergic neurons project to the lateral habenula via multiple pathways. Correlation and cluster analysis indicated that glutamatergic and GABAergic neurons in the same raphe nucleus receive inputs from heterogeneous neurons in upstream brain regions and send different collateral projections. This connectivity atlas provides insights into the cell heterogeneity, anatomical connectivity and behavioral functions of the raphe nucleus.

scholarly journals A whole-brain connectivity map of mouse insular cortex

2020 ◽  
Author(s):  
Daniel A. Gehrlach ◽  
Thomas N. Gaitanos ◽  
Alexandra S. Klein ◽  
Caroline Weiand ◽  
Alexandru A. Hennrich ◽  
...  
Keyword(s):  
Brain Connectivity ◽  
Insular Cortex ◽  
Structural Basis ◽  
Subcortical Structures ◽  
Whole Brain ◽  
Brain Functions ◽  
Complex Functions ◽  
Cell Type Specific ◽  
Cortical Regions ◽  
The Brain

AbstractThe insular cortex (IC) plays key roles in emotional and regulatory brain functions and is affected across psychiatric diseases. However, the brain-wide connections of the mouse IC have not been comprehensively mapped. Here we traced the whole-brain inputs and outputs of the mouse IC across its rostro-caudal extent. We employed cell-type specific monosynaptic rabies virus tracings to characterize afferent connections onto either excitatory or inhibitory IC neurons, and adeno-associated viral tracings to label excitatory efferent axons. While the connectivity between the IC and other cortical regions was highly reciprocal, the IC connectivity with subcortical structures was often unidirectional, revealing prominent top-down and bottom-up pathways. The posterior and medial IC exhibited resembling connectivity patterns, while the anterior IC connectivity was distinct, suggesting two major functional compartments. Our results provide insights into the anatomical architecture of the mouse IC and thus a structural basis to guide investigations into its complex functions.

scholarly journals A whole-brain connectivity map of mouse insular cortex

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Daniel A Gehrlach ◽  
Caroline Weiand ◽  
Thomas N Gaitanos ◽  
Eunjae Cho ◽  
Alexandra S Klein ◽  
...  
Keyword(s):  
Brain Connectivity ◽  
Insular Cortex ◽  
Structural Basis ◽  
Subcortical Structures ◽  
Whole Brain ◽  
Brain Functions ◽  
Complex Functions ◽  
Cell Type Specific ◽  
Cortical Regions ◽  
The Brain

The insular cortex (IC) plays key roles in emotional and regulatory brain functions and is affected across psychiatric diseases. However, the brain-wide connections of the mouse IC have not been comprehensively mapped. Here, we traced the whole-brain inputs and outputs of the mouse IC across its rostro-caudal extent. We employed cell-type-specific monosynaptic rabies virus tracings to characterize afferent connections onto either excitatory or inhibitory IC neurons, and adeno-associated viral tracings to label excitatory efferent axons. While the connectivity between the IC and other cortical regions was highly bidirectional, the IC connectivity with subcortical structures was often unidirectional, revealing prominent cortical-to-subcortical or subcortical-to-cortical pathways. The posterior and medial IC exhibited resembling connectivity patterns, while the anterior IC connectivity was distinct, suggesting two major functional compartments. Our results provide insights into the anatomical architecture of the mouse IC and thus a structural basis to guide investigations into its complex functions.

scholarly journals Lynn_etal_MathSkills_CPM_Preprint_V1_05July2021

2021 ◽  
Author(s):  
Andrew Lynn ◽  
Eric D. Wilkey ◽  
Gavin Price
Keyword(s):  
Functional Connectivity ◽  
Predictive Modeling ◽  
Brain Connectivity ◽  
Network Connectivity ◽  
Brain Regions ◽  
Math Skills ◽  
Whole Brain ◽  
Building Models ◽  
State Dependent ◽  
Brain Behavior

The human brain comprises multiple canonical networks, several of which are distributed across frontal, parietal, and temporooccipital regions. Studies report both positive and negative correlations between children’s math skills and the strength of functional connectivity among these regions during math-related tasks and at rest. Yet, it is unclear how the relation between children’s math skills and functional connectivity map onto patterns of distributed whole-brain connectivity, canonical network connectivity, and whether these relations are consistent across different task-states. We used connectome-based predictive modeling to test whether functional connectivity during number comparison and at rest predicts children’s math skills (N=31, Mage=9.21years) using distributed whole-brain connections versus connections among canonical networks. We found that weaker connectivity distributed across the whole brain and weaker connectivity between key math-related brain regions in specific canonical networks predicts better math skills in childhood. The specific connections predicting math skills, and whether they were distributed or mapped onto canonical networks, varied between tasks, suggesting that state-dependent rather than trait-level functional network architectures support children’s math skills. Furthermore, the current predictive modeling approach moves beyond brain-behavior correlations and toward building models of brain connectivity that may eventually aid in predicting future math skills.

Effective brain connectivity estimation between active brain regions in autism using the dual Kalman-based method

2020 ◽  
Vol 65 (1) ◽  
pp. 23-32
Author(s):  
Mehdi Rajabioun ◽  
Ali Motie Nasrabadi ◽  
Mohammad Bagher Shamsollahi ◽  
Robert Coben
Keyword(s):  
Resting State ◽  
Brain Connectivity ◽  
Effective Connectivity ◽  
Estimation Error ◽  
Brain Regions ◽  
Estimation Methods ◽  
Estimation Errors ◽  
Normal Children ◽  
Brain Functions ◽  
The Brain

AbstractBrain connectivity estimation is a useful method to study brain functions and diagnose neuroscience disorders. Effective connectivity is a subdivision of brain connectivity which discusses the causal relationship between different parts of the brain. In this study, a dual Kalman-based method is used for effective connectivity estimation. Because of connectivity changes in autism, the method is applied to autistic signals for effective connectivity estimation. For method validation, the dual Kalman based method is compared with other connectivity estimation methods by estimation error and the dual Kalman-based method gives acceptable results with less estimation errors. Then, connectivities between active brain regions of autistic and normal children in the resting state are estimated and compared. In this simulation, the brain is divided into eight regions and the connectivity between regions and within them is calculated. It can be concluded from the results that in the resting state condition the effective connectivity of active regions is decreased between regions and is increased within each region in autistic children. In another result, by averaging the connectivity between the extracted active sources of each region, the connectivity between the left and right of the central part is more than that in other regions and the connectivity in the occipital part is less than that in others.

scholarly journals Linear Input as a Fundamental Motif of Brain Connectivity Organization

2019 ◽  
Author(s):  
Jonathan F. O’Rawe ◽  
Hoi-Chung Leung
Keyword(s):  
Functional Connectivity ◽  
Information Transfer ◽  
Brain Connectivity ◽  
Brain Regions ◽  
Fundamental Aspect ◽  
Biased Sampling ◽  
Whole Brain ◽  
3 Dimensional ◽  
Face Area ◽  
Learning Techniques

AbstractDescribing the pattern of region-to-region functional connectivity is an important step towards understanding information transfer and transformation between brain regions. Although fMRI data are limited in spatial resolution, recent advances in technology afford more precise mapping. Here, we extended previous methods, connective field mapping, to 3 dimensions to provide a more concise estimate of the organization and potential information transformation from one region to another. We first replicated previous work with the 3 dimensional model by showing that the topology of functional connectivity between early visual regions maintained along their eccentricity axis or the anterior-posterior dimension. We then examined higher order visual regions (e,g, fusiform face area) and showed that their pattern of connectivity, the convergence and biased sampling, seem to contribute to some of their core receptive field properties. We further demonstrated that linearity of input is a fundamental aspect of functional connectivity of the whole brain, with higher linearity between regions within a network than across networks; that is, high connective linearity was evident between early visual areas, and between prefrontal areas, but less evident between them. By decomposing the whole brain linearity matrix with manifold learning techniques, we found that the principle mode of the linearity maps onto decompositions in both functional connectivity and genetic expression reported in previous studies. The current work provides evidence supporting that linearity of input is likely a fundamental motif of functional connectivity between regions for information processing across the brain, with high linearity preserving the integrity of information from one region to another within a network.

scholarly journals Whole-brain connectivity atlas of glutamatergic and GABAergic neurons in the mouse dorsal and median raphe nuclei

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Zhengchao Xu ◽  
Zhao Feng ◽  
Mengting Zhao ◽  
Qingtao Sun ◽  
Lei Deng ◽  
...  
Keyword(s):  
Brain Regions ◽  
Gabaergic Neurons ◽  
Raphe Nucleus ◽  
Raphe Nuclei ◽  
Brain Atlas ◽  
Median Raphe ◽  
Whole Brain ◽  
Lateral Habenula ◽  
Raphé Nuclei ◽  
Median Raphé

The dorsal raphe nucleus (DR) and median raphe nucleus (MR) contain populations of glutamatergic and GABAergic neurons that regulate diverse behavioral functions. However, their whole-brain input-output circuits remain incompletely elucidated. We used viral tracing combined with fluorescence micro-optical sectioning tomography to generate a comprehensive whole-brain atlas of inputs and outputs of glutamatergic and GABAergic neurons in the DR and MR. We found that these neurons received inputs from similar upstream brain regions. The glutamatergic and GABAergic neurons in the same raphe nucleus had divergent projection patterns with differences in critical brain regions. Specifically, MR glutamatergic neurons projected to the lateral habenula through multiple pathways. Correlation and cluster analysis revealed that glutamatergic and GABAergic neurons in the same raphe nucleus received heterogeneous inputs and sent different collateral projections. This connectivity atlas further elucidates the anatomical architecture of the raphe nuclei, which could facilitate better understanding of their behavioral functions.

scholarly journals Directed brain connectivity identifies widespread functional network changes in Parkinson’s disease

2021 ◽  
Author(s):  
Mite Mijalkov ◽  
Giovanni Volpe ◽  
Joana B. Pereira
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Large Scale ◽  
Neurodegenerative Disorder ◽  
Brain Connectivity ◽  
Brain Regions ◽  
New Method ◽  
Functional Network ◽  
Whole Brain ◽  
Functional Brain Networks

AbstractParkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by topological changes in large-scale functional brain networks. These networks are commonly analysed using undirected correlations between the activation signals of brain regions. However, this approach suffers from an important drawback: it assumes that brain regions get activated at the same time, despite previous evidence showing that brain activation features causality, with signals being typically generated in one region and then propagated to other ones. Thus, in order to address this limitation, in this study we developed a new method to assess whole-brain directed functional connectivity in patients with PD and healthy controls using anti-symmetric delayed correlations, which capture better this underlying causality. To test the potential of this new method, we compared it to standard connectivity analyses based on undirected correlations. Our results show that whole-brain directed connectivity identifies widespread changes in the functional networks of PD patients compared to controls, in contrast to undirected methods. These changes are characterized by increased global efficiency, clustering and transitivity as well as lower modularity. In addition, changes in the directed connectivity patterns in the precuneus, thalamus and superior frontal gyrus were associated with motor, executive and memory deficits in PD patients. Altogether, these findings suggest that directional brain connectivity is more sensitive to functional network changes occurring in PD compared to standard methods. This opens new opportunities for the analysis of brain connectivity and the development of new brain connectivity markers to track PD progression.

scholarly journals Cell type-specific modulation of sensory and affective components of itch in the periaqueductal gray

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Vijay K. Samineni ◽  
Jose G. Grajales-Reyes ◽  
Saranya S. Sundaram ◽  
Judy J. Yoo ◽  
Robert W. Gereau
Keyword(s):  
Neural Circuits ◽  
Periaqueductal Gray ◽  
Gabaergic Neurons ◽  
Cell Type ◽  
Glutamatergic Neurons ◽  
Neuronal Populations ◽  
Chronic Itch ◽  
Cell Type Specific ◽  
Bidirectional Modulation ◽  
Affective Components

Abstract Itch is a distinct aversive sensation that elicits a strong urge to scratch. Despite recent advances in our understanding of the peripheral basis of itch, we know very little regarding how central neural circuits modulate acute and chronic itch processing. Here we establish the causal contributions of defined periaqueductal gray (PAG) neuronal populations in itch modulation in mice. Chemogenetic manipulations demonstrate bidirectional modulation of scratching by neurons in the PAG. Fiber photometry studies show that activity of GABAergic and glutamatergic neurons in the PAG is modulated in an opposing manner during chloroquine-evoked scratching. Furthermore, activation of PAG GABAergic neurons or inhibition of glutamatergic neurons resulted in attenuation of scratching in both acute and chronic pruritis. Surprisingly, PAG GABAergic neurons, but not glutamatergic neurons, may encode the aversive component of itch. Thus, the PAG represents a neuromodulatory hub that regulates both the sensory and affective aspects of acute and chronic itch.

scholarly journals Functional connectivity predicts the dispositional use of expressive suppression but not cognitive reappraisal

2019 ◽  
Author(s):  
Daisy A. Burr ◽  
Tracy d'Arbeloff ◽  
Maxwell Elliott ◽  
Annchen R. Knodt ◽  
Bartholomew D. Brigidi ◽  
...  
Keyword(s):  
Individual Differences ◽  
Functional Connectivity ◽  
Brain Connectivity ◽  
Cognitive Reappraisal ◽  
Predictive Performance ◽  
Brain Regions ◽  
Expressive Suppression ◽  
Whole Brain ◽  
Functional Connections ◽  
Neural Signature

Previous research has identified specific brain regions associated with regulating emotion using common strategies such as expressive suppression and cognitive reappraisal. However, most research focuses on a priori regions and directs participants how to regulate, which may not reflect how people naturally regulate outside the laboratory. Here, we used a data-driven approach to investigate how individual differences in distributed intrinsic functional brain connectivity predict emotion regulation tendency. Specifically, we used connectome-based predictive modeling to extract functional connections in the brain significantly related to the dispositional use of suppression and reappraisal. These edges were then used in a predictive model and cross-validated in novel participants to identify a neural signature that reflects individual differences in the tendency to suppress and reappraise emotion. We found a significant neural signature for the dispositional use of suppression, but not reappraisal. Within this whole-brain signature, the intrinsic connectivity of the default mode network was most informative of suppression tendency. In addition, the predictive performance of this model was significant in males, but not females. These findings help inform how whole-brain networks of functional connectivity characterize how people tend to regulate emotion outside the laboratory.

Sign in / Sign up

Export Citation Format

Share Document