Intelligence and EEG current density using low-resolution electromagnetic tomography (LORETA)

Brain Functional Correlates of Intelligence Score in ADHD Based on EEG

Introduction

It has been shown that intelligence as a general mental ability is related to the structure and function of the brain regions. However, the specificity of these regional dependencies to the intelligence scores in the typical and atypical developed individuals needs to be well understood. In this study, we hypothesized that neural correlates of IQ should not have a fixed pattern rather they must follow a dynamic pattern to compensate for the functional deficits caused by a neurodevelopmental disorder. Therefore, electroencephalography (EEG) correlates of normal IQ in various subtypes of attention deficit hyperactive disorder (ADHD) were compared with a group of healthy controls.

Methods

Sixty-three ADHD subjects comprising combined, inattentive, and hyperactive individuals diagnosed by a psychiatrist using structural clinical interview for DSM-V, and 46 healthy controls with similar normal IQ scores were recruited in this study. The subjects' EEG data were then recorded during an eye-closed resting condition. The subjects' intelligence level was measured by Raven's standard progressive matrices. Then, the association between IQ and the power of the EEG signal was computed in the conventional frequency bands. Subsequently, topographical representations of these associations were compared between the groups.

Results

Our results demonstrated that the association between IQ score and EEG power is not the same in various ADHD subtypes and healthy controls.

Conclusion

This finding suggests a compensatory mechanism in ADHD individuals for changing the regional oscillatory pattern to maintain the IQ within a normal range.

INTELLIGENCE LEVEL MIGHT BE PREDICTED BY THE CHARACTERISTICS OF EEG SIGNALS AT SPECIFIC FREQUENCIES AND BRAIN REGIONS

The total energy the brain consumed and the intensities of information flows across different brain regions in an intellectual activity may help to explain an individual’s intelligence level. To verify this assumption, 43 students aged 18–25 were recruited as the research subjects. Their intelligence quotients (IQ) were scored by using Wechsler Adult Intelligence Scale (WAIS), while their electroencephalogram (EEG) signals were recorded simultaneously by using Neuroscan system. The total energy and distribution patterns of EEG signals were acquired in Curry 8.0. The intensities of information flow across different brain regions were measured by Phase Slope Index (PSI). 20 channels and 190 channel combinations were selected for data analysis. The results show that the IQ score negatively correlates to the EEG energy and positively correlates to the intensities of information flows at specific frequency bands in specific channel pairs, especially in some long distance (18–24[Formula: see text]cm) channel pairs.

Resting State EEG Related to Mathematical Improvement After Spatial Training in Children

Spatial cognitive abilities, including mental rotation (MR) and visuo-spatial working memory (vsWM) are correlated with mathematical performance, and several studies have shown that training of these abilities can enhance mathematical performance. Here, we investigated the behavioral and neural correlates of MR and vsWM training combined with number line (NL) training. Fifty-seven children, aged 6–7, performed 25 days of NL training combined with either vsWM or MR and participated in an Electroencephalography (EEG)-session in school to measure resting state activity and steady-state visual evoked potentials during a vsWM task before and after training. Fifty children, aged 6–7, received usual teaching and acted as a control group. Compared to the control group, both training groups improved on a combined measure of mathematics. Cognitive improvement was specific to the training. Significant pre-post changes in resting state-EEG (rs-EEG), common to both training groups, were found for power as well as for coherence, with no significant differences in rs-EEG-changes between the vsWM and MR groups. Two of the common rs-EEG changes were correlated with mathematical improvement: (1) an increase in coherence between the central frontal lobe and the right parietal lobe in frequencies ranging from 16 to 25 Hz, and (2) an increase in coherence between the left frontal lobe and the right parietal lobe ranging from 23 to 25 Hz. These results indicate that changes in fronto-parietal coherence are related to an increase in mathematical performance, which thus might be a useful measure in further investigations of mathematical interventions in children.

Resting-State Brain Network Deficits in Multiple Sclerosis Participants: Evidence from Electroencephalography and Graph Theoretical Analysis

Background: Multiple sclerosis (MS) is a chronic inflammatory disease leading to demyelination and axonal loss in the central nervous system that causes focal lesions of gray and white matter. However, the functional impairments of brain networks in this disease are still unspecified and need to be clearer. Materials and Methods: In the present study, we investigate the resting-state brain network impairments for MS participants in comparison to a normal group using electroencephalography (EEG) and graph theoretical analysis with a source localization method. Thirty-four age- and gender-matched participants from each MS group and normal group participated in this study. We recorded 5 min of EEG in the resting-state eyes open condition for each participant. One min (15 equal 4-sec artifact-free segments) of the EEG signals were selected for each participant, and the Low-Resolution Electromagnetic Tomography software was employed to calculate the functional connectivity among whole cortical regions in six frequency bands (delta, theta, alpha, beta1, beta2, and beta3). Graph theoretical analysis was used to calculate the clustering coefficient (CL), betweenness centrality (BC), shortest path length (SPL), and small-world propensity (SWP) for weighted connectivity matrices. Nonparametric permutation tests were utilized to compare these measures between groups. Results: Significant differences between the MS group and the normal group in the average of BC and SWP were found in the alpha band. The significant differences in the BC were spread over all lobes. Conclusion: These results suggest that the resting-state brain network for the MS group is disrupted in local and global scales, and EEG has the capability of revealing these impairments.

The genome-wide risk alleles for psychiatric disorders at 3p21.1 show convergent effects on mRNA expression, cognitive function, and mushroom dendritic spine

Schizophrenia and bipolar disorder (BPD) are believed to share clinical features, etiological factors, and disease pathologies (such as impaired cognitive functions and dendritic spine pathology). Meanwhile, there is growing evidence of shared genetic risk between schizophrenia and BPD, despite that our knowledge of the functional risk variations and biological mechanisms is still limited. Here, we conduct summary data-based Mendelian randomization (SMR) analyses through combining the statistical data from genome-wide association studies (GWAS) of both schizophrenia and BPD and multiple expression quantitative trait loci (eQTL) datasets of the human brain dorsolateral prefrontal cortex (DLPFC) tissues. These integrative investigations identify a lead risk locus at the chromosome 3p21.1 region, which contains numerous single-nucleotide polymorphisms (SNPs) in varied linkage disequilibrium (LD) and encompasses more than 20 genes. Further analyses suggest that many SNPs at 3p21.1 are significantly associated with both schizophrenia and BPD, and even depression, and the psychiatric risk alleles at 3p21.1 are correlated with mRNA expression of multiple genes such as NEK4, GNL3, and PBRM1. We also identify a 335-bp functional Alu polymorphism rs71052682 in significant LD with the psychiatric GWAS risk SNP rs2251219, and confirm the regulatory effects of this Alu polymorphism on transcription activities. We then explore the involvement of the 3p21.1 locus in the common clinical features and etiology of these illnesses. We reveal that psychiatric risk alleles at 3p21.1 in low-to-high LD consistently predict worse cognitive functions in humans, and manipulating the gene expression (NEK4, GNL3, and PBRM1) linked with higher genetic risk could reduce the density of mushroom dendritic spines in rat primary cortical neurons, mirroring the spine pathology in the prefrontal cortex of psychiatric patients. Our results find that, although the risk alleles at 3p21.1 are in low-to-moderate LD spanning a large genomic area, their underlying biological mechanisms in psychiatric disorders likely converge. These results provide essential insights into the neural mechanisms underlying the chromosome 3p21.1 risk locus in the shared pathological and etiological features of both schizophrenia and BPD.

EEG coherence in theta, alpha, and beta bands in frontal regions and executive functions

Executive functions are higdevel cognitive processes that make possible the formation of flexible and adaptive goal-directed behaviors and the frontal lobes regulate these functions. The purpose of this study was to investigate the relationship between frontal EEG coherence in theta, alpha, and beta bands and executive functions in adults. A sample of 168 students (M_age = 25.44 years, SD = 4.52) were included in this study. EEG records were recorded at the psychology laboratory of Mohaghegh Ardabili University (Iran), then intrahemispheric and interhemispheric coherence of frontal regions were analyzed using the NeuroGuide software. The participants were asked to fill in the Adult Executive Skills Questionnaire. Correlational results showed that there is a positive relationship between executive functions and EEG coherence in theta, alpha, and beta bands in frontal regions of the left hemisphere, EEG coherence of alpha and beta bands in frontal regions of the right hemisphere and EEG coherence of alpha band between frontal regions of the two hemispheres. The results of the regression analysis also revealed that coherence of alpha, beta, and theta bands between left and right frontal regions and coherence of beta and theta bands in the left frontal regions predict executive functions. These results indicate that the common activity of frontal cortex, especially the left hemisphere, is associated with executive functions and cognitive control.

Inter-ictal network of focal epilepsy and effects of clinical factors on network activity

OBJECTIVE

Aim of the study was to explore the inter-ictal, resting-state EEG network in patients with focal epilepsy (FE) and to specify clinical factors that influence network activity.

METHODS

Functional EEG connectivity (EEGfC) differences were computed between 232 FE patients (FE group) and 77 healthy controls. EEGfC was computed among 23 cortical regions within each hemisphere, for 25 very narrow bands from 1 to 25 Hz. We computed independent effects for six clinical factors on EEGfC in the FE group, by ANOVA and post-hoc t-statistics, corrected for multiple comparisons by false discovery rate method.

RESULTS

Robust, statistically significant EEGfC differences emerged between the FE and the healthy control groups. Etiology, seizure type, duration of the illness and antiepileptic treatment were independent factors that influenced EEGfC. Statistically significant results occurred selectively in one or a few very narrow bands and outlined networks. Most abnormal EEGfC findings occurred at frequencies that mediate integrative and motor activities.

CONCLUSIONS

FE patients have abnormal resting-state EEGfC network activity. Clinical factors significantly modify EEGfC.

SIGNIFICANCE

Delineation of the FE network and modifying factors can open the way for targeted investigations and introduction of EEGfC into epilepsy research and practice.

Genome-wide association analysis links multiple psychiatric liability genes to oscillatory brain activity

Oscillatory activity is crucial for information processing in the brain, and has a long history as a biomarker for psychopathology. Variation in oscillatory activity is highly heritable, but current understanding of specific genetic influences remains limited. We performed the largest genome-wide association study to date of oscillatory power during eyes-closed resting electroencephalogram (EEG) across a range of frequencies (delta 1-3.75 Hz, theta 4-7.75 Hz, alpha 8-12.75 Hz, and beta 13-30 Hz) in 8,425 subjects. Additionally, we performed KGG positional gene-based analysis and brain-expression analyses. GABRA2-a known genetic marker for alcohol use disorder and epilepsy-significantly affected beta power, consistent with the known relation between GABAA interneuron activity and beta oscillations. Tissue-specific SNP-based imputation of gene-expression levels based on the GTEx database revealed that hippocampal GABRA2 expression may mediate this effect. Twenty-four genes at 3p21.1 were significant for alpha power (FDR q < .05). SNPs in this region were linked to expression of GLYCTK in hippocampal tissue, and GNL3 and ITIH4 in the frontal cortex-genes that were previously implicated in schizophrenia and bipolar disorder. In sum, we identified several novel genetic variants associated with oscillatory brain activity; furthermore, we replicated and advanced understanding of previously known genes associated with psychopathology (i.e., schizophrenia and alcohol use disorders). Importantly, these psychopathological liability genes affect brain functioning, linking the genes' expression to specific cortical/subcortical brain regions.

The sleep EEG spectrum is a sexually dimorphic marker of general intelligence

The shape of the EEG spectrum in sleep relies on genetic and anatomical factors and forms an individual "EEG fingerprint". Spectral components of EEG were shown to be connected to mental ability both in sleep and wakefulness. EEG sleep spindle correlates of intelligence, however, exhibit a sexual dimorphism, with a more pronounced association to intelligence in females than males. In a sample of 151 healthy individuals, we investigated how intelligence is related to spectral components of full-night sleep EEG, while controlling for the effects of age. A positive linear association between intelligence and REM anterior beta power was found in females but not males. Transient, spindle-like "REM beta tufts" are described in the EEG of healthy subjects, which may reflect the functioning of a recently described cingular-prefrontal emotion and motor regulation network. REM sleep frontal high delta power was a negative correlate of intelligence. NREM alpha and sigma spectral power correlations with intelligence did not unequivocally remain significant after multiple comparisons correction, but exhibited a similar sexual dimorphism. These results suggest that the neural oscillatory correlates of intelligence in sleep are sexually dimorphic, and they are not restricted to either sleep spindles or NREM sleep.

Intelligence and eeg measures of information flow: efficiency and homeostatic neuroplasticity

The purpose of this study was to explore the relationship between the magnitude of EEG information flow and intelligence. The electroencephalogram (EEG) was recorded from 19 scalp locations from 371 subjects ranging in age from 5 years to 17.6 years. The Wechler Intelligence Scale for Children (WISC-R) was administered for individuals between 5 years of age and 16 years and the Weschler Adult Intelligence Scale revised (WAIS-R) was administered to subjects older than 16 years to estimate I.Q. The phase slope index estimated the magnitude of information flow between all electrode combinations for difference frequency bands. Discriminant analyses were performed between high I.Q. (>120) and low I.Q. groups (<90). The magnitude of information flow was inversely related to I.Q. especially in the alpha and beta frequency bands. Long distance inter-electrode distances exhibited greater information flow than short inter-electrode distances. Frontal-parietal correlations were the most significant. It is concluded that higher I.Q. is related to increased efficiency of local information processing and reduced long distance compensatory dynamics that supports a small-world model of intelligence.

Age-related changes in sleep EEG are attenuated in highly intelligent individuals

Impaired sleep is a frequent complaint in ageing and a risk factor for many diseases. Non-rapid eye movement (NREM) sleep EEG delta power reflects neural plasticity and, in line with age-related cognitive decline, decreases with age. Individuals with higher general intelligence are less affected by age-related cognitive decline or other disorders and have longer lifespans. We investigated the correlation between age and EEG power in 159 healthy human subjects (age range: 17-69 years), and compared an average (IQ<120; N=87) with a high (IQ≥120; N=72) intelligence subgroup. We found less age-related decrease in all-night relative NREM sleep EEG delta power in the high intelligence subgroup. Our results suggest that highly intelligent individuals are less affected by the sleep-related effects of biological ageing, and therefore potentially less at risk for age-related cognitive deficits and other diseases.

Low-Resolution Electromagnetic Tomography (LORETA) of changed Brain Function Provoked by Pro-Dopamine Regulator (KB220z) in one Adult ADHD case

Attention Deficit-Hyperactivity Disorder (ADHD) often continues into adulthood. Recent neuroimaging studies found lowered baseline dopamine tone in the brains of affected individuals that may place them at risk for Substance Use Disorder (SUD). This is an observational case study of the potential for novel management of Adult ADHD with a non-addictive glutaminergic-dopaminergic optimization complex KB200z. Low-resolution electromagnetic tomography (LORETA) was used to evaluate the effects of KB220z on a 72-year-old male with ADHD, at baseline and one hour following administration. The resultant z-scores, averaged across Eyes Closed, Eyes Open and Working Memory conditions, increased for each frequency band, in the anterior, dorsal and posterior cingulate regions, as well as the right dorsolateral prefrontal cortex during Working Memory, with KB220z. These scores are consistent with other human and animal neuroimaging studies that demonstrated increased connectivity volumes in reward circuitry and may offer a new approach to ADHD treatment. However, larger randomized trials to confirm these results are required.

The Athlete's Brain: Cross-Sectional Evidence for Neural Efficiency during Cycling Exercise

The “neural efficiency” hypothesis suggests that experts are characterized by a more efficient cortical function in cognitive tests. Although this hypothesis has been extended to a variety of movement-related tasks within the last years, it is unclear whether or not neural efficiency is present in cyclists performing endurance exercise. Therefore, this study examined brain cortical activity at rest and during exercise between cyclists of higher (HIGH; n = 14; 55.6 ± 2.8 mL/min/kg) and lower (LOW; n = 15; 46.4 ± 4.1 mL/min/kg) maximal oxygen consumption (VO_2MAX). Male and female participants performed a graded exercise test with spirometry to assess VO_2MAX. After 3 to 5 days, EEG was recorded at rest with eyes closed and during cycling at the individual anaerobic threshold over a 30 min period. Possible differences in alpha/beta ratio as well as alpha and beta power were investigated at frontal, central, and parietal sites. The statistical analysis revealed significant differences between groups (F = 12.04; p = 0.002), as the alpha/beta ratio was increased in HIGH compared to LOW in both the resting state (p ≤ 0.018) and the exercise condition (p ≤ 0.025). The present results indicate enhanced neural efficiency in subjects with high VO_2MAX, possibly due to the inhibition of task-irrelevant cognitive processes.

Development of Network Synchronization Predicts Language Abilities

Synchronization of oscillations among brain areas is understood to mediate network communication supporting cognition, perception, and language. How task-dependent synchronization during word production develops throughout childhood and adolescence, as well as how such network coherence is related to the development of language abilities, remains poorly understood. To address this, we recorded magnetoencephalography while 73 participants aged 4-18 years performed a verb generation task. Atlas-guided source reconstruction was performed, and phase synchronization among regions was calculated. Task-dependent increases in synchronization were observed in the theta, alpha, and beta frequency ranges, and network synchronization differences were observed between age groups. Task-dependent synchronization was strongest in the theta band, as were differences between age groups. Network topologies were calculated for brain regions associated with verb generation and were significantly associated with both age and language abilities. These findings establish the maturational trajectory of network synchronization underlying expressive language abilities throughout childhood and adolescence and provide the first evidence for an association between large-scale neurophysiological network synchronization and individual differences in the development of language abilities.

How to trust a perfect stranger: predicting initial trust behavior from resting-state brain-electrical connectivity

Reciprocal exchanges can be understood as the updating of an initial belief about a partner. This initial level of trust is essential when it comes to establishing cooperation with an unknown partner, as cooperation cannot arise without a minimum of trust not justified by previous successful exchanges with this partner. Here we demonstrate the existence of a representation of the initial trust level before an exchange with a partner has occurred. Specifically, we can predict the Investor's initial investment--i.e. his initial level of trust toward the unknown trustee in Round 1 of a standard 10-round Trust Game-from resting-state functional connectivity data acquired several minutes before the start of the Trust Game. Resting-state functional connectivity is, however, not significantly associated with the level of trust in later rounds, potentially mirroring the updating of the initial belief about the partner. Our results shed light on how the initial level of trust is represented. In particular, we show that a person's initial level of trust is, at least in part, determined by brain electrical activity acquired well before the beginning of an exchange.

LORETA EEG phase reset of the default mode network

Objectives: The purpose of this study was to explore phase reset of 3-dimensional current sources in Brodmann areas located in the human default mode network (DMN) using Low Resolution Electromagnetic Tomography (LORETA) of the human electroencephalogram (EEG).

Methods: The EEG was recorded from 19 scalp locations from 70 healthy normal subjects ranging in age from 13 to 20 years. A time point by time point computation of LORETA current sources were computed for 14 Brodmann areas comprising the DMN in the delta frequency band. The Hilbert transform of the LORETA time series was used to compute the instantaneous phase differences between all pairs of Brodmann areas. Phase shift and lock durations were calculated based on the 1st and 2nd derivatives of the time series of phase differences.

Results: Phase shift duration exhibited three discrete modes at approximately: (1) 25 ms, (2) 50 ms, and (3) 65 ms. Phase lock duration present primarily at: (1) 300–350 ms and (2) 350–450 ms. Phase shift and lock durations were inversely related and exhibited an exponential change with distance between Brodmann areas.

Conclusions: The results are explained by local neural packing density of network hubs and an exponential decrease in connections with distance from a hub. The results are consistent with a discrete temporal model of brain function where anatomical hubs behave like a “shutter” that opens and closes at specific durations as nodes of a network giving rise to temporarily phase locked clusters of neurons for specific durations.

Cognitive impairment and EEG background activity in adults with Down's syndrome: a topographic study

OBJECTIVE

Studies correlating electroencephalographic (EEG) data and cognitive performance in Down's syndrome (DS) showed conflicting results. The aims of this study were to investigate the sources of EEG rhythms in adults with DS at three dimensional representation of current source density (CSD) using exact/standard Low Resolution Electromagnetic Tomography (e/sLORETA), and their correlation with cognitive performance.

METHODS

Twenty-five adults with DS underwent a neuropsychological battery and 5 min of resting, eye-closed 29-channel EEG were recorded. After e/sLORETA analysis, data were compared with those from age and gender-matching control subjects as following: absolute and relative power in delta (1-3 Hz), theta (4-7 Hz), alpha1 (8-9 Hz), alpha2 (10-12 Hz), beta1 (13-18 Hz), beta2 (19-21 Hz), beta3 (22-30 Hz); alpha and theta bands adjusted to individual alpha peak frequency (IAF). Current source activities in DS group in regions showing significant differences compared with controls underwent correlation analysis with psychometric scores.

RESULTS

In DS, IAF was shifted to lower frequencies and correlated positively with Wechsler Adult Intelligence Scale and Mini-Mental State examination. Compared with controls, DS showed increased CSD in: theta, alpha-1, and beta1 classical bands and in IAF-adjusted bands, while relative alpha2 was decreased. A negative correlation between cognitive performance and theta/alpha CSD in the right frontal lobe and right posterior cingulate cortex was found. The relative alpha2 correlated positively with cognitive tests.

CONCLUSIONS

Increased CSD in DS, correlating with cognitive performance, for both slow and fast rhythms suggests involving of cortical and subcortical mechanisms. LORETA might be useful for objective measure of cognitive decline in DS.

Diffusion spectral imaging modules correlate with EEG LORETA neuroimaging modules

OBJECTIVES

The purpose of this study was to test the hypothesis that the highest temporal correlations between 3-dimensional EEG current source density corresponds to anatomical Modules of high synaptic connectivity.

METHODS

Eyes closed and eyes open EEG was recorded from 19 scalp locations with a linked ears reference from 71 subjects age 13-42 years. LORETA was computed from 1 to 30 Hz in 2,394 cortical gray matter voxels that were grouped into six anatomical Modules corresponding to the ROIs in the Hagmann et al.'s [2008] diffusion spectral imaging (DSI) study. All possible cross-correlations between voxels within a DSI Module were compared with the correlations between Modules.

RESULTS

The Hagmann et al. [ 2008] Module correlation structure was replicated in the correlation structure of EEG three-dimensional current source density.

CONCLUSIONS

EEG Temporal correlation between brain regions is related to synaptic density as measured by diffusion spectral imaging.

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.

Neurodevelopmental effects of prenatal exposure to psychotropic medications

Until now, studies on the reproductive safety of psychotropics have typically assessed the risk of congenital malformations and perinatal complications associated with in utero exposure to such medications. However, little is known of their inherent potential neurobehavioral teratogenicity. The objective is to analyze available data from studies investigating developmental outcome of children exposed prenatally to psychotropics. A computerized Medline/PubMed/TOXNET/ENBASE search (1960-2010) was conducted using the following keywords: pregnancy, child/infant development/neurodevelopment, antidepressants, benzodiazepines, mood stabilizers, and antipsychotics. A separate search was also run to complete the safety profile of single specific medications. Resultant articles were cross-referenced for other relevant articles not identified in the initial search. A noncomputerized review of pertinent journals and textbooks was also performed. All studies published in English and reporting primary data on the developmental outcome of infants exposed in utero to psychotropics and born without malformations were collected. As regards antiepileptic drugs, only studies that provided data on specific medications approved for psychiatric practice use (carbamazepine, lamotrigine, and valproate) were considered. Data were extracted from 41 articles (38 identified electronically and 3 nonelectronically), which met the inclusion criteria. Despite reviewed studies showing relevant methodological limitations, concordant, albeit preliminary, information seems to exclude that prenatal exposure to both selective serotonin reuptake inhibitors and tricyclic antidepressants may interfere with the infants' psychological and cognitive development. Conversely, information on valproate strongly discourages its use in pregnant women. Moreover, although data on carbamazepine remain controversial, information on whole classes of drugs and single medications is either absent (second-generation antipsychotics) or too limited (first-generation antipsychotics, benzodiazepines, lithium, and lamotrigine) to inform the decision-making process. For all classes of psychotropics, new and/or further studies are warranted to answer definitively the urgent question about the impact of prenatal exposure to such medications on infant development.

Functional and anatomical connectivity abnormalities in left inferior frontal gyrus in schizophrenia

Functional studies in schizophrenia demonstrate prominent abnormalities within the left inferior frontal gyrus (IFG) and also suggest the functional connectivity abnormalities in language network including left IFG and superior temporal gyrus during semantic processing. White matter connections between regions involved in the semantic network have also been indicated in schizophrenia. However, an association between functional and anatomical connectivity disruptions within the semantic network in schizophrenia has not been established. Functional (using levels of processing paradigm) as well as diffusion tensor imaging data from 10 controls and 10 chronic schizophrenics were acquired and analyzed. First, semantic encoding specific activation was estimated, showing decreased activation within the left IFG in schizophrenia. Second, functional time series were extracted from this area, and left IFG specific functional connectivity maps were produced for each subject. In an independent analysis, tract-based spatial statistics (TBSS) was used to compare fractional anisotropy (FA) values between groups, and to correlate these values with functional connectivity maps. Schizophrenia patients showed weaker functional connectivity within the language network that includes left IFG and left superior temporal sulcus/middle temporal gyrus. FA was reduced in several white matter regions including left inferior frontal and left internal capsule. Finally, left inferior frontal white matter FA was positively correlated with connectivity measures of the semantic network in schizophrenics, but not in controls. Our results indicate an association between anatomical and functional connectivity abnormalities within the semantic network in schizophrenia, suggesting further that the functional abnormalities observed in this disorder might be directly related to white matter disruptions.

Intelligence and EEG phase reset: a two compartmental model of phase shift and lock

OBJECTIVES

The purpose of this study was to explore the relationship between EEG phase reset and performance on the Wechsler Intelligence test.

METHODS

The electroencephalogram (EEG) was recorded from 19 scalp locations from 378 subjects ranging in age from 5 years to 17.6 years. The Wechsler Intelligence test (WISC-R) was administered to the same subjects on the same day but not while the EEG was recorded. Complex demodulation was used to compute instantaneous EEG phase differences between pairs of electrodes and the 1st and 2nd derivatives were used to measure phase reset by phase shift duration and phase lock duration. The dependent variable was full scale I.Q. and the independent variables were phase shift duration (SD) and phase lock duration (LD) with age as a covariate.

RESULTS

Phase shift duration (40-90 ms) was positively related to intelligence (P<.00001) and the phase lock duration (100-800 ms) was negatively related to intelligence (P<.00001). Phase reset in short interelectrode distances (6 cm) was more highly correlated to I.Q. (P<.0001) than in long distances (>12 cm).

CONCLUSIONS

The duration of unstable phase dynamics and phase locking represent a bounded optimization process, for example, too long a duration of phase locking then less flexibility and too short of a phase shift then reduced neural resources. A two compartmental model of local field coupling and neuron synchrony to a preferred phase was developed to explain the findings.

The neuronal basis of intelligence: A riddle, wrapped in a mystery?

“Where in the brain is intelligence?” is an intriguing question, and Jung & Haier (J&H) resist the temptation to provide a simple answer. Their concept tries to integrate and transcend previous findings, and, while omitting the contributions from complementary methods, results seem to converge. Whether similarities or differences in such networks are more important, though, is still open for discussion.