Dual Representation of the Auditory Space.

Auditory spatial cues contribute to two distinct functions, of which one leads to explicit localization of sound sources and the other provides a location-linked representation of sound objects. Behavioral and imaging studies demonstrated right-hemispheric dominance for explicit sound localization. An early clinical case study documented the dissociation between the explicit sound localizations, which was heavily impaired, and fully preserved use of spatial cues for sound object segregation. The latter involves location-linked encoding of sound objects. We review here evidence pertaining to brain regions involved in location-linked representation of sound objects. Auditory evoked potential (AEP) and functional magnetic resonance imaging (fMRI) studies investigated this aspect by comparing encoding of individual sound objects, which changed their locations or remained stationary. Systematic search identified 1 AEP and 12 fMRI studies. Together with studies of anatomical correlates of impaired of spatial-cue-based sound object segregation after focal brain lesions, the present evidence indicates that the location-linked representation of sound objects involves strongly the left hemisphere and to a lesser degree the right hemisphere. Location-linked encoding of sound objects is present in several early-stage auditory areas and in the specialized temporal voice area. In these regions, emotional valence benefits from location-linked encoding as well.

Individual connectivity-based parcellations reflect functional properties of human auditory cortex.

Neuroimaging studies of the functional organization of human auditory cortex have focused on group-level analyses to identify tendencies that represent the typical brain. Here, we mapped auditory areas of the human superior temporal cortex (STC) in 30 participants by combining functional network analysis and 1-mm isotropic resolution 7T functional magnetic resonance imaging (fMRI). Two resting-state fMRI sessions, and one or two auditory and audiovisual speech localizer sessions, were collected on 3-4 separate days. We generated a set of functional network-based parcellations from these data. Solutions with 4, 6, and 11 networks were selected for closer examination based on local maxima of Dice and Silhouette values. The resulting parcellation of auditory cortices showed high intraindividual reproducibility both between resting state sessions (Dice coefficient: 69-78%) and between resting state and task sessions (Dice coefficient: 62-73%). This demonstrates that auditory areas in STC can be reliably segmented into functional subareas. The interindividual variability was significantly larger than intraindividual variability (Dice coefficient: 57%-68%, p<0.001), indicating that the parcellations also captured meaningful interindividual variability. The individual-specific parcellations yielded the highest alignment with task response topographies, suggesting that individual variability in parcellations reflects individual variability in auditory function. Connectional homogeneity within networks was also highest for the individual-specific parcellations. Furthermore, the similarity in the functional parcellations was not explainable by the similarity of macroanatomical properties of auditory cortex. Our findings suggest that individual-level parcellations capture meaningful idiosyncrasies in auditory cortex organization.

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.

3T vs. 7T fMRI: capturing early human memory consolidation after motor task utilizing the observed higher functional specificity of 7T.

Objective: Functional magnetic resonance imaging (fMRI) visualizes brain structures at increasingly higher resolution and better signal-to-noise ratio (SNR) as field strength increases. Yet, mapping the blood oxygen level dependent (BOLD) response to distinct neuronal processes continues to be challenging. Here, we investigated the characteristics of 7 T-fMRI compared to 3 T-fMRI in the human brain beyond the effect of increased SNR and verified the benefits of 7 T-fMRI in the detection of tiny, highly specific modulations of functional connectivity in the resting state following a motor task. Methods: 18 healthy volunteers underwent two resting state and a stimulus driven measurement using a finger tapping motor task at 3 and 7 T, respectively. The SNR for each field strength was adjusted by targeted voxel size variation to minimize the effect of SNR on the field strength specific outcome. Spatial and temporal characteristics of resting state ICA, network graphs, and motor task related activated areas were compared. Finally, a graph theoretical approach was used to detect resting state modulation subsequent to a simple motor task. Results: Spatial extensions of resting state ICA and motor task related activated areas were consistent between field strengths, but temporal characteristics varied, indicating that 7 T achieved a higher functional specificity of the BOLD response than 3 T-fMRI. Following the motor task, only 7 T-fMRI enabled the detection of highly specific connectivity modulations representing an "offline replay" of previous motor activation. Modulated connections of the motor cortex were directly linked to brain regions associated with memory consolidation. Conclusion: These findings reveal how memory processing is initiated even after simple motor tasks, and that it begins earlier than previously shown. Thus, the superior capability of 7 T-fMRI to detect subtle functional dynamics promises to improve diagnostics and therapeutic assessment of neurological diseases.

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.

Emotional sounds in space: asymmetrical representation within early-stage auditory areas.

Evidence from behavioral studies suggests that the spatial origin of sounds may influence the perception of emotional valence. Using 7T fMRI we have investigated the impact of the categories of sound (vocalizations; non-vocalizations), emotional valence (positive, neutral, negative) and spatial origin (left, center, right) on the encoding in early-stage auditory areas and in the voice area. The combination of these different characteristics resulted in a total of 18 conditions (2 categories x 3 valences x 3 lateralizations), which were presented in a pseudo-randomized order in blocks of 11 different sounds (of the same condition) in 12 distinct runs of 6 min. In addition, two localizers, i.e., tonotopy mapping; human vocalizations, were used to define regions of interest. A three-way repeated measure ANOVA on the BOLD responses revealed bilateral significant effects and interactions in the primary auditory cortex, the lateral early-stage auditory areas, and the voice area. Positive vocalizations presented on the left side yielded greater activity in the ipsilateral and contralateral primary auditory cortex than did neutral or negative vocalizations or any other stimuli at any of the three positions. Right, but not left area L3 responded more strongly to (i) positive vocalizations presented ipsi- or contralaterally than to neutral or negative vocalizations presented at the same positions; and (ii) to neutral than positive or negative non-vocalizations presented contralaterally. Furthermore, comparison with a previous study indicates that spatial cues may render emotional valence more salient within the early-stage auditory areas.

Temporal lobe perceptual predictions for speech are instantiated in motor cortex and reconciled by inferior frontal cortex.

Humans use predictions to improve speech perception, especially in noisy environments. Here we use 7-T functional MRI (fMRI) to decode brain representations of written phonological predictions and degraded speech signals in healthy humans and people with selective frontal neurodegeneration (non-fluent variant primary progressive aphasia [nfvPPA]). Multivariate analyses of item-specific patterns of neural activation indicate dissimilar representations of verified and violated predictions in left inferior frontal gyrus, suggestive of processing by distinct neural populations. In contrast, precentral gyrus represents a combination of phonological information and weighted prediction error. In the presence of intact temporal cortex, frontal neurodegeneration results in inflexible predictions. This manifests neurally as a failure to suppress incorrect predictions in anterior superior temporal gyrus and reduced stability of phonological representations in precentral gyrus. We propose a tripartite speech perception network in which inferior frontal gyrus supports prediction reconciliation in echoic memory, and precentral gyrus invokes a motor model to instantiate and refine perceptual predictions for speech.

Layer-specific correlates of detected and undetected auditory targets during attention.

In everyday life, the processing of acoustic information allows us to react to subtle changes in the auditory scene. Yet even when closely attending to sounds in the context of a task, we occasionally miss task-relevant features. The neural computations that underlie our ability to detect behavioral relevant sound changes are thought to be grounded in both feedforward and feedback processes within the auditory hierarchy. Here, we assessed the role of feedforward and feedback contributions in primary and non-primary auditory areas during behavioral detection of target sounds using submillimeter spatial resolution functional magnetic resonance imaging (fMRI) at high-fields (7 T) in humans. We demonstrate that the successful detection of subtle temporal shifts in target sounds leads to a selective increase of activation in superficial layers of primary auditory cortex (PAC). These results indicate that feedback signals reaching as far back as PAC may be relevant to the detection of targets in the auditory scene.

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.

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.

Noninvasive Characterization of Functional Pathways in Layer-Specific Microcircuits of the Human Brain Using 7T fMRI.

Layer-specific cortical microcircuits have been explored through invasive animal studies, yet it is not possible to reliably characterize them functionally and noninvasively in the human brain. However, recent advances in ultra-high-field functional magnetic resonance imaging (fMRI) have made it feasible to reasonably resolve layer-specific fMRI signals with sub-millimeter resolution. Here, we propose an experimental and analytical framework that enables the noninvasive functional characterization of layer-specific cortical microcircuits. Specifically, we illustrate this framework by characterizing layer-specific functional pathways in the corticogeniculate network of the human visual system by obtaining sub-millimeter fMRI at 7T using a task which engages the magnocellular pathway between the lateral geniculate nucleus (LGN) and the primary visual cortex. Our results demonstrate that: (i) center-surround inhibition in magnocellular neurons within LGN is detectable using localized fMRI responses; (ii) feedforward (LGN → layers VI/IV, layer IV → layer VI) and feedback (layer VI → LGN) functional pathways, known to exist from invasive animal studies, can be inferred using dynamic directional connectivity models of fMRI and could potentially explain the mechanism underlying center-surround inhibition as well as gain control by layer VI in the human visual system. Our framework is domain-neutral and could potentially be employed to investigate the layer-specific cortical microcircuits in other systems related to cognition, memory and language.

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.

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.

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.

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.

Layer-dependent multiplicative effects of spatial attention on contrast responses in human early visual cortex.

Attention mechanisms at different cortical layers of human visual cortex remain poorly understood. Using submillimeter-resolution fMRI at 7 Tesla, we investigated the effects of top-down spatial attention on the contrast responses across different cortical depths in human early visual cortex. Gradient echo (GE) T2* weighted BOLD signal showed an additive effect of attention on contrast responses across cortical depths. Compared to the middle cortical depth, attention modulation was stronger in the superficial and deep depths of V1, and also stronger in the superficial depth of V2 and V3. Using ultra-high resolution (0.3 mm in-plane) balanced steady-state free precession (bSSFP) fMRI, a multiplicative scaling effect of attention was found in the superficial and deep layers, but not in the middle layer of V1. Attention modulation of low contrast response was strongest in the middle cortical depths, indicating baseline enhancement or contrast gain of attention modulation on feedforward input. Finally, the additive vs. scaling effect of attention from GE-EPI and bSSFP signals can be explained by stronger nonlinearity of BOLD signals from large than small blood vessels, suggesting multiplicative effect of attention on neural activity. These findings support that top-down spatial attention mainly operates through feedback connections from higher order cortical areas, and a distinct mechanism of attention may also be associated with feedforward input through subcortical pathway.

Layer-dependent functional connectivity methods.

Recent methodological advances in fMRI contrast and readout strategies have allowed researchers to approach the mesoscopic spatial regime of cortical layers. This has revolutionized the ability to map cortical information processing within and across brain systems. However, until recently, most layer-fMRI studies have been confined to primary cortices using basic block-design tasks and macro-vascular-contaminated sequence contrasts. To become an established method for user-friendly applicability in neuroscience practice, layer-fMRI acquisition and analysis methods need to be extended to more flexible connectivity-based experiment designs; they must be able to capture subtle changes in brain networks of higher-order cognitive areas, and they should not be spatially biased with unwanted vein signals. In this article, we review the most pressing challenges of layer-dependent fMRI for large-scale neuroscientific applicability and describe recently developed acquisition methodologies that can resolve them. In doing so, we review technical tradeoffs and capabilities of modern MR-sequence approaches to achieve measurements that are free of locally unspecific vein signal, with whole-brain coverage, sub-second sampling, high resolutions, and with a combination of those capabilities. The presented approaches provide whole-brain layer-dependent connectivity data that open a new window to investigate brain network connections. We exemplify this by reviewing a number of candidate tools for connectivity analyses that will allow future studies to address new questions in network neuroscience. The considered network analysis tools include: hierarchy mapping, directional connectomics, source-specific connectivity mapping, and network sub-compartmentalization. We conclude: Whole-brain layer-fMRI without large-vessel contamination is applicable for human neuroscience and opens the door to investigate biological mechanisms behind any number of psychological and psychiatric phenomena, such as selective attention, hallucinations and delusions, and even conscious perception.

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.