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Chaimow, D.

Publications and source records attributed to Chaimow, D..

9 recordsLinked to original sources

Evolution of the motor cortex microstructure and its lateralization: a comparative study of chimpanzees and humans

Human hand coordination exceeds that of other species, including great apes, and is marked by pronounced right-hand dominance. This specialization parallels an expansion of its cortical representation, forming the hand-knob in the motor cortex. In humans, this region shows high myelination on quantitative MRI (qMRI), but whether this feature is shared with great apes remains unclear. It is also unknown whether increased right-hand dominance in humans is mirrored by greater hemispheric asymmetry in cortical microstructure. Using high-resolution qMRI, we compared motor cortex subdivisions controlling the leg, hand, and face in humans and chimpanzees. We found consistently higher myelin and iron content in the hand-knob in both species, suggesting an evolutionarily conserved role. However, only humans showed enhanced rightward lateralization. These results highlight both conserved and species-specific features of the motor cortex, offering insights into the evolution of manual dexterity and handedness.

neuroscience↗

Vascular draining confounds laminar decoding in fMRI

Laminar fMRI using GE-BOLD is vulnerable to spatial blurring from intracortical veins, while multivariate pattern analysis (MVPA) is often assumed to mitigate these biases. Yet, this assumption has not been systematically investigated. We thus developed a mechanistic laminar response model that simulates voxel-wise patterns across cortical depths, incorporating a vascular draining model. We conducted simulations in which the ground-truth signal originated in a single, several, or across all layers, and applied standard MVPA decoding before and after deconvolution of the draining effect. Decoding accuracies were consistently influenced by draining veins: deep-origin signals yielded above-chance decoding in superficial layers, and null scenarios produced false positives in middle or deep layers. Vascular deconvolution enhanced specificity in single-layer cases but did not resolve ambiguities in null decoding profiles. Simulating six thinner layers improved decoding accuracies, especially in the deconvolved signal scenarios. These findings demonstrate that multivariate techniques are not inherently immune to vascular biases, but also demonstrate that careful modeling can help correct draining effects.

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Spatial specificity of the functional gradient echo and spin echo BOLD signal across cortical depth at 7 T

Functional magnetic resonance imaging (fMRI) at high magnetic field strengths ([≥] 7 T) is a promising technique to study the functioning of the human brain at the spatial scale of cortical columns and layers. However, measurements most often rely on the blood oxygenation level dependent (BOLD) response sampled with a gradient echo (GE) sequence, which is known to be most sensitive to macrovascular contributions that limit their effective spatial resolution. Alternatively, a spin echo (SE) sequence can be used to increase the weighting toward the microvasculature and, therefore, the location of neural activation. In addition, due to the heterogeneous structure of the cortical cerebrovascular system, the effective spatial resolution can change across cortical depth. For high-resolution fMRI applications, it is hence important to know how much the effective spatial resolution varies across cortical depth. In this study, we used flickering rotating wedge stimuli to induce traveling waves with varying spatial frequencies in the retinotopically organized primary visual cortex (V1), which allowed us to infer the modulation transfer function (MTF) of the BOLD response that characterizes the spatial specificity of the measured signal. We acquired GE- and SE-BOLD data at 7 T and compared the MTF between acquisition techniques at different cortical depths. Our results show a small but consistent increase in spatial specificity when using SE-BOLD. But across cortical depth, both acquisition techniques generally show a similar decrease of specificity toward the pial surface demonstrating the dependence on macrovascular contributions, which needs to be carefully considered when interpreting the results of high-resolution fMRI studies.

neuroscience↗

Challenges in replicating layer-specificity of working memory processes in human dlPFC

Although working memory reliably activates the dorsolateral prefrontal cortex (dlPFC), the functional contributions of its cortical layers in humans remain unclear. A seminal study reported a laminar dissociation in dlPFC--superficial layers engaged during working-memory manipulation and deeper layers during motor response execution. Like many current layer-resolved studies, that work relied on several manual and semi-manual processing steps, including the selection of regions of interest. We conducted a preregistered replication in 21 human participants using an automated and fully reproducible analysis pipeline. While we replicated the superficial-layer effect during manipulation, we found no evidence for preferential deep-layer activation during response execution. This biologically plausible result refines current models of laminar organization in the human prefrontal cortex and aligns human evidence with the more heterogeneous animal literature. By demonstrating reproducibility through preregistration and automation, this work establishes a benchmark for laminar analyses in cognitive neuroscience.

neuroscience↗

Connectivity at fine scale: mapping structural connective fields by tractography of short association fibres in vivo

The extraordinary number of short association fibres (SAF) connecting neighbouring cortical areas is a prominent feature of the large gyrified human brain. The contribution of SAF to the human connectome is largely unknown because of methodological challenges in mapping them. We present a method to characterise cortico-cortical connectivity mediated by SAF in topologically organised cortical areas. We introduce the structural connective fields (sCF) metric which specifically quantifies neuronal signal propagation and integration mediated by SAF. This new metric complements functional connective field metrics integrating across contributions from short- and long-range white matter and intracortical fibres. Applying the method in the human early visual processing stream, we show that SAF preserve cortical functional topology. Retinotopic maps of V2 and V3 could be predicted from retinotopy in V1 and SAF connectivity. The sCF sizes increased along the cortical hierarchy and were smaller than their functional counterparts, in line with the latter being additionally broadened by long-range and intracortical connections. In vivo sCF mapping provides insights into short-range cortico- cortical connectivity in humans comparable to tract tracing studies in animal research and is an essential step towards creating a complete human connectome. HighlightsO_LINon-invasive mapping of Short Association Fibre (SAF) connectivity via diffusion-weighted MRI-based probabilistic tractography accurately predicted cortical functional neuroanatomy. C_LIO_LIThe novel structural Connective Fields (sCF) concept provides a quantitative measure of cortico-cortical integration facilitated by SAF, complementing the existing functional Connective Field (CF) concept. C_LIO_LISub-millimeter resolution diffusion-weighted MRI enables tractography and connective field modeling of SAF, unlocking applications previously restricted to invasive tract tracing in animal studies. C_LI

neuroscience↗

Dynamic layer-specific processing in the prefrontal cortex during working memory

The dorsolateral prefrontal cortex (dlPFC) is reliably engaged in working memory (WM). Evidence from non-human primates indicates that the dlPFC comprises different cytoarchitectonic layers that play distinct roles in WM subprocesses; yet the functional role of the dlPFCs laminar circuitry in human WM is not well understood. In this study, participants completed a delayed-match-to-sample WM task while undergoing functional magnetic resonance imaging (fMRI) at ultra-high resolution, which allowed us to examine layer-specific responses of the dlPFC to manipulations in WM load and motor response. We conducted univariate and multivariate analyses across all periods of the WM task: encoding, delay and retrieval. First, we observed that superficial layers activate stronger than deep layers to higher WM load during the delay period. This aligns with earlier work showing preferential superficial layer activation to WM manipulation and as such may indicate lamina-specific activation of the frontoparietal network to heightened task demands more generally. Second, we found that superficial layers show higher decoding of WM load differences than deep layers during the retrieval period. In this context, we could show that decoding of WM load in the superficial layer exhibited dynamic changes across the encoding, delay and retrieval period of the task, indicative of separate WM control processes that occur on the WM content. Last, we found that superficial and deep layers are both non-differentially involved in the motor response, contradicting earlier findings of a preferential deep layer activation in humans. Taken together, our results provide new insights into the functional laminar circuitry of the dlPFC during WM and provide further support for a dynamic account of dlPFC coding.

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Decoding of columnar-level organization across cortical depth using BOLD- and CBV-fMRI at 7 T

Multivariate pattern analysis (MVPA) methods are a versatile tool to retrieve information from neurophysiological data obtained with functional magnetic resonance imaging (fMRI) techniques. Since fMRI is based on measuring the hemodynamic response following neural activation, the spatial specificity of the fMRI signal is inherently limited by contributions of macrovascular compartments that drain the signal from the actual location of neural activation, making it challenging to image cortical structures at the spatial scale of cortical columns and layers. By relying on information from multiple voxels, MVPA has shown promising results in retrieving information encoded in fine-grained spatial patterns. We examined the spatial specificity of the signal exploited by MVPA. Over multiple sessions, we measured ocular dominance columns (ODCs) in human primary visual cortex (V1) with different acquisition techniques at 7 T. For measurements with blood oxygenation level dependent (BOLD) contrast, we included both gradient echo- (GE-BOLD) and spin echo-based (SE-BOLD) sequences. Furthermore, we acquired data using the vascular-space-occupancy (VASO) fMRI technique, which is sensitive to cerebral blood volume (CBV) changes. We used the data to decode eye-of-origin from signals across cortical layers. While ocularity information can be decoded with all imaging techniques, laminar profiles reveal that macrovascular contributions affect all acquisition methods, limiting their specificity across cortical depth. Therefore, although MVPA is a promising approach for investigating the mesoscopic circuitry of the human cerebral cortex, careful consideration of macrovascular contributions is needed that render the spatial specificity of the extracted signal.

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A more accurate account of the effect of k-space sampling and signal decay on the effective spatial resolution in functional MRI

The effects of k-space sampling and signal decay on the effective spatial resolution of MRI and functional MRI (fMRI) are commonly assessed by means of the magnitude point-spread function (PSF), defined as the absolute values (magnitudes) of the complex MR imaging PSF. It is commonly assumed that this magnitude PSF signifies blurring, which can be quantified by its full-width at half-maximum (FWHM). Here we show that the magnitude PSF fails to accurately represent the true effects of k-space sampling and signal decay.\n\nFirstly, a substantial part of the width of the magnitude PSF is due to MRI sampling per se. This part is independent of any signal decay and its effect depends on the spatial frequency composition of the imaged object. Therefore, it cannot always be expected to introduce blurring. Secondly, MRI reconstruction is typically followed by taking the absolute values (magnitude image) of the reconstructed complex image. This introduces a non-linear stage into the process of image formation. The complex imaging PSF does not fully describe this process, since it does not reflect the stage of taking the magnitude image. Its corresponding magnitude PSF fails to correctly describe this process, since convolving the original pattern with the magnitude PSF is different from the true process of taking the absolute following a convolution with the complex imaging PSF. Lastly, signal decay can have not only a blurring, but also a high-pass filtering effect. This cannot be reflected by the strictly positive width of the magnitude PSF.\n\nAs an alternative, we propose to first approximate the MRI process linearly. We then model the linear approximation by decomposing it into a signal decay-independent MR sampling part and an approximation of the signal decay effect. We approximate the latter as a convolution with a Gaussian PSF or, if the effect is that of high-pass filtering, as reversing the effect of a convolution with a Gaussian PSF. We show that for typical high-resolution fMRI at 7 Tesla, signal decay in Spin-Echo has a moderate blurring effect (FWHM = 0.89 voxels, corresponds to 0.44 mm for 0.5 mm wide voxels). In contrast, Gradient-Echo acts as a moderate high-pass filter that can be interpreted as reversing a Gaussian blurring with FWHM = 0.59 voxels (0.30 mm for 0.5 mm wide voxels). Our improved approximations and findings hold not only for Gradient-Echo and Spin-Echo fMRI but also for GRASE and VASO fMRI. Our findings support the correct planning, interpretation, and modeling of high-resolution fMRI.

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Spatial specificity of the functional MRI blood oxygenation response relative to neuronal activity

Previous attempts at characterizing the spatial specificity of the blood oxygenation level dependent functional MRI (BOLD fMRI) response by estimating its point-spread function (PSF) have conventionally relied on spatial representations of visual stimuli in area V1. Consequently, their estimates were confounded by the width and scatter of receptive fields of V1 neurons. Here, we circumvent these limits by instead using the inherent cortical spatial organization of ocular dominance columns (ODCs) to determine the PSF for both Gradient Echo (GE) and Spin Echo (SE) BOLD imaging at 7 Tesla. By applying Markov Chain Monte Carlo sampling on a probabilistic generative model of imaging ODCs, we quantified the PSFs that best predict the spatial structure and magnitude of differential ODCs responses. Prior distributions for the ODC model parameters were determined by analyzing published data of cytochrome oxidase patterns from post-mortem histology of human V1 and of neurophysio-logical ocular dominance indices. The most probable PSF full-widths at halfmaximum were 0.82 mm (SE) and 1.02 mm (GE). Our results provide a quantitative basis for the spatial specificity of BOLD fMRI at ultra-high fields, which can be used for planning and interpretation of high-resolution differential fMRI of fine-scale cortical organizations.

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