scholarly journals Distinctive BOLD Connectivity Patterns in the Schizophrenic Brain: Machine-learning based comparison between various connectivity measures

2016 ◽  
Author(s):  
Hio-Been Han
Keyword(s):  
Functional Connectivity ◽  
Memory Task ◽  
Similarity Measures ◽  
Low Frequency ◽  
Pattern Discrimination ◽  
Brain Regions ◽  
Connectivity Pattern ◽  
Time Frequency ◽  
Connectivity Patterns ◽  
Network Properties

AbstractRecent functional magnetic resonance imaging (fMRI) studies have found distinctive functional connectivity in the schizophrenic brain. However, most of the studies focused on the correlation value to define the functional connectivity for BOLD fluctuations between brain regions, which resulted in the limited understanding to the network properties of altered wirings in the schizophrenic brain. Here I characterized the distinctiveness of BOLD connectivity pattern in the schizophrenic brain relative to healthy brain with various similarity measures in the time-frequency domain, while participants are performing the working memory task in the MRI scanner. To assess the distinctiveness of the connectivity pattern, discrimination performances of the pattern classifier machine trained with each similarity measure were compared. Interestingly, the classifier machine trained by time-lagging patterns of low frequency fluctuation (LFF) produced higher classifying sensitivity than the machines trained by other measures. Also, the classifier machine trained by coherence pattern in LFF band also made better performance than the machine trained by correlation-based connectivity pattern. These results indicate that there are unobserved but considerable features in the functional connectivity pattern of schizophrenic brain which traditional emphasis on correlation analysis does not capture.

scholarly journals Effects of amnesia on processing in the hippocampus and default mode network during a naturalistic memory task: a case study

2018 ◽  
Author(s):  
Christiane Oedekoven ◽  
James L. Keidel ◽  
Stuart Anderson ◽  
Angus Nisbet ◽  
Chris Bird
Keyword(s):  
Functional Connectivity ◽  
Episodic Memory ◽  
Memory Performance ◽  
Memory Task ◽  
Structural Mri ◽  
Brain Regions ◽  
Left Hippocampus ◽  
Cortical Regions ◽  
The Right ◽  
Encoding And Retrieval

Despite their severely impaired episodic memory, individuals with amnesia are able to comprehend ongoing events. Online representations of a current event are thought to be supported by a network of regions centred on the posterior midline cortex (PMC). By contrast, episodic memory is widely believed to be supported by interactions between the hippocampus and these cortical regions. In this MRI study, we investigated the encoding and retrieval of lifelike events (video clips) in a patient with severe amnesia likely resulting from a stroke to the right thalamus, and a group of 20 age-matched controls. Structural MRI revealed grey matter reductions in left hippocampus and left thalamus in comparison to controls. We first characterised the regions activated in the controls while they watched and retrieved the videos. There were no differences in activation between the patient and controls in any of the regions. We then identified a widespread network of brain regions, including the hippocampus, that were functionally connected with the PMC in controls. However, in the patient there was a specific reduction in functional connectivity between the PMC and a region of left hippocampus when both watching and attempting to retrieve the videos. A follow up analysis revealed that in controls the functional connectivity between these regions when watching the videos was correlated with memory performance. Taken together, these findings support the view that the interactions between the PMC and the hippocampus enable the encoding and retrieval of multimodal representations of the contents of an event.

scholarly journals Large-scale network integration in the human brain tracks temporal fluctuations in memory encoding performance

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Ruedeerat Keerativittayayut ◽  
Ryuta Aoki ◽  
Mitra Taghizadeh Sarabi ◽  
Koji Jimura ◽  
Kiyoshi Nakahara
Keyword(s):  
Functional Connectivity ◽  
Human Brain ◽  
Large Scale ◽  
Brain Regions ◽  
Brain Network ◽  
Time Varying ◽  
Memory Encoding ◽  
Graph Metrics ◽  
Connectivity Patterns ◽  
Network States

Although activation/deactivation of specific brain regions has been shown to be predictive of successful memory encoding, the relationship between time-varying large-scale brain networks and fluctuations of memory encoding performance remains unclear. Here, we investigated time-varying functional connectivity patterns across the human brain in periods of 30–40 s, which have recently been implicated in various cognitive functions. During functional magnetic resonance imaging, participants performed a memory encoding task, and their performance was assessed with a subsequent surprise memory test. A graph analysis of functional connectivity patterns revealed that increased integration of the subcortical, default-mode, salience, and visual subnetworks with other subnetworks is a hallmark of successful memory encoding. Moreover, multivariate analysis using the graph metrics of integration reliably classified the brain network states into the period of high (vs. low) memory encoding performance. Our findings suggest that a diverse set of brain systems dynamically interact to support successful memory encoding.

scholarly journals How the Statistical Validation of Functional Connectivity Patterns Can Prevent Erroneous Definition of Small-World Properties of a Brain Connectivity Network

2012 ◽  
Vol 2012 ◽  
pp. 1-13 ◽  
Author(s):  
J. Toppi ◽  
F. De Vico Fallani ◽  
G. Vecchiato ◽  
A. G. Maglione ◽  
F. Cincotti ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Adjacency Matrix ◽  
Brain Connectivity ◽  
Small World ◽  
Connectivity Pattern ◽  
Edge Density ◽  
Statistical Validation ◽  
Common Procedure ◽  
Connectivity Patterns ◽  
Definition Of

The application of Graph Theory to the brain connectivity patterns obtained from the analysis of neuroelectrical signals has provided an important step to the interpretation and statistical analysis of such functional networks. The properties of a network are derived from the adjacency matrix describing a connectivity pattern obtained by one of the available functional connectivity methods. However, no common procedure is currently applied for extracting the adjacency matrix from a connectivity pattern. To understand how the topographical properties of a network inferred by means of graph indices can be affected by this procedure, we compared one of the methods extensively used in Neuroscience applications (i.e. fixing the edge density) with an approach based on the statistical validation of achieved connectivity patterns. The comparison was performed on the basis of simulated data and of signals acquired on a polystyrene head used as a phantom. The results showed (i) the importance of the assessing process in discarding the occurrence of spurious links and in the definition of the real topographical properties of the network, and (ii) a dependence of the small world properties obtained for the phantom networks from the spatial correlation of the neighboring electrodes.

scholarly journals Longitudinal Spatial Patterns of Intrinsic Brain Activity and Functional Connectivity in Upper Limb Amputees Patients

2020 ◽  
Author(s):  
bingbo bao ◽  
xuyun hua ◽  
haifeng wei ◽  
pengbo luo ◽  
hongyi zhu ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Spatial Patterns ◽  
Brain Plasticity ◽  
Brain Activity ◽  
Low Frequency ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Brain Network ◽  
Intrinsic Connectivity ◽  
Intrinsic Brain Activity

Abstract Background: Amputation in adults is a serious condition and most patients were associated with the remapping of representations in motor and sensory brain network. Methods: The present study includes 8 healthy volunteers and 16 patients with amputation. We use resting-state fMRI to investigate the local and extent brain plasticity in patients suffering from amputation simultaneously. Both the amplitude of low-frequency fluctuations (ALFF) and degree centrality (DC) were used for the assessment of neuroplasticity in central level. Results: We described changes in spatial patterns of intrinsic brain activity and functional connectivity in amputees in the present study and we found that not only the sensory and motor cortex, but also the related brain regions involved in the functional plasticity after upper extremity deafferentation. Conclusion: Our findings showed local and extensive cortical changes in the sensorimotor and cognitive-related brain regions, which may imply the dysfunction in not only sensory and motor function, but also sensorimotor integration and motor plan. The activation and intrinsic connectivity in the brain changed a lot showed correlation with the deafferentation status.

scholarly journals The more you know: Investigating why adults get a bigger memory boost from semantic congruency than children

2018 ◽  
Author(s):  
Wei-Chun Wang ◽  
Simona Ghetti ◽  
Garvin Brod ◽  
Silvia A. Bunge
Keyword(s):  
Functional Connectivity ◽  
Prior Knowledge ◽  
Source Memory ◽  
Multivariate Analyses ◽  
Memory Performance ◽  
Memory Task ◽  
Neural Substrates ◽  
Brain Regions ◽  
Age Related ◽  
With Memory

AbstractHumans possess the capacity to employ prior knowledge in the service of our ability to remember; thus, memory is oftentimes superior for information that is semantically congruent with our prior knowledge. This congruency benefit grows during development, but little is understood about neurodevelopmental differences that underlie this growth. Here, we sought to explore the brain mechanisms underlying these phenomena. To this end, we examined the neural substrates of semantically congruent vs. incongruent item-context associations in 116 children and 25 young adults who performed encoding and retrieval tasks during functional MRI data collection. Participants encoded item-context pairs by judging whether an item belonged in a scene. Episodic memory was then tested with a source memory task. Consistent with prior work, source memory accuracy improved with age, and was greater for congruent than incongruent pairs; further, this congruency benefit was greater in adults than children. Age-related differences were observed across univariate, functional connectivity, and multivariate analyses, particularly in lateral prefrontal cortex (PFC). In sum, our results revealed two general age differences. First, left ventrolateral/rostrolateral PFC exhibited age-related increases in univariate activity, as well as greater functional connectivity with temporal regions during the processing of congruency. Second, right rostrolateral PFC activation was associated with successfully encoded congruent associations in adults, but not children. Finally, multivariate analyses provided evidence for stronger veridical memory in adults than children in right ventrolateral PFC. These effects in right lateral PFC were significantly correlated with memory performance, implicating them in the process of remembering congruent associations. These results connect brain regions associated with top-down control in the congruency benefit and age-related improvements therein.

scholarly journals Causally informed activity flow models provide mechanistic insight into the emergence of cognitive processes from brain network interactions

2021 ◽  
Author(s):  
Ruben Sanchez-Romero ◽  
Takuya Ito ◽  
Ravi D. Mill ◽  
Stephen José Hanson ◽  
Michael W. Cole
Keyword(s):  
Functional Connectivity ◽  
Effective Connectivity ◽  
Pearson Correlation ◽  
Explanatory Power ◽  
Memory Task ◽  
Brain Regions ◽  
Brain Network ◽  
List Type ◽  
Flow Models ◽  
Insight Into

AbstractBrain activity flow models estimate the movement of task-evoked activity over brain connections to help explain the emergence of task-related functionality. Activity flow estimates have been shown to accurately predict task-evoked brain activations across a wide variety of brain regions and task conditions. However, these predictions have had limited explanatory power, given known issues with causal interpretations of the standard functional connectivity measures used to parameterize activity flow models. We show here that functional/effective connectivity (FC) measures grounded in causal principles facilitate mechanistic interpretation of activity flow models. Starting from Pearson correlation (the current field standard), we progress from FC measures with poor to excellent causal grounding, demonstrating a continuum of causal validity using simulations and empirical fMRI data. Finally, we apply a causal FC method to a dorsolateral prefrontal cortex region, demonstrating causal network mechanisms contributing to its strong activation during a 2-back (relative to a 0-back) working memory task. Together, these results reveal the promise of parameterizing activity flow models using causal FC methods to identify network mechanisms underlying cognitive computations in the human brain.Highlights-Activity flow models provide insight into how cognitive neural effects emerge from brain network interactions.-Functional connectivity methods grounded in causal principles facilitate mechanistic interpretations of task activity flow models.-Mechanistic activity flow models accurately predict task-evoked neural effects across a wide variety of brain regions and cognitive tasks.

scholarly journals No evidence for changes in GABA concentration, functional connectivity, or working memory following continuous theta burst stimulation over dorsolateral prefrontal cortex

2021 ◽  
Author(s):  
Tribikram Thapa ◽  
Joshua Hendrikse ◽  
Sarah Thompson ◽  
Chao Suo ◽  
Mana Biabani ◽  
...  
Keyword(s):  
Working Memory ◽  
Functional Connectivity ◽  
Memory Performance ◽  
Memory Task ◽  
Low Frequency ◽  
Theta Burst Stimulation ◽  
Gaba Concentration ◽  
Dorsolateral Prefrontal ◽  
Theta Burst ◽  
Continuous Theta Burst Stimulation

Continuous theta burst stimulation (cTBS) is thought to reduce cortical excitability and modulate functional connectivity, possibly by altering cortical inhibition at the site of stimulation. However, most evidence comes from the motor cortex and it remains unclear whether similar effects occur following stimulation over other brain regions. We assessed whether cTBS over left dorsolateral prefrontal cortex altered gamma aminobutyric acid (GABA) concentration, functional connectivity and brain dynamics at rest, and brain activation and memory performance during a working memory task. Seventeen healthy individuals participated in a randomised, sham-controlled, cross-over experiment. Before and after either real or sham cTBS, magnetic resonance spectroscopy was obtained at rest to measure GABA concentrations, whereas functional magnetic resonance imaging (fMRI) was recorded at rest and during an n-back working memory task to measure functional connectivity, brain dynamics (low-frequency fluctuations), and task-related patterns of brain activity. We could not find evidence for changes in GABA concentration (P=0.66, Bayes factor [BF10]=0.07), resting-state functional connectivity (P(FWE)>0.05), resting-state low-frequency fluctuations (P=0.88, BF10=0.04), blood-oxygen level dependent activity during the n-back task (P(FWE) >0.05), or working memory performance (P=0.13, BF10=0.05) following real or sham cTBS. Our findings add to a growing body of literature suggesting the effects of cTBS are highly variable between individuals and question the notion that cTBS is a universal 'inhibitory' paradigm.

scholarly journals Regionally Specific Regulation of Sensorimotor Network Connectivity Following Tactile Improvement

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Stefanie Heba ◽  
Melanie Lenz ◽  
Tobias Kalisch ◽  
Oliver Höffken ◽  
Lauren M. Schweizer ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Neural Plasticity ◽  
Resting State ◽  
Low Frequency ◽  
Sensory Stimulation ◽  
Brain Regions ◽  
Blood Oxygenation ◽  
Cortical Reorganization ◽  
Sensorimotor Network ◽  
Specific Regulation

Correlations between inherent, task-free low-frequency fluctuations in the blood oxygenation level-dependent (BOLD) signals of the brain provide a potent tool to delineate its functional architecture in terms of intrinsic functional connectivity (iFC). Still, it remains unclear how iFC is modulated during learning. We employed whole-brain resting-state magnetic resonance imaging prior to and after training-independent repetitive sensory stimulation (rSS), which is known to induce somatosensory cortical reorganization. We investigated which areas in the sensorimotor network are susceptible to neural plasticity (i.e., where changes in functional connectivity occurred) and where iFC might be indicative of enhanced tactile performance. We hypothesized iFC to increase in those brain regions primarily receiving the afferent tactile input. Strengthened intrinsic connectivity within the sensorimotor network after rSS was found not only in the postcentral gyrus contralateral to the stimulated hand, but also in associative brain regions, where iFC correlated positively with tactile performance or learning. We also observed that rSS led to attenuation of the network at higher cortical levels, which possibly promotes facilitation of tactile discrimination. We found that resting-state BOLD fluctuations are linked to behavioral performance and sensory learning, indicating that network fluctuations at rest are predictive of behavioral changes and neuroplasticity.

The Role of Anterior Cingulate Cortex in Working Memory is Shaped by Functional Connectivity

2005 ◽  
Vol 17 (7) ◽  
pp. 1026-1042 ◽  
Author(s):  
Agatha Lenartowicz ◽  
Anthony R. McIntosh
Keyword(s):  
Working Memory ◽  
Functional Connectivity ◽  
Memory Performance ◽  
Activity Patterns ◽  
Standard Condition ◽  
Memory Task ◽  
Anterior Cingulate ◽  
Connectivity Pattern ◽  
Attention And Memory ◽  
Speed Accuracy

The anterior cingulate (AC) cortex seems to be similarly engaged by attentional and memory processes. We tested the hypothesis that this common activation is best explained by changes in the regions interacting (functionally connected) with AC. Subjects were tested on two variants of a 2-back working memory task: a standard version with strong attentional demands, and a cued version that more strongly promoted memory retrieval. AC activation, measured with functional MRI, was found in both tasks, although more sustained in the standard condition. The regions functionally connected to the AC, and the relation of these activity patterns to memory performance, were completely different across tasks. In the standard task, the pattern related to a speed-accuracy tradeoff, whereas the connectivity pattern unique to the cued task related only to better accuracy. By virtue of these changing patterns of functional connectivity, the contribution of AC to attention-and memory-driven performance was similarly changed.

scholarly journals The olfactory bulb modulates entorhinal cortex oscillations during spatial working memory

2021 ◽  
Vol 71 (1) ◽  
Author(s):  
Morteza Salimi ◽  
Farhad Tabasi ◽  
Milad Nazari ◽  
Sepideh Ghazvineh ◽  
Alireza Salimi ◽  
...  
Keyword(s):  
Working Memory ◽  
Olfactory Bulb ◽  
Entorhinal Cortex ◽  
Spatial Working Memory ◽  
Memory Performance ◽  
Memory Task ◽  
Low Frequency ◽  
Rhythmic Activity ◽  
Brain Regions ◽  
Simultaneous Recording

AbstractCognitive functions such as working memory require integrated activity among different brain regions. Notably, entorhinal cortex (EC) activity is associated with the successful working memory task. Olfactory bulb (OB) oscillations are known as rhythms that modulate rhythmic activity in widespread brain regions during cognitive tasks. Since the OB is structurally connected to the EC, we hypothesized that OB could modulate EC activity during working memory performance. Herein, we explored OB–EC functional connectivity during spatial working memory performance by simultaneous recording local field potentials when rats performed a Y-maze task. Our results showed that the coherence of delta, theta, and gamma-band oscillations between OB and EC was increased during correct trials compared to wrong trials. Cross-frequency coupling analyses revealed that the modulatory effect of OBs low-frequency phase on EC gamma power and phase was enhanced when animals correctly performed working memory task. The influx of information from OB to EC was also increased at delta and gamma bands within correct trials. These findings indicated that the modulatory influence of OB rhythms on EC oscillations might be necessary for successful working memory performance.

Sign in / Sign up

Export Citation Format

Share Document