Functional Magnetic Resonance Imaging (fMRI)

Functional magnetic resonance imaging (fMRI) is a non invasive method of registering cerebral vascular responses resulting from changes in neural activity following activation. Blood oxygen level dependent (BOLD) fMRI is the most commonly used technique in this field and arterial spin labelling (ASL) is also employed. Functional MRI techniques are based on the close relationship between local neural activity, metabolism and changes in the cerebral blood flow (CBF) (Raichle and Mintun, 2006). A major advantage offered by these techniques is the possibility for non invasive longitudinal studies of brain plasticity (Dijkhuizen and Nicolay, 2003) and functional recovery processes in models of brain injury (Mueggler et al., 2001; Schroeter et al., 2009). The tight coupling of regional CBF and neuronal activity was remarked upon by Roy and Sherrington more than a century ago (Roy and Sherrington, 1890). In 1948, Kety and Schmidt first described a method for quantification of CBF in humans using N 2 O as a freely diffusible tracer (Kety and

and is currently maintained by him at the NIH (see Fig. 3). AFNI is a rich software package for processing and displaying fMRI data (Robert, 1996). AFNI is a power- ful package of C programs that is described for process- ing, analyzing, and visualization of three dimensional human brain functional magnetic resonance imaging (fMRI) results. The software can map the neural activa- tion onto higher resolution anatomical scans with differ- ent colors. Slices in each cardinal plane can be viewed simultaneously. Manual placement of markers on ana- tomical landmarks allows transformation of anatomical and functional scans into stereotaxic (Talairach-Tourn- oux) coordinate. Several statistical analysis methods for 3D functional datasets are available in this software. This software has an interface for AC-PC alignment and transformation to Talairach coordinates. It can map the fMRI activation pattern onto 2D and 3D structural (ana- tomical) images. Here, temporal data processing and visualization is utilized. There are different plug-ins for Fourier and wavelet filtering, real-time fMRI analysis, histogram generation, and etc.

However, 3D real time image registration (rotation) algo- rithm chose the axes ordering that resulted in the least intermediate image distortion (minimum net rotation) at proper flip angle about x, y or z-axes i.e. generalized and windowed sinc interpolation. It applied real-time functional MRI acquisition and activation analysis mod- ules within AFNI package. Functional MRI requires the rigid body transformations: small rotations, translations, zooms, rotating tensors and shears in 1–2 degrees or 1–2 voxel dimensions [39,41]. So, repeated linearization of weighted least squares penalty functions with respect to motion parameters accomplishes the registration of a base image to a target image. This method minimized the regional influences and intrinsic variability in function- ally active voxels in the brain. However, fMRI registration suffers from motion-related artifacts: interpolation errors, spin excitation in slice, spatial distortion by Gy and Nyquist ghosts. Intensity based intermodal registration AIR use variance of intensity ratios (VIR) cost function. Real-time image reconstruction was reported using Vision 3.5 software in communication with AFNI or TCP/IP sockets for intra- or intercomputer communications. These registration and rotation algorithms are available as AFNI registration and Visualization program [39,42]. Post-processing methods for fMRI images Several post-processing programs 'BrainVoyager', 'AFNI', 'LOFA', 'AIR' are available as a highly optimized and user- friendly software systems for the analysis and visualiza- tion of functional magnetic resonance imaging data [43- 46]. These combine surface-based and volume-based tools to study the structure and function of the brain to explore the secrets of the active brain by fast and highly optimized 2D and 3D image analysis and visualization routines, as shown in Figure 15. These are built-in-support for major standard and advanced data formats.

We report a technique for functional magnetic resonance imaging fMRl in an awake, co-operative, rhesus macaque Macaca mulaua in a conventional 1.5 T clinical MR scanner, thus accomplishi[r]

The implications of learned self-regulation of a brain area are two-fold. The first implication of NFB would be to complement conventional neuroimaging methods in making inferences about brain function. Conventional neuroimaging experiments measure brain activity as the dependent variable which changes due to sensory stimulation or performing a behavioural task, while NFB allows investigating the effects of changing the BOLD signal (independent variable) on behaviour (dependent variable). Therefore, while conventional neuroimaging studies provide correlational information, fMRI- NFB complements these methods by additionally allowing researchers to investigate questions of causality (12). The potential impact would be substantial as corresponding capabilities are currently limited to interventional techniques such as transcranial magnetic stimulation, deep brain stimulation, and focal lesions. The second implication of the causal link between brain activity and behaviour is the possibility to modulate behaviour by influencing brain activity. One may argue against the success of NFB by saying that it merely trains the regulation of blood flow instead of the neuronal activity, particularly because biofeedback itself has been employed for modulating blood pressure (13). The modulation of the behaviour as a result of self-regulation of the corresponding neural activity is a proof against this argument.

risk factors (preterm birth ⱕ 30 weeks’ GA), as well as morphologic brain lesions (IVH, WMD) diagnosed on serial routine ultrasound examinations. The fMRI/MRI session took place between 38 and 39 weeks’ PCA to allow for functional studies at a precisely defined matu- rational stage of the neonatal brain. None of the infants showed cystic WMD or asymmetric myelinization of the internal capsula on MRI predicting gross motor deficit (Table 1). In 2 patients, DWI revealed elevated ADC ratios in the bilateral periventricular WM. DEHSI has been related to oligodendrocyte or axonal abnormality throughout the WM 18 and to poor developmental out-

events (Rugg and Coles, 1995). On the one hand, there is a set o f components whose characteristics (amplitude, latency, and distribution) depend on the physical properties o f sensory stimuli, such as their modality and intensity. These are “exogenous components”. On the other hand, there is a second set o f components whose characteristics depend on the nature o f the subject’s interaction with the stimulus (i.e. processing or top-down effects). These are “endogenous components”. The event- related brain potentials that occur within the first 100 milliseconds o f stimulus presentation tend to be exogenous, whereas the event-related brain potentials that occur later tend to be endogenous. Irrespective o f the subject’s state, some stimuli tend to elicit late endogenous components more than others. For instance, in the temporal lobe, visual and auditory words are known to elicit both an exogenous component and a late endogenous component (N400) (Kutas and Hillyard, 1980). These late components are due to the complex nature o f verbal stimuli that involve functional integration among a number o f brain regions over time. It has been argued that the N400 is only elicited by linguistic stimuli and reflects high-level lexical processing (Van Petten and Kutas,

effects of discomfort glare and another group who had only minor problems. We will study the brain activity of both groups via functional magnetic resonance imaging (fMRI) whilst they are given various visual tasks to do with different levels of discomfort glare. From the fMRI scans we hope to find certain patterns of brain activity that are associated with the sensation of glare. This work is discussed in more detail in the following section on fMRI.

Today there is a similar issue with regard to the use of the fMRI (functional Magnetic Resonance Imaging) test which was originally developed to determine brain fu[r]

At the root of all our thoughts, emotions and behaviors is the communication between neurons within our brains. Brainwaves are produced by synchronized electrical pulses from masses of neurons communicating with each other. Brain activity can be recorded either by measuring the Blood flow in the brain or by measuring the neurons‟ electrical activity. To the first category belong approaches like functional magnetic resonance imaging (fMRI), which measures the concentration of oxygenated and deoxygenated hemoglobin in response to magnetic fields; near-infrared spectroscopy (NIRS), which measures the concentration of oxygenated and deoxygenated hemoglobin by means of the reflection of infrared light by the brain cortex through the skull; positron emission tomography (PET), which measures neuron metabolism through the injection of a radioactive substance in the subject.Magnetoencephalography (MEG) is a functional neuro imaging technique for mapping brain activity by recording magnetic fields produced by electrical currents occurring naturally in the brain, using very sensitive magnetometers.

Here we present a test-retest dataset of functional magnetic resonance imaging (fMRI) data acquired at rest. 22 participants were scanned during two sessions spaced one week apart. Each session includes two 1.5 mm isotropic whole-brain scans and one 0.75 mm isotropic scan of the prefrontal cortex, giving a total of six time-points. Additionally, the dataset includes measures of mood, sustained attention, blood pressure, respiration, pulse, and the content of self-generated thoughts (mind wandering). This data enables the investigation of sources of both intra- and inter-session variability not only limited to physiological changes, but also including alterations in cognitive and affective states, at high spatial resolution. The dataset is accompanied by a detailed experimental protocol and source code of all stimuli used.

The IZ can be evaluated by interictal non-invasive neuroimaging techniques such as scalp electroencephalography (EEG), magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) or combination of them as well as invasive intracranial electroencephalography (icEEG); the latter has high sensitivity and specificity (Blount et al., 2008, Vulliemoz et al., 2011) and is considered as the “gold standard” for defining the epileptogenic area (Blount et al., 2008). Despite its diagnostic benefits, it is considered invasive, sample-limited, costly and risky (hematomas, acute bleeding or infections; Blount et al., 2008, Zhang et al., 2014).

Purpose: This study assessed changes in functional dysmetria (FD) and in brain activation observable by functional magnetic resonance imaging (fMRI) during a leg flexion-extension motor task following brain stimulation with a single radioelectric asymmetric conveyer (REAC) pulse, according to the precisely defined neuropostural optimization (NPO) protocol.

Different kinds of neuroimaging methods can be principally classified as structural and functional biomarkers. The main structural imaging techniques are computational tomography (CT), magnetic resonance imaging (MRI) and functional neuroimaging techniques including: functional magnetic resonance imaging (fMRI), positron emission tomography (PET), and single photon emission computed tomography (SPECT) [30]. Neuroimaging biomarkers of mild cognitive impairment can be diagnosed in preclinical stages of AD. These techniques have been developed to provide evidence for Aβ deposition, tau aggregation and neurodegenerations at the early stages of the disease [20, 31, 32]. The two types of neuroimaging most commonly used as AD biomarkers are PET and MRI. There are two types of PET; a) amyloid tracers that determine pathological Aβ by employing radio ligands such as C-Pittsburgh compound B and florbetapir, which bind to fibrillar amyloid plaques [33, 34], b) Fluorodeoxyglucose (FDG) which evaluates brain metabolism. MRI is one of the non-invasive imaging

The executive control network (ECN) is critical for higher cognition and executive function (EF). Despite its importance, no scientific consensus has been reached on how and when it begins to function. In the present study, we assessed the development of the ECN in awake infants less than a year old by employing functional magnetic resonance imaging (fMRI) and naturalistic stimuli. First, we identified evocative movies that engaged infant attention. We then transferred them into adult imaging to test for which movie evoked the highest ECN response. Strong ECN responses were evoked while viewing Despicable Me, therefore we implemented this movie into infant imaging. We found that as early as 3- months of age, infants showed a similar response to that of adults. Overall, we demonstrated a technique that could potentially gauge EF in very young infants and developed a tool capable of imaging awake infants under natural conditions.

Transcranial direct current stimulation (tDCS) has been proposed for experimental and therapeutic modulation of regional brain function. Specifically, anodal tDCS of the dorsolateral prefrontal cortex (DLPFC) together with cathodal tDCS of the supraorbital region have been associated with improvement of cognition and mood, and have been suggested for the treatment of several neurological and psychiatric disorders. Although modeled mathematically, the distribution, direction, and extent of tDCS- mediated effects on brain physiology are not well understood. The current study investigates whether tDCS of the human prefron- tal cortex modulates resting-state network (RSN) connectivity measured by functional magnetic resonance imaging (fMRI). Thirteen healthy subjects underwent real and sham tDCS in random order on separate days. tDCS was applied for 20 min at 2 mA with the anode positioned over the left DLPFC and the cathode over the right supraorbital region. Patterns of resting-state brain connectivity were assessed before and after tDCS with 3 T fMRI, and changes were analyzed for relevant networks related to the stimulation– electrode localizations. At baseline, four RSNs were detected, corresponding to the default mode network (DMN), the left and right frontal-parietal networks (FPNs) and the self-referential network. After real tDCS and compared with sham tDCS, significant changes of regional brain connectivity were found for the DMN and the FPNs both close to the primary stimulation site and in connected brain regions. These findings show that prefrontal tDCS modulates resting-state functional connectivity in distinct functional networks of the human brain.

CCL: Clique complex filtration; CORT: Cortical regions of corticosterone; DBLP: Digital Bibliography & Library Project; dim: dimension. DSS: Dowker sink and source filtration; DTI: Diffusion tensor imaging; EEG: Electroencephalography; FMG: Functional metric graph filtration; fMRI: Functional magnetic resonance imaging; GDP: Gross domestic product; GVR: Generalizations of Vietoris-Rips filtration; IC: Intrinsic ˇCech filtration; IMDB: Internet movie database; kCL: k-clique filtration; MDS: Multidimensional scaling; MRI: Magnetic resonance imaging; OSN: Online social networks; PB: Persistence barcode; PCA: Principal component analysis; PD: Persistence diagram; PH: Persistent homology; POW: Power filtration; PPH: Persistent path homology; PPI: Protein-protein interaction networks; SLD: Single-linkage dendrograms; TMP: Temporal filtration; US: United States; VBCL: Vertex-Based clique filtration; VFB: Vertex function based filtration; VR: Vietoris-Rips filtration; WRCL: Weight rank clique filtration; WS: Weighted simplex filtration; ZSF: Zigzag simplicial filtration

A systematic search and retrieval of all literature was conducted and papers were identified. Devised search terms used were: (Infant/ OR Adolescent/ OR Minors/ OR Child/ OR Schools/ OR Schools, Nursery/ OR Infant, Newborn/ OR Puberty/ OR exp Pediatrics/ OR Infan* OR Newborn* OR New-born* OR Neonat* OR Neo-nat* OR Baby* OR Babies OR Postnat* OR Post-nat* OR Child* OR School* OR Kid OR Kids OR adoles* OR Teen* OR Girl* OR Boy* OR Minor* OR Underag* OR Under- ag* OR Puber* OR Prepubescent* OR Pre-pubescen* OR Youth* OR Kindergar* Or Kinder-gar* OR Prepuberty Or Pre-puberty OR P?ediatric* ) AND (exp Epilepsy/ OR Seizure/ OR Cognit* OR Neuropsych* OR Neuro-psych* OR Epilep* OR Seizure* ) AND (General Surgery/ OR Surg* OR Operat* ) AND (Magnetoencephalography/ OR MEG OR Magnetoencephalograh* ) OR (Magnetic Resonance Imaging/ OR MRI or fMRI OR Magnet* Resonance Imag* ) OR (Language/ OR Communication/ OR Speech/ OR Languag* OR Speech* OR Communi* ) OR (Movement/ OR Motor Activity/ OR Motor Skills/ OR movement* OR dexter* OR co-ordin* OR coordin* ) OR (exp Memory/ OR Memor* OR Recall* OR Remember* OR Recogni* OR Forget* ).

(http://www.fmrib.ox.ac.uk/fsl) using the standard steps (Jenkinson, Beckmann, et al. 2012; Woolrich, Jbabdi, et al. 2009; Smith, Jenkinson, et al. 2004). Both anatomical and resting state data were brain extracted using FSL’s brain extraction tool (BET) to remove the skull and non-brain structures (Smith, 2002). Various parameters were used for different subjects and extracted brains were visually inspected to ensure only non-brain structures were removed. Functional data was then preprocessed using the fMRI Expert Analysis Tool (FEAT) with: motion correction using FMRIB’s Linear Image Registration Tool (FLIRT) using the middle volume as a reference (Jenkinson, Bannister, et al. 2002), 5mm spatial smoothing, and low and high pass frequency filtering (between 0.01 – 0.1 Hz). Transformation matrices describing functional and anatomical data transformations to a standard space, the Montreal Neurological Institute (MNI) T1-weighted brain image (with 2mm isotropic voxel size), were found using FLIRT and applied to all preprocessed EPI images (Mazziotta, et al. 1995). Further denoising was performed using Multivariate Exploratory Linear Optimized Decomposition into Independent Components

An increasing number of studies have considered resting-state functional magnetic resonance imaging to understand the connectivity pattern shifts in the de- fault mode network observed after tDCS. Sankarasu- bramanian and colleagues [106] reported a Thalamocortical networks study focused on the pain matrix. They demonstrated that anodal M1 tDCS in- creased FC between ventroposterolateral area and sen- sorimotor cortices and also between motor dorsal and motor cortices. The findings suggest that M1 stimula- tion modulates FC of sensory networks. Lefebvre et al. [107] showed that a single session of dual-tDCS com- bined with motor skill learning increases FC between M1 and PMd of the damaged hemisphere in chronic stroke patients, supporting the hypothesis that changes in FC correlate with recovery. Chen and coau- thors [108] analyzed FC in individuals with stroke. The connectivity increased between ipsilesional motor cortex and contralesional premotor cortex after tDCS in motor rehabilitation, suggesting that the activation of interactions between motor and premotor cortex might be beneficial for stroke motor recovery. Sehm and colleagues [109] studied different setups of tDCS over the M1. The bilateral and unilateral M1 tDCS in- duced a decrease in interhemispheric FC during stimulation and the bilateral M1 tDCS induced an in- crease in intracortical FC within right M1 after the intervention. Depending on the tDCS montage, the con- nectivity analysis revealed different effects in M1 processing and can explain the induced changes in motor performance and learning from the perspective of the neural networks modulation. Rosso et al. [110] examined brain connectivity after cathodal tDCS applied to the right inferior frontal gyrus, before a picture-naming task performed in healthy individuals. They found greater FC between the right Bro- ca’s area and the supplementary motor area (SMA) and these findings were correlated to the improvement of learn- ing abilities, in the sense that subjects named pictures faster after cathodal relative to sham tDCS.