Connectivity analysis with structural equation modelling: an example of the effects of voxel selection

Structural equation modelling (SEM) of neuroimaging data is commonly applied to a network of distributed brain regions. We applied SEM to an fMRI dataset to identify condition-specific effects in a simple experiment composed of visual stimulation and baseline conditions. The visual network was composed of three well-defined anatomical regions (V1, V2, and V5) and three path connections (V1 → V2, V1 → V5, and V2 → V5). This network was used to test four hypotheses: (1) whether the condition-specific effects for all three connections vary according to the data selected for modelling; (2) whether the “summary” measures that are often used are indeed appropriate; (3) whether measures taken from the voxel timecourse can reliably predict the condition-specific effects for each one of the three path connections, and (4) whether all voxels within an anatomical region yield equivalent SEM outcomes. There was some variability in the significance of the condition-specific effects across randomly selected voxels within regions. However, the SEM outcome from the “summary” measures was comparable to the most frequent pattern of condition-specific effects. Magnitude, delay, spread, and goodness-of-fit measures taken from a gamma fit to the voxel time courses predicted reliably the significance of the SEM condition-specific effects for each connection. This result enabled us to identify spatially coherent regions at the boundaries of V2 that displayed different condition-specific effects from those seen in the majority of the voxels. Although the generality of these results awaits further investigation, this example highlights a number of important issues for SEM

Auditory neuroscience: the salience of looming sounds

Sounds that move towards us have a greater biological salience than those that move away. Recent studies in human and non-human primates demonstrate a perceptual and behavioural priority for such looming sounds that is also reflected in an asymmetric pattern of cortical activation

Relationships between human auditory cortical structure and function

The human auditory cortex comprises multiple areas, largely distributed across the supratemporal plane, but the precise number and configuration of auditory areas and their functional significance have not yet been clearly established. In this paper, we discuss recent research concerning architectonic and functional organisation within the human auditory cortex, as well as architectonic and neurophysiological studies in non-human species, which can provide a broad conceptual framework for interpreting functional specialisation in humans. We review the pattern in human auditory cortex of the functional responses to various acoustic cues, such as frequency, pitch, sound level, temporal variation, motion and spatial location, and we discuss their correspondence to what is known about the organisation of the auditory cortex in other primates. There is some neuroimaging evidence of multiple tonotopically organised fields in humans and of functional specialisations of the fields in the processing of different sound features. It is thought that the primary area, on Heschl's gyrus, may have a larger involvement in processing basic sound features, such as frequency and level, and that posterior non-primary areas on the planum temporale may play a larger role in processing more spectrotemporally complex sounds. Ways in which current knowledge of auditory cortical organisation and different data analysis approaches may benefit future functional neuroimaging studies which seek to link auditory cortical structure and function are discussed

The mechanisms of tinnitus: perspectives from human functional neuroimaging

In this review, we highlight the contribution of advances in human neuroimaging to the current understanding of central mechanisms underpinning tinnitus and explain how interpretations of neuroimaging data have been guided by animal models. The primary motivation for studying the neural substrates of tinnitus in humans has been to demonstrate objectively its representation in the central auditory system and to develop a better understanding of its diverse pathophysiology and of the functional interplay between sensory, cognitive and affective systems. The ultimate goal of neuroimaging is to identify subtypes of tinnitus in order to better inform treatment strategies. The three neural mechanisms considered in this review may provide a basis for TI classification. While human neuroimaging evidence strongly implicates the central auditory system and emotional centres in TI, evidence for the precise contribution from the three mechanisms is unclear because the data are somewhat inconsistent. We consider a number of methodological issues limiting the field of human neuroimaging and recommend approaches to overcome potential inconsistency in results arising from poorly matched participants, lack of appropriate controls and low statistical power

Amplitude and frequency-modulated stimuli activate common regions of human auditory cortex

Hall et al. (Hall et al., 2002, Cerebral Cortex 12:140–149) recently showed that pulsed frequency-modulated tones generate considerably higher activation than their unmodulated counterparts in non-primary auditory regions immediately posterior and lateral to Heschl’s gyrus (HG). Here, we use fMRI to explore the type of modulation necessary to evoke such differential activation. Carrier signals were a single tone and a harmonic-complex tone, with a 300 Hz fundamental, that were modulated at a rate of 5 Hz either in frequency, or in amplitude, to create six stimulus conditions (unmodulated, FM, AM). Relative to the silent baseline, the modulated tones, in particular, activated widespread regions of the auditory cortex bilaterally along the supra-temporal plane. When compared with the unmodulated tones, both AM and FM tones generated significantly greater activation in lateral HG and the planum temporale, replicating the previous findings. These activation patterns were largely overlapping, indicating a common sensitivity to both AM and FM. Direct comparisons between AM and FM revealed a higher magnitude of activation in response to the variation in amplitude than in frequency, plus a small part of the posterolateral region in the right hemisphere whose response was specifically AM-, and not FM-, dependent. The dominant pattern of activation was that of co-localized activation by AM and FM, which is consistent with a common neural code for AM and FM within these brain regions

Periodicity and frequency coding in human auditory cortex

Understanding the neural coding of pitch and frequency is fundamental to the understanding of speech comprehension, music perception and the segregation of concurrent sound sources. Neuroimaging has made important contributions to defining the pattern of frequency sensitivity in humans. However, the precise way in which pitch sensitivity relates to these frequency-dependent regions remains unclear. Single-frequency tones also cannot be used to test this hypothesis as their pitch always equals their frequency. Here, temporal pitch (periodicity) and frequency coding were dissociated using stimuli that were bandpassed in different frequency spectra (centre frequencies 800 and 4500 Hz), yet were matched in their pitch characteristics. Cortical responses to both pitch-evoking stimuli typically occurred within a region that was also responsive to low frequencies. Its location extended across both primary and nonprimary auditory cortex. An additional control experiment demonstrated that this pitch-related effect was not simply caused by the generation of combination tones. Our findings support recent neurophysiological evidence for a cortical representation of pitch at the lateral border of the primary auditory cortex, while revealing new evidence that additional auditory fields are also likely to play a role in pitch coding

Can meaningful effective connectivities be obtained between auditory cortical regions?

Structural equation modelling (SEM) of neuroimaging data can be evaluated both for the goodness of fit of the model and for the strength of path coefficients (as an index of effective connectivity). SEM of auditory fMRI data is made difficult by the necessary sparse temporal sampling of the time series (to avoid contamination of auditory activation by the response to scanner noise), and by the paucity of well-defined anatomical information to constrain the functional model. We used SEM (i.e. a model incorporating latent variables) to investigate how well fMRI data in four adjacent cortical fields can be described as an auditory network. Seven out of 14 models (2 hemispheres x (6 subjects and 1 group)) produced a plausible description of the measured data. Since the auditory model to be tested is not fully validated by anatomical data, our approach requires that goodness of fit must be confirmed to assure generalisability of connectivity patterns. For good-fitting models, connectivity patterns varied significantly across subjects and were not replicable across stimulus conditions. SEM of central auditory function therefore appears to be highly sensitive to the voxel-selection procedure and/or the sampling of the time series

Speech perception in MRI scanner noise by persons with aphasia

Purpose. To examine reductions in performance on auditory tasks by aphasic and neurologically-intact individuals as a result of concomitant MRI scanner noise. Methods. Four tasks together forming a continuum of linguistic complexity were developed. They included complex-tone pitch discrimination, same/different discrimination of minimal pair syllables, lexical decision, and sentence plausibility. Each task was performed by persons with aphasia (PWA) and by controls. The stimuli were presented in silence and also in the noise recorded from within the bore of a 3T MRI scanner at three signal-to-noise ratios (S/Ns). Results. Across the four tasks, the PWA scored lower than the controls and performance fell as a function of decreased S/N. However, the rate at which performance fell was not different across the two listener groups in any task. Conclusions. Depending upon the relative levels of the signals and noise, the intense noise accompanying MRI scanning has the potential to severely disrupt performance. However, PWA are no more susceptible to the disruptive influence of this noise than are unimpaired individuals usually employed as controls. Thus, fMRI data from aphasic and control individuals may be interpreted without complications associated with large interactions between scanner noise and performance reduction

Critical basis dependence in bounding R-parity breaking couplings from neutral meson mixing

Assuming one nonzero product of two $\lambda'$-type couplings and working in two different bases for the left-handed quark superfields, the neutral meson mixings are used to bound these products. We emphasize the strong basis dependence of the bounds: in one basis many products contribute to neutral meson mixings at tree level, while in the other these products except one contribute at 1-loop level only and the GIM mechanism takes place. Correspondingly, these bounds differ between bases by orders of magnitudes.Comment: 10 pages, two references and some discussion adde