Role of articulatory motor networks in perceptual categorization of speech signals: a 7T fMRI study.

Speech and language processing involve complex interactions between cortical areas necessary for articulatory movements and auditory perception and a range of areas through which these are connected and interact. Despite their fundamental importance, the precise mechanisms underlying these processes are not fully elucidated. We measured BOLD signals from normal hearing participants using high-field 7 Tesla fMRI with 1-mm isotropic voxel resolution. The subjects performed 2 speech perception tasks (discrimination and classification) and a speech production task during the scan. By employing univariate and multivariate pattern analyses, we identified the neural signatures associated with speech production and perception. The left precentral, premotor, and inferior frontal cortex regions showed significant activations that correlated with phoneme category variability during perceptual discrimination tasks. In addition, the perceived sound categories could be decoded from signals in a region of interest defined based on activation related to production task. The results support the hypothesis that articulatory motor networks in the left hemisphere, typically associated with speech production, may also play a critical role in the perceptual categorization of syllables. The study provides valuable insights into the intricate neural mechanisms that underlie speech processing.

Improving robustness of 3D multi-shot EPI by structured low-rank reconstruction of segmented CAIPI sampling for fMRI at 7T.

Three-dimensional (3D) encoding methods are increasingly being explored as alternatives to two-dimensional (2D) multi-slice acquisitions in fMRI, particularly in cases where high isotropic resolution is needed. 3D multi-shot EPI acquisition, as the workhorse of 3D fMRI imaging, is susceptible to physiological fluctuations which can induce inter-shot phase variations, and thus reducing the achievable tSNR, negating some of the benefit of 3D encoding. This issue can be particularly problematic at ultra-high fields like 7T, which have more severe off-resonance effects. In this work, we aim to improve the temporal stability of 3D multi-shot EPI at 7T by improving its robustness to inter-shot phase variations. We presented a 3D segmented CAIPI sampling trajectory ("seg-CAIPI") and an improved reconstruction method based on Hankel structured low-rank matrix recovery. Simulation and in-vivo results demonstrate that the combination of the seg-CAIPI sampling scheme and the proposed structured low-rank reconstruction is a promising way to effectively reduce the unwanted temporal variance induced by inter-shot physiological fluctuations, and thus improve the robustness of 3D multi-shot EPI for fMRI.

Mechanisms of speed encoding in the human middle temporal cortex measured by 7T fMRI.

Perception of dynamic scenes in our environment results from the evaluation of visual features such as the fundamental spatial and temporal frequency components of a moving object. The ratio between these two components represents the object's speed of motion. The human middle temporal cortex hMT+ has a crucial biological role in the direct encoding of object speed. However, the link between hMT+ speed encoding and the spatiotemporal frequency components of a moving object is still under explored. Here, we recorded high resolution 7T blood oxygen level-dependent BOLD responses to different visual motion stimuli as a function of their fundamental spatial and temporal frequency components. We fitted each hMT+ BOLD response with a 2D Gaussian model allowing for two different speed encoding mechanisms: (1) distinct and independent selectivity for the spatial and temporal frequencies of the visual motion stimuli; (2) pure tuning for the speed of motion. We show that both mechanisms occur but in different neuronal groups within hMT+, with the largest subregion of the complex showing separable tuning for the spatial and temporal frequency of the visual stimuli. Both mechanisms were highly reproducible within participants, reconciling single cell recordings from MT in animals that have showed both encoding mechanisms. Our findings confirm that a more complex process is involved in the perception of speed than initially thought and suggest that hMT+ plays a primary role in the evaluation of the spatial features of the moving visual input.

Two-Dimensional Population Receptive Field Mapping of Human Primary Somatosensory Cortex.

Functional magnetic resonance imaging can provide detailed maps of how sensory space is mapped in the human brain. Here, we use a novel 16 stimulator setup (a 4 × 4 grid) to measure two-dimensional sensory maps of between and within-digit (D2-D4) space using high spatial-resolution (1.25 mm isotropic) imaging at 7 Tesla together with population receptive field (pRF) mapping in 10 participants. Using a 2D Gaussian pRF model, we capture maps of the coverage of digits D2-D5 across Brodmann areas and estimate pRF size and shape. In addition, we compare results to previous studies that used fewer stimulators by constraining pRF models to a 1D Gaussian Between Digit or 1D Gaussian Within Digit model. We show that pRFs across somatosensory areas tend to have a strong preference to cover the within-digit axis. We show an increase in pRF size moving from D2-D5. We quantify pRF shapes in Brodmann area (BA) 3b, 3a, 1, 2 and show differences in pRF size in Brodmann areas 3a-2, with larger estimates for BA2. Generally, the 2D Gaussian pRF model better represents pRF coverage maps generated by our data, which itself is produced from a 2D stimulation grid.

A Gradient of Sharpening Effects by Perceptual Prior across the Human Cortical Hierarchy.

Prior knowledge profoundly influences perceptual processing. Previous studies have revealed consistent suppression of predicted stimulus information in sensory areas, but how prior knowledge modulates processing higher up in the cortical hierarchy remains poorly understood. In addition, the mechanism leading to suppression of predicted sensory information remains unclear, and studies thus far have revealed a mixed pattern of results in support of either the "sharpening" or "dampening" model. Here, using 7T fMRI in humans (both sexes), we observed that prior knowledge acquired from fast, one-shot perceptual learning sharpens neural representation throughout the ventral visual stream, generating suppressed sensory responses. In contrast, the frontoparietal and default mode networks exhibit similar sharpening of content-specific neural representation, but in the context of unchanged and enhanced activity magnitudes, respectively: a pattern we refer to as "selective enhancement." Together, these results reveal a heretofore unknown macroscopic gradient of prior knowledge's sharpening effect on neural representations across the cortical hierarchy.SIGNIFICANCE STATEMENT A fundamental question in neuroscience is how prior knowledge shapes perceptual processing. Perception is constantly informed by internal priors in the brain acquired from past experiences, but the neural mechanisms underlying this process are poorly understood. To date, research on this question has focused on early visual regions, reporting a consistent downregulation when predicted stimuli are encountered. Here, using a dramatic one-shot perceptual learning paradigm, we observed that prior knowledge results in sharper neural representations across the cortical hierarchy of the human brain through a gradient of mechanisms. In visual regions, neural responses tuned away from internal predictions are suppressed. In frontoparietal regions, neural activity consistent with priors is selectively enhanced. These results deepen our understanding of how prior knowledge informs perception.

Neural and computational processes of accelerated perceptual awareness and decisions: A 7T fMRI study.

Rapidly detecting salient information in our environments is critical for survival. Visual processing in subcortical areas like the pulvinar and amygdala has been shown to facilitate unconscious processing of salient stimuli. It is unknown, however, if and how these areas might interact with cortical regions to facilitate faster conscious perception of salient stimuli. Here we investigated these neural processes using 7T functional magnetic resonance imaging (fMRI) in concert with computational modelling while participants (n = 33) engaged in a breaking continuous flash suppression paradigm (bCFS) in which fearful and neutral faces are initially suppressed from conscious perception but then eventually 'breakthrough' into awareness. Participants reported faster breakthrough times for fearful faces compared with neutral faces. Drift-diffusion modelling suggested that perceptual evidence was accumulated at a faster rate for fearful faces compared with neutral faces. For both neutral and fearful faces, faster response times were associated with greater activity in the amygdala (specifically within its subregions, including superficial, basolateral and amygdalo-striatal transition area) and the insula. Faster rates of evidence accumulation coincided with greater activity in frontoparietal regions and occipital lobe, as well as the amygdala. A lower decision-boundary correlated with activity in the insula and the posterior cingulate cortex (PCC), but not with the amygdala. Overall, our findings suggest that hastened perceptual awareness of salient stimuli recruits the amygdala and, more specifically, is driven by accelerated evidence accumulation in fronto-parietal and visual areas. In sum, we have mapped distinct neural computations that accelerate perceptual awareness of visually suppressed faces.

Functional magnetic resonance imaging responses during perceptual decision-making at 3 and 7 T in human cortex, striatum, and brainstem.

While functional magnetic resonance imaging (fMRI) at ultra-high field (7 T) promises a general increase in sensitivity compared to lower field strengths, the benefits may be most pronounced for specific applications. The current study aimed to evaluate the relative benefit of 7 over 3 T fMRI for the assessment of responses evoked in different brain regions by a well-controlled cognitive task. At 3 and 7 T, the same participants made challenging perceptual decisions about visual motion combined with monetary rewards for correct choices. Previous work on this task has extensively characterized the underlying cognitive computations and single-cell responses in cortical and subcortical structures. We quantified the evoked fMRI responses in extrastriate visual cortical areas, the striatum, and the brainstem during the decision interval and the post-feedback interval of the task. The dependence of response amplitudes on field strength during the decision interval differed between cortical, striatal, and brainstem regions, with a generally bigger 7 versus 3 T benefit in subcortical structures. We also found stronger responses during relatively easier than harder decisions at 7 T for dopaminergic midbrain nuclei, in line with reward expectation. Our results demonstrate the potential of 7 T fMRI for illuminating the contribution of small brainstem nuclei to the orchestration of cognitive computations in the human brain.

Distinct Representational Structure and Localization for Visual Encoding and Recall during Visual Imagery.

During memory recall and visual imagery, reinstatement is thought to occur as an echoing of the neural patterns during encoding. However, the precise information in these recall traces is relatively unknown, with previous work primarily investigating either broad distinctions or specific images, rarely bridging these levels of information. Using ultra-high-field (7T) functional magnetic resonance imaging with an item-based visual recall task, we conducted an in-depth comparison of encoding and recall along a spectrum of granularity, from coarse (scenes, objects) to mid (e.g., natural, manmade scenes) to fine (e.g., living room, cupcake) levels. In the scanner, participants viewed a trial-unique item, and after a distractor task, visually imagined the initial item. During encoding, we observed decodable information at all levels of granularity in category-selective visual cortex. In contrast, information during recall was primarily at the coarse level with fine-level information in some areas; there was no evidence of mid-level information. A closer look revealed segregation between voxels showing the strongest effects during encoding and those during recall, and peaks of encoding-recall similarity extended anterior to category-selective cortex. Collectively, these results suggest visual recall is not merely a reactivation of encoding patterns, displaying a different representational structure and localization from encoding, despite some overlap.

Visual adaptation and 7T fMRI reveal facial identity processing in the human brain under shallow interocular suppression.

Face identity is represented at a high level of the visual hierarchy. Whether the human brain can process facial identity information in the absence of visual awareness remains unclear. In this study, we investigated potential face identity representation through face-identity adaptation with the adapting faces interocularly suppressed by Continuous Flash Suppression (CFS) noise, a modified binocular rivalry paradigm. The strength of interocular suppression was manipulated by varying the contrast of CFS noise. While obeservers reported the face images subjectively unperceived and the face identity objectively unrecognizable, a significant face identity aftereffect was observed under low but not high contrast CFS noise. In addition, the identity of face images under shallow interocular suppression can be decoded from multi-voxel patterns in the right fusiform face area (FFA) obtained with high-resolution 7T fMRI. Thus the comined evidence from visual adaptation and 7T fMRI suggest that face identity can be represented in the human brain without explicit perceptual recognition. The processing of interocularly suppressed faces could occur at different levels depending on how "deep" the information is suppressed.

Adaptation to visual numerosity changes neural numerosity selectivity.

Perceiving numerosity, i.e. the set size of a group of items, is an evolutionarily preserved ability found in humans and animals. A useful method to infer the neural underpinnings of a given perceptual property is sensory adaptation. Like other primary perceptual attributes, numerosity is susceptible to adaptation. Recently, we have shown numerosity-selective neural populations with a topographic organization in the human brain. Here, we investigated whether numerosity adaptation can affect the numerosity selectivity of these populations using ultra-high field (7 Tesla) functional magnetic resonance imaging (fMRI). Participants viewed stimuli of changing numerosity (1 to 7 dots), which allowed the mapping of numerosity selectivity. We interleaved a low or high numerosity adapter stimulus with these mapping stimuli, repeatedly presenting 1 or 20 dots respectively to adapt the numerosity-selective neural populations. We analyzed the responses using custom-build population receptive field neural models of numerosity encoding and compared estimated numerosity preferences between adaptation conditions. We replicated our previous studies where we found several topographic maps of numerosity-selective responses. We found that overall, numerosity adaptation altered the preferred numerosities within the numerosity maps, resulting in predominantly attractive biases towards the numerosity of the adapter. The differential biases could be explained by the difference between the unadapted preferred numerosity and the numerosity of the adapter, with attractive biases being observed with higher difference. The results could link perceptual numerosity adaptation effects to changes in neural numerosity selectivity.

Neural mediators of subjective and autonomic responding during threat learning and regulation.

Threat learning elicits robust changes across multiple affective domains, including changes in autonomic indices and subjective reports of fear and anxiety. It has been argued that the underlying causes of such changes may be dissociable at a neural level, but there is currently limited evidence to support this notion. To address this, we examined the neural mediators of trial-by-trial skin conductance responses (SCR), and subjective reports of anxious arousal and valence in participants (n = 27; 17 females) performing a threat reversal task during ultra-high field functional magnetic resonance imaging. This allowed us to identify brain mediators during initial threat learning and subsequent threat reversal. Significant neural mediators of anxious arousal during threat learning included the dorsal anterior cingulate, anterior insula cortex (AIC), and ventromedial prefrontal cortex (vmPFC), subcortical regions including the amygdala, ventral striatum, caudate and putamen, and brain-stem regions including the pons and midbrain. By comparison, autonomic changes (SCR) were mediated by a subset of regions embedded within this broader circuitry that included the caudate, putamen and thalamus, and two distinct clusters within the vmPFC. The neural mediators of subjective negative valence showed prominent effects in posterior cortical regions and, with the exception of the AIC, did not overlap with threat learning task effects. During threat reversal, positive mediators of both subjective anxious arousal and valence mapped to the default mode network; this included the vmPFC, posterior cingulate, temporoparietal junction, and angular gyrus. Decreased SCR during threat reversal was positively mediated by regions including the mid cingulate, AIC, two sub-regions of vmPFC, the thalamus, and the hippocampus. Our findings add novel evidence to support distinct underlying neural processes facilitating autonomic and subjective responding during threat learning and threat reversal. The results suggest that the brain systems engaged in threat learning mostly capture the subjective (anxious arousal) nature of the learning process, and that appropriate responding during threat reversal is facilitated by participants engaging self- and valence-based processes. Autonomic changes (SCR) appear to involve distinct facilitatory and regulatory contributions of vmPFC sub-regions.

Relation between palm and finger cortical representations in primary somatosensory cortex: A 7T fMRI study.

Many studies focused on the cortical representations of fingers, while the palm is relatively neglected despite its importance for hand function. Here, we investigated palm representation (PR) and its relationship with finger representations (FRs) in primary somatosensory cortex (S1). Few studies in humans suggested that PR is located medially with respect to FRs in S1, yet to date, no study directly quantified the somatotopic organization of PR and the five FRs. Importantly, the link between the somatotopic organization of PR and FRs and their activation properties remains largely unexplored. Using 7T fMRI, we mapped PR and the five FRs at the single subject level. First, we analyzed the cortical distance between PR and FRs to determine their somatotopic organization. Results show that PR was located medially with respect to D5. Second, we tested whether the observed cortical distances would predict the relationship between PR and FRs activations. Using three complementary measures (cross-activations, pattern similarity and resting-state connectivity), we show that the relationship between PR and FRs activations were not determined by their somatotopic organization, that is, there was no gradient moving from D5 to D1, except for resting-state connectivity, which was predicted by the somatotopy. Instead, we show that the representational geometry of PR and FRs activations reflected the physical structure of the hand. Collectively, our findings suggest that the spatial proximity between topographically organized neuronal populations do not necessarily predicts their functional properties, rather the structure of the sensory space (e.g., the hand shape) better describes the observed results.

Holistic Recollection via Pattern Completion Involves Hippocampal Subfield CA3.

Episodic memories typically comprise multiple elements. A defining characteristic of episodic retrieval is holistic recollection, i.e., comprehensive recall of the elements a memorized event encompasses. A recent study implicated activity in the human hippocampus with holistic recollection of multi-element events based on cues (Horner et al., 2015). Here, we obtained ultra-high resolution functional neuroimaging data at 7 tesla in 30 younger adults (12 female) using the same paradigm. In accordance with anatomically inspired computational models and animal research, we found that metabolic activity in hippocampal subfield CA3 (but less pronounced in dentate gyrus) correlated with this form of mnemonic pattern completion across participants. Our study provides the first evidence in humans for a strong involvement of hippocampal subfield CA3 in holistic recollection via pattern completion.SIGNIFICANCE STATEMENT Memories of daily events usually involve multiple elements, although a single element can be sufficient to prompt recollection of the whole event. Such holistic recollection is thought to require reactivation of brain activity representing the full event from one event element ("pattern completion"). Computational and animal models suggest that mnemonic pattern completion is accomplished in a specific subregion of the hippocampus called CA3, but empirical evidence in humans was lacking. Here, we leverage the ultra-high resolution of 7 tesla neuroimaging to provide first evidence for a strong involvement of the human CA3 in holistic recollection of multi-element events via pattern completion.

Cortical laminar resting-state signal fluctuations scale with the hypercapnic blood oxygenation level-dependent response.

Calibrated functional magnetic resonance imaging can remove unwanted sources of signal variability in the blood oxygenation level-dependent (BOLD) response. This is achieved by scaling, using information from a perfusion-sensitive scan during a purely vascular challenge, typically induced by a gas manipulation or a breath-hold task. In this work, we seek for a validation of the use of the resting-state fluctuation amplitude (RSFA) as a scaling factor to remove vascular contributions from the BOLD response. Given the peculiarity of depth-dependent vascularization in gray matter, BOLD and vascular space occupancy (VASO) data were acquired at submillimeter resolution and averaged across cortical laminae. RSFA from the primary motor cortex was, thus, compared to the amplitude of hypercapnia-induced signal changes (tSDhc ) and with the M factor of the Davis model on a laminar level. High linear correlations were observed for RSFA and tSDhc ( R2 = 0.92 ± 0.06) and somewhat reduced for RSFA and M ( R2 = 0.62 ± 0.19). Laminar profiles of RSFA-normalized BOLD signal changes yielded good agreement with corresponding VASO profiles. Overall, this suggests that RSFA contains strong vascular components and is also modulated by baseline quantities contained in the M factor. We conclude that RSFA may replace the scaling factor tSDhc for normalizing the laminar BOLD response.

Robust functional mapping of layer-selective responses in human lateral geniculate nucleus with high-resolution 7T fMRI.

The lateral geniculate nucleus (LGN) of the thalamus is the major subcortical relay of retinal input to the visual cortex. It plays important roles in visual perception and cognition and is closely related with several eye diseases and brain disorders. Primate LGNs mainly consist of six layers of monocular neurons with distinct cell types and functions. The non-invasive measure of layer-selective activities of the human LGN would have broad scientific and clinical implications. Using high-resolution functional magnetic resonance imaging (fMRI) at 7 Tesla (T) and carefully designed visual stimuli, we achieved robust functional mapping of eye-specific and also magnocellular/parvocellular-specific laminar patterns of the human LGN. These laminar patterns were highly reproducible with different pulse sequences scanned on separate days, between different subjects, and were in remarkable consistency with the simulation from high-resolution histology of the human LGNs. These findings clearly demonstrate that 7T fMRI can robustly resolve layer-specific responses of the human LGN. This paves the way for future investigation of the critical roles of the LGN in human visual perception and cognition, as well as the neural mechanisms of many developmental and neurodegenerative diseases.

Ultra-High-Field fMRI Reveals a Role for the Subiculum in Scene Perceptual Discrimination.

Recent "representational" accounts suggest a key role for the hippocampus in complex scene perception. Due to limitations in scanner field strength, however, the functional neuroanatomy of hippocampal-dependent scene perception is unknown. Here, we applied 7 T high-resolution functional magnetic resonance imaging (fMRI) alongside a perceptual oddity task, modified from nonhuman primate studies. This task requires subjects to discriminate highly similar scenes, faces, or objects from multiple viewpoints, and has revealed selective impairments during scene discrimination following hippocampal lesions. Region-of-interest analyses identified a preferential response in the subiculum subfield of the hippocampus during scene, but not face or object, discriminations. Notably, this effect was in the anteromedial subiculum and was not modulated by whether scenes were subsequently remembered or forgotten. These results highlight the value of ultra-high-field fMRI in generating more refined, anatomically informed, functional accounts of hippocampal contributions to cognition, and a unique role for the human subiculum in discrimination of complex scenes from different viewpoints.SIGNIFICANCE STATEMENT There is increasing evidence that the human hippocampus supports functions beyond just episodic memory, with human lesion studies suggesting a contribution to the perceptual processing of navigationally relevant, complex scenes. While the hippocampus itself contains several small, functionally distinct subfields, examining the role of these in scene processing has been previously limited by scanner field strength. By applying ultra-high-resolution 7 T fMRI, we delineated the functional contribution of individual hippocampal subfields during a perceptual discrimination task for scenes, faces, and objects. This demonstrated that the discrimination of scenes, relative to faces and objects, recruits the anterior subicular region of the hippocampus, regardless of whether scenes were subsequently remembered or forgotten.

7T-fMRI: Faster temporal resolution yields optimal BOLD sensitivity for functional network imaging specifically at high spatial resolution.

Recent developments in accelerated imaging methods allow faster acquisition of high spatial resolution images. This could improve the applications of functional magnetic resonance imaging at 7 Tesla (7T-fMRI), such as neurosurgical planning and Brain Computer Interfaces (BCIs). However, increasing the spatial and temporal resolution will both lead to signal-to-noise ratio (SNR) losses due to decreased net magnetization per voxel and T1-relaxation effect, respectively. This could potentially offset the SNR efficiency gains made with increasing temporal resolution. We investigated the effects of varying spatial and temporal resolution on fMRI sensitivity measures and their implications on fMRI-based BCI simulations. We compared temporal signal-to-noise ratio (tSNR), observed percent signal change (%∆S), volumes of significant activation, Z-scores and decoding performance of linear classifiers commonly used in BCIs across a range of spatial and temporal resolution images acquired during an ankle-tapping task. Our results revealed an average increase of 22% in %∆S (p=0.006) and 9% in decoding performance (p=0.015) with temporal resolution only at the highest spatial resolution of 1.5×1.5×1.5mm3, despite a 29% decrease in tSNR (p<0.001) and plateaued Z-scores. Further, the volume of significant activation was indifferent (p>0.05) across spatial resolution specifically at the highest temporal resolution of 500ms. These results demonstrate that the overall BOLD sensitivity can be increased significantly with temporal resolution, granted an adequately high spatial resolution with minimal physiological noise level. This shows the feasibility of diffuse motor-network imaging at high spatial and temporal resolution with robust BOLD sensitivity with 7T-fMRI. Importantly, we show that this sensitivity improvement could be extended to an fMRI application such as BCIs.

Visual field biases for near and far stimuli in disparity selective columns in human visual cortex.

When visual objects are located in the lower visual field, human observers perceive objects to be nearer than their real physical location. Conversely, objects in the upper visual field are viewed farther than their physical location. This bias may be linked to the statistics of natural scenes, and perhaps the ecological relevance of objects in the upper and lower visual fields (Previc, 1990; Yang and Purves, 2003). However, the neural mechanisms underlying such perceptual distortions have remained unknown. To test for underlying brain mechanisms, we presented visual stimuli at different perceptual distances, while measuring high-resolution fMRI in human subjects. First, we localized disparity-selective thick stripes and thick-type columns in secondary and third visual cortical areas, respectively. Consistent with the perceptual bias, we found that the thick stripe/columns that represent the lower visual field also responded more selectively to near rather than far visual stimuli. Conversely, thick stripe/columns that represent the upper visual field show a complementary bias, i.e. selectively higher activity to far rather than near stimuli. Thus, the statistics of natural scenes may play a significant role in the organization of near- and far-selective neurons within V2 thick stripes and V3 thick-type columns.

Effects of transcranial focused ultrasound on human primary motor cortex using 7T fMRI: a pilot study.

BACKGROUND: Transcranial focused ultrasound (tFUS) is a new non-invasive neuromodulation technique that uses mechanical energy to modulate neuronal excitability with high spatial precision. tFUS has been shown to be capable of modulating EEG brain activity in humans that is spatially restricted, and here, we use 7T MRI to extend these findings. We test the effect of tFUS on 7T BOLD fMRI signals from individual finger representations in the human primary motor cortex (M1) and connected cortical motor regions. Participants (N = 5) performed a cued finger tapping task in a 7T MRI scanner with their thumb, index, and middle fingers to produce a BOLD signal for individual M1 finger representations during either tFUS or sham neuromodulation to the thumb representation. RESULTS: Results demonstrated a statistically significant increase in activation volume of the M1 thumb representation for the tFUS condition as compared to sham. No differences in percent BOLD changes were found. This effect was spatially confined as the index and middle finger M1 finger representations did not show similar significant changes in either percent change or activation volume. No effects were seen during tFUS to M1 in the supplementary motor area or the dorsal premotor cortex. CONCLUSIONS: Single element tFUS can be paired with high field MRI that does not induce significant artifact. tFUS increases activation volumes of the targeted finger representation that is spatially restricted within M1 but does not extend to functionally connected motor regions. Trial registration ClinicalTrials.gov NCT03634631 08/14/18.

Topographic representations of object size and relationships with numerosity reveal generalized quantity processing in human parietal cortex.

Humans and many animals analyze sensory information to estimate quantities that guide behavior and decisions. These quantities include numerosity (object number) and object size. Having recently demonstrated topographic maps of numerosity, we ask whether the brain also contains maps of object size. Using ultra-high-field (7T) functional MRI and population receptive field modeling, we describe tuned responses to visual object size in bilateral human posterior parietal cortex. Tuning follows linear Gaussian functions and shows surround suppression, and tuning width narrows with increasing preferred object size. Object size-tuned responses are organized in bilateral topographic maps, with similar cortical extents responding to large and small objects. These properties of object size tuning and map organization all differ from the numerosity representation, suggesting that object size and numerosity tuning result from distinct mechanisms. However, their maps largely overlap and object size preferences correlate with numerosity preferences, suggesting associated representations of these two quantities. Object size preferences here show no discernable relation to visual position preferences found in visuospatial receptive fields. As such, object size maps (much like numerosity maps) do not reflect sensory organ structure but instead emerge within the brain. We speculate that, as in sensory processing, optimization of cognitive processing using topographic maps may be a common organizing principle in association cortex. Interactions between object size and numerosity maps may associate cognitive representations of these related features, potentially allowing consideration of both quantities together when making decisions.