Analysis of spontaneous MEG activity in mild cognitive impairment and Alzheimer's disease using spectral entropies and statistical complexity measures

Alzheimer's disease (AD) is the most common cause of dementia. Over the last few years, a considerable effort has been devoted to exploring new biomarkers. Nevertheless, a better understanding of brain dynamics is still required to optimize therapeutic strategies. In this regard, the characterization of mild cognitive impairment (MCI) is crucial, due to the high conversion rate from MCI to AD. However, only a few studies have focused on the analysis of magnetoencephalographic (MEG) rhythms to characterize AD and MCI. In this study, we assess the ability of several parameters derived from information theory to describe spontaneous MEG activity from 36 AD patients, 18 MCI subjects and 26 controls. Three entropies (Shannon, Tsallis and Rényi entropies), one disequilibrium measure (based on Euclidean distance ED) and three statistical complexities (based on Lopez Ruiz–Mancini–Calbet complexity LMC) were used to estimate the irregularity and statistical complexity of MEG activity. Statistically significant differences between AD patients and controls were obtained with all parameters (p < 0.01). In addition, statistically significant differences between MCI subjects and controls were achieved by ED and LMC (p < 0.05). In order to assess the diagnostic ability of the parameters, a linear discriminant analysis with a leave-one-out cross-validation procedure was applied. The accuracies reached 83.9% and 65.9% to discriminate AD and MCI subjects from controls, respectively. Our findings suggest that MCI subjects exhibit an intermediate pattern of abnormalities between normal aging and AD. Furthermore, the proposed parameters provide a new description of brain dynamics in AD and MCI.

Dynamics of brain networks in aesthetic appreciation

Neuroimage experiments have been essential for identifying active brain networks. During cognitive tasks as in, e.g., aesthetic appreciation, such networks include regions that belong to the default mode network (DMN). Theoretically, DMN activity should be interrupted during cognitive tasks demanding attention, as is the case for aesthetic appreciation. Analyzing the functional connectivity dynamics along three temporal windows and two conditions, beautiful and not beautiful stimuli, here we report experimental support for the hypothesis that aesthetic appreciation relies on the activation of two different networks, an initial aesthetic network and a delayed aesthetic network, engaged within distinct time frames. Activation of the DMN might correspond mainly to the delayed aesthetic network. We discuss adaptive and evolutionary explanations for the relationships existing between the DMN and aesthetic networks and offer unique inputs to debates on the mind/brain interaction.

Background noise and its influence on the brain waves related to attention

In this work, we present a study whose objective is to prove the influence of background noise produced inside university facilities on the brain waves related to attention processes. Recordings of background noise were carried out in study areas inside university facilities. Volunteers were asked to perform an attention test without any background noise but also while being exposed to the sound recordings, and their cerebral activity was recorded through electroencephalography (EEG). After the application of the test in both conditions, changes in the frequency bands related to attention processes (beta 13-30 Hz and theta 4-7 Hz) were studied. The results of this study show that when the students were performing the test while being exposed to background noise, both beta and theta frequency bands decreased statistically significantly. Because attentional improvement is related to increases of the beta and theta waves, we believe that those decreases are directly related to a lack of attention caused by the exposure to background noise. Nevertheless, the results do not allow us to conclude that background noise produced inside university facilities has an influence on the attentional processes.

Brain-wide slowing of spontaneous alpha rhythms in mild cognitive impairment

The neurophysiological changes associated with Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI) include an increase in low frequency activity, as measured with electroencephalography or magnetoencephalography (MEG). A relevant property of spectral measures is the alpha peak, which corresponds to the dominant alpha rhythm. Here we studied the spatial distribution of MEG resting state alpha peak frequency and amplitude values in a sample of 27 MCI patients and 24 age-matched healthy controls. Power spectra were reconstructed in source space with linearly constrained minimum variance beamformer. Then, 88 Regions of Interest (ROIs) were defined and an alpha peak per ROI and subject was identified. Statistical analyses were performed at every ROI, accounting for age, sex and educational level. Peak frequency was significantly decreased (p < 0.05) in MCIs in many posterior ROIs. The average peak frequency over all ROIs was 9.68 ± 0.71 Hz for controls and 9.05 ± 0.90 Hz for MCIs and the average normalized amplitude was (2.57 ± 0.59)·10−2 for controls and (2.70 ± 0.49)·10−2 for MCIs. Age and gender were also found to play a role in the alpha peak, since its frequency was higher in females than in males in posterior ROIs and correlated negatively with age in frontal ROIs. Furthermore, we examined the dependence of peak parameters with hippocampal volume, which is a commonly used marker of early structural AD-related damage. Peak frequency was positively correlated with hippocampal volume in many posterior ROIs. Overall, these findings indicate a pathological alpha slowing in MCI.

White matter damage disorganizes brain functional networks in amnestic mild cognitive impairment

Although progressive functional brain network disruption has been one of the hallmarks of Alzheimer?s Dis- ease, little is known about the origin of this functional impairment that underlies cognitive symptoms. We in- vestigated how the loss of white matter (WM) integrity disrupts the organization of the functional networks at different frequency bands. The analyses were performed in a sample of healthy elders and mild cognitive im- pairment (MCI) subjects. Spontaneous brain magnetic activity (measured with magnetoencephalography) was characterized with phase synchronization analysis, and graph theory was applied to the functional networks. We identified WM areas (using diffusion weighted magnetic resonance imaging) that showed a statistical de- pendence between the fractional anisotropy and the graph metrics. These regions are part of an episodic mem- ory network and were also related to cognitive functions. Our data support the hypothesis that disruption of the anatomical networks influences the organization at the functional level resulting in the prodromal dementia syndrome of MCI.

Cognitive reserve is associated with the functional organization of brain networks in healthy aging: a MEG study

The proportion of elderly people in the population has increased rapidly in the last century and consequently "healthy aging" is expected to become a critical area of research in neuroscience. Evidence reveals how healthy aging depends on three main behavioral factors: social lifestyle, cognitive activity and physical activity. In this study, we focused on the role of cognitive activity, concentrating specifically on educational and occupational attainment factors, which were considered two of the main pillars of cognitive reserve. 21 subjects with similar rates of social lifestyle, physical and cognitive activity were selected from a sample of 55 healthy adults. These subjects were divided into two groups according to their level of cognitive reserve; one group comprised subjects with high cognitive reserve (9 members) and the other contained those with low cognitive reserve (12 members). To evaluate the cortical brain connectivity network, all participants were recorded by Magnetoencephalography (MEG) while they performed a memory task (modified version of the Sternberg¿s Task). We then applied two algorithms (Phase Locking Value & Phase-Lag Index) to study the dynamics of functional connectivity. In response to the same task, the subjects with lower cognitive reserve presented higher functional connectivity than those with higher cognitive reserve. These results may indicate that participants with low cognitive reserve needed a greater 'effort' than those with high cognitive reserve to achieve the same level of cognitive performance. Therefore, we conclude that cognitive reserve contributes to the modulation of the functional connectivity patterns of the aging brain.

Cardiac arrest in rodents: Maximal duration compatible with a recovery of neuronal activity

We report here that during a permanent cardiac arrest, rodent brain tissue is “physiologically” preserved in situ in a particular quiescent state. This state is characterized by the absence of electrical activity and by a critical period of 5–6 hr during which brain tissue can be reactivated upon restoration of a simple energy (glucose/oxygen) supply. In rat brain slices prepared 1–6 hr after cardiac arrest and maintained in vitro for several hours, cells with normal morphological features, intrinsic membrane properties, and spontaneous synaptic activity were recorded from various brain regions. In addition to functional membrane channels, these neurons expressed mRNA, as revealed by single-cell reverse transcription–PCR, and could synthesize proteins de novo. Slices prepared after longer delays did not recover. In a guinea pig isolated whole-brain preparation that was cannulated and perfused with oxygenated saline 1–2 hr after cardiac arrest, cell activity and functional long-range synaptic connections could be restored although the electroencephalogram remained isoelectric. Perfusion of the isolated brain with the γ-aminobutyric acid A receptor antagonist picrotoxin, however, could induce self-sustained temporal lobe epilepsy. Thus, in rodents, the duration of cardiac arrest compatible with a short-term recovery of neuronal activity is much longer than previously expected. The analysis of the parameters that regulate this duration may bring new insights into the prevention of postischemic damages.

Activity differentially regulates the surface expression of synaptic AMPA and NMDA glutamate receptors

Distinct subtypes of glutamate receptors often are colocalized at individual excitatory synapses in the mammalian brain yet appear to subserve distinct functions. To address whether neuronal activity may differentially regulate the surface expression at synapses of two specific subtypes of ionotropic glutamate receptors we epitope-tagged an AMPA (α-amino-3-hydroxy-5-methylisoxazole-4-propionic acid) receptor subunit (GluR1) and an NMDA (N-methyl-d-aspartate) receptor subunit (NR1) on their extracellular termini and expressed these proteins in cultured hippocampal neurons using recombinant adenoviruses. Both receptor subtypes were appropriately targeted to the synaptic plasma membrane as defined by colocalization with the synaptic vesicle protein synaptophysin. Increasing activity in the network of cultured cells by prolonged blockade of inhibitory synapses with the γ-aminobutyric acid type A receptor antagonist picrotoxin caused an activity-dependent and NMDA receptor-dependent decrease in surface expression of GluR1, but not NR1, at synapses. Consistent with this observation identical treatment of noninfected cultures decreased the contribution of endogenous AMPA receptors to synaptic currents relative to endogenous NMDA receptors. These results indicate that neuronal activity can differentially regulate the surface expression of AMPA and NMDA receptors at individual synapses.

Activity-dependent regulation of synaptic clustering in a hippocampal culture system

Currently, there is a limited understanding of the factors that influence the localization and density of individual synapses in the central nervous system. Here we have studied the effects of activity on synapse formation between hippocampal dentate granule cells and CA3 pyramidal neurons in culture, taking advantage of FM1–43 as a fluorescent marker of synaptic boutons. We observed an early tendency for synapses to group together, quickly followed by the appearance of synaptic clusters on dendritic processes. These events were strongly influenced by N-methyl-d-aspartic acid receptor- and cyclic AMP-dependent signaling. The microstructure and localization of the synaptic clusters resembled that found in hippocampus, at mossy fiber synapses of stratum lucidum. Activity-dependent clustering of synapses represents a means for synaptic targeting that might contribute to synaptic organization in the brain.

Blind separation of auditory event-related brain responses into independent components

Averaged event-related potential (ERP) data recorded from the human scalp reveal electroencephalographic (EEG) activity that is reliably time-locked and phase-locked to experimental events. We report here the application of a method based on information theory that decomposes one or more ERPs recorded at multiple scalp sensors into a sum of components with fixed scalp distributions and sparsely activated, maximally independent time courses. Independent component analysis (ICA) decomposes ERP data into a number of components equal to the number of sensors. The derived components have distinct but not necessarily orthogonal scalp projections. Unlike dipole-fitting methods, the algorithm does not model the locations of their generators in the head. Unlike methods that remove second-order correlations, such as principal component analysis (PCA), ICA also minimizes higher-order dependencies. Applied to detected—and undetected—target ERPs from an auditory vigilance experiment, the algorithm derived ten components that decomposed each of the major response peaks into one or more ICA components with relatively simple scalp distributions. Three of these components were active only when the subject detected the targets, three other components only when the target went undetected, and one in both cases. Three additional components accounted for the steady-state brain response to a 39-Hz background click train. Major features of the decomposition proved robust across sessions and changes in sensor number and placement. This method of ERP analysis can be used to compare responses from multiple stimuli, task conditions, and subject states.

Synapsin I interacts with c-Src and stimulates its tyrosine kinase activity

Synapsin I is a synaptic vesicle-associated phosphoprotein that has been implicated in the formation of presynaptic specializations and in the regulation of neurotransmitter release. The nonreceptor tyrosine kinase c-Src is enriched on synaptic vesicles, where it accounts for most of the vesicle-associated tyrosine kinase activity. Using overlay, affinity chromatography, and coprecipitation assays, we have now shown that synapsin I is the major binding protein for the Src homology 3 (SH3) domain of c-Src in highly purified synaptic vesicle preparations. The interaction was mediated by the proline-rich domain D of synapsin I and was not significantly affected by stoichiometric phosphorylation of synapsin I at any of the known regulatory sites. The interaction of purified c-Src and synapsin I resulted in a severalfold stimulation of tyrosine kinase activity and was antagonized by the purified c-Src-SH3 domain. Depletion of synapsin I from purified synaptic vesicles resulted in a decrease of endogenous tyrosine kinase activity. Portions of the total cellular pools of synapsin I and Src were coprecipitated from detergent extracts of rat brain synaptosomal fractions using antibodies to either protein species. The interaction between synapsin I and c-Src, as well as the synapsin I-induced stimulation of tyrosine kinase activity, may be physiologically important in signal transduction and in the modulation of the function of axon terminals, both during synaptogenesis and at mature synapses.

Visual stimuli induce waves of electrical activity in turtle cortex

The computations involved in the processing of a visual scene invariably involve the interactions among neurons throughout all of visual cortex. One hypothesis is that the timing of neuronal activity, as well as the amplitude of activity, provides a means to encode features of objects. The experimental data from studies on cat [Gray, C. M., Konig, P., Engel, A. K. & Singer, W. (1989) Nature (London) 338, 334–337] support a view in which only synchronous (no phase lags) activity carries information about the visual scene. In contrast, theoretical studies suggest, on the one hand, the utility of multiple phases within a population of neurons as a means to encode independent visual features and, on the other hand, the likely existence of timing differences solely on the basis of network dynamics. Here we use widefield imaging in conjunction with voltage-sensitive dyes to record electrical activity from the virtually intact, unanesthetized turtle brain. Our data consist of single-trial measurements. We analyze our data in the frequency domain to isolate coherent events that lie in different frequency bands. Low frequency oscillations (<5 Hz) are seen in both ongoing activity and activity induced by visual stimuli. These oscillations propagate parallel to the afferent input. Higher frequency activity, with spectral peaks near 10 and 20 Hz, is seen solely in response to stimulation. This activity consists of plane waves and spiral-like waves, as well as more complex patterns. The plane waves have an average phase gradient of ≈π/2 radians/mm and propagate orthogonally to the low frequency waves. Our results show that large-scale differences in neuronal timing are present and persistent during visual processing.

Selective serotonin reuptake inhibitors directly alter activity of neurosteroidogenic enzymes

The neurosteroid 3α-hydroxysteroid-5α-pregnan-20-one (allopregnanolone) acts as a positive allosteric modulator of γ-aminobutyric acid at γ-aminobutyric acid type A receptors and hence is a powerful anxiolytic, anticonvulsant, and anesthetic agent. Allopregnanolone is synthesized from progesterone by reduction to 5α-dihydroprogesterone, mediated by 5α-reductase, and by reduction to allopregnanolone, mediated by 3α-hydroxysteroid dehydrogenase (3α-HSD). Previous reports suggested that some selective serotonin reuptake inhibitors (SSRIs) could alter concentrations of allopregnanolone in human cerebral spinal fluid and in rat brain sections. We determined whether SSRIs directly altered the activities of either 5α-reductase or 3α-HSD, using an in vitro system containing purified recombinant proteins. Although rats appear to express a single 3α-HSD isoform, the human brain contains several isoforms of this enzyme, including a new isoform we cloned from human fetal brains. Our results indicate that the SSRIs fluoxetine, sertraline, and paroxetine decrease the Km of the conversion of 5α-dihydroprogesterone to allopregnanolone by human 3α-HSD type III 10- to 30-fold. Only sertraline inhibited the reverse oxidative reaction. SSRIs also affected conversions of androgens to 3α- and 3α, 17β-reduced or -oxidized androgens mediated by 3α-HSD type IIBrain. Another antidepressant, imipramine, was without any effect on allopregnanolone or androstanediol production. The region-specific expression of 3α-HSD type IIBrain and 3α-HSD type III mRNAs suggest that SSRIs will affect neurosteroid production in a region-specific manner. Our results may thus help explain the rapid alleviation of the anxiety and dysphoria associated with late luteal phase dysphoria disorder and major unipolar depression by these SSRIs.

How the brain keeps the eyes still

The brain can hold the eyes still because it stores a memory of eye position. The brain’s memory of horizontal eye position appears to be represented by persistent neural activity in a network known as the neural integrator, which is localized in the brainstem and cerebellum. Existing experimental data are reinterpreted as evidence for an “attractor hypothesis” that the persistent patterns of activity observed in this network form an attractive line of fixed points in its state space. Line attractor dynamics can be produced in linear or nonlinear neural networks by learning mechanisms that precisely tune positive feedback.

Cloning and expression of a cDNA encoding a bovine brain brefeldin A-sensitive guanine nucleotide-exchange protein for ADP-ribosylation factor

A 200-kDa guanine nucleotide-exchange protein (p200 or GEP) for ADP-ribosylation factors 1 and 3 (ARF1 and ARF3) that was inhibited by brefeldin A (BFA) was purified earlier from cytosol of bovine brain cortex. Amino acid sequences of four tryptic peptides were 47% identical to that of Sec7 from Saccharomyces cerevisiae, which is involved in vesicular trafficking in the Golgi. By using a PCR-based procedure with two degenerate primers representing sequences of these peptides, a product similar in size to Sec7 that contained the peptide sequences was generated. Two oligonucleotides based on this product were used to screen a bovine brain library, which yielded one clone that was a partial cDNA for p200. The remainder of the cDNA was obtained by 5′ and 3′ rapid amplification of cDNA ends (RACE). The ORF of the cDNA encodes a protein of 1,849 amino acids (≈208 kDa) that is 33% identical to yeast Sec7 and 50% identical in the Sec7 domain region. On Northern blot analysis of bovine tissues, a ≈7.4-kb mRNA was identified that hybridized with a p200 probe; it was abundant in kidney, somewhat less abundant in lung, spleen, and brain, and still less abundant in heart. A six-His-tagged fusion protein synthesized in baculovirus-infected Sf9 cells demonstrated BFA-inhibited GEP activity, confirming that BFA sensitivity is an intrinsic property of this ARF GEP and not conferred by another protein component of the complex from which p200 was originally purified.