scholarly journals Prefrontal, striatal, and VTA subnetwork dynamics during novelty and exploration

2021 ◽  
Author(s):  
Adam JO Dede ◽  
Nader Marzban ◽  
Ashutosh Mishra ◽  
Robert Reichert ◽  
Paul M Anderson ◽  
...  
Keyword(s):  
Time Series ◽  
Functional Connectivity ◽  
Information Exchange ◽  
Network Connectivity ◽  
Baseline Period ◽  
Male Rats ◽  
Memory Processing ◽  
Delta Band ◽  
Eigen Decomposition ◽  
Regional Clustering

Multiple distinct brain areas have been implicated in memory including the prefrontal cortex (PFC), striatum (STR), and ventral tegmental area (VTA). Information-exchange across these widespread networks requires flexible coordination at a fine time-scale. In the present study, we collected high-density recordings from the PFC, STR, and VTA of male rats during baseline, encoding, consolidation, and retrieval stages of memory formation. Novel sub-regional clustering analyses identified patterns of spatially restricted, temporally coherent, and frequency specific signals that were reproducible across days and were modulated by behavioral states. Clustering identified miniscule patches of neural tissue. Generalized eigen decomposition (GED) reduced each cluster to a single time series. Amplitude envelope correlation of the cluster time series was used to assess functional connectivity between clusters. Dense intra- and inter regional functional connectivity characterized the baseline period, with delta oscillations playing an outsized role. There was a dramatic pruning of network connectivity during encoding. Connectivity rebounded during consolidation, but connections in the theta band became stronger, and those in the delta band were weaker. Finally, during retrieval, connections were not as severely reduced as they had been during encoding, and specifically theta and higher-frequency connections were stronger. Underlying these connectivity changes, the anatomical extent of clusters observed in the gamma band in the PFC and in both the gamma and delta bands in the VTA changed markedly across behavioral conditions. These results demonstrate the brain's ability to reorganize functionally at both the intra- and inter-regional levels during different stages of memory processing.

scholarly journals Increased task-dependent functional connectivity by stimulation of the hippocampal network predicts memory enhancement

2019 ◽  
Author(s):  
Kristen N. Warren ◽  
Molly S. Hermiller ◽  
Aneesha S. Nilakantan ◽  
Joel L. Voss
Keyword(s):  
Functional Connectivity ◽  
Episodic Memory ◽  
Memory Retrieval ◽  
Medial Temporal Lobe ◽  
Network Connectivity ◽  
Network Control ◽  
Retrieval Task ◽  
Memory Processing ◽  
Hippocampal Network ◽  
Hippocampal Networks

AbstractSuccessful episodic memory involves dynamic increases in the coordination of activity across distributed hippocampal networks, including the posterior-medial network (PMN) and the anterior-temporal network (ATN). We tested whether this up-regulation of functional connectivity during memory processing can be enhanced within hippocampal networks by noninvasive stimulation, and whether such task-dependent connectivity enhancement predicts episodic memory improvement. Participants received stimulation targeting either the PMN or an out-of-network control location. We compared the effects of stimulation on fMRI connectivity measured during an autobiographical memory retrieval task versus during rest within the PMN and the ATN. PMN-targeted stimulation significantly increased connectivity during memory retrieval versus rest within the PMN. This effect was not observed in the ATN, or in either network due to control out-of-network stimulation. Task-dependent increases in connectivity due to PMN-targeted stimulation within the medial temporal lobe predicted improved performance of a separate episodic memory test. It is therefore possible to enhance the task-dependent regulation of hippocampal network connectivity that supports memory processing using noninvasive stimulation.

scholarly journals Glutamate connectivity associations converge upon the salience network in schizophrenia and healthy controls

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Robert A. McCutcheon ◽  
Toby Pillinger ◽  
Maria Rogdaki ◽  
Juan Bustillo ◽  
Oliver D. Howes
Keyword(s):  
Functional Connectivity ◽  
Frontal Cortex ◽  
Network Connectivity ◽  
Resonance Spectroscopy ◽  
Salience Network ◽  
Healthy Controls ◽  
1H Mrs ◽  
Before And After ◽  
Functional Brain Networks ◽  
The Relationship

AbstractAlterations in cortical inter-areal functional connectivity, and aberrant glutamatergic signalling are implicated in the pathophysiology of schizophrenia but the relationship between the two is unclear. We used multimodal imaging to identify areas of convergence between the two systems. Two separate cohorts were examined, comprising 195 participants in total. All participants received resting state functional MRI to characterise functional brain networks and proton magnetic resonance spectroscopy (1H-MRS) to measure glutamate concentrations in the frontal cortex. Study A investigated the relationship between frontal cortex glutamate concentrations and network connectivity in individuals with schizophrenia and healthy controls. Study B also used 1H-MRS, and scanned individuals with schizophrenia and healthy controls before and after a challenge with the glutamatergic modulator riluzole, to investigate the relationship between changes in glutamate concentrations and changes in network connectivity. In both studies the network based statistic was used to probe associations between glutamate and connectivity, and glutamate associated networks were then characterised in terms of their overlap with canonical functional networks. Study A involved 76 individuals with schizophrenia and 82 controls, and identified a functional network negatively associated with glutamate concentrations that was concentrated within the salience network (p < 0.05) and did not differ significantly between patients and controls (p > 0.85). Study B involved 19 individuals with schizophrenia and 17 controls and found that increases in glutamate concentrations induced by riluzole were linked to increases in connectivity localised to the salience network (p < 0.05), and the relationship did not differ between patients and controls (p > 0.4). Frontal cortex glutamate concentrations are associated with inter-areal functional connectivity of a network that localises to the salience network. Changes in network connectivity in response to glutamate modulation show an opposite effect compared to the relationship observed at baseline, which may complicate pharmacological attempts to simultaneously correct glutamatergic and connectivity aberrations.

scholarly journals Cerebral functional networks during sleep in young and older individuals

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Véronique Daneault ◽  
Pierre Orban ◽  
Nicolas Martin ◽  
Christian Dansereau ◽  
Jonathan Godbout ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Brain Plasticity ◽  
Network Connectivity ◽  
Sleep Stages ◽  
Functional Networks ◽  
Older Individuals ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Age Related ◽  
Light Sleep

AbstractEven though sleep modification is a hallmark of the aging process, age-related changes in functional connectivity using functional Magnetic Resonance Imaging (fMRI) during sleep, remain unknown. Here, we combined electroencephalography and fMRI to examine functional connectivity differences between wakefulness and light sleep stages (N1 and N2 stages) in 16 young (23.1 ± 3.3y; 7 women), and 14 older individuals (59.6 ± 5.7y; 8 women). Results revealed extended, distributed (inter-between) and local (intra-within) decreases in network connectivity during sleep both in young and older individuals. However, compared to the young participants, older individuals showed lower decreases in connectivity or even increases in connectivity between thalamus/basal ganglia and several cerebral regions as well as between frontal regions of various networks. These findings reflect a reduced ability of the older brain to disconnect during sleep that may impede optimal disengagement for loss of responsiveness, enhanced lighter and fragmented sleep, and contribute to age effects on sleep-dependent brain plasticity.

scholarly journals Effect of corpus callosum agenesis on the language network in children and adolescents

2021 ◽  
Author(s):  
Lisa Bartha-Doering ◽  
Ernst Schwartz ◽  
Kathrin Kollndorfer ◽  
Florian Ph. S. Fischmeister ◽  
Astrid Novak ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Corpus Callosum ◽  
Network Connectivity ◽  
Functional Language ◽  
Healthy Controls ◽  
Language Abilities ◽  
Verbal Abilities ◽  
Left And Right ◽  
Language Network

AbstractThe present study is interested in the role of the corpus callosum in the development of the language network. We, therefore, investigated language abilities and the language network using task-based fMRI in three cases of complete agenesis of the corpus callosum (ACC), three cases of partial ACC and six controls. Although the children with complete ACC revealed impaired functions in specific language domains, no child with partial ACC showed a test score below average. As a group, ACC children performed significantly worse than healthy controls in verbal fluency and naming. Furthermore, whole-brain ROI-to-ROI connectivity analyses revealed reduced intrahemispheric and right intrahemispheric functional connectivity in ACC patients as compared to controls. In addition, stronger functional connectivity between left and right temporal areas was associated with better language abilities in the ACC group. In healthy controls, no association between language abilities and connectivity was found. Our results show that ACC is associated not only with less interhemispheric, but also with less right intrahemispheric language network connectivity in line with reduced verbal abilities. The present study, thus, supports the excitatory role of the corpus callosum in functional language network connectivity and language abilities.

CNTM-03. Functional connectivity networks in patients with brain tumors and vascular lesions in the occipital cortex

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi224-vi225
Author(s):  
Katharina Rosengarth ◽  
Katharina Hense ◽  
Tina Plank ◽  
Mark Greenlee ◽  
Christina Wendl ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Brain Tumors ◽  
Visual Processing ◽  
Network Connectivity ◽  
Occipital Cortex ◽  
Brain Lesions ◽  
Vascular Lesions ◽  
Surrounding Tissue ◽  
Tumor Patients ◽  
Default Mode

Abstract OBJECTIVE Space-occupying brain lesions as brain tumors in the occipital lobe have only been sparsely investigated so far, as this localization is extremely rare with only 1% of cases. It is still unclear how this affects the overall organization of the visual system. We investigated functional connectivity of functional networks associated with higher visual processing between patients with occipital space-occupying lesion in the occipital cortex and healthy controls. METHODS 12 patients with brain tumors, 7 patients with vascular lesions in the occipital cortex and 19 healthy subjects matched for age and sex were included. During functional MRI patients and subjects performed a visual excentricity mapping task. Data analysis was done using CONN toolbox based on Matlab. See-to-ROI connectivities of 23 Regions of Interest (ROIs) implemented in the CONN toolbox which were assigned to the Default Mode, Visual, Salience, Dorsal Attention, and Frontoparietal network were assessed. For each subject, connectivity was calculated using Fischer transformed pairwise correlations. These correlations were first considered separately for each group in one-sample analyses and then compared between the groups. RESULTS Main results show, that compared to control subjects and vascular patients, tumor patients showed weaker intra-network connectivity of components of all networks except the default-network. Tumor patients showed even stronger between-network connectivity in the default-mode network compared to the other groups. Weaker connectivity was observed within the salience network in both patient groups compared to controls. CONCLUSION The results indicate that in the course of the disease, compensatory countermeasures take place in the brain against a brain tumor or a space-occupying brain lesion with the aim of maintaining the performance level and cognitive processes for as long as possible. However, more research is needed in this area to understand the mechanisms and effects of brain tumors and space-consuming brain lesions on surrounding tissue.

Type 1 diabetes affects the brain functional connectivity underlying working memory processing

2021 ◽  
Author(s):  
Geisa B. Gallardo‐Moreno ◽  
Francisco J. Alvarado‐Rodríguez ◽  
Rebeca Romo‐Vázquez ◽  
Hugo Vélez‐Pérez ◽  
Andrés A. González‐Garrido
Keyword(s):  
Working Memory ◽  
Type 1 Diabetes ◽  
Functional Connectivity ◽  
Memory Processing ◽  
Brain Functional Connectivity ◽  
The Brain

scholarly journals Selective increase of functional network connectivity in Arc-positive neuronal engrams after long-term potentiation

2020 ◽  
Author(s):  
Yuheng Jiang ◽  
Antonius M.J. VanDongen
Keyword(s):  
Functional Connectivity ◽  
Hippocampal Neurons ◽  
Network Effects ◽  
Network Connectivity ◽  
Long Term Potentiation ◽  
Early Gene ◽  
Memory Traces ◽  
Term Potentiation ◽  
Memory Engram

ABSTRACTNew tools in optogenetics and molecular biology have culminated in recent studies which mark immediate-early gene (IEG)-expressing neurons as memory traces or engrams. Although the activity-dependent expression of IEGs has been successfully utilised to label memory traces, their roles in engram specification is incompletely understood. Outstanding questions remain as to whether expression of IEGs can interplay with network properties such as functional connectivity and also if neurons expressing different IEGs are functionally distinct. We investigated the expression of Arc and c-Fos, two commonly utilised IEGs in memory engram specification, in cultured hippocampal neurons. After pharmacological induction of long-term potentiation (LTP) in the network, we noted an emergent network property of refinement in functional connectivity between neurons, characterized by a global down-regulation of network connectivity, together with strengthening of specific connections. Subsequently, we show that Arc expression correlates with the effects of network refinement, with Arc-positive neurons being selectively strengthened. Arc positive neurons were also found to be located in closer physical proximity to each other in the network. While the expression pattern of IEGs c-Fos and Arc strongly overlaps, Arc was more selectively expressed than c-Fos. These IEGs also act together in coding information about connection strength pruning. These results demonstrate important links between IEG expression and network connectivity, which serve to bridge the gap between cellular correlates and network effects in learning and memory.

scholarly journals Local GABA concentration is related to network-level resting functional connectivity

eLife ◽  
2014 ◽  
Vol 3 ◽  
Author(s):  
Charlotte J Stagg ◽  
Velicia Bachtiar ◽  
Ugwechi Amadi ◽  
Christel A Gudberg ◽  
Andrei S Ilie ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Primary Motor Cortex ◽  
Empirical Studies ◽  
Network Connectivity ◽  
Resting State Fmri ◽  
Resonance Spectroscopy ◽  
Resting State Networks ◽  
Inhibitory Neurotransmitter ◽  
Motor Network

Anatomically plausible networks of functionally inter-connected regions have been reliably demonstrated at rest, although the neurochemical basis of these ‘resting state networks’ is not well understood. In this study, we combined magnetic resonance spectroscopy (MRS) and resting state fMRI and demonstrated an inverse relationship between levels of the inhibitory neurotransmitter GABA within the primary motor cortex (M1) and the strength of functional connectivity across the resting motor network. This relationship was both neurochemically and anatomically specific. We then went on to show that anodal transcranial direct current stimulation (tDCS), an intervention previously shown to decrease GABA levels within M1, increased resting motor network connectivity. We therefore suggest that network-level functional connectivity within the motor system is related to the degree of inhibition in M1, a major node within the motor network, a finding in line with converging evidence from both simulation and empirical studies.

scholarly journals Joint estimation of neural sources and their functional connections from MEG data

2020 ◽  
Author(s):  
Narayan Puthanmadam Subramaniyam ◽  
Filip Tronarp ◽  
Simo Särkkä ◽  
Lauri Parkkonen
Keyword(s):  
Time Series ◽  
Functional Connectivity ◽  
Structural Connectivity ◽  
Identification Problem ◽  
Joint Estimation ◽  
Bayesian Filtering ◽  
Sequential Approach ◽  
Connectivity Structure ◽  
Saem Algorithm ◽  
Functional Connections

AbstractCurrent techniques to estimate directed functional connectivity from magnetoencephalography (MEG) signals involve two sequential steps; 1) Estimation of the sources and their amplitude time series from the MEG data by solving the inverse problem, and 2) fitting a multivariate autoregressive (MVAR) model to these time series for the estimation of AR coefficients, which reflect the directed interactions between the sources. However, such a sequential approach is not optimal since i) source estimation algorithms typically assume that the sources are independent, ii) the information provided by the connectivity structure is not used to inform the estimation of source amplitudes, and iii) the limited spatial resolution of source estimates often leads to spurious connectivity due to spatial leakage.Here, we present an algorithm to jointly estimate the source and connectivity parameters using Bayesian filtering, which does not require anatomical constraints in form of structural connectivity or a-priori specified regions-of-interest. By formulating a state-space model for the locations and amplitudes of a given number of sources, we show that estimation of functional connectivity can be reduced to a system identification problem. We derive a solution to this problem using a variant of the expectation–maximization (EM) algorithm known as stochastic approximation EM (SAEM).Compared to the traditional two-step approach, the joint approach using the SAEM algorithm provides a more accurate reconstruction of connectivity parameters, which we show with a connectivity benchmark simulation as well as with an electrocorticography-based simulation of MEG data. Using real MEG responses to visually presented faces in 16 subjects, we also demonstrate that our method gives source and connectivity estimates that are both physiologically plausible and largely consistent across subjects. In conclusion, the proposed joint-estimation approach based on the SAEM algorithm outperforms the traditional two-step approach in determining functional connectivity structure in MEG data.

scholarly journals Multiple overlapping dynamic patterns of the visual sensory network in schizophrenia

2020 ◽  
Author(s):  
Mohammad S.E Sendi ◽  
Godfrey D Pearlson ◽  
Daniel H Mathalon ◽  
Judith M Ford ◽  
Adrian Preda ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Visual Processing ◽  
Information Transfer ◽  
Pearson Correlation ◽  
Visual Learning ◽  
Network Connectivity ◽  
Resting State Fmri ◽  
Connectivity Pattern ◽  
Middle Temporal Gyrus ◽  
Middle Temporal

Although visual processing impairments have been explored in schizophrenia (SZ), their underlying neurobiology of the visual processing impairments has not been widely studied. Also, while some research has hinted at differences in information transfer and flow in SZ, there are few investigations of the dynamics of functional connectivity within visual networks. In this study, we analyzed resting-state fMRI data of the visual sensory network (VSN) in 160 healthy control (HC) subjects and 151 SZ subjects. We estimated 9 independent components within the VSN. Then, we calculated the dynamic functional network connectivity (dFNC) using the Pearson correlation. Next, using k-means clustering, we partitioned the dFNCs into five distinct states, and then we calculated the portion of time each subject spent in each state, that we termed the occupancy rate (OCR). Using OCR, we compared HC with SZ subjects and investigated the link between OCR and visual learning in SZ subjects. Besides, we compared the VSN functional connectivity of SZ and HC subjects in each state. We found that this network is indeed highly dynamic. Each state represents a unique connectivity pattern of fluctuations in VSN FNC, and all states showed significant disruption in SZ. Overall, HC showed stronger connectivity within the VSN in states. SZ subjects spent more time in a state in which the connectivity between the middle temporal gyrus and other regions of VNS is highly negative. Besides, OCR in a state with strong positive connectivity between middle temporal gyrus and other regions correlated significantly with visual learning scores in SZ.

Sign in / Sign up

Export Citation Format

Share Document