The impact of cumulative obstetric complications and childhood trauma on brain volume in young people with psychotic experiences.

Psychotic experiences (PEs) occur in 5-10% of the general population and are associated with exposure to childhood trauma and obstetric complications. However, the neurobiological mechanisms underlying these associations are unclear. Using the Avon Longitudinal Study of Parents and Children (ALSPAC), we studied 138 young people aged 20 with PEs (n = 49 suspected, n = 53 definite, n = 36 psychotic disorder) and 275 controls. Voxel-based morphometry assessed whether MRI measures of grey matter volume were associated with (i) PEs, (ii) cumulative childhood psychological trauma (weighted summary score of 6 trauma types), (iii) cumulative pre/peri-natal risk factors for psychosis (weighted summary score of 16 risk factors), and (iv) the interaction between PEs and cumulative trauma or pre/peri-natal risk. PEs were associated with smaller left posterior cingulate (pFWE < 0.001, Z = 4.19) and thalamus volumes (pFWE = 0.006, Z = 3.91). Cumulative pre/perinatal risk was associated with smaller left subgenual cingulate volume (pFWE < 0.001, Z = 4.54). A significant interaction between PEs and cumulative pre/perinatal risk found larger striatum (pFWE = 0.04, Z = 3.89) and smaller right insula volume extending into the supramarginal gyrus and superior temporal gyrus (pFWE = 0.002, Z = 4.79), specifically in those with definite PEs and psychotic disorder. Cumulative childhood trauma was associated with larger left dorsal striatum (pFWE = 0.002, Z = 3.65), right prefrontal cortex (pFWE < 0.001, Z = 4.63) and smaller left insula volume in all participants (pFWE = 0.03, Z = 3.60), and there was no interaction with PEs group. In summary, pre/peri-natal risk factors and childhood psychological trauma impact similar brain pathways, namely smaller insula and larger striatum volumes. The effect of pre/perinatal risk was greatest in those with more severe PEs, whereas effects of trauma were seen in all participants. In conclusion, environmental risk factors affect brain networks implicated in schizophrenia, which may increase an individual's propensity to develop later psychotic disorders.

Morphometric Analysis of Structural MRI Using Schizophrenia Meta-analytic Priors Distinguish Patients from Controls in Two Independent Samples and in a Sample of Individuals With High Polygenic Risk.

Schizophrenia (SCZ) is associated with structural brain changes, with considerable variation in the extent to which these cortical regions are influenced. We present a novel metric that summarises individual structural variation across the brain, while considering prior effect sizes, established via meta-analysis. We determine individual participant deviation from a within-sample-norm across structural MRI regions of interest (ROIs). For each participant, we weight the normalised deviation of each ROI by the effect size (Cohen's d) of the difference between SCZ/control for the corresponding ROI from the SCZ Enhancing Neuroimaging Genomics through Meta-Analysis working group. We generate a morphometric risk score (MRS) representing the average of these weighted deviations. We investigate if SCZ-MRS is elevated in a SCZ case/control sample (NCASE = 50; NCONTROL = 125), a replication sample (NCASE = 23; NCONTROL = 20) and a sample of asymptomatic young adults with extreme SCZ polygenic risk (NHIGH-SCZ-PRS = 95; NLOW-SCZ-PRS = 94). SCZ cases had higher SCZ-MRS than healthy controls in both samples (Study 1: ß = 0.62, P < 0.001; Study 2: ß = 0.81, P = 0.018). The high liability SCZ-PRS group also had a higher SCZ-MRS (Study 3: ß = 0.29, P = 0.044). Furthermore, the SCZ-MRS was uniquely associated with SCZ status, but not attention-deficit hyperactivity disorder (ADHD), whereas an ADHD-MRS was linked to ADHD status, but not SCZ. This approach provides a promising solution when considering individual heterogeneity in SCZ-related brain alterations by identifying individual's patterns of structural brain-wide alterations.

Global Brain Flexibility During Working Memory Is Reduced in a High-Genetic-Risk Group for Schizophrenia.

BACKGROUND: Altered functional brain connectivity has been proposed as an intermediate phenotype between genetic risk loci and clinical expression of schizophrenia. Genetic high-risk groups of healthy subjects are particularly suited for the investigation of this proposition because they can be tested in the absence of medication or other secondary effects of schizophrenia. METHODS: Here, we applied dynamic functional connectivity analysis to functional magnetic resonance imaging data to reveal the reconfiguration of brain networks during a cognitive task. We recruited healthy carriers of common risk variants using the recall-by-genotype design. We assessed 197 individuals: 99 individuals (52 female, 47 male) with low polygenic risk scores (schizophrenia risk profile scores [SCZ-PRSs]) and 98 individuals (52 female, 46 male) with high SCZ-PRSs from both tails of the SCZ-PRS distribution from a genotyped population cohort, the Avon Longitudinal Study of Parents and Children (N = 8169). We compared groups both on conventional brain activation profiles, using the general linear model of the experiment, and on the neural flexibility index, which quantifies how frequent a brain region's community affiliation changes over experimental time. RESULTS: Behavioral performance and standard brain activation profiles did not differ significantly between groups. High SCZ-PRS was associated with reduced flexibility index and network modularity across n-back levels. The whole-brain flexibility index and that of the frontoparietal working memory network was associated with n-back performance. We identified a dynamic network phenotype related to high SCZ-PRS. CONCLUSIONS: Such neurophysiological markers can become important for the elucidation of biological mechanisms of schizophrenia and, particularly, the associated cognitive deficit.

The gamma response to colour hue in humans: Evidence from MEG.

It has recently been demonstrated through invasive electrophysiology that visual stimulation with extended patches of uniform colour generates pronounced gamma oscillations in the visual cortex of both macaques and humans. In this study we sought to discover if this oscillatory response to colour can be measured non-invasively in humans using magnetoencephalography. We were able to demonstrate increased gamma (40-70 Hz) power in response to full-screen stimulation with four different colour hues and found that the gamma response is particularly strong for long wavelength (i.e. red) stimulation, as was found in previous studies. However, we also found that gamma power in response to colour was generally weaker than the response to an identically sized luminance-defined grating. We also observed two additional responses in the gamma frequency: a lower frequency response around 25-35 Hz that showed fewer clear differences between conditions than the gamma response, and a higher frequency response around 70-100 Hz that was present for red stimulation but not for other colours. In a second experiment we sought to test whether differences in the gamma response between colour hues could be explained by their chromatic separation from the preceding display. We presented stimuli that alternated between each of the three pairings of the three primary colours (red, green, blue) at two levels of chromatic separation defined in the CIELUV colour space. We observed that the gamma response was significantly greater to high relative to low chromatic separation, but that at each level of separation the response was greater for both red-blue and red-green than for blue-green stimulation. Our findings suggest that the stronger gamma response to red stimulation cannot be wholly explained by the chromatic separation of the stimuli.

Population neuroimaging: generation of a comprehensive data resource within the ALSPAC pregnancy and birth cohort.

Neuroimaging offers a valuable insight into human brain development by allowing in vivo assessment of structure, connectivity and function. Multimodal neuroimaging data have been obtained as part of three sub-studies within the Avon Longitudinal Study of Parents and Children, a prospective multigenerational pregnancy and birth cohort based in the United Kingdom. Brain imaging data were acquired when offspring were between 18 and 24 years of age, and included acquisition of structural, functional and magnetization transfer magnetic resonance, diffusion tensor, and magnetoencephalography imaging. This resource provides a unique opportunity to combine neuroimaging data with extensive phenotypic and genotypic measures from participants, their mothers, and fathers.

Electrophysiological network alterations in adults with copy number variants associated with high neurodevelopmental risk.

Rare copy number variants associated with increased risk for neurodevelopmental and psychiatric disorders (referred to as ND-CNVs) are characterized by heterogeneous phenotypes thought to share a considerable degree of overlap. Altered neural integration has often been linked to psychopathology and is a candidate marker for potential convergent mechanisms through which ND-CNVs modify risk; however, the rarity of ND-CNVs means that few studies have assessed their neural correlates. Here, we used magnetoencephalography (MEG) to investigate resting-state oscillatory connectivity in a cohort of 42 adults with ND-CNVs, including deletions or duplications at 22q11.2, 15q11.2, 15q13.3, 16p11.2, 17q12, 1q21.1, 3q29, and 2p16.3, and 42 controls. We observed decreased connectivity between occipital, temporal, and parietal areas in participants with ND-CNVs. This pattern was common across genotypes and not exclusively characteristic of 22q11.2 deletions, which were present in a third of our cohort. Furthermore, a data-driven graph theory framework enabled us to successfully distinguish participants with ND-CNVs from unaffected controls using differences in node centrality and network segregation. Together, our results point to alterations in electrophysiological connectivity as a putative common mechanism through which genetic factors confer increased risk for neurodevelopmental and psychiatric disorders.

Structural and Functional Neuroimaging of Polygenic Risk for Schizophrenia: A Recall-by-Genotype-Based Approach.

Risk profile scores (RPS) derived from genome-wide association studies (GWAS) explain a considerable amount of susceptibility for schizophrenia (SCZ). However, little is known about how common genetic risk factors for SCZ influence the structure and function of the human brain, largely due to the constraints of imaging sample sizes. In the current study, we use a novel recall-by-genotype (RbG) methodological approach, where we sample young adults from a population cohort (Avon Longitudinal Study of Parents and Children: N genotyped = 8365) based on their SCZ-RPS. We compared 197 healthy individuals at extremes of low (N = 99) or high (N = 98) SCZ-RPS with behavioral tests, and structural and functional magnetic resonance imaging (fMRI). We first provide methodological details that will inform the design of future RbG studies for common SCZ genetic risk. We further provide an between group analysis of the RbG individuals (low vs high SCZ-RPS) who underwent structural neuroimaging data (T1-weighted scans) and fMRI data during a reversal learning task. While we found little evidence for morphometric differences between the low and high SCZ-RPS groups, we observed an impact of SCZ-RPS on blood oxygen level-dependent (BOLD) signal during reward processing in the ventral striatum (PFWE-VS-CORRECTED = .037), a previously investigated broader reward-related network (PFWE-ROIS-CORRECTED = .008), and across the whole brain (PFWE-WHOLE-BRAIN-CORRECTED = .013). We also describe the study strategy and discuss specific challenges of RbG for SCZ risk (such as SCZ-RPS related homoscedasticity). This study will help to elucidate the behavioral and imaging phenotypes that are associated with SCZ genetic risk.

Spatial frequency supports the emergence of categorical representations in visual cortex during natural scene perception.

In navigating our environment, we rapidly process and extract meaning from visual cues. However, the relationship between visual features and categorical representations in natural scene perception is still not well understood. Here, we used natural scene stimuli from different categories and filtered at different spatial frequencies to address this question in a passive viewing paradigm. Using representational similarity analysis (RSA) and cross-decoding of magnetoencephalography (MEG) data, we show that categorical representations emerge in human visual cortex at ∼180 ms and are linked to spatial frequency processing. Furthermore, dorsal and ventral stream areas reveal temporally and spatially overlapping representations of low and high-level layer activations extracted from a feedforward neural network. Our results suggest that neural patterns from extrastriate visual cortex switch from low-level to categorical representations within 200 ms, highlighting the rapid cascade of processing stages essential in human visual perception.

Spatiotemporal dynamics in human visual cortex rapidly encode the emotional content of faces.

Recognizing emotion in faces is important in human interaction and survival, yet existing studies do not paint a consistent picture of the neural representation supporting this task. To address this, we collected magnetoencephalography (MEG) data while participants passively viewed happy, angry and neutral faces. Using time-resolved decoding of sensor-level data, we show that responses to angry faces can be discriminated from happy and neutral faces as early as 90 ms after stimulus onset and only 10 ms later than faces can be discriminated from scrambled stimuli, even in the absence of differences in evoked responses. Time-resolved relevance patterns in source space track expression-related information from the visual cortex (100 ms) to higher-level temporal and frontal areas (200-500 ms). Together, our results point to a system optimised for rapid processing of emotional faces and preferentially tuned to threat, consistent with the important evolutionary role that such a system must have played in the development of human social interactions.

Assessment and elimination of the effects of head movement on MEG resting-state measures of oscillatory brain activity.

Magnetoencephalography (MEG) is increasingly being used to study brain function because of its excellent temporal resolution and its direct association with brain activity at the neuronal level. One possible cause of error in the analysis of MEG data comes from the fact that participants, even MEG-experienced ones, move their head in the MEG system. Head movement can cause source localization errors during the analysis of MEG data, which can result in the appearance of source variability that does not reflect brain activity. The MEG community places great importance in eliminating this source of possible errors as is evident, for example, by recent efforts to develop head casts that limit head movement in the MEG system. In this work we use software tools to identify, assess and eliminate from the analysis of MEG data any possible correlations between head movement in the MEG system and widely-used measures of brain activity derived from MEG resting-state recordings. The measures of brain activity we study are a) the Hilbert-transform derived amplitude envelope of the beamformer time series and b) functional networks; both measures derived by MEG resting-state recordings. Ten-minute MEG resting-state recordings were performed on healthy participants, with head position continuously recorded. The sources of the measured magnetic signals were localized via beamformer spatial filtering. Temporal independent component analysis was subsequently used to derive resting-state networks. Significant correlations were observed between the beamformer envelope time series and head movement. The correlations were substantially reduced, and in some cases eliminated, after a participant-specific temporal high-pass filter was applied to those time series. Regressing the head movement metrics out of the beamformer envelope time series had an even stronger effect in reducing these correlations. Correlation trends were also observed between head movement and the activation time series of the default-mode and frontal networks. Regressing the head movement metrics out of the beamformer envelope time series completely eliminated these correlations. Additionally, applying the head movement correction resulted in changes in the network spatial maps for the visual and sensorimotor networks. Our results a) show that the results of MEG resting-state studies that use the above-mentioned analysis methods are confounded by head movement effects, b) suggest that regressing the head movement metrics out of the beamformer envelope time series is a necessary step to be added to these analyses, in order to eliminate the effect that head movement has on the amplitude envelope of beamformer time series and the network time series and c) highlight changes in the connectivity spatial maps when head movement correction is applied.

Intersubject variability and induced gamma in the visual cortex: DCM with empirical Bayes and neural fields.

This article describes the first application of a generic (empirical) Bayesian analysis of between-subject effects in the dynamic causal modeling (DCM) of electrophysiological (MEG) data. It shows that (i) non-invasive (MEG) data can be used to characterize subject-specific differences in cortical microcircuitry and (ii) presents a validation of DCM with neural fields that exploits intersubject variability in gamma oscillations. We find that intersubject variability in visually induced gamma responses reflects changes in the excitation-inhibition balance in a canonical cortical circuit. Crucially, this variability can be explained by subject-specific differences in intrinsic connections to and from inhibitory interneurons that form a pyramidal-interneuron gamma network. Our approach uses Bayesian model reduction to evaluate the evidence for (large sets of) nested models-and optimize the corresponding connectivity estimates at the within and between-subject level. We also consider Bayesian cross-validation to obtain predictive estimates for gamma-response phenotypes, using a leave-one-out procedure. Hum Brain Mapp 37:4597-4614, 2016. © The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

The visual gamma response to faces reflects the presence of sensory evidence and not awareness of the stimulus.

It has been suggested that gamma (30-100 Hz) oscillations mediate awareness of visual stimuli, but tests of this hypothesis have produced differing results. We used phase scrambling to vary the perceptibility of face stimuli in order to determine whether gamma is indeed linked to perceptual awareness. Magnetoencephalography was used to measure the gamma response in 25 participants while viewing three conditions in which faces were presented either above, below or at the threshold for detection. In each of 400 trials (100 each for the sub- and suprathreshold conditions, 200 for the threshold condition), participants indicated whether they perceived a face in the stimulus. Gamma-band activity during the task was localized to bilateral ventral occipito-temporal cortex. For the threshold condition, we failed to find a significant difference in gamma amplitude between trials in which a face was perceived relative to those in which no face was perceived. However, we did find that gamma amplitude was significantly increased for threshold relative to subthreshold stimuli and for suprathreshold relative to threshold stimuli. This leads us to conclude that the gamma response to faces is primarily modulated by the presence of sensory evidence of a face rather by perceptual awareness.

Structural and neurochemical correlates of individual differences in gamma frequency oscillations in human visual cortex.

Neuronal oscillations in the gamma frequency range play an important role in stimulus processing in the brain. The frequency of these oscillations can vary widely between participants and is strongly genetically determined, but the cause of this variability is not understood. Previous studies have reported correlations between individual differences in gamma frequency and the concentration of the inhibitory neurotransmitter, gamma-aminobutyric acid (GABA), as well as with age and primary visual cortex (V1) area and thickness. This study assessed the relationships between all of these variables in the same group of participants. There were no significant correlations between gamma frequency and GABA+ concentration, V1 area or V1 thickness, although the relationship with GABA+/Cr approached significance. Considering age as a covariate further reduced the strength of all correlations and, in an additional dataset with a larger age range, gamma frequency was strongly inversely correlated with age but not V1 thickness or area, suggesting that age modulates gamma frequency via an additional, as yet unknown, mechanism. Consistent with other recent studies, these findings do not demonstrate a clear relationship between gamma frequency and GABA+ concentration. Further investigation of additional variables and the interactions between them will be necessary in order to more accurately determine predictors of the frequency of gamma oscillations.

The effects of cross-orientation masking on the visual gamma response in humans.

Electrophysiological recordings in primates indicate that visual gamma contains distinct broad- and narrowband components that reflect different neuronal processes. Evidence suggests that cross-orientation masking of luminance-defined gratings should differentially modulate these two components. To test this we measured the effect of cross-orientation masking on the gamma response in 12 human participants using magentoencephalography (MEG). Although both the amplitude and the frequency of gamma were modulated by the presence of a cross-orientation mask, we failed to find evidence for distinguishable components: both broadband gamma at stimulus onset and sustained narrowband gamma were similarly modulated by mask contrast. However, we could not confirm the presence of masking effects due to mask contrast being confounded with the contrast of the stimulus as a whole. We therefore tested a further 12 participants in a second experiment in which the stimuli were: a plaid stimulus, the two component gratings which formed the plaid and the same two gratings but with Michelson contrast matched to the plaid. We found that gamma amplitude was reduced and gamma frequency increased to the plaid stimulus when compared with the contrast-matched gratings or with the sum of the two component gratings, indicating that visual gamma was indeed modulated by cross-orientation masking. Surprisingly, masking did not affect the pattern-onset evoked response, challenging previous hypotheses that cross-orientation suppression - the phenomenon by which the response to an orientated grating is suppressed by a cross-orientation mask - is driven by feedforward inputs to V1.

Linear tuning of gamma amplitude and frequency to luminance contrast: evidence from a continuous mapping paradigm.

Individual differences in the visual gamma (30-100 Hz) response and their potential as trait markers of underlying physiology (particularly related to GABAergic inhibition) have become a matter of increasing interest in recent years. There is growing evidence, however, that properties of the gamma response (e.g., its amplitude and frequency) are highly stimulus dependent, and that individual differences in the gamma response may reflect individual differences in the stimulus tuning functions of gamma oscillations. Here, we measured the tuning functions of gamma amplitude and frequency to luminance contrast in eighteen participants using MEG. We used a grating stimulus in which stimulus contrast was modulated continuously over time. We found that both gamma amplitude and frequency were linearly modulated by stimulus contrast, but that the gain of this modulation (as reflected in the linear gradient) varied across individuals. We additionally observed a stimulus-induced response in the beta frequency range (10-25 Hz), but neither the amplitude nor the frequency of this response was consistently modulated by the stimulus over time. Importantly, we did not find a correlation between the gain of the gamma-band amplitude and frequency tuning functions across individuals, suggesting that these may be independent traits driven by distinct neurophysiological processes.

Evidence for increased visual gamma responses in photosensitive epilepsy.

BACKGROUND: A sustained gamma (30-70 Hz) oscillation induced in occipital cortex by high-contrast visual stimulation has been well characterised in animal local field potential recordings and in healthy human participants using magnetoencephalography (MEG). The spatial frequency of a static grating stimulus that gives maximal gamma is also that most likely to provoke seizures in photosensitive epilepsy. METHODS: We used MEG to study visual responses induced by grating stimuli of varying contrast and size in twelve patients with photosensitive epilepsy and two matched control groups, one with epilepsy but no photosensitivity, the other healthy controls. We used a beamformer approach to localise cortical responses and to characterise the time-frequency dynamics of evoked and induced oscillatory responses. RESULTS: A greater number of patients with photosensitivity had particularly amplitude gamma responses compared to controls. Formal statistical testing failed to find a group difference. One photosensitive patient, tested before and after sodium valproate, had a peak gamma amplitude when drug naive over four times larger than the group mean for controls; this high amplitude was substantially decreased after treatment with sodium valproate. We found no difference in the frequency of the sustained gamma response between the three groups. DISCUSSION: Altered power, but not frequency, in induced cortical responses to a static grating stimulus may be a characteristic of photosensitive epilepsy. Our failure to find a group difference on statistical testing may have been due to a wide intersubject variability and heterogeneity of the photosensitive group. A high amplitude response would be in keeping with previous evidence of altered contrast gain and increased spatial recruitment in photosensitive epilepsy.

Localizing evoked and induced responses to faces using magnetoencephalography.

A rich pattern of responses in frequency, time and space are known to be generated in the visual cortex in response to faces. Recently, a number of studies have used magnetoencephalography (MEG) to try to record these responses non-invasively - in many cases using source analysis techniques based on the beamforming method. Here we sought both to characterize best practice for measuring face-specific responses using MEG beamforming, and to determine whether the results produced by the beamformer match evidence from other modalities. We measured activity to visual presentation of face stimuli and phase-scrambled control stimuli, and performed source analyses of both induced and evoked responses using Synthetic Aperture Magnetometry. We localized the gamma-band response to bilateral lateral occipital cortex, and both the gamma-band response and the M170-evoked response to the right fusiform gyrus. Differences in the gamma-band response between faces and scrambled stimuli were confined to the frequency range 50-90 Hz; gamma-band activity at higher frequencies did not differ between the two stimulus categories. We additionally identified a component of the M220-evoked response - localized to the parieto-occipital sulcus - which was enhanced for scrambled vs. unscrambled faces. These findings help to establish that MEG beamforming can localize face-specific responses in time, frequency and space with good accuracy (when validated against established findings from functional magnetic resonance imaging and intracranial recordings), as well as contributing to the establishment of best methodological practice for the use of the beamformer method to measure face-specific responses.

The properties of induced gamma oscillations in human visual cortex show individual variability in their dependence on stimulus size.

The role of gamma-band (typically 30-100 Hz) oscillations in visual processing is a topic of increasing interest. One hypothesis is that gamma oscillations reflect the action of GABAergic inhibitory processes in the visual cortex responsible for surround-suppression. Evidence from primate neurophysiology [Gieselmann & Thiele, A., 2008. European Journal of Neuroscience 28, 447-459.] suggests that the amplitude of the gamma-band response increases as a visual grating stimulus expands outside of the classical receptive field into the inhibitory surround; with the amplitude of the response increasing, and the frequency of the response decreasing, monotonically with stimulus size. In this study, we tested the relationship between the gamma-band response and the size of visual grating stimuli in humans using MEG. In two initial experiments we found that, while the absolute magnitude of the gamma-band response varied considerably across participants, in all cases the amplitude of the response had a monotonically increasing relationship with size. In contrast, we did not find any relationship between the frequency of the response and the size of the stimulus. Previously, the frequency of the visual gamma-band response has been found to correlate across individuals with the surface area of cortical area V1 [Schwarzkopf et al., 2012. Journal of Neuroscience 32, 1507-12.] We, however, were unable to find any correlation between the frequency or the magnitude of the gamma-band response and the dimensions of V1 cortical gray matter as measured from participants' MR images. Consistent with a saturation of the gamma-band response found for some individuals in the first two experiments, in a third experiment we found that the magnitude of the response to our largest stimulus (8°) was less than that predicted from the response to the stimulus' parts.

Retinotopic mapping of the primary visual cortex - a challenge for MEG imaging of the human cortex.

Magnetoencephalography (MEG) can be used to reconstruct neuronal activity with high spatial and temporal resolution. However, this reconstruction problem is ill-posed, and requires the use of prior constraints in order to produce a unique solution. At present there are a multitude of inversion algorithms, each employing different assumptions, but one major problem when comparing the accuracy of these different approaches is that often the true underlying electrical state of the brain is unknown. In this study, we explore one paradigm, retinotopic mapping in the primary visual cortex (V1), for which the ground truth is known to a reasonable degree of accuracy, enabling the comparison of MEG source reconstructions with the true electrical state of the brain. Specifically, we attempted to localize, using a beanforming method, the induced responses in the visual cortex generated by a high contrast, retinotopically varying stimulus. Although well described in primate studies, it has been an open question whether the induced gamma power in humans due to high contrast gratings derives from V1 rather than the prestriate cortex (V2). We show that the beanformer source estimate in the gamma and theta bands does vary in a manner consistent with the known retinotopy of V1. However, these peak locations, although retinotopically organized, did not accurately localize to the cortical surface. We considered possible causes for this discrepancy and suggest that improved MEG/magnetic resonance imaging co-registration and the use of more accurate source models that take into account the spatial extent and shape of the active cortex may, in future, improve the accuracy of the source reconstructions.

Daily rhythms in olfactory discrimination depend on clock genes but not the suprachiasmatic nucleus.

The suprachiasmatic nucleus (SCN) regulates a wide range of daily behaviors and has been described as the master circadian pacemaker. The role of daily rhythmicity in other tissues, however, is unknown. We hypothesized that circadian changes in olfactory discrimination depend on a genetic circadian oscillator outside the SCN. We developed an automated assay to monitor olfactory discrimination in individual mice throughout the day. We found olfactory sensitivity increased approximately 6-fold from a minimum during the day to a peak in the early night. This circadian rhythm was maintained in SCN-lesioned mice and mice deficient for the Npas2 gene but was lost in mice lacking Bmal1 or both Per1 and Per2 genes. We conclude that daily rhythms in olfactory sensitivity depend on the expression of canonical clock genes. Olfaction is, thus, the first circadian behavior that is not based on locomotor activity and does not require the SCN.