Longevity of a Brain-Computer Interface for Amyotrophic Lateral Sclerosis.

The durability of communication with the use of brain-computer interfaces in persons with progressive neurodegenerative disease has not been extensively examined. We report on 7 years of independent at-home use of an implanted brain-computer interface for communication by a person with advanced amyotrophic lateral sclerosis (ALS), the inception of which was reported in 2016. The frequency of at-home use increased over time to compensate for gradual loss of control of an eye-gaze-tracking device, followed by a progressive decrease in use starting 6 years after implantation. At-home use ended when control of the brain-computer interface became unreliable. No signs of technical malfunction were found. Instead, the amplitude of neural signals declined, and computed tomographic imaging revealed progressive atrophy, which suggested that ALS-related neurodegeneration ultimately rendered the brain-computer interface ineffective after years of successful use, although alternative explanations are plausible. (Funded by the National Institute on Deafness and Other Communication Disorders and others; ClinicalTrials.gov number, NCT02224469.).

Decoding Single and Paired Phonemes Using 7T Functional MRI.

Several studies have shown that mouth movements related to the pronunciation of individual phonemes are represented in the sensorimotor cortex. This would theoretically allow for brain computer interfaces that are capable of decoding continuous speech by training classifiers based on the activity in the sensorimotor cortex related to the production of individual phonemes. To address this, we investigated the decodability of trials with individual and paired phonemes (pronounced consecutively with one second interval) using activity in the sensorimotor cortex. Fifteen participants pronounced 3 different phonemes and 3 combinations of two of the same phonemes in a 7T functional MRI experiment. We confirmed that support vector machine (SVM) classification of single and paired phonemes was possible. Importantly, by combining classifiers trained on single phonemes, we were able to classify paired phonemes with an accuracy of 53% (33% chance level), demonstrating that activity of isolated phonemes is present and distinguishable in combined phonemes. A SVM searchlight analysis showed that the phoneme representations are widely distributed in the ventral sensorimotor cortex. These findings provide insights about the neural representations of single and paired phonemes. Furthermore, it supports the notion that speech BCI may be feasible based on machine learning algorithms trained on individual phonemes using intracranial electrode grids.

Distinct representation of ipsilateral hand movements in sensorimotor areas.

There is ample evidence that the contralateral sensorimotor areas play an important role in movement generation, with the primary motor cortex and the primary somatosensory cortex showing a detailed spatial organization of the representation of contralateral body parts. Interestingly, there are also indications for a role of the motor cortex in controlling the ipsilateral side of the body. However, the precise function of ipsilateral sensorimotor cortex in unilateral movement control is still unclear. Here, we show hand movement representation in the ipsilateral sensorimotor hand area, in which hand gestures can be distinguished from each other and from contralateral hand gestures. High-field functional magnetic resonance imaging (fMRI) data acquired during the execution of six left- and six right-hand gestures by healthy volunteers showed ipsilateral activation mainly in the anterior section of precentral gyrus and the posterior section of the postcentral gyrus. Despite the lower activation in ipsilateral areas closer to the central sulcus, activity patterns for the 12 hand gestures could be mutually distinguished in these areas. The existence of a unique representation of ipsilateral hand movements in the human sensorimotor cortex favours the notion of transcallosal integrative processes that support optimal coordination of hand movements.

Preservation of hand movement representation in the sensorimotor areas of amputees.

Denervation due to amputation is known to induce cortical reorganization in the sensorimotor cortex. Although there is evidence that reorganization does not lead to a complete loss of the representation of the phantom limb, it is unclear to what extent detailed, finger-specific activation patterns are preserved in motor cortex, an issue that is also relevant for development of brain-computer interface solutions for paralysed people. We applied machine learning to obtain a quantitative measure for the functional organization within the motor and adjacent cortices in amputees, using high resolution functional MRI and attempted hand gestures. Subjects with above-elbow arm amputation (n = 8) and non-amputated controls (n = 9) made several gestures with either their right or left hand. Amputees attempted to make gestures with their amputated hand. Images were acquired using 7 T functional MRI. The sensorimotor cortex was divided into four regions, and activity patterns were classified in individual subjects using a support vector machine. Classification scores were significantly above chance for all subjects and all hands, and were highly similar between amputees and controls in most regions. Decodability of phantom movements from primary motor cortex reached the levels of right hand movements in controls. Attempted movements were successfully decoded from primary sensory cortex in amputees, albeit lower than in controls but well above chance level despite absence of somatosensory feedback. There was no significant correlation between decodability and years since amputation, or age. The ability to decode attempted gestures demonstrates that the detailed hand representation is preserved in motor cortex and adjacent regions after denervation. This encourages targeting sensorimotor activity patterns for development of brain-computer interfaces.

Intracranial Recordings of Occipital Cortex Responses to Illusory Visual Events.

UNLABELLED: Ambiguous visual stimuli elicit different perceptual interpretations over time, creating the illusion that a constant stimulus is changing. We investigate whether such spontaneous changes in visual perception involve occipital brain regions specialized for processing visual information, despite the absence of concomitant changes in stimulation. Spontaneous perceptual changes observed while viewing a binocular rivalry stimulus or an ambiguous structure-from-motion stimulus were compared with stimulus-induced perceptual changes that occurred in response to an actual stimulus change. Intracranial recordings from human occipital cortex revealed that spontaneous and stimulus-induced perceptual changes were both associated with an early transient increase in high-frequency power that was more spatially confined than a later transient decrease in low-frequency power. We suggest that the observed high-frequency and low-frequency modulations relate to initiation and maintenance of a percept, respectively. Our results are compatible with the idea that spontaneous changes in perception originate from competitive interactions within visual neural networks. SIGNIFICANCE STATEMENT: Ambiguous visual stimuli elicit different perceptual interpretations over time, creating the illusion that a constant stimulus is changing. The literature on the neural correlates of conscious visual perception remains inconclusive regarding the extent to which such spontaneous changes in perception involve sensory brain regions. In an attempt to bridge the gap between existing animal and human studies, we recorded from intracranial electrodes placed on the human occipital lobe. We compared two different kinds of ambiguous stimuli, binocular rivalry and the phenomenon of ambiguous structure-from-motion, enabling generalization of our findings across different stimuli. Our results indicate that spontaneous and stimulus-induced changes in perception (i.e., "illusory" and "real" changes in the stimulus, respectively) may involve sensory regions to a similar extent.

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.

Task and task-free FMRI reproducibility comparison for motor network identification.

Test-retest reliability of individual functional magnetic resonance imaging (fMRI) results is of importance in clinical practice and longitudinal experiments. While several studies have investigated reliability of task-induced motor network activation, less is known about the reliability of the task-free motor network. Here, we investigate the reproducibility of task-free fMRI, and compare it to motor task activity. Sixteen healthy subjects participated in this study with a test-retest interval of seven weeks. The task-free motor network was assessed with a univariate, seed-voxel-based correlation analysis. Reproducibility was tested by means of intraclass correlation (ICC) values and ratio of overlap. Higher ICC values and a better overlap were found for task fMRI as compared to task-free fMRI. Furthermore, ratio of overlap improved for task fMRI at higher thresholds, while it decreased for task-free fMRI, suggesting a less focal spatial pattern of the motor network during resting state. However, for both techniques the most active voxels were located in the primary motor cortex. This indicates that, just like task fMRI, task-free fMRI can properly identify critical brain areas for motor task performance. Although both fMRI techniques are able to detect the motor network, resting-state fMRI is less reliable than task fMRI.

Give me a sign: decoding complex coordinated hand movements using high-field fMRI.

Decoding movements from the human cortex has been a topic of great interest for controlling an artificial limb in non-human primates and severely paralyzed people. Here we investigate feasibility of decoding gestures from the sensorimotor cortex in humans, using 7 T fMRI. Twelve healthy volunteers performed four hand gestures from the American Sign Language Alphabet. These gestures were performed in a rapid event related design used to establish the classifier and a slow event-related design, used to test the classifier. Single trial patterns were classified using a pattern-correlation classifier. The four hand gestures could be classified with an average accuracy of 63 % (range 35­95 %), which was significantly above chance (25 %). The hand region was, as expected, the most active region, and the optimal volume for classification was on average about 200 voxels, although this varied considerably across individuals. Importantly, classification accuracy correlated significantly with consistency of gesture execution. The results of our study demonstrate that decoding gestures from the hand region of the sensorimotor cortex using 7 T fMRI can reach very high accuracy, provided that gestures are executed in a consistent manner. Our results further indicate that the neuronal representation of hand gestures is robust and highly reproducible. Given that the most active foci were located in the hand region, and that 7 T fMRI has been shown to agree with electrocorticography, our results suggest that this confined region could serve to decode sign language gestures for intracranial brain­computer interfacing using surface grids.

Reliability of two clinically relevant fiber pathways reconstructed with constrained spherical deconvolution.

The single diffusion tensor model is inadequate for the reconstruction of fiber pathways in brain regions with multiple fiber orientations. To overcome this limitation, constrained spherical deconvolution has been proposed. A high reliability of constrained spherical deconvolution is, however, a pre-requisite for its use in clinical applications. Reliability of reconstructed fiber pathways can be assessed in terms of architectural (addressing their spatial configuration) and microstructural (addressing diffusion-derived measures along the fibers) reproducibility. We assess the reliability for two clinically relevant fiber pathways: the corticospinal tract and arcuate fasciculus. The fiber pathways were reconstructed using constrained spherical deconvolution in 11 healthy subjects who were scanned on three occasions. Coefficients of variations of diffusion-derived measures were used to assess the microstructural reproducibility. Image correlation and fiber overlap were used to assess the architectural reproducibility. The mean correlation between sessions was 72% for both the corticospinal tract and arcuate fasciculus. The mean overlap between sessions was 63% for the corticospinal tract and 58% for the arcuate fasciculus. Coefficients of variations of diffusion-derived measures showed very low variation (all measures <3.1%). These results are comparable with reliability results based on the diffusion tensor model, which is commonly used in clinical settings. The reliability results found here are, therefore, promising to further investigate the use of constrained spherical deconvolution in clinical practice.

Reliability of the corticospinal tract and arcuate fasciculus reconstructed with DTI-based tractography: implications for clinical practice.

OBJECTIVES: To assess the reliability of diffusion tensor imaging (DTI)-based fibre tractography (FT), which is a prerequisite for clinical applications of this technique. Here we assess the test-retest reproducibility of the architectural and microstructural features of two clinically relevant tracts reconstructed with DTI-FT. METHODS: The corticospinal tract (CST), arcuate fasciculus (AF) and its long segment (AFl) were reconstructed in 17 healthy subjects imaged twice using a deterministic approach. Coefficients of variation (CVs) of diffusion-derived tract values were used to assess the microstructural reproducibility. Spatial correlation and fibre overlap were used to assess the architectural reproducibility. RESULTS: Spatial correlation was 68 % for the CST and AF, and 69 % for the AFl. Overlap was 69 % for the CST, 61 % for the AF, and 59 % for the AFl. This was comparable to 2-mm tract shift variability. CVs of diffusion-derived tract values were at most 3.4 %. CONCLUSIONS: The results showed low architectural and microstructural variability for the reconstruction of the tracts. The architectural reproducibility results encourage the further investigation of the use of DTI-FT for neurosurgical planning. The high microstructural reproducibility results are promising for using DTI-FT in neurology to assess or predict functional recovery.

Using fMRI to localize target regions for implanted brain-computer interfaces in locked-in syndrome.

OBJECTIVE: Electrocorticography (ECoG)-based brain-computer interface (BCI) systems have the potential to improve quality of life of people with locked-in syndrome (LIS) by restoring their ability to communicate independently. Before implantation of such a system, it is important to localize ECoG electrode target regions. Here, we assessed the predictive value of functional magnetic resonance imaging (fMRI) for the localization of suitable target regions on the sensorimotor cortex for ECoG-based BCI in people with locked-in syndrome. METHODS: Three people with locked-in syndrome were implanted with a chronic, fully implantable ECoG-BCI system. We compared pre-surgical fMRI activity with post-implantation ECoG activity from areas known to be active and inactive during attempted hand movement (sensorimotor hand region and dorsolateral prefrontal cortex, respectively). RESULTS: Results showed a spatial match between fMRI activity and changes in ECoG low and high frequency band power (10 - 30 and 65 - 95 Hz, respectively) during attempted movement. Also, we found that fMRI can be used to select a sub-set of electrodes that show strong task-related signal changes that are therefore likely to generate adequate BCI control. CONCLUSIONS: Our findings indicate that fMRI is a useful non-invasive tool for the pre-surgical workup of BCI implant candidates. SIGNIFICANCE: If these results are confirmed in more BCI studies, fMRI might be used for more efficient surgical BCI procedures with focused cortical coverage and lower participant burden.

Investigating secondary white matter degeneration following ischemic stroke by modelling affected fiber tracts.

Secondary white matter degeneration is a common occurrence after ischemic stroke, as identified by Diffusion Tensor Imaging (DTI). However, despite recent advances, the time course of the process is not completely understood. The primary aim of this study was to assess secondary degeneration using an approach whereby we create a patient-specific model of damaged fibers based on the volumetric characteristics of lesions. We also examined the effects of secondary degeneration along the modelled streamlines at different distances from the primary infarction using DTI. Eleven patients who presented with upper limb motor deficits at the time of a first-ever ischemic stroke were included. They underwent scanning at weeks 6 and 29 post-stroke. The fractional anisotropy (FA), mean diffusivity (MD), primary eigenvalue (λ1), and transverse eigenvalue (λ23) were measured. Using regions of interest based on the simulation output, the differences between the modelled fibers and matched contralateral areas were analyzed. The longitudinal change between the two time points and across five distances from the primary lesion was also assessed using the ratios of diffusion quantities (rFA, rMD, rλ1, and rλ23) between the ipsilesional and contralesional hemisphere. At week 6 post-stroke, significantly decreased λ1 was found along the ipsilesional corticospinal tract (CST) with a trend towards lower FA, reduced MD and λ23. At week 29 post-stroke, significantly decreased FA was shown relative to the non-lesioned side, with a trend towards lower λ1, unchanged MD, and higher λ23. Along the ipsilesional tract, the rFA diminished, whereas the rMD, rλ1, and rλ23 significantly increased over time. No significant variations in the time progressive effect with distance were demonstrated. The findings support previously described mechanisms of secondary degeneration and suggest that it spreads along the entire length of a damaged tract. Future investigations using higher-order tractography techniques can further explain the intravoxel alterations caused by ischemic injury.

Implied motion activation in cortical area MT can be explained by visual low-level features.

To investigate form-related activity in motion-sensitive cortical areas, we recorded cell responses to animate implied motion in macaque middle temporal (MT) and medial superior temporal (MST) cortex and investigated these areas using fMRI in humans. In the single-cell studies, we compared responses with static images of human or monkey figures walking or running left or right with responses to the same human and monkey figures standing or sitting still. We also investigated whether the view of the animate figure (facing left or right) that elicited the highest response was correlated with the preferred direction for moving random dot patterns. First, figures were presented inside the cell's receptive field. Subsequently, figures were presented at the fovea while a dynamic noise pattern was presented at the cell's receptive field location. The results show that MT neurons did not discriminate between figures on the basis of the implied motion content. Instead, response preferences for implied motion correlated with preferences for low-level visual features such as orientation and size. No correlation was found between the preferred view of figures implying motion and the preferred direction for moving random dot patterns. Similar findings were obtained in a smaller population of MST cortical neurons. Testing human MT+ responses with fMRI further corroborated the notion that low-level stimulus features might explain implied motion activation in human MT+. Together, these results suggest that prior human imaging studies demonstrating animate implied motion processing in area MT+ can be best explained by sensitivity for low-level features rather than sensitivity for the motion implied by animate figures.

Changes in Intranetwork Functional Connectivity of Resting State Networks Between Sessions Under Anesthesia in Neurosurgical Patients.

BACKGROUND: In this study, we evaluated the changes in resting-state networks (RSNs) under anesthesia in neurosurgical patients. METHODS: RSNs were analyzed in 12 patients with pituitary adenoma presented by chiasma compression operated via standard transsphenoidal approach under propofol anesthesia before and after tumor resection. All the patients had suprasellar tumor extension with compression of the optic chiasma. We investigated second-level effects by contrasting dummy-encoded covariates representing the effects of the sessions (first vs. second) on RSNs. We corrected for multiple comparisons using a false discovery rate of 0.05 (2-sided). RESULTS: Connectivity between the right and left precentral gyri (motor network) decreased significantly from the first to the second session (P = 0.0002), as did the connectivity between the postcentral gyri (P = 0.009). The same was valid for connectivity between the visual cortices (P = 0.0002). The salience network showed a significant decrease in the connectivity of the anterior part of the cingulate gyrus and insular cortex (P = 0.0001). The default mode network showed a decrease in the connectivity between the posterior part of the cingulate gyrus, parietal, and frontal cortices (P = 0.0002). There was no significant correlation between the reduction in connectivity and dose or duration of anesthesia. CONCLUSIONS: Different RSNs could be identified under anesthesia and used for intraoperative brain mapping and remapping during tumor resection. However, RSNs showed a significant decrease in connectivity with the continuation of anesthesia.

Reduced brain activation during spoken language processing in children with developmental language disorder and children with 22q11.2 deletion syndrome.

Language difficulties of children with Developmental Language Disorder (DLD) have been associated with multiple underlying factors and are still poorly understood. One way of investigating the mechanisms of DLD language problems is to compare language-related brain activation patterns of children with DLD to those of a population with similar language difficulties and a uniform etiology. Children with 22q11.2 deletion syndrome (22q11DS) constitute such a population. Here, we conducted an fMRI study, in which children (6-10yo) with DLD and 22q11DS listened to speech alternated with reversed speech. We compared language laterality and language-related brain activation levels with those of typically developing (TD) children who performed the same task. The data revealed no significant differences between groups in language lateralization, but task-related activation levels were lower in children with language impairment than in TD children in several nodes of the language network. We conclude that language impairment in children with DLD and in children with 22q11DS may involve (partially) overlapping cortical areas.

Intraoperative Resting-State Functional Connectivity and Resting-State Networks in Patients with Intracerebral Lesions: Detectability and Variations Between Sessions.

OBJECTIVE: To evaluate the functional connectivity (FC) and resting-state networks (RSNs) in patients under anesthesia operated for resection of intracerebral lesions. METHODS: We performed intraoperative resting-state functional magnetic resonance imaging (irs-fMRI) in 24 patients under anesthesia before and after lesion resection. Correlation matrices were established for each session (a total 48 of sessions). We analyzed the changes in overall FC and in FC of the healthy and operated hemispheres between the first and second sessions. We tested the correlation between changes in FC and clinical outcomes and the duration, rate, and total dosage of anesthesia. We also performed a group analysis to detect topographic changes in RSNs in patients under anesthesia. A single-subject analysis was performed to detect clinically relevant RSNs in each patient. RESULTS: FC decreased significantly in the second session, as did interhemispheric connectivity. The decrease in the pathological hemisphere was significant and significantly greater than the decrease in the intrahemispheric connectivity of the healthy hemisphere. The change in FC was not correlated with clinical outcome or with the duration, rate, or dosage of anesthesia. Group analysis showed topographic changes in RSNs, especially in high-level networks such as default mode and salience networks. Identification of clinically relevant networks was also possible. CONCLUSIONS: FC and RSNs could be identified under anesthesia and used for extended brain mapping. Further studies are needed to optimize the depth of hypnosis to stabilize FC between sessions.

The Fluctuations of Blood Oxygen Level-Dependent Signals as a Method of Brain Tumor Characterization: A Preliminary Report.

OBJECTIVE: In this study we present the nature and characteristic of the fluctuation of blood oxygen level-dependent (BOLD) signals measured from brain tumors. METHODS: Supratentorial astrocytomas, which were neither operated nor previously managed with chemotherapy or radiotherapy, were segmented, and the time series of the BOLD signal fluctuations were extracted. The mean (across patients) power spectra were plotted for the different World Health Organization tumor grades. One-way analysis of variance (ANOVA) was performed to identify significant differences between the power spectra of different tumor grades. Results were considered significant at P < 0.05. RESULTS: A total of 58 patients were included in the study. This group of patients included 1 patient with grade I glioma; 15 with grade II; 12 with grade III; and 30 with grade IV. The power spectra of the tumor time series were individually inspected, and all tumors exhibited high peaks at the lower frequency signals, but these were more pronounced in high-grade tumors. ANOVA showed a significant difference in power spectra between groups (P = 0.000). Post hoc analysis with Bonferroni correction showed a significant difference between grade II and grade III (P = 0.012) and grade IV (P = 0.000). There was no significant power spectra difference between grade III and IV tumors (P = 1). CONCLUSIONS: The power spectra of BOLD signals from tumor tissue showed fluctuations in the low-frequency signals and were significantly correlated with tumor grade. These signals could have a misleading effect when analyzing resting state functional magnetic resonance imaging and could be also viewed as a potential method of tumor characterization.

The brain in a box: A toolbox for creating Cartesian geometric representations with isometric dimensions (Cgrids).

BACKGROUND: The folding of the human cortex complicates extraction of position information and recognition of patterns across the cortical surface. NEW METHOD: As straight lines correspond better to our intuitions in spatial orientation, we developed an approach for imposing Cartesian grids on portions of the cortical surface, which can then be represented in a rectangular matrix. These functions have been implemented in the Cgrid (Cartesian Geometric Representation with Isometric Dimensions) toolbox. Cgrids can be generated based on regions of interest, or combinations thereof, according to any one of the Freesurfer's annotation schemes. RESULTS: The toolbox was evaluated using the surface reconstructions of T1-weighted images of 30 subjects, and 17 different Cgrids that in combination covered nearly the entire surface area of the brain. The vast majority of Cgrids (90.4 %) could be generated without issues. COMPARISON WITH EXISTING METHOD(S): The toolbox facilitates spatial orientation and pattern recognition, in addition to allowing detailed comparison between the left and right hemisphere, and bringing existing volumetric tools to bear on surface-based data. The output of the toolbox is fully compatible with most existing fMRI/MRI analyses packages, and is immediately suitable as input for second level analysis. CONCLUSIONS: The toolbox has the potential for broad applicability, especially when ease of data handling and representation are critical factors. The toolbox can be downloaded from: https://github.com/mathijsraemaekers/Cgrid-toolbox.

Inter-Network Functional Connectivity Changes in Patients With Brain Tumors: A Resting-State Functional Magnetic Resonance Imaging Study.

OBJECTIVE: Measuring functional connectivity (FC) and resting state networks (RSNs) using resting state functional magnetic resonance imaging is a method of preoperative planning in patients with brain tumors. However, the baseline FC and RSNs are altered in patients with brain tumors. In this study, we examined changes in inter-network FC in patients with brain tumors. METHODS: We performed region of interest (ROI) analysis of FC in 34 patients with supratentorial gliomas and 14 healthy subjects. We performed bivariate correlation analyses at the level of each subject. Resulting correlations were Fischer Z-transformed. The used nodes included 132 ROIs from the automated anatomical labeling atlas in addition to 32 ROIs representing the different functional brain networks. We investigated second-level effects by contrasting dummy encoded covariates representing the effects of group membership on functional connectivity. The significant 2-sided P value with corrected false discovery rate was set to 0.05. We set the t contrast between the group of patients with brain tumors and the group of healthy subjects to detect the effects of tumors on inter-network connectivity. RESULTS: Overall, the inter-network FC was significantly higher in patients with brain tumors compared with healthy subjects. The anterior and posterior cerebellar networks, as well as the supratentorial network, showed significantly higher connectivity in patients with brain tumors than in healthy subjects. CONCLUSION: Although brain tumors affect the FC and RSNs, the current study showed higher baseline inter-network connectivity in patients with brain tumors, which could indicate an intrinsic neural compensatory mechanism.

A Novel 2D Standard Cartesian Representation for the Human Sensorimotor Cortex.

For some experimental approaches in brain imaging, the existing normalization techniques are not always sufficient. This may be the case if the anatomical shape of the region of interest varies substantially across subjects, or if one needs to compare the left and right hemisphere in the same subject. Here we propose a new standard representation, building upon existing normalization methods: Cgrid (Cartesian geometric representation with isometric dimensions). Cgrid is based on imposing a Cartesian grid over a cortical region of interest that is bounded by anatomical (atlas-based) landmarks. We applied this new representation to the sensorimotor cortex and we evaluated its performance by studying the similarity of activation patterns for hand, foot and tongue movements between subjects, and similarity between hemispheres within subjects. The Cgrid similarities were benchmarked against the similarities of activation patterns when transformed into standard MNI space using SPM, and to similarities from FreeSurfer's surface-based normalization. For both between-subject and between-hemisphere comparisons, similarity scores in Cgrid were high, similar to those from FreeSurfer normalization and higher than similarity scores from SPM's MNI normalization. This indicates that Cgrid allows for a straightforward way of representing and comparing sensorimotor activity patterns across subjects and between hemispheres of the same subjects.