Ben M. Harvey

Topographic Representation of Numerosity in the Human Parietal Cortex

Number Sense Numerosity perception resembles primary sensory perception and, indeed, it has been called the number sense. As all primary senses are organized topographically in the cortex, Harvey et al. (p. 1123) tested the hypothesis that numerosity is also organized topographically. Applying ultrahighfield functional brain scanning and using custom-designed analysis, they confirmed that a topographical numerosity map occurs in the human parietal cortex, which displays conventional characteristics, such as a systematic relationship between the cortical locations preferred numerosity and cortical magnification and tuning width. There is a map of numerical magnitude in the human brain. Numerosity, the set size of a group of items, is processed by the association cortex, but certain aspects mirror the properties of primary senses. Sensory cortices contain topographic maps reflecting the structure of sensory organs. Are the cortical representation and processing of numerosity organized topographically, even though no sensory organ has a numerical structure? Using high-field functional magnetic resonance imaging (at a field strength of 7 teslas), we described neural populations tuned to small numerosities in the human parietal cortex. They are organized topographically, forming a numerosity map that is robust to changes in low-level stimulus features. The cortical surface area devoted to specific numerosities decreases with increasing numerosity, and the tuning width increases with preferred numerosity. These organizational properties extend topographic principles to the representation of higher-order abstract features in the association cortex.

The Relationship between Cortical Magnification Factor and Population Receptive Field Size in Human Visual Cortex: Constancies in Cortical Architecture

Receptive field (RF) sizes and cortical magnification factor (CMF) are fundamental organization properties of the visual cortex. At increasing visual eccentricity, RF sizes increase and CMF decreases. A relationship between RF size and CMF suggests constancies in cortical architecture, as their product, the cortical representation of an RF (point image), may be constant. Previous animal neurophysiology studies of this question yield conflicting results. Here, we use fMRI to determine the relationship between the population RF (pRF) and CMF in humans. In average and individual data, the product of CMF and pRF size, the population point image, is near constant, decreasing slightly with eccentricity in V1. Interhemisphere and subject variations in CMF, pRF size, and V1 surface area are correlated, and the population point image varies less than these properties. These results suggest a V1 cortical processing architecture of approximately constant size between humans. Up the visual hierarchy, to V2, V3, hV4, and LO1, the population point image decreases with eccentricity, and both the absolute values and rate of change increase. PRF sizes increase between visual areas and with eccentricity, but when expressed in V1 cortical surface area (i.e., corticocortical pRFs), they are constant across eccentricity in V2/V3. Thus, V2/V3, and to some degree hV4, sample from a constant extent of V1. This may explain population point image changes in later areas. Consequently, the constant factor determining pRF size may not be the relationship to the local CMF, but rather pRF sizes and CMFs in visual areas from which the pRF samples.

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

Significance Processing of quantities such as object sizes and numbers relies on analyses of sensory information and informs cognitive tasks such as decision making and mathematics. Whereas sensory processing is organized into topographic maps reflecting sensory organ structure, organization of cognitive processing is poorly understood. We demonstrate topographic representation of object size-tuned responses. This arises separately from object number tuning, but these two quantities are associated in overlapping maps. This generalized quantity representation may allow us to consider object size and number together when making decisions. Optimization of cognitive processing using topographic maps may be a common organizing principle in association cortex, as it is in sensory processing. Linking cognitive representations in maps of related features may support increasingly abstract cognition. 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.

Attraction of position preference by spatial attention throughout human visual cortex.

Voluntary spatial attention concentrates neural resources at the attended location. Here, we examined the effects of spatial attention on spatial position selectivity in humans. We measured population receptive fields (pRFs) using high-field functional MRI (fMRI) (7T) while subjects performed an attention-demanding task at different locations. We show that spatial attention attracts pRF preferred positions across the entire visual field, not just at the attended location. This global change in pRF preferred positions systematically increases up the visual hierarchy. We model these pRF preferred position changes as an interaction between two components: an attention field and a pRF without the influence of attention. This computational model suggests that increasing effects of attention up the hierarchy result primarily from differences in pRF size and that the attention field is similar across the visual hierarchy. A similar attention field suggests that spatial attention transforms different neural response selectivities throughout the visual hierarchy in a similar manner.

Frequency specific spatial interactions in human electrocorticography: V1 alpha oscillations reflect surround suppression

Electrical brain signals are often decomposed into frequency ranges that are implicated in different functions. Using subdural electrocorticography (ECoG, intracranial EEG) and functional magnetic resonance imaging (fMRI), we measured frequency spectra and BOLD responses in primary visual cortex (V1) and intraparietal sulcus (IPS). In V1 and IPS, 30-120 Hz (gamma, broadband) oscillations allowed population receptive field (pRF) reconstruction comparable to fMRI estimates. Lower frequencies, however, responded very differently in V1 and IPS. In V1, broadband activity extends down to 3 Hz. In the 4-7 Hz (theta) and 18-30 Hz (beta) ranges broadband activity increases power during stimulation within the pRF. However, V1 9-12 Hz (alpha) frequency oscillations showed a different time course. The broadband power here is exceeded by a frequency-specific power increase during stimulation of the area outside the pRF. As such, V1 alpha oscillations reflected surround suppression of the pRF, much like negative fMRI responses. They were consequently highly localized, depending on stimulus and pRF position, and independent between nearby electrodes. In IPS, all 3-25 Hz oscillations were strongest during baseline recording and correlated between nearby electrodes, consistent with large-scale disengagement. These findings demonstrate V1 alpha oscillations result from locally active functional processes and relate these alpha oscillations to negative fMRI signals. They highlight that similar oscillations in different areas reflect processes with different functional roles. However, both of these roles of alpha seem to reflect suppression of spiking activity.

Connective field modeling.

The traditional way to study the properties of visual neurons is to measure their responses to visually presented stimuli. A second way to understand visual neurons is to characterize their responses in terms of activity elsewhere in the brain. Understanding the relationships between responses in distinct locations in the visual system is essential to clarify this network of cortical signaling pathways. Here, we describe and validate connective field modeling, a model-based analysis for estimating the dependence between signals in distinct cortical regions using functional magnetic resonance imaging (fMRI). Just as the receptive field of a visual neuron predicts its response as a function of stimulus position, the connective field of a neuron predicts its response as a function of activity in another part of the brain. Connective field modeling opens up a wide range of research opportunities to study information processing in the visual system and other topographically organized cortices.

Measurement of population receptive fields in human early visual cortex using back-projection tomography

Properties of human visual population receptive fields (pRFs) are currently estimated by performing measurements of visual stimulation using functional magnetic resonance imaging (fMRI), and then fitting the results using a predefined model shape for the pRF. Various models exist and different models may be appropriate under different circumstances, but the validity of the models has never been verified, suggesting the need for a model-free approach. Here, we demonstrate that pRFs can be directly reconstructed using a back-projection-tomography approach that requires no a priori model. The back-projection method involves sweeping thin contrast-defined bars across the visual field whose orientation and direction is rotated through 0°-180° in discrete increments. The measured fMRI time series within a cortical location can be approximated as a projection of the pRF along the long axis of the bar. The signals produced by a set of bar sweeps encircling the visual field form a sinogram. pRFs were reconstructed from these sinograms with a novel scheme that corrects for the blur introduced by the hemodynamic response and the stimulus-bar width. pRF positions agree well with the conventional model-based approach. Notably, a subset of the reconstructed pRFs shows significant asymmetry for both their excitatory and suppressive regions. Reconstructing pRFs using the tomographic approach is a fast, reliable, and accurate way to noninvasively estimate human pRF parameters and visual-field maps without the need for any a priori shape assumption.

Action preparation shapes processing in early visual cortex

Preparation for an action, such as grasping an object, is accompanied by an enhanced perception of the objects action-relevant features, such as orientation and size. Cortical feedback from motor planning areas to early visual areas may drive this enhanced perception. To examine whether action preparation modulates activity in early human visual cortex, subjects grasped or pointed to oriented objects while high-resolution fMRI data were acquired. Using multivoxel pattern analysis techniques, we could decode with >70% accuracy whether a grasping or pointing action was prepared from signals in visual cortex as early as V1. These signals in early visual cortex were observed even when actions were only prepared but not executed. Anterior parietal cortex, on the other hand, showed clearest modulation for actual movements. This demonstrates that preparation of actions, even without execution, modulates relevant neuronal populations in early visual areas.

Cortical connective field estimates from resting state fMRI activity

One way to study connectivity in visual cortical areas is by examining spontaneous neural activity. In the absence of visual input, such activity remains shaped by the underlying neural architecture and, presumably, may still reflect visuotopic organization. Here, we applied population connective field (CF) modeling to estimate the spatial profile of functional connectivity in the early visual cortex during resting state functional magnetic resonance imaging (RS-fMRI). This model-based analysis estimates the spatial integration between blood-oxygen level dependent (BOLD) signals in distinct cortical visual field maps using fMRI. Just as population receptive field (pRF) mapping predicts the collective neural activity in a voxel as a function of response selectivity to stimulus position in visual space, CF modeling predicts the activity of voxels in one visual area as a function of the aggregate activity in voxels in another visual area. In combination with pRF mapping, CF locations on the cortical surface can be interpreted in visual space, thus enabling reconstruction of visuotopic maps from resting state data. We demonstrate that V1 ➤ V2 and V1 ➤ V3 CF maps estimated from resting state fMRI data show visuotopic organization. Therefore, we conclude that—despite some variability in CF estimates between RS scans—neural properties such as CF maps and CF size can be derived from resting state data.

Contour extracting networks in early extrastriate cortex

Neurons in the visual cortex process a local region of visual space, but in order to adequately analyze natural images, neurons need to interact. The notion of an ‘‘association field’’ proposes that neurons interact to extract extended contours. Here, we identify the site and properties of contour integration mechanisms. We used functional magnetic resonance imaging (fMRI) and population receptive field (pRF) analyses. We devised pRF mapping stimuli consisting of contours. We isolated the contribution of contour integration mechanisms to the pRF by manipulating the contour content. This stimulus manipulation led to systematic changes in pRF size. Whereas a bank of Gabor filters quantitatively explains pRF size changes in V1, only V2/V3 pRF sizes match the predictions of the association field. pRF size changes in later visual field maps, hV4, LO-1, and LO-2 do not follow either prediction and are probably driven by distinct classical receptive field properties or other extraclassical integration mechanisms. These pRF changes do not follow conventional fMRI signal strength measures. Therefore, analyses of pRF changes provide a novel computational neuroimaging approach to investigating neural interactions. We interpreted these results as evidence for neural interactions along cooriented, cocircular receptive fields in the early extrastriate visual cortex (V2/V3), consistent with the notion of a contour association field.