Neural correlates of disbalanced motor control in major depression

Motor retardation is a common symptom of major depressive disorder (MDD). Despite the existence of various assessment methods, little is known on the pathobiology of motor retardation. We aimed to elucidate aspects of motor control investigating the association of objective motor activity and resting state cerebral blood flow (CBF).

Effects of transcranial direct current stimulation (tDCS) on behaviour and electrophysiology of language production

Excitatory anodal transcranial direct current stimulation (A-tDCS) over the left dorsal prefrontal cortex (DPFC) has been shown to improve language production. The present study examined neurophysiological underpinnings of this effect. In a single-blinded within-subject design, we traced effects of A-tDCS compared to sham stimulation over the left DPFC using electrophysiological and behavioural correlates during overt picture naming. Online effects were examined during A-tDCS by employing the semantic interference (SI-)Effect – a marker that denotes the functional integrity of the language system. The behavioural SI-Effect was found to be reduced, whereas the electrophysiological SI-Effect was enhanced over left compared to right temporal scalp-electrode sites. This modulation is suggested to reflect a superior tuning of neural responses within language-related generators. After -(offline) effects of A-tDCS were detected in the delta frequency band, a marker of neural inhibition. After A-tDCS there was a reduction in delta activity during picture naming and the resting state, interpreted to indicate neural disinhibition. Together, these findings demonstrate electrophysiological modulations induced by A-tDCS of the left DPFC. They suggest that A-tDCS is capable of enhancing neural processes during and after application. The present functional and oscillatory neural markers could detect positive effects of prefrontal A-tDCS, which could be of use in the neuro-rehabilitation of frontal language functions.

Discovering imaging endophenotypes for major depression

Psychiatry research lacks an in-depth understanding of mood disorders phenotypes, leading to limited success of genetics studies of major depressive disorder (MDD). The dramatic progress in safe and affordable magnetic resonance-based imaging methods has the potential to identify subtle abnormalities of neural structures, connectivity and function in mood disordered subjects. This review paper presents strategies to improve the phenotypic definition of MDD by proposing imaging endophenotypes derived from magnetic resonance spectroscopy measures, such as cortical gamma-amino butyric acid (GABA) and glutamate/glutamine concentrations, and from measures of resting-state activity and functional connectivity. The proposed endophenotypes are discussed regarding specificity, mood state-independence, heritability, familiarity, clinical relevance and possible associations with candidate genes. By improving phenotypic definitions, the discovery of new imaging endophenotypes will increase the power of candidate gene and genome-wide associations studies. It will also help to develop and evaluate novel therapeutic treatments and enable clinicians to apply individually tailored therapeutic approaches. Finally, improvements of the phenotypic definition of MDD based on neuroimaging measures will contribute to a new classification system of mood disorders based on etiology and pathophysiology.

Reduced Cerebral Blood Flow Within the Default-Mode Network and Within Total Gray Matter in Major Depression

The default-mode network (DMN) was shown to have aberrant blood oxygenation-level-dependent (BOLD) activity in major depressive disorder (MDD). While BOLD is a relative measure of neural activity, cerebral blood flow (CBF) is an absolute measure. Resting-state CBF alterations have been reported in MDD. However, the association of baseline CBF and CBF fluctuations is unclear in MDD. Therefore, the aim was to investigate the CBF within the DMN in MDD, applying a strictly data-driven approach. In 22 MDD patients and 22 matched healthy controls, CBF was acquired using arterial spin labeling (ASL) at rest. A concatenated independent component analysis was performed to identify the DMN within the ASL data. The perfusion of the DMN and its nodes was quantified and compared between groups. The DMN was identified in both groups with high spatial similarity. Absolute CBF values within the DMN were reduced in MDD patients (p<0.001). However, after controlling for whole-brain gray matter CBF and age, the group difference vanished. In patients, depression severity was correlated with reduced perfusion in the DMN in the posterior cingulate cortex and the right inferior parietal lobe. Hypoperfusion within the DMN in MDD is not specific to the DMN. Still, depression severity was linked to DMN node perfusion, supporting a role of the DMN in depression pathobiology. The finding has implications for the interpretation of BOLD functional magnetic resonance imaging data in MDD.

A neurophysiological signature of motivational incongruence: EEG changes related to insufficient goal satisfaction

Human behavior and psychological functioning is motivated and guided by individual goals. Motivational incongruence refers to states of insufficient goal satisfaction and is tightly related to psychological problems and even psychopathology. In the present study, individual levels of motivational incongruence were assessed with the incongruence-questionnaire (INC) in a healthy sample. In addition, multi-channel resting-state EEG was measured. Individual variations of EEG synchronization and spectral power were related to individual levels of motivational incongruence. For significant correlations, the relation to intracerebral sources of electrical brain activity was investigated with sLORETA. The results indicate that, even in a healthy sample with rather low degrees of motivational incongruence, this insufficient goal satisfaction is related to consistent changes in resting state brain activity. Upper Alpha band attenuation seems to be most indicative of increased levels of motivational incongruence. This is reflected not only in significantly reduced functional connectivity, but also in changes regarding the level of brain activation, as indicated by significant effects in the spectral power and LORETA analyses. Results are related to research investigating the upper Alpha band and are discussed in the framework of Grawe's consistency theory.

Early autonomic dysfunction in patients with diabetes mellitus assessed by spectral analysis of heart rate and blood pressure variability

Patients with diabetes mellitus (DM) often have alterations of the autonomic nervous system (ANS), even early in their disease course. Previous research has not evaluated whether these changes may have consequences on adaptation mechanisms in DM, e.g. to mental stress. We therefore evaluated whether patients with DM who already had early alterations of the ANS reacted with an abnormal regulatory pattern to mental stress. We used the spectral analysis technique, known to be valuable and reliable in the investigation of disturbances of the ANS. We investigated 34 patients with DM without clinical evidence of ANS dysfunction (e.g. orthostatic hypotension) and 44 normal control subjects (NC group). No patients on medication known to alter ANS responses were accepted. The investigation consisted of a resting state evaluation and a mental stress task (BonnDet). In basal values, only the 21 patients with type 2 DM were different in respect to body mass index and systolic blood pressure. In the study parameters we found significantly lower values in resting and mental stress spectral power of mid-frequency band (known to represent predominantly sympathetic influences) and of high-frequency and respiration bands (known to represent parasympathetic influences) in patients with DM (types 1 and 2) compared with NC group (5.3 +/- 1.2 ms2 vs. 6.1 +/- 1.3 ms2, and 5.5 +/- 1.6 ms2 vs. 6.2 +/- 1.5 ms2, and 4.6 +/- 1.7 ms2 vs. 6.2 +/- 1.5 ms2, for resting values respectively; 4.7 +/- 1.4 ms2 vs. 5.9 +/- 1.2 ms2, and 4.6 +/- 1.9 ms2 vs. 5.6 +/- 1.7 ms2, and 3.7 +/- 2.1 ms2 vs. 5.6 +/- 1.7 ms2, for stress values respectively; M/F ratio 6/26 vs. 30/14). These differences remained significant even when controlled for age, sex, and body weight. However, patients with DM type 2 (and significantly higher body weight) showed only significant values in mental stress modulus values. There were no specific group effects in the patients with DM in adaptation mechanisms to mental stress compared with the NC group. These findings demonstrate that power spectral examinations at rest are sufficiently reliable to diagnose early alterations in ANS in patients with DM. The spectral analysis technique is sensitive and reliable in investigation of ANS in patients with DM without clinically symptomatic autonomic dysfunction.

Electrical neuroimaging in the time domain

A publication entitled “A default mode of brain function” initiated a new way of looking at functional imaging data. In this PET study the authors discussed the often-observed consistent decrease of brain activation in a variety of tasks as compared with the baseline. They suggested that this deactivation is due to a task-induced suspension of a default mode of brain function that is active during rest, i.e. that there exists intrinsic well-organized brain activity during rest in several distinct brain regions. This suggestion led to a large number of imaging studies on the resting state of the brain and to the conclusion that the study of this intrinsic activity is crucial for understanding how the brain works. The fact that the brain is active during rest has been well known from a variety of EEG recordings for a very long time. Different states of the brain in the sleep–wake continuum are characterized by typical patterns of spontaneous oscillations in different frequency ranges and in different brain regions. Best studied are the evolving states during the different sleep stages, but characteristic EEG oscillation patterns have also been well described during awake periods (see Chapter 1 for details). A highly recommended comprehensive review on the brain's default state defined by oscillatory electrical brain activities is provided in the recent book by György Buzsaki, showing how these states can be measured by electrophysiological procedures at the global brain level as well as at the local cellular level.

Is excessive EEG beta activity associated with delinquent behavior in adult subjects with ADHD?

Objective: The attention deficit/hyperactivity disorder (ADHD) shows an increased prevalence in arrested offenders compared to the normal population. ADHD and delinquency seem to share some neurophysiological abnormalities. In recent studies, a subgroup of subjects with ADHD as well as delinquents displayed excessive EEG activity in the beta band compared to controls, which has been associated with antisocial behavior and aggression in ADHD children. The goal of the present study was to investigate whether delinquent behavior in ADHD is related to excessive beta activity. Methods: We compared the resting state EEGs (eyes closed and eyes open) of 13 non-delinquent and 13 delinquent subjects with ADHD and 13 controls regarding power spectra and topography of the EEG activity. Results: Offenders with ADHD showed more beta power mainly at frontal, central and parietal brain regions than non-delinquent subjects with ADHD. Conclusions: Excessive beta power may represent a risk-factor for delinquent behavior in adults with ADHD. Significance: The awareness of such risk-factors may be helpful in the assessment of the risk for delinquent behavior in a psychiatric context and may provide a neurobiological background for therapeutic interventions.

Functional brain network efficiency predicts intelligence

The neuronal causes of individual differences in mental abilities such as intelligence are complex and profoundly important. Understanding these abilities has the potential to facilitate their enhancement. The purpose of this study was to identify the functional brain network characteristics and their relation to psychometric intelligence. In particular, we examined whether the functional network exhibits efficient small-world network attributes (high clustering and short path length) and whether these small-world network parameters are associated with intellectual performance. High-density resting state electroencephalography (EEG) was recorded in 74 healthy subjects to analyze graph-theoretical functional network characteristics at an intracortical level. Ravens advanced progressive matrices were used to assess intelligence. We found that the clustering coefficient and path length of the functional network are strongly related to intelligence. Thus, the more intelligent the subjects are the more the functional brain network resembles a small-world network. We further identified the parietal cortex as a main hub of this resting state network as indicated by increased degree centrality that is associated with higher intelligence. Taken together, this is the first study that substantiates the neural efficiency hypothesis as well as the Parieto-Frontal Integration Theory (P-FIT) of intelligence in the context of functional brain network characteristics. These theories are currently the most established intelligence theories in neuroscience. Our findings revealed robust evidence of an efficiently organized resting state functional brain network for highly productive cognitions.

Tonic activity level in the right prefrontal cortex predicts individuals' risk taking

Human risk taking is characterized by a large amount of individual heterogeneity. In this study, we applied resting-state electroencephalography, which captures stable individual differences in neural activity, before subjects performed a risk-taking task. Using a source-localization technique, we found that the baseline cortical activity in the right prefrontal cortex predicts individual risk-taking behavior. Individuals with higher baseline cortical activity in this brain area display more risk aversion than do other individuals. This finding demonstrates that neural characteristics that are stable over time can predict a highly complex behavior such as risk-taking behavior and furthermore suggests that hypoactivity in the right prefrontal cortex might serve as a dispositional indicator of lower regulatory abilities, which is expressed in greater risk-taking behavior.

Baclofen and gamma-hydroxybutyrate differentially altered behavior, EEG activity and sleep in rats.

OBJECTIVES Animal and human studies have shown that sleep may have an impact on functional recovery after brain damage. Baclofen (Bac) and gamma-hydroxybutyrate (GHB) have been shown to induce physiological sleep in humans, however, their effects in rodents are unclear. The aim of this study is to characterize sleep and electroencelphalogram (EEG) after Bac and GHB administration in rats. We hypothesized that both drugs would induce physiological sleep. METHODS Adult male Sprague-Dawley rats were implanted with EEG/electromyogram (EMG) electrodes for sleep recordings. Bac (10 or 20 mg/kg), GHB (150 or 300 mg/kg) or saline were injected 1 h after light and dark onset to evaluate time of day effect of the drugs. Vigilance states and EEG spectra were quantified. RESULTS Bac and GHB induced a non-physiological state characterized by atypical behavior and an abnormal EEG pattern. After termination of this state, Bac was found to increase the duration of non-rapid eye movement (NREM) and rapid eye movement (REM) sleep (∼90 and 10 min, respectively), reduce sleep fragmentation and affect NREM sleep episode frequency and duration (p<0.05). GHB had no major effect on vigilance states. Bac drastically increased EEG power density in NREM sleep in the frequencies 1.5-6.5 and 9.5-21.5 Hz compared to saline (p<0.05), while GHB enhanced power in the 1-5-Hz frequency band and reduced it in the 7-9-Hz band. Slow-wave activity in NREM sleep was enhanced 1.5-3-fold during the first 1-2 h following termination of the non-physiological state. The magnitude of drug effects was stronger during the dark phase. CONCLUSION While both Bac and GHB induced a non-physiological resting state, only Bac facilitated and consolidated sleep, and promoted EEG delta oscillations thereafter. Hence, Bac can be considered a sleep-promoting drug and its effects on functional recovery after stroke can be evaluated both in humans and rats.

Psychomotor retardation is linked to frontal alpha asymmetry in major depression

BACKGROUND Psychomotor disturbances are a main clinical feature of major depressive disorder (MDD) but little is known about their EEG signature. One of the most replicated EEG findings in MDD is resting frontal asymmetry in the alpha band (FAA), which is thought to be a correlate of withdrawal behavior and reduced approach motivation. The purpose of this study was to assess psychomotor alterations, alpha band power, FAA and investigate the association between them. METHODS 20 MDD patients and 19 healthy subjects were enrolled. Alpha power and FAA scores were calculated from a resting state EEG. Wrist actigraphy was recorded from the non-dominant arm for 24 h and activity level scores (AL) were extrapolated from the wakeful periods. RESULTS MDD patients had a left-lateralized frontal alpha activity and lower AL scores when compared to healthy subjects. A significant correlation was found between mean FAA and AL scores. A negative covariance between power in the lower alpha range and AL scores over the motor cortex bilaterally was detected. LIMITATIONS Relatively small sample size. Patients were pharmacologically treated with antidepressants. CONCLUSIONS This study replicates the finding of left-lateralized FAA and lower AL scores in MDD patients, and establishes the first evidence of significant correlations between alpha power, FAA scores and measures of motor activity, which may be interpreted as an expression of impaired motivational drive in MDD.

Towards Using Microstate-Neurofeedback for the Treatment of Psychotic Symptoms in Schizophrenia. A Feasibility Study in Healthy Participants

Spontaneous EEG signal can be parsed into sub-second periods of stable functional states (microstates) that assumingly correspond to brief large scale synchronization events. In schizophrenia, a specific class of microstate (class "D") has been found to be shorter than in healthy controls and to be correlated with positive symptoms. To explore potential new treatment options in schizophrenia, we tested in healthy controls if neurofeedback training to self-regulate microstate D presence is feasible and what learning patterns are observed. Twenty subjects underwent EEG-neurofeedback training to up-regulate microstate D presence. The protocol included 20 training sessions, consisting of baseline trials (resting state), regulation trials with auditory feedback contingent on microstate D presence, and a transfer trial. Response to neurofeedback was assessed with mixed effects modelling. All participants increased the percentage of time spent producing microstate D in at least one of the three conditions (p < 0.05). Significant between-subjects across-sessions results showed an increase of 0.42 % of time spent producing microstate D in baseline (reflecting a sustained change in the resting state), 1.93 % of increase during regulation and 1.83 % during transfer. Within-session analysis (performed in baseline and regulation trials only) showed a significant 1.65 % increase in baseline and 0.53 % increase in regulation. These values are in a range that is expected to have an impact upon psychotic experiences. Additionally, we found a negative correlation between alpha power and microstate D contribution during neurofeedback training. Given that microstate D has been related to attentional processes, this result provides further evidence that the training was to some degree specific for the attentional network. We conclude that microstate-neurofeedback training proved feasible in healthy subjects. The implementation of the same protocol in schizophrenia patients may promote skills useful to reduce positive symptoms by means of EEG-neurofeedback.

Lempel-Ziv complexity in schizophrenia: A MEG study

Objective The neurodevelopmental–neurodegenerative debate is a basic issue in the field of the neuropathological basis of schizophrenia (SCH). Neurophysiological techniques have been scarcely involved in such debate, but nonlinear analysis methods may contribute to it. Methods Fifteen patients (age range 23–42 years) matching DSM IV-TR criteria for SCH, and 15 sex- and age-matched control subjects (age range 23–42 years) underwent a resting-state magnetoencephalographic evaluation and Lempel–Ziv complexity (LZC) scores were calculated. Results Regression analyses indicated that LZC values were strongly dependent on age. Complexity scores increased as a function of age in controls, while SCH patients exhibited a progressive reduction of LZC values. A logistic model including LZC scores, age and the interaction of both variables allowed the classification of patients and controls with high sensitivity and specificity. Conclusions Results demonstrated that SCH patients failed to follow the “normal” process of complexity increase as a function of age. In addition, SCH patients exhibited a significant reduction of complexity scores as a function of age, thus paralleling the pattern observed in neurodegenerative diseases. Significance Our results support the notion of a progressive defect in SCH, which does not contradict the existence of a basic neurodevelopmental alteration. Highlights ► Schizophrenic patients show higher complexity values as compared to controls. ► Schizophrenic patients showed a tendency to reduced complexity values as a function of age while controls showed the opposite tendency. ► The tendency observed in schizophrenic patients parallels the tendency observed in Alzheimer disease patients.

Functional connectivity measured with magnetoencephalography identifies persons with HIV disease

There is need for a valid and reliable biomarker for HIV Associated Neurocognitive Disorder (HAND). The purpose of the present study was to provide preliminary evidence of the potential utility of neuronal functional connectivity measures obtained using magnetoencephalography (MEG) to identify HIV-associated changes in brain function. Resting state, eyes closed, MEG data from 10 HIV-infected individuals and 8 seronegative controls were analyzed using mutual information (MI) between all pairs of MEG sensors to ...