scholarly journals Basal forebrain contributes to default mode network regulation

2018 ◽  
Vol 115 (6) ◽  
pp. 1352-1357 ◽  
Author(s):  
Jayakrishnan Nair ◽  
Arndt-Lukas Klaassen ◽  
Jozsef Arato ◽  
Alexei L. Vyssotski ◽  
Michael Harvey ◽  
...  

The default mode network (DMN) is a collection of cortical brain regions that is active during states of rest or quiet wakefulness in humans and other mammalian species. A pertinent characteristic of the DMN is a suppression of local field potential gamma activity during cognitive task performance as well as during engagement with external sensory stimuli. Conversely, gamma activity is elevated in the DMN during rest. Here, we document that the rat basal forebrain (BF) exhibits the same pattern of responses, namely pronounced gamma oscillations during quiet wakefulness in the home cage and suppression of this activity during active exploration of an unfamiliar environment. We show that gamma oscillations are localized to the BF and that gamma-band activity in the BF has a directional influence on a hub of the rat DMN, the anterior cingulate cortex, during DMN-dominated brain states. The BF is well known as an ascending, activating, neuromodulatory system involved in wake–sleep regulation, memory formation, and regulation of sensory information processing. Our findings suggest a hitherto undocumented role of the BF as a subcortical node of the DMN, which we speculate may be important for switching between internally and externally directed brain states. We discuss potential BF projection circuits that could underlie its role in DMN regulation and highlight that certain BF nuclei may provide potential target regions for up- or down-regulation of DMN activity that might prove useful for treatment of DMN dysfunction in conditions such as epilepsy or major depressive disorder.

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Caroline A. Wilson ◽  
Sarah Fouda ◽  
Shuzo Sakata

Abstract Neuronal activity can modify Alzheimer’s disease pathology. Overexcitation of neurons can facilitate disease progression whereas the induction of cortical gamma oscillations can reduce amyloid load and improve cognitive functions in mouse models. Although previous studies have induced cortical gamma oscillations by either optogenetic activation of cortical parvalbumin-positive (PV+) neurons or sensory stimuli, it is still unclear whether other approaches to induce gamma oscillations can also be beneficial. Here we show that optogenetic activation of PV+ neurons in the basal forebrain (BF) increases amyloid burden, rather than reducing it. We applied 40 Hz optical stimulation in the BF by expressing channelrhodopsin-2 (ChR2) in PV+ neurons of 5xFAD mice. After 1-h induction of cortical gamma oscillations over three days, we observed the increase in the concentration of amyloid-β42 in the frontal cortical region, but not amyloid-β40. Amyloid plaques were accumulated more in the medial prefrontal cortex and the septal nuclei, both of which are targets of BF PV+ neurons. These results suggest that beneficial effects of cortical gamma oscillations on Alzheimer’s disease pathology can depend on the induction mechanisms of cortical gamma oscillations.


2021 ◽  
Vol 15 ◽  
Author(s):  
Mohammad S. E. Sendi ◽  
Elaheh Zendehrouh ◽  
Charles A. Ellis ◽  
Zhijia Liang ◽  
Zening Fu ◽  
...  

Background: Schizophrenia affects around 1% of the global population. Functional connectivity extracted from resting-state functional magnetic resonance imaging (rs-fMRI) has previously been used to study schizophrenia and has great potential to provide novel insights into the disorder. Some studies have shown abnormal functional connectivity in the default mode network (DMN) of individuals with schizophrenia, and more recent studies have shown abnormal dynamic functional connectivity (dFC) in individuals with schizophrenia. However, DMN dFC and the link between abnormal DMN dFC and symptom severity have not been well-characterized.Method: Resting-state fMRI data from subjects with schizophrenia (SZ) and healthy controls (HC) across two datasets were analyzed independently. We captured seven maximally independent subnodes in the DMN by applying group independent component analysis and estimated dFC between subnode time courses using a sliding window approach. A clustering method separated the dFCs into five reoccurring brain states. A feature selection method modeled the difference between SZs and HCs using the state-specific FC features. Finally, we used the transition probability of a hidden Markov model to characterize the link between symptom severity and dFC in SZ subjects.Results: We found decreases in the connectivity of the anterior cingulate cortex (ACC) and increases in the connectivity between the precuneus (PCu) and the posterior cingulate cortex (PCC) (i.e., PCu/PCC) of SZ subjects. In SZ, the transition probability from a state with weaker PCu/PCC and stronger ACC connectivity to a state with stronger PCu/PCC and weaker ACC connectivity increased with symptom severity.Conclusions: To our knowledge, this was the first study to investigate DMN dFC and its link to schizophrenia symptom severity. We identified reproducible neural states in a data-driven manner and demonstrated that the strength of connectivity within those states differed between SZs and HCs. Additionally, we identified a relationship between SZ symptom severity and the dynamics of DMN functional connectivity. We validated our results across two datasets. These results support the potential of dFC for use as a biomarker of schizophrenia and shed new light upon the relationship between schizophrenia and DMN dynamics.


2018 ◽  
Vol 8 (12) ◽  
pp. e01186
Author(s):  
Tabea Kamp ◽  
Bettina Sorger ◽  
Caroline Benjamins ◽  
Lars Hausfeld ◽  
Rainer Goebel

2020 ◽  
Vol 6 (11) ◽  
pp. eaaz0087 ◽  
Author(s):  
Zirui Huang ◽  
Jun Zhang ◽  
Jinsong Wu ◽  
George A. Mashour ◽  
Anthony G. Hudetz

The ongoing stream of human consciousness relies on two distinct cortical systems, the default mode network and the dorsal attention network, which alternate their activity in an anticorrelated manner. We examined how the two systems are regulated in the conscious brain and how they are disrupted when consciousness is diminished. We provide evidence for a “temporal circuit” characterized by a set of trajectories along which dynamic brain activity occurs. We demonstrate that the transitions between default mode and dorsal attention networks are embedded in this temporal circuit, in which a balanced reciprocal accessibility of brain states is characteristic of consciousness. Conversely, isolation of the default mode and dorsal attention networks from the temporal circuit is associated with unresponsiveness of diverse etiologies. These findings advance the foundational understanding of the functional role of anticorrelated systems in consciousness.


2009 ◽  
Vol 21 (1-2) ◽  
pp. 77-91 ◽  
Author(s):  
Maija Pihlajamäki ◽  
Reisa A. Sperling

Alzheimer’s disease (AD) is the most common form of dementia in old age, and is characterized by prominent impairment of episodic memory. Recent functional imaging studies in AD have demonstrated alterations in a distributed network of brain regions supporting memory function, including regions of the default mode network. Previous positron emission tomography studies of older individuals at risk for AD have revealed hypometabolism of association cortical regions similar to the metabolic abnormalities seen in AD patients. In recent functional magnetic resonance imaging (fMRI) studies of AD, corresponding brain default mode regions have also been found to demonstrate an abnormal fMRI task-induced deactivation response pattern. That is, the relative decreases in fMRI signal normally observed in the default mode regions in healthy subjects performing a cognitive task are not seen in AD patients, or may even be reversed to a paradoxical activation response. Our recent studies have revealed alterations in the pattern of deactivation also in elderly individuals at risk for AD by virtue of their APOE e4 genotype, or evidence of mild cognitive impairment (MCI). In agreement with recent reports from other groups, these studies demonstrate that the pattern of fMRI task-induced deactivation is progressively disrupted along the continuum from normal aging to MCI and to clinical AD and more impaired in e4 carriers compared to non-carriers. These findings will be discussed in the context of current literature regarding functional imaging of the default network in AD and at-risk populations.


2013 ◽  
Vol 109 (5) ◽  
pp. 1250-1258 ◽  
Author(s):  
Oliver Hinds ◽  
Todd W. Thompson ◽  
Satrajit Ghosh ◽  
Julie J. Yoo ◽  
Susan Whitfield-Gabrieli ◽  
...  

We used real-time functional magnetic resonance imaging (fMRI) to determine which regions of the human brain have a role in vigilance as measured by reaction time (RT) to variably timed stimuli. We first identified brain regions where activation before stimulus presentation predicted RT. Slower RT was preceded by greater activation in the default-mode network, including lateral parietal, precuneus, and medial prefrontal cortices; faster RT was preceded by greater activation in the supplementary motor area (SMA). We examined the roles of these brain regions in vigilance by triggering trials based on brain states defined by blood oxygenation level-dependent activation measured using real-time fMRI. When activation of relevant neural systems indicated either a good brain state (increased activation of SMA) or a bad brain state (increased activation of lateral parietal cortex and precuneus) for performance, a target was presented and RT was measured. RTs on trials triggered by a good brain state were significantly faster than RTs on trials triggered by a bad brain state. Thus human performance was controlled by monitoring brain states that indicated high or low vigilance. These findings identify neural systems that have a role in vigilance and provide direct evidence that the default-mode network has a role in human performance. The ability to control and enhance human behavior based on brain state may have broad implications.


2019 ◽  
Vol 50 (6) ◽  
pp. 404-412 ◽  
Author(s):  
Berrie Gerrits ◽  
Madelon A. Vollebregt ◽  
Sebastian Olbrich ◽  
Hanneke van Dijk ◽  
Donna Palmer ◽  
...  

Studies have shown that specific networks (default mode network [DMN] and task positive network [TPN]) activate in an anticorrelated manner when sustaining attention. Related EEG studies are scarce and often lack behavioral validation. We performed independent component analysis (ICA) across different frequencies (source-level), using eLORETA-ICA, to extract brain-network activity during resting-state and sustained attention. We applied ICA to the voxel domain, similar to functional magnetic resonance imaging methods of analyses. The obtained components were contrasted and correlated to attentional performance (omission errors) in a large sample of healthy subjects (N = 1397). We identified one component that robustly correlated with inattention and reflected an anticorrelation of delta activity in the anterior cingulate and precuneus, and delta and theta activity in the medial prefrontal cortex and with alpha and gamma activity in medial frontal regions. We then compared this component between optimal and suboptimal attentional performers. For the latter group, we observed a greater change in component loading between resting-state and sustained attention than for the optimal performers. Following the National Institute of Mental Health Research Domain Criteria (RDoC) approach, we prospectively replicated and validated these findings in subjects with attention deficit/hyperactivity disorder. Our results provide further support for the “default mode interference hypothesis.”


2019 ◽  
Vol 286 (1908) ◽  
pp. 20191016 ◽  
Author(s):  
Amir-Homayoun Javadi ◽  
Eva Zita Patai ◽  
Eugenia Marin-Garcia ◽  
Aaron Margois ◽  
Heng-Ru M. Tan ◽  
...  

Successful navigation can require realizing the current path choice was a mistake and the best strategy is to retreat along the recent path: ‘back-track’. Despite the wealth of studies on the neural correlates of navigation little is known about backtracking. To explore the neural underpinnings of backtracking we tested humans during functional magnetic resonance imaging on their ability to navigate to a set of goal locations in a virtual desert island riven by lava which constrained the paths that could be taken. We found that on a subset of trials, participants spontaneously chose to backtrack and that the majority of these choices were optimal. During backtracking, activity increased in frontal regions and the dorsal anterior cingulate cortex, while activity was suppressed in regions associated with the core default-mode network. Using the same task, magnetoencephalography and a separate group of participants, we found that power in the alpha band was significantly decreased immediately prior to such backtracking events. These results highlight the importance for navigation of brain networks previously identified in processing internally-generated errors and that such error-detection responses may involve shifting the brain from default-mode states to aid successful spatial orientation.


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