A review of brain oscillations in cognitive disorders and the role of neurotransmitters

Correlation between cerebral neurotransmitters levels by proton magnetic resonance spectroscopy and HbA1c in patients with type 2 diabetes

BACKGROUND

Cognitive dysfunction is the main manifestation of central neuropathy. Although cognitive impairments tend to be overlooked in patients with diabetes mellitus (DM), there is a growing body of evidence linking DM to cognitive dysfunction. Hyperglycemia is closely related to neurological abnormalities, while often disregarded in clinical practice. Changes in cerebral neurotransmitter levels are associated with a variety of neurological abnormalities and may be closely related to blood glucose control in patients with type 2 DM (T2DM).

AIM

To evaluate the concentrations of cerebral neurotransmitters in T2DM patients exhibiting different hemoglobin A1c (HbA1c) levels.

METHODS

A total of 130 T2DM patients were enrolled at the Department of Endocrinology of Shanghai East Hospital. The participants were divided into four groups according to their HbA1c levels using the interquartile method, namely Q1 (< 7.875%), Q2 (7.875%-9.050%), Q3 (9.050%-11.200%) and Q4 (≥ 11.200%). Clinical data were collected and measured, including age, height, weight, neck/waist/hip circumferences, blood pressure, comorbidities, duration of DM, and biochemical indicators. Meanwhile, neurotransmitters in the left hippocampus and left brainstem area were detected by proton magnetic resonance spectroscopy.

RESULTS

The HbA1c level was significantly associated with urinary microalbumin (mALB), triglyceride, low-density lipoprotein cholesterol (LDL-C), homeostasis model assessment of insulin resistance (HOMA-IR), and beta cell function (HOMA-β), N-acetylaspartate/creatine (NAA/Cr), and NAA/choline (NAA/Cho). Spearman correlation analysis showed that mALB, LDL-C, HOMA-IR and NAA/Cr in the left brainstem area were positively correlated with the level of HbA1c (P < 0.05), whereas HOMA-β was negatively correlated with the HbA1c level (P < 0.05). Ordered multiple logistic regression analysis showed that NAA/Cho [Odds ratio (OR): 1.608, 95% confidence interval (95%CI): 1.004-2.578, P < 0.05], LDL-C (OR: 1.627, 95%CI: 1.119-2.370, P < 0.05), and HOMA-IR (OR: 1.107, 95%CI: 1.031-1.188, P < 0.01) were independent predictors of poor glycemic control.

CONCLUSION

The cerebral neurotransmitter concentrations in the left brainstem area in patients with T2DM are closely related to glycemic control, which may be the basis for the changes in cognitive function in diabetic patients.

Electrophysiology Methods for Assessing of Neurodegenerative and Post-Traumatic Processes as Applied to Translational Research

Electrophysiological studies have long established themselves as reliable methods for assessing the functional state of the brain and spinal cord, the degree of neurodegeneration, and evaluating the effectiveness of therapy. In addition, they can be used to diagnose, predict functional outcomes, and test the effectiveness of therapeutic and rehabilitation programs not only in clinical settings, but also at the preclinical level. Considering the urgent need to develop potential stimulators of neuroregeneration, it seems relevant to obtain objective data when modeling neurological diseases in animals. Thus, in the context of the application of electrophysiological methods, not only the comparison of the basic characteristics of bioelectrical activity of the brain and spinal cord in humans and animals, but also their changes against the background of neurodegenerative and post-traumatic processes are of particular importance. In light of the above, this review will contribute to a better understanding of the results of electrophysiological assessment in neurodegenerative and post-traumatic processes as well as the possibility of translating these methods from model animals to humans.

Effects of different speed-accuracy instructions on perception in psychology experiments: evidence from event-related potential and oscillation

Introduction

In cognitive behavioral experiments, we often asked participants to make judgments within a deadline. However, the most common instruction of "do the task quickly and accurately" does not highlight the importance of the balance between being fast and accurate.

Methods

Our research aimed to explore how instructions about speed or accuracy affect perceptual process, focus on event-related potentials (ERPs) and event-related oscillations (EROs) of two brain responses for visual stimuli, known as P1 and N1. Additionally, we compared the conventional analysis approach with principal component analysis (PCA) based methods to analyze P1 and N1 ERP amplitude and ERO power.

Results

The results showed that individuals instructed to respond quickly had lower P1 amplitude and alpha ERO than those who prioritized accuracy, using the PCA-based approach. However, these two groups had no differences between groups in the N1 theta band using both methods. The traditional time-frequency analysis method could not detect any ERP or ERO distinctions between groups due to limitations in detecting specific components in time or frequency domains. That means PCA is effective in separating these components.

Discussion

Our findings indicate that the instructions given regarding speed and accuracy impact perceptual process of subjects during cognitive behavioral experiments. We suggest that future researchers should choose their instructions carefully, considering the purpose of study.

Neuronal hypofunction and network dysfunction in a mouse model at an early stage of tauopathy

We previously reported altered neuronal Ca 2+ dynamics in the motor cortex of 12-month-old JNPL3 tauopathy mice during quiet wakefulness or forced running, with a tau antibody treatment significantly restoring the neuronal Ca 2+ activity profile and decreasing pathological tau in these mice 1 . Whether neuronal functional deficits occur at an early stage of tauopathy and if tau antibody treatment is effective in younger tauopathy mice needed further investigation. In addition, neuronal network activity and neuronal firing patterns have not been well studied in behaving tauopathy models. In this study, we first performed in vivo two-photon Ca 2+ imaging in JNPL3 mice in their early stage of tauopathy at 6 months of age, compared to 12 month old mice and age-matched wild-type controls to evaluate neuronal functional deficits. At the animal level, frequency of neuronal Ca 2+ transients decreased only in 6 month old tauopathy mice compared to controls, and only when animals were running on a treadmill. The amplitude of neuronal transients decreased in tauopathy mice compared to controls under resting and running conditions in both age groups. Total neuronal activity decreased only in 6 month old tauopathy mice compared to controls under resting and running conditions. Within either tauopathy or wild-type group, only total activity decreased in older wild-type animals. The tauopathy mice at different ages did not differ in neuronal Ca 2+ transient frequency, amplitude or total activity. In summary, neuronal function did significantly attenuate at an early age in tauopathy mice compared to controls but interestingly did not deteriorate between 6 and 12 months of age. A more detailed populational analysis of the pattern of Ca 2+ activity at the neuronal level in the 6 month old cohort confirmed neuronal hypoactivity in layer 2/3 of primary motor cortex, compared to wild-type controls, when animals were either resting or running on a treadmill. Despite reduced activity, neuronal Ca 2+ profiles exhibited enhanced synchrony and dysregulated responses to running stimulus. Further ex vivo electrophysiological recordings revealed reduction of spontaneous excitatory synaptic transmission onto and in pyramidal neurons and enhanced excitability of inhibitory neurons in motor cortex, which were likely responsible for altered neuronal network activity in this region. Lastly, tau antibody treatment reduced pathological tau and gliosis partially restored the neuronal Ca 2+ activity deficits but failed to rescue altered network changes. Taken together, substantial neuronal and network dysfunction occurred in the early stage of tauopathy that was partially alleviated with acute tau antibody treatment, which highlights the importance of functional assessment when evaluating the therapeutic potential of tau antibodies.

Highlights

Layer 2/3 motor cortical neurons exhibited hypofunction in awake and behaving mice at the early stage of tauopathy.Altered neuronal network activity disrupted local circuitry engagement in tauopathy mice during treadmill running.Layer 2/3 motor cortical neurons in tauopathy mice exhibited enhanced neuronal excitability and altered excitatory synaptic transmissions.Acute tau antibody treatment reduced pathological tau and gliosis, and partially restored neuronal hypofunction profiles but not network dysfunction.

Emergence of complex oscillatory dynamics in the neuronal networks with long activity time of inhibitory synapses

The brain displays complex dynamics, including collective oscillations, and extensive research has been conducted to understand their generation. However, our understanding of how biological constraints influence these oscillations is incomplete. This study investigates the essential properties of neuronal networks needed to generate oscillations resembling those in the brain. A simple discrete-time model of interconnected excitable elements is developed, capable of closely resembling the complex oscillations observed in biological neural networks. In the model, synaptic connections remain active for a duration exceeding individual neuron activity. We show that the inhibitory synapses must exhibit longer activity than excitatory synapses to produce a diverse range of the dynamical states, including biologically plausible oscillations. Upon meeting this condition, the transition between different dynamical states can be controlled by external stochastic input to the neurons. The study provides a comprehensive explanation for the emergence of distinct dynamical states in neural networks based on specific parameters.

Neonatal hypoxia impairs serotonin release and cognitive functions in adult mice

Children who experienced moderate perinatal asphyxia (MPA) are at risk of developing long lasting subtle cognitive and behavioral deficits, including learning disabilities and emotional problems. The prefrontal cortex (PFC) regulates cognitive flexibility and emotional behavior. Neurons that release serotonin (5-HT) project to the PFC, and compounds modulating 5-HT activity influence emotion and cognition. Whether 5-HT dysregulations contribute to MPA-induced cognitive problems is unknown. We established a MPA mouse model, which displays recognition and spatial memory impairments and dysfunctional cognitive flexibility. We found that 5-HT expression levels, quantified by immunohistochemistry, and 5-HT release, quantified by in vivo microdialysis in awake mice, are reduced in PFC of adult MPA mice. MPA mice also show impaired body temperature regulation following injection of the 5-HT1A receptor agonist 8-OH-DPAT, suggesting the presence of deficits in 5-HT auto-receptor function on raphe neurons. Finally, chronic treatment of adult MPA mice with fluoxetine, an inhibitor of 5-HT reuptake transporter, or the 5-HT1A receptor agonist tandospirone rescues cognitive flexibility and memory impairments. All together, these data demonstrate that the development of 5-HT system function is vulnerable to moderate perinatal asphyxia. 5-HT hypofunction might in turn contribute to long-term cognitive impairment in adulthood, indicating a potential target for pharmacological therapies.

Breakdown of oscillatory effective networks in disorders of consciousness

INTRODUCTION

Combining transcranial magnetic stimulation with electroencephalography (TMS-EEG), oscillatory reactivity can be measured, allowing us to investigate the interaction between local and distant cortical oscillations. However, the extent to which human consciousness is related to these oscillatory effective networks has yet to be explored.

AIMS

We tend to investigate the link between oscillatory effective networks and brain consciousness, by monitoring the global transmission of TMS-induced oscillations in disorders of consciousness (DOC).

RESULTS

A cohort of DOC patients was included in this study, which included 28 patients with a minimally conscious state (MCS) and 20 patients with vegetative state/unresponsive wakefulness syndrome (VS/UWS). Additionally, 25 healthy controls were enrolled. The oscillatory reactivity to single-pulse TMS of the frontal, sensorimotor and parietal cortex was measured using event-related spectral perturbation of TMS-EEG. The temporal-spatial properties of the oscillatory reactivity were illustrated through life time, decay gradients and accumulative power. In DOC patients, an oscillatory reactivity was observed to be temporally and spatially suppressed. TMS-EEG of DOC patients showed that the oscillations did not travel as far in healthy controls, in terms of both temporal and spatial dimensions. Moreover, cortical theta reactivity was found to be a reliable indicator in distinguishing DOC versus healthy controls when TMS of the parietal region and in distinguishing MCS versus VS/UWS when TMS of the frontal region. Additionally, a positive correlation was observed between the Coma Recovery Scale-Revised scores of the DOC patients and the cortical theta reactivity.

CONCLUSIONS

The findings revealed a breakdown of oscillatory effective networks in DOC patients, which has implications for the use of TMS-EEG in DOC evaluation and offers a neural oscillation viewpoint on the neurological basis of human consciousness.

osl-dynamics, a toolbox for modeling fast dynamic brain activity

Neural activity contains rich spatiotemporal structure that corresponds to cognition. This includes oscillatory bursting and dynamic activity that span across networks of brain regions, all of which can occur on timescales of tens of milliseconds. While these processes can be accessed through brain recordings and imaging, modeling them presents methodological challenges due to their fast and transient nature. Furthermore, the exact timing and duration of interesting cognitive events are often a priori unknown. Here, we present the OHBA Software Library Dynamics Toolbox (osl-dynamics), a Python-based package that can identify and describe recurrent dynamics in functional neuroimaging data on timescales as fast as tens of milliseconds. At its core are machine learning generative models that are able to adapt to the data and learn the timing, as well as the spatial and spectral characteristics, of brain activity with few assumptions. osl-dynamics incorporates state-of-the-art approaches that can be, and have been, used to elucidate brain dynamics in a wide range of data types, including magneto/electroencephalography, functional magnetic resonance imaging, invasive local field potential recordings, and electrocorticography. It also provides novel summary measures of brain dynamics that can be used to inform our understanding of cognition, behavior, and disease. We hope osl-dynamics will further our understanding of brain function, through its ability to enhance the modeling of fast dynamic processes.

ERP-aligned delta transcranial alternating current stimulation modulates the P3 amplitude

The underlying mechanisms of the event-related potential (ERP) generation are still under debate. One popular model considers the ERP as a superposition of phase-resets of ongoing endogenous oscillations of different frequencies. Brain oscillations have been shown to be modulated by transcranial alternating current stimulation (tACS). Thus, it seems feasible, that an ERP could be altered by modulating the contributing oscillations using tACS. One possible approach would be to target a frequency-matched stimulation signal to a specific ERP-component. One possible target for such an approach is the P3, which appears as delta/theta oscillations in the frequency-domain. Thus, an ERP-aligned stimulation in the delta/theta-range might be suitable to force synchronization in the stimulated frequency band and thus increase the amplitude of the P3 component. Building on an existing paradigm, in the present study 21 healthy participants received individualized ERP-aligned delta tACS and control stimulation while performing a visual task. The visual stimulation was matched to the continuous tACS in order to align the tACS peak with the P3 peak. Both the P3 amplitude and the evoked delta power were significantly increased after ERP-aligned tACS but not after control stimulation. The investigated behavioral parameter showed no stimulation dependent effect. Our results may provide new insights into the debate on the contribution of phase-reset mechanisms to the generation of ERPs and offer new opportunities for clinical trials.

Theta and Gamma Activity Differences in Obsessive-Compulsive Disorder and Panic Disorder: Insights from Resting-State EEG with eLORETA

Background: Obsessive-compulsive disorder (OCD) and panic disorder (PD) are debilitating psychiatric conditions, yet their underlying neurobiological differences remain underexplored. This study aimed to directly compare resting-state EEGs in patients with OCD and PD, without a healthy control group, using the eLORETA method. Methods: We collected retrospective EEG data from 24 OCD patients and 22 PD patients who were hospitalized due to significant impairment in daily life functions. eLORETA was used to analyze the EEG data. Results: Heightened theta activity was observed in the anterior cingulate cortex (ACC) of OCD patients compared to PD patients (PD vs. OCD, t = -2.168, p < 0.05). Conversely, higher gamma activity was found in the medial frontal gyrus (MFG) and paracentral lobule (PCL) in PD patients (PD vs. OCD, t = 2.173, p < 0.05). Conclusions: Our findings highlight neurobiological differences between OCD and PD patients. Specifically, the increased theta activity in the ACC for OCD patients and elevated gamma activity in the MFG and PCL for PD patients offer preliminary insights into the neural mechanisms of these disorders. Further studies are essential to validate these results and delve deeper into the neural underpinnings.

Processing of attentional and emotional stimuli depends on retrospective response of foot pressure: Conceptualizing neuron-cognitive distribution in human brain

Cognitive function of human brain requires temporal execution of emotional or attentional tasks, or their inter-dependence influences. Smooth execution of such tasks requires spontaneous distribution of cognitive load at specific regions of brain based on its classification. A strong connectivity between peripheral sensors and central nervous system is thought to assist the cognitive load distribution effectively. Novelty of current study evaluates the modulation of foot pressure and its mapping with distributed cognitive load while executing attentional biased emotional tasks. Emotional stimulus in form of happy and sad faces with attentional paradigm drawn on them were used in the study. Behavioral results were measured with respect to the analysis of response time (RT) and response accuracy (%). Neurological signals were acquired using 10-channel EEG data acquisition system, whereas, another 6 channels were used to measure foot pressure in the left and right feet at three different locations of foot. Acquired signals were further analyzed in time and frequency domains to interpret the cognitive load distribution, and the influence of foot pressure on distribution of cognitive loads. We found that the foot pressure accelerated the response accuracy rate in attending the local scope of attention, which was not in the case of global scope of attention. This means that the global attention does not require any pressure from peripheral sensory neurons. Our event related potential (ERP) results revealed that the early sensory negative N100 characterized the processing of global scope of attention coupled with high-foot pressure. However, the late positive peak of P300 and P600 associated with local scope of attention along with high-foot pressure. The global scope of attention with low-foot pressure modulates delta and theta oscillations. These results largely contribute to the literature on cognitive neuroscience of attention and it corelation with the peripheral sensory foot pressure.

Identifying the distinct spectral dynamics of laminar-specific interhemispheric connectivity with bilateral line-scanning fMRI

Despite extensive efforts to identify interhemispheric functional connectivity (FC) with resting-state (rs-) fMRI, correlated low-frequency rs-fMRI signal fluctuation across homotopic cortices originates from multiple sources. It remains challenging to differentiate circuit-specific FC from global regulation. Here, we developed a bilateral line-scanning fMRI method to detect laminar-specific rs-fMRI signals from homologous forepaw somatosensory cortices with high spatial and temporal resolution in rat brains. Based on spectral coherence analysis, two distinct bilateral fluctuation spectral features were identified: ultra-slow fluctuation (<0.04 Hz) across all cortical laminae versus Layer (L) 2/3-specific evoked BOLD at 0.05 Hz based on 4 s on/16 s off block design and resting-state fluctuations at 0.08-0.1 Hz. Based on the measurements of evoked BOLD signal at corpus callosum (CC), this L2/3-specific 0.05 Hz signal is likely associated with neuronal circuit-specific activity driven by the callosal projection, which dampened ultra-slow oscillation less than 0.04 Hz. Also, the rs-fMRI power variability clustering analysis showed that the appearance of L2/3-specific 0.08-0.1 Hz signal fluctuation is independent of the ultra-slow oscillation across different trials. Thus, distinct laminar-specific bilateral FC patterns at different frequency ranges can be identified by the bilateral line-scanning fMRI method.

The EEG pen-on-paper sound: History and recent advances

The electroencephalogram (EEG) is one of the most useful technologies for brain research and clinical neurology, characterized by non-invasiveness and high time resolution. The acquired traces are visibly displayed, but various studies investigate the translation of brain waves in sound (i.e., a process called sonification). Several articles have been published since 1934 about the sonification of EEG traces, in the attempt to identify the "brain-sound." However, for a long time this sonification technique was not used for clinical purposes. The analog EEG was in fact already equipped with an auditory output, although rarely mentioned in scientific papers: the pen-on-paper noise made by the writer unit. EEG technologists often relied on the sound that pens made on paper to facilitate the diagnosis. This article provides a sample of analog video-EEG recordings with audio support representing the strengths of a combined visual-and-auditory detection of different types of seizures. The purpose of the present article is to illustrate how the analog EEG "sounded," as well as to highlight the advantages of this pen-writing noise. It was considered so useful that early digital EEG devices could be equipped with special software to duplicate it digitally. Even in the present days, the sonification can be considered as an attempt to modify the EEG practice using auditory neurofeedback with applications in therapeutic interventions, cognitive improvement, and basic research.

Neuroprotective Efficacy of Europinidin in Streptozotocin-Induced Memory Impairment by Modulation of Oxidative Stress, Inflammatory Mediators, and Cholinesterase Activity in Rats

Materials and Methods

Oral acute toxicity studies were performed to evaluate the toxicological effects of europinidin in animals. In this study, four different animal groups (n = 6) were used. Group I was the normal control, group II was the STZ-induced diabetes control, group III was STZ + europinidin-treated (10 mg/kg), and group IV was STZ + europinidin-treated (10 mg/kg). The efficacy of europinidin at a dose of 10 mg/kg and 20 mg/kg was studied with single-dose administration of streptozotocin, which experimentally induced memory impairments in Wistar male rats for 38 days. The mean body weight and blood glucose levels were recorded at the initial and end of the study. The two behavioural paradigms (Y-maze and Morris water maze) were performed to evaluate spatial and working memory in rats. The biochemical parameters such as acetylcholinesterase, choline acetyltransferase, superoxide dismutase, glutathione transferase, malonaldehyde, catalase, and nitric oxide level as hallmarks of oxidative stress were measured. Additionally, the proinflammatory parameters were also determined to evaluate the neuroinflammatory responses associated with streptozotocin such as tumor necrosis factor-alpha (TNF-α) interleukin-1β (IL-1β), interleukin (IL-6), nuclear factor-kappa B (NF-ƙB), interleukin (IL-10), and nuclear factor-erythroid factor 2-related factor 2 (Nrf2) in the perfused brain.

Results

The rats in the europinidin-treated group exhibited a significant restoration of body weight and blood glucose level as compared with the streptozotocin control group. Furthermore, europinidin significantly modulated the spatial and working memory in rats, when assessed through behavioural paradigms. Streptozotocin caused a significant alteration in biochemical, neuronal enzymatic, and neuroinflammatory parameters, which were significantly restored to normal levels by europinidin.

Conclusion

The present study attributed the neuroprotective efficacy of europinidin in experimental animal models by subsiding the several biomarkers of oxidative stress, neuroinflammation, and neuronal enzymatic activities.

Theta power and functional connectivity as neurophysiological markers of executive functions in individuals with cognitive complaints in daily life

Impairments in executive functions (EFs) are common across psychological disorders. Research into the neural oscillations underlying EFs has the potential to help understand these impairments and contribute to the development of interventions. The aim of this study is to assess theta power and functional theta connectivity in the sensor space of the regions of the superordinate network for the core EFs: conflict monitoring, response inhibition, set-shifting, and working memory updating. We recruited adults with self-reported everyday EFs complaints and formed two groups: one with attention deficit hyperactivity disorder (ADHD) (n=27) and another without any diagnosis (n=22), and compared them to controls (n=21) on the Stroop, Stop-signal, Switching, and N-back task using EEG. Power and functional connectivity analyses were conducted for four regions of interest: frontal-midline, frontolateral left and right, and parietal region. For all four EFs, the groups showed a dynamical increase in theta power over time in the four regions of interest, as well as in functional theta connectivity between these regions. Group differences were found especially for conflict monitoring, with differences in theta power in the frontal-midline and frontolateral right region. These neural markers are also associated with behavioural performance and complaints in daily life. For set-shifting, group differences were less pronounced and for response inhibition and working memory updating no group differences were observed.

Oscillatory Activities in Multiple Frequency Bands in Patients with Schizophrenia During Motion Perception

Patients with schizophrenia show impairment in binding stimulus features into coherent objects, which are reflected in disturbed oscillatory activities. This study aimed to identify disturbances in multiple oscillatory bands during perceptual organization of motion perception in patients with schizophrenia. EEG was recorded from healthy controls and patients with schizophrenia during continuous presentation of a motion stimulus which induces reversals between two exogenously generated perceptions. This stimulus was used to investigate differences in motion binding processes between healthy controls and patients with schizophrenia. EEG signals were transformed into frequency components by means of the Morlet wavelet transformation in order to analyse inter-trial coherences (ITC) in the delta (1-4 Hz), theta (4-7 Hz), alpha (8-12 Hz), and gamma (28-48 Hz) frequency bands during exogenous motion binding. Patients showed decreased delta-ITC in occipital and theta-ITC in central and parietal areas, while no significant differences were found for neither alpha nor gamma-ITCs. The present study provides one of the first insights on the oscillatory synchronizations related with the motion perception in schizophrenia. The ITC differences revealed alterations in the consistency of large-scale integration and transfer functions in patients with schizophrenia.

Heterogeneous mechanisms for synchronization of networks of resonant neurons under different E/I balance regimes

Rhythmic synchronization of neuronal firing patterns is a widely present phenomenon in the brain-one that seems to be essential for many cognitive processes. A variety of mechanisms contribute to generation and synchronization of network oscillations, ranging from intrinsic cellular excitability to network mediated effects. However, it is unclear how these mechanisms interact together. Here, using computational modeling of excitatory-inhibitory neural networks, we show that different synchronization mechanisms dominate network dynamics at different levels of excitation and inhibition (i.e. E/I levels) as synaptic strength is systematically varied. Our results show that with low synaptic strength networks are sensitive to external oscillatory drive as a synchronizing mechanism-a hallmark of resonance. In contrast, in a strongly-connected regime, synchronization is driven by network effects via the direct interaction between excitation and inhibition, and spontaneous oscillations and cross-frequency coupling emerge. Unexpectedly, we find that while excitation dominates network synchrony at low excitatory coupling strengths, inhibition dominates at high excitatory coupling strengths. Together, our results provide novel insights into the oscillatory modulation of firing patterns in different excitation/inhibition regimes.

Association between abnormal brain oscillations and cognitive performance in patients with bipolar disorder; Molecular mechanisms and clinical evidence

Brain oscillations have gained great attention in neuroscience during recent decades as functional building blocks of cognitive-sensory processes. Research has shown that oscillations in "alpha," "beta," "gamma," "delta," and "theta" frequency windows are highly modified in brain pathology, including in patients with cognitive impairment like bipolar disorder (BD). The study of changes in brain oscillations can provide fundamental knowledge for exploring neurophysiological biomarkers in cognitive impairment. The present article reviews findings from the role and molecular basis of abnormal neural oscillation and synchronization in the symptoms of patients with BD. An overview of the results clearly demonstrates that, in cognitive-sensory processes, resting and evoked/event-related electroencephalogram (EEG) spectra in the delta, theta, alpha, beta, and gamma bands are abnormally changed in patients with BD showing psychotic features. Abnormal oscillations have been found to be associated with several neural dysfunctions and abnormalities contributing to BD, including abnormal GABAergic neurotransmission signaling, hippocampal cell discharge, abnormal hippocampal neurogenesis, impaired cadherin and synaptic contact-based cell adhesion processes, extended lateral ventricles, decreased prefrontal cortical gray matter, and decreased hippocampal volume. Mechanistically, impairment in calcium voltage-gated channel subunit alpha1 I, neurotrophic tyrosine receptor kinase proteins, genes involved in brain neurogenesis and synaptogenesis like WNT3 and ACTG2, genes involved in the cell adhesion process like CDH12 and DISC1, and gamma-aminobutyric acid (GABA) signaling have been reported as the main molecular contributors to the abnormalities in resting-state low-frequency oscillations in BD patients. Findings also showed the association of impaired synaptic connections and disrupted membrane potential with abnormal beta/gamma oscillatory activity in patients with BD. Of note, the synaptic GABA neurotransmitter has been found to be a fundamental requirement for the occurrence of long-distance synchronous gamma oscillations necessary for coordinating the activity of neural networks between various brain regions. This article is protected by copyright. All rights reserved.

Increasing the Excitatory Drive Rescues Excitatory/Inhibitory Imbalance and Mismatch Negativity Deficit Caused by Parvalbumin Specific GluA1 Deletion

Disturbance in synaptic excitatory and inhibitory (E/I) transmission in the prefrontal cortex is considered a critical factor for cognitive dysfunction, a core symptom in schizophrenia. However, the cortical network pathophysiology induced by E/I imbalance is not well characterized, and an effective therapeutic strategy is lacking. In this study, we simulated imbalanced cortical network by using mice with parvalbumin neuron (PV) specific knockout of GluA1 (AMPA receptor subunit 1) (Gria1-PV KO) as an experimental model. Applying high-content confocal imaging and electrophysiological recordings in the medial prefrontal cortex (mPFC), we found structural and functional alterations in the local network of Gria1-PV KO mice. Additionally, we applied electroencephalography (EEG) to assess potential deficits in mismatch negativity (MMN), the standard readout in the clinic for measuring deviance detection and sensory information processing. Gria1-PV KO animals exhibited abnormal theta oscillation and MMN, which is consistent with clinical findings in cognitively impaired patients. Remarkably, we demonstrated that the glycine transporter 1 (GlyT1) inhibitor, Bitopertin, ameliorates E/I imbalance, hyperexcitability, and sensory processing malfunction in Gria1-PV KO mice. Our results suggest that PV-specific deletion of GluA1 might be an experimental approach for back translating the E/I imbalance observed in schizophrenic patients. Our work offers a systematic workflow to understand the effect of GlyT1 inhibition in restoring cortical network activity from single cells to local brain circuitry. This study highlights that selectively boosting NMDA receptor-mediated excitatory drive to enhance the network inhibitory transmission from interneurons to pyramidal neurons (PYs) is a potential therapeutic strategy for restoring E/I imbalance-associated cognitive-related abnormality.

Treatment effects on event-related EEG potentials and oscillations in Alzheimer's disease

Alzheimer's disease dementia (ADD) is the most diffuse neurodegenerative disorder belonging to mild cognitive impairment (MCI) and dementia in old persons. This disease is provoked by an abnormal accumulation of amyloid-beta and tauopathy proteins in the brain. Very recently, the first disease-modifying drug has been licensed with reserve (i.e., Aducanumab). Therefore, there is a need to identify and use biomarkers probing the neurophysiological underpinnings of human cognitive functions to test the clinical efficacy of that drug. In this regard, event-related electroencephalographic potentials (ERPs) and oscillations (EROs) are promising candidates. Here, an Expert Panel from the Electrophysiology Professional Interest Area of the Alzheimer's Association and Global Brain Consortium reviewed the field literature on the effects of the most used symptomatic drug against ADD (i.e., Acetylcholinesterase inhibitors) on ERPs and EROs in ADD patients with MCI and dementia at the group level. The most convincing results were found in ADD patients. In those patients, Acetylcholinesterase inhibitors partially normalized ERP P300 peak latency and amplitude in oddball paradigms using visual stimuli. In these same paradigms, those drugs partially normalize ERO phase-locking at the theta band (4-7 Hz) and spectral coherence between electrode pairs at the gamma (around 40 Hz) band. These results are of great interest and may motivate multicentric, double-blind, randomized, and placebo-controlled clinical trials in MCI and ADD patients for final cross-validation.

Ensemble of coupling forms and networks among brain rhythms as function of states and cognition

The current paradigm in brain research focuses on individual brain rhythms, their spatiotemporal organization, and specific pairwise interactions in association with physiological states, cognitive functions, and pathological conditions. Here we propose a conceptually different approach to understanding physiologic function as emerging behavior from communications among distinct brain rhythms. We hypothesize that all brain rhythms coordinate as a network to generate states and facilitate functions. We analyze healthy subjects during rest, exercise, and cognitive tasks and show that synchronous modulation in the micro-architecture of brain rhythms mediates their cross-communications. We discover that brain rhythms interact through an ensemble of coupling forms, universally observed across cortical areas, uniquely defining each physiological state. We demonstrate that a dynamic network regulates the collective behavior of brain rhythms and that network topology and links strength hierarchically reorganize with transitions across states, indicating that brain-rhythm interactions play an essential role in generating physiological states and cognition.

Characterizing Hippocampal Oscillatory Signatures Underlying Seizures in Temporal Lobe Epilepsy

Temporal Lobe Epilepsy (TLE) is a neurological condition characterized by focal brain hyperexcitability, resulting in abnormal neuronal discharge and uncontrollable seizures. The hippocampus, with its inherently highly synchronized firing patterns and relatively high excitability, is prone to epileptic seizures, and it is usually the focus of TLE. Researchers have identified hippocampal high-frequency oscillations (HFOs) as a salient feature in people with TLE and animal models of this disease, arising before or at the onset of the epileptic event. To a certain extent, these pathological HFOs have served as a marker and a potential target for seizure attenuation using electrical or optogenetic interventions. However, many questions remain about whether we can reliably distinguish pathological from non-pathological HFOs and whether they can tell us about the development of the disease. While this would be an arduous task to perform in humans, animal models of TLE provide an excellent opportunity to study the characteristics of HFOs in predicting how epilepsy evolves. This minireview will (1) summarize what we know about the oscillatory disruption in TLE, (2) summarize knowledge about oscillatory changes in the latent period and their role in predicting seizures, and (3) propose future studies essential to uncovering potential treatments based on early detection of pathological HFOs.

Combining the Katritzky Reaction and Paper Spray Ionization Mass Spectrometry for Enhanced Detection of Amino Acid Neurotransmitters in Mouse Brain Sections

This work describes the development of a system that combines a derivatization protocol based on the Katritzky reaction with paper spray ionization mass spectrometry (PSI-MS) for the analysis of amino acid neurotransmitters in mouse brain tissues. The system is relatively simple, consisting of spraying the derivatization solution onto a mouse brain section mounted on a glass slide, applying a small volume of solvent to moisten the sample, pressing a triangular paper onto the sample surface to transfer the sample constituents to the paper surface, and using the paper as a substrate for PSI-MS analysis. The Katritzky reaction facilitated the ionization of the amino acids by reacting a pyrylium salt with the amino group of the analytes, forming very stable pyridinium cations, which greatly increased the sensitivity of the PSI-MS analysis. Most of the intensities of the amino acids modified by the Katritzky reaction were more than 10 times greater than the nonderivatized ones. The system was applied for the analysis of brain sections obtained from mice with Parkinson's disease, and the amino acids gamma-aminobutyric acid (GABA) and glycine (Gly), two compounds very well-known in studies of Parkinson's disease, were readily detected. The results suggest that the Katritzky reaction combined with PSI-MS might offer a significant advance in the knowledge on protocols that improve the sensitivity of detection of crucial biological compounds.

Impaired spike-gamma coupling of area CA3 fast-spiking interneurons as the earliest functional impairment in the AppNL-G-F mouse model of Alzheimer's disease

In Alzheimer's disease (AD) the accumulation of amyloid-β (Aβ) correlates with degradation of cognition-relevant gamma oscillations. The gamma rhythm relies on proper neuronal spike-gamma coupling, specifically of fast-spiking interneurons (FSN). Here we tested the hypothesis that decrease in gamma power and FSN synchrony precede amyloid plaque deposition and cognitive impairment in AppNL-G-F knock-in mice (AppNL-G-F). The aim of the study was to evaluate the amyloidogenic pathology progression in the novel AppNL-G-F mouse model using in vitro electrophysiological network analysis. Using patch clamp of FSNs and pyramidal cells (PCs) with simultaneous gamma oscillation recordings, we compared the activity of the hippocampal network of wild-type mice (WT) and the AppNL-G-F mice at four disease stages (1, 2, 4, and 6 months of age). We found a severe degradation of gamma oscillation power that is independent of, and precedes Aβ plaque formation, and the cognitive impairment reported previously in this animal model. The degradation correlates with increased Aβ1-42 concentration in the brain. Analysis on the cellular level showed an impaired spike-gamma coupling of FSN from 2 months of age that correlates with the degradation of gamma oscillations. From 6 months of age PC firing becomes desynchronized also, correlating with reports in the literature of robust Aβ plaque pathology and cognitive impairment in the AppNL-G-F mice. This study provides evidence that impaired FSN spike-gamma coupling is one of the earliest functional impairment caused by the amyloidogenic pathology progression likely is the main cause for the degradation of gamma oscillations and consequent cognitive impairment. Our data suggests that therapeutic approaches should be aimed at restoring normal FSN spike-gamma coupling and not just removal of Aβ.

Application of Three Ecological Assessment Tools in Examining Chromatographic Methods for the Green Analysis of a Mixture of Dopamine, Serotonin, Glutamate and GABA: A Comparative Study

The assessment of greenness of analytical protocols is of great importance now to preserve the environment. Some studies have analyzed either only the neurotransmitters, dopamine, serotonin, glutamate, and gamma-aminobutyric acid (GABA), together or with other neurotransmitters and biomarkers. However, these methods have not been investigated for their greenness and were not compared with each other to find the optimum one. Therefore, this study aims to compare seven published chromatographic methods that analyzed the four neurotransmitters and their mixtures using the National Environmental Method Index, Analytical Eco-Scale Assessment (ESA), and Green Analytical Procedure Index (GAPI). As these methods cover both qualitative and quantitative aspects, they offer better transparency. Overall, GAPI showed maximum greenness throughout the analysis. Method 6 was proven to be the method of choice for analyzing the mixture, owing to its greenness, according to NEMI, ESA, and GAPI. Additionally, method 6 has a wide scope of application (13 components can be analyzed), high sensitivity (low LOQ values), and fast analysis (low retention times, especially for glutamate and GABA).

Prediction of cortical theta oscillations in humans for phase-locked visual stimulation

BACKGROUND

The timing of an event within an oscillatory phase is considered to be one of the key strategies used by the brain to code and process neural information. Whereas existing methods of studying this phenomenon are chiefly based on retrospective analysis of electroencephalography (EEG) data, we now present a method to study it prospectively. New method: We present a system that allows for the delivery of visual stimuli at a specific phase of the cortical theta oscillation by fitting a sine to raw surface EEG data to estimate and predict the phase. One noteworthy feature of the method is that it can minimize potentially confounding effects of previous trials by using only a short sequence of past data.

RESULTS

In a trial with 10 human participants we achieved a significant phase locking with an inter-trial phase coherence of 0.39. We demonstrated successful phase locking on synthetic signals with a signal-to-noise ratio of less than - 20 dB. Comparison with existing method(s): We compared the new method to an autoregressive method published in the literature and found the new method was superior in mean phase offset, circular standard deviation, and prediction latency.

CONCLUSIONS

By fitting sine waves to raw EEG traces, we locked visual stimuli to arbitrary phases within the theta oscillatory cycle of healthy humans.

EEG measures for clinical research in major vascular cognitive impairment: recommendations by an expert panel

Vascular contribution to cognitive impairment (VCI) and dementia is related to etiologies that may affect the neurophysiological mechanisms regulating brain arousal and generating electroencephalographic (EEG) activity. A multidisciplinary expert panel reviewed the clinical literature and reached consensus about the EEG measures consistently found as abnormal in VCI patients with dementia. As compared to cognitively unimpaired individuals, those VCI patients showed (1) smaller amplitude of resting state alpha (8-12 Hz) rhythms dominant in posterior regions; (2) widespread increases in amplitude of delta (< 4 Hz) and theta (4-8 Hz) rhythms; and (3) delayed N200/P300 peak latencies in averaged event-related potentials, especially during the detection of auditory rare target stimuli requiring participants' responses in "oddball" paradigms. The expert panel formulated the following recommendations: (1) the above EEG measures are not specific for VCI and should not be used for its diagnosis; (2) they may be considered as "neural synchronization" biomarkers to enlighten the relationships between features of the VCI-related cerebrovascular lesions and abnormalities in neurophysiological brain mechanisms; and (3) they may be tested in future clinical trials as prognostic biomarkers and endpoints of interventions aimed at normalizing background brain excitability and vigilance in wakefulness.

Differential auditory brain response abnormalities in two intellectual disability conditions: SYNGAP1 mutations and Down syndrome

OBJECTIVE

Altered sensory processing is common in intellectual disability (ID). Here, we study electroencephalographic responses to auditory stimulation in human subjects presenting a rare condition (mutations in SYNGAP1) which causes ID, epilepsy and autism.

METHODS

Auditory evoked potentials, time-frequency and inter-trial coherence analyses were used to compare subjects with SYNGAP1 mutations with Down syndrome (DS) and neurotypical (NT) participants (N = 61 ranging from three to 19 years of age).

RESULTS

Altered synchronization in the brain responses to sound were found in both ID groups. The SYNGAP1 mutations group showed less phase-locking in early time windows and lower frequency bands compared to NT, and in later time windows compared to NT and DS. Time-frequency analysis showed more power in beta-gamma in the SYNGAP1 group compared to NT participants.

CONCLUSIONS

This study indicated reduced synchronization as well as more high frequencies power in SYNGAP1 mutations, while maintained synchronization was found in the DS group. These results might reflect dysfunctional sensory information processing caused by excitation/inhibition imbalance, or an imperfect compensatory mechanism in SYNGAP1 mutations individuals.

SIGNIFICANCE

Our study is the first to reveal brain response abnormalities in auditory sensory processing in SYNGAP1 mutations individuals, that are distinct from DS, another ID condition.

Computational exploration of dynamic mechanisms of steady state visual evoked potentials at the whole brain level

Periodic visual stimulation can induce stable steady-state visual evoked potentials (SSVEPs) distributed in multiple brain regions and has potential applications in both neural engineering and cognitive neuroscience. However, the underlying dynamic mechanisms of SSVEPs at the whole-brain level are still not completely understood. Here, we addressed this issue by simulating the rich dynamics of SSVEPs with a large-scale brain model designed with constraints of neuroimaging data acquired from the human brain. By eliciting activity of the occipital areas using an external periodic stimulus, our model was capable of replicating both the spatial distributions and response features of SSVEPs that were observed in experiments. In particular, we confirmed that alpha-band (8-12 Hz) stimulation could evoke stronger SSVEP responses; this frequency sensitivity was due to nonlinear entrainment and resonance, and could be modulated by endogenous factors in the brain. Interestingly, the stimulus-evoked brain networks also exhibited significant superiority in topological properties near this frequency-sensitivity range, and stronger SSVEP responses were demonstrated to be supported by more efficient functional connectivity at the neural activity level. These findings not only provide insights into the mechanistic understanding of SSVEPs at the whole-brain level but also indicate a bright future for large-scale brain modeling in characterizing the complicated dynamics and functions of the brain.

Intermittent Light Exposures in Humans: A Case for Dual Entrainment in the Treatment of Alzheimer's Disease

Circadian sleep disorders are common among American adults and can become especially acute among older adults, especially those living with Alzheimer's disease (AD) and mild cognitive impairment (MCI), leading to the exacerbation of symptoms and contributing to the development and advancement of the diseases. This review explores the connections between circadian sleep disorders, cognition, and neurodegenerative disease, offering insights on rapidly developing therapeutic interventions employing intermittent light stimuli for improving sleep and cognition in persons with AD and MCI. Light therapy has the potential to affect sleep and cognition via at least two pathways: (1) a regular and robust light-dark pattern reaching the retina that promotes circadian phase shifting, which can promote entrainment and (2) 40 Hz flickering light that promotes gamma-wave entrainment. While this is a new area of research, preliminary evidence shows the potential of dual circadian and gamma-wave entrainment as an important therapy not only for those with AD, but for others with cognitive impairment.

Language Dysfunction in Schizophrenia: Assessing Neural Tracking to Characterize the Underlying Disorder(s)?

Deficits in language production and comprehension are characteristic of schizophrenia. To date, it remains unclear whether these deficits arise from dysfunctional linguistic knowledge, or dysfunctional predictions derived from the linguistic context. Alternatively, the deficits could be a result of dysfunctional neural tracking of auditory information resulting in decreased auditory information fidelity and even distorted information. Here, we discuss possible ways for clinical neuroscientists to employ neural tracking methodology to independently characterize deficiencies on the auditory-sensory and abstract linguistic levels. This might lead to a mechanistic understanding of the deficits underlying language related disorder(s) in schizophrenia. We propose to combine naturalistic stimulation, measures of speech-brain synchronization, and computational modeling of abstract linguistic knowledge and predictions. These independent but likely interacting assessments may be exploited for an objective and differential diagnosis of schizophrenia, as well as a better understanding of the disorder on the functional level-illustrating the potential of neural tracking methodology as translational tool in a range of psychotic populations.

Dance on the Brain: Enhancing Intra- and Inter-Brain Synchrony

Dance has traditionally been viewed from a Eurocentric perspective as a mode of self-expression that involves the human body moving through space, performed for the purposes of art, and viewed by an audience. In this Hypothesis and Theory article, we synthesize findings from anthropology, sociology, psychology, dance pedagogy, and neuroscience to propose The Synchronicity Hypothesis of Dance, which states that humans dance to enhance both intra- and inter-brain synchrony. We outline a neurocentric definition of dance, which suggests that dance involves neurobehavioral processes in seven distinct areas including sensory, motor, cognitive, social, emotional, rhythmic, and creative. We explore The Synchronicity Hypothesis of Dance through several avenues. First, we examine evolutionary theories of dance, which suggest that dance drives interpersonal coordination. Second, we examine fundamental movement patterns, which emerge throughout development and are omnipresent across cultures of the world. Third, we examine how each of the seven neurobehaviors increases intra- and inter-brain synchrony. Fourth, we examine the neuroimaging literature on dance to identify the brain regions most involved in and affected by dance. The findings presented here support our hypothesis that we engage in dance for the purpose of intrinsic reward, which as a result of dance-induced increases in neural synchrony, leads to enhanced interpersonal coordination. This hypothesis suggests that dance may be helpful to repattern oscillatory activity, leading to clinical improvements in autism spectrum disorder and other disorders with oscillatory activity impairments. Finally, we offer suggestions for future directions and discuss the idea that our consciousness can be redefined not just as an individual process but as a shared experience that we can positively influence by dancing together.

Characterization of Source-Localized EEG Activity During Sustained Deep-Tissue Pain

Musculoskeletal pain is a clinical condition that is characterized by ongoing pain and discomfort in the deep tissues such as muscle, bones, ligaments, nerves, and tendons. In the last decades, it was subject to extensive research due to its high prevalence. Still, a quantitative description of the electrical brain activity during musculoskeletal pain is lacking. This study aimed to characterize intracranial current source density (CSD) estimations during sustained deep-tissue experimental pain. Twenty-three healthy volunteers received three types of tonic stimuli for three minutes each: computer-controlled cuff pressure (1) below pain threshold (sustained deep-tissue no-pain, SDTnP), (2) above pain threshold (sustained deep-tissue pain, SDTP) and (3) vibrotactile stimulation (VT). The CSD in response to these stimuli was calculated in seven regions of interest (ROIs) likely involved in pain processing: contralateral anterior cingulate cortex, contralateral primary somatosensory cortex, bilateral anterior insula, contralateral dorsolateral prefrontal cortex, posterior parietal cortex and contralateral premotor cortex. Results showed that participants exhibited an overall increase in spectral power during SDTP in all seven ROIs compared to both SDTnP and VT, likely reflecting the differences in the salience of these stimuli. Moreover, we observed a difference is CSD due to the type of stimulus, likely reflecting somatosensory discrimination of stimulus intensity. These results describe the different contributions of neural oscillations within these brain regions in the processing of sustained deep-tissue pain.

Alpha Power and Functional Connectivity in Cognitive Decline: A Systematic Review and Meta-Analysis

Background:

Mild cognitive impairment (MCI) is a stage between expected age-related cognitive decline and dementia. Dementias have been associated with changes in neural oscillations across the frequency spectrum, including the alpha range. Alpha is the most prominent rhythm in human EEG and is best detected during awake resting state (RS). Though several studies measured alpha power and synchronization in MCI, findings have not yet been integrated.

Objective:

To consolidate findings on power and synchronization of alpha oscillations across stages of cognitive decline.

Methods:

We included studies published until January 2020 that compared power or functional connectivity between 1) people with MCI and cognitively healthy older adults (OA) or people with a neurodegenerative dementia, and 2) people with progressive and stable MCI. Random-effects meta-analyses were performed when enough data was available.

Results:

Sixty-eight studies were included in the review. Global RS alpha power was lower in AD than in MCI (ES = –0.30; 95% CI = –0.51, –0.10; k = 6), and in MCI than in OA (ES = –1.49; 95% CI = –2.69, –0.29; k = 5). However, the latter meta-analysis should be interpreted cautiously due to high heterogeneity. The review showed lower RS alpha power in progressive than in stable MCI, and lower task-related alpha reactivity in MCI than in OA. People with MCI had both lower and higher functional connectivity than OA. Publications lacked consistency in MCI diagnosis and EEG measures.

Conclusion:

Research indicates that RS alpha power decreases with increasing impairment, and could—combined with measures from other frequency bands—become a biomarker of early cognitive decline.

The role of norepinephrine in the pathophysiology of schizophrenia

Several lines of evidence have suggested for decades a role for norepinephrine (NE) in the pathophysiology and treatment of schizophrenia. Recent experimental findings reveal anatomical and physiological properties of the locus coeruleus-norepinephrine (LC-NE) system and its involvement in brain function and cognition. Here, we integrate these two lines of evidence. First, we review the functional and structural properties of the LC-NE system and its impact on functional brain networks, cognition, and stress, with special emphasis on recent experimental and theoretical advances. Subsequently, we present an update about the role of LC-associated functions for the pathophysiology of schizophrenia, focusing on the cognitive and motivational deficits. We propose that schizophrenia phenomenology, in particular cognitive symptoms, may be explained by an abnormal interaction between genetic susceptibility and stress-initiated LC-NE dysfunction. This in turn, leads to imbalance between LC activity modes, dysfunctional regulation of brain network integration and neural gain, and deficits in cognitive functions. Finally, we suggest how recent development of experimental approaches can be used to characterize LC function in schizophrenia.

Electrocortical dynamics differentiate athletes exhibiting low- and high- ACL injury risk biomechanics

Anterior cruciate ligament (ACL) injuries are physically and emotionally debilitating for athletes,while motor and biomechanical deficits that contribute to ACL injury have been identified, limited knowledge about the relationship between the central nervous system (CNS) and biomechanical patterns of motion has impeded approaches to optimize ACL injury risk reduction strategies. In the current study it was hypothesized that high-risk athletes would exhibit altered temporal dynamics in their resting state electrocortical activity when compared to low-risk athletes. Thirty-eight female athletes performed a drop vertical jump (DVJ) to assess their biomechanical risk factors related to an ACL injury. The athletes' electrocortical activity was also recorded during resting state in the same visit as the DVJ assessment. Athletes were divided into low- and high-risk groups based on their performance of the DVJ. Recurrence quantification analysis was used to quantify the temporal dynamics of two frequency bands previously shown to relate to sensorimotor and attentional control. Results revealed that high-risk participants showed more deterministic electrocortical behavior than the low-risk group in the frontal theta and central/parietal alpha-2 frequency bands. The more deterministic resting state electrocortical dynamics for the high-risk group may reflect maladaptive neural behavior-excessively stable deterministic patterning that makes transitioning among functional task-specific networks more difficult-related to attentional control and sensorimotor processing neural regions.

Video games as rich environments to foster brain plasticity

This chapter highlights the key role of two main factors, attentional control and reward processing, in unlocking brain plasticity. We first review the evidence for the role that each of these mechanisms plays in neuroplasticity, and then make the case that tools and technologies that combine these two are likely to result in maximal and broad, generalized benefits. In this context, we review the evidence concerning the impact of video game play on brain plasticity, with an eye toward plasticity-driving methods such as the seamless integration of neurofeedback into the video game platforms.

Alpha rhythm slowing in a modified thalamo-cortico-thalamic model related with Alzheimer's disease

A decrease in alpha band power is defined as a hallmark of electroencephalogram (EEG) in Alzheimer’s disease (AD). This study devotes to understanding the neuronal correlates of alpha rhythm slowing associated with AD from the view of neurocomputation. Firstly, a modified computational model of thalamo-cortico-thalamic (TCT) circuitry is constructed by incorporating two important biologically plausible ingredients. One is the disinhibition property between different inhibitory interneurons in the cortical module. The other is the full relay function of thalamic relay nucleus (TCR) to the cortical module. Then, by decreasing synaptic connectivity parameters to mimic the neuropathological condition of synapse loss in AD, the correlation between neuronal synaptic behavior and abnormal alpha rhythm is simulated by means of power spectral analysis. The results indicate that these decreases of synaptic activity, i.e., not only the excitatory synaptic connections from TCR to fast inhibitory interneurons C_fte and from excitatory interneurons to pyramidal neurons C_pxe but also the inhibitory synaptic connections from fast inhibitory interneurons to slow inhibitory interneurons C_lfi and from inhibitory interneurons to TCR C_tii, can significantly diminish the peak power density over the alpha band of the thalamic output, which implies that there is a slowing of alpha band. Furthermore, the underlying mechanism behind the alpha rhythmic changes is analyzed using nonlinear dynamical technique. The results reveal that decreases of C_fte, C_pxe, C_lfi and C_tii can make the thalamic module transfer from a limit cycle mode to a point attractor mode, which may lead to the alpha rhythm slowing in the modified TCT model. We expect this work can be helpful in identifying early biomarkers of AD’s EEG and understanding potential pathogenesis of AD.

Time Irreversibility of Resting-State Activity in the Healthy Brain and Pathology

Characterizing brain activity at rest is of paramount importance to our understanding both of general principles of brain functioning and of the way brain dynamics is affected in the presence of neurological or psychiatric pathologies. We measured the time-reversal symmetry of spontaneous electroencephalographic brain activity recorded from three groups of patients and their respective control group under two experimental conditions (eyes open and closed). We evaluated differences in time irreversibility in terms of possible underlying physical generating mechanisms. The results showed that resting brain activity is generically time-irreversible at sufficiently long time scales, and that brain pathology is generally associated with a reduction in time-asymmetry, albeit with pathology-specific patterns. The significance of these results and their possible dynamical etiology are discussed. Some implications of the differential modulation of time asymmetry by pathology and experimental condition are examined.

Flickering Red-Light Stimulus for Promoting Coherent 40 Hz Neural Oscillation: A Feasibility Study

BACKGROUND

Coherent 40 Hz (gamma) neural oscillation indicates healthy brain activity and is known to be disrupted in Alzheimer's disease (AD) patients. 40 Hz entrainment by flickering light is known to significantly attenuate AD pathology in mice.

OBJECTIVE

To demonstrate the feasibility of using a lighting intervention to promote coherent 40 Hz neural oscillation, improved working memory performance, and reduced subjective sleepiness among a population of healthy young adults. If successful, the intervention could be extended to address cognitive impairment associated with mild cognitive impairment and AD.

METHODS

Nine healthy participants (median age 22 years, five females) were exposed to one of two lighting conditions per session in a within-subjects counterbalanced manner. The study's two sessions were separated by 1 week. Custom-built light masks provided either a 40 Hz flickering red light (FRL) intervention or a dark control condition (i.e., total darkness, light mask not energized) at participants' eyes. Data were collected four times per session: pre-exposure, after 25-min exposure, after 50-min exposure, and post-exposure. Each data collection period included a Karolinska Sleepiness Scale report, an electroencephalogram, and working memory (n-back) auditory performance testing.

RESULTS

The FRL intervention induced a significant increase in 40 Hz power and a modest increase in low gamma power. The intervention had no significant impact on working memory performance and subjective sleepiness compared to the control. However, increases in 40 Hz power were significantly correlated with reduced subjective sleepiness.

CONCLUSION

The results clearly demonstrate the feasibility of using a flickering light to increase 40 Hz power.

Decomposed Temporal Complexity Analysis of Neural Oscillations and Machine Learning Applied to Alzheimer's Disease Diagnosis

Despite growing evidence of aberrant neuronal complexity in Alzheimer's disease (AD), it remains unclear how this variation arises. Neural oscillations reportedly comprise different functions depending on their own properties. Therefore, in this study, we investigated details of the complexity of neural oscillations by decomposing the oscillations into frequency, amplitude, and phase for AD patients. We applied resting-state magnetoencephalography (MEG) to 17 AD patients and 21 healthy control subjects. We first decomposed the source time series of the MEG signal into five intrinsic mode functions using ensemble empirical mode decomposition. We then analyzed the temporal complexities of these time series using multiscale entropy. Results demonstrated that AD patients had lower complexity on short time scales and higher complexity on long time scales in the alpha band in temporal regions of the brain. We evaluated the alpha band complexity further by decomposing it into amplitude and phase using Hilbert spectral analysis. Consequently, we found lower amplitude complexity and higher phase complexity in AD patients. Correlation analyses between spectral complexity and decomposed complexities revealed scale-dependency. Specifically, amplitude complexity was positively correlated with spectral complexity on short time scales, whereas phase complexity was positively correlated with spectral complexity on long time scales. Regarding the relevance of cognitive function to the complexity measures, the phase complexity on the long time scale was found to be correlated significantly with the Mini-Mental State Examination score. Additionally, we examined the diagnostic utility of the complexity characteristics using machine learning (ML) methods. We prepared a feature pool using multiple sparse autoencoders (SAEs), chose some discriminating features, and applied them to a support vector machine (SVM). Compared to the simple SVM and the SVM after feature selection (FS + SVM), the SVM with multiple SAEs (SAE + FS + SVM) had improved diagnostic accuracy. Through this study, we 1) advanced the understanding of neuronal complexity in AD patients using decomposed temporal complexity analysis and 2) demonstrated the effectiveness of combining ML methods with information about signal complexity for the diagnosis of AD.

Insights into the dynamic control of breathing revealed through cell-type-specific responses to substance P

The rhythm generating network for breathing must continuously adjust to changing metabolic and behavioral demands. Here, we examined network-based mechanisms in the mouse preBötzinger complex using substance P, a potent excitatory modulator of breathing frequency and stability, as a tool to dissect network properties that underlie dynamic breathing. We find that substance P does not alter the balance of excitation and inhibition during breaths or the duration of the resulting refractory period. Instead, mechanisms of recurrent excitation between breaths are enhanced such that the rate that excitation percolates through the network is increased. We propose a conceptual framework in which three distinct phases of inspiration, the burst phase, refractory phase, and percolation phase, can be differentially modulated to control breathing dynamics and stability. Unraveling mechanisms that support this dynamic control may improve our understanding of nervous system disorders that destabilize breathing, many of which involve changes in brainstem neuromodulatory systems.