Phonological Processing in Human Auditory Cortical Fields

We used population-based cortical-surface analysis of functional magnetic imaging data to characterize the processing of consonant–vowel–consonant syllables (CVCs) and spectrally matched amplitude-modulated noise bursts (AMNBs) in human auditory cortex as subjects attended to auditory or visual stimuli in an intermodal selective attention paradigm. Average auditory cortical field (ACF) locations were defined using tonotopic mapping in a previous study. Activations in auditory cortex were defined by two stimulus-preference gradients: (1) Medial belt ACFs preferred AMNBs and lateral belt and parabelt fields preferred CVCs. This preference extended into core ACFs with medial regions of primary auditory cortex (A1) and the rostral field preferring AMNBs and lateral regions preferring CVCs. (2) Anterior ACFs showed smaller activations but more clearly defined stimulus preferences than did posterior ACFs. Stimulus preference gradients were unaffected by auditory attention suggesting that ACF preferences reflect the automatic processing of different spectrotemporal sound features

Functional Properties of Human Auditory Cortical Fields

While auditory cortex in non-human primates has been subdivided into multiple functionally specialized auditory cortical fields (ACFs), the boundaries and functional specialization of human ACFs have not been defined. In the current study, we evaluated whether a widely accepted primate model of auditory cortex could explain regional tuning properties of fMRI activations on the cortical surface to attended and non-attended tones of different frequency, location, and intensity. The limits of auditory cortex were defined by voxels that showed significant activations to non-attended sounds. Three centrally located fields with mirror-symmetric tonotopic organization were identified and assigned to the three core fields of the primate model while surrounding activations were assigned to belt fields following procedures similar to those used in macaque fMRI studies. The functional properties of core, medial belt, and lateral belt field groups were then analyzed. Field groups were distinguished by tonotopic organization, frequency selectivity, intensity sensitivity, contralaterality, binaural enhancement, attentional modulation, and hemispheric asymmetry. In general, core fields showed greater sensitivity to sound properties than did belt fields, while belt fields showed greater attentional modulation than core fields. Significant distinctions in intensity sensitivity and contralaterality were seen between adjacent core fields A1 and R, while multiple differences in tuning properties were evident at boundaries between adjacent core and belt fields. The reliable differences in functional properties between fields and field groups suggest that the basic primate pattern of auditory cortex organization is preserved in humans. A comparison of the sizes of functionally defined ACFs in humans and macaques reveals a significant relative expansion in human lateral belt fields implicated in the processing of speech

Automated measurement of the human corpus callosum using MRI

The corpus callosum includes the majority of fibers that connect the two cortical hemispheres. Studies of cross-sectional callosal morphometry and area have revealed developmental, gender, and hemispheric differences in healthy populations and callosal deficits associated with neurodegenerative disease and brain injury. However, accurate quantification of the callosum using magnetic resonance imaging is complicated by intersubject variability in callosal size, shape, and location and often requires manual outlining of the callosum in order to achieve adequate performance. Here we describe an objective, fully automated protocol that utilizes voxel-based image to quantify the area and thickness both of the entire callosum and of different callosal compartments. We verify the method’s accuracy, reliability, robustness and multisite consistency and make comparisons with manual measurements using public brain-image databases. An analysis of age-related changes in the callosum showed increases in length and reductions in thickness and area with age. A comparison of older subjects with and without mild dementia revealed that reductions in anterior callosal area independently predicted poorer cognitive performance after factoring out Mini-Mental Status Examination scores and normalized whole brain volume. Open-source software implementing the algorithm is available at www.nitrc.org/projects/c8c8