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Yaniv Assaf

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18 papers

1 author row

YNIMG Journal 2021 Journal Article

Brain volumetric changes in the general population following the COVID-19 outbreak and lockdown

Tom Salomon
Adi Cohen
Daniel Barazany
Gal Ben-Zvi
Rotem Botvinik-Nezer
Rani Gera
Shiran Oren
Dana Roll

The coronavirus disease 2019 (COVID-19) outbreak introduced unprecedented health-risks, as well as pressure on the economy, society, and psychological well-being due to the response to the outbreak. In a preregistered study, we hypothesized that the intense experience of the outbreak potentially induced stress-related brain modifications in the healthy population, not infected with the virus. We examined volumetric changes in 50 participants who underwent MRI scans before and after the COVID-19 outbreak and lockdown in Israel. Their scans were compared with those of 50 control participants who were scanned twice prior to the pandemic. Following COVID-19 outbreak and lockdown, the test group participants uniquely showed volumetric increases in bilateral amygdalae, putamen, and the anterior temporal cortices. Changes in the amygdalae diminished as time elapsed from lockdown relief, suggesting that the intense experience associated with the pandemic induced transient volumetric changes in brain regions commonly associated with stress and anxiety. The current work utilizes a rare opportunity for real-life natural experiment, showing evidence for brain plasticity following the COVID-19 global pandemic. These findings have broad implications, relevant both for the scientific community as well as the general public.

YNIMG Journal 2019 Journal Article

Imaging laminar structures in the gray matter with diffusion MRI

Yaniv Assaf

The cortical layers define the architecture of the gray matter and its neuroanatomical regions and are essential for brain function. Abnormalities in cortical layer development, growth patterns, organization, or size can affect brain physiology and cognition. Unfortunately, while large population studies are underway that will greatly increase our knowledge about these processes, current non-invasive techniques for characterizing the cortical layers remain inadequate. For decades, high-resolution T1 and T2 Weighted Magnetic Resonance Imaging (MRI) have been the method-of-choice for gray matter and layer characterization. In the past few years, however, diffusion MRI has shown increasing promise for its unique insights into the fine structure of the cortex. Several different methods, including surface analysis, connectivity exploration, and sub-voxel component modeling, are now capable of exploring the diffusion characteristics of the cortex. In this review, we will discuss current advances in the application of diffusion imaging for cortical characterization and its unique features, with a particular emphasis on its spatial resolution, arguably its greatest limitation. In addition, we will explore the relationship between the diffusion MRI signal and the cellular components of the cortex, as visualized by histology. While the obstacles facing the widespread application of cortical diffusion imaging remain daunting, the information it can reveal may prove invaluable. Within the next few years, we predict a surge in the application of this technique and a concomitant expansion of our knowledge of cortical layers.

YNIMG Journal 2018 Journal Article

Resolution considerations in imaging of the cortical layers

Shlomi Lifshits
Omri Tomer
Ittai Shamir
Daniel Barazany
Galia Tsarfaty
Saharon Rosset
Yaniv Assaf

The cortical layers are a finger print of brain development, function, connectivity and pathology. Obviously, the formation of the layers and their composition is essential to cognition and behavior. The layers were traditionally measured by histological means but recent studies utilizing MRI suggested that T1 relaxation imaging consist of enough contrast to separate the layers. Indeed extreme resolution, post mortem, studies demonstrated this phenomenon. Yet, one of the limiting factors of using T1 MRI to visualize the layers in neuroimaging research is partial volume effect. This happen when the image resolution is not high enough and two or more layers resides within the same voxel. In this paper we demonstrate that due to the physical small thickness of the layers it is highly unlikely that high resolution imaging could resolve the layers. By contrast, we suggest that low resolution multi T1 mapping conjugate with composition analysis could provide practical means for measuring the T1 layers. We suggest an acquisition platform that is clinically feasible and could quantify measures of the layers. The key feature of the suggested platform is that separation of the layers is better achieved in the T1 relaxation domain rather than in the spatial image domain.

YNIMG Journal 2017 Journal Article

The rapid development of structural plasticity through short water maze training: A DTI study

Shir Hofstetter
Yaniv Assaf

Diffusion MRI is sensitive to the microstructure of tissue and allows the study of structural plasticity over short time scales of only hours. The initial temporal and spatial progression of this process, however, has yet to be elucidated. With the aim of examining early temporal progression of structural plasticity, we subjected rats to short training periods on a task in the Morris water maze (MWM), a paradigm previously shown to induce rapid changes in diffusion tensor imaging (DTI) indices. Two groups of rats were each divided into subgroups that consecutively completed 1, 2 or 3 sets of short trials (up to 60s) in the MWM. Each set comprised 4 trials (1 from each quadrant of the WMW), with a specific time interval between sets. To assess the effect of the duration of the task on the evolving changes in DTI indices, we allowed a rest of 45min between sets in one group of rats and a 2-h rest in the other. All rats were scanned with a DTI protocol before and 45min after their last trial. We found that a few minutes of training in a new task sufficed to generate changes in diffusion indices. The earliest changes in DTI (measured after one set of trials) progressed with further training (measured after two sets), but within a few more minutes (after three sets) they reached a plateau. Lengthening the duration of the overall task by prolonging the time interval between sessions did not alter this pattern of change, suggesting that at least within this short time scale such changes are task-dependent, but not time dependent. Our results demonstrate the progression of structural neuroplasticity at different stages of exposure to a novel experience, and show that DTI can be used to trace, in vivo, the localization of structural plasticity induced by training.

YNIMG Journal 2016 Journal Article

T 1 relaxometry of crossing fibres in the human brain

Silvia De Santis
Yaniv Assaf
Ben Jeurissen
Derek K Jones
Alard Roebroeck

A comprehensive tract-based characterisation of white matter should include the ability to quantify myelin and axonal attributes irrespective of the complexity of fibre organisation within the voxel. Recently, a new experimental framework that combines inversion recovery and diffusion MRI, called inversion recovery diffusion tensor imaging (IR-DTI), was introduced and applied in an animal study. IR-DTI provides the ability to assign to each unique fibre population within a voxel a specific value of the longitudinal relaxation time, T 1, which is a proxy for myelin content. Here, we apply the IR-DTI approach to the human brain in vivo on 7 healthy subjects for the first time. We demonstrate that the approach is able to measure differential tract properties in crossing fibre areas, reflecting the different myelination of tracts. We also show that tract-specific T 1 has less inter-subject variability compared to conventional T 1 in areas of crossing fibres, suggesting increased specificity to distinct fibre populations. Finally we show in simulations that changes in myelination selectively affecting one fibre bundle in crossing fibre areas can potentially be detected earlier using IR-DTI.

YNIMG Journal 2014 Journal Article

Assessing white matter microstructure of the newborn with multi-shell diffusion MRI and biophysical compartment models

Nicolas Kunz
Hui Zhang
Lana Vasung
Kieran R. O'Brien
Yaniv Assaf
François Lazeyras
Daniel C. Alexander
Petra S. Hüppi

Brain white matter connections have become a focus of major interest with important maturational processes occurring in newborns. To study the complex microstructural developmental changes in-vivo, it is imperative that non-invasive neuroimaging approaches are developed for this age-group. Multi-b-value diffusion weighted imaging data were acquired in 13 newborns, and the biophysical compartment diffusion models CHARMED-light and NODDI, providing new microstructural parameters such as intra-neurite volume fraction (ν in ) and neurite orientation dispersion index (ODI), were developed for newborn data. Comparative analysis was performed and twenty ROIs in the white matter were investigated. Diffusion tensor imaging and both biophysical compartment models highlighted the compact and oriented structure of the corpus-callosum with the highest FA and ν in values and the smallest ODI values. We could clearly differentiate, using the FA, ν in and ODI, the posterior and anterior internal capsule representing similar cellular structure but with different maturation (i. e. partially myelinated and absence of myelin, respectively). Late maturing regions (external capsule and periventricular crossroads of pathways) had lower ν in values, but displayed significant differences in ODI. The compartmented models CHARMED-light and NODDI bring new indices corroborating the cellular architectures, with the lowest ν in, reflecting the late maturation of areas with thin non-myelinated fibers, and with highest ODI indicating the presence of fiber crossings and fanning. The application of biophysical compartment diffusion models adds new insights to the brain white matter development in vivo.

YNIMG Journal 2014 Journal Article

Separate parts of occipito-temporal white matter fibers are associated with recognition of faces and places

Ido Tavor
Maya Yablonski
Aviv Mezer
Shirley Rom
Yaniv Assaf
Galit Yovel

A central finding of functional MRI studies is the highly selective response of distinct brain areas in the occipital temporal cortex to faces and places. However, little is known about the association of white matter fibers with the processing of these object categories. In the current study we used DTI-based tractography to reconstruct two main fibers that connect the occipital lobe with the anterior temporal lobe (inferior longitudinal fasciculus-ILF) and with the frontal lobe (inferior fronto-occipital fasciculus-IFOF) in normal individuals. In addition to MRI scans subjects performed face, scene and body recognition tasks outside the scanner. Results show that recognition of faces and scenes were selectively associated with separate parts of the ILF. In particular, face recognition was highly associated with the fractional anisotropy (FA) of the anterior part of the ILF in the right hemisphere. In contrast, scene recognition was strongly correlated with the FA of the posterior and middle but not the anterior part of the ILF bilaterally. Our findings provide the first demonstration that faces and places are not only associated with distinct brain areas but also with separate parts of white matter fibers.

YNIMG Journal 2014 Journal Article

Why diffusion tensor MRI does well only some of the time: Variance and covariance of white matter tissue microstructure attributes in the living human brain

Silvia De Santis
Mark Drakesmith
Sonya Bells
Yaniv Assaf
Derek K. Jones

Fundamental to increasing our understanding of the role of white matter microstructure in normal/abnormal function in the living human is the development of MR-based metrics that provide increased specificity to distinct attributes of the white matter (e. g. , local fibre architecture, axon morphology, and myelin content). In recent years, different approaches have been developed to enhance this specificity, and the Tractometry framework was introduced to combine the resulting multi-parametric data for a comprehensive assessment of white matter properties. The present work exploits that framework to characterise the statistical properties, specifically the variance and covariance, of these advanced microstructural indices across the major white matter pathways, with the aim of giving clear indications on the preferred metric(s) given the specific research question. A cohort of healthy subjects was scanned with a protocol that combined multi-component relaxometry with conventional and advanced diffusion MRI acquisitions to build the first comprehensive MRI atlas of white matter microstructure. The mean and standard deviation of the different metrics were analysed in order to understand how they vary across different brain regions/individuals and the correlation between them. Characterising the fibre architectural complexity (in terms of number of fibre populations in a voxel) provides clear insights into correlation/lack of correlation between the different metrics and explains why DT-MRI is a good model for white matter only some of the time. The study also identifies the metrics that account for the largest inter-subject variability and reports the minimal sample size required to detect differences in means, showing that, on the other hand, conventional DT-MRI indices might still be the safest choice in many contexts.

YNIMG Journal 2013 Journal Article

Micro-structural assessment of short term plasticity dynamics

Ido Tavor
Shir Hofstetter
Yaniv Assaf

Diffusion MRI enables the non-invasive investigation of neuroplasticity in the human brain. A recent DTI study has shown that a short learning task of only 2h can yield changes in diffusion parameters. In the current study we aimed to discover whether a biophysical model of diffusion MRI, the CHARMED framework, which models hindered and restricted compartments within the tissue can constitute a more specific method than DTI to study structural plasticity. In addition we set to explore the time scale of the MRI learning-induced-changes. Subjects were scanned with both DTI and CHARMED before and after participating in the same car-racing task. Repetition of a shorter version of the task was done the following week. Results provide additional support to the former discovery of reduction in mean diffusivity after 2h training using DTI. In addition we show that the CHARMED framework provides a more sensitive method than DTI for discovering microstructural modification. An increase in the fraction of the restricted compartment (Fr) was found after participating in the tasks. Between tasks values of Fr returned to baseline, reflecting the dynamics of structural remodeling. By modeling different compartments in the tissue we suggest that interpretation of the biological processes that induced changes in diffusion is more straightforward, and allows improved detection of the progression of these changes.

YNIMG Journal 2013 Journal Article

The CONNECT project: Combining macro- and micro-structure

Yaniv Assaf
Daniel C. Alexander
Derek K. Jones
Albero Bizzi
Tim E.J. Behrens
Chris A. Clark
Yoram Cohen
Tim B. Dyrby

In recent years, diffusion MRI has become an extremely important tool for studying the morphology of living brain tissue, as it provides unique insights into both its macrostructure and microstructure. Recent applications of diffusion MRI aimed to characterize the structural connectome using tractography to infer connectivity between brain regions. In parallel to the development of tractography, additional diffusion MRI based frameworks (CHARMED, AxCaliber, ActiveAx) were developed enabling the extraction of a multitude of micro-structural parameters (axon diameter distribution, mean axonal diameter and axonal density). This unique insight into both tissue microstructure and connectivity has enormous potential value in understanding the structure and organization of the brain as well as providing unique insights to abnormalities that underpin disease states. The CONNECT (Consortium Of Neuroimagers for the Non-invasive Exploration of brain Connectivity and Tracts) project aimed to combine tractography and micro-structural measures of the living human brain in order to obtain a better estimate of the connectome, while also striving to extend validation of these measurements. This paper summarizes the project and describes the perspective of using micro-structural measures to study the connectome.

YNIMG Journal 2010 Journal Article

Structural correlates of memory performance with diffusion tensor imaging

Efrat Sasson
Glen M. Doniger
Ofer Pasternak
Yaniv Assaf

Aging is associated with a variety of structural and pathological brain changes. Memory, or the ability to store and retrieve information, declines significantly during aging. In order to characterize the brain micro-structural correlates of memory performance, 52 healthy subjects, age 25–82 years, completed a computerized non-verbal memory test and were scanned using magnetic resonance diffusion tensor imaging. Partial correlation was conducted between DTI parameters and memory performance (accuracy and reaction time (RT) for different learning stages) controlling for age. A similar correlation pattern was found for apparent diffusion coefficient (ADC), FA, and radial and axial diffusivities, but correlations between ADC and memory performance were the most informative and are therefore reported here. While ADC was correlated with accuracy mainly in temporal and frontal cortical regions, it was correlated with RT in temporal and frontal white matter pathways, including the inferior longitudinal fasciculus and uncinate fasciculus. The task was repeated four times, performance in the first repetition was correlated with ADC in frontal white matter and in the fourth repetition with ADC in temporal gray matter structures mainly the parahippocapus and in the middle temporal gyrus. The localization of the correlations of ADC with the different task parameters is in line with previous studies. Thus, inter-subject variability in memory performance and tissue morphology, as expressed by diffusion tensor magnetic resonance imaging, can be used to relate tissue microstructures with cognitive performance, and to provide information to corroborate other functional localization techniques.

YNIMG Journal 2009 Journal Article

Cluster analysis of resting-state fMRI time series

Aviv Mezer
Yossi Yovel
Ofer Pasternak
Tali Gorfine
Yaniv Assaf

Functional MRI (fMRI) has become one of the leading methods for brain mapping in neuroscience. Recent advances in fMRI analysis were used to define the default state of brain activity, functional connectivity and basal activity. Basal activity measured with fMRI raised tremendous interest among neuroscientists since synchronized brain activity pattern could be retrieved while the subject rests (resting state fMRI). During recent years, a few signal processing schemes have been suggested to analyze the resting state blood oxygenation level dependent (BOLD) signal from simple correlations to spectral decomposition. In most of these analysis schemes, the question asked was which brain areas “behave” in the time domain similarly to a pre-specified ROI. In this work we applied short time frequency analysis and clustering to study the spatial signal characteristics of resting state fMRI time series. Such analysis revealed that clusters of similar BOLD fluctuations are found in the cortex but also in the white matter and sub-cortical gray matter regions (thalamus). We found high similarities between the BOLD clusters and the neuro-anatomical appearance of brain regions. Additional analysis of the BOLD time series revealed a strong correlation between head movements and clustering quality. Experiments performed with T1-weighted time series also provided similar quality of clustering. These observations led us to the conclusion that non-functional contributions to the BOLD time series can also account for symmetric appearance of signal fluctuations. These contributions may include head motions, the underling microvasculature anatomy and cellular morphology.

YNIMG Journal 2009 Journal Article

Combinatorial fiber-tracking of the human brain

Shlomi Lifshits
Arie Tamir
Yaniv Assaf

This paper presents a novel fiber-tracking algorithm, termed combinatorial tracking, which uses stochastic process modeling and global optimization algorithm for tractography. Combinatorial tracking is a probabilistic tracking algorithm that transforms the brain's white matter into a grid in which each voxel has 26 weighted connections with adjacent voxels. We model the random walk on this graph using a Markov Chain model and suggest two approaches for fiber reconstruction. In the first approach, we find the most probable paths between two voxels with prior connectivity knowledge using a shortest path algorithm. In the second approach, the all-pairs mean first passage time (MFPT) matrix M (or hitting time as referred to in the Spectral Graph theory literature) is calculated analytically. We suggest that M can be interpreted as a global connectivity matrix and use it for fiber reconstruction. We also introduce a simulation framework that can be used to calculate specific elements of the matrix M, and show how it can be employed to select the target of a fiber in a high resolution diffusion tensor imaging (DTI) dataset. Because any source and any target voxel can be connected, combinatorial tracking permits true connectivity analysis, overcoming the limitations of conventional tracking, especially stopping criteria (e. g. low FA). We applied combinatorial tracking to a standard DTI dataset and demonstrated the reconstruction of the cortico-thalamic pathway, the pyramidal decussation, and the medial cerebellar peduncle fibers. While the DTI ellipsoid served as input for the algorithms, any diffusion imaging based orientation density function (ODF) can be used. This framework can potentially turn diffusion imaging tractography into a true connectivity measure.

YNIMG Journal 2007 Journal Article

Virtual definition of neuronal tissue by cluster analysis of multi-parametric imaging (virtual-dot-com imaging)

Yossi Yovel
Yaniv Assaf

Individual mapping of cerebral, morphological, functionally related structures using MRI was carried out using a new multi-contrast acquisition and analysis framework, called virtual-dot-com imaging. So far, conventional anatomical MRI has been able to provide gross segmentation of gray/white matter boundaries and a few sub-cortical structures. By combining a handful of imaging contrasts mechanisms (T1, T2, magnetization transfer, T2* and proton density), we were able to further segment sub-cortical tissue to its sub-nuclei arrangement, a segmentation that is difficult based on conventional, single-contrast MRI. Using an automatic four-step image and signal processing algorithm, we segmented the thalamus to at least 7 sub-nuclei with high similarity across subjects and high statistical significance within subjects (p <0. 0001). The identified sub-nuclei resembled the known anatomical arrangement of the thalamus given in various atlases. Each cluster was characterized by a unique MRI contrast fingerprint. With this procedure, the weighted proportions of the different cellular compartments could be estimated, a property available to date only by histological analysis. Each sub-nucleus could be characterized in terms of normalized MRI contrast and compared to other sub-nuclei. The different weights of the contrasts (T1/T2/T2*/PD/MT, etc.) for each sub-nuclei cluster might indicate the intra-cluster morphological arrangement of the tissue that it represents. The implications of this methodology are far-ranging, from non-invasive, in vivo, individual mapping of histologically distinct brain areas to automatic identification of pathological processes.

YNIMG Journal 2006 Journal Article

Characterization of displaced white matter by brain tumors using combined DTI and fMRI

Tom Schonberg
Pazit Pianka
Talma Hendler
Ofer Pasternak
Yaniv Assaf

In vivo white matter tractography by diffusion tensor imaging (DTI) has become a popular tool for investigation of white matter architecture in the normal brain. Despite some unresolved issues regarding the accuracy of DTI, recent studies applied DTI for delineating white matter organization in the vicinity of brain lesions and especially brain tumors. Apart from the intrinsic limitations of DTI, the tracking of fibers in the vicinity or within lesions is further complicated due to changes in diseased tissue such as elevated water content (edema), tissue compression and degeneration. These changes deform the architecture of the white matter and in some cases prevent definite selection of the seed region of interest (ROI) from which fiber tracking begins. We show here that for displaced fiber systems, the use of anatomical approach for seed ROI selection yields insufficient results. Alternatively, we propose to select the seed points based on functional MRI activations which constrain the subjective seed ROI selection. The results are demonstrated on two major fiber systems: the pyramidal tract and the superior longitudinal fasciculus that connect critical motor and language areas, respectively. The fMRI based seed ROI selection approach enabled a more comprehensive mapping of these fiber systems. Furthermore, this procedure enabled the characterization of displaced white matter using the eigenvalue decomposition of DTI. We show that along the compressed fiber system, the diffusivity parallel to the fiber increases, while that perpendicular to the fibers decreases, leading to an overall increase in the fractional anisotropy index reflecting the compression of the fiber bundle. We conclude that definition of the functional network of a subject with deformed white matter should be done carefully. With fMRI, one can more accurately define the seed ROI for DTI based tractography and to provide a more comprehensive, functionally related, white matter mapping, a very important tool used in pre-surgical mapping.

YNIMG Journal 2006 Journal Article

Sleep-anticipating effects of melatonin in the human brain

Tali Gorfine
Yaniv Assaf
Yonatan Goshen-Gottstein
Yaara Yeshurun
Nava Zisapel

Melatonin, the hormone produced nocturnally by the pineal gland, is an endogenous regulator of the sleep–wake cycle. The effects of melatonin on brain activities and their relation to induction of sleepiness were studied in a randomized, double-blind, placebo controlled functional magnetic resonance imaging (fMRI) study. Melatonin, but not placebo, reduced task-related activity in the rostro-medial aspect of the occipital cortex during a visual-search task and in the auditory cortex during a music task. These effects correlated with subjective measurements of fatigue. In addition, melatonin enhanced the activation in the left parahippocampus in an autobiographic memory task. Results demonstrate that melatonin modulates brain activity in a manner resembling actual sleep although subjects are fully awake. Furthermore, the fatigue inducing effect of melatonin on brain activity is essentially different from that of sleep deprivation thus revealing differences between fatigues related to the circadian sleep regulation as opposed to increased homeostatic sleep need. Our findings highlight the role of melatonin in priming sleep-associated brain activation patterns in anticipation of sleep.

YNIMG Journal 2005 Journal Article

Composite hindered and restricted model of diffusion (CHARMED) MR imaging of the human brain

Yaniv Assaf
Peter J. Basser

High b value diffusion-weighted images sampled at high angular resolution were analyzed using a composite hindered and restricted model of diffusion (CHARMED). Measurements and simulations of diffusion in white matter using CHARMED provide an unbiased estimate of fiber orientation with consistently smaller angular uncertainty than when calculated using a DTI model or with a dual tensor model for any given signal-to-noise level. Images based on the population fraction of the restricted compartment provide a new contrast mechanism that enhances white matter like DTI. Nevertheless, it is assumed that these images might be more sensitive than DTI to white matter disorders. We also provide here an experimental design and analysis framework to implement CHARMED MRI that is feasible on human clinical scanners.

NeurIPS Conference 2005 Conference Paper

Neuronal Fiber Delineation in Area of Edema from Diffusion Weighted MRI

Ofer Pasternak
Nathan Intrator
Nir Sochen
Yaniv Assaf

Diffusion Tensor Magnetic Resonance Imaging (DT-MRI) is a non inva- sive method for brain neuronal ﬁbers delineation. Here we show a mod- iﬁcation for DT-MRI that allows delineation of neuronal ﬁbers which are inﬁltrated by edema. We use the Muliple Tensor Variational (MTV) framework which replaces the diffusion model of DT-MRI with a mul- tiple component model and ﬁts it to the signal attenuation with a vari- ational regularization mechanism. In order to reduce free water con- tamination we estimate the free water compartment volume fraction in each voxel, remove it, and then calculate the anisotropy of the remaining compartment. The variational framework was applied on data collected with conventional clinical parameters, containing only six diffusion di- rections. By using the variational framework we were able to overcome the highly ill posed ﬁtting. The results show that we were able to ﬁnd ﬁbers that were not found by DT-MRI.