Changes In Oscillatory Activity Research Articles

Predicting brain age across the adult lifespan with spontaneous oscillations and functional coupling in resting brain networks captured with magnetoencephalography

Abstract The functional repertoire of the human brain changes dramatically throughout the developmental trajectories of early life and even all the way throughout the adult lifespan into older age. Capturing this arc is important to understand healthy brain ageing, and conversely, how injury and diseased states can lead to accelerated brain ageing. Regression modelling using lifespan imaging data can reliably predict an individual’s brain age based on expected arcs of ageing. One feature of brain function that is important in this respect, and understudied to date, is neural oscillations—the rhythmic fluctuations of brain activity that index neural cell assemblies and their functioning, as well as coordinating information flow around networks. Here, we analysed resting-state magnetoencephalography (MEG) recordings from 367 healthy participants aged 18 to 83, using two distinct statistical approaches to link neural oscillations and functional coupling with that of healthy ageing. Spectral power and leakage-corrected amplitude envelope correlations were calculated for each canonical frequency band from delta through gamma ranges. Spatially and spectrally consistent associations between healthy ageing and neurophysiological features were found across the applied methods, showing differential effects on neural oscillations, with decreasing amplitude of low frequencies throughout the adult lifespan, and increasing high-frequency amplitude. Functional connectivity within and between resting-state brain networks mediated by alpha coupling generally decreased throughout adulthood and increased in the beta band. Predictive modelling of brain age via regression showed an age-dependent prediction bias, resulting in overestimating the age of younger people (<40 years old) and underestimating the age of older individuals. These findings evidence strong age-related neurophysiological changes in oscillatory activity and functional networks of the brain as measured by resting-state MEG and that cortical oscillations are moderately reliable markers for predictive modelling. For researchers in the field of predictive brain age modelling with neurophysiological data, we recommend attention is paid to predictive biases for younger and older age ranges and consider using specific models for different age brackets. Nevertheless, these results suggest brain age prediction from MEG data can be used to model arcs of ageing throughout the adult lifespan and predict accelerated ageing in pathological brain states.

Better with age: Developmental changes in oscillatory activity during verbal working memory encoding and maintenance

Numerous investigations have characterized the oscillatory dynamics serving working memory in adults, but few have probed its relationship with chronological age in developing youth. We recorded magnetoencephalography during a modified Sternberg verbal working memory task in 82 youth participants aged 6–14 years old. Significant oscillatory responses were identified and imaged using a beamforming approach and the resulting whole-brain maps were probed for developmental effects during the encoding and maintenance phases. Our results indicated robust oscillatory responses in the theta (4–7 Hz) and alpha (8–14 Hz) range, with older participants exhibiting stronger alpha oscillations in left-hemispheric language regions. Older participants also had greater occipital theta power during encoding. Interestingly, there were sex-by-age interaction effects in cerebellar cortices during encoding and in the right superior temporal region during maintenance. These results extend the existing literature on working memory development by showing strong associations between age and oscillatory dynamics across a distributed network. To our knowledge, these findings are the first to link chronological age to alpha and theta oscillatory responses serving working memory encoding and maintenance, both across and between male and female youth; they reveal robust developmental effects in crucial brain regions serving higher order functions.

Altered age-related alpha and gamma prefrontal-occipital connectivity serving distinct cognitive interference variants

The presence of conflicting stimuli adversely affects behavioral outcomes, which could either be at the level of stimulus (Flanker), response (Simon), or both (Multisource). Briefly, flanker interference involves conflicting stimuli requiring selective attention, Simon interference is caused by an incongruity between the spatial location of the task-relevant stimulus and prepotent motor mapping, and multisource is combination of both. Irrespective of the variant, interference resolution necessitates cognitive control to filter irrelevant information and allocate neural resources to task-related goals. Though previously studied in healthy young adults, the direct quantification of changes in oscillatory activity serving such cognitive control and associated inter-regional interactions in healthy aging are poorly understood. Herein, we used an adapted version of the multisource interference task and magnetoencephalography to investigate age-related alterations in the neural dynamics governing both divergent and convergent cognitive interference in 78 healthy participants (age range: 20-66 years). We identified weaker alpha connectivity between bilateral visual and right dorsolateral prefrontal cortices (DLPFC) and left dorsomedial prefrontal cortices (dmPFC), as well as weaker gamma connectivity between bilateral occipital regions and the right dmPFC during flanker interference with advancing age. Further, an age-related decrease in gamma power was observed in the left cerebellum and parietal region for Simon and differential interference effects (i.e., flanker-Simon), respectively. Moreover, the superadditivity model showed decreased gamma power in the right temporoparietal junction (TPJ) with increasing age. Overall, our findings suggest age-related declines in the engagement of top-down attentional control secondary to reduced alpha and gamma coupling between prefrontal and occipital cortices.

Electrophysiological and Behavioral Effects of Alpha-Band Sensory Entrainment: Neural Mechanisms and Clinical Applications.

Alpha-band (7-13 Hz) activity has been linked to visuo-attentional performance in healthy participants and to impaired functionality of the visual system in a variety of clinical populations including patients with acquired posterior brain lesion and neurodevelopmental and psychiatric disorders. Crucially, several studies suggested that short uni- and multi-sensory rhythmic stimulation (i.e., visual, auditory and audio-visual) administered in the alpha-band effectively induces transient changes in alpha oscillatory activity and improvements in visuo-attentional performance by synchronizing the intrinsic brain oscillations to the external stimulation (neural entrainment). The present review aims to address the current state of the art on the alpha-band sensory entrainment, outlining its potential functional effects and current limitations. Indeed, the results of the alpha-band entrainment studies are currently mixed, possibly due to the different stimulation modalities, task features and behavioral and physiological measures employed in the various paradigms. Furthermore, it is still unknown whether prolonged alpha-band sensory entrainment might lead to long-lasting effects at a neural and behavioral level. Overall, despite the limitations emerging from the current literature, alpha-band sensory entrainment may represent a promising and valuable tool, inducing functionally relevant changes in oscillatory activity, with potential rehabilitative applications in individuals characterized by impaired alpha activity.

The effect of deep brain stimulation in Parkinson’s disease reflected in EEG microstates

Mechanisms of deep brain stimulation (DBS) on cortical networks were explored mainly by fMRI. Advanced analysis of high-density EEG is a source of additional information and may provide clinically useful biomarkers. The presented study evaluates EEG microstates in Parkinson’s disease and the effect of DBS of the subthalamic nucleus (STN). The association between revealed spatiotemporal dynamics of brain networks and changes in oscillatory activity and clinical examination were assessed. Thirty-seven patients with Parkinson’s disease treated by STN-DBS underwent two sessions (OFF and ON stimulation conditions) of resting-state EEG. EEG microstates were analyzed in patient recordings and in a matched healthy control dataset. Microstate parameters were then compared across groups and were correlated with clinical and neuropsychological scores. Of the five revealed microstates, two differed between Parkinson’s disease patients and healthy controls. Another microstate differed between ON and OFF stimulation conditions in the patient group and restored parameters in the ON stimulation state toward to healthy values. The mean beta power of that microstate was the highest in patients during the OFF stimulation condition and the lowest in healthy controls; sources were localized mainly in the supplementary motor area. Changes in microstate parameters correlated with UPDRS and neuropsychological scores. Disease specific alterations in the spatiotemporal dynamics of large-scale brain networks can be described by EEG microstates. The approach can reveal changes reflecting the effect of DBS on PD motor symptoms as well as changes probably related to non-motor symptoms not influenced by DBS.

Translating network activity in an Alzheimer mouse model to human Alzheimer's disease mutation carriers

AbstractBackgroundAlzheimer’s disease (AD) mouse models allow for the identification of cellular and molecular processes underlying neuronal network imbalance. In order to interpret these processes in a disease context, we need to link network changes in AD animals to those in human patients. Brain oscillations reflect neuronal network (im)balance and offer a tool to translate findings from mice to men. In this preliminary study, we investigate and compare cortical and hippocampal oscillatory activity using magnetoencephalography (MEG) in human patients and longitudinal electrophysiology recordings in AD mice.MethodsSource reconstructed resting state whole‐brain MEG of ten APP and PSEN1 mutation carriers and ten age‐ and gender‐matched control subjects were acquired. Carriers did not show objectively impaired cognitive functioning on any of the composite scores after extensive neuropsychological testing. Longitudinal local field potential recordings were obtained by implanted electrodes in APP/PS1 transgenic and wildtype controls from 3 until 10 months of age in different brain regions of the left hemisphere: hippocampus, prefrontal and parietal cortex. MEG analyses were constrained to similar brain regions. We estimated peak frequency, total (absolute broadband) and relative power across canonical frequency bands and compared these between human or mice mutation carriers and controls.ResultsHuman APP and PSEN1 mutation carriers showed lower peak frequency in the hippocampus and lower relative alpha 2 power in the precuneus and frontal cortex compared to controls (Fig1.). APP/PS1 mice also showed specific network alterations compared to wildtype control mice, but these seem to have more faster oscillations instead.ConclusionIn cognitively unimpaired human APP and PS1 mutation carriers we find oscillatory activity changes in the cortex and hippocampus, indicating network imbalance. However, opposite network changes are observed in the APP/PS1 AD mouse model compared to human mutation carriers using spectral measures. Future studies should explore other measures of network imbalance to identify potential cross‐species mechanistic links of early stage AD.

Developments in Transcranial Magnetic Stimulation to Study Human Cognition.

Developments in Transcranial Magnetic Stimulation to Study Human Cognition.

Evaluation and comparison of most prevalent artifact reduction methods for EEG acquired simultaneously with fMRI.

Multimodal neuroimaging using EEG and fMRI provides deeper insights into brain function by improving the spatial and temporal resolution of the acquired data. However, simultaneous EEG-fMRI inevitably compromises the quality of the EEG and fMRI signals due to the high degree of interaction between the two systems. Fluctuations in the magnetic flux flowing through the participant and the EEG system, whether due to movement within the magnetic field of the scanner or to changes in magnetic field strength, induce electrical potentials in the EEG recordings that mask the much weaker electrical activity of the neuronal populations. A number of different methods have been proposed to reduce MR artifacts. We present an overview of the most commonly used methods and an evaluation of the methods using three sets of diverse EEG data. We limited the evaluation to open-access and easy-to-use methods and a reference signal regression method using a set of six carbon-wire loops (CWL), which allowed evaluation of their added value. The evaluation was performed by comparing EEG signals recorded outside the MRI scanner with artifact-corrected EEG signals recorded simultaneously with fMRI. To quantify and evaluate the quality of artifact reduction methods in terms of the spectral content of the signal, we analyzed changes in oscillatory activity during a resting-state and a finger tapping motor task. The quality of artifact reduction in the time domain was assessed using data collected during a visual stimulation task. In the study we utilized hierarchical Bayesian probabilistic modeling for statistical inference and observed significant differences between the evaluated methods in the success of artifact reduction and associated signal quality in both the frequency and time domains. In particular, the CWL system proved superior to the other methods evaluated in improving spectral contrast in the alpha and beta bands and in recovering visual evoked responses. Based on the results of the evaluation study, we proposed guidelines for selecting the optimal method for MR artifact reduction.

Sleep disturbance and changes in oscillatory activity in a mouse model of depression: effects of sleep deprivation, ketamine and circadian clock modulation

Sleep disturbance and changes in oscillatory activity in a mouse model of depression: effects of sleep deprivation, ketamine and circadian clock modulation

Frequency-specific medial septal nucleus deep brain stimulation improves spatial memory in MK-801-treated male rats

BackgroundFew treatments exist for the cognitive symptoms of schizophrenia. Pharmacological agents resulting in glutamate N-methyl-d-aspartate (NMDA) receptor hypofunction, such as MK-801, mimic many of these symptoms and disrupt neural activity. Recent evidence suggests that deep brain stimulation (DBS) of the medial septal nucleus (MSN) can modulate medial prefrontal cortex (mPFC) and hippocampal activity and improve spatial memory. ObjectiveHere, we examine the effects of acute MK-801 administration on oscillatory activity within the septohippocampal circuit and behavior. We also evaluate the potential for MSN stimulation to improve cognitive behavioral measures following MK-801 administration. Methods59 Sprague Dawley male rats received either acute intraperitoneal (IP) saline vehicle injections or MK-801 (0.1 mg/kg). Theta (5–12 Hz), low gamma (30–50 Hz) and high frequency oscillatory (HFO) power were analyzed in the mPFC, MSN, thalamus and hippocampus. Rats underwent MSN theta (7.7 Hz), gamma (100 Hz) or no stimulation during behavioral tasks (Novel object recognition (NOR), elevated plus maze, Barnes maze (BM)). ResultsInjection of MK-801 resulted in frequency-specific changes in oscillatory activity, decreasing theta while increasing HFO power. Theta, but not gamma, stimulation enhanced the anxiolytic effects of MK-801 on the elevated plus maze. While MK-801 treated rats exhibited spatial memory deficits on the Barnes maze, those that also received MSN theta, but not gamma, stimulation found the escape hole sooner. ConclusionsThese findings demonstrate that acute MK-801 administration leads to altered neural activity in the septohippocampal circuit and impaired spatial memory. Further, these findings suggest that MSN theta-frequency stimulation improves specific spatial memory deficits and may be a possible treatment for cognitive impairments caused by NMDA hypofunction.

The effect of alterations of schizophrenia-associated genes on gamma band oscillations

Abnormalities in the synchronized oscillatory activity of neurons in general and, specifically in the gamma band, might play a crucial role in the pathophysiology of schizophrenia. While these changes in oscillatory activity have traditionally been linked to alterations at the synaptic level, we demonstrate here, using computational modeling, that common genetic variants of ion channels can contribute strongly to this effect. Our model of primary auditory cortex highlights multiple schizophrenia-associated genetic variants that reduce gamma power in an auditory steady-state response task. Furthermore, we show that combinations of several of these schizophrenia-associated variants can produce similar effects as the more traditionally considered synaptic changes. Overall, our study provides a mechanistic link between schizophrenia-associated common genetic variants, as identified by genome-wide association studies, and one of the most robust neurophysiological endophenotypes of schizophrenia.

No indications for altered EEG oscillatory activity in patients with chronic post-burn itch compared to healthy controls

A large proportion of patients with burn injuries develop chronic itch, which impacts quality of life. The underlying pathophysiological mechanisms are poorly understood. This cross-sectional pilot study investigates whether altered cortical oscillatory processes are involved in chronic post-burn itch. Continuous electroencephalography (EEG) data were recorded during rest and stimulation of non-injured skin, inducing itch (histamine and electrical) and cold-pressor task pain for 15 adults with chronic post-burn itch and 15 matched healthy controls. Quantitative metrics comprised oscillatory power and peak frequencies in theta, alpha, and beta bands. No statistical differences between patients and healthy controls were found in oscillatory activity during rest or stimulation, with Bayesian analysis suggesting equivocal evidence. However, post-traumatic stress symptoms and duration of chronic itch may be associated with changes in oscillatory activity. A lack of differences in cortical oscillatory processing and itch levels at non-injured sites, suggests that itch symptoms have a localised character in this sample of patients with post-burn itch. For future studies, a biopsychological approach with integration of peripheral and central nervous system techniques, linear and non-linear EEG analysis, injured and non-injured stimulation sites, and incorporation of individual characteristics is recommended. Insight into pathophysiological mechanisms underlying chronic post-burn itch could improve diagnostics and treatments.

Power spectrum slope confounds estimation of instantaneous oscillatory frequency

Oscillatory neural dynamics are highly non-stationary and require methods capable of quantifying time-resolved changes in oscillatory activity in order to understand neural function. Recently, a method termed ‘frequency sliding’ was introduced to estimate the instantaneous frequency of oscillatory activity, providing a means of tracking temporal changes in the dominant frequency within a sub-band of field potential recordings. Here, the ability of frequency sliding to recover ground-truth oscillatory frequency in simulated data is tested while the exponent (slope) of the 1/fx component of the signal power spectrum is systematically varied, mimicking real electrophysiological data. The results show that 1) in the presence of 1/f activity, frequency sliding systematically underestimates the true frequency of the signal, 2) the magnitude of underestimation is correlated with the steepness of the slope, suggesting that, if unaccounted for, slope changes could be misinterpreted as frequency changes, 3) the impact of slope on frequency estimates interacts with oscillation amplitude, indicating that changes in oscillation amplitude alone may also influence instantaneous frequency estimates in the presence of strong 1/f activity; and 4) analysis parameters such as filter bandwidth and location also mediate the influence of slope on estimated frequency, indicating that these settings should be considered when interpreting estimates obtained via frequency sliding. The origin of these biases resides in the output of the filtering step of frequency sliding, whose energy is biased towards lower frequencies precisely because of the 1/f structure of the data. We discuss several strategies to mitigate these biases and provide a proof-of-principle for a 1/f normalization strategy.

Brief neuronal afterdischarges in the rat hippocampus lead to transient changes in oscillatory activity and to a very long-lasting decline in BOLD signals without inducing a hypoxic state

The effects of hippocampal neuronal afterdischarges (nAD) on hemodynamic parameters, such as blood-oxygen-level-dependent (BOLD) signals) and local cerebral blood volume (CBV) changes, as well as neuronal activity and metabolic parameters in the dentate gyrus, was investigated in rats by combining in vivo electrophysiology with functional magnetic resonance imaging (fMRI) or 1H-nuclear magnetic resonance spectroscopy (1H-NMRS). Brief electrical high-frequency pulse-burst stimulation of the right perforant pathway triggered nAD, a seizure-like activity, in the right dentate gyrus with a high incidence, a phenomenon that in turn caused a sustained decrease in BOLD signals for more than 30 min. The decrease was associated with a reduction in CBV but not with signs of hypoxic metabolism. nAD also triggered transient changes mainly in the low gamma frequency band that recovered within 20 min, so that the longer-lasting altered hemodynamics reflected a switch in blood supply rather than transient changes in ongoing neuronal activity. Even in the presence of reduced baseline BOLD signals, neurovascular coupling mechanisms remained intact, making long-lasting vasospasm unlikely. Subsequently generated nAD did not further alter the baseline BOLD signals. Similarly, nAD did not alter baseline BOLD signals when acetaminophen was previously administered, because acetaminophen alone had already caused a similar decrease in baseline BOLD signals as observed after the first nAD. Thus, at least two different blood supply states exist for the hippocampus, one low and one high, with both states allowing similar neuronal activity. Both acetaminophen and nAD switch from the high to the low blood supply state. As a result, the hemodynamic response function to an identical stimulus differed after nAD or acetaminophen, although the triggered neuronal activity was similar.

The impact of 1/f activity and baseline correction on the results and interpretation of time-frequency analyses of EEG/MEG data: A cautionary tale

Typically, time-frequency analysis (TFA) of electrophysiological data is aimed at isolating narrowband signals (oscillatory activity) from broadband non-oscillatory (1/f) activity, so that changes in oscillatory activity resulting from experimental manipulations can be assessed. A widely used method to do this is to convert the data to the decibel (dB) scale through baseline division and log transformation. This procedure assumes that, for each frequency, sources of power (i.e., oscillations and 1/f activity) scale by the same factor relative to the baseline (multiplicative model). This assumption may be incorrect when signal and noise are independent contributors to the power spectrum (additive model). Using resting-state EEG data from 80 participants, we found that the level of 1/f activity and alpha power are not positively correlated within participants, in line with the additive but not the multiplicative model. Then, to assess the effects of dB conversion on data that violate the multiplicativity assumption, we simulated a mixed design study with one between-subject (noise level, i.e., level of 1/f activity) and one within-subject (signal amplitude, i.e., amplitude of oscillatory activity added onto the background 1/f activity) factor. The effect size of the noise level × signal amplitude interaction was examined as a function of noise difference between groups, following dB conversion. Findings revealed that dB conversion led to the over- or under-estimation of the true interaction effect when groups differing in 1/f levels were compared, and it also led to the emergence of illusory interactions when none were present. This is because signal amplitude was systematically underestimated in the noisier compared to the less noisy group. Hence, we recommend testing whether the level of 1/f activity differs across groups or conditions and using multiple baseline correction strategies to validate results if it does. Such a situation may be particularly common in aging, developmental, or clinical studies.

Somatosensory Targeted Memory Reactivation Modulates Oscillatory Brain Activity but not Motor Memory Consolidation

Previous research has shown that targeted memory reactivation (TMR) protocols using acoustic or olfactory stimuli can boost motor memory consolidation. While somatosensory information is crucial for motor control and learning, the effects of somatosensory TMR on motor memory consolidation remain elusive. Here, healthy young adults (n = 28) were trained on a sequential serial reaction time task and received, during the offline consolidation period that followed, sequential electrical stimulation of the fingers involved in the task. This somatosensory TMR procedure was applied during either a 90-minute diurnal sleep (NAP) or wake (NONAP) interval that was monitored with electroencephalography. Consolidation was assessed with a retest following the NAP/NONAP episode. Behavioral results revealed no effect of TMR on motor performance in either of the groups. At the brain level, somatosensory stimulation elicited changes in oscillatory activity in both groups. Specifically, TMR induced an increase in power in the mu band in the NONAP group and in the beta band in both the NAP and NONAP groups. Additionally, TMR elicited an increase in sigma power and a decrease in delta oscillations in the NAP group. None of these TMR-induced modulations of oscillatory activity, however, were correlated with measures of motor memory consolidation. The present results collectively suggest that while somatosensory TMR modulates oscillatory brain activity during post-learning sleep and wakefulness, it does not influence motor performance in an immediate retest.

Working memory after and during 6 Hz transcranial alternating current stimulation

IntroductionTranscranial alternating current stimulation (tACS) is a non-invasive brain stimulation technique allowing to induce changes in oscillatory activity. Theta activity has been reported to play a major role in maintenance of information in working memory (WM).ObjectivesThe current study had the initial goal to check the effect of theta tACS on accuracy and resting state EEG in a set of match-to-sample WM tasks.MethodsIn the first experiment, we tested 31 participants in the WM task after 20-min tACS applied at Fpz and CPz at 6 Hz, 1 mA.). In the second experiment, we compared the after-effects and online effects of the stimulation in a sample of 25 individuals. Five similar 25-min blocks filled with the same working memory task were distributed over 3 days. We assessed the same group of participants in all three sessions. On the Training day, the participants performed one block without stimulation. On the Sham-Verum day (SV), the first block with Sham stimulation followed by the second block with Verum stimulation. On the Verum-Sham day (VS), the blocks order reversed.ResultsAfter-effects of the stimulation did not produce any significant changes either in behavior (accuracy in the task) or resting-state EEG (theta frequency band spectral power in the first experiment. In the second experiment, 6 Hz tACS delivered before the WM task was not able to produce any observable changes in working memory performance. The same hold true for online stimulation.ConclusionsTheta frequency tACS applied to Fpz-CPz electrodes is not an efficient method to improve WM.

Evoked and induced power oscillations linked to audiovisual integration of affect

Our affective experiences are influenced by combined multisensory information. Although the enhanced effects of congruent audiovisual information on our affective experiences have been well documented, the role of neural oscillations in the audiovisual integration of affective signals remains unclear. First, it is unclear whether oscillatory activity changes as a function of valence. Second, the function of phase-locked and non-phase-locked power changes in audiovisual integration of affect has not yet been clearly distinguished. To fill this gap, the present study performed time-frequency analyses on EEG data acquired while participants perceived positive, neutral and negative naturalistic video and music clips. A comparison between the congruent audiovisual condition and the sum of unimodal conditions was used to identify supra-additive (Audiovisual > Visual + Auditory) or sub-additive (Audiovisual < Visual + Auditory) integration effects. The results showed that early evoked sub-additive theta and sustained induced supra-additive delta and beta activities are linked to audiovisual integration of affect regardless of affective content.

A loss of neuronal inhibition best explains EEG abnormalities in preclinical Alzheimer’s disease: A multiscale computational modeling study

AbstractBackgroundA better understanding of the earliest functional brain changes in human preclinical Alzheimer’s Disease (AD) may improve diagnosis and intervention. Evidence accumulating from experimental neurophysiological research illustrates that neuronal excitation/inhibition imbalance is an early sign of AD (Palop and Mucke, 2016). However, how this microscale phenomenon relates to the typical changes in oscillatory activity during preclinical AD stages at the macroscale as assessed by electroencephalography/magnetoencephalography (EEG/MEG), remains unclear. This computational modeling study of a network of coupled neural masses aims to find the most probable pathophysiologic mechanism by linking the microscopic level of neurons with the macroscopic level of observable human brain dynamics.MethodThe brain dynamics simulation model consists of 78 neural mass models (describing regional brain activity), coupled according to human DTI‐based structural network topology (Ponten et al., 2010). The model produces EEG‐like data that can be analyzed the same way as patient recordings. We first examined the effect of gradually increasing or decreasing global excitability of either inhibitory or excitatory neurons on overall oscillatory behavior (average total and relative power, peak frequency and spike density), by changing the average membrane threshold potential. Consequently, these four different scenarios were compared with (CSF) amyloid‐positive mild cognitively impaired (MCI) patient data (Gouw et al., 2017) to identify the most compatible underlying mechanism.ResultThe results confirm previous literature (Isaacson and Scanziani 2011), showing an overall stronger effect of changes to inhibitory neurons on oscillatory activity compared to excitatory neurons. Simulating a decrease in inhibition of the network is associated to a reduction in peak frequency, lower relative alpha power and higher relative theta power, which best matches to preclinical AD data (Gouw et al., 2017). The decreased inhibition scenario resulted furthermore in a strong increase in total power and the highest spike density levels.ConclusionThis study provides theoretical support for the hypothesis that inhibitory (inter)neuron dysfunction is one possible mechanism underlying cortical oscillatory activity changes and a hyperactive network in early AD, in line with recent insights from experimental animal studies.

Increase in serum prolactin levels in females improves the performance of spatial learning by promoting changes in the circuital dynamics of the hippocampus

Beyond the direct physiological functions associated with motherhood in mammals, previous studies have suggested the potential role of prolactin (Prl) in distinct brain processes such as neuroprotection, neurogenesis, and stress responses. However, the cognitive influence of Prl remains unclear, particularly regarding the mechanisms of acquisition, consolidation and retrieval of information in the brain. Using chronic implanted electrodes in freely moving female mice combined with behavioral tests, we investigated the rhythmic activity changes induced by Prl in a model of hippocampus-dependent learning and memory. Our results show that Prl improves the learning of a spatial memory task in the acquisition stage. The main variations at the circuitry level were in the theta frequency band (4−8 Hz and 8−12 Hz), marked by a faster change in oscillatory activity with no modifications to higher frequencies. These results show that Prl plays a significant role in the acquisition of information during learning of a spatial memory task, suggesting that an increase in Prl levels may induce changes in circuital network plasticity.