Michelle Moerel

Optimizing functional accuracy of tms in cognitive studies: A comparison of methods

Transcranial magnetic stimulation (TMS) is a tool for inducing transient disruptions of neural activity noninvasively in conscious human volunteers. In recent years, the investigative domain of TMS has expanded and now encompasses causal structure–function relationships across the whole gamut of cognitive functions and associated cortical brain regions. Consequently, the importance of how to determine the target stimulation site has increased and a number of alternative methods have emerged. Comparison across studies is precluded because different studies necessarily use different tasks, sites, TMS conditions, and have different goals. Here, therefore, we systematically compare four commonly used TMS coil positioning approaches by using them to induce behavioral change in a single cognitive study. Specifically, we investigated the behavioral impact of right parietal TMS during a number comparison task, while basing TMS localization either on (i) individual fMRI-guided TMS neuronavigation, (ii) individual MRI-guided TMS neuronavigation, (iii) group functional Talairach coordinates, or (iv) 10–20 EEG position P4. We quantified the exact behavioral effects induced by TMS using each approach, calculated the standardized experimental effect sizes, and conducted a statistical power analysis in order to calculate the optimal sample size required to reveal statistical significance. Our findings revealed a systematic difference between the four approaches, with the individual fMRI-guided TMS neuronavigation yielding the strongest and the P4 stimulation approach yielding the smallest behavioral effect size. Accordingly, power analyses revealed that although in the fMRI-guided neuronavigation approach five participants were sufficient to reveal a significant behavioral effect, the number of necessary participants increased to n = 9 when employing MRI-guided neuronavigation, to n = 13 in case of TMS based on group Talairach coordinates, and to n = 47 when applying TMS over P4. We discuss these graded effect size differences in light of the revealed interindividual variances in the actual target stimulation site within and between approaches.

Processing of Natural Sounds in Human Auditory Cortex: Tonotopy, Spectral Tuning, and Relation to Voice Sensitivity

Auditory cortical processing of complex meaningful sounds entails the transformation of sensory (tonotopic) representations of incoming acoustic waveforms into higher-level sound representations (e.g., their category). However, the precise neural mechanisms enabling such transformations remain largely unknown. In the present study, we use functional magnetic resonance imaging (fMRI) and natural sounds stimulation to examine these two levels of sound representation (and their relation) in the human auditory cortex. In a first experiment, we derive cortical maps of frequency preference (tonotopy) and selectivity (tuning width) by mathematical modeling of fMRI responses to natural sounds. The tuning width maps highlight a region of narrow tuning that follows the main axis of Heschls gyrus and is flanked by regions of broader tuning. The narrowly tuned portion on Heschls gyrus contains two mirror-symmetric frequency gradients, presumably defining two distinct primary auditory areas. In addition, our analysis indicates that spectral preference and selectivity (and their topographical organization) extend well beyond the primary regions and also cover higher-order and category-selective auditory regions. In particular, regions with preferential responses to human voice and speech occupy the low-frequency portions of the tonotopic map. We confirm this observation in a second experiment, where we find that speech/voice selective regions exhibit a response bias toward the low frequencies characteristic of human voice and speech, even when responding to simple tones. We propose that this frequency bias reflects the selective amplification of relevant and category-characteristic spectral bands, a useful processing step for transforming a sensory (tonotopic) sound image into higher level neural representations.

An anatomical and functional topography of human auditory cortical areas.

While advances in magnetic resonance imaging (MRI) throughout the last decades have enabled the detailed anatomical and functional inspection of the human brain non-invasively, to date there is no consensus regarding the precise subdivision and topography of the areas forming the human auditory cortex. Here, we propose a topography of the human auditory areas based on insights on the anatomical and functional properties of human auditory areas as revealed by studies of cyto- and myelo-architecture and fMRI investigations at ultra-high magnetic field (7 Tesla). Importantly, we illustrate that—whereas a group-based approach to analyze functional (tonotopic) maps is appropriate to highlight the main tonotopic axis—the examination of tonotopic maps at single subject level is required to detail the topography of primary and non-primary areas that may be more variable across subjects. Furthermore, we show that considering multiple maps indicative of anatomical (i.e., myelination) as well as of functional properties (e.g., broadness of frequency tuning) is helpful in identifying auditory cortical areas in individual human brains. We propose and discuss a topography of areas that is consistent with old and recent anatomical post-mortem characterizations of the human auditory cortex and that may serve as a working model for neuroscience studies of auditory functions.

Encoding of natural sounds at multiple spectral and temporal resolutions in the human auditory cortex.

Functional neuroimaging research provides detailed observations of the response patterns that natural sounds (e.g. human voices and speech, animal cries, environmental sounds) evoke in the human brain. The computational and representational mechanisms underlying these observations, however, remain largely unknown. Here we combine high spatial resolution (3 and 7 Tesla) functional magnetic resonance imaging (fMRI) with computational modeling to reveal how natural sounds are represented in the human brain. We compare competing models of sound representations and select the model that most accurately predicts fMRI response patterns to natural sounds. Our results show that the cortical encoding of natural sounds entails the formation of multiple representations of sound spectrograms with different degrees of spectral and temporal resolution. The cortex derives these multi-resolution representations through frequency-specific neural processing channels and through the combined analysis of the spectral and temporal modulations in the spectrogram. Furthermore, our findings suggest that a spectral-temporal resolution trade-off may govern the modulation tuning of neuronal populations throughout the auditory cortex. Specifically, our fMRI results suggest that neuronal populations in posterior/dorsal auditory regions preferably encode coarse spectral information with high temporal precision. Vice-versa, neuronal populations in anterior/ventral auditory regions preferably encode fine-grained spectral information with low temporal precision. We propose that such a multi-resolution analysis may be crucially relevant for flexible and behaviorally-relevant sound processing and may constitute one of the computational underpinnings of functional specialization in auditory cortex.

High-Resolution Mapping of Myeloarchitecture In Vivo: Localization of Auditory Areas in the Human Brain

The precise delineation of auditory areas in vivo remains problematic. Histological analysis of postmortem tissue indicates that the relation of areal borders to macroanatomical landmarks is variable across subjects. Furthermore, functional parcellation schemes based on measures of, for example, frequency preference (tonotopy) remain controversial. Here, we propose a 7 Tesla magnetic resonance imaging method that enables the anatomical delineation of auditory cortical areas in vivo and in individual brains, through the high-resolution visualization (0.6 × 0.6 × 0.6 mm(3)) of intracortical anatomical contrast related to myelin. The approach combines the acquisition and analysis of images with multiple MR contrasts (T1, T2*, and proton density). Compared with previous methods, the proposed solution is feasible at high fields and time efficient, which allows collecting myelin-related and functional images within the same measurement session. Our results show that a data-driven analysis of cortical depth-dependent profiles of anatomical contrast allows identifying a most densely myelinated cortical region on the medial Heschls gyrus. Analyses of functional responses show that this region includes neuronal populations with typical primary functional properties (single tonotopic gradient and narrow frequency tuning), thus indicating that it may correspond to the human homolog of monkey A1.

Spatial organization of frequency preference and selectivity in the human inferior colliculus

To date, the functional organization of human auditory sub-cortical structures can only be inferred from animal models. Here we use high-resolution functional MRI at ultra-high magnetic fields (7 Tesla) to map the organization of spectral responses in the human inferior colliculus (hIC), a sub-cortical structure fundamental for sound processing. We reveal a tonotopic map with a spatial gradient of preferred frequencies approximately oriented from dorso-lateral (low frequencies) to ventro-medial (high frequencies) locations. Furthermore, we observe a spatial organization of spectral selectivity (tuning) of fMRI responses in the hIC. Along isofrequency contours, fMRI-tuning is narrowest in central locations and broadest in the surrounding regions. Finally, by comparing sub-cortical and cortical auditory areas we show that fMRI-tuning is narrower in hIC than on the cortical surface. Our findings pave the way to non-invasive investigations of sound processing in human sub-cortical nuclei and to studying the interplay between sub-cortical and cortical neuronal populations.

Frequency preference and attention effects across cortical depths in the human primary auditory cortex.

Significance To the best of our knowledge, our data provide the first imaging evidence compatible with columnar processing of sound frequency in the human auditory cortex. Our study depicts the human auditory cortex with unprecedented spatial detail and demonstrates the feasibility of acquiring submillimeter functional images outside visual/motor cortices, setting the stage for a wide range of research possibilities. Our results elucidate the role of cortical layers in bottom-up and top-down processing of sounds, and suggest that ongoing behavioral goals shape population-based sound representations especially in superficial layers of A1 columns. These results may inform and improve computational models of auditory cortical processing and may be relevant for understanding neurological conditions that do not yet have an imaging “biomarker” (e.g., tinnitus). Columnar arrangements of neurons with similar preference have been suggested as the fundamental processing units of the cerebral cortex. Within these columnar arrangements, feed-forward information enters at middle cortical layers whereas feedback information arrives at superficial and deep layers. This interplay of feed-forward and feedback processing is at the core of perception and behavior. Here we provide in vivo evidence consistent with a columnar organization of the processing of sound frequency in the human auditory cortex. We measure submillimeter functional responses to sound frequency sweeps at high magnetic fields (7 tesla) and show that frequency preference is stable through cortical depth in primary auditory cortex. Furthermore, we demonstrate that—in this highly columnar cortex—task demands sharpen the frequency tuning in superficial cortical layers more than in middle or deep layers. These findings are pivotal to understanding mechanisms of neural information processing and flow during the active perception of sounds.

Processing of Natural Sounds: Characterization of Multipeak Spectral Tuning in Human Auditory Cortex

We examine the mechanisms by which the human auditory cortex processes the frequency content of natural sounds. Through mathematical modeling of ultra-high field (7 T) functional magnetic resonance imaging responses to natural sounds, we derive frequency-tuning curves of cortical neuronal populations. With a data-driven analysis, we divide the auditory cortex into five spatially distributed clusters, each characterized by a spectral tuning profile. Beyond neuronal populations with simple single-peaked spectral tuning (grouped into two clusters), we observe that ∼60% of auditory populations are sensitive to multiple frequency bands. Specifically, we observe sensitivity to multiple frequency bands (1) at exactly one octave distance from each other, (2) at multiple harmonically related frequency intervals, and (3) with no apparent relationship to each other. We propose that beyond the well known cortical tonotopic organization, multipeaked spectral tuning amplifies selected combinations of frequency bands. Such selective amplification might serve to detect behaviorally relevant and complex sound features, aid in segregating auditory scenes, and explain prominent perceptual phenomena such as octave invariance.

Spin echo functional MRI in bilateral auditory cortices at 7T: An application of B(1) shimming

Ultra high fields (UHF) permit unprecedented explorations of functional organizations and insight into basic neuronal processes. Increases in the signal and contrast to noise ratios have allowed increases in the spatial resolution of T(2) weighted gradient echo (GE) echo planar imaging (EPI). Furthermore, while the use of T(2) weighted imaging methods at UHF (e.g. spin echo (SE) EPI, gradient and spin echo (GRASE) EPI) can also permit higher resolution images, they in addition allow for increased spatial specificity of functional responses, permitting the in-vivo study of functional organizations down to the columnar level of the cortex. The study of the visual cortex has, thus far, benefitted the most from higher resolution T(2) weighted studies as achieving the required transmit B(1) magnitude at 7T is more challenging in other brain regions, such as the auditory cortex. As such, auditory fMRI studies at UHF have been limited to T(2) weighted GE sequences. Recent advances in multi-channel RF transmission (e.g. B(1) shimming) have enabled procedures to efficiently address deficiencies in transmit B(1) profiles. However, these techniques, shown to be advantageous in anatomical imaging at UHF, are not generally utilized to facilitate T(2) weighted fMRI studies. Here we investigate the feasibility of applying B(1) shimming to achieve efficient RF transmission in the human auditory cortex. We demonstrate that, with B(1) shimming, functional responses to simple tones and to complex sounds (i.e. voices, speech, animal cries, tools and nature) can be efficiently measured with T(2) weighted SE-EPI in the bilateral human auditory cortex at 7T without exceeding specific absorption rate (SAR) limits.

Processing of frequency and location in human subcortical auditory structures.

To date it remains largely unknown how fundamental aspects of natural sounds, such as their spectral content and location in space, are processed in human subcortical structures. Here we exploited the high sensitivity and specificity of high field fMRI (7 Tesla) to examine the human inferior colliculus (IC) and medial geniculate body (MGB). Subcortical responses to natural sounds were well explained by an encoding model of sound processing that represented frequency and location jointly. Frequency tuning was organized in one tonotopic gradient in the IC, whereas two tonotopic maps characterized the MGB reflecting two MGB subdivisions. In contrast, no topographic pattern of preferred location was detected, beyond an overall preference for peripheral (as opposed to central) and contralateral locations. Our findings suggest the functional organization of frequency and location processing in human subcortical auditory structures, and pave the way for studying the subcortical to cortical interaction required to create coherent auditory percepts.