Frontotemporal function]al connectivity and executive functions contribute to episodic memory performance

Assessing Cerebral Oxygen Metabolism Changes in Patients With Preeclampsia Using Voxel-Based Morphometry of Oxygen Extraction Fraction Maps in Magnetic Resonance Imaging

OBJECTIVE

The objective of this study was to analyze the different brain oxygen metabolism statuses in preeclampsia using magnetic resonance imaging and investigate the factors that affect cerebral oxygen metabolism in preeclampsia.

MATERIALS AND METHODS

Forty-nine women with preeclampsia (mean age 32.4 years; range, 18-44 years), 22 pregnant healthy controls (PHCs) (mean age 30.7 years; range, 23-40 years), and 40 non-pregnant healthy controls (NPHCs) (mean age 32.5 years; range, 20-42 years) were included in this study. Brain oxygen extraction fraction (OEF) values were computed using quantitative susceptibility mapping (QSM) plus quantitative blood oxygen level-dependent magnitude-based OEF mapping (QSM + quantitative blood oxygen level-dependent imaging or QQ) obtained with a 1.5-T scanner. Voxel-based morphometry (VBM) was used to investigate the differences in OEF values in the brain regions among the groups.

RESULTS

Among the three groups, the average OEF values were significantly different in multiple brain areas, including the parahippocampus, multiple gyri of the frontal lobe, calcarine, cuneus, and precuneus (all P-values were less than 0.05, after correcting for multiple comparisons). The average OEF values of the preeclampsia group were higher than those of the PHC and NPHC groups. The bilateral superior frontal gyrus/bilateral medial superior frontal gyrus had the largest size of the aforementioned brain regions, and the OEF values in this area were 24.2 ± 4.6, 21.3 ± 2.4, and 20.6 ± 2.8 in the preeclampsia, PHC, and NPHC groups, respectively. In addition, the OEF values showed no significant differences between NPHC and PHC. Correlation analysis revealed that the OEF values of some brain regions (mainly involving the frontal, occipital, and temporal gyrus) were positively correlated with age, gestational week, body mass index, and mean blood pressure in the preeclampsia group (r = 0.361-0.812).

CONCLUSION

Using whole-brain VBM analysis, we found that patients with preeclampsia had higher OEF values than controls.

Longitudinal investigation of executive function development employing task-based, teacher reports, and fNIRS multimethodology in 4- to 5-year-old children

Increased focus on resting-state functional connectivity (rsFC) and the use and accessibility of functional near-infrared spectroscopy (fNIRS) have advanced knowledge on the interconnected nature of neural substrates underlying executive function (EF) development in adults and clinical populations. Less is known about the relationship between rsFC and developmental changes in EF during preschool years in typically developing children, a gap the present study addresses employing task-based assessment, teacher reports, and fNIRS multimethodology. This preregistered study contributes to our understanding of the neural basis of EF development longitudinally with 41 children ages 4-5. Changes in prefrontal cortex (PFC) rsFC utilizing fNIRS, EF measured with a common task-based assessment (Day-Night task), and teacher reports of behavior (BRIEF-P) were monitored over multiple timepoints: Initial Assessment, 72 h follow-up, 1 Month Follow-up, and 4 Month Follow-up. Measures of rsFC were strongly correlated 72 h apart, providing evidence of high rsFC measurement reliability using fNIRS with preschool-aged children. PFC rsFC was positively correlated with performance on task-based and report-based EF assessments. Children's PFC functional connectivity at rest uniquely predicted later EF, controlling for verbal IQ, age, and sex. Functional connectivity at rest using fNIRS may potentially show the rapid changes in EF development in young children, not only neurophysiologically, but also as a correlate of task-based EF performance and ecologically-relevant teacher reports of EF in a classroom context.

Electroencephalogram Analysis of Magnetic Stimulation at Different Acupoints

Magnetic stimulation has some similarities with acupuncture, and it has broad application prospects because of its non-invasiveness and easy quantification. This paper combines magnetic stimulation technology with electroencephalography to analyze the time-frequency and the brain functional network results elicited by magnetic stimulation at different acupoints. This paper hopes to observe the different effects of stimulating different acupoints on the brain from the perspective of EEG. The EEG signals during magnetic stimulation at ST36, ST40, and GB37 were recorded, respectively. The time-frequency results showed that the magnetic stimulation at ST36 and ST40 on the Foot Yangming Stomach Meridian increased the energy in the left parietal lobe and the right central region, and the energy increased mainly in the theta and alpha bands. However, during the magnetic stimulation at GB37 on the Foot Shaoyang Gallbladder Meridian, the energy in the central region and the frontal lobe increased, and the energy increased mainly in the delta, theta, and alpha bands. Moreover, the energy in the right parietal lobe decreased during magnetic stimulation at GB37. The results of brain functional network were also consistent with time-frequency results. The brain network connections of GB37 stimulation in the central region were significantly less than that of ST36 and ST40 (p < 0.01). In addition, the connections between central region and frontal lobe and the connections between central region and parietal lobe of GB37 stimulation were significantly different from that of ST36 and ST40 (p < 0.01). The above results indicate that ST36 and ST40 on the same meridian have similar effects on the brain, while GB37 on the other meridian has completely different effects from ST36 and ST40. The results of this paper explain the reason why stimulating ST36 and ST40 can treat similar diseases from the perspective of EEG, and also explain that stimulating GB37 has significantly different effects on the brain from that of ST36 and ST40.

Electroacupuncture Alters BCI-Based Brain Network in Stroke Patients

Goal. Stroke patients are usually accompanied by motor dysfunction, which greatly affects daily life. Electroacupuncture is a kind of nondrug therapy that can effectively improve motor function. However, the effect of electroacupuncture is hard to be measured immediately in clinic. This paper is aimed to reveal the instant changes in brain activity of three groups of stroke patients before, during, and after the electroacupuncture treatment by the EEG analysis in the alpha band and beta band. Methods. Seven different functional connectivity indicators including Pearson correlation coefficient, spectral coherence, mutual information, phase locking value, phase lag index, partial directed coherence, and directed transfer function were used to build the BCI-based brain network in stroke patients. Results and Conclusion. The results showed that the brain activity based on the alpha band of EEG decreased after the electroacupuncture treatment, while in the beta band of EEG, the brain activity decreased only in the first two groups. Significance. This method could be used to evaluate the effect of electroacupuncture instantly and quantitatively. The study will hopefully provide some neurophysiological evidence of the relationship between changes in brain activity and the effects of electroacupuncture. The study of BCI-based brain network changes in the alpha and beta bands before, during, and after electroacupuncture in stroke patients of different periods is helpful in adjusting and selecting the electroacupuncture regimens for different patients. The trial was registered on the Chinese clinical trial registry (ChiCTR2000036959).

Understanding, Explanation, and Active Inference

While machine learning techniques have been transformative in solving a range of problems, an important challenge is to understand why they arrive at the decisions they output. Some have argued that this necessitates augmenting machine intelligence with understanding such that, when queried, a machine is able to explain its behaviour (i.e., explainable AI). In this article, we address the issue of machine understanding from the perspective of active inference. This paradigm enables decision making based upon a model of how data are generated. The generative model contains those variables required to explain sensory data, and its inversion may be seen as an attempt to explain the causes of these data. Here we are interested in explanations of one's own actions. This implies a deep generative model that includes a model of the world, used to infer policies, and a higher-level model that attempts to predict which policies will be selected based upon a space of hypothetical (i.e., counterfactual) explanations-and which can subsequently be used to provide (retrospective) explanations about the policies pursued. We illustrate the construct validity of this notion of understanding in relation to human understanding by highlighting the similarities in computational architecture and the consequences of its dysfunction.

Examining the limits of Memory-Guided Planning in 3- and 4-year olds

Stored memories may be drawn upon when accomplishing goals. In two experiments, we investigated limits on the ability to use episodic memories to support planning in 3- and 4-year-old children. We designed a new memory-guided planning task that required children to both retrieve memories and apply those memories to accomplish multiple, nested goals. We manipulated the difficulty of the task by varying the number of steps required to achieve the goals, and examined the impact of this manipulation on both memory retrieval and planning. We found that, overall, 4-year-olds outperformed 3-year-olds, but as task difficulty increased, all children made more errors. Analysis of these errors suggested that retrieval and planning processes might impose separate limits on memory-guided planning in early childhood, but that these limits may ease across early childhood.

Modulation Effect of Acupuncture on Functional Brain Networks and Classification of Its Manipulation With EEG Signals

Acupuncture manipulation is the key of Chinese medicine acupuncture therapy. In clinical practice, different acupuncture manipulations are required to achieve different therapeutic effects, which means it is crucial to distinguish different acupuncture manipulations. In this paper, we proposed a classification framework for different acupuncture manipulations, which employed the graph theory and machine learning method. Multichannel EEG signals evoked by acupuncture at "Zusanli" acupoint were recorded from healthy humans by two acupuncture manipulations: twirling-rotating (TR) and lifting-thrusting (LT). Phase locking value was used to estimate the phase synchronization of pair-wise EEG channels. It was found that acupunctured by TR manipulation exhibit significantly higher synchronization degree than acupunctured by LT manipulation. With the construction of functional brain network, the topological features of graph theory were extracted. Taken the network features as inputs, machine learning classifiers were established to classify acupuncture manipulations. The highest accuracy can achieve 92.14% with support vector machine. By further optimizing the network features utilized in machine learning classifiers, it was found that the combination of node betweenness and small world network index is the most effective factor for acupuncture manipulations classification. These findings suggested that our approach provides new ideas for automatically identify acupuncture manipulations from the perspective of functional brain networks and machine learning methods.

EEG coherence in theta, alpha, and beta bands in frontal regions and executive functions

Executive functions are higdevel cognitive processes that make possible the formation of flexible and adaptive goal-directed behaviors and the frontal lobes regulate these functions. The purpose of this study was to investigate the relationship between frontal EEG coherence in theta, alpha, and beta bands and executive functions in adults. A sample of 168 students (M_age = 25.44 years, SD = 4.52) were included in this study. EEG records were recorded at the psychology laboratory of Mohaghegh Ardabili University (Iran), then intrahemispheric and interhemispheric coherence of frontal regions were analyzed using the NeuroGuide software. The participants were asked to fill in the Adult Executive Skills Questionnaire. Correlational results showed that there is a positive relationship between executive functions and EEG coherence in theta, alpha, and beta bands in frontal regions of the left hemisphere, EEG coherence of alpha and beta bands in frontal regions of the right hemisphere and EEG coherence of alpha band between frontal regions of the two hemispheres. The results of the regression analysis also revealed that coherence of alpha, beta, and theta bands between left and right frontal regions and coherence of beta and theta bands in the left frontal regions predict executive functions. These results indicate that the common activity of frontal cortex, especially the left hemisphere, is associated with executive functions and cognitive control.

Ten years younger: Practice of chronic aerobic exercise improves attention and spatial memory functions in ageing

Aerobic exercise is associated with changes in brain morphology and improvement of cognitive functions. Physical activity may be especially important after age 60 when cognitive decline is more pronounced. In this paper, the effect of chronic practice of aerobic sports was studied in old adults by assessing their executive and mnesic functions, supported by frontal and temporal brain structures. Two groups were formed according to their age (60-69 and 70-79 years-old) including sportsmen (n = 23) and sedentary men (n = 24). Spatial memory and efficiency of attentional networks were measured, as well as general intelligence. Results showed that sportsmen outperformed sedentary participants in many of the tests employed. Thus their alerting, orienting and executive networks worked more effectively in the ANT-I task for executive functions, and they were more accurate in the spatial memory task, displaying a better spatial orientation. Scores in other neuropsychological tasks followed the same tendency. These data support the protective effect of aerobic exercise on cognitive functions.

Features of Resting-State Electroencephalogram Theta Coherence in Somatic Symptom Disorder Compared With Major Depressive Disorder: A Pilot Study

OBJECTIVE

Somatic symptom disorder (SSD) often co-occurs with major depressive disorder (MDD). Both conditions share common psychobiological and biobehavioral characteristics, but little is known about differential patterns in brain function. In this study, we compared resting-state functional brain connectivity between SSD and MDD using quantitative electroencephalography.

METHODS

Fifteen patients with SSD (SSD group), 15 patients with MDD (MDD group), and 15 healthy volunteers (healthy control [HC] group) participated in this study. Participants were assessed with quantitative electroencephalography using a 21-channel electroencephalogram system. Electroencephalogram coherence in the theta frequency range (3.5-7.5 Hz) was assessed between the following seven electrode pairs: Fp1 and Fp2, F7 and T3, F8 and T4, T5 and P3, P4 and T6, P3 and Pz, and Pz and P4. Differences in coherence between groups were analyzed using analysis of variance.

RESULTS

Theta coherence between the F7 and T3 electrodes was lower in the SSD group than the MDD and HC groups (F(2,42) = 6.67, p = .0030). Theta coherence between the T5 and P3 electrodes was lower in the SSD and MDD groups than the HC group (F(2,42) = 5.65, p = .0067). Theta coherence between the Pz and P4 electrodes was lower in the SSD group than the MDD group (F(2,42) = 6.41, p = .0037).

CONCLUSIONS

Both SSD and MDD patients commonly showed decreased functional connectivity within the left temporoparietal junction, which has neurophysiological implications for cognitive-attentional processing and social interaction. Frontostriatal circuit dysfunction affects processes that control perception and emotion, as well as misperception of somatosensory data in the parietal somatosensory area, and is more likely to be a neuropathology of SSD than MDD.

Single-trial EEG-informed fMRI analysis of emotional decision problems in hot executive function

BACKGROUND

Executive function refers to conscious control in psychological process which relates to thinking and action. Emotional decision is a part of hot executive function and contains emotion and logic elements. As a kind of important social adaptation ability, more and more attention has been paid in recent years.

OBJECTIVE

Gambling task can be well performed in the study of emotional decision. As fMRI researches focused on gambling task show not completely consistent brain activation regions, this study adopted EEG-fMRI fusion technology to reveal brain neural activity related with feedback stimuli.

METHODS

In this study, an EEG-informed fMRI analysis was applied to process simultaneous EEG-fMRI data. First, relative power-spectrum analysis and K-means clustering method were performed separately to extract EEG-fMRI features. Then, Generalized linear models were structured using fMRI data and using different EEG features as regressors.

RESULTS

The results showed that in the win versus loss stimuli, the activated regions almost covered the caudate, the ventral striatum (VS), the orbital frontal cortex (OFC), and the cingulate. Wide activation areas associated with reward and punishment were revealed by the EEG-fMRI integration analysis than the conventional fMRI results, such as the posterior cingulate and the OFC. The VS and the medial prefrontal cortex (mPFC) were found when EEG power features were performed as regressors of GLM compared with results entering the amplitudes of feedback-related negativity (FRN) as regressors. Furthermore, the brain region activation intensity was the strongest when theta-band power was used as a regressor compared with the other two fusion results.

CONCLUSIONS

The EEG-based fMRI analysis can more accurately depict the whole-brain activation map and analyze emotional decision problems.

Deqi Induction by HT7 Acupuncture Alters Theta and Alpha Band Coherence in Human Healthy Subjects

The aim of this preliminary study is to investigate the changes in phase synchronization in the theta and alpha bands before and during the performance of classical acupuncture on the Sinmun (HT7). The electroencephalogram (EEG) signals from nine healthy young subjects were recorded before and during acupuncture in the “closed-eye” state. The EEG signals were acquired from 19 surface scalp electrodes (FP1, FP2, F7, F3, Fz F4, F8, T3, C3, Cz, C4, T4, T5, P3, Pz, P4, T6, O1, and O2). Needles were inserted into the HT7 bilaterally and were then manipulated to induce deqi and retained for 15 minutes. Phase synchronization was measured by phase coherence. In the theta band, coherence significantly increased between the temporal (T5, T6) and occipital areas (O1, O2) during the acupuncture stimulation. In the alpha band, coherence significantly increased between the left temporal area (T5) and other areas (frontal, parietal, and occipital). Phase coherence in the theta and alpha bands tended to increase during the retention of the acupuncture needles after deqi. Therefore, it can be concluded that acupuncture stimulation with deqi is clinically effective via the central nervous system (CNS).