Neural correlates of true and false memory in mild cognitive impairment

The role of brain oscillations in feature integration

Our sensory system is able to build a unified perception of the world, which although rich, is limited and inaccurate. Sometimes, features from different objects are erroneously combined. At the neural level, the role of the parietal cortex in feature integration is well-known. However, the brain dynamics underlying correct and incorrect feature integration are less clear. To explore the temporal dynamics of feature integration, we studied the modulation of different frequency bands in trials in which feature integration was correct or incorrect. Participants responded to the color of a shape target, surrounded by distractors. A calibration procedure ensured that accuracy was around 70% in each participant. To explore the role of expectancy in feature integration, we introduced an unexpected feature to the target in the last blocks of trials. Results demonstrated the contribution of several frequency bands to feature integration. Alpha and beta power was reduced for hits compared to illusions. Moreover, gamma power was overall larger during the experiment for participants who were aware of the unexpected target presented during the last blocks of trials (as compared to unaware participants). These results demonstrate that feature integration is a complex process that can go wrong at different stages of information processing and is influenced by top-down expectancies.

Parietal cortical alpha/beta suppression during prospective memory retrieval

Prospective memory (PM) impairment is among the most frequent memory complaints, yet little is known about the underlying neural mechanisms. PM for a planned intention may be achieved through strategic monitoring of the environment for cues, involving ongoing attentional processes, or through spontaneous retrieval. We hypothesized that parietal spectral power modulation accompanies prospectively encoded intention retrieval, irrespective of PM retrieval approach. A cognitively engaging arithmetic-based ongoing task (OGT) was employed to encourage spontaneous retrieval, with a focal, internally generated PM cue to eliminate OGT/PM trial differentiation based on perceptual or conceptual PM cue features. Two PM repetition frequencies were used to vary the extent of strategic monitoring. We observed a transient parietal alpha/beta spectral power reduction directly preceding the response, which was distinguishable on a single trial basis, as revealed by an OGT/PM trial classification rate exceeding 70% using linear discriminant analysis. The alpha/beta idling rhythm reflects cortical inhibition. A disengagement of task-relevant neural assemblies from this rhythm, reflected in alpha/beta power reduction, is deemed to increase information content, facilitate information integration, and enable engagement of neural assemblies in task-related cortical networks. The observed power reduction is consistent with the Dual Pathways model, where PM strategies converge at the PM retrieval stage.

Are there consistent abnormalities in event-related EEG oscillations in patients with Alzheimer's disease compared to other diseases belonging to dementia?

Cerebrospinal and structural-molecular neuroimaging in-vivo biomarkers are recommended for diagnostic purposes in Alzheimer's disease (AD) and other dementias; however, they do not explain the effects of AD neuropathology on neurophysiological mechanisms underpinning cognitive processes. Here, an Expert Panel from the Electrophysiology Professional Interest Area of the Alzheimer's Association reviewed the field literature and reached consensus on the event-related electroencephalographic oscillations (EROs) that show consistent abnormalities in patients with significant cognitive deficits due to Alzheimer's, Parkinson's (PD), Lewy body (LBD), and cerebrovascular diseases. Converging evidence from oddball paradigms showed that, as compared to cognitively unimpaired (CU) older adults, AD patients had lower amplitude in widespread delta (>4 Hz) and theta (4-7 Hz) phase-locked EROs as a function of disease severity. Similar effects were also observed in PD, LBD, and/or cerebrovascular cognitive impairment patients. Non-phase-locked alpha (8-12 Hz) and beta (13-30 Hz) oscillations were abnormally reduced (event-related desynchronization, ERD) in AD patients relative to CU. However, studies on patients with other dementias remain lacking. Delta and theta phase-locked EROs during oddball tasks may be useful neurophysiological biomarkers of cognitive systems at work in heuristic and intervention clinical trials performed in AD patients, but more research is needed regarding their potential role for other dementias.

Electrophysiological Studies of Cognitive Reappraisal Success and Failure in aMCI

BACKGROUND

Although successful reappraisal relies on cognitive resources, how cognitive impairment affects brain processes related to cognitive reappraisal is not yet clear.

METHODS

Forty-four amnestic mild cognitive impairment (aMCI) subjects and 72 healthy elderly controls (HECs) were divided into the MCI-Failure (n = 23), MCI-Success (n = 21), HEC-Failure (n = 26), and HEC-Success (n = 46) groups according to changes in self-reported affect using reappraisal. All participants viewed 30 negative and 30 neutral images preceded by straightforward descriptions of these images and 30 negative images preceded by more neutral descriptions.

RESULTS

Reappraisal failure was found to be more common in people with MCI. Reappraisal failure is associated with altered neurophysiological indices of negative-reappraisal stimuli processing that are reflected in smaller theta responsivity to negative-reappraisal stimuli between 350-550 ms. The MCI-Success group showed enhanced LPP for negative-reappraisal stimuli from 1200 to 3500 ms, reflecting compensatory effort to complete the reappraisal task, while subjects in other groups showed reduced LPP for negative-reappraisal stimuli from 550 to 1200 ms.

CONCLUSIONS

These findings deepen our understanding of how cognitive decline impacts reappraisal and informs early diagnosis and interventions for MCI.

Effect of valerian on cognitive disorders and electroencephalography in hemodialysis patients: a randomized, cross over, double-blind clinical trial

BACKGROUND

The prevalence of cognitive disorders in hemodialysis patients is twice as high as the general population, while these disorders often are undiagnosed. Timely prevention and treatment can improve their personal and social functions. Aim of study was determined the effect of Valerian on cognitive disorders and electroencephalography (EGG) in hemodialysis patients.

METHODS

This crossover, double-blind clinical trial was conducted on 39 hemodialysis patients. The patients were randomly divided into two groups. Group A (n = 19) took Valerian capsules and Group B (n = 20) received placebo capsules 60 min before bedtime for one month. The type of treatment was replaced between the two groups after a one-month wash-out. The Mini Mental State Examination (MMSE) questionnaire was completed and EGG was performed before and after intervention in both periods.

RESULTS

The cognitive scores of the Group valerian were increased significantly in the first (p = 0.003) and the second (p = 0.005) periods. In addition, the mean increase in the cognitive scores in the Group valerian was significant in the first (p = 0.028) and the second periods (p = 0.030). However, the changes in EGG showed no significant difference before and after intervention in two groups.

CONCLUSION

The findings of this study indicated that valerian could be effective and significantly improve patients' cognitive status; however, no significant changes were observed in the electroencephalography of the hemodialysis patients.

TRIAL REGISTRATION

IRCT201606076318N7 -2016-06-17.

Modulation of Working Memory Using Transcranial Electrical Stimulation: A Direct Comparison Between TACS and TDCS

Transcranial electrical stimulation (TES) has been considered a promising tool for improving working memory (WM) performance. Recent studies have demonstrated modulation of networks underpinning WM processing through application of transcranial alternating current (TACS) as well as direct current (TDCS) stimulation. Differences between study designs have limited direct comparison of the efficacy of these approaches, however. Here we directly compared the effects of theta TACS (6 Hz) and anodal TDCS on WM, applying TACS to the frontal-parietal loop and TDCS to the dorsolateral prefrontal cortex (DLPFC). WM was evaluated using a visual 2-back WM task. A within-subject, crossover design was applied (N = 30) in three separate sessions. TACS, TDCS, and sham stimulation were administered in a counterbalanced order, and the WM task was performed before, during, and after stimulation. Neither reaction times for hits (RT-hit) nor accuracy differed according to stimulation type with this study design. A marked practice effect was noted, however, with improvement in RT-hit irrespective of stimulation type, which peaked at the end of the second session. Pre-stimulation RT-hits in session three returned to the level observed pre-stimulation in session two, irrespective of stimulation type. The participants who received sham stimulation in session one and had therefore improved their performance due to practice alone, had thus reached a plateau by session two, enabling us to pool RT-hits from sessions two and three for these participants. The pooling allowed implementation of a within-subject crossover study design, with a direct comparison of the effects of TACS and TDCS in a subgroup of participants (N = 10), each of whom received both stimulation types, in a counterbalanced order, with pre-stimulation performance the same for both sessions. TACS resulted in a greater improvement in RT-hits than TDCS (F(2,18) = 4.31 p = 0.03). Our findings suggest that future work optimizing the application of TACS has the potential to facilitate WM performance.

Improving forecasting accuracy for stock market data using EMD-HW bagging

Many researchers documented that the stock market data are nonstationary and nonlinear time series data. In this study, we use EMD-HW bagging method for nonstationary and nonlinear time series forecasting. The EMD-HW bagging method is based on the empirical mode decomposition (EMD), the moving block bootstrap and the Holt-Winter. The stock market time series of six countries are used to compare EMD-HW bagging method. This comparison is based on five forecasting error measurements. The comparison shows that the forecasting results of EMD-HW bagging are more accurate than the forecasting results of the fourteen selected methods.

Neurophysiological correlates in Mild Cognitive Impairment detected using group Independent Component Analysis

Alzheimer's disease is the most prevalent cause of dementia. Mild Cognitive Impairment (MCI) is defined as a grey area between intact cognitive functioning and clinical dementia. Electroencephalography (EEG) has been used to identify biomarkers in dementia. Currently, there is a great interest in translating the study from raw signals to signal generators, trying to keep the relationship with neurophysiology. In the current study, EEG recordings during an encoding task were acquired in MCI subjects and healthy controls. Data was decomposed using group Independent Component Analysis (gICA) and the most neuronal components were analyzed using Phase Intertrial Coherence (PIC) and Phase shift Intertrial Coherence (PsIC). MCI subjects exhibited an increase of PIC in the theta band, while controls showed increase in PsIC in the alpha band. Correlation between PIC and PsIC and clinical scales were also found. Those findings indicate that the methodology proposed based in gICA can help to extract information from EEG recordings with neurophysiological meaning.

A critical review: coupling and synchronization analysis methods of EEG signal with mild cognitive impairment

At present, the clinical diagnosis of mild cognitive impairment (MCI) patients becomes the important approach of evaluating early Alzheimer's disease. The methods of EEG signal coupling and synchronization act as a key role in evaluating and diagnosing MCI patients. Recently, these coupling and synchronization methods were used to analyze the EEG signals of MCI patients according to different angles, and many important discoveries have been achieved. However, considering that every method is single-faceted in solving problems, these methods have various deficiencies when analyzing EEG signals of MCI patients. This paper reviewed in detail the coupling and synchronization analysis methods, analyzed their advantages and disadvantages, and proposed a few research questions needed to solve in the future. Also, the principles and best performances of these methods were described. It is expected that the performance analysis of these methods can provide the theoretical basis for the method selection of analyzing EEG signals of MCI patients and the future research directions.

Corticothalamic phase synchrony and cross-frequency coupling predict human memory formation

The anterior thalamic nucleus (ATN) is thought to play an important role in a brain network involving the hippocampus and neocortex, which enables human memories to be formed. However, its small size and location deep within the brain have impeded direct investigation in humans with non-invasive techniques. Here we provide direct evidence for a functional role for the ATN in memory formation from rare simultaneous human intrathalamic and scalp electroencephalogram (EEG) recordings from eight volunteering patients receiving intrathalamic electrodes implanted for the treatment of epilepsy, demonstrating real-time communication between neocortex and ATN during successful memory encoding. Neocortical-ATN theta oscillatory phase synchrony of local field potentials and neocortical-theta-to-ATN-gamma cross-frequency coupling during presentation of complex photographic scenes predicted later memory for the scenes, demonstrating a key role for the ATN in human memory encoding.

Identification of under-detected periodicity in time-series microarray data by using empirical mode decomposition

Detecting periodicity signals from time-series microarray data is commonly used to facilitate the understanding of the critical roles and underlying mechanisms of regulatory transcriptomes. However, time-series microarray data are noisy. How the temporal data structure affects the performance of periodicity detection has remained elusive. We present a novel method based on empirical mode decomposition (EMD) to examine this effect. We applied EMD to a yeast microarray dataset and extracted a series of intrinsic mode function (IMF) oscillations from the time-series data. Our analysis indicated that many periodically expressed genes might have been under-detected in the original analysis because of interference between decomposed IMF oscillations. By validating a protein complex coexpression analysis, we revealed that 56 genes were newly determined as periodic. We demonstrated that EMD can be used incorporating with existing periodicity detection methods to improve their performance. This approach can be applied to other time-series microarray studies.

Exploration of the neural correlates of cerebral palsy for sensorimotor BCI control

Cerebral palsy (CP) includes a broad range of disorders, which can result in impairment of posture and movement control. Brain-computer interfaces (BCIs) have been proposed as assistive devices for individuals with CP. Better understanding of the neural processing underlying motor control in affected individuals could lead to more targeted BCI rehabilitation and treatment options. We have explored well-known neural correlates of movement, including event-related desynchronization (ERD), phase synchrony, and a recently-introduced measure of phase dynamics, in participants with CP and healthy control participants. Although present, significantly less ERD and phase locking were found in the group with CP. Additionally, inter-group differences in phase dynamics were also significant. Taken together these findings suggest that users with CP exhibit lower levels of motor cortex activation during motor imagery, as reflected in lower levels of ongoing mu suppression and less functional connectivity. These differences indicate that development of BCIs for individuals with CP may pose additional challenges beyond those faced in providing BCIs to healthy individuals.

Chiropractic management using a brain-based model of care for a 15-year-old adolescent boy with migraine headaches and behavioral and learning difficulties: a case report

OBJECTIVE

The purpose of this report is to describe chiropractic management, using a brain-based model of care, of a teen who had migraine headaches and several social and learning difficulties.

CLINICAL FEATURES

A 15-year-old adolescent boy with a chronic history of migraines and more than 10 years of learning and behavioral difficulties, including attention-deficit/hyperactivity disorder, obsessive compulsive disorder, and Tourette syndrome, presented for chiropractic care.

INTERVENTION AND OUTCOME

The patient received spinal manipulation and was given home physical coordination activities that were contralateral to the side of the involved basal ganglia and ipsilateral to the involved cerebellum, along with interactive metronome training. Quantitative changes were noted in neurological soft signs, tests of variables of attention Conners' Parent Rating Scale, the California Achievement Test, grade point, and reduction of medications. The patient reported qualitative improvements in tics, attention, reading, vision, health, relationships with his peers and his family, and self-esteem.

CONCLUSION

The patient with migraine headaches and learning difficulties responded well to the course of chiropractic care. This study suggests that there may be value in a brain-based model of care in the chiropractic management of conditions that are beyond musculoskeletal in nature.

Memory and self-neuroscientific landscapes

Relations between memory and the self are framed from a number of perspectives-developmental aspects, forms of memory, interrelations between memory and the brain, and interactions between the environment and memory. The self is seen as dividable into more rudimentary and more advanced aspects. Special emphasis is laid on memory systems and within them on episodic autobiographical memory which is seen as a pure human form of memory that is dependent on a proper ontogenetic development and shaped by the social environment, including culture. Self and episodic autobiographical memory are seen as interlocked in their development and later manifestation. Aside from content-based aspects of memory, time-based aspects are seen along two lines-the division between short-term and long-term memory and anterograde-future-oriented-and retrograde-past-oriented memory. The state dependency of episodic autobiographical is stressed and implications of it-for example, with respect to the occurrence of false memories and forensic aspects-are outlined. For the brain level, structural networks for encoding, consolidation, storage, and retrieval are discussed both by referring to patient data and to data obtained in normal participants with functional brain imaging methods. It is elaborated why descriptions from patients with functional or dissociative amnesia are particularly apt to demonstrate the facets in which memory, self, and personal temporality are interwoven.