Abstract
Functional magnetic resonance imaging (fMRI) has become an indispensable tool for investigating the human brain. However, the inherently poor signal-to-noise-ratio (SNR) of the fMRI ...measurement represents a major barrier to expanding its spatiotemporal scale as well as its utility and ultimate impact. Here we introduce a denoising technique that selectively suppresses the thermal noise contribution to the fMRI experiment. Using 7-Tesla, high-resolution human brain data, we demonstrate improvements in key metrics of functional mapping (temporal-SNR, the detection and reproducibility of stimulus-induced signal changes, and accuracy of functional maps) while leaving the amplitude of the stimulus-induced signal changes, spatial precision, and functional point-spread-function unaltered. We demonstrate that the method enables the acquisition of ultrahigh resolution (0.5 mm isotropic) functional maps but is also equally beneficial for a large variety of fMRI applications, including supra-millimeter resolution 3- and 7-Tesla data obtained over different cortical regions with different stimulation/task paradigms and acquisition strategies.
Neuronal cortical circuitry comprises feedforward, lateral, and feedback projections, each of which terminates in distinct cortical layers 1–3. In sensory systems, feedforward processing transmits ...signals from the external world into the cortex, whereas feedback pathways signal the brain’s inference of the world 4–11. However, the integration of feedforward, lateral, and feedback inputs within each cortical area impedes the investigation of feedback, and to date, no technique has isolated the feedback of visual scene information in distinct layers of healthy human cortex. We masked feedforward input to a region of V1 cortex and studied the remaining internal processing. Using high-resolution functional brain imaging (0.8 mm3) and multivoxel pattern information techniques, we demonstrate that during normal visual stimulation scene information peaks in mid-layers. Conversely, we found that contextual feedback information peaks in outer, superficial layers. Further, we found that shifting the position of the visual scene surrounding the mask parametrically modulates feedback in superficial layers of V1. Our results reveal the layered cortical organization of external versus internal visual processing streams during perception in healthy human subjects. We provide empirical support for theoretical feedback models such as predictive coding 10, 12 and coherent infomax 13 and reveal the potential of high-resolution fMRI to access internal processing in sub-millimeter human cortex.
Display omitted
•High-resolution MRI shows functional information patterns in non-stimulated V1•Non-stimulated V1 receives cortical feedback information to superficial layers•Feedback to non-stimulated V1 superficial layers is predictive of visual context
Muckli et al. have discovered that the superficial layers of visual cortex V1 receive information when not directly stimulated. This information contains contextual feedback from higher visual areas. The data provide empirical evidence for layer-specific cortical feedback relevant for the neurobiology of predictive coding.
•We review the study of the human auditory system with ultra-high field (UHF) (f)MRI.•UHF fMRI can detail processing in the small subcortical auditory regions.•Primary auditory cortex may be ...localized through use of the versatile MRI contrasts.•Laminar UHF fMRI may reveal how a categorical sound representation emerges.•UHF (f)MRI is well suited to study the sound representation in the auditory pathway.
Following rapid methodological advances, ultra-high field (UHF) functional and anatomical magnetic resonance imaging (MRI) has been repeatedly and successfully used for the investigation of the human auditory system in recent years. Here, we review this work and argue that UHF MRI is uniquely suited to shed light on how sounds are represented throughout the network of auditory brain regions. That is, the provided gain in spatial resolution at UHF can be used to study the functional role of the small subcortical auditory processing stages and details of cortical processing. Further, by combining high spatial resolution with the versatility of MRI contrasts, UHF MRI has the potential to localize the primary auditory cortex in individual hemispheres. This is a prerequisite to study how sound representation in higher-level auditory cortex evolves from that in early (primary) auditory cortex. Finally, the access to independent signals across auditory cortical depths, as afforded by UHF, may reveal the computations that underlie the emergence of an abstract, categorical sound representation based on low-level acoustic feature processing. Efforts on these research topics are underway. Here we discuss promises as well as challenges that come with studying these research questions using UHF MRI, and provide a future outlook.
The development of ultra high field fMRI signal readout strategies and contrasts has led to the possibility of imaging the human brain in vivo and non-invasively at increasingly higher spatial ...resolutions of cortical layers and columns. One emergent layer-fMRI acquisition method with increasing popularity is the cerebral blood volume sensitive sequence named vascular space occupancy (VASO). This approach has been shown to be mostly sensitive to locally-specific changes of laminar microvasculature, without unwanted biases of trans-laminar draining veins. Until now, however, VASO has not been applied in the technically challenging cortical area of the auditory cortex. Here, we describe the main challenges we encountered when developing a VASO protocol for auditory neuroscientific applications and the solutions we have adopted. With the resulting protocol, we present preliminary results of laminar responses to sounds and as a proof of concept for future investigations, we map the topographic representation of frequency preference (tonotopy) in the auditory cortex.
The specific contents of human consciousness rely on the activity of specialized neurons in cerebral cortex. We hypothesized that the conscious experience of a specific visual motion axis is ...reflected in response amplitudes of direction-selective clusters in the human motion complex. Using submillimeter fMRI at ultrahigh field (7 T) we identified fine-grained clusters that were tuned to either horizontal or vertical motion presented in an unambiguous motion display. We then recorded their responses while human observers reported the perceived axis of motion for an ambiguous apparent motion display. Although retinal stimulation remained constant, subjects reported recurring changes between horizontal and vertical motion percepts every 7 to 13 s. We found that these perceptual states were dissociatively reflected in the response amplitudes of the identified horizontal and vertical clusters. We also found that responses to unambiguous motion were organized in a columnar fashion such that motion preferences were stable in the direction of cortical depth and changed when moving along the cortical surface. We suggest that activity in these specialized clusters is involved in tracking the distinct conscious experience of a particular motion axis.
Using ultra-high field fMRI, we explored the cortical depth-dependent stability of acoustic feature preference in human auditory cortex. We collected responses from human auditory cortex (subjects ...from either sex) to a large number of natural sounds at submillimeter spatial resolution, and observed that these responses were well explained by a model that assumes neuronal population tuning to frequency-specific spectrotemporal modulations. We observed a relatively stable (columnar) tuning to frequency and temporal modulations. However, spectral modulation tuning was variable throughout the cortical depth. This difference in columnar stability between feature maps could not be explained by a difference in map smoothness, as the preference along the cortical sheet varied in a similar manner for the different feature maps. Furthermore, tuning to all three features was more columnar in primary than nonprimary auditory cortex. The observed overall lack of overlapping columnar regions across acoustic feature maps suggests, especially for primary auditory cortex, a coding strategy in which across cortical depths tuning to some features is kept stable, whereas tuning to other features systematically varies.
In the human auditory cortex, sound aspects are processed in large-scale maps. Invasive animal studies show that an additional processing organization may be implemented orthogonal to the cortical sheet (i.e., in the columnar direction), but it is unknown whether observed organizational principles apply to the human auditory cortex. Combining ultra-high field fMRI with natural sounds, we explore the columnar organization of various sound aspects. Our results suggest that the human auditory cortex contains a modular coding strategy, where, for each module, several sound aspects act as an anchor along which computations are performed while the processing of another sound aspect undergoes a transformation. This strategy may serve to optimally represent the content of our complex acoustic natural environment.
Can we decipher speech content ("what" is being said) and speaker identity ("who" is saying it) from observations of brain activity of a listener? Here, we combine functional magnetic resonance ...imaging with a data-mining algorithm and retrieve what and whom a person is listening to from the neural fingerprints that speech and voice signals elicit in the listener's auditory cortex. These cortical fingerprints are spatially distributed and insensitive to acoustic variations of the input so as to permit the brain-based recognition of learned speech from unknown speakers and of learned voices from previously unheard utterances. Our findings unravel the detailed cortical layout and computational properties of the neural populations at the basis of human speech recognition and speaker identification.
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 feedforward 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.
The layers of the neocortex each have a unique anatomical connectivity and functional role. Their exploration in the human brain, however, has been severely restricted by the limited spatial ...resolution of non-invasive measurement techniques. Here, we exploit the sensitivity and specificity of ultra-high field fMRI at 7 Tesla to investigate responses to natural sounds at deep, middle, and superficial cortical depths of the human auditory cortex. Specifically, we compare the performance of computational models that represent different hypotheses on sound processing inside and outside the primary auditory cortex (PAC). We observe that while BOLD responses in deep and middle PAC layers are equally well represented by a simple frequency model and a more complex spectrotemporal modulation model, responses in superficial PAC are better represented by the more complex model. This indicates an increase in processing complexity in superficial PAC, which remains present throughout cortical depths in the non-primary auditory cortex. These results suggest that a relevant transformation in sound processing takes place between the thalamo-recipient middle PAC layers and superficial PAC. This transformation may be a first computational step towards sound abstraction and perception, serving to form an increasingly more complex representation of the physical input.
Multi-Voxel Pattern Analysis (MVPA) is a well established tool to disclose weak, distributed effects in brain activity patterns. The generalization ability is assessed by testing the learning model ...on new, unseen data. However, when limited data is available, the decoding success is estimated using cross-validation. There is general consensus on assessing statistical significance of cross-validated accuracy with non-parametric permutation tests. In this work we focus on the false positive control of different permutation strategies and on the statistical power of different cross-validation schemes.
With simulations, we show that estimating the entire cross-validation error on each permuted dataset is the only statistically valid permutation strategy. Furthermore, using both simulations and real data from the HCP WU-Minn 3T fMRI dataset, we show that, among the different cross-validation schemes, a repeated split-half cross-validation is the most powerful, despite achieving slightly lower classification accuracy, when compared to other schemes. Our findings provide additional insights into the optimization of the experimental design for MVPA, highlighting the benefits of having many short runs.
PDF
