No abstract

Ten healthy adults encountered pictures of unfamiliar archaic tools and successfully learned either their name, verbal definition of their usage, or both. Neural representation of the newly acquired information was probed with magnetoencephalography in an overt picture-naming task before and after learning, and in two categorization tasks after learning. Within 400 ms, activation proceeded from occipital through parietal to left temporal cortex, inferior frontal cortex (naming) and right temporal cortex (categorization). Comparison of naming of newly learned versus familiar pictures indicated that acquisition and maintenance of word forms are supported by the same neural network. Explicit access to newly learned phonology when such information was known strongly enhanced left temporal activation. By contrast, access to newly learned semantics had no comparable, direct neural effects. Both the behavioral learning pattern and neurophysiological results point to fundamentally different implementation of and access to phonological versus semantic features in processing pictured objects.

There is an increasing interest to integrate electrophysiological and hemodynamic measures for characterizing spatial and temporal aspects of cortical processing. However, an informative combination of responses that have markedly different sensitivities to the underlying neural activity is not straightforward, especially in complex cognitive tasks. Here, we used parametric stimulus manipulation in magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) recordings on the same subjects, to study effects of noise on processing of spoken words and environmental sounds. The added noise influenced MEG response strengths in the bilateral supratemporal auditory cortex, at different times for the different stimulus types. Specifically for spoken words, the effect of noise on the electrophysiological response was remarkably nonlinear. Therefore, we used the single-subject MEG responses to construct parametrization for fMRI data analysis and obtained notably higher sensitivity than with conventional stimulus-based parametrization. fMRI results showed that partly different temporal areas were involved in noise-sensitive processing of words and environmental sounds. These results indicate that cortical processing of sounds in background noise is stimulus specific in both timing and location and provide a new functionally meaningful platform for combining information obtained with electrophysiological and hemodynamic measures of brain function.

Neural processes are explored through macroscopic neuroimaging and microscopic molecular measures, but the two levels remain primarily detached. The identification of direct links between the levels would facilitate use of imaging signals as probes of genetic function and, vice versa, access to molecular correlates of imaging measures. Neuroimaging patterns have been mapped for a few isolated genes, chosen based on their connection with a clinical disorder. Here we propose an approach that allows an unrestricted discovery of the genetic basis of a neuroimaging phenotype in the normal human brain. The essential components are a subject population that is composed of relatives and selection of a neuroimaging phenotype that is reproducible within an individual and similar between relatives but markedly variable across a population. Our present combined magnetoencephalography and genome-wide linkage study in 212 healthy siblings demonstrates that auditory cortical activation strength is highly heritable and, specifically in the right hemisphere, regulated oligogenically with linkages to chromosomes 2q37, 3p12, and 8q24. The identified regions delimit as candidate genes TRAPPC9, operating in neuronal differentiation, and ROBO1, regulating projections of thalamocortical axons. Identification of normal genetic variation underlying neurophysiological phenotypes offers a non-invasive platform for an in-depth, concerted capitalization of molecular and neuroimaging levels in exploring neural function.

Several functional and morphological brain measures are partly under genetic control. The identification of direct links between neuroimaging signals and corresponding genetic factors can reveal cellular-level mechanisms behind the measured macroscopic signals and contribute to the use of imaging signals as probes of genetic function. To uncover possible genetic determinants of the most prominent brain signal oscillation, the parieto-occipital 10-Hz alpha rhythm, we measured spontaneous brain activity with magnetoencephalography in 210 healthy siblings while the subjects were resting, with eyes closed and open. The reactivity of the alpha rhythm was quantified from the difference spectra between the two conditions. We focused on three measures: peak frequency, peak amplitude and the width of the main spectral peak. In accordance with earlier electroencephalography studies, spectral peak amplitude was highly heritable (h 2 > 0.75). Variance component-based analysis of 28 000 single-nucleotide polymorphism markers revealed linkage for both the width and the amplitude of the spectral peak. The strongest linkage was detected for the width of the spectral peak over the left parieto-occipital cortex on chromosome 10 (LOD = 2.814, nominal P < 0.03). This genomic region contains several functionally plausible genes, including GRID1 and ATAD1 that regulate glutamate receptor channels mediating synaptic transmission, NRG3 with functions in brain development and HRT7 involved in the serotonergic system and circadian rhythm. Our data suggest that the alpha oscillation is in part genetically regulated, and that it may be possible to identify its regulators by genetic analyses on a realistically modest number of samples.