Natalia Petridou

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.

Direct magnetic resonance detection of neuronal electrical activity

Present noninvasive neuroimaging methods measure neuronal activity indirectly, via either cerebrovascular changes or extracranial measurements of electrical/magnetic signals. Recent studies have shown evidence that MRI may be used to directly and noninvasively map electrical activity associated with human brain activation, but results are inconclusive. Here, we show that MRI can detect cortical electrical activity directly. We use organotypic rat-brain cultures in vitro that are spontaneously active in the absence of a cerebrovascular system. Single-voxel magnetic resonance (MR) measurements obtained at 7 T were highly correlated with multisite extracellular local field potential recordings of the same cultures before and after blockade of neuronal activity with tetrodotoxin. Similarly, for MR images obtained at 3 T, the MR signal changed solely in voxels containing the culture, thus allowing the spatial localization of the active neuronal tissue.

Cortical depth-dependent temporal dynamics of the BOLD response in the human brain

Recent animal studies at high field have shown that blood oxygen level-dependent (BOLD) contrast can be specific to the laminar vascular architecture of the cortex, by differences in its temporal dynamics in reference to cortical depth. In this study, we characterize the temporal dynamics of the hemodynamic response (HDR) across cortical depth in the human primary motor and visual cortex, at 7T and using very short stimuli and with high spatial and temporal resolution. We find that the shape and temporal dynamics of the HDR changed in an orderly manner across cortical depth. Compared with the pial vasculature, HDRs in deeper gray matter are significantly faster in onset time (by ∼ 0.5 second) and peak time (∼2 seconds), and are narrower (by ∼1 second) and with smaller amplitude, in line with the known vascular organization across cortical depth and the transit of deoxygenated blood through the vasculature. The width of the HDR in deeper gray matter was as short as 2.1 seconds, indicating that neurovascular coupling takes place at a shorter timescale than previously reported in the human brain. These findings open the possibility to probe layer-specific hemodynamics and neurovascular coupling mechanisms in human gray matter.

Periods of Rest in fMRI Contain Individual Spontaneous Events which are Related to Slowly Fluctuating Spontaneous Activity

fMRI studies of brain activity at rest study slow (<0.1 Hz) intrinsic fluctuations in the blood‐oxygenation‐level‐dependent (BOLD) signal that are observed in a temporal scale of several minutes. The origin of these fluctuations is not clear but has previously been associated with slow changes in rhythmic neuronal activity resulting from changes in cortical excitability or neuronal synchronization. In this work, we show that individual spontaneous BOLD events occur during rest, in addition to slow fluctuations. Individual spontaneous BOLD events were identified by deconvolving the hemodynamic impulse response function for each time point in the fMRI time series, thus requiring no information on timing or a‐priori spatial information of events. The patterns of activation detected were related to the motor, visual, default‐mode, and dorsal attention networks. The correspondence between spontaneous events and slow fluctuations in these networks was assessed using a sliding window, seed‐correlation analysis, where seed regions were selected based on the individual spontaneous event BOLD activity maps. We showed that the correlation varied considerably over time, peaking at the time of spontaneous events in these networks. By regressing spontaneous events out of the fMRI signal, we showed that both the correlation strength and the power in spectral frequencies <0.1 Hz decreased, indicating that spontaneous activation events contribute to low‐frequency fluctuations observed in resting state networks with fMRI. This work provides new insights into the origin of signals detected in fMRI studies of functional connectivity. Hum Brain Mapp, 2013.

Fast high resolution whole brain T2* weighted imaging using echo planar imaging at 7 T

Magnetic susceptibility based (T(2)* weighted) contrast in MRI at high magnetic field strength is of great value in research on brain structure and cortical architecture, but its use is hampered by the low signal-to-noise ratio (SNR) efficiency of the conventional spoiled gradient echo sequence (GRE) leading to long scan times even for a limited number of slices. In this work, we show that high resolution (0.5mm isotropic) T(2)* weighted images of the whole brain can be obtained in 6min by utilizing the high SNR efficiency of echo-planar imaging (EPI). A volumetric (3D) EPI protocol is presented and compared to conventional 3D GRE images acquired with the same resolution, amount of T(2)* weighting, and imaging duration. Spatial coverage in 3D EPI was increased by a factor of 4.5 compared to 3D GRE, while also the SNR was increased by a factor of 2. Image contrast for both magnitude and phase between gray and white matter was similar for both sequences, with enhanced conspicuity of anatomic details in the 3D EPI images due to the increased SNR. Even at 7T, image blurring and distortion is limited if the EPI train length remains short (not longer than the T(2)* of the imaged tissue). 3D EPI provides steps (speed, whole brain coverage, and high isotropic resolution) that are necessary to utilize the benefits of high field MRI in research that employs T(2)* weighted imaging.

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.

BOLD matches neuronal activity at the mm scale: A combined 7 T fMRI and ECoG study in human sensorimotor cortex

High resolution BOLD fMRI has the potential to map activation patterns of small neuronal populations at the scale of cortical columns. However, BOLD fMRI does not measure neuronal activity, but only a correlate thereof, since it measures blood dynamics. To confirm that BOLD activation maps reflect neuronal population activity patterns, a direct comparison with neuro-electrophysiological data from the same cortical patch is necessary. Here, we compare BOLD activation patterns obtained with fMRI at 7 T to electrophysiological patterns obtained with implanted high density electrocorticography (ECoG) grids in the same patch of human sensorimotor cortex, and with similar resolution (1.5mm). We used high spatially sampled high-frequency broadband (HFB) power from ECoG, which reflects local neuronal population activity. The spatial distribution of 7 T BOLD activation matched the spatial distribution of ECoG HFB-power changes in the covered patch of sensorimotor cortex. BOLD fMRI activation foci were located within 1-3mm of the HFB-power ECoG foci. Both methods distinguished individual finger movement activation within a 1cm cortical patch, revealing a topographical medial to lateral layout for the little finger to index to thumb. These findings demonstrate that the BOLD signal at 7 T is strongly correlated with the underlying electrophysiology, and is capable of discriminating patterns of neuronal population activity at a millimeter scale. The results further indicate the utility of 7 T fMRI for investigation of intra-area organization of function and network dynamics.

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.

Patterns of resting state connectivity in human primary visual cortical areas: A 7T fMRI study

The nature and origin of fMRI resting state fluctuations and connectivity are still not fully known. More detailed knowledge on the relationship between resting state patterns and brain function may help to elucidate this matter. We therefore performed an in depth study of how resting state fluctuations map to the well known architecture of the visual system. We investigated resting state connectivity at both a fine and large scale within and across visual areas V1, V2 and V3 in ten human subjects using a 7Tesla scanner. We found evidence for several coexisting and overlapping connectivity structures at different spatial scales. At the fine-scale level we found enhanced connectivity between the same topographic locations in the fieldmaps of V1, V2 and V3, enhanced connectivity to the contralateral functional homologue, and to a lesser extent enhanced connectivity between iso-eccentric locations within the same visual area. However, by far the largest proportion of the resting state fluctuations occurred within large-scale bilateral networks. These large-scale networks mapped to some extent onto the architecture of the visual system and could thereby obscure fine-scale connectivity. In fact, most of the fine-scale connectivity only became apparent after the large-scale network fluctuations were filtered from the timeseries. We conclude that fMRI resting state fluctuations in the visual cortex may in fact be a composite signal of different overlapping sources. Isolating the different sources could enhance correlations between BOLD and electrophysiological correlates of resting state activity.

BOLD Consistently Matches Electrophysiology in Human Sensorimotor Cortex at Increasing Movement Rates: A Combined 7T fMRI and ECoG Study on Neurovascular Coupling

Blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) is widely used to measure human brain function and relies on the assumption that hemodynamic changes mirror the underlying neuronal activity. However, an often reported saturation of the BOLD response at high movement rates has led to the notion of a mismatch in neurovascular coupling. We combined BOLD fMRI at 7T and intracranial electrocorticography (ECoG) to assess the relationship between BOLD and neuronal population activity in human sensorimotor cortex using a motor task with increasing movement rates. Though linear models failed to predict BOLD responses from the task, the measured BOLD and ECoG responses from the same tissue were in good agreement. Electrocorticography explained almost 80% of the mismatch between measured- and model-predicted BOLD responses, indicating that in human sensorimotor cortex, a large portion of the BOLD nonlinearity with respect to behavior (movement rate) is well predicted by electrophysiology. The results further suggest that other reported examples of BOLD mismatch may be related to neuronal processes, rather than to neurovascular uncoupling.