Subthalamic nucleus deep brain stimulation for Parkinson's disease: evidence for effectiveness and limitations from 12 years' experience.

PubMed

Chan, Anne Y Y; Yeung, Jonas H M; Mok, Vincent C T; Ip, Vincent H L; Wong, Adrian; Kuo, S H; Chan, Danny T M; Zhu, X L; Wong, Edith; Lau, Claire K Y; Wong, Rosanna K M; Tang, Venus; Lau, Christine; Poon, W S

2014-12-01

To present the result and experience of subthalamic nucleus deep brain stimulation for Parkinson's disease. Case series. Prince of Wales Hospital, Hong Kong. A cohort of patients with Parkinson's disease received subthalamic nucleus deep brain stimulation from September 1998 to January 2010. Patient assessment data before and after the operation were collected prospectively. Forty-one patients (21 male and 20 female) with Parkinson's disease underwent bilateral subthalamic nucleus deep brain stimulation and were followed up for a median interval of 12 months. For the whole group, the mean improvements of Unified Parkinson's Disease Rating Scale (UPDRS) parts II and III were 32.5% and 31.5%, respectively (P<0.001). Throughout the years, a multidisciplinary team was gradually built. The deep brain stimulation protocol evolved and was substantiated by updated patient selection criteria and outcome assessment, integrated imaging and neurophysiological targeting, refinement of surgical technique as well as the accumulation of experience in deep brain stimulation programming. Most of the structural improvement occurred before mid-2005. Patients receiving the operation before June 2005 (19 cases) and after (22 cases) were compared; the improvements in UPDRS part III were 13.2% and 55.2%, respectively (P<0.001). There were three operative complications (one lead migration, one cerebral haematoma, and one infection) in the group operated on before 2005. There was no operative mortality. The functional state of Parkinson's disease patients with motor disabilities refractory to best medical treatment improved significantly after subthalamic nucleus deep brain stimulation. A dedicated multidisciplinary team building, refined protocol for patient selection and assessment, improvement of targeting methods, meticulous surgical technique, and experience in programming are the key factors contributing to the improved outcome.

Mapping the order and pattern of brain structural MRI changes using change-point analysis in premanifest Huntington's disease.

PubMed

Wu, Dan; Faria, Andreia V; Younes, Laurent; Mori, Susumu; Brown, Timothy; Johnson, Hans; Paulsen, Jane S; Ross, Christopher A; Miller, Michael I

2017-10-01

Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder that progressively affects motor, cognitive, and emotional functions. Structural MRI studies have demonstrated brain atrophy beginning many years prior to clinical onset ("premanifest" period), but the order and pattern of brain structural changes have not been fully characterized. In this study, we investigated brain regional volumes and diffusion tensor imaging (DTI) measurements in premanifest HD, and we aim to determine (1) the extent of MRI changes in a large number of structures across the brain by atlas-based analysis, and (2) the initiation points of structural MRI changes in these brain regions. We adopted a novel multivariate linear regression model to detect the inflection points at which the MRI changes begin (namely, "change-points"), with respect to the CAG-age product (CAP, an indicator of extent of exposure to the effects of CAG repeat expansion). We used approximately 300 T1-weighted and DTI data from premanifest HD and control subjects in the PREDICT-HD study, with atlas-based whole brain segmentation and change-point analysis. The results indicated a distinct topology of structural MRI changes: the change-points of the volumetric measurements suggested a central-to-peripheral pattern of atrophy from the striatum to the deep white matter; and the change points of DTI measurements indicated the earliest changes in mean diffusivity in the deep white matter and posterior white matter. While interpretation needs to be cautious given the cross-sectional nature of the data, these findings suggest a spatial and temporal pattern of spread of structural changes within the HD brain. Hum Brain Mapp 38:5035-5050, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

[Emotion and basal ganglia (II): what can we learn from subthalamic nucleus deep brain stimulation in Parkinson's disease?].

PubMed

Péron, J; Dondaine, T

2012-01-01

The subthalamic nucleus deep-brain stimulation Parkinson's disease patient model seems to represent a unique opportunity for studying the functional role of the basal ganglia and notably the subthalamic nucleus in human emotional processing. Indeed, in addition to constituting a therapeutic advance for severely disabled Parkinson's disease patients, deep brain stimulation is a technique, which selectively modulates the activity of focal structures targeted by surgery. There is growing evidence of a link between emotional impairments and deep-brain stimulation of the subthalamic nucleus. In this context, according to the definition of emotional processing exposed in the companion paper available in this issue, the aim of the present review will consist in providing a synopsis of the studies that investigated the emotional disturbances observed in subthalamic nucleus deep brain stimulation Parkinson's disease patients. This review leads to the conclusion that several emotional components would be disrupted after subthalamic nucleus deep brain stimulation in Parkinson's disease: subjective feeling, neurophysiological activation, and motor expression. Finally, after a description of the limitations of this study model, we discuss the functional role of the subthalamic nucleus (and the striato-thalamo-cortical circuits in which it is involved) in emotional processing. It seems reasonable to conclude that the striato-thalamo-cortical circuits are indeed involved in emotional processing and that the subthalamic nucleus plays a central in role the human emotional architecture. Copyright © 2012 Elsevier Masson SAS. All rights reserved.

Segmenting Brain Tissues from Chinese Visible Human Dataset by Deep-Learned Features with Stacked Autoencoder

PubMed Central

Zhao, Guangjun; Wang, Xuchu; Niu, Yanmin; Tan, Liwen; Zhang, Shao-Xiang

2016-01-01

Cryosection brain images in Chinese Visible Human (CVH) dataset contain rich anatomical structure information of tissues because of its high resolution (e.g., 0.167 mm per pixel). Fast and accurate segmentation of these images into white matter, gray matter, and cerebrospinal fluid plays a critical role in analyzing and measuring the anatomical structures of human brain. However, most existing automated segmentation methods are designed for computed tomography or magnetic resonance imaging data, and they may not be applicable for cryosection images due to the imaging difference. In this paper, we propose a supervised learning-based CVH brain tissues segmentation method that uses stacked autoencoder (SAE) to automatically learn the deep feature representations. Specifically, our model includes two successive parts where two three-layer SAEs take image patches as input to learn the complex anatomical feature representation, and then these features are sent to Softmax classifier for inferring the labels. Experimental results validated the effectiveness of our method and showed that it outperformed four other classical brain tissue detection strategies. Furthermore, we reconstructed three-dimensional surfaces of these tissues, which show their potential in exploring the high-resolution anatomical structures of human brain. PMID:27057543

Segmenting Brain Tissues from Chinese Visible Human Dataset by Deep-Learned Features with Stacked Autoencoder.

PubMed

Zhao, Guangjun; Wang, Xuchu; Niu, Yanmin; Tan, Liwen; Zhang, Shao-Xiang

2016-01-01

Cryosection brain images in Chinese Visible Human (CVH) dataset contain rich anatomical structure information of tissues because of its high resolution (e.g., 0.167 mm per pixel). Fast and accurate segmentation of these images into white matter, gray matter, and cerebrospinal fluid plays a critical role in analyzing and measuring the anatomical structures of human brain. However, most existing automated segmentation methods are designed for computed tomography or magnetic resonance imaging data, and they may not be applicable for cryosection images due to the imaging difference. In this paper, we propose a supervised learning-based CVH brain tissues segmentation method that uses stacked autoencoder (SAE) to automatically learn the deep feature representations. Specifically, our model includes two successive parts where two three-layer SAEs take image patches as input to learn the complex anatomical feature representation, and then these features are sent to Softmax classifier for inferring the labels. Experimental results validated the effectiveness of our method and showed that it outperformed four other classical brain tissue detection strategies. Furthermore, we reconstructed three-dimensional surfaces of these tissues, which show their potential in exploring the high-resolution anatomical structures of human brain.

Deep Brain Stimulation of the Memory Circuit: Improving Cognition in Alzheimer's Disease.

PubMed

Posporelis, Sotirios; David, Anthony S; Ashkan, Keyoumars; Shotbolt, Paul

2018-05-26

Deep brain stimulation (DBS) is an effective invasive treatment for a wide range of neurological and psychiatric disorders. Neurosurgically implanted electrodes deliver stimulation of pre-programmed amplitude, frequency, and pulse width within deep brain structures; those settings can be adjusted at a later stage according to individual needs for optimal response. This results in variable effects dependent on the targeted region. An established treatment for movement disorders, the effectiveness of DBS in dementia remains under investigation. Translational studies have uncovered a pro-cognitive effect mediated by changes on cellular as well as network level. Several groups have attempted to examine the benefits of DBS in Alzheimer's disease; differences in inclusion criteria and methodology make generalization of results difficult. This review aims to summarize all completed and ongoing human studies of DBS in Alzheimer's disease. The results are classified by targeted anatomical structure. Future directions, as well as economical and ethical arguments, are explored in the final section.

A computational framework for the detection of subcortical brain dysmaturation in neonatal MRI using 3D Convolutional Neural Networks.

PubMed

Ceschin, Rafael; Zahner, Alexandria; Reynolds, William; Gaesser, Jenna; Zuccoli, Giulio; Lo, Cecilia W; Gopalakrishnan, Vanathi; Panigrahy, Ashok

2018-05-21

Deep neural networks are increasingly being used in both supervised learning for classification tasks and unsupervised learning to derive complex patterns from the input data. However, the successful implementation of deep neural networks using neuroimaging datasets requires adequate sample size for training and well-defined signal intensity based structural differentiation. There is a lack of effective automated diagnostic tools for the reliable detection of brain dysmaturation in the neonatal period, related to small sample size and complex undifferentiated brain structures, despite both translational research and clinical importance. Volumetric information alone is insufficient for diagnosis. In this study, we developed a computational framework for the automated classification of brain dysmaturation from neonatal MRI, by combining a specific deep neural network implementation with neonatal structural brain segmentation as a method for both clinical pattern recognition and data-driven inference into the underlying structural morphology. We implemented three-dimensional convolution neural networks (3D-CNNs) to specifically classify dysplastic cerebelli, a subset of surface-based subcortical brain dysmaturation, in term infants born with congenital heart disease. We obtained a 0.985 ± 0. 0241-classification accuracy of subtle cerebellar dysplasia in CHD using 10-fold cross-validation. Furthermore, the hidden layer activations and class activation maps depicted regional vulnerability of the superior surface of the cerebellum, (composed of mostly the posterior lobe and the midline vermis), in regards to differentiating the dysplastic process from normal tissue. The posterior lobe and the midline vermis provide regional differentiation that is relevant to not only to the clinical diagnosis of cerebellar dysplasia, but also genetic mechanisms and neurodevelopmental outcome correlates. These findings not only contribute to the detection and classification of a subset of neonatal brain dysmaturation, but also provide insight to the pathogenesis of cerebellar dysplasia in CHD. In addition, this is one of the first examples of the application of deep learning to a neuroimaging dataset, in which the hidden layer activation revealed diagnostically and biologically relevant features about the clinical pathogenesis. The code developed for this project is open source, published under the BSD License, and designed to be generalizable to applications both within and beyond neonatal brain imaging. Copyright © 2018 Elsevier Inc. All rights reserved.

Postmortem diffusion MRI of the human brainstem and thalamus for deep brain stimulator electrode localization

PubMed Central

Calabrese, Evan; Hickey, Patrick; Hulette, Christine; Zhang, Jingxian; Parente, Beth; Lad, Shivanand P.; Johnson, G. Allan

2015-01-01

Deep brain stimulation (DBS) is an established surgical therapy for medically refractory tremor disorders including essential tremor (ET) and is currently under investigation for use in a variety of other neurologic and psychiatric disorders. There is growing evidence that the anti-tremor effects of DBS for ET are directly related to modulation of the dentatorubrothalamic tract (DRT), a white matter pathway that connects the cerebellum, red nucleus, and ventral intermediate nucleus of the thalamus. Emerging white matter targets for DBS, like the DRT, will require improved 3D reference maps of deep brain anatomy and structural connectivity for accurate electrode targeting. High-resolution diffusion MRI of postmortem brain specimens can provide detailed volumetric images of important deep brain nuclei and 3D reconstructions of white matter pathways with probabilistic tractography techniques. We present a high spatial and angular resolution diffusion MRI template of the postmortem human brainstem and thalamus with 3D reconstructions of the nuclei and white matter tracts involved in ET circuitry. We demonstrate accurate registration of these data to in vivo, clinical images from patients receiving DBS therapy, and correlate electrode proximity to tractography of the DRT with improvement of ET symptoms. PMID:26043869

Neurosurgery of the future: Deep brain stimulations and manipulations.

PubMed

Nicolaidis, Stylianos

2017-04-01

Important advances are afoot in the field of neurosurgery-particularly in the realms of deep brain stimulation (DBS), deep brain manipulation (DBM), and the newly introduced refinement "closed-loop" deep brain stimulation (CLDBS). Use of closed-loop technology will make both DBS and DBM more precise as procedures and will broaden their indications. CLDBS utilizes as feedback a variety of sources of electrophysiological and neurochemical afferent information about the function of the brain structures to be treated or studied. The efferent actions will be either electric, i.e. the classic excitatory or inhibitory ones, or micro-injection of such things as neural proteins and transmitters, neural grafts, implants of pluripotent stem cells or mesenchymal stem cells, and some variants of gene therapy. The pathologies to be treated, beside Parkinson's disease and movement disorders, include repair of neural tissues, neurodegenerative pathologies, psychiatric and behavioral dysfunctions, i.e. schizophrenia in its various guises, bipolar disorders, obesity, anorexia, drug addiction, and alcoholism. The possibility of using these new modalities to treat a number of cognitive dysfunctions is also under consideration. Because the DBS-CLDBS technology brings about a cross-fertilization between scientific investigation and surgical practice, it will also contribute to an enhanced understanding of brain function. Copyright © 2017. Published by Elsevier Inc.

Deep learning for neuroimaging: a validation study.

PubMed

Plis, Sergey M; Hjelm, Devon R; Salakhutdinov, Ruslan; Allen, Elena A; Bockholt, Henry J; Long, Jeffrey D; Johnson, Hans J; Paulsen, Jane S; Turner, Jessica A; Calhoun, Vince D

2014-01-01

Deep learning methods have recently made notable advances in the tasks of classification and representation learning. These tasks are important for brain imaging and neuroscience discovery, making the methods attractive for porting to a neuroimager's toolbox. Success of these methods is, in part, explained by the flexibility of deep learning models. However, this flexibility makes the process of porting to new areas a difficult parameter optimization problem. In this work we demonstrate our results (and feasible parameter ranges) in application of deep learning methods to structural and functional brain imaging data. These methods include deep belief networks and their building block the restricted Boltzmann machine. We also describe a novel constraint-based approach to visualizing high dimensional data. We use it to analyze the effect of parameter choices on data transformations. Our results show that deep learning methods are able to learn physiologically important representations and detect latent relations in neuroimaging data.

Resection of a Pediatric Thalamic Juvenile Pilocytic Astrocytoma with Whole Brain Tractography

PubMed Central

Weiner, Howard L

2017-01-01

The resection of deep-seated brain tumors has been associated with morbidity due to injury to critical neural structures during the approach. Recent technological advancements in navigation and stereotaxy, surgical planning, brain tractography and minimal-access brain ports present the opportunity to overcome such limitations. Here, we present the case of a pediatric patient with a left thalamic/midbrain juvenile pilocytic astrocytoma (JPA). The tumor displaced the corticospinal fibers posteriorly and resulted in hemiparesis. Using whole brain tractography to plan a corridor for the approach, neuronavigation, a tubular retractor and an exoscope for visualization, we obtained gross total resection of the tumor, while minimizing injury to white matter bundles, including the corticospinal fibers. We propose that surgical planning with whole brain tractography is essential for reducing morbidity while accessing deep-lying brain lesions via retractor tubes, by means of sparing critical fiber tracts. PMID:29234572

The habenula in neurosurgery for depression: A convergence of functional neuroanatomy, psychiatry and imaging.

PubMed

Skandalakis, Georgios P; Koutsarnakis, Christos; Kalyvas, Aristotelis V; Skandalakis, Panagiotis; Johnson, Elizabeth O; Stranjalis, George

2018-05-05

The habenula is a small, mostly underrated structure in the pineal region. Multidisciplinary findings demonstrate an underlying complex connectivity of the habenula with the rest of the brain, subserving its major role in normal behavior and the pathophysiology of depression. These findings suggest the potential application of "habenular psychosurgery" in the treatment of mental disorders. The remission of two patients with treatment-resistant major depression treated with deep brain stimulation of the habenula supported the hypothesis that the habenula is an effective target for deep brain stimulation and initiated a surge of basic science research. This review aims to assess the viability of the deep brain stimulation of the habenula as a treatment option for treatment resistant depression. PubMed and the Cochrane Library databases were searched with no chronological restrictions for the identification of relevant articles. The results of this review are presented in a narrative form describing the functional neuroanatomy of the human habenula, its implications in major depression, findings of electrode implantation of this region and findings of deep brain stimulation of the habenula for the treatment of depression. Data assessing the hypothesis are scarce. Nonetheless, findings highlight the major role of the habenula in normal, as well as in pathological brain function, particularly in depression disorders. Moreover, findings of studies utilizing electrode implantation in the region of the habenula underscore our growing realization that research in neuroscience and deep brain stimulation complement each other in a reciprocal relationship; they are as self-reliant, as much as they depend on each other. Copyright © 2018. Published by Elsevier B.V.

A Deep Learning Approach to Neuroanatomical Characterisation of Alzheimer's Disease.

PubMed

Ambastha, Abhinit Kumar; Leong, Tze-Yun

2017-01-01

Alzheimer's disease (AD) is a neurological degenerative disorder that leads to progressive mental deterioration. This work introduces a computational approach to improve our understanding of the progression of AD. We use ensemble learning methods and deep neural networks to identify salient structural correlations among brain regions that degenerate together in AD; this provides an understanding of how AD progresses in the brain. The proposed technique has a classification accuracy of 81.79% for AD against healthy subjects using a single modality imaging dataset.

External trial deep brain stimulation device for the application of desynchronizing stimulation techniques.

PubMed

Hauptmann, C; Roulet, J-C; Niederhauser, J J; Döll, W; Kirlangic, M E; Lysyansky, B; Krachkovskyi, V; Bhatti, M A; Barnikol, U B; Sasse, L; Bührle, C P; Speckmann, E-J; Götz, M; Sturm, V; Freund, H-J; Schnell, U; Tass, P A

2009-12-01

In the past decade deep brain stimulation (DBS)-the application of electrical stimulation to specific target structures via implanted depth electrodes-has become the standard treatment for medically refractory Parkinson's disease and essential tremor. These diseases are characterized by pathological synchronized neuronal activity in particular brain areas. We present an external trial DBS device capable of administering effectively desynchronizing stimulation techniques developed with methods from nonlinear dynamics and statistical physics according to a model-based approach. These techniques exploit either stochastic phase resetting principles or complex delayed-feedback mechanisms. We explain how these methods are implemented into a safe and user-friendly device.

[An automatic system for anatomophysiological correlation in three planes simultaneously during functional neurosurgery].

PubMed

Teijeiro, E J; Macías, R J; Morales, J M; Guerra, E; López, G; Alvarez, L M; Fernández, F; Maragoto, C; Seijo, F; Alvarez, E

The Neurosurgical Deep Recording System (NDRS) using a personal computer takes the place of complex electronic equipment for recording and processing deep cerebral electrical activity, as a guide in stereotaxic functional neurosurgery. It also permits increased possibilities of presenting information in direct graphic form with automatic management and sufficient flexibility to implement different analyses. This paper describes the possibilities of automatic simultaneous graphic representation in three almost orthogonal planes, available with the new 5.1 version of NDRS so as to facilitate the analysis of anatomophysiological correlation in the localization of deep structures of the brain during minimal access surgery. This new version can automatically show the spatial behaviour of signals registered throughout the path of the electrode inside the brain, superimposed simultaneously on sagittal, coronal and axial sections of an anatomical atlas of the brain, after adjusting the scale automatically according to the dimensions of the brain of each individual patient. This may also be shown in a tridimensional representation of the different planes themselves intercepting. The NDRS system has been successfully used in Spain and Cuba in over 300 functional neurosurgery operations. The new version further facilitates analysis of spatial anatomophysiological correlation for the localization of brain structures. This system has contributed to increase the precision and safety in selecting surgical targets in the control of Parkinson s disease and other disorders of movement.

Functional correlates of the therapeutic and adverse effects evoked by thalamic stimulation for essential tremor

PubMed Central

Gibson, William S.; Jo, Hang Joon; Testini, Paola; Cho, Shinho; Felmlee, Joel P.; Welker, Kirk M.; Klassen, Bryan T.; Min, Hoon-Ki

2016-01-01

Deep brain stimulation is an established neurosurgical therapy for movement disorders including essential tremor and Parkinson’s disease. While typically highly effective, deep brain stimulation can sometimes yield suboptimal therapeutic benefit and can cause adverse effects. In this study, we tested the hypothesis that intraoperative functional magnetic resonance imaging could be used to detect deep brain stimulation-evoked changes in functional and effective connectivity that would correlate with the therapeutic and adverse effects of stimulation. Ten patients receiving deep brain stimulation of the ventralis intermedius thalamic nucleus for essential tremor underwent functional magnetic resonance imaging during stimulation applied at a series of stimulation localizations, followed by evaluation of deep brain stimulation-evoked therapeutic and adverse effects. Correlations between the therapeutic effectiveness of deep brain stimulation (3 months postoperatively) and deep brain stimulation-evoked changes in functional and effective connectivity were assessed using region of interest-based correlation analysis and dynamic causal modelling, respectively. Further, we investigated whether brain regions might exist in which activation resulting from deep brain stimulation might correlate with the presence of paraesthesias, the most common deep brain stimulation-evoked adverse effect. Thalamic deep brain stimulation resulted in activation within established nodes of the tremor circuit: sensorimotor cortex, thalamus, contralateral cerebellar cortex and deep cerebellar nuclei (FDR q < 0.05). Stimulation-evoked activation in all these regions of interest, as well as activation within the supplementary motor area, brainstem, and inferior frontal gyrus, exhibited significant correlations with the long-term therapeutic effectiveness of deep brain stimulation (P < 0.05), with the strongest correlation (P < 0.001) observed within the contralateral cerebellum. Dynamic causal modelling revealed a correlation between therapeutic effectiveness and attenuated within-region inhibitory connectivity in cerebellum. Finally, specific subregions of sensorimotor cortex were identified in which deep brain stimulation-evoked activation correlated with the presence of unwanted paraesthesias. These results suggest that thalamic deep brain stimulation in tremor likely exerts its effects through modulation of both olivocerebellar and thalamocortical circuits. In addition, our findings indicate that deep brain stimulation-evoked functional activation maps obtained intraoperatively may contain predictive information pertaining to the therapeutic and adverse effects induced by deep brain stimulation. PMID:27329768

Mapping the "Depression Switch" During Intraoperative Testing of Subcallosal Cingulate Deep Brain Stimulation.

PubMed

Choi, Ki Sueng; Riva-Posse, Patricio; Gross, Robert E; Mayberg, Helen S

2015-11-01

The clinical utility of monitoring behavioral changes during intraoperative testing of subcallosal cingulate deep brain stimulation is unknown. To characterize the structural connectivity correlates of deep brain stimulation-evoked behavioral effects using probabilistic tractography in depression. Categorization of acute behavioral effects was conducted in 9 adults undergoing deep brain stimulation implantation surgery for chronic treatment-resistant depression in a randomized and blinded testing session at Emory University. Patients were studied from September 1, 2011, through June 30, 2013. Post hoc analyses of the structural tractography patterns mediating distinct categories of evoked behavioral effects were defined, including the best response overall. Data analyses were performed from May 1 through July 1, 2015. Categorization of stimulation-induced transient behavioral effects and delineation of the shared white matter tracts mediating response subtypes. Among the 9 patients, 72 active and 36 sham trials were recorded. The following stereotypical behavior patterns were identified: changes in interoceptive (noted changes in body state in 30 of 72 active and 4 of 36 sham trials) and in exteroceptive (shift in attention from patient to others in 9 of 72 active and 0 sham trials) awareness. The best response was a combination of exteroceptive and interoceptive changes at a single left contact for all 9 patients. Structural connectivity showed that the best response contacts had a pattern of connections to the bilateral ventromedial frontal cortex (via forceps minor and left uncinate fasciculus) and to the cingulate cortex (via left cingulum bundle), whereas behaviorally salient but nonbest contacts had only cingulate involvement. The involvement of the 3 white matter bundles during stimulation of the best contacts suggests a mechanism for the observed transient "depression switch." This analysis of transient behavior changes during intraoperative deep brain stimulation of the subcallosal cingulate and the subsequent identification of unique connectivity patterns may provide a biomarker of a rapid-onset depression switch to guide surgical implantation and to refine and optimize algorithms for the selection of contacts in long-term stimulation for treatment-resistant depression.

Postmortem diffusion MRI of the human brainstem and thalamus for deep brain stimulator electrode localization.

PubMed

Calabrese, Evan; Hickey, Patrick; Hulette, Christine; Zhang, Jingxian; Parente, Beth; Lad, Shivanand P; Johnson, G Allan

2015-08-01

Deep brain stimulation (DBS) is an established surgical therapy for medically refractory tremor disorders including essential tremor (ET) and is currently under investigation for use in a variety of other neurologic and psychiatric disorders. There is growing evidence that the anti-tremor effects of DBS for ET are directly related to modulation of the dentatorubrothalamic tract (DRT), a white matter pathway that connects the cerebellum, red nucleus, and ventral intermediate nucleus of the thalamus. Emerging white matter targets for DBS, like the DRT, will require improved three-dimensional (3D) reference maps of deep brain anatomy and structural connectivity for accurate electrode targeting. High-resolution diffusion MRI of postmortem brain specimens can provide detailed volumetric images of important deep brain nuclei and 3D reconstructions of white matter pathways with probabilistic tractography techniques. We present a high spatial and angular resolution diffusion MRI template of the postmortem human brainstem and thalamus with 3D reconstructions of the nuclei and white matter tracts involved in ET circuitry. We demonstrate registration of these data to in vivo, clinical images from patients receiving DBS therapy, and correlate electrode proximity to tractography of the DRT with improvement of ET symptoms. © 2015 Wiley Periodicals, Inc.

[The brain in stereotaxic coordinates (a textbook for colleges)].

PubMed

Budantsev, A Iu; Kisliuk, O S; Shul'govskiĭ, V V; Rykunov, D S; Iarkov, A V

1993-01-01

The present textbook is directed forward students of universities and medical colleges, young scientists and practicing doctors dealing with stereotaxic method. The Paxinos and Watson stereotaxic rat brain atlas (1982) is the basis of the textbook. The atlas has been transformed into computer educational program and seven laboratory works: insertion of the electrode into brain, microelectrophoresis, microinjection of drugs into brain, electrolytic destruction in the brain structures, local brain superfusion. The laboratory works are compiled so that they allow not only to study practical use of the stereotaxic method but to model simple problems involving stereotaxic surgery in the deep structures of brain. The textbook is intended for carrying by IBM PC/AT computers. The volume of the textbook is 1.7 Mbytes.

On the possibility of using multi-element phased arrays for shock-wave action on deep brain structures

NASA Astrophysics Data System (ADS)

Rosnitskiy, P. B.; Gavrilov, L. R.; Yuldashev, P. V.; Sapozhnikov, O. A.; Khokhlova, V. A.

2017-09-01

A noninvasive ultrasound surgery method that relies on using multi-element focused phased arrays is being successfully used to destroy tumors and perform neurosurgical operations in deep structures of the human brain. However, several drawbacks that limit the possibilities of the existing systems in their clinical use have been revealed: a large size of the hemispherical array, impossibility of its mechanical movement relative to the patient's head, limited volume of dynamic focusing around the center of curvature of the array, and side effect of overheating skull. Here we evaluate the possibility of using arrays of smaller size and aperture angles to achieve shock-wave formation at the focus for thermal and mechanical ablation (histotripsy) of brain tissue taking into account current intensity limitations at the array elements. The proposed approach has potential advantages to mitigate the existing limitations and expand the possibilities of transcranial ultrasound surgery.

The modulatory effect of adaptive deep brain stimulation on beta bursts in Parkinson's disease.

PubMed

Tinkhauser, Gerd; Pogosyan, Alek; Little, Simon; Beudel, Martijn; Herz, Damian M; Tan, Huiling; Brown, Peter

2017-04-01

Adaptive deep brain stimulation uses feedback about the state of neural circuits to control stimulation rather than delivering fixed stimulation all the time, as currently performed. In patients with Parkinson's disease, elevations in beta activity (13-35 Hz) in the subthalamic nucleus have been demonstrated to correlate with clinical impairment and have provided the basis for feedback control in trials of adaptive deep brain stimulation. These pilot studies have suggested that adaptive deep brain stimulation may potentially be more effective, efficient and selective than conventional deep brain stimulation, implying mechanistic differences between the two approaches. Here we test the hypothesis that such differences arise through differential effects on the temporal dynamics of beta activity. The latter is not constantly increased in Parkinson's disease, but comes in bursts of different durations and amplitudes. We demonstrate that the amplitude of beta activity in the subthalamic nucleus increases in proportion to burst duration, consistent with progressively increasing synchronization. Effective adaptive deep brain stimulation truncated long beta bursts shifting the distribution of burst duration away from long duration with large amplitude towards short duration, lower amplitude bursts. Critically, bursts with shorter duration are negatively and bursts with longer duration positively correlated with the motor impairment off stimulation. Conventional deep brain stimulation did not change the distribution of burst durations. Although both adaptive and conventional deep brain stimulation suppressed mean beta activity amplitude compared to the unstimulated state, this was achieved by a selective effect on burst duration during adaptive deep brain stimulation, whereas conventional deep brain stimulation globally suppressed beta activity. We posit that the relatively selective effect of adaptive deep brain stimulation provides a rationale for why this approach could be more efficacious than conventional continuous deep brain stimulation in the treatment of Parkinson's disease, and helps inform how adaptive deep brain stimulation might best be delivered. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved.

Novel fingerprinting method characterises the necessary and sufficient structural connectivity from deep brain stimulation electrodes for a successful outcome

NASA Astrophysics Data System (ADS)

Fernandes, Henrique M.; Van Hartevelt, Tim J.; Boccard, Sandra G. J.; Owen, Sarah L. F.; Cabral, Joana; Deco, Gustavo; Green, Alex L.; Fitzgerald, James J.; Aziz, Tipu Z.; Kringelbach, Morten L.

2015-01-01

Deep brain stimulation (DBS) is a remarkably effective clinical tool, used primarily for movement disorders. DBS relies on precise targeting of specific brain regions to rebalance the oscillatory behaviour of whole-brain neural networks. Traditionally, DBS targeting has been based upon animal models (such as MPTP for Parkinson’s disease) but has also been the result of serendipity during human lesional neurosurgery. There are, however, no good animal models of psychiatric disorders such as depression and schizophrenia, and progress in this area has been slow. In this paper, we use advanced tractography combined with whole-brain anatomical parcellation to provide a rational foundation for identifying the connectivity ‘fingerprint’ of existing, successful DBS targets. This knowledge can then be used pre-surgically and even potentially for the discovery of novel targets. First, using data from our recent case series of cingulate DBS for patients with treatment-resistant chronic pain, we demonstrate how to identify the structural ‘fingerprints’ of existing successful and unsuccessful DBS targets in terms of their connectivity to other brain regions, as defined by the whole-brain anatomical parcellation. Second, we use a number of different strategies to identify the successful fingerprints of structural connectivity across four patients with successful outcomes compared with two patients with unsuccessful outcomes. This fingerprinting method can potentially be used pre-surgically to account for a patient’s individual connectivity and identify the best DBS target. Ultimately, our novel fingerprinting method could be combined with advanced whole-brain computational modelling of the spontaneous dynamics arising from the structural changes in disease, to provide new insights and potentially new targets for hitherto impenetrable neuropsychiatric disorders.

The modulatory effect of adaptive deep brain stimulation on beta bursts in Parkinson’s disease

PubMed Central

Tinkhauser, Gerd; Pogosyan, Alek; Little, Simon; Beudel, Martijn; Herz, Damian M.; Tan, Huiling

2017-01-01

Abstract Adaptive deep brain stimulation uses feedback about the state of neural circuits to control stimulation rather than delivering fixed stimulation all the time, as currently performed. In patients with Parkinson’s disease, elevations in beta activity (13–35 Hz) in the subthalamic nucleus have been demonstrated to correlate with clinical impairment and have provided the basis for feedback control in trials of adaptive deep brain stimulation. These pilot studies have suggested that adaptive deep brain stimulation may potentially be more effective, efficient and selective than conventional deep brain stimulation, implying mechanistic differences between the two approaches. Here we test the hypothesis that such differences arise through differential effects on the temporal dynamics of beta activity. The latter is not constantly increased in Parkinson’s disease, but comes in bursts of different durations and amplitudes. We demonstrate that the amplitude of beta activity in the subthalamic nucleus increases in proportion to burst duration, consistent with progressively increasing synchronization. Effective adaptive deep brain stimulation truncated long beta bursts shifting the distribution of burst duration away from long duration with large amplitude towards short duration, lower amplitude bursts. Critically, bursts with shorter duration are negatively and bursts with longer duration positively correlated with the motor impairment off stimulation. Conventional deep brain stimulation did not change the distribution of burst durations. Although both adaptive and conventional deep brain stimulation suppressed mean beta activity amplitude compared to the unstimulated state, this was achieved by a selective effect on burst duration during adaptive deep brain stimulation, whereas conventional deep brain stimulation globally suppressed beta activity. We posit that the relatively selective effect of adaptive deep brain stimulation provides a rationale for why this approach could be more efficacious than conventional continuous deep brain stimulation in the treatment of Parkinson’s disease, and helps inform how adaptive deep brain stimulation might best be delivered. PMID:28334851

Toward defining deep brain stimulation targets in MNI space: A subcortical atlas based on multimodal MRI, histology and structural connectivity.

PubMed

Ewert, Siobhan; Plettig, Philip; Li, Ningfei; Chakravarty, M Mallar; Collins, D Louis; Herrington, Todd M; Kühn, Andrea A; Horn, Andreas

2018-04-15

Three-dimensional atlases of subcortical brain structures are valuable tools to reference anatomy in neuroscience and neurology. For instance, they can be used to study the position and shape of the three most common deep brain stimulation (DBS) targets, the subthalamic nucleus (STN), internal part of the pallidum (GPi) and ventral intermediate nucleus of the thalamus (VIM) in spatial relationship to DBS electrodes. Here, we present a composite atlas based on manual segmentations of a multimodal high resolution brain template, histology and structural connectivity. In a first step, four key structures were defined on the template itself using a combination of multispectral image analysis and manual segmentation. Second, these structures were used as anchor points to coregister a detailed histological atlas into standard space. Results show that this approach significantly improved coregistration accuracy over previously published methods. Finally, a sub-segmentation of STN and GPi into functional zones was achieved based on structural connectivity. The result is a composite atlas that defines key nuclei on the template itself, fills the gaps between them using histology and further subdivides them using structural connectivity. We show that the atlas can be used to segment DBS targets in single subjects, yielding more accurate results compared to priorly published atlases. The atlas will be made publicly available and constitutes a resource to study DBS electrode localizations in combination with modern neuroimaging methods. Copyright © 2017 Elsevier Inc. All rights reserved.

Adaptive optical microscope for brain imaging in vivo

NASA Astrophysics Data System (ADS)

Wang, Kai

2017-04-01

The optical heterogeneity of biological tissue imposes a major limitation to acquire detailed structural and functional information deep in the biological specimens using conventional microscopes. To restore optimal imaging performance, we developed an adaptive optical microscope based on direct wavefront sensing technique. This microscope can reliably measure and correct biological samples induced aberration. We demonstrated its performance and application in structural and functional brain imaging in various animal models, including fruit fly, zebrafish and mouse.

Pathways of translation: deep brain stimulation.

PubMed

Gionfriddo, Michael R; Greenberg, Alexandra J; Wahegaonkar, Abhijeet L; Lee, Kendall H

2013-12-01

Electrical stimulation of the brain has a 2000 year history. Deep brain stimulation (DBS), one form of neurostimulation, is a functional neurosurgical approach in which a high-frequency electrical current stimulates targeted brain structures for therapeutic benefit. It is an effective treatment for certain neuropathologic movement disorders and an emerging therapy for psychiatric conditions and epilepsy. Its translational journey did not follow the typical bench-to-bedside path, but rather reversed the process. The shift from ancient and medieval folkloric remedy to accepted medical practice began with independent discoveries about electricity during the 19th century and was fostered by technological advances of the 20th. In this paper, we review that journey and discuss how the quest to expand its applications and improve outcomes is taking DBS from the bedside back to the bench. © 2013 Wiley Periodicals, Inc.

Time-lapse imaging of disease progression in deep brain areas using fluorescence microendoscopy

PubMed Central

Barretto, Robert P. J.; Ko, Tony H.; Jung, Juergen C.; Wang, Tammy J.; Capps, George; Waters, Allison C.; Ziv, Yaniv; Attardo, Alessio; Recht, Lawrence; Schnitzer, Mark J.

2013-01-01

The combination of intravital microscopy and animal models of disease has propelled studies of disease mechanisms and treatments. However, many disorders afflict tissues inaccessible to light microscopy in live subjects. Here we introduce cellular-level time-lapse imaging deep within the live mammalian brain by one- and two-photon fluorescence microendoscopy over multiple weeks. Bilateral imaging sites allowed longitudinal comparisons within individual subjects, including of normal and diseased tissues. Using this approach we tracked CA1 hippocampal pyramidal neuron dendrites in adult mice, revealing these dendrites' extreme stability (>8,000 day mean lifetime) and rare examples of their structural alterations. To illustrate disease studies, we tracked deep lying gliomas by observing tumor growth, visualizing three-dimensional vasculature structure, and determining microcirculatory speeds. Average erythrocyte speeds in gliomas declined markedly as the disease advanced, notwithstanding significant increases in capillary diameters. Time-lapse microendoscopy will be applicable to studies of numerous disorders, including neurovascular, neurological, cancerous, and trauma-induced conditions. PMID:21240263

Corpus callosum segmentation using deep neural networks with prior information from multi-atlas images

NASA Astrophysics Data System (ADS)

Park, Gilsoon; Hong, Jinwoo; Lee, Jong-Min

2018-03-01

In human brain, Corpus Callosum (CC) is the largest white matter structure, connecting between right and left hemispheres. Structural features such as shape and size of CC in midsagittal plane are of great significance for analyzing various neurological diseases, for example Alzheimer's disease, autism and epilepsy. For quantitative and qualitative studies of CC in brain MR images, robust segmentation of CC is important. In this paper, we present a novel method for CC segmentation. Our approach is based on deep neural networks and the prior information generated from multi-atlas images. Deep neural networks have recently shown good performance in various image processing field. Convolutional neural networks (CNN) have shown outstanding performance for classification and segmentation in medical image fields. We used convolutional neural networks for CC segmentation. Multi-atlas based segmentation model have been widely used in medical image segmentation because atlas has powerful information about the target structure we want to segment, consisting of MR images and corresponding manual segmentation of the target structure. We combined the prior information, such as location and intensity distribution of target structure (i.e. CC), made from multi-atlas images in CNN training process for more improving training. The CNN with prior information showed better segmentation performance than without.

The Chomsky—Place correspondence 1993–1994

PubMed Central

Chomsky, Noam; Place, Ullin T.

2000-01-01

Edited correspondence between Ullin T. Place and Noam Chomsky, which occurred in 1993–1994, is presented. The principal topics are (a) deep versus surface structure; (b) computer modeling of the brain; (c) the evolutionary origins of language; (d) behaviorism; and (e) a dispositional account of language. This correspondence includes Chomsky's denial that he ever characterized deep structure as innate; Chomsky's critique of computer modeling (both traditional and connectionist) of the brain; Place's critique of Chomsky's alleged failure to provide an adequate account of the evolutionary origins of language, and Chomsky's response that such accounts are “pop-Darwinian fairy tales”; and Place's arguments for, and Chomsky's against, the relevance of behaviorism to linguistic theory, especially the relevance of a behavioral approach to language that is buttressed by a dispositional account of sentence construction. PMID:22477211

The Chomsky-Place correspondence 1993-1994.

PubMed

Chomsky, N; Place, U T

2000-01-01

Edited correspondence between Ullin T. Place and Noam Chomsky, which occurred in 1993-1994, is presented. The principal topics are (a) deep versus surface structure; (b) computer modeling of the brain; (c) the evolutionary origins of language; (d) behaviorism; and (e) a dispositional account of language. This correspondence includes Chomsky's denial that he ever characterized deep structure as innate; Chomsky's critique of computer modeling (both traditional and connectionist) of the brain; Place's critique of Chomsky's alleged failure to provide an adequate account of the evolutionary origins of language, and Chomsky's response that such accounts are "pop-Darwinian fairy tales"; and Place's arguments for, and Chomsky's against, the relevance of behaviorism to linguistic theory, especially the relevance of a behavioral approach to language that is buttressed by a dispositional account of sentence construction.

Automated sub-cortical brain structure segmentation combining spatial and deep convolutional features.

PubMed

Kushibar, Kaisar; Valverde, Sergi; González-Villà, Sandra; Bernal, Jose; Cabezas, Mariano; Oliver, Arnau; Lladó, Xavier

2018-06-15

Sub-cortical brain structure segmentation in Magnetic Resonance Images (MRI) has attracted the interest of the research community for a long time as morphological changes in these structures are related to different neurodegenerative disorders. However, manual segmentation of these structures can be tedious and prone to variability, highlighting the need for robust automated segmentation methods. In this paper, we present a novel convolutional neural network based approach for accurate segmentation of the sub-cortical brain structures that combines both convolutional and prior spatial features for improving the segmentation accuracy. In order to increase the accuracy of the automated segmentation, we propose to train the network using a restricted sample selection to force the network to learn the most difficult parts of the structures. We evaluate the accuracy of the proposed method on the public MICCAI 2012 challenge and IBSR 18 datasets, comparing it with different traditional and deep learning state-of-the-art methods. On the MICCAI 2012 dataset, our method shows an excellent performance comparable to the best participant strategy on the challenge, while performing significantly better than state-of-the-art techniques such as FreeSurfer and FIRST. On the IBSR 18 dataset, our method also exhibits a significant increase in the performance with respect to not only FreeSurfer and FIRST, but also comparable or better results than other recent deep learning approaches. Moreover, our experiments show that both the addition of the spatial priors and the restricted sampling strategy have a significant effect on the accuracy of the proposed method. In order to encourage the reproducibility and the use of the proposed method, a public version of our approach is available to download for the neuroimaging community. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Magnetization Transfer Ratio Relates to Cognitive Impairment in Normal Elderly

PubMed Central

Seiler, Stephan; Pirpamer, Lukas; Hofer, Edith; Duering, Marco; Jouvent, Eric; Fazekas, Franz; Mangin, Jean-Francois; Chabriat, Hugues; Dichgans, Martin; Ropele, Stefan; Schmidt, Reinhold

2014-01-01

Magnetization transfer imaging (MTI) can detect microstructural brain tissue changes and may be helpful in determining age-related cerebral damage. We investigated the association between the magnetization transfer ratio (MTR) in gray and white matter (WM) and cognitive functioning in 355 participants of the Austrian stroke prevention family study (ASPS-Fam) aged 38–86 years. MTR maps were generated for the neocortex, deep gray matter structures, WM hyperintensities, and normal appearing WM (NAWM). Adjusted mixed models determined whole brain and lobar cortical MTR to be directly and significantly related to performance on tests of memory, executive function, and motor skills. There existed an almost linear dose-effect relationship. MTR of deep gray matter structures and NAWM correlated to executive functioning. All associations were independent of demographics, vascular risk factors, focal brain lesions, and cortex volume. Further research is needed to understand the basis of this association at the tissue level, and to determine the role of MTR in predicting cognitive decline and dementia. PMID:25309438

Landmark-based deep multi-instance learning for brain disease diagnosis.

PubMed

Liu, Mingxia; Zhang, Jun; Adeli, Ehsan; Shen, Dinggang

2018-01-01

In conventional Magnetic Resonance (MR) image based methods, two stages are often involved to capture brain structural information for disease diagnosis, i.e., 1) manually partitioning each MR image into a number of regions-of-interest (ROIs), and 2) extracting pre-defined features from each ROI for diagnosis with a certain classifier. However, these pre-defined features often limit the performance of the diagnosis, due to challenges in 1) defining the ROIs and 2) extracting effective disease-related features. In this paper, we propose a landmark-based deep multi-instance learning (LDMIL) framework for brain disease diagnosis. Specifically, we first adopt a data-driven learning approach to discover disease-related anatomical landmarks in the brain MR images, along with their nearby image patches. Then, our LDMIL framework learns an end-to-end MR image classifier for capturing both the local structural information conveyed by image patches located by landmarks and the global structural information derived from all detected landmarks. We have evaluated our proposed framework on 1526 subjects from three public datasets (i.e., ADNI-1, ADNI-2, and MIRIAD), and the experimental results show that our framework can achieve superior performance over state-of-the-art approaches. Copyright © 2017 Elsevier B.V. All rights reserved.

High-throughput isotropic mapping of whole mouse brain using multi-view light-sheet microscopy

NASA Astrophysics Data System (ADS)

Nie, Jun; Li, Yusha; Zhao, Fang; Ping, Junyu; Liu, Sa; Yu, Tingting; Zhu, Dan; Fei, Peng

2018-02-01

Light-sheet fluorescence microscopy (LSFM) uses an additional laser-sheet to illuminate selective planes of the sample, thereby enabling three-dimensional imaging at high spatial-temporal resolution. These advantages make LSFM a promising tool for high-quality brain visualization. However, even by the use of LSFM, the spatial resolution remains insufficient to resolve the neural structures across a mesoscale whole mouse brain in three dimensions. At the same time, the thick-tissue scattering prevents a clear observation from the deep of brain. Here we use multi-view LSFM strategy to solve this challenge, surpassing the resolution limit of standard light-sheet microscope under a large field-of-view (FOV). As demonstrated by the imaging of optically-cleared mouse brain labelled with thy1-GFP, we achieve a brain-wide, isotropic cellular resolution of 3μm. Besides the resolution enhancement, multi-view braining imaging can also recover complete signals from deep tissue scattering and attenuation. The identification of long distance neural projections across encephalic regions can be identified and annotated as a result.

Comparison of the induced fields using different coil configurations during deep transcranial magnetic stimulation.

PubMed

Lu, Mai; Ueno, Shoogo

2017-01-01

Stimulation of deeper brain structures by transcranial magnetic stimulation (TMS) plays a role in the study of reward and motivation mechanisms, which may be beneficial in the treatment of several neurological and psychiatric disorders. However, electric field distributions induced in the brain by deep transcranial magnetic stimulation (dTMS) are still unknown. In this paper, the double cone coil, H-coil and Halo-circular assembly (HCA) coil which have been proposed for dTMS have been numerically designed. The distributions of magnetic flux density, induced electric field in an anatomically based realistic head model by applying the dTMS coils were numerically calculated by the impedance method. Results were compared with that of standard figure-of-eight (Fo8) coil. Simulation results show that double cone, H- and HCA coils have significantly deep field penetration compared to the conventional Fo8 coil, at the expense of induced higher and wider spread electrical fields in superficial cortical regions. Double cone and HCA coils have better ability to stimulate deep brain subregions compared to that of the H-coil. In the mean time, both double cone and HCA coils increase risk for optical nerve excitation. Our results suggest although the dTMS coils offer new tool with potential for both research and clinical applications for psychiatric and neurological disorders associated with dysfunctions of deep brain regions, the selection of the most suitable coil settings for a specific clinical application should be based on a balanced evaluation between stimulation depth and focality.

Segmentation of human brain using structural MRI.

PubMed

Helms, Gunther

2016-04-01

Segmentation of human brain using structural MRI is a key step of processing in imaging neuroscience. The methods have undergone a rapid development in the past two decades and are now widely available. This non-technical review aims at providing an overview and basic understanding of the most common software. Starting with the basis of structural MRI contrast in brain and imaging protocols, the concepts of voxel-based and surface-based segmentation are discussed. Special emphasis is given to the typical contrast features and morphological constraints of cortical and sub-cortical grey matter. In addition to the use for voxel-based morphometry, basic applications in quantitative MRI, cortical thickness estimations, and atrophy measurements as well as assignment of cortical regions and deep brain nuclei are briefly discussed. Finally, some fields for clinical applications are given.

Deep-brain-stimulation does not impair deglutition in Parkinson's disease.

PubMed

Lengerer, Sabrina; Kipping, Judy; Rommel, Natalie; Weiss, Daniel; Breit, Sorin; Gasser, Thomas; Plewnia, Christian; Krüger, Rejko; Wächter, Tobias

2012-08-01

A large proportion of patients with Parkinson's disease develop dysphagia during the course of the disease. Dysphagia in Parkinson's disease affects different phases of deglutition, has a strong impact on quality of life and may cause severe complications, i.e., aspirational pneumonia. So far, little is known on how deep-brain-stimulation of the subthalamic nucleus influences deglutition in PD. Videofluoroscopic swallowing studies on 18 patients with Parkinson's disease, which had been performed preoperatively, and postoperatively with deep-brain-stimulation-on and deep-brain-stimulation-off, were analyzed retrospectively. The patients were examined in each condition with three consistencies (viscous, fluid and solid). The 'New Zealand index for multidisciplinary evaluation of swallowing (NZIMES) Subscale One' for qualitative and 'Logemann-MBS-Parameters' for quantitative evaluation were assessed. Preoperatively, none of the patients presented with clinically relevant signs of dysphagia. While postoperatively, the mean daily levodopa equivalent dosage was reduced by 50% and deep-brain-stimulation led to a 50% improvement in motor symptoms measured by the UPDRS III, no clinically relevant influence of deep-brain-stimulation-on swallowing was observed using qualitative parameters (NZIMES). However quantitative parameters (Logemann scale) found significant changes of pharyngeal parameters with deep-brain-stimulation-on as compared to preoperative condition and deep-brain-stimulation-off mostly with fluid consistency. In Parkinson patients without dysphagia deep-brain-stimulation of the subthalamic nucleus modulates the pharyngeal deglutition phase but has no clinically relevant influence on deglutition. Further studies are needed to test if deep-brain-stimulation is a therapeutic option for patients with swallowing disorders. Copyright © 2012 Elsevier Ltd. All rights reserved.

Deep brain stimulation during early adolescence prevents microglial alterations in a model of maternal immune activation.

PubMed

Hadar, Ravit; Dong, Le; Del-Valle-Anton, Lucia; Guneykaya, Dilansu; Voget, Mareike; Edemann-Callesen, Henriette; Schweibold, Regina; Djodari-Irani, Anais; Goetz, Thomas; Ewing, Samuel; Kettenmann, Helmut; Wolf, Susanne A; Winter, Christine

2017-07-01

In recent years schizophrenia has been recognized as a neurodevelopmental disorder likely involving a perinatal insult progressively affecting brain development. The poly I:C maternal immune activation (MIA) rodent model is considered as a neurodevelopmental model of schizophrenia. Using this model we and others demonstrated the association between neuroinflammation in the form of altered microglia and a schizophrenia-like endophenotype. Therapeutic intervention using the anti-inflammatory drug minocycline affected altered microglia activation and was successful in the adult offspring. However, less is known about the effect of preventive therapeutic strategies on microglia properties. Previously we found that deep brain stimulation of the medial prefrontal cortex applied pre-symptomatically to adolescence MIA rats prevented the manifestation of behavioral and structural deficits in adult rats. We here studied the effects of deep brain stimulation during adolescence on microglia properties in adulthood. We found that in the hippocampus and nucleus accumbens, but not in the medial prefrontal cortex, microglial density and soma size were increased in MIA rats. Pro-inflammatory cytokine mRNA was unchanged in all brain areas before and after implantation and stimulation. Stimulation of either the medial prefrontal cortex or the nucleus accumbens normalized microglia density and soma size in main projection areas including the hippocampus and in the area around the electrode implantation. We conclude that in parallel to an alleviation of the symptoms in the rat MIA model, deep brain stimulation has the potential to prevent the neuroinflammatory component in this disease. Copyright © 2016 Elsevier Inc. All rights reserved.

Kinds of Thinking, Styles of Reasoning

ERIC Educational Resources Information Center

Peters, Michael A.

2007-01-01

There is no more central issue to education than thinking and reasoning. Certainly, such an emphasis chimes with the rationalist and cognitive deep structure of the Western educational tradition. The contemporary tendency reinforced by cognitive science is to treat thinking ahistorically and aculturally as though physiology, brain structure and…

In vivo three-photon microscopy of subcortical structures within an intact mouse brain

NASA Astrophysics Data System (ADS)

Horton, Nicholas G.; Wang, Ke; Kobat, Demirhan; Clark, Catharine G.; Wise, Frank W.; Schaffer, Chris B.; Xu, Chris

2013-03-01

Two-photon fluorescence microscopy enables scientists in various fields including neuroscience, embryology and oncology to visualize in vivo and ex vivo tissue morphology and physiology at a cellular level deep within scattering tissue. However, tissue scattering limits the maximum imaging depth of two-photon fluorescence microscopy to the cortical layer within mouse brain, and imaging subcortical structures currently requires the removal of overlying brain tissue or the insertion of optical probes. Here, we demonstrate non-invasive, high-resolution, in vivo imaging of subcortical structures within an intact mouse brain using three-photon fluorescence microscopy at a spectral excitation window of 1,700 nm. Vascular structures as well as red fluorescent protein-labelled neurons within the mouse hippocampus are imaged. The combination of the long excitation wavelength and the higher-order nonlinear excitation overcomes the limitations of two-photon fluorescence microscopy, enabling biological investigations to take place at a greater depth within tissue.

Acute and chronic changes in brain activity with deep brain stimulation for refractory depression.

PubMed

Conen, Silke; Matthews, Julian C; Patel, Nikunj K; Anton-Rodriguez, José; Talbot, Peter S

2018-04-01

Deep brain stimulation is a potential option for patients with treatment-refractory depression. Deep brain stimulation benefits have been reported when targeting either the subgenual cingulate or ventral anterior capsule/nucleus accumbens. However, not all patients respond and optimum stimulation-site is uncertain. We compared deep brain stimulation of the subgenual cingulate and ventral anterior capsule/nucleus accumbens separately and combined in the same seven treatment-refractory depression patients, and investigated regional cerebral blood flow changes associated with acute and chronic deep brain stimulation. Deep brain stimulation-response was defined as reduction in Montgomery-Asberg Depression Rating Scale score from baseline of ≥50%, and remission as a Montgomery-Asberg Depression Rating Scale score ≤8. Changes in regional cerebral blood flow were assessed using [ 15 O]water positron emission tomography. Remitters had higher relative regional cerebral blood flow in the prefrontal cortex at baseline and all subsequent time-points compared to non-remitters and non-responders, with prefrontal cortex regional cerebral blood flow generally increasing with chronic deep brain stimulation. These effects were consistent regardless of stimulation-site. Overall, no significant regional cerebral blood flow changes were apparent when deep brain stimulation was acutely interrupted. Deep brain stimulation improved treatment-refractory depression severity in the majority of patients, with consistent changes in local and distant brain regions regardless of target stimulation. Remission of depression was reached in patients with higher baseline prefrontal regional cerebral blood flow. Because of the small sample size these results are preliminary and further evaluation is necessary to determine whether prefrontal cortex regional cerebral blood flow could be a predictive biomarker of treatment response.

Exploring Deep Space - Uncovering the Anatomy of Periventricular Structures to Reveal the Lateral Ventricles of the Human Brain.

PubMed

Colibaba, Alexandru S; Calma, Aicee Dawn B; Webb, Alexandra L; Valter, Krisztina

2017-10-22

Anatomy students are typically provided with two-dimensional (2D) sections and images when studying cerebral ventricular anatomy and students find this challenging. Because the ventricles are negative spaces located deep within the brain, the only way to understand their anatomy is by appreciating their boundaries formed by related structures. Looking at a 2D representation of these spaces, in any of the cardinal planes, will not enable visualisation of all of the structures that form the boundaries of the ventricles. Thus, using 2D sections alone requires students to compute their own mental image of the 3D ventricular spaces. The aim of this study was to develop a reproducible method for dissecting the human brain to create an educational resource to enhance student understanding of the intricate relationships between the ventricles and periventricular structures. To achieve this, we created a video resource that features a step-by-step guide using a fiber dissection method to reveal the lateral and third ventricles together with the closely related limbic system and basal ganglia structures. One of the advantages of this method is that it enables delineation of the white matter tracts that are difficult to distinguish using other dissection techniques. This video is accompanied by a written protocol that provides a systematic description of the process to aid in the reproduction of the brain dissection. This package offers a valuable anatomy teaching resource for educators and students alike. By following these instructions educators can create teaching resources and students can be guided to produce their own brain dissection as a hands-on practical activity. We recommend that this video guide be incorporated into neuroanatomy teaching to enhance student understanding of the morphology and clinical relevance of the ventricles.

DeepNAT: Deep convolutional neural network for segmenting neuroanatomy.

PubMed

Wachinger, Christian; Reuter, Martin; Klein, Tassilo

2018-04-15

We introduce DeepNAT, a 3D Deep convolutional neural network for the automatic segmentation of NeuroAnaTomy in T1-weighted magnetic resonance images. DeepNAT is an end-to-end learning-based approach to brain segmentation that jointly learns an abstract feature representation and a multi-class classification. We propose a 3D patch-based approach, where we do not only predict the center voxel of the patch but also neighbors, which is formulated as multi-task learning. To address a class imbalance problem, we arrange two networks hierarchically, where the first one separates foreground from background, and the second one identifies 25 brain structures on the foreground. Since patches lack spatial context, we augment them with coordinates. To this end, we introduce a novel intrinsic parameterization of the brain volume, formed by eigenfunctions of the Laplace-Beltrami operator. As network architecture, we use three convolutional layers with pooling, batch normalization, and non-linearities, followed by fully connected layers with dropout. The final segmentation is inferred from the probabilistic output of the network with a 3D fully connected conditional random field, which ensures label agreement between close voxels. The roughly 2.7million parameters in the network are learned with stochastic gradient descent. Our results show that DeepNAT compares favorably to state-of-the-art methods. Finally, the purely learning-based method may have a high potential for the adaptation to young, old, or diseased brains by fine-tuning the pre-trained network with a small training sample on the target application, where the availability of larger datasets with manual annotations may boost the overall segmentation accuracy in the future. Copyright © 2017 Elsevier Inc. All rights reserved.

Deep brain optical measurements of cell type-specific neural activity in behaving mice.

PubMed

Cui, Guohong; Jun, Sang Beom; Jin, Xin; Luo, Guoxiang; Pham, Michael D; Lovinger, David M; Vogel, Steven S; Costa, Rui M

2014-01-01

Recent advances in genetically encoded fluorescent sensors enable the monitoring of cellular events from genetically defined groups of neurons in vivo. In this protocol, we describe how to use a time-correlated single-photon counting (TCSPC)-based fiber optics system to measure the intensity, emission spectra and lifetime of fluorescent biosensors expressed in deep brain structures in freely moving mice. When combined with Cre-dependent selective expression of genetically encoded Ca(2+) indicators (GECIs), this system can be used to measure the average neural activity from a specific population of cells in mice performing complex behavioral tasks. As an example, we used viral expression of GCaMPs in striatal projection neurons (SPNs) and recorded the fluorescence changes associated with calcium spikes from mice performing a lever-pressing operant task. The whole procedure, consisting of virus injection, behavior training and optical recording, takes 3-4 weeks to complete. With minor adaptations, this protocol can also be applied to recording cellular events from other cell types in deep brain regions, such as dopaminergic neurons in the ventral tegmental area. The simultaneously recorded fluorescence signals and behavior events can be used to explore the relationship between the neural activity of specific brain circuits and behavior.

Visualization of cortical, subcortical, and deep brain neural circuit dynamics during naturalistic mammalian behavior with head-mounted microscopes and chronically implanted lenses

PubMed Central

Resendez, Shanna L.; Jennings, Josh H.; Ung, Randall L.; Namboodiri, Vijay Mohan K.; Zhou, Zhe Charles; Otis, James M.; Nomura, Hiroshi; McHenry, Jenna A.; Kosyk, Oksana; Stuber, Garret D.

2016-01-01

Genetically encoded calcium indicators for visualizing dynamic cellular activity have greatly expanded our understanding of the brain. However, due to light scattering properties of the brain as well as the size and rigidity of traditional imaging technology, in vivo calcium imaging has been limited to superficial brain structures during head fixed behavioral tasks. This limitation can now be circumvented by utilizing miniature, integrated microscopes in conjunction with an implantable microendoscopic lens to guide light into and out of the brain, thus permitting optical access to deep brain (or superficial) neural ensembles during naturalistic behaviors. Here, we describe procedural steps to conduct such imaging studies using mice. However, we anticipate the protocol can be easily adapted for use in other small vertebrates. Successful completion of this protocol will permit cellular imaging of neuronal activity and the generation of data sets with sufficient statistical power to correlate neural activity with stimulus presentation, physiological state, and other aspects of complex behavioral tasks. This protocol takes 6–11 weeks to complete. PMID:26914316

Endovascular brain intervention and mapping in a dog experimental model using magnetically-guided micro-catheter technology.

PubMed

Kara, Tomas; Leinveber, Pavel; Vlasin, Michal; Jurak, Pavel; Novak, Miroslav; Novak, Zdenek; Chrastina, Jan; Czechowicz, Krzysztof; Belehrad, Milos; Asirvatham, Samuel J

2014-06-01

Despite the substantial progress that has been achieved in interventional cardiology and cardiac electrophysiology, endovascular intervention for the diagnosis and treatment of central nervous system (CNS) disorders such as stroke, epilepsy and CNS malignancy is still limited, particularly due to highly tortuous nature of the cerebral arterial and venous system. Existing interventional devices and techniques enable only limited and complicated access especially into intra-cerebral vessels. The aim of this study was to develop a micro-catheter magnetically-guided technology specifically designed for endovascular intervention and mapping in deep CNS vascular structures. Mapping of electrical brain activity was performed via the venous system on an animal dog model with the support of the NIOBE II system. A novel micro-catheter specially designed for endovascular interventions in the CNS, with the support of the NIOBE II technology, was able to reach safely deep intra-cerebral venous structures and map the electrical activity there. Such structures are not currently accessible using standard catheters. This is the first study demonstrating successful use of a new micro-catheter in combination with NIOBE II technology for endovascular intervention in the brain.

Comparison of the induced fields using different coil configurations during deep transcranial magnetic stimulation

PubMed Central

Ueno, Shoogo

2017-01-01

Stimulation of deeper brain structures by transcranial magnetic stimulation (TMS) plays a role in the study of reward and motivation mechanisms, which may be beneficial in the treatment of several neurological and psychiatric disorders. However, electric field distributions induced in the brain by deep transcranial magnetic stimulation (dTMS) are still unknown. In this paper, the double cone coil, H-coil and Halo-circular assembly (HCA) coil which have been proposed for dTMS have been numerically designed. The distributions of magnetic flux density, induced electric field in an anatomically based realistic head model by applying the dTMS coils were numerically calculated by the impedance method. Results were compared with that of standard figure-of-eight (Fo8) coil. Simulation results show that double cone, H- and HCA coils have significantly deep field penetration compared to the conventional Fo8 coil, at the expense of induced higher and wider spread electrical fields in superficial cortical regions. Double cone and HCA coils have better ability to stimulate deep brain subregions compared to that of the H-coil. In the mean time, both double cone and HCA coils increase risk for optical nerve excitation. Our results suggest although the dTMS coils offer new tool with potential for both research and clinical applications for psychiatric and neurological disorders associated with dysfunctions of deep brain regions, the selection of the most suitable coil settings for a specific clinical application should be based on a balanced evaluation between stimulation depth and focality. PMID:28586349

Chasing Tics in the Human Brain: Development of Open, Scheduled and Closed Loop Responsive Approaches to Deep Brain Stimulation for Tourette Syndrome

PubMed Central

Martinez-Ramirez, Daniel; Rossi, Peter J.; Peng, Zhongxing; Gunduz, Aysegul; Okun, Michael S.

2015-01-01

Tourette syndrome is a childhood-onset disorder characterized by a combination of motor and vocal tics, often associated with psychiatric comorbidities including attention deficit and hyperactivity disorder and obsessive-compulsive disorder. Despite an onset early in life, half of patients may present symptoms in adulthood, with variable degrees of severity. In select cases, the syndrome may lead to significant physical and social impairment, and a worrisome risk for self injury. Evolving research has provided evidence supporting the idea that the pathophysiology of Tourette syndrome is directly related to a disrupted circuit involving the cortex and subcortical structures, including the basal ganglia, nucleus accumbens, and the amygdala. There has also been a notion that a dysfunctional group of neurons in the putamen contributes to an abnormal facilitation of competing motor responses in basal ganglia structures ultimately underpinning the generation of tics. Surgical therapies for Tourette syndrome have been reserved for a small group of patients not responding to behavioral and pharmacological therapies, and these therapies have been directed at modulating the underlying pathophysiology. Lesion therapy as well as deep brain stimulation has been observed to suppress tics in at least some of these cases. In this article, we will review the clinical aspects of Tourette syndrome, as well as the evolution of surgical approaches and we will discuss the evidence and clinical responses to deep brain stimulation in various brain targets. We will also discuss ongoing research and future directions as well as approaches for open, scheduled and closed loop feedback-driven electrical stimulation for the treatment of Tourette syndrome. PMID:25851890

What is special about the adolescent (JME) brain?

PubMed

Craiu, Dana

2013-07-01

Juvenile myoclonic epilepsy (JME) involves cortico-thalamo-cortical networks. Thalamic, frontal gray matter, connectivity, and neurotransmitter disturbances have been demonstrated by structural/functional imaging studies. Few patients with JME show mutations in genes coding ion channels or GABAA (gamma-aminobutyric acid) receptor subunits. Recent research points to EFHC1 gene mutations leading to microdysgenesis and possible aberrant circuitry. Imaging studies have shown massive structural/functional changes of normally developing adolescent brain structures maturing at strikingly different rates and times. Gray matter (GM) volume diminishes in cortical areas (frontal and parietal) and deep structures (anterior thalamus, putamen, and caudate). Diffusion tensor imaging (DTI) findings support continued microstructural change in WM (white matter) during late adolescence with robust developmental changes in thalamocortical connectivity. The GABAA receptor distribution and specific receptor subunits' expression patterns change with age from neonate to adolescent/adult, contributing to age-related changes in brain excitability. Hormonal influence on brain structure development during adolescence is presented. Possible implications of brain changes during adolescence on the course of JME are discussed. Copyright © 2012 Elsevier Inc. All rights reserved.

Effects of thalamic deep brain stimulation on spontaneous language production.

PubMed

Ehlen, Felicitas; Vonberg, Isabelle; Kühn, Andrea A; Klostermann, Fabian

2016-08-01

The thalamus is thought to contribute to language-related processing, but specifications of this notion remain vague. An assessment of potential effects of thalamic deep brain stimulation (DBS) on spontaneous language may help to delineate respective functions. For this purpose, we analyzed spontaneous language samples from thirteen (six female / seven male) patients with essential tremor treated with DBS of the thalamic ventral intermediate nucleus (VIM) in their respective ON vs. OFF conditions. Samples were obtained from semi-structured interviews and examined on multidimensional linguistic levels. In the VIM-DBS ON condition, participants used a significantly higher proportion of paratactic as opposed to hypotactic sentence structures. This increase correlated negatively with the change in the more global cognitive score, which in itself did not change significantly. In conclusion, VIM-DBS appears to induce the use of a simplified syntactic structure. The findings are discussed in relation to concepts of thalamic roles in language-related cognitive behavior. Copyright © 2016 Elsevier Ltd. All rights reserved.

Deep learning based syndrome diagnosis of chronic gastritis.

PubMed

Liu, Guo-Ping; Yan, Jian-Jun; Wang, Yi-Qin; Zheng, Wu; Zhong, Tao; Lu, Xiong; Qian, Peng

2014-01-01

In Traditional Chinese Medicine (TCM), most of the algorithms used to solve problems of syndrome diagnosis are superficial structure algorithms and not considering the cognitive perspective from the brain. However, in clinical practice, there is complex and nonlinear relationship between symptoms (signs) and syndrome. So we employed deep leaning and multilabel learning to construct the syndrome diagnostic model for chronic gastritis (CG) in TCM. The results showed that deep learning could improve the accuracy of syndrome recognition. Moreover, the studies will provide a reference for constructing syndrome diagnostic models and guide clinical practice.

Deep Learning Based Syndrome Diagnosis of Chronic Gastritis

PubMed Central

Liu, Guo-Ping; Wang, Yi-Qin; Zheng, Wu; Zhong, Tao; Lu, Xiong; Qian, Peng

2014-01-01

In Traditional Chinese Medicine (TCM), most of the algorithms used to solve problems of syndrome diagnosis are superficial structure algorithms and not considering the cognitive perspective from the brain. However, in clinical practice, there is complex and nonlinear relationship between symptoms (signs) and syndrome. So we employed deep leaning and multilabel learning to construct the syndrome diagnostic model for chronic gastritis (CG) in TCM. The results showed that deep learning could improve the accuracy of syndrome recognition. Moreover, the studies will provide a reference for constructing syndrome diagnostic models and guide clinical practice. PMID:24734118

Deep-tissue two-photon imaging in brain and peripheral nerve with a compact high-pulse energy ytterbium fiber laser

NASA Astrophysics Data System (ADS)

Fontaine, Arjun K.; Kirchner, Matthew S.; Caldwell, John H.; Weir, Richard F.; Gibson, Emily A.

2018-02-01

Two-photon microscopy is a powerful tool of current scientific research, allowing optical visualization of structures below the surface of tissues. This is of particular value in neuroscience, where optically accessing regions within the brain is critical for the continued advancement in understanding of neural circuits. However, two-photon imaging at significant depths have typically used Ti:Sapphire based amplifiers that are prohibitively expensive and bulky. In this study, we demonstrate deep tissue two-photon imaging using a compact, inexpensive, turnkey operated Ytterbium fiber laser (Y-Fi, KM Labs). The laser is based on all-normal dispersion (ANDi) that provides short pulse durations and high pulse energies. Depth measurements obtained in ex vivo mouse cortex exceed those obtainable with standard two-photon microscopes using Ti:Sapphire lasers. In addition to demonstrating the capability of deep-tissue imaging in the brain, we investigated imaging depth in highly-scattering white matter with measurements in sciatic nerve showing limited optical penetration of heavily myelinated nerve tissue relative to grey matter.

Microfiberoptic fluorescence photobleaching reveals size-dependent macromolecule diffusion in extracellular space deep in brain.

PubMed

Zador, Zsolt; Magzoub, Mazin; Jin, Songwan; Manley, Geoffrey T; Papadopoulos, Marios C; Verkman, A S

2008-03-01

Diffusion in brain extracellular space (ECS) is important for nonsynaptic intercellular communication, extracellular ionic buffering, and delivery of drugs and metabolites. We measured macromolecular diffusion in normally light-inaccessible regions of mouse brain by microfiberoptic epifluorescence photobleaching, in which a fiberoptic with a micron-size tip is introduced deep in brain tissue. In brain cortex, the diffusion of a noninteracting molecule [fluorescein isothiocyanate (FITC)-dextran, 70 kDa] was slowed 4.5 +/- 0.5-fold compared with its diffusion in water (D(o)/D), and was depth-independent down to 800 microm from the brain surface. Diffusion was significantly accelerated (D(o)/D of 2.9+/-0.3) in mice lacking the glial water channel aquaporin-4. FITC-dextran diffusion varied greatly in different regions of brain, with D(o)/D of 3.5 +/- 0.3 in hippocampus and 7.4 +/- 0.3 in thalamus. Remarkably, D(o)/D in deep brain was strongly dependent on solute size, whereas diffusion in cortex changed little with solute size. Mathematical modeling of ECS diffusion required nonuniform ECS dimensions in deep brain, which we call "heterometricity," to account for the size-dependent diffusion. Our results provide the first data on molecular diffusion in ECS deep in brain in vivo and demonstrate previously unrecognized hindrance and heterometricity for diffusion of large macromolecules in deep brain.

Abnormal subcortical nuclei shapes in patients with type 2 diabetes mellitus.

PubMed

Chen, Ji; Zhang, Junxiang; Liu, Xuebing; Wang, Xiaoyang; Xu, Xiangjin; Li, Hui; Cao, Bo; Yang, Yanqiu; Lu, Jingjing; Chen, Ziqian

2017-10-01

Type 2 diabetes mellitus (T2DM) increases the risk of brain atrophy and dementia. We aimed to elucidate deep grey matter (GM) structural abnormalities and their relationships with T2DM cognitive deficits by combining region of interest (ROI)-based volumetry, voxel-based morphometry (VBM) and shape analysis. We recruited 23 T2DM patients and 24 age-matched healthy controls to undergo T1-weighted structural MRI scanning. Images were analysed using the three aforementioned methods to obtain deep GM structural shapes and volumes. Biochemical and cognitive assessments were made and were correlated with the resulting metrics. Shape analysis revealed that T2DM is associated with focal atrophy in the bilateral caudate head and dorso-medial part of the thalamus. ROI-based volumetry only detected thalamic volume reduction in T2DM when compared to the controls. No significant between-group differences were found by VBM. Furthermore, a worse performance of cognitive processing speed correlated with more severe GM atrophy in the bilateral dorso-medial part of the thalamus. Also, the GM volume in the bilateral dorso-medial part of the thalamus changed negatively with HbA 1c . Shape analysis is sensitive in identifying T2DM deep GM structural abnormalities and their relationships with cognitive impairments, which may greatly assist in clarifying the neural substrate of T2DM cognitive dysfunction. • Type 2 diabetes mellitus is accompanied with brain atrophy and cognitive dysfunction • Deep grey matter structures are essential for multiple cognitive processes • Shape analysis revealed local atrophy in the dorso-medial thalamus and caudatum in patients • Dorso-medial thalamic atrophy correlated to cognitive processing speed slowing and high HbA1c. • Shape analysis has advantages in unraveling neural substrates of diabetic cognitive deficits.

A three-dimensional histological atlas of the human basal ganglia. II. Atlas deformation strategy and evaluation in deep brain stimulation for Parkinson disease.

PubMed

Bardinet, Eric; Bhattacharjee, Manik; Dormont, Didier; Pidoux, Bernard; Malandain, Grégoire; Schüpbach, Michael; Ayache, Nicholas; Cornu, Philippe; Agid, Yves; Yelnik, Jérôme

2009-02-01

The localization of any given target in the brain has become a challenging issue because of the increased use of deep brain stimulation to treat Parkinson disease, dystonia, and nonmotor diseases (for example, Tourette syndrome, obsessive compulsive disorders, and depression). The aim of this study was to develop an automated method of adapting an atlas of the human basal ganglia to the brains of individual patients. Magnetic resonance images of the brain specimen were obtained before extraction from the skull and histological processing. Adaptation of the atlas to individual patient anatomy was performed by reshaping the atlas MR images to the images obtained in the individual patient using a hierarchical registration applied to a region of interest centered on the basal ganglia, and then applying the reshaping matrix to the atlas surfaces. Results were evaluated by direct visual inspection of the structures visible on MR images and atlas anatomy, by comparison with electrophysiological intraoperative data, and with previous atlas studies in patients with Parkinson disease. The method was both robust and accurate, never failing to provide an anatomically reliable atlas to patient registration. The registration obtained did not exceed a 1-mm mismatch with the electrophysiological signatures in the region of the subthalamic nucleus. This registration method applied to the basal ganglia atlas forms a powerful and reliable method for determining deep brain stimulation targets within the basal ganglia of individual patients.

Relationship between brain lesion characteristics and communication in preschool children with cerebral palsy.

PubMed

Coleman, Andrea; Fiori, Simona; Weir, Kelly A; Ware, Robert S; Boyd, Roslyn N

2016-11-01

MRI shows promise as a prognostic tool for clinical findings such as gross motor function in children with cerebral palsy(CP), however the relationship with communication skills requires exploration. To examine the relationship between the type and severity of brain lesion on MRI and communication skills in children with CP. 131 children with CP (73 males(56%)), mean corrected age(SD) 28(5) months, Gross Motor Functional Classification System distribution: I=57(44%), II=14(11%), III=19(14%), IV=17(13%), V=24(18%). Children were assessed on the Communication and Symbolic Behavioral Scales Developmental Profile (CSBS-DP) Infant-Toddler Checklist. Structural MRI was analysed with reference to type and semi-quantitative assessment of the severity of brain lesion. Children were classified for motor type, distribution and GMFCS. The relationships between type/severity of brain lesion and communication ability were analysed using multivariable tobit regression. Children with periventricular white matter lesions had better speech than children with cortical/deep grey matter lesions (β=-2.6, 95%CI=-5.0, -0.2, p=0.04). Brain lesion severity on the semi-quantitative scale was related to overall communication skills (β=-0.9, 95%CI=-1.4, -0.5, p<0.001). Motor impairment better accounted for impairment in overall communication skills than brain lesion severity. Structural MRI has potential prognostic value for communication impairment in children with CP. WHAT THIS PAPER ADDS?: This is the first paper to explore important aspects of communication in relation to the type and severity of brain lesion on MRI in a representative cohort of preschool-aged children with CP. We found a relationship between the type of brain lesion and communication skills, children who had cortical and deep grey matter lesions had overall communication skills>1 SD below children with periventricular white matter lesions. Children with more severe brain lesions on MRI had poorer overall communication skills. Children with CP born at term had poorer communication than those born prematurely and were more likely to have cortical and deep grey matter lesions. Gross motor function better accounted for overall communication skills than the type of brain lesion or brain lesion severity. Copyright © 2016. Published by Elsevier Ltd.

Embedded Ultrathin Cluster Electrodes for Long-Term Recordings in Deep Brain Centers

PubMed Central

Thorbergsson, Palmi Thor; Ekstrand, Joakim; Friberg, Annika; Granmo, Marcus; Pettersson, Lina M. E.; Schouenborg, Jens

2016-01-01

Neural interfaces which allow long-term recordings in deep brain structures in awake freely moving animals have the potential of becoming highly valuable tools in neuroscience. However, the recording quality usually deteriorates over time, probably at least partly due to tissue reactions caused by injuries during implantation, and subsequently micro-forces due to a lack of mechanical compliance between the tissue and neural interface. To address this challenge, we developed a gelatin embedded neural interface comprising highly flexible electrodes and evaluated its long term recording properties. Bundles of ultrathin parylene C coated platinum electrodes (N = 29) were embedded in a hard gelatin based matrix shaped like a needle, and coated with Kollicoat™ to retard dissolution of gelatin during the implantation. The implantation parameters were established in an in vitro model of the brain (0.5% agarose). Following a craniotomy in the anesthetized rat, the gelatin embedded electrodes were stereotactically inserted to a pre-target position, and after gelatin dissolution the electrodes were further advanced and spread out in the area of the subthalamic nucleus (STN). The performance of the implanted electrodes was evaluated under anesthesia, during 8 weeks. Apart from an increase in the median-noise level during the first 4 weeks, the electrode impedance and signal-to-noise ratio of single-units remained stable throughout the experiment. Histological postmortem analysis confirmed implantation in the area of STN in most animals. In conclusion, by combining novel biocompatible implantation techniques and ultra-flexible electrodes, long-term neuronal recordings from deep brain structures with no significant deterioration of electrode function were achieved. PMID:27159159

Deep Brain Electrical Stimulation in Epilepsy

NASA Astrophysics Data System (ADS)

Rocha, Luisa L.

2008-11-01

The deep brain electrical stimulation has been used for the treatment of neurological disorders such as Parkinson's disease, chronic pain, depression and epilepsy. Studies carried out in human brain indicate that the application of high frequency electrical stimulation (HFS) at 130 Hz in limbic structures of patients with intractable temporal lobe epilepsy abolished clinical seizures and significantly decreased the number of interictal spikes at focus. The anticonvulsant effects of HFS seem to be more effective in patients with less severe epilepsy, an effect associated with a high GABA tissue content and a low rate of cell loss. In addition, experiments using models of epilepsy indicate that HFS (pulses of 60 μs width at 130 Hz at subthreshold current intensity) of specific brain areas avoids the acquisition of generalized seizures and enhances the postictal seizure suppression. HFS is also able to modify the status epilepticus. It is concluded that the effects of HFS may be a good strategy to reduce or avoid the epileptic activity.

Inferring deep-brain activity from cortical activity using functional near-infrared spectroscopy

PubMed Central

Liu, Ning; Cui, Xu; Bryant, Daniel M.; Glover, Gary H.; Reiss, Allan L.

2015-01-01

Functional near-infrared spectroscopy (fNIRS) is an increasingly popular technology for studying brain function because it is non-invasive, non-irradiating and relatively inexpensive. Further, fNIRS potentially allows measurement of hemodynamic activity with high temporal resolution (milliseconds) and in naturalistic settings. However, in comparison with other imaging modalities, namely fMRI, fNIRS has a significant drawback: limited sensitivity to hemodynamic changes in deep-brain regions. To overcome this limitation, we developed a computational method to infer deep-brain activity using fNIRS measurements of cortical activity. Using simultaneous fNIRS and fMRI, we measured brain activity in 17 participants as they completed three cognitive tasks. A support vector regression (SVR) learning algorithm was used to predict activity in twelve deep-brain regions using information from surface fNIRS measurements. We compared these predictions against actual fMRI-measured activity using Pearson’s correlation to quantify prediction performance. To provide a benchmark for comparison, we also used fMRI measurements of cortical activity to infer deep-brain activity. When using fMRI-measured activity from the entire cortex, we were able to predict deep-brain activity in the fusiform cortex with an average correlation coefficient of 0.80 and in all deep-brain regions with an average correlation coefficient of 0.67. The top 15% of predictions using fNIRS signal achieved an accuracy of 0.7. To our knowledge, this study is the first to investigate the feasibility of using cortical activity to infer deep-brain activity. This new method has the potential to extend fNIRS applications in cognitive and clinical neuroscience research. PMID:25798327

Optical coherence tomography and optical coherence domain reflectometry for deep brain stimulation probe guidance

NASA Astrophysics Data System (ADS)

Jeon, Sung W.; Shure, Mark A.; Baker, Kenneth B.; Chahlavi, Ali; Hatoum, Nagi; Turbay, Massud; Rollins, Andrew M.; Rezai, Ali R.; Huang, David

2005-04-01

Deep Brain Stimulation (DBS) is FDA-approved for the treatment of Parkinson's disease and essential tremor. Currently, placement of DBS leads is guided through a combination of anatomical targeting and intraoperative microelectrode recordings. The physiological mapping process requires several hours, and each pass of the microelectrode into the brain increases the risk of hemorrhage. Optical Coherence Domain Reflectometry (OCDR) in combination with current methodologies could reduce surgical time and increase accuracy and safety by providing data on structures some distance ahead of the probe. For this preliminary study, we scanned a rat brain in vitro using polarization-insensitive Optical Coherence Tomography (OCT). For accurate measurement of intensity and attenuation, polarization effects arising from tissue birefringence are removed by polarization diversity detection. A fresh rat brain was sectioned along the coronal plane and immersed in a 5 mm cuvette with saline solution. OCT images from a 1294 nm light source showed depth profiles up to 2 mm. Light intensity and attenuation rate distinguished various tissue structures such as hippocampus, cortex, external capsule, internal capsule, and optic tract. Attenuation coefficient is determined by linear fitting of the single scattering regime in averaged A-scans where Beer"s law is applicable. Histology showed very good correlation with OCT images. From the preliminary study using OCT, we conclude that OCDR is a promising approach for guiding DBS probe placement.

Prediction of brain-computer interface aptitude from individual brain structure.

PubMed

Halder, S; Varkuti, B; Bogdan, M; Kübler, A; Rosenstiel, W; Sitaram, R; Birbaumer, N

2013-01-01

Brain-computer interface (BCI) provide a non-muscular communication channel for patients with impairments of the motor system. A significant number of BCI users is unable to obtain voluntary control of a BCI-system in proper time. This makes methods that can be used to determine the aptitude of a user necessary. We hypothesized that integrity and connectivity of involved white matter connections may serve as a predictor of individual BCI-performance. Therefore, we analyzed structural data from anatomical scans and DTI of motor imagery BCI-users differentiated into high and low BCI-aptitude groups based on their overall performance. Using a machine learning classification method we identified discriminating structural brain trait features and correlated the best features with a continuous measure of individual BCI-performance. Prediction of the aptitude group of each participant was possible with near perfect accuracy (one error). Tissue volumetric analysis yielded only poor classification results. In contrast, the structural integrity and myelination quality of deep white matter structures such as the Corpus Callosum, Cingulum, and Superior Fronto-Occipital Fascicle were positively correlated with individual BCI-performance. This confirms that structural brain traits contribute to individual performance in BCI use.

Prediction of brain-computer interface aptitude from individual brain structure

PubMed Central

Halder, S.; Varkuti, B.; Bogdan, M.; Kübler, A.; Rosenstiel, W.; Sitaram, R.; Birbaumer, N.

2013-01-01

Objective: Brain-computer interface (BCI) provide a non-muscular communication channel for patients with impairments of the motor system. A significant number of BCI users is unable to obtain voluntary control of a BCI-system in proper time. This makes methods that can be used to determine the aptitude of a user necessary. Methods: We hypothesized that integrity and connectivity of involved white matter connections may serve as a predictor of individual BCI-performance. Therefore, we analyzed structural data from anatomical scans and DTI of motor imagery BCI-users differentiated into high and low BCI-aptitude groups based on their overall performance. Results: Using a machine learning classification method we identified discriminating structural brain trait features and correlated the best features with a continuous measure of individual BCI-performance. Prediction of the aptitude group of each participant was possible with near perfect accuracy (one error). Conclusions: Tissue volumetric analysis yielded only poor classification results. In contrast, the structural integrity and myelination quality of deep white matter structures such as the Corpus Callosum, Cingulum, and Superior Fronto-Occipital Fascicle were positively correlated with individual BCI-performance. Significance: This confirms that structural brain traits contribute to individual performance in BCI use. PMID:23565083

Asleep Deep Brain Stimulation Reduces Incidence of Intracranial Air during Electrode Implantation.

PubMed

Ko, Andrew L; Magown, Philippe; Ozpinar, Alp; Hamzaoglu, Vural; Burchiel, Kim J

2018-05-30

Asleep deep brain stimulation (aDBS) implantation replaces microelectrode recording for image-guided implantation, shortening the operative time and reducing cerebrospinal fluid egress. This may decrease pneumocephalus, thus decreasing brain shift during implantation. To compare the incidence and volume of pneumocephalus during awake (wkDBS) and aDBS procedures. A retrospective review of bilateral DBS cases performed at Oregon Health & Science University from 2009 to 2017 was undertaken. Postimplantation imaging was reviewed to determine the presence and volume of intracranial air and measure cortical brain shift. Among 371 patients, pneumocephalus was noted in 66% of wkDBS and 15.6% of aDBS. The average volume of air was significantly higher in wkDBS than aDBS (8.0 vs. 1.8 mL). Volumes of air greater than 7 mL, which have previously been linked to brain shift, occurred significantly more frequently in wkDBS than aDBS (34 vs 5.6%). wkDBS resulted in significantly larger cortical brain shifts (5.8 vs. 1.2 mm). We show that aDBS reduces the incidence of intracranial air, larger air volumes, and cortical brain shift. Large volumes of intracranial air have been correlated to shifting of brain structures during DBS procedures, a variable that could impact accuracy of electrode placement. © 2018 S. Karger AG, Basel.

Bilateral deep brain stimulation vs best medical therapy for patients with advanced Parkinson disease: a randomized controlled trial.

PubMed

Weaver, Frances M; Follett, Kenneth; Stern, Matthew; Hur, Kwan; Harris, Crystal; Marks, William J; Rothlind, Johannes; Sagher, Oren; Reda, Domenic; Moy, Claudia S; Pahwa, Rajesh; Burchiel, Kim; Hogarth, Penelope; Lai, Eugene C; Duda, John E; Holloway, Kathryn; Samii, Ali; Horn, Stacy; Bronstein, Jeff; Stoner, Gatana; Heemskerk, Jill; Huang, Grant D

2009-01-07

Deep brain stimulation is an accepted treatment for advanced Parkinson disease (PD), although there are few randomized trials comparing treatments, and most studies exclude older patients. To compare 6-month outcomes for patients with PD who received deep brain stimulation or best medical therapy. Randomized controlled trial of patients who received either deep brain stimulation or best medical therapy, stratified by study site and patient age (< 70 years vs > or = 70 years) at 7 Veterans Affairs and 6 university hospitals between May 2002 and October 2005. A total of 255 patients with PD (Hoehn and Yahr stage > or = 2 while not taking medications) were enrolled; 25% were aged 70 years or older. The final 6-month follow-up visit occurred in May 2006. Bilateral deep brain stimulation of the subthalamic nucleus (n = 60) or globus pallidus (n = 61). Patients receiving best medical therapy (n = 134) were actively managed by movement disorder neurologists. The primary outcome was time spent in the "on" state (good motor control with unimpeded motor function) without troubling dyskinesia, using motor diaries. Other outcomes included motor function, quality of life, neurocognitive function, and adverse events. Patients who received deep brain stimulation gained a mean of 4.6 h/d of on time without troubling dyskinesia compared with 0 h/d for patients who received best medical therapy (between group mean difference, 4.5 h/d [95% CI, 3.7-5.4 h/d]; P < .001). Motor function improved significantly (P < .001) with deep brain stimulation vs best medical therapy, such that 71% of deep brain stimulation patients and 32% of best medical therapy patients experienced clinically meaningful motor function improvements (> or = 5 points). Compared with the best medical therapy group, the deep brain stimulation group experienced significant improvements in the summary measure of quality of life and on 7 of 8 PD quality-of-life scores (P < .001). Neurocognitive testing revealed small decrements in some areas of information processing for patients receiving deep brain stimulation vs best medical therapy. At least 1 serious adverse event occurred in 49 deep brain stimulation patients and 15 best medical therapy patients (P < .001), including 39 adverse events related to the surgical procedure and 1 death secondary to cerebral hemorrhage. In this randomized controlled trial of patients with advanced PD, deep brain stimulation was more effective than best medical therapy in improving on time without troubling dyskinesias, motor function, and quality of life at 6 months, but was associated with an increased risk of serious adverse events. clinicaltrials.gov Identifier: NCT00056563.

Nonthermal ablation with microbubble-enhanced focused ultrasound close to the optic tract without affecting nerve function.

PubMed

McDannold, Nathan; Zhang, Yong-Zhi; Power, Chanikarn; Jolesz, Ferenc; Vykhodtseva, Natalia

2013-11-01

Tumors at the skull base are challenging for both resection and radiosurgery given the presence of critical adjacent structures, such as cranial nerves, blood vessels, and brainstem. Magnetic resonance imaging-guided thermal ablation via laser or other methods has been evaluated as a minimally invasive alternative to these techniques in the brain. Focused ultrasound (FUS) offers a noninvasive method of thermal ablation; however, skull heating limits currently available technology to ablation at regions distant from the skull bone. Here, the authors evaluated a method that circumvents this problem by combining the FUS exposures with injected microbubble-based ultrasound contrast agent. These microbubbles concentrate the ultrasound-induced effects on the vasculature, enabling an ablation method that does not cause significant heating of the brain or skull. In 29 rats, a 525-kHz FUS transducer was used to ablate tissue structures at the skull base that were centered on or adjacent to the optic tract or chiasm. Low-intensity, low-duty-cycle ultrasound exposures (sonications) were applied for 5 minutes after intravenous injection of an ultrasound contrast agent (Definity, Lantheus Medical Imaging Inc.). Using histological analysis and visual evoked potential (VEP) measurements, the authors determined whether structural or functional damage was induced in the optic tract or chiasm. Overall, while the sonications produced a well-defined lesion in the gray matter targets, the adjacent tract and chiasm had comparatively little or no damage. No significant changes (p > 0.05) were found in the magnitude or latency of the VEP recordings, either immediately after sonication or at later times up to 4 weeks after sonication, and no delayed effects were evident in the histological features of the optic nerve and retina. This technique, which selectively targets the intravascular microbubbles, appears to be a promising method of noninvasively producing sharply demarcated lesions in deep brain structures while preserving function in adjacent nerves. Because of low vascularity--and thus a low microbubble concentration--some large white matter tracts appear to have some natural resistance to this type of ablation compared with gray matter. While future work is needed to develop methods of monitoring the procedure and establishing its safety at deep brain targets, the technique does appear to be a potential solution that allows FUS ablation of deep brain targets while sparing adjacent nerve structures.

Nonthermal ablation with microbubble-enhanced focused ultrasound close to the optic tract without affecting nerve function

PubMed Central

McDannold, Nathan; Zhang, Yong-Zhi; Power, Chanikarn; Jolesz, Ferenc; Vykhodtseva, Natalia

2014-01-01

Object Tumors at the skull base are challenging for both resection and radiosurgery given the presence of critical adjacent structures, such as cranial nerves, blood vessels, and brainstem. Magnetic resonance imaging–guided thermal ablation via laser or other methods has been evaluated as a minimally invasive alternative to these techniques in the brain. Focused ultrasound (FUS) offers a noninvasive method of thermal ablation; however, skull heating limits currently available technology to ablation at regions distant from the skull bone. Here, the authors evaluated a method that circumvents this problem by combining the FUS exposures with injected microbubble-based ultrasound contrast agent. These microbubbles concentrate the ultrasound-induced effects on the vasculature, enabling an ablation method that does not cause significant heating of the brain or skull. Methods In 29 rats, a 525-kHz FUS transducer was used to ablate tissue structures at the skull base that were centered on or adjacent to the optic tract or chiasm. Low-intensity, low-duty-cycle ultrasound exposures (sonications) were applied for 5 minutes after intravenous injection of an ultrasound contrast agent (Definity, Lantheus Medical Imaging Inc.). Using histological analysis and visual evoked potential (VEP) measurements, the authors determined whether structural or functional damage was induced in the optic tract or chiasm. Results Overall, while the sonications produced a well-defined lesion in the gray matter targets, the adjacent tract and chiasm had comparatively little or no damage. No significant changes (p > 0.05) were found in the magnitude or latency of the VEP recordings, either immediately after sonication or at later times up to 4 weeks after sonication, and no delayed effects were evident in the histological features of the optic nerve and retina. Conclusions This technique, which selectively targets the intravascular microbubbles, appears to be a promising method of noninvasively producing sharply demarcated lesions in deep brain structures while preserving function in adjacent nerves. Because of low vascularity—and thus a low microbubble concentration—some large white matter tracts appear to have some natural resistance to this type of ablation compared with gray matter. While future work is needed to develop methods of monitoring the procedure and establishing its safety at deep brain targets, the technique does appear to be a potential solution that allows FUS ablation of deep brain targets while sparing adjacent nerve structures. PMID:24010975

Computational analysis of transcranial magnetic stimulation in the presence of deep brain stimulation probes

NASA Astrophysics Data System (ADS)

Syeda, F.; Holloway, K.; El-Gendy, A. A.; Hadimani, R. L.

2017-05-01

Transcranial Magnetic Stimulation is an emerging non-invasive treatment for depression, Parkinson's disease, and a variety of other neurological disorders. Many Parkinson's patients receive the treatment known as Deep Brain Stimulation, but often require additional therapy for speech and swallowing impairment. Transcranial Magnetic Stimulation has been explored as a possible treatment by stimulating the mouth motor area of the brain. We have calculated induced electric field, magnetic field, and temperature distributions in the brain using finite element analysis and anatomically realistic heterogeneous head models fitted with Deep Brain Stimulation leads. A Figure of 8 coil, current of 5000 A, and frequency of 2.5 kHz are used as simulation parameters. Results suggest that Deep Brain Stimulation leads cause surrounding tissues to experience slightly increased E-field (Δ Emax =30 V/m), but not exceeding the nominal values induced in brain tissue by Transcranial Magnetic Stimulation without leads (215 V/m). The maximum temperature in the brain tissues surrounding leads did not change significantly from the normal human body temperature of 37 °C. Therefore, we ascertain that Transcranial Magnetic Stimulation in the mouth motor area may stimulate brain tissue surrounding Deep Brain Stimulation leads, but will not cause tissue damage.

Mapping higher-order relations between brain structure and function with embedded vector representations of connectomes.

PubMed

Rosenthal, Gideon; Váša, František; Griffa, Alessandra; Hagmann, Patric; Amico, Enrico; Goñi, Joaquín; Avidan, Galia; Sporns, Olaf

2018-06-05

Connectomics generates comprehensive maps of brain networks, represented as nodes and their pairwise connections. The functional roles of nodes are defined by their direct and indirect connectivity with the rest of the network. However, the network context is not directly accessible at the level of individual nodes. Similar problems in language processing have been addressed with algorithms such as word2vec that create embeddings of words and their relations in a meaningful low-dimensional vector space. Here we apply this approach to create embedded vector representations of brain networks or connectome embeddings (CE). CE can characterize correspondence relations among brain regions, and can be used to infer links that are lacking from the original structural diffusion imaging, e.g., inter-hemispheric homotopic connections. Moreover, we construct predictive deep models of functional and structural connectivity, and simulate network-wide lesion effects using the face processing system as our application domain. We suggest that CE offers a novel approach to revealing relations between connectome structure and function.

Resting state functional MRI in Parkinson’s disease: the impact of deep brain stimulation on ‘effective’ connectivity

PubMed Central

Kahan, Joshua; Urner, Maren; Moran, Rosalyn; Flandin, Guillaume; Marreiros, Andre; Mancini, Laura; White, Mark; Thornton, John; Yousry, Tarek; Zrinzo, Ludvic; Hariz, Marwan; Limousin, Patricia; Friston, Karl

2014-01-01

Depleted of dopamine, the dynamics of the parkinsonian brain impact on both ‘action’ and ‘resting’ motor behaviour. Deep brain stimulation has become an established means of managing these symptoms, although its mechanisms of action remain unclear. Non-invasive characterizations of induced brain responses, and the effective connectivity underlying them, generally appeals to dynamic causal modelling of neuroimaging data. When the brain is at rest, however, this sort of characterization has been limited to correlations (functional connectivity). In this work, we model the ‘effective’ connectivity underlying low frequency blood oxygen level-dependent fluctuations in the resting Parkinsonian motor network—disclosing the distributed effects of deep brain stimulation on cortico-subcortical connections. Specifically, we show that subthalamic nucleus deep brain stimulation modulates all the major components of the motor cortico-striato-thalamo-cortical loop, including the cortico-striatal, thalamo-cortical, direct and indirect basal ganglia pathways, and the hyperdirect subthalamic nucleus projections. The strength of effective subthalamic nucleus afferents and efferents were reduced by stimulation, whereas cortico-striatal, thalamo-cortical and direct pathways were strengthened. Remarkably, regression analysis revealed that the hyperdirect, direct, and basal ganglia afferents to the subthalamic nucleus predicted clinical status and therapeutic response to deep brain stimulation; however, suppression of the sensitivity of the subthalamic nucleus to its hyperdirect afferents by deep brain stimulation may subvert the clinical efficacy of deep brain stimulation. Our findings highlight the distributed effects of stimulation on the resting motor network and provide a framework for analysing effective connectivity in resting state functional MRI with strong a priori hypotheses. PMID:24566670

Resting state functional MRI in Parkinson's disease: the impact of deep brain stimulation on 'effective' connectivity.

PubMed

Kahan, Joshua; Urner, Maren; Moran, Rosalyn; Flandin, Guillaume; Marreiros, Andre; Mancini, Laura; White, Mark; Thornton, John; Yousry, Tarek; Zrinzo, Ludvic; Hariz, Marwan; Limousin, Patricia; Friston, Karl; Foltynie, Tom

2014-04-01

Depleted of dopamine, the dynamics of the parkinsonian brain impact on both 'action' and 'resting' motor behaviour. Deep brain stimulation has become an established means of managing these symptoms, although its mechanisms of action remain unclear. Non-invasive characterizations of induced brain responses, and the effective connectivity underlying them, generally appeals to dynamic causal modelling of neuroimaging data. When the brain is at rest, however, this sort of characterization has been limited to correlations (functional connectivity). In this work, we model the 'effective' connectivity underlying low frequency blood oxygen level-dependent fluctuations in the resting Parkinsonian motor network-disclosing the distributed effects of deep brain stimulation on cortico-subcortical connections. Specifically, we show that subthalamic nucleus deep brain stimulation modulates all the major components of the motor cortico-striato-thalamo-cortical loop, including the cortico-striatal, thalamo-cortical, direct and indirect basal ganglia pathways, and the hyperdirect subthalamic nucleus projections. The strength of effective subthalamic nucleus afferents and efferents were reduced by stimulation, whereas cortico-striatal, thalamo-cortical and direct pathways were strengthened. Remarkably, regression analysis revealed that the hyperdirect, direct, and basal ganglia afferents to the subthalamic nucleus predicted clinical status and therapeutic response to deep brain stimulation; however, suppression of the sensitivity of the subthalamic nucleus to its hyperdirect afferents by deep brain stimulation may subvert the clinical efficacy of deep brain stimulation. Our findings highlight the distributed effects of stimulation on the resting motor network and provide a framework for analysing effective connectivity in resting state functional MRI with strong a priori hypotheses.

Optimized beamforming for simultaneous MEG and intracranial local field potential recordings in deep brain stimulation patients.

PubMed

Litvak, Vladimir; Eusebio, Alexandre; Jha, Ashwani; Oostenveld, Robert; Barnes, Gareth R; Penny, William D; Zrinzo, Ludvic; Hariz, Marwan I; Limousin, Patricia; Friston, Karl J; Brown, Peter

2010-05-01

Insight into how brain structures interact is critical for understanding the principles of functional brain architectures and may lead to better diagnosis and therapy for neuropsychiatric disorders. We recorded, simultaneously, magnetoencephalographic (MEG) signals and subcortical local field potentials (LFP) in a Parkinson's disease (PD) patient with bilateral deep brain stimulation (DBS) electrodes in the subthalamic nucleus (STN). These recordings offer a unique opportunity to characterize interactions between the subcortical structures and the neocortex. However, high-amplitude artefacts appeared in the MEG. These artefacts originated from the percutaneous extension wire, rather than from the actual DBS electrode and were locked to the heart beat. In this work, we show that MEG beamforming is capable of suppressing these artefacts and quantify the optimal regularization required. We demonstrate how beamforming makes it possible to localize cortical regions whose activity is coherent with the STN-LFP, extract artefact-free virtual electrode time-series from regions of interest and localize cortical areas exhibiting specific task-related power changes. This furnishes results that are consistent with previously reported results using artefact-free MEG data. Our findings demonstrate that physiologically meaningful information can be extracted from heavily contaminated MEG signals and pave the way for further analysis of combined MEG-LFP recordings in DBS patients. 2009 Elsevier Inc. All rights reserved.

New MR imaging assessment tool to define brain abnormalities in very preterm infants at term.

PubMed

Kidokoro, H; Neil, J J; Inder, T E

2013-01-01

WM injury is the dominant form of injury in preterm infants. However, other cerebral structures, including the deep gray matter and the cerebellum, can also be affected by injury and/or impaired growth. Current MR imaging injury assessment scales are subjective and are challenging to apply. Thus, we developed a new assessment tool and applied it to MR imaging studies obtained from very preterm infants at term age. MR imaging scans from 97 very preterm infants (< 30 weeks' gestation) and 22 healthy term-born infants were evaluated retrospectively. The severity of brain injury (defined by signal abnormalities) and impaired brain growth (defined with biometrics) was scored in the WM, cortical gray matter, deep gray matter, and cerebellum. Perinatal variables for clinical risks were collected. In very preterm infants, brain injury was observed in the WM (n=23), deep GM (n=5), and cerebellum (n=23). Combining measures of injury and impaired growth showed moderate to severe abnormalities most commonly in the WM (n=38) and cerebellum (n=32) but still notable in the cortical gray matter (n=16) and deep gray matter (n=11). WM signal abnormalities were associated with a reduced deep gray matter area but not with cerebellar abnormality. Intraventricular and/or parenchymal hemorrhage was associated with cerebellar signal abnormality and volume reduction. Multiple clinical risk factors, including prolonged intubation, prolonged parenteral nutrition, postnatal corticosteroid use, and postnatal sepsis, were associated with increased global abnormality on MR imaging. Very preterm infants demonstrate a high prevalence of injury and growth impairment in both the WM and gray matter. This MR imaging scoring system provides a more comprehensive and objective classification of the nature and extent of abnormalities than existing measures.

The evolution of endovascular electroencephalography: historical perspective and future applications.

PubMed

Sefcik, Roberta K; Opie, Nicholas L; John, Sam E; Kellner, Christopher P; Mocco, J; Oxley, Thomas J

2016-05-01

Current standard practice requires an invasive approach to the recording of electroencephalography (EEG) for epilepsy surgery, deep brain stimulation (DBS), and brain-machine interfaces (BMIs). The development of endovascular techniques offers a minimally invasive route to recording EEG from deep brain structures. This historical perspective aims to describe the technical progress in endovascular EEG by reviewing the first endovascular recordings made using a wire electrode, which was followed by the development of nanowire and catheter recordings and, finally, the most recent progress in stent-electrode recordings. The technical progress in device technology over time and the development of the ability to record chronic intravenous EEG from electrode arrays is described. Future applications for the use of endovascular EEG in the preoperative and operative management of epilepsy surgery are then discussed, followed by the possibility of the technique's future application in minimally invasive operative approaches to DBS and BMI.

VoxResNet: Deep voxelwise residual networks for brain segmentation from 3D MR images.

PubMed

Chen, Hao; Dou, Qi; Yu, Lequan; Qin, Jing; Heng, Pheng-Ann

2018-04-15

Segmentation of key brain tissues from 3D medical images is of great significance for brain disease diagnosis, progression assessment and monitoring of neurologic conditions. While manual segmentation is time-consuming, laborious, and subjective, automated segmentation is quite challenging due to the complicated anatomical environment of brain and the large variations of brain tissues. We propose a novel voxelwise residual network (VoxResNet) with a set of effective training schemes to cope with this challenging problem. The main merit of residual learning is that it can alleviate the degradation problem when training a deep network so that the performance gains achieved by increasing the network depth can be fully leveraged. With this technique, our VoxResNet is built with 25 layers, and hence can generate more representative features to deal with the large variations of brain tissues than its rivals using hand-crafted features or shallower networks. In order to effectively train such a deep network with limited training data for brain segmentation, we seamlessly integrate multi-modality and multi-level contextual information into our network, so that the complementary information of different modalities can be harnessed and features of different scales can be exploited. Furthermore, an auto-context version of the VoxResNet is proposed by combining the low-level image appearance features, implicit shape information, and high-level context together for further improving the segmentation performance. Extensive experiments on the well-known benchmark (i.e., MRBrainS) of brain segmentation from 3D magnetic resonance (MR) images corroborated the efficacy of the proposed VoxResNet. Our method achieved the first place in the challenge out of 37 competitors including several state-of-the-art brain segmentation methods. Our method is inherently general and can be readily applied as a powerful tool to many brain-related studies, where accurate segmentation of brain structures is critical. Copyright © 2017 Elsevier Inc. All rights reserved.

Syringe Port: A Convenient, Safe, and Cost-Effective Tubular Retractor for Transportal Removal of Deep-Seated Lesions of the Brain.

PubMed

Singh, Harnarayan; Patir, Rana; Vaishya, Sandeep; Miglani, Rahul; Kaur, Amandeep

2018-06-01

Minimally invasive transportal resection of deep intracranial lesions has become a widely accepted surgical technique. Many disposable, mountable port systems are available in the market for this purpose, like the ViewSite Brain Access System. The objective of this study was to find a cost-effective substitute for these systems. Deep-seated brain lesions were treated with a port system made from disposable syringes. The syringe port could be inserted through minicraniotomies placed and planned with navigation. All deep-seated lesions like ventricular tumours, colloid cysts, deep-seated gliomas, and basal ganglia hemorrhages were treated with this syringe port system and evaluated for safety, operative site hematomas, and blood loss. 62 patients were operated on during the study period from January 2015 to July 2017, using this innovative syringe port system for deep-seated lesions of the brain. No operative site hematoma or contusions were seen along the port entry site and tract. Syringe port is a cost-effective and safe alternative to the costly disposable brain port systems, especially for neurosurgical setups in developing countries for minimally invasive transportal resection of deep brain lesions. Copyright © 2018 Elsevier Inc. All rights reserved.

From miracle to reconciliation: a hermeneutic phenomenological study exploring the experience of living with Parkinson's disease following deep brain stimulation.

PubMed

Haahr, Anita; Kirkevold, Marit; Hall, Elisabeth O C; Ostergaard, Karen

2010-10-01

Deep Brain Stimulation for Parkinson's disease is a promising treatment for patients who can no longer be treated satisfactorily with L-dopa. Deep Brain Stimulation is known to relieve motor symptoms of Parkinson's disease and improve quality of life. Focusing on how patients experience life when treated with Deep Brain Stimulation can provide essential information on the process patients go through when receiving a treatment that alters the body and changes the illness trajectory. The aim of this study was to explore and describe the experience of living with Parkinson's disease when treated with Deep Brain Stimulation. The study was designed as a longitudinal study and data were gathered through qualitative in-depth interviews three times during the first year of treatment. Nine patients participated in the study. They were included when they had accepted treatment with Deep Brain Stimulation for Parkinson's disease. Data collection and data analysis were inspired by the hermeneutic phenomenological methodology of Van Manen. The treatment had a major impact on the body. Participants experienced great bodily changes and went through a process of adjustment in three phases during the first year of treatment with Deep Brain Stimulation. These stages were; being liberated: a kind of miracle, changes as a challenge: decline or opportunity and reconciliation: re-defining life with Parkinson's disease. The course of the process was unique for each participant, but dominant was that difficulties during the adjustment of stimulation and medication did affect the re-defining process. Patients go through a dramatic process of change following Deep Brain Stimulation. A changing body affects their entire lifeworld. Some adjust smoothly to changes while others are affected by loss of control, uncertainty and loss of everyday life as they knew it. These experiences affect the process of adjusting to life with Deep Brain Stimulation and re-define life with Parkinson's disease. It is of significant importance that health care professionals are aware of these dramatic changes in the patients' life and offer support during the adjustment process following Deep Brain Stimulation. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Beamspace dual signal space projection (bDSSP): a method for selective detection of deep sources in MEG measurements.

PubMed

Sekihara, Kensuke; Adachi, Yoshiaki; Kubota, Hiroshi K; Cai, Chang; Nagarajan, Srikantan S

2018-06-01

Magnetoencephalography (MEG) has a well-recognized weakness at detecting deeper brain activities. This paper proposes a novel algorithm for selective detection of deep sources by suppressing interference signals from superficial sources in MEG measurements. The proposed algorithm combines the beamspace preprocessing method with the dual signal space projection (DSSP) interference suppression method. A prerequisite of the proposed algorithm is prior knowledge of the location of the deep sources. The proposed algorithm first derives the basis vectors that span a local region just covering the locations of the deep sources. It then estimates the time-domain signal subspace of the superficial sources by using the projector composed of these basis vectors. Signals from the deep sources are extracted by projecting the row space of the data matrix onto the direction orthogonal to the signal subspace of the superficial sources. Compared with the previously proposed beamspace signal space separation (SSS) method, the proposed algorithm is capable of suppressing much stronger interference from superficial sources. This capability is demonstrated in our computer simulation as well as experiments using phantom data. The proposed bDSSP algorithm can be a powerful tool in studies of physiological functions of midbrain and deep brain structures.

Beamspace dual signal space projection (bDSSP): a method for selective detection of deep sources in MEG measurements

NASA Astrophysics Data System (ADS)

Sekihara, Kensuke; Adachi, Yoshiaki; Kubota, Hiroshi K.; Cai, Chang; Nagarajan, Srikantan S.

2018-06-01

Objective. Magnetoencephalography (MEG) has a well-recognized weakness at detecting deeper brain activities. This paper proposes a novel algorithm for selective detection of deep sources by suppressing interference signals from superficial sources in MEG measurements. Approach. The proposed algorithm combines the beamspace preprocessing method with the dual signal space projection (DSSP) interference suppression method. A prerequisite of the proposed algorithm is prior knowledge of the location of the deep sources. The proposed algorithm first derives the basis vectors that span a local region just covering the locations of the deep sources. It then estimates the time-domain signal subspace of the superficial sources by using the projector composed of these basis vectors. Signals from the deep sources are extracted by projecting the row space of the data matrix onto the direction orthogonal to the signal subspace of the superficial sources. Main results. Compared with the previously proposed beamspace signal space separation (SSS) method, the proposed algorithm is capable of suppressing much stronger interference from superficial sources. This capability is demonstrated in our computer simulation as well as experiments using phantom data. Significance. The proposed bDSSP algorithm can be a powerful tool in studies of physiological functions of midbrain and deep brain structures.

Malignant neuroleptic syndrome following deep brain stimulation surgery: a case report.

PubMed

Themistocleous, Marios S; Boviatsis, Efstathios J; Stavrinou, Lampis C; Stathis, Pantelis; Sakas, Damianos E

2011-06-29

The neuroleptic malignant syndrome is an uncommon but dangerous complication characterized by hyperthermia, autonomic dysfunction, altered mental state, hemodynamic dysregulation, elevated serum creatine kinase, and rigor. It is most often caused by an adverse reaction to anti-psychotic drugs or abrupt discontinuation of neuroleptic or anti-parkinsonian agents. To the best of our knowledge, it has never been reported following the common practice of discontinuation of anti-parkinsonian drugs during the pre-operative preparation for deep brain stimulation surgery for Parkinson's disease. We present the first case of neuroleptic malignant syndrome associated with discontinuation of anti-parkinsonian medication prior to deep brain stimulation surgery in a 54-year-old Caucasian man. The characteristic neuroleptic malignant syndrome symptoms can be attributed to other, more common causes associated with deep brain stimulation treatment for Parkinson's disease, thus requiring a high index of clinical suspicion to timely establish the correct diagnosis. As more centers become eligible to perform deep brain stimulation, neurologists and neurosurgeons alike should be aware of this potentially fatal complication. Timely activation of the deep brain stimulation system may be important in accelerating the patient's recovery.

Evidence from a rare case study for Hebbian-like changes in structural connectivity induced by long-term deep brain stimulation.

PubMed

van Hartevelt, Tim J; Cabral, Joana; Møller, Arne; FitzGerald, James J; Green, Alexander L; Aziz, Tipu Z; Deco, Gustavo; Kringelbach, Morten L

2015-01-01

It is unclear whether Hebbian-like learning occurs at the level of long-range white matter connections in humans, i.e., where measurable changes in structural connectivity (SC) are correlated with changes in functional connectivity. However, the behavioral changes observed after deep brain stimulation (DBS) suggest the existence of such Hebbian-like mechanisms occurring at the structural level with functional consequences. In this rare case study, we obtained the full network of white matter connections of one patient with Parkinson's disease (PD) before and after long-term DBS and combined it with a computational model of ongoing activity to investigate the effects of DBS-induced long-term structural changes. The results show that the long-term effects of DBS on resting-state functional connectivity is best obtained in the computational model by changing the structural weights from the subthalamic nucleus (STN) to the putamen and the thalamus in a Hebbian-like manner. Moreover, long-term DBS also significantly changed the SC towards normality in terms of model-based measures of segregation and integration of information processing, two key concepts of brain organization. This novel approach using computational models to model the effects of Hebbian-like changes in SC allowed us to causally identify the possible underlying neural mechanisms of long-term DBS using rare case study data. In time, this could help predict the efficacy of individual DBS targeting and identify novel DBS targets.

Interleukin-6 -174 and -572 genotypes and the volume of deep gray matter in preterm infants.

PubMed

Reiman, Milla; Parkkola, Riitta; Lapinleimu, Helena; Lehtonen, Liisa; Haataja, Leena

2009-01-01

Preterm infants have smaller cerebral and cerebellar volumes at term compared with term born infants. Perinatal factors leading to the reduction in volumes are not well known. IL-6 -174 and -572 genotypes partly regulate individual immunologic responses and have also been connected with deviant neurologic development in preterm infants. Our hypothesis was that IL-6 -174 and -572 genetic polymorphisms are associated with brain lesions and regional brain volumes in very low birth weight or in very preterm infants. DNA was genotyped for IL-6 -174 and -572 polymorphisms (GG/GC/CC). Study infants (n = 175) were categorized into three groups according to the most pathologic brain finding in ultrasound examinations until term. The brain MRI performed at term was analyzed for regional brain volumes. Analyzed IL-6 genotypes did not show statistically significant association with structural brain lesions. However, IL-6 -174 CC and -572 GG genotypes associated with reduced volume of one brain region, the combined volume of basal ganglia and thalami, both in univariate and in multivariate analyses (p = 0.009, 0.009, respectively). The association of IL-6 -174 and -572 genetic polymorphisms with smaller volumes in deep gray matter provides us new ways to understand the processes leading to neurologic impairments in preterm infants.

Deep brain stimulation modulates synchrony within spatially and spectrally distinct resting state networks in Parkinson's disease.

PubMed

Oswal, Ashwini; Beudel, Martijn; Zrinzo, Ludvic; Limousin, Patricia; Hariz, Marwan; Foltynie, Tom; Litvak, Vladimir; Brown, Peter

2016-05-01

Chronic dopamine depletion in Parkinson's disease leads to progressive motor and cognitive impairment, which is associated with the emergence of characteristic patterns of synchronous oscillatory activity within cortico-basal-ganglia circuits. Deep brain stimulation of the subthalamic nucleus is an effective treatment for Parkinson's disease, but its influence on synchronous activity in cortico-basal-ganglia loops remains to be fully characterized. Here, we demonstrate that deep brain stimulation selectively suppresses certain spatially and spectrally segregated resting state subthalamic nucleus-cortical networks. To this end we used a validated and novel approach for performing simultaneous recordings of the subthalamic nucleus and cortex using magnetoencephalography (during concurrent subthalamic nucleus deep brain stimulation). Our results highlight that clinically effective subthalamic nucleus deep brain stimulation suppresses synchrony locally within the subthalamic nucleus in the low beta oscillatory range and furthermore that the degree of this suppression correlates with clinical motor improvement. Moreover, deep brain stimulation relatively selectively suppressed synchronization of activity between the subthalamic nucleus and mesial premotor regions, including the supplementary motor areas. These mesial premotor regions were predominantly coupled to the subthalamic nucleus in the high beta frequency range, but the degree of deep brain stimulation-associated suppression in their coupling to the subthalamic nucleus was not found to correlate with motor improvement. Beta band coupling between the subthalamic nucleus and lateral motor areas was not influenced by deep brain stimulation. Motor cortical coupling with subthalamic nucleus predominantly involved driving of the subthalamic nucleus, with those drives in the higher beta frequency band having much shorter net delays to subthalamic nucleus than those in the lower beta band. These observations raise the possibility that cortical connectivity with the subthalamic nucleus in the high and low beta bands may reflect coupling mediated predominantly by the hyperdirect and indirect pathways to subthalamic nucleus, respectively, and that subthalamic nucleus deep brain stimulation predominantly suppresses the former. Yet only the change in strength of local subthalamic nucleus oscillations correlates with the degree of improvement during deep brain stimulation, compatible with the current view that a strengthened hyperdirect pathway is a prerequisite for locally generated beta activity but that it is the severity of the latter that may determine or index motor impairment. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain.

Research on image retrieval using deep convolutional neural network combining L1 regularization and PRelu activation function

NASA Astrophysics Data System (ADS)

QingJie, Wei; WenBin, Wang

2017-06-01

In this paper, the image retrieval using deep convolutional neural network combined with regularization and PRelu activation function is studied, and improves image retrieval accuracy. Deep convolutional neural network can not only simulate the process of human brain to receive and transmit information, but also contains a convolution operation, which is very suitable for processing images. Using deep convolutional neural network is better than direct extraction of image visual features for image retrieval. However, the structure of deep convolutional neural network is complex, and it is easy to over-fitting and reduces the accuracy of image retrieval. In this paper, we combine L1 regularization and PRelu activation function to construct a deep convolutional neural network to prevent over-fitting of the network and improve the accuracy of image retrieval

Deep-brain magnetic stimulation promotes adult hippocampal neurogenesis and alleviates stress-related behaviors in mouse models for neuropsychiatric disorders

PubMed Central

2014-01-01

Background Repetitive Transcranial Magnetic Stimulation (rTMS)/ Deep-brain Magnetic Stimulation (DMS) is an effective therapy for various neuropsychiatric disorders including major depression disorder. The molecular and cellular mechanisms underlying the impacts of rTMS/DMS on the brain are not yet fully understood. Results Here we studied the effects of deep-brain magnetic stimulation to brain on the molecular and cellular level. We examined the adult hippocampal neurogenesis and hippocampal synaptic plasticity of rodent under stress conditions with deep-brain magnetic stimulation treatment. We found that DMS promotes adult hippocampal neurogenesis significantly and facilitates the development of adult new-born neurons. Remarkably, DMS exerts anti-depression effects in the learned helplessness mouse model and rescues hippocampal long-term plasticity impaired by restraint stress in rats. Moreover, DMS alleviates the stress response in a mouse model for Rett syndrome and prolongs the life span of these animals dramatically. Conclusions Deep-brain magnetic stimulation greatly facilitates adult hippocampal neurogenesis and maturation, also alleviates depression and stress-related responses in animal models. PMID:24512669

Sensitivity analysis of brain morphometry based on MRI-derived surface models

NASA Astrophysics Data System (ADS)

Klein, Gregory J.; Teng, Xia; Schoenemann, P. T.; Budinger, Thomas F.

1998-07-01

Quantification of brain structure is important for evaluating changes in brain size with growth and aging and for characterizing neurodegeneration disorders. Previous quantification efforts using ex vivo techniques suffered considerable error due to shrinkage of the cerebrum after extraction from the skull, deformation of slices during sectioning, and numerous other factors. In vivo imaging studies of brain anatomy avoid these problems and allow repetitive studies following progression of brain structure changes due to disease or natural processes. We have developed a methodology for obtaining triangular mesh models of the cortical surface from MRI brain datasets. The cortex is segmented from nonbrain tissue using a 2D region-growing technique combined with occasional manual edits. Once segmented, thresholding and image morphological operations (erosions and openings) are used to expose the regions between adjacent surfaces in deep cortical folds. A 2D region- following procedure is then used to find a set of contours outlining the cortical boundary on each slice. The contours on all slices are tiled together to form a closed triangular mesh model approximating the cortical surface. This model can be used for calculation of cortical surface area and volume, as well as other parameters of interest. Except for the initial segmentation of the cortex from the skull, the technique is automatic and requires only modest computation time on modern workstations. Though the use of image data avoids many of the pitfalls of ex vivo and sectioning techniques, our MRI-based technique is still vulnerable to errors that may impact the accuracy of estimated brain structure parameters. Potential inaccuracies include segmentation errors due to incorrect thresholding, missed deep sulcal surfaces, falsely segmented holes due to image noise and surface tiling artifacts. The focus of this paper is the characterization of these errors and how they affect measurements of cortical surface area and volume.

Deep brain stimulation for people with Alzheimer's disease: Anticipating potential effects on the tripartite self.

PubMed

Viaña, John Noel M; Gilbert, Frederic

2018-01-01

Memory dysfunction and cognitive impairments due to Alzheimer's disease can affect the selfhood and identity of afflicted individuals, causing distress to both people with Alzheimer's disease and their caregivers. Recently, a number of case studies and clinical trials have been conducted to determine the potential of deep brain stimulation as a therapeutic modality for people with Alzheimer's disease. Some of these studies have shown that deep brain stimulation could induce flashbacks and stabilize or even improve memory. However, deep brain stimulation itself has also been attributed as a potential threat to identity and selfhood, especially when procedure-related adverse events arise. We anticipate potential effects of deep brain stimulation for people with Alzheimer's disease on selfhood, reconciling information from medical reports, psychological, and sociological investigations on the impacts of deep brain stimulation or Alzheimer's disease on selfhood. A tripartite model of the self that extends the scope of Rom Harré's and Steve Sabat's social constructionist framework was used. In this model, potential effects of deep brain stimulation for Alzheimer's disease on Self 1 or singularity through use of first-person indexicals, and gestures of self-reference, attribution, and recognition; Self 2 or past and present attributes, knowledge of these characteristics, and continuity of narrative identity; and Self 3 or the relational and social self are explored. The ethical implications of potential effects of deep brain stimulation for Alzheimer's disease on the tripartite self are then highlighted, focusing on adapting informed consent procedures and care provided throughout the trial to account for both positive and negative plausible effects on Self 1, Self 2, and Self 3.

False recognition depends on depth of prior word processing: a magnetoencephalographic (MEG) study.

PubMed

Walla, P; Hufnagl, B; Lindinger, G; Deecke, L; Imhof, H; Lang, W

2001-04-01

Brain activity was measured with a whole head magnetoencephalograph (MEG) during the test phases of word recognition experiments. Healthy young subjects had to discriminate between previously presented and new words. During prior study phases two different levels of word processing were provided according to two different kinds of instructions (shallow and deep encoding). Event-related fields (ERFs) associated with falsely recognized words (false alarms) were found to depend on the depth of processing during the prior study phase. False alarms elicited higher brain activity (as reflected by dipole strength) in case of prior deep encoding as compared to shallow encoding between 300 and 500 ms after stimulus onset at temporal brain areas. Between 500 and 700 ms we found evidence for differences in the involvement of neural structures related to both conditions of false alarms. Furthermore, the number of false alarms was found to depend on depth of processing. Shallow encoding led to a higher number of false alarms than deep encoding. All data are discussed as strong support for the ideas that a certain level of word processing is performed by a distinct set of neural systems and that the same neural systems which encode information are reactivated during the retrieval.

Deep brain stimulation of the subthalamic nucleus alters the cortical profile of response inhibition in the beta frequency band: a scalp EEG study in Parkinson's disease

PubMed Central

Swann, Nicole; Poizner, Howard; Houser, Melissa; Gould, Sherrie; Greenhouse, Ian; Cai, Weidong; Strunk, Jon; George, Jobi; Aron, Adam R

2011-01-01

Stopping an initiated response could be implemented by a fronto-basal-ganglia circuit, including the right inferior frontal cortex (rIFC) and the subthalamic nucleus (STN). Intracranial recording studies in humans reveal an increase in beta-band power (~16-20 Hz) within the rIFC and STN when a response is stopped. This suggests that the beta-band could be important for communication in this network. If this is the case, then altering one region should affect the electrophysiological response at the other. We addressed this hypothesis by recording scalp EEG during a stop task while modulating STN activity with deep brain stimulation. We studied 15 human patients with Parkinson's Disease and 15 matched healthy control subjects. Behaviorally, patients OFF stimulation were slower than controls to stop their response. Moreover, stopping speed was improved for ON compared to OFF stimulation. For scalp EEG, there was greater beta power, around the time of stopping, for patients ON compared to OFF stimulation. This effect was stronger over the right compared to left frontal cortex, consistent with the putative right-lateralization of the stopping network. Thus, deep brain stimulation of the STN improved behavioral stopping performance and increased the beta-band response over the right frontal cortex. These results complement other evidence for a structurally-connected, functional, circuit between right frontal cortex and the basal ganglia. The results also suggest that deep brain stimulation of the STN may improve task performance by increasing the fidelity of information transfer within a fronto-basal ganglia circuit. PMID:21490213

Swept-source optical coherence tomography powered by a 1.3-μm vertical cavity surface emitting laser enables 2.3-mm-deep brain imaging in mice in vivo

NASA Astrophysics Data System (ADS)

Choi, Woo June; Wang, Ruikang K.

2015-10-01

We report noninvasive, in vivo optical imaging deep within a mouse brain by swept-source optical coherence tomography (SS-OCT), enabled by a 1.3-μm vertical cavity surface emitting laser (VCSEL). VCSEL SS-OCT offers a constant signal sensitivity of 105 dB throughout an entire depth of 4.25 mm in air, ensuring an extended usable imaging depth range of more than 2 mm in turbid biological tissue. Using this approach, we show deep brain imaging in mice with an open-skull cranial window preparation, revealing intact mouse brain anatomy from the superficial cerebral cortex to the deep hippocampus. VCSEL SS-OCT would be applicable to small animal studies for the investigation of deep tissue compartments in living brains where diseases such as dementia and tumor can take their toll.

Frameless Stereotactic Insertion of Viewsite Brain Access System with Microscope-Mounted Tracking Device for Resection of Deep Brain Lesions: Technical Report

PubMed Central

Chakraborty, Shamik; Lall, Rohan; Fanous, Andrew A; Boockvar, John; Langer, David J

2017-01-01

The surgical management of deep brain tumors is often challenging due to the limitations of stereotactic needle biopsies and the morbidity associated with transcortical approaches. We present a novel microscopic navigational technique utilizing the Viewsite Brain Access System (VBAS) (Vycor Medical, Boca Raton, FL, USA) for resection of a deep parietal periventricular high-grade glioma as well as another glioma and a cavernoma with no related morbidity. The approach utilized a navigational tracker mounted on a microscope, which was set to the desired trajectory and depth. It allowed gentle continuous insertion of the VBAS directly to a deep lesion under continuous microscopic visualization, increasing safety by obviating the need to look up from the microscope and thus avoiding loss of trajectory. This technique has broad value for the resection of a variety of deep brain lesions. PMID:28331774

Frameless Stereotactic Insertion of Viewsite Brain Access System with Microscope-Mounted Tracking Device for Resection of Deep Brain Lesions: Technical Report.

PubMed

White, Tim; Chakraborty, Shamik; Lall, Rohan; Fanous, Andrew A; Boockvar, John; Langer, David J

2017-02-04

The surgical management of deep brain tumors is often challenging due to the limitations of stereotactic needle biopsies and the morbidity associated with transcortical approaches. We present a novel microscopic navigational technique utilizing the Viewsite Brain Access System (VBAS) (Vycor Medical, Boca Raton, FL, USA) for resection of a deep parietal periventricular high-grade glioma as well as another glioma and a cavernoma with no related morbidity. The approach utilized a navigational tracker mounted on a microscope, which was set to the desired trajectory and depth. It allowed gentle continuous insertion of the VBAS directly to a deep lesion under continuous microscopic visualization, increasing safety by obviating the need to look up from the microscope and thus avoiding loss of trajectory. This technique has broad value for the resection of a variety of deep brain lesions.

A Stepwise Approach: Decreasing Infection in Deep Brain Stimulation for Childhood Dystonic Cerebral Palsy.

PubMed

Johans, Stephen J; Swong, Kevin N; Hofler, Ryan C; Anderson, Douglas E

2017-09-01

Dystonia is a movement disorder characterized by involuntary muscle contractions, which cause twisting movements or abnormal postures. Deep brain stimulation has been used to improve the quality of life for secondary dystonia caused by cerebral palsy. Despite being a viable treatment option for childhood dystonic cerebral palsy, deep brain stimulation is associated with a high rate of infection in children. The authors present a small series of patients with dystonic cerebral palsy who underwent a stepwise approach for bilateral globus pallidus interna deep brain stimulation placement in order to decrease the rate of infection. Four children with dystonic cerebral palsy who underwent a total of 13 surgical procedures (electrode and battery placement) were identified via a retrospective review. There were zero postoperative infections. Using a multistaged surgical plan for pediatric patients with dystonic cerebral palsy undergoing deep brain stimulation may help to reduce the risk of infection.

Deep grey matter growth predicts neurodevelopmental outcomes in very preterm children.

PubMed

Young, Julia M; Powell, Tamara L; Morgan, Benjamin R; Card, Dallas; Lee, Wayne; Smith, Mary Lou; Sled, John G; Taylor, Margot J

2015-05-01

We evaluated whether the volume and growth rate of critical brain structures measured by MRI in the first weeks of life following very preterm (<32/40 weeks) birth could predict subsequent neurodevelopmental outcomes at 4 years of age. A significant proportion of children born very prematurely have cognitive deficits, but these problems are often only detected at early school age. Structural T2-weighted magnetic resonance images were acquired in 96 very preterm neonates scanned within 2 weeks of birth and 70 of these at term-equivalent age. An automated 3D image analysis procedure was used to measure the volume of selected brain structures across all scans and time points. At 4 years of age, 53 children returned for neuropsychological assessments evaluating IQ, language and visual motor integration. Associations with maternal education and perinatal measures were also explored. Multiple regression analyses revealed that growth of the caudate and globus pallidus between preterm birth and term-equivalent age predicted visual motor integration scores after controlling for sex and gestational age. Further associations were found between caudate and putamen growth with IQ and language scores. Analyses at either preterm or term-equivalent age only found associations between normalized deep grey matter growth and visual motor integration scores at term-equivalent age. Maternal education levels were associated with measures of IQ and language, but not visual motor integration. Thalamic growth was additionally linked with perinatal measures and presence of white matter lesions. These results highlight deep grey matter growth rates as promising biomarkers of long-term outcomes following very preterm birth, and contribute to our understanding of the brain-behaviour relations in these children. Copyright © 2015 Elsevier Inc. All rights reserved.

Fast and robust segmentation of the striatum using deep convolutional neural networks.

PubMed

Choi, Hongyoon; Jin, Kyong Hwan

2016-12-01

Automated segmentation of brain structures is an important task in structural and functional image analysis. We developed a fast and accurate method for the striatum segmentation using deep convolutional neural networks (CNN). T1 magnetic resonance (MR) images were used for our CNN-based segmentation, which require neither image feature extraction nor nonlinear transformation. We employed two serial CNN, Global and Local CNN: The Global CNN determined approximate locations of the striatum. It performed a regression of input MR images fitted to smoothed segmentation maps of the striatum. From the output volume of Global CNN, cropped MR volumes which included the striatum were extracted. The cropped MR volumes and the output volumes of Global CNN were used for inputs of Local CNN. Local CNN predicted the accurate label of all voxels. Segmentation results were compared with a widely used segmentation method, FreeSurfer. Our method showed higher Dice Similarity Coefficient (DSC) (0.893±0.017 vs. 0.786±0.015) and precision score (0.905±0.018 vs. 0.690±0.022) than FreeSurfer-based striatum segmentation (p=0.06). Our approach was also tested using another independent dataset, which showed high DSC (0.826±0.038) comparable with that of FreeSurfer. Comparison with existing method Segmentation performance of our proposed method was comparable with that of FreeSurfer. The running time of our approach was approximately three seconds. We suggested a fast and accurate deep CNN-based segmentation for small brain structures which can be widely applied to brain image analysis. Copyright © 2016 Elsevier B.V. All rights reserved.

Gradual emergence of spontaneous correlated brain activity during fading of general anesthesia in rats: Evidences from fMRI and local field potentials

PubMed Central

Bettinardi, Ruggero G.; Tort-Colet, Núria; Ruiz-Mejias, Marcel; Sanchez-Vives, Maria V.; Deco, Gustavo

2015-01-01

Intrinsic brain activity is characterized by the presence of highly structured networks of correlated fluctuations between different regions of the brain. Such networks encompass different functions, whose properties are known to be modulated by the ongoing global brain state and are altered in several neurobiological disorders. In the present study, we induced a deep state of anesthesia in rats by means of a ketamine/medetomidine peritoneal injection, and analyzed the time course of the correlation between the brain activity in different areas while anesthesia spontaneously decreased over time. We compared results separately obtained from fMRI and local field potentials (LFPs) under the same anesthesia protocol, finding that while most profound phases of anesthesia can be described by overall sparse connectivity, stereotypical activity and poor functional integration, during lighter states different frequency-specific functional networks emerge, endowing the gradual restoration of structured large-scale activity seen during rest. Noteworthy, our in vivo results show that those areas belonging to the same functional network (the default-mode) exhibited sustained correlated oscillations around 10 Hz throughout the protocol, suggesting the presence of a specific functional backbone that is preserved even during deeper phases of anesthesia. Finally, the overall pattern of results obtained from both imaging and in vivo-recordings suggests that the progressive emergence from deep anesthesia is reflected by a corresponding gradual increase of organized correlated oscillations across the cortex. PMID:25804643

Attenuation correction for brain PET imaging using deep neural network based on dixon and ZTE MR images.

PubMed

Gong, Kuang; Yang, Jaewon; Kim, Kyungsang; El Fakhri, Georges; Seo, Youngho; Li, Quanzheng

2018-05-23

Positron Emission Tomography (PET) is a functional imaging modality widely used in neuroscience studies. To obtain meaningful quantitative results from PET images, attenuation correction is necessary during image reconstruction. For PET/MR hybrid systems, PET attenuation is challenging as Magnetic Resonance (MR) images do not reflect attenuation coefficients directly. To address this issue, we present deep neural network methods to derive the continuous attenuation coefficients for brain PET imaging from MR images. With only Dixon MR images as the network input, the existing U-net structure was adopted and analysis using forty patient data sets shows it is superior than other Dixon based methods. When both Dixon and zero echo time (ZTE) images are available, we have proposed a modified U-net structure, named GroupU-net, to efficiently make use of both Dixon and ZTE information through group convolution modules when the network goes deeper. Quantitative analysis based on fourteen real patient data sets demonstrates that both network approaches can perform better than the standard methods, and the proposed network structure can further reduce the PET quantification error compared to the U-net structure. © 2018 Institute of Physics and Engineering in Medicine.

Potential predictors for the amount of intra-operative brain shift during deep brain stimulation surgery

NASA Astrophysics Data System (ADS)

Datteri, Ryan; Pallavaram, Srivatsan; Konrad, Peter E.; Neimat, Joseph S.; D'Haese, Pierre-François; Dawant, Benoit M.

2011-03-01

A number of groups have reported on the occurrence of intra-operative brain shift during deep brain stimulation (DBS) surgery. This has a number of implications for the procedure including an increased chance of intra-cranial bleeding and complications due to the need for more exploratory electrodes to account for the brain shift. It has been reported that the amount of pneumocephalus or air invasion into the cranial cavity due to the opening of the dura correlates with intraoperative brain shift. Therefore, pre-operatively predicting the amount of pneumocephalus expected during surgery is of interest toward accounting for brain shift. In this study, we used 64 DBS patients who received bilateral electrode implantations and had a post-operative CT scan acquired immediately after surgery (CT-PI). For each patient, the volumes of the pneumocephalus, left ventricle, right ventricle, third ventricle, white matter, grey matter, and cerebral spinal fluid were calculated. The pneumocephalus was calculated from the CT-PI utilizing a region growing technique that was initialized with an atlas-based image registration method. A multi-atlas-based image segmentation method was used to segment out the ventricles of each patient. The Statistical Parametric Mapping (SPM) software package was utilized to calculate the volumes of the cerebral spinal fluid (CSF), white matter and grey matter. The volume of individual structures had a moderate correlation with pneumocephalus. Utilizing a multi-linear regression between the volume of the pneumocephalus and the statistically relevant individual structures a Pearson's coefficient of r = 0.4123 (p = 0.0103) was found. This study shows preliminary results that could be used to develop a method to predict the amount of pneumocephalus ahead of the surgery.

Innovations in deep brain stimulation methodology.

PubMed

Kühn, Andrea A; Volkmann, Jens

2017-01-01

Deep brain stimulation is a powerful clinical method for movement disorders that no longer respond satisfactorily to pharmacological management, but its progress has been hampered by stagnation in technological procedure solutions and device development. Recently, the combined research efforts of bioengineers, neuroscientists, and clinicians have helped to better understand the mechanisms of deep brain stimulation, and solutions for the translational roadblock are emerging. Here, we define the needs for methodological advances in deep brain stimulation from a neurophysiological perspective and describe technological solutions that are currently evaluated for near-term clinical application. © 2016 International Parkinson and Movement Disorder Society. © 2016 International Parkinson and Movement Disorder Society.

Deep brain stimulation modulates synchrony within spatially and spectrally distinct resting state networks in Parkinson’s disease

PubMed Central

Oswal, Ashwini; Beudel, Martijn; Zrinzo, Ludvic; Limousin, Patricia; Hariz, Marwan; Foltynie, Tom; Litvak, Vladimir

2016-01-01

Abstract Chronic dopamine depletion in Parkinson’s disease leads to progressive motor and cognitive impairment, which is associated with the emergence of characteristic patterns of synchronous oscillatory activity within cortico-basal-ganglia circuits. Deep brain stimulation of the subthalamic nucleus is an effective treatment for Parkinson’s disease, but its influence on synchronous activity in cortico-basal-ganglia loops remains to be fully characterized. Here, we demonstrate that deep brain stimulation selectively suppresses certain spatially and spectrally segregated resting state subthalamic nucleus–cortical networks. To this end we used a validated and novel approach for performing simultaneous recordings of the subthalamic nucleus and cortex using magnetoencephalography (during concurrent subthalamic nucleus deep brain stimulation). Our results highlight that clinically effective subthalamic nucleus deep brain stimulation suppresses synchrony locally within the subthalamic nucleus in the low beta oscillatory range and furthermore that the degree of this suppression correlates with clinical motor improvement. Moreover, deep brain stimulation relatively selectively suppressed synchronization of activity between the subthalamic nucleus and mesial premotor regions, including the supplementary motor areas. These mesial premotor regions were predominantly coupled to the subthalamic nucleus in the high beta frequency range, but the degree of deep brain stimulation-associated suppression in their coupling to the subthalamic nucleus was not found to correlate with motor improvement. Beta band coupling between the subthalamic nucleus and lateral motor areas was not influenced by deep brain stimulation. Motor cortical coupling with subthalamic nucleus predominantly involved driving of the subthalamic nucleus, with those drives in the higher beta frequency band having much shorter net delays to subthalamic nucleus than those in the lower beta band. These observations raise the possibility that cortical connectivity with the subthalamic nucleus in the high and low beta bands may reflect coupling mediated predominantly by the hyperdirect and indirect pathways to subthalamic nucleus, respectively, and that subthalamic nucleus deep brain stimulation predominantly suppresses the former. Yet only the change in strength of local subthalamic nucleus oscillations correlates with the degree of improvement during deep brain stimulation, compatible with the current view that a strengthened hyperdirect pathway is a prerequisite for locally generated beta activity but that it is the severity of the latter that may determine or index motor impairment. PMID:27017189

Brain and sense organ anatomy and histology of the Falkland Islands mullet, Eleginops maclovinus (Eleginopidae), the sister group of the Antarctic notothenioid fishes (Perciformes: Notothenioidei).

PubMed

Eastman, Joseph T; Lannoo, Michael J

2008-01-01

The perciform notothenioid fish Eleginops maclovinus, representing the monotypic family Eleginopidae, has a non-Antarctic distribution in the Falkland Islands and southern South America. It is the sister group of the five families and 103 species of Antarctic notothenioids that dominate the cold shelf waters of Antarctica. Eleginops is the ideal subject for documenting the ancestral morphology of nervous and sensory systems that have not had historical exposure to the unusual Antarctic thermal and light regimes, and for comparing these systems with those of the phyletically derived Antarctic species. We present a detailed description of the brain and cranial nerves of Eleginops and ask how does the neural and sensory morphology of this non-Antarctic notothenioid differ from that seen in the phyletically derived Antarctic notothenioids? The brain of Eleginops is similar to those of visually oriented temperate and tropical perciforms. The tectum is smaller but it has well-developed olfactory and mechanoreceptive lateral line areas and a large, caudally projecting corpus cerebellum. Eye diameter is about twofold smaller in Eleginops than in many Antarctic species. Eleginops has a duplex (rod and cone) retina with single and occasional twin cones conspicuous centrally. Ocular vascular structures include a large choroid rete mirabile and a small lentiform body; a falciform process and hyaloid arteries are absent. The olfactory rosette is oval with 50-55 lamellae, a large number for notothenioids. The inconspicuous bony canals of the cephalic lateral line system are simple with membranous secondary branches that lack neuromasts. In Antarctic species, the corpus cerebellum is the most variable brain region, ranging in size from large and caudally projecting to small and round. "Stalked" brains showing reduction in the size of the telencephalon, tectum, and corpus cerebellum are present in the deep-living artedidraconid Dolloidraco longedorsalis and in most of the deep-living members of the Bathydraconini. Eye diameter is generally larger in Antarctic species but there is a phylogenetic loss of cellularity in the retina, including cone photoreceptors. Some deep-living Antarctic species have lost most of their cones. Mechanosensation is expanded in some species, most notably the nototheniid Pleuragramma antarcticum, the artedidraconid genera Dolloidraco and Pogonophryne, and the deep living members of the bathydraconid tribe Bathydraconini. Reduction in retinal cellularity, expansion of mechanoreception, and stalking are the most noteworthy departures from the morphology seen in Eleginops. These features reflect a modest depth or deep-sea effect, and they are not uniquely "Antarctic" attributes. Thus, at the level of organ system morphology, perciform brain and sensory systems are suitable for conditions on the Antarctic shelf, with only minor alterations in structure in directions exhibited by other fish groups inhabiting deep water. Notothenioids retain a relative balance among their array of senses that reflects their heritage as inshore perciforms. (c) 2007 Wiley-Liss, Inc.

Optogenetic interrogation of neural circuits: technology for probing mammalian brain structures

PubMed Central

Zhang, Feng; Gradinaru, Viviana; Adamantidis, Antoine R; Durand, Remy; Airan, Raag D; de Lecea, Luis; Deisseroth, Karl

2015-01-01

Elucidation of the neural substrates underlying complex animal behaviors depends on precise activity control tools, as well as compatible readout methods. Recent developments in optogenetics have addressed this need, opening up new possibilities for systems neuroscience. Interrogation of even deep neural circuits can be conducted by directly probing the necessity and sufficiency of defined circuit elements with millisecond-scale, cell type-specific optical perturbations, coupled with suitable readouts such as electrophysiology, optical circuit dynamics measures and freely moving behavior in mammals. Here we collect in detail our strategies for delivering microbial opsin genes to deep mammalian brain structures in vivo, along with protocols for integrating the resulting optical control with compatible readouts (electrophysiological, optical and behavioral). The procedures described here, from initial virus preparation to systems-level functional readout, can be completed within 4–5 weeks. Together, these methods may help in providing circuit-level insight into the dynamics underlying complex mammalian behaviors in health and disease. PMID:20203662

Spinal cord stimulation alleviates motor deficits in a primate model of Parkinson disease.

PubMed

Santana, Maxwell B; Halje, Pär; Simplício, Hougelle; Richter, Ulrike; Freire, Marco Aurelio M; Petersson, Per; Fuentes, Romulo; Nicolelis, Miguel A L

2014-11-19

Although deep brain electrical stimulation can alleviate the motor symptoms of Parkinson disease (PD), just a small fraction of patients with PD can take advantage of this procedure due to its invasive nature. A significantly less invasive method--epidural spinal cord stimulation (SCS)--has been suggested as an alternative approach for symptomatic treatment of PD. However, the mechanisms underlying motor improvements through SCS are unknown. Here, we show that SCS reproducibly alleviates motor deficits in a primate model of PD. Simultaneous neuronal recordings from multiple structures of the cortico-basal ganglia-thalamic loop in parkinsonian monkeys revealed abnormal highly synchronized neuronal activity within each of these structures and excessive functional coupling among them. SCS disrupted this pathological circuit behavior in a manner that mimics the effects caused by pharmacological dopamine replacement therapy or deep brain stimulation. These results suggest that SCS should be considered as an additional treatment option for patients with PD. Copyright © 2014 Elsevier Inc. All rights reserved.

[Neurological and technical aspects of deep brain stimulation].

PubMed

Voges, J; Krauss, J K

2010-06-01

Deep brain stimulation (DBS) is an important component of the therapy of movement disorders and has almost completely replaced high-frequency coagulation of brain tissue in stereotactic neurosurgery. Despite the functional efficacy of DBS, which in parts is documented on the highest evidence level, the underlying mechanisms are still not completely understood. According to the current state of knowledge electrophysiological and functional data give evidence that high-frequency DBS has an inhibitory effect around the stimulation electrode whilst at the same time axons entering or leaving the stimulated brain area are excited leading to modulation of neuronal networks. The latter effect modifies pathological discharges of neurons in key structures of the basal ganglia network (e.g. irregular bursting activity, oscillations or synchronization) which are found in particular movement disorders such as Parkinson' s disease or dystonia. The introduction of technical standards, such as the integration of high resolution MRI into computer-assisted treatment planning, in combination with special treatment planning software have contributed significantly to the reduction of severe surgical complications (frequency of intracranial hemorrhaging 1-3%) in recent years. Future developments will address the modification of hardware components of the stimulation system, the evaluation of new brain target areas, the simultaneous stimulation of different brain areas and the assessment of different stimulation paradigms (high-frequency vs low-frequency DBS).

Deep Independence Network Analysis of Structural Brain Imaging: Application to Schizophrenia

PubMed Central

Castro, Eduardo; Hjelm, R. Devon; Plis, Sergey M.; Dinh, Laurent; Turner, Jessica A.; Calhoun, Vince D.

2016-01-01

Linear independent component analysis (ICA) is a standard signal processing technique that has been extensively used on neuroimaging data to detect brain networks with coherent brain activity (functional MRI) or covarying structural patterns (structural MRI). However, its formulation assumes that the measured brain signals are generated by a linear mixture of the underlying brain networks and this assumption limits its ability to detect the inherent nonlinear nature of brain interactions. In this paper, we introduce nonlinear independent component estimation (NICE) to structural MRI data to detect abnormal patterns of gray matter concentration in schizophrenia patients. For this biomedical application, we further addressed the issue of model regularization of nonlinear ICA by performing dimensionality reduction prior to NICE, together with an appropriate control of the complexity of the model and the usage of a proper approximation of the probability distribution functions of the estimated components. We show that our results are consistent with previous findings in the literature, but we also demonstrate that the incorporation of nonlinear associations in the data enables the detection of spatial patterns that are not identified by linear ICA. Specifically, we show networks including basal ganglia, cerebellum and thalamus that show significant differences in patients versus controls, some of which show distinct nonlinear patterns. PMID:26891483

Neuroprotection trek--the next generation: neuromodulation I. Techniques--deep brain stimulation, vagus nerve stimulation, and transcranial magnetic stimulation

NASA Technical Reports Server (NTRS)

Andrews, Russell J.

2003-01-01

Neuromodulation denotes controlled electrical stimulation of the central or peripheral nervous system. The three forms of neuromodulation described in this paper-deep brain stimulation, vagus nerve stimulation, and transcranial magnetic stimulation-were chosen primarily for their demonstrated or potential clinical usefulness. Deep brain stimulation is a completely implanted technique for improving movement disorders, such as Parkinson's disease, by very focal electrical stimulation of the brain-a technique that employs well-established hardware (electrode and pulse generator/battery). Vagus nerve stimulation is similar to deep brain stimulation in being well-established (for the treatment of refractory epilepsy), completely implanted, and having hardware that can be considered standard at the present time. Vagus nerve stimulation differs from deep brain stimulation, however, in that afferent stimulation of the vagus nerve results in diffuse effects on many regions throughout the brain. Although use of deep brain stimulation for applications beyond movement disorders will no doubt involve placing the stimulating electrode(s) in regions other than the thalamus, subthalamus, or globus pallidus, the use of vagus nerve stimulation for applications beyond epilepsy-for example, depression and eating disorders-is unlikely to require altering the hardware significantly (although stimulation protocols may differ). Transcranial magnetic stimulation is an example of an external or non-implanted, intermittent (at least given the current state of the hardware) stimulation technique, the clinical value of which for neuromodulation and neuroprotection remains to be determined.

Neuroprotection trek--the next generation: neuromodulation I. Techniques--deep brain stimulation, vagus nerve stimulation, and transcranial magnetic stimulation.

PubMed

Andrews, Russell J

2003-05-01

Neuromodulation denotes controlled electrical stimulation of the central or peripheral nervous system. The three forms of neuromodulation described in this paper-deep brain stimulation, vagus nerve stimulation, and transcranial magnetic stimulation-were chosen primarily for their demonstrated or potential clinical usefulness. Deep brain stimulation is a completely implanted technique for improving movement disorders, such as Parkinson's disease, by very focal electrical stimulation of the brain-a technique that employs well-established hardware (electrode and pulse generator/battery). Vagus nerve stimulation is similar to deep brain stimulation in being well-established (for the treatment of refractory epilepsy), completely implanted, and having hardware that can be considered standard at the present time. Vagus nerve stimulation differs from deep brain stimulation, however, in that afferent stimulation of the vagus nerve results in diffuse effects on many regions throughout the brain. Although use of deep brain stimulation for applications beyond movement disorders will no doubt involve placing the stimulating electrode(s) in regions other than the thalamus, subthalamus, or globus pallidus, the use of vagus nerve stimulation for applications beyond epilepsy-for example, depression and eating disorders-is unlikely to require altering the hardware significantly (although stimulation protocols may differ). Transcranial magnetic stimulation is an example of an external or non-implanted, intermittent (at least given the current state of the hardware) stimulation technique, the clinical value of which for neuromodulation and neuroprotection remains to be determined.

Advanced MR Imaging of the Human Nucleus Accumbens--Additional Guiding Tool for Deep Brain Stimulation.

PubMed

Lucas-Neto, Lia; Reimão, Sofia; Oliveira, Edson; Rainha-Campos, Alexandre; Sousa, João; Nunes, Rita G; Gonçalves-Ferreira, António; Campos, Jorge G

2015-07-01

The human nucleus accumbens (Acc) has become a target for deep brain stimulation (DBS) in some neuropsychiatric disorders. Nonetheless, even with the most recent advances in neuroimaging it remains difficult to accurately delineate the Acc and closely related subcortical structures, by conventional MRI sequences. It is our purpose to perform a MRI study of the human Acc and to determine whether there are reliable anatomical landmarks that enable the precise location and identification of the nucleus and its core/shell division. For the Acc identification and delineation, based on anatomical landmarks, T1WI, T1IR and STIR 3T-MR images were acquired in 10 healthy volunteers. Additionally, 32-direction DTI was obtained for Acc segmentation. Seed masks for the Acc were generated with FreeSurfer and probabilistic tractography was performed using FSL. The probability of connectivity between the seed voxels and distinct brain areas was determined and subjected to k-means clustering analysis, defining 2 different regions. With conventional T1WI, the Acc borders are better defined through its surrounding anatomical structures. The DTI color-coded vector maps and IR sequences add further detail in the Acc identification and delineation. Additionally, using probabilistic tractography it is possible to segment the Acc into a core and shell division and establish its structural connectivity with different brain areas. Advanced MRI techniques allow in vivo delineation and segmentation of the human Acc and represent an additional guiding tool in the precise and safe target definition for DBS. © 2015 International Neuromodulation Society.

Connectivity Predicts Deep Brain Stimulation Outcome in Parkinson Disease

PubMed Central

Horn, Andreas; Reich, Martin; Vorwerk, Johannes; Li, Ningfei; Wenzel, Gregor; Fang, Qianqian; Schmitz-Hübsch, Tanja; Nickl, Robert; Kupsch, Andreas; Volkmann, Jens; Kühn, Andrea A.; Fox, Michael D.

2018-01-01

Objective The benefit of deep brain stimulation (DBS) for Parkinson disease (PD) may depend on connectivity between the stimulation site and other brain regions, but which regions and whether connectivity can predict outcome in patients remain unknown. Here, we identify the structural and functional connectivity profile of effective DBS to the subthalamic nucleus (STN) and test its ability to predict outcome in an independent cohort. Methods A training dataset of 51 PD patients with STN DBS was combined with publicly available human connectome data (diffusion tractography and resting state functional connectivity) to identify connections reliably associated with clinical improvement (motor score of the Unified Parkinson Disease Rating Scale [UPDRS]). This connectivity profile was then used to predict outcome in an independent cohort of 44 patients from a different center. Results In the training dataset, connectivity between the DBS electrode and a distributed network of brain regions correlated with clinical response including structural connectivity to supplementary motor area and functional anticorrelation to primary motor cortex (p<0.001). This same connectivity profile predicted response in an independent patient cohort (p<0.01). Structural and functional connectivity were independent predictors of clinical improvement (p<0.001) and estimated response in individual patients with an average error of 15% UPDRS improvement. Results were similar using connectome data from normal subjects or a connectome age, sex, and disease matched to our DBS patients. Interpretation Effective STN DBS for PD is associated with a specific connectivity profile that can predict clinical outcome across independent cohorts. This prediction does not require specialized imaging in PD patients themselves. PMID:28586141

A multiscale cerebral neurochemical connectome of the rat brain

PubMed Central

Schöttler, Judith; Ercsey-Ravasz, Maria; Cosa-Linan, Alejandro; Varga, Melinda; Toroczkai, Zoltan; Spanagel, Rainer

2017-01-01

Understanding the rat neurochemical connectome is fundamental for exploring neuronal information processing. By using advanced data mining, supervised machine learning, and network analysis, this study integrates over 5 decades of neuroanatomical investigations into a multiscale, multilayer neurochemical connectome of the rat brain. This neurochemical connectivity database (ChemNetDB) is supported by comprehensive systematically-determined receptor distribution maps. The rat connectome has an onion-type structural organization and shares a number of structural features with mesoscale connectomes of mouse and macaque. Furthermore, we demonstrate that extremal values of graph theoretical measures (e.g., degree and betweenness) are associated with evolutionary-conserved deep brain structures such as amygdala, bed nucleus of the stria terminalis, dorsal raphe, and lateral hypothalamus, which regulate primitive, yet fundamental functions, such as circadian rhythms, reward, aggression, anxiety, and fear. The ChemNetDB is a freely available resource for systems analysis of motor, sensory, emotional, and cognitive information processing. PMID:28671956

Deep brain stimulation for severe treatment-resistant obsessive-compulsive disorder: An open-label case series.

PubMed

Farrand, Sarah; Evans, Andrew H; Mangelsdorf, Simone; Loi, Samantha M; Mocellin, Ramon; Borham, Adam; Bevilacqua, JoAnne; Blair-West, Scott; Walterfang, Mark A; Bittar, Richard G; Velakoulis, Dennis

2017-09-01

Deep brain stimulation can be of benefit in carefully selected patients with severe intractable obsessive-compulsive disorder. The aim of this paper is to describe the outcomes of the first seven deep brain stimulation procedures for obsessive-compulsive disorder undertaken at the Neuropsychiatry Unit, Royal Melbourne Hospital. The primary objective was to assess the response to deep brain stimulation treatment utilising the Yale-Brown Obsessive Compulsive Scale as a measure of symptom severity. Secondary objectives include assessment of depression and anxiety, as well as socio-occupational functioning. Patients with severe obsessive-compulsive disorder were referred by their treating psychiatrist for assessment of their suitability for deep brain stimulation. Following successful application to the Psychosurgery Review Board, patients proceeded to have deep brain stimulation electrodes implanted in either bilateral nucleus accumbens or bed nucleus of stria terminalis. Clinical assessment and symptom rating scales were undertaken pre- and post-operatively at 6- to 8-week intervals. Rating scales used included the Yale-Brown Obsessive Compulsive Scale, Obsessive Compulsive Inventory, Depression Anxiety Stress Scale and Social and Occupational Functioning Assessment Scale. Seven patients referred from four states across Australia underwent deep brain stimulation surgery and were followed for a mean of 31 months (range, 8-54 months). The sample included four females and three males, with a mean age of 46 years (range, 37-59 years) and mean duration of obsessive-compulsive disorder of 25 years (range, 15-38 years) at the time of surgery. The time from first assessment to surgery was on average 18 months. All patients showed improvement on symptom severity rating scales. Three patients showed a full response, defined as greater than 35% improvement in Yale-Brown Obsessive Compulsive Scale score, with the remaining showing responses between 7% and 20%. Deep brain stimulation was an effective treatment for obsessive-compulsive disorder in these highly selected patients. The extent of the response to deep brain stimulation varied between patients, as well as during the course of treatment for each patient. The results of this series are comparable with the literature, as well as having similar efficacy to ablative psychosurgery techniques such as capsulotomy and cingulotomy. Deep brain stimulation provides advantages over lesional psychosurgery but is more expensive and requires significant multidisciplinary input at all stages, pre- and post-operatively, ideally within a specialised tertiary clinical and/or academic centre. Ongoing research is required to better understand the neurobiological basis for obsessive-compulsive disorder and how this can be manipulated with deep brain stimulation to further improve the efficacy of this emerging treatment.

Retrograde Cerebral Perfusion Results in Better Perfusion to the Striatum Than the Cerebral Cortex During Deep Hypothermic Circulatory Arrest: A Microdialysis Study.

PubMed

Liang, Meng-Ya; Chen, Guang-Xian; Tang, Zhi-Xian; Rong, Jian; Yao, Jian-ping; Wu, Zhong-Kai

2016-03-01

It remains controversial whether contemporary cerebral perfusion techniques, utilized during deep hypothermic circulatory arrest (DHCA), establish adequate perfusion to deep structures in the brain. This study aimed to investigate whether selective antegrade cerebral perfusion (SACP) or retrograde cerebral perfusion (RCP) can provide perfusion equally to various anatomical positions in the brain using metabolic evidence obtained from microdialysis. Eighteen piglets were randomly assigned to 40 min of circulatory arrest (CA) at 18°C without cerebral perfusion (DHCA group, n = 6) or with SACP (SACP group, n = 6) or RCP (RCP group, n = 6). Microdialysis parameters (glucose, lactate, pyruvate, and glutamate) were measured every 30 min in cortex and striatum. After 3 h of reperfusion, brain tissue was harvested for Western blot measurement of α-spectrin. After 40 min of CA, the DHCA group showed marked elevations of lactate and glycerol and a reduction in glucose in the microdialysis perfusate (all P < 0.05). The changes in glucose, lactate, and glycerol in the perfusate and α-spectrin expression in brain tissue were similar between cortex and striatum in the SACP group (all P > 0.05). In the RCP group, the cortex exhibited lower glucose, higher lactate, and higher glycerol in the perfusate and higher α-spectrin expression in brain tissue compared with the striatum (all P < 0.05). Glutamate showed no difference between cortex and striatum in all groups (all P > 0.05). In summary, SACP provided uniform and continuous cerebral perfusion to most anatomical sites in the brain, whereas RCP resulted in less sufficient perfusion to the cortex but better perfusion to the striatum. Copyright © 2015 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Fornix deep brain stimulation enhances acetylcholine levels in the hippocampus.

PubMed

Hescham, Sarah; Jahanshahi, Ali; Schweimer, Judith V; Mitchell, Stephen N; Carter, Guy; Blokland, Arjan; Sharp, Trevor; Temel, Yasin

2016-11-01

Deep brain stimulation (DBS) of the fornix has gained interest as a potential therapy for advanced treatment-resistant dementia, yet the mechanism of action remains widely unknown. Previously, we have reported beneficial memory effects of fornix DBS in a scopolamine-induced rat model of dementia, which is dependent on various brain structures including hippocampus. To elucidate mechanisms of action of fornix DBS with regard to memory restoration, we performed c-Fos immunohistochemistry in the hippocampus. We found that fornix DBS induced a selective activation of cells in the CA1 and CA3 subfields of the dorsal hippocampus. In addition, hippocampal neurotransmitter levels were measured using microdialysis before, during and after 60 min of fornix DBS in a next experiment. We observed a substantial increase in the levels of extracellular hippocampal acetylcholine, which peaked 20 min after stimulus onset. Interestingly, hippocampal glutamate levels did not change compared to baseline. Therefore, our findings provide first experimental evidence that fornix DBS activates the hippocampus and induces the release of acetylcholine in this region.

A study of the comparative anatomy of the brain of domestic ruminants using magnetic resonance imaging.

PubMed

Schmidt, M J; Langen, N; Klumpp, S; Nasirimanesh, F; Shirvanchi, P; Ondreka, N; Kramer, M

2012-01-01

Although magnetic resonance imaging has been used to examine the brain of domestic ruminants, detailed information relating the precise anatomical features in these species is lacking. In this study the brain structures of calves (Bos taurus domesticus), sheep (Ovis aries), goats (Capra hircus) and a mesaticephalic dog (Canis lupis familiaris) were examined using T2-weighed Turbo Spin Echo sequences; three-dimensional models based on high-resolution gradient echo scans were used to identify brain sulci and gyri in two-dimensional images. The ruminant brains examined were similar in structure and organisation to those of other mammals but particular features included the deep depression of the insula and the pronounced gyri of the cortices, the dominant position of the visual (optic nerve, optic chiasm and rostral colliculus) and olfactory (olfactory bulb, olfactory tracts and piriform lobe) systems, and the relatively large size of the diencephalon. Copyright © 2010 Elsevier Ltd. All rights reserved.

Pilot study assessing the feasibility of applying bilateral subthalamic nucleus deep brain stimulation in very early stage Parkinson's disease: study design and rationale.

PubMed

Charles, David; Tolleson, Christopher; Davis, Thomas L; Gill, Chandler E; Molinari, Anna L; Bliton, Mark J; Tramontana, Michael G; Salomon, Ronald M; Kao, Chris; Wang, Lily; Hedera, Peter; Phibbs, Fenna T; Neimat, Joseph S; Konrad, Peter E

2012-01-01

Deep brain stimulation provides significant symptomatic benefit for people with advanced Parkinson's disease whose symptoms are no longer adequately controlled with medication. Preliminary evidence suggests that subthalamic nucleus stimulation may also be efficacious in early Parkinson's disease, and results of animal studies suggest that it may spare dopaminergic neurons in the substantia nigra. We report the methodology and design of a novel Phase I clinical trial testing the safety and tolerability of deep brain stimulation in early Parkinson's disease and discuss previous failed attempts at neuroprotection. We recently conducted a prospective, randomized, parallel-group, single-blind pilot clinical trial of deep brain stimulation in early Parkinson's disease. Subjects were randomized to receive either optimal drug therapy or deep brain stimulation plus optimal drug therapy. Follow-up visits occurred every six months for a period of two years and included week-long therapy washouts. Thirty subjects with Hoehn & Yahr Stage II idiopathic Parkinson's disease were enrolled over a period of 32 months. Twenty-nine subjects completed all follow-up visits; one patient in the optimal drug therapy group withdrew from the study after baseline. Baseline characteristics for all thirty patients were not significantly different. This study demonstrates that it is possible to recruit and retain subjects in a clinical trial testing deep brain stimulation in early Parkinson's disease. The results of this trial will be used to support the design of a Phase III, multicenter trial investigating the efficacy of deep brain stimulation in early Parkinson's disease.

Pilot Study Assessing the Feasibility of Applying Bilateral Subthalamic Nucleus Deep Brain Stimulation in Very Early Stage Parkinson's Disease: Study design and rationale

PubMed Central

Charles, David; Tolleson, Christopher; Davis, Thomas L.; Gill, Chandler E.; Molinari, Anna L.; Bliton, Mark J.; Tramontana, Michael G.; Salomon, Ronald M.; Kao, Chris; Wang, Lily; Hedera, Peter; Phibbs, Fenna T.; Neimat, Joseph S.; Konrad, Peter E.

2014-01-01

Background Deep brain stimulation provides significant symptomatic benefit for people with advanced Parkinson's disease whose symptoms are no longer adequately controlled with medication. Preliminary evidence suggests that subthalamic nucleus stimulation may also be efficacious in early Parkinson's disease, and results of animal studies suggest that it may spare dopaminergic neurons in the substantia nigra. Objective We report the methodology and design of a novel Phase I clinical trial testing the safety and tolerability of deep brain stimulation in early Parkinson's disease and discuss previous failed attempts at neuroprotection. Methods We recently conducted a prospective, randomized, parallel-group, single-blind pilot clinical trial of deep brain stimulation in early Parkinson's disease. Subjects were randomized to receive either optimal drug therapy or deep brain stimulation plus optimal drug therapy. Follow-up visits occurred every six months for a period of two years and included week-long therapy washouts. Results Thirty subjects with Hoehn & Yahr Stage II idiopathic Parkinson's disease were enrolled over a period of 32 months. Twenty-nine subjects completed all follow-up visits; one patient in the optimal drug therapy group withdrew from the study after baseline. Baseline characteristics for all thirty patients were not significantly different. Conclusions This study demonstrates that it is possible to recruit and retain subjects in a clinical trial testing deep brain stimulation in early Parkinson's disease. The results of this trial will be used to support the design of a Phase III, multicenter trial investigating the efficacy of deep brain stimulation in early Parkinson's disease. PMID:23938229

Quantitative Visualization of Dynamic Tracer Transportation in the Extracellular Space of Deep Brain Regions Using Tracer-Based Magnetic Resonance Imaging.

PubMed

Hou, Jin; Wang, Wei; Quan, Xianyue; Liang, Wen; Li, Zhiming; Chen, Deji; Han, Hongbin

2017-09-03

BACKGROUND This study assessed an innovative tracer-based magnetic resonance imaging (MRI) system to visualize the dynamic transportation of tracers in regions of deep brain extracellular space (ECS) and to measure transportation ability and ECS structure. MATERIAL AND METHODS Gadolinium-diethylene triamine pentaacetic acid (Gd-DTPA) was the chosen tracer and was injected into the caudate nucleus and thalamus. Real-time dynamic transportation of Gd-DTPA in ECS was observed and the results were verified by laser scanning confocal microscopy. Using Transwell assay across the blood-brain barrier, a modified diffusion equation was further simplified. Effective diffusion coefficient D* and tortuosity λ were calculated. Immunohistochemical staining and Western blot analysis were used to investigate the extracellular matrix contributing to ECS structure. RESULTS Tracers injected into the caudate nucleus were transported to the ipsilateral frontal and temporal cortices away from the injection points, while both of them injected into the thalamus were only distributed on site. Although the caudate nucleus was closely adjacent to the thalamus, tracer transportation between partitions was not observed. In addition, D* and the λ showed statistically significant differences between partitions. ECS was shown to be a physiologically partitioned system, and its division is characterized by the unique distribution territory and transportation ability of substances located in it. Versican and Tenascin R are possible contributors to the tortuosity of ECS. CONCLUSIONS Tracer-based MRI will improve our understanding of the brain microenvironment, improve the techniques for local delivery of drugs, and highlight brain tissue engineering fields in the future.

The treatment of Parkinson's disease with deep brain stimulation: current issues.

PubMed

Moldovan, Alexia-Sabine; Groiss, Stefan Jun; Elben, Saskia; Südmeyer, Martin; Schnitzler, Alfons; Wojtecki, Lars

2015-07-01

Deep brain stimulation has become a well-established symptomatic treatment for Parkinson's disease during the last 25 years. Besides improving motor symptoms and long-term motor complications, positive effects on patients' mobility, activities of daily living, emotional well-being and health-related quality of life have been recognized. Apart from that, numerous clinical trials analyzed effects on non-motor symptoms and side effects of deep brain stimulation. Several technical issues and stimulation paradigms have been and are still being developed to optimize the therapeutic effects, minimize the side effects and facilitate handling. This review summarizes current therapeutic issues, i.e., patient and target selection, surgical procedure and programming paradigms. In addition it focuses on neuropsychological effects and side effects of deep brain stimulation.

[Long-term care of Parkinson patients with deep brain stimulation].

PubMed

Allert, N; Barbe, M T; Timmermann, L; Coenen, V A

2011-12-01

For more than 15 years deep brain stimulation of the subthalamic nucleus and globus pallidus internus have become therapeutic options in advanced Parkinson's disease. The number of patients with long-term treatment is increasing steadily. This review focuses on issues of the long-term care of these Parkinson's patients, including differences of the available deep brain stimulation systems, recommendations for follow-up examinations, implications for medical diagnostics and therapies and an algorithm for symptom deterioration. Today, there is no profound evidence that deep brain stimulation prevents disease progression. However, symptomatic relief from motor symptoms is maintained during long-term follow-up and interruption of the therapy remains an exception. © Georg Thieme Verlag KG Stuttgart · New York.

Gamma knife radiosurgery in movement disorders: Indications and limitations.

PubMed

Higuchi, Yoshinori; Matsuda, Shinji; Serizawa, Toru

2017-01-01

Functional radiosurgery has advanced steadily during the past half century since the development of the gamma knife technique for treating intractable cancer pain. Applications of radiosurgery for intracranial diseases have increased with a focus on understanding radiobiology. Currently, the use of gamma knife radiosurgery to ablate deep brain structures is not widespread because visualization of the functional targets remains difficult despite the increased availability of advanced neuroimaging technology. Moreover, most existing reports have a small sample size or are retrospective. However, increased experience with intraoperative neurophysiological evaluations in radiofrequency thalamotomy and deep brain stimulation supports anatomical and neurophysiological approaches to the ventralis intermedius nucleus. Two recent prospective studies have promoted the clinical application of functional radiosurgery for movement disorders. For example, unilateral gamma knife thalamotomy is a potential alternative to radiofrequency thalamotomy and deep brain stimulation techniques for intractable tremor patients with contraindications for surgery. Despite the promising efficacy of gamma knife thalamotomy, however, these studies did not include sufficient follow-up to confirm long-term effects. Herein, we review the radiobiology literature, various techniques, and the treatment efficacy of gamma knife radiosurgery for patients with movement disorders. Future research should focus on randomized controlled studies and long-term effects. © 2016 International Parkinson and Movement Disorder Society. © 2016 International Parkinson and Movement Disorder Society.

Scaling and intermittency of brain events as a manifestation of consciousness

NASA Astrophysics Data System (ADS)

Paradisi, P.; Allegrini, P.; Gemignani, A.; Laurino, M.; Menicucci, D.; Piarulli, A.

2013-01-01

We discuss the critical brain hypothesis and its relationship with intermittent renewal processes displaying power-law decay in the distribution of waiting times between two consecutive renewal events. In particular, studies on complex systems in a "critical" condition show that macroscopic variables, integrating the activities of many individual functional units, undergo fluctuations with an intermittent serial structure characterized by avalanches with inverse-power-law (scale-free) distribution densities of sizes and inter-event times. This condition, which is denoted as "fractal intermittency", was found in the electroencephalograms of subjects observed during a resting state wake condition. It remained unsolved whether fractal intermittency correlates with the stream of consciousness or with a non-task-driven default mode activity, also present in non-conscious states, like deep sleep. After reviewing a method of scaling analysis of intermittent systems based of eventdriven random walks, we show that during deep sleep fractal intermittency breaks down, and reestablishes during REM (Rapid Eye Movement) sleep, with essentially the same anomalous scaling of the pre-sleep wake condition. From the comparison of the pre-sleep wake, deep sleep and REM conditions we argue that the scaling features of intermittent brain events are related to the level of consciousness and, consequently, could be exploited as a possible indicator of consciousness in clinical applications.

Paradoxical augmented relapse in alcohol-dependent rats during deep-brain stimulation in the nucleus accumbens

PubMed Central

Hadar, R; Vengeliene, V; Barroeta Hlusicke, E; Canals, S; Noori, H R; Wieske, F; Rummel, J; Harnack, D; Heinz, A; Spanagel, R; Winter, C

2016-01-01

Case reports indicate that deep-brain stimulation in the nucleus accumbens may be beneficial to alcohol-dependent patients. The lack of clinical trials and our limited knowledge of deep-brain stimulation call for translational experiments to validate these reports. To mimic the human situation, we used a chronic-continuous brain-stimulation paradigm targeting the nucleus accumbens and other brain sites in alcohol-dependent rats. To determine the network effects of deep-brain stimulation in alcohol-dependent rats, we combined electrical stimulation of the nucleus accumbens with functional magnetic resonance imaging (fMRI), and studied neurotransmitter levels in nucleus accumbens-stimulated versus sham-stimulated rats. Surprisingly, we report here that electrical stimulation of the nucleus accumbens led to augmented relapse behavior in alcohol-dependent rats. Our associated fMRI data revealed some activated areas, including the medial prefrontal cortex and caudate putamen. However, when we applied stimulation to these areas, relapse behavior was not affected, confirming that the nucleus accumbens is critical for generating this paradoxical effect. Neurochemical analysis of the major activated brain sites of the network revealed that the effect of stimulation may depend on accumbal dopamine levels. This was supported by the finding that brain-stimulation-treated rats exhibited augmented alcohol-induced dopamine release compared with sham-stimulated animals. Our data suggest that deep-brain stimulation in the nucleus accumbens enhances alcohol-liking probably via augmented dopamine release and can thereby promote relapse. PMID:27327255

A neurosurgical simulation of skull base tumors using a 3D printed rapid prototyping model containing mesh structures.

PubMed

Kondo, Kosuke; Harada, Naoyuki; Masuda, Hiroyuki; Sugo, Nobuo; Terazono, Sayaka; Okonogi, Shinichi; Sakaeyama, Yuki; Fuchinoue, Yutaka; Ando, Syunpei; Fukushima, Daisuke; Nomoto, Jun; Nemoto, Masaaki

2016-06-01

Deep regions are not visible in three-dimensional (3D) printed rapid prototyping (RP) models prepared from opaque materials, which is not the case with translucent images. The objectives of this study were to develop an RP model in which a skull base tumor was simulated using mesh, and to investigate its usefulness for surgical simulations by evaluating the visibility of its deep regions. A 3D printer that employs binder jetting and is mainly used to prepare plaster models was used. RP models containing a solid tumor, no tumor, and a mesh tumor were prepared based on computed tomography, magnetic resonance imaging, and angiographic data for four cases of petroclival tumor. Twelve neurosurgeons graded the three types of RP model into the following four categories: 'clearly visible,' 'visible,' 'difficult to see,' and 'invisible,' based on the visibility of the internal carotid artery, basilar artery, and brain stem through a craniotomy performed via the combined transpetrosal approach. In addition, the 3D positional relationships between these structures and the tumor were assessed. The internal carotid artery, basilar artery, and brain stem and the positional relationships of these structures with the tumor were significantly more visible in the RP models with mesh tumors than in the RP models with solid or no tumors. The deep regions of PR models containing mesh skull base tumors were easy to visualize. This 3D printing-based method might be applicable to various surgical simulations.

Deep Sequencing to Identify the Causes of Viral Encephalitis

PubMed Central

Chan, Benjamin K.; Wilson, Theodore; Fischer, Kael F.; Kriesel, John D.

2014-01-01

Deep sequencing allows for a rapid, accurate characterization of microbial DNA and RNA sequences in many types of samples. Deep sequencing (also called next generation sequencing or NGS) is being developed to assist with the diagnosis of a wide variety of infectious diseases. In this study, seven frozen brain samples from deceased subjects with recent encephalitis were investigated. RNA from each sample was extracted, randomly reverse transcribed and sequenced. The sequence analysis was performed in a blinded fashion and confirmed with pathogen-specific PCR. This analysis successfully identified measles virus sequences in two brain samples and herpes simplex virus type-1 sequences in three brain samples. No pathogen was identified in the other two brain specimens. These results were concordant with pathogen-specific PCR and partially concordant with prior neuropathological examinations, demonstrating that deep sequencing can accurately identify viral infections in frozen brain tissue. PMID:24699691

Centromedian-parafascicular deep brain stimulation induces differential functional inhibition of the motor, associative, and limbic circuits in large animals.

PubMed

Kim, Joo Pyung; Min, Hoon-Ki; Knight, Emily J; Duffy, Penelope S; Abulseoud, Osama A; Marsh, Michael P; Kelsey, Katherine; Blaha, Charles D; Bennet, Kevin E; Frye, Mark A; Lee, Kendall H

2013-12-15

Deep brain stimulation (DBS) of the centromedian-parafascicular (CM-Pf) thalamic nuclei has been considered an option for treating Tourette syndrome. Using a large animal DBS model, this study was designed to explore the network effects of CM-Pf DBS. The combination of DBS and functional magnetic resonance imaging is a powerful means of tracing brain circuitry and testing the modulatory effects of electrical stimulation on a neuronal network in vivo. With a within-subjects design, we tested the proportional effects of CM and Pf DBS by manipulating current spread and varying stimulation contacts in healthy pigs (n = 5). Our results suggests that CM-Pf DBS has an inhibitory modulating effect in areas that have been suggested as contributing to impaired sensory-motor and emotional processing. The results also help to define the differential neural circuitry effects of the CM and Pf with evidence of prominent sensorimotor/associative effects for CM DBS and prominent limbic/associative effects for Pf DBS. Our results support the notion that stimulation of deep brain structures, such as the CM-Pf, modulates multiple networks with cortical effects. The networks affected by CM-Pf stimulation in this study reinforce the conceptualization of Tourette syndrome as a condition with psychiatric and motor symptoms and of CM-Pf DBS as a potentially effective tool for treating both types of symptoms. Copyright © 2013 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Brain responses differ to faces of mothers and fathers.

PubMed

Arsalidou, Marie; Barbeau, Emmanuel J; Bayless, Sarah J; Taylor, Margot J

2010-10-01

We encounter many faces each day but relatively few are personally familiar. Once faces are familiar, they evoke semantic and social information known about the person. Neuroimaging studies demonstrate differential brain activity to familiar and non-familiar faces; however, brain responses related to personally familiar faces have been more rarely studied. We examined brain activity with fMRI in adults in response to faces of their mothers and fathers compared to faces of celebrities and strangers. Overall, faces of mothers elicited more activity in core and extended brain regions associated with face processing, compared to fathers, celebrity or stranger faces. Fathers' faces elicited activity in the caudate, a deep brain structure associated with feelings of love. These new findings of differential brain responses elicited by faces of mothers and fathers are consistent with psychological research on attachment, evident even during adulthood. 2010 Elsevier Inc. All rights reserved.

Contributions of Subsurface Cortical Modulations to Discrimination of Executed and Imagined Grasp Forces through Stereoelectroencephalography

PubMed Central

Murphy, Brian A.; Miller, Jonathan P.; Gunalan, Kabilar; Ajiboye, A. Bolu

2016-01-01

Stereoelectroencephalographic (SEEG) depth electrodes have the potential to record neural activity from deep brain structures not easily reached with other intracranial recording technologies. SEEG electrodes were placed through deep cortical structures including central sulcus and insular cortex. In order to observe changes in frequency band modulation, participants performed force matching trials at three distinct force levels using two different grasp configurations: a power grasp and a lateral pinch. Signals from these deeper structures were found to contain information useful for distinguishing force from rest trials as well as different force levels in some participants. High frequency components along with alpha and beta bands recorded from electrodes located near the primary motor cortex wall of central sulcus and electrodes passing through sensory cortex were found to be the most useful for classification of force versus rest although one participant did have significant modulation in the insular cortex. This study electrophysiologically corroborates with previous imaging studies that show force-related modulation occurs inside of central sulcus and insular cortex. The results of this work suggest that depth electrodes could be useful tools for investigating the functions of deeper brain structures as well as showing that central sulcus and insular cortex may contain neural signals that could be used for control of a grasp force BMI. PMID:26963246

Carbon nanotube yarns for deep brain stimulation electrode.

PubMed

Jiang, Changqing; Li, Luming; Hao, Hongwei

2011-12-01

A new form of deep brain stimulation (DBS) electrode was proposed that was made of carbon nanotube yarns (CNTYs). Electrode interface properties were examined using cyclic voltammetry (CV) and electrochemical impedance spectrum (EIS). The CNTY electrode interface exhibited large charge storage capacity (CSC) of 12.3 mC/cm(2) which increased to 98.6 mC/cm(2) after acid treatment, compared with 5.0 mC/cm(2) of Pt-Ir. Impedance spectrum of both untreated and treated CNTY electrodes showed that finite diffusion process occurred at the interface due to their porous structure and charge was delivered through capacitive mechanism. To evaluate stability electrical stimulus was exerted for up to 72 h and CV and EIS results of CNTY electrodes revealed little alteration. Therefore CNTY could make a good electrode material for DBS.

Deep brain stimulation effects in dystonia: time course of electrophysiological changes in early treatment.

PubMed

Ruge, Diane; Tisch, Stephen; Hariz, Marwan I; Zrinzo, Ludvic; Bhatia, Kailash P; Quinn, Niall P; Jahanshahi, Marjan; Limousin, Patricia; Rothwell, John C

2011-08-15

Deep brain stimulation to the internal globus pallidus is an effective treatment for primary dystonia. The optimal clinical effect often occurs only weeks to months after starting stimulation. To better understand the underlying electrophysiological changes in this period, we assessed longitudinally 2 pathophysiological markers of dystonia in patients prior to and in the early treatment period (1, 3, 6 months) after deep brain stimulation surgery. Transcranial magnetic stimulation was used to track changes in short-latency intracortical inhibition, a measure of excitability of GABA(A) -ergic corticocortical connections and long-term potentiation-like synaptic plasticity (as a response to paired associative stimulation). Deep brain stimulation remained on for the duration of the study. Prior to surgery, inhibition was reduced and plasticity increased in patients compared with healthy controls. Following surgery and commencement of deep brain stimulation, short-latency intracortical inhibition increased toward normal levels over the following months with the same monotonic time course as the patients' clinical benefit. In contrast, synaptic plasticity changed rapidly, following a nonmonotonic time course: it was absent early (1 month) after surgery, and then over the following months increased toward levels observed in healthy individuals. We postulate that before surgery preexisting high levels of plasticity form strong memories of dystonic movement patterns. When deep brain stimulation is turned on, it disrupts abnormal basal ganglia signals, resulting in the absent response to paired associative stimulation at 1 month. Clinical benefit is delayed because engrams of abnormal movement persist and take time to normalize. Our observations suggest that plasticity may be a driver of long-term therapeutic effects of deep brain stimulation in dystonia. Copyright © 2011 Movement Disorder Society.

Long-Term Efficacy of Constant Current Deep Brain Stimulation in Essential Tremor.

PubMed

Rezaei Haddad, Ali; Samuel, Michael; Hulse, Natasha; Lin, Hsin-Ying; Ashkan, Keyoumars

2017-07-01

Ventralis intermedius deep brain stimulation is an established intervention for medication-refractory essential tremor. Newer constant current stimulation technology offers theoretical advantage over the traditional constant voltage systems in terms of delivering a more biologically stable therapy. There are no previous reports on the outcomes of constant current deep brain stimulation in the treatment of essential tremor. This study aimed to evaluate the long-term efficacy of ventralis intermedius constant current deep brain stimulation in patients diagnosed with essential tremor. Essential tremor patients implanted with constant current deep brain stimulation for a minimum of three years were evaluated. Clinical outcomes were assessed using the Fahn-Tolosa-Marin tremor rating scale at baseline and postoperatively at the time of evaluation. The quality of life in the patients was assessed using the Quality of Life in Essential Tremor questionnaire. Ten patients were evaluated with a median age at evaluation of 74 years (range 66-79) and a mean follow up time of 49.7 (range 36-78) months since starting stimulation. Constant current ventralis intermedius deep brain stimulation was well tolerated and effective in all patients with a mean score improvement from 50.7 ± 5.9 to 17.4 ± 5.7 (p = 0.0020) in the total Fahn-Tolosa-Marin rating scale score (65.6%). Furthermore, the total combined mean Quality of Life in Essential Tremor score was improved from 56.2 ± 4.9 to 16.8 ± 3.5 (p value = 0.0059) (70.1%). This report shows that long-term constant current ventralis intermedius deep brain stimulation is a safe and effective intervention for essential tremor patients. © 2017 International Neuromodulation Society.

High-resolution anatomy of the human brain stem using 7-T MRI: improved detection of inner structures and nerves?

PubMed

Gizewski, Elke R; Maderwald, Stefan; Linn, Jennifer; Dassinger, Benjamin; Bochmann, Katja; Forsting, Michael; Ladd, Mark E

2014-03-01

The purpose of this paper is to assess the value of 7 Tesla (7 T) MRI for the depiction of brain stem and cranial nerve (CN) anatomy. Six volunteers were examined at 7 T using high-resolution SWI, MPRAGE, MP2RAGE, 3D SPACE T2, T2, and PD images to establish scanning parameters targeted at optimizing spatial resolution. Direct comparisons between 3 and 7 T were performed in two additional subjects using the finalized sequences (3 T: T2, PD, MPRAGE, SWAN; 7 T: 3D T2, MPRAGE, SWI, MP2RAGE). Artifacts and the depiction of structures were evaluated by two neuroradiologists using a standardized score sheet. Sequences could be established for high-resolution 7 T imaging even in caudal cranial areas. High in-plane resolution T2, PD, and SWI images provided depiction of inner brain stem structures such as pons fibers, raphe, reticular formation, nerve roots, and periaqueductal gray. MPRAGE and MP2RAGE provided clear depiction of the CNs. 3D T2 images improved depiction of inner brain structure in comparison to T2 images at 3 T. Although the 7-T SWI sequence provided improved contrast to some inner structures, extended areas were influenced by artifacts due to image disturbances from susceptibility differences. Seven-tesla imaging of basal brain areas is feasible and might have significant impact on detection and diagnosis in patients with specific diseases, e.g., trigeminal pain related to affection of the nerve root. Some inner brain stem structures can be depicted at 3 T, but certain sequences at 7 T, in particular 3D SPACE T2, are superior in producing anatomical in vivo images of deep brain stem structures.

Early development of structural networks and the impact of prematurity on brain connectivity.

PubMed

Batalle, Dafnis; Hughes, Emer J; Zhang, Hui; Tournier, J-Donald; Tusor, Nora; Aljabar, Paul; Wali, Luqman; Alexander, Daniel C; Hajnal, Joseph V; Nosarti, Chiara; Edwards, A David; Counsell, Serena J

2017-04-01

Preterm infants are at high risk of neurodevelopmental impairment, which may be due to altered development of brain connectivity. We aimed to (i) assess structural brain development from 25 to 45 weeks gestational age (GA) using graph theoretical approaches and (ii) test the hypothesis that preterm birth results in altered white matter network topology. Sixty-five infants underwent MRI between 25 +3 and 45 +6 weeks GA. Structural networks were constructed using constrained spherical deconvolution tractography and were weighted by measures of white matter microstructure (fractional anisotropy, neurite density and orientation dispersion index). We observed regional differences in brain maturation, with connections to and from deep grey matter showing most rapid developmental changes during this period. Intra-frontal, frontal to cingulate, frontal to caudate and inter-hemispheric connections matured more slowly. We demonstrated a core of key connections that was not affected by GA at birth. However, local connectivity involving thalamus, cerebellum, superior frontal lobe, cingulate gyrus and short range cortico-cortical connections was related to the degree of prematurity and contributed to altered global topology of the structural brain network. The relative preservation of core connections at the expense of local connections may support more effective use of impaired white matter reserve following preterm birth. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Transmission in near-infrared optical windows for deep brain imaging.

PubMed

Shi, Lingyan; Sordillo, Laura A; Rodríguez-Contreras, Adrián; Alfano, Robert

2016-01-01

Near-infrared (NIR) radiation has been employed using one- and two-photon excitation of fluorescence imaging at wavelengths 650-950 nm (optical window I) for deep brain imaging; however, longer wavelengths in NIR have been overlooked due to a lack of suitable NIR-low band gap semiconductor imaging detectors and/or femtosecond laser sources. This research introduces three new optical windows in NIR and demonstrates their potential for deep brain tissue imaging. The transmittances are measured in rat brain tissue in the second (II, 1,100-1,350 nm), third (III, 1,600-1,870 nm), and fourth (IV, centered at 2,200 nm) NIR optical tissue windows. The relationship between transmission and tissue thickness is measured and compared with the theory. Due to a reduction in scattering and minimal absorption, window III is shown to be the best for deep brain imaging, and windows II and IV show similar but better potential for deep imaging than window I. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Human Brain Activity Patterns beyond the Isoelectric Line of Extreme Deep Coma

PubMed Central

Kroeger, Daniel; Florea, Bogdan; Amzica, Florin

2013-01-01

The electroencephalogram (EEG) reflects brain electrical activity. A flat (isoelectric) EEG, which is usually recorded during very deep coma, is considered to be a turning point between a living brain and a deceased brain. Therefore the isoelectric EEG constitutes, together with evidence of irreversible structural brain damage, one of the criteria for the assessment of brain death. In this study we use EEG recordings for humans on the one hand, and on the other hand double simultaneous intracellular recordings in the cortex and hippocampus, combined with EEG, in cats. They serve to demonstrate that a novel brain phenomenon is observable in both humans and animals during coma that is deeper than the one reflected by the isoelectric EEG, and that this state is characterized by brain activity generated within the hippocampal formation. This new state was induced either by medication applied to postanoxic coma (in human) or by application of high doses of anesthesia (isoflurane in animals) leading to an EEG activity of quasi-rhythmic sharp waves which henceforth we propose to call ν-complexes (Nu-complexes). Using simultaneous intracellular recordings in vivo in the cortex and hippocampus (especially in the CA3 region) we demonstrate that ν-complexes arise in the hippocampus and are subsequently transmitted to the cortex. The genesis of a hippocampal ν-complex depends upon another hippocampal activity, known as ripple activity, which is not overtly detectable at the cortical level. Based on our observations, we propose a scenario of how self-oscillations in hippocampal neurons can lead to a whole brain phenomenon during coma. PMID:24058669

Stacking denoising auto-encoders in a deep network to segment the brainstem on MRI in brain cancer patients: A clinical study.

PubMed

Dolz, Jose; Betrouni, Nacim; Quidet, Mathilde; Kharroubi, Dris; Leroy, Henri A; Reyns, Nicolas; Massoptier, Laurent; Vermandel, Maximilien

2016-09-01

Delineation of organs at risk (OARs) is a crucial step in surgical and treatment planning in brain cancer, where precise OARs volume delineation is required. However, this task is still often manually performed, which is time-consuming and prone to observer variability. To tackle these issues a deep learning approach based on stacking denoising auto-encoders has been proposed to segment the brainstem on magnetic resonance images in brain cancer context. Additionally to classical features used in machine learning to segment brain structures, two new features are suggested. Four experts participated in this study by segmenting the brainstem on 9 patients who underwent radiosurgery. Analysis of variance on shape and volume similarity metrics indicated that there were significant differences (p<0.05) between the groups of manual annotations and automatic segmentations. Experimental evaluation also showed an overlapping higher than 90% with respect to the ground truth. These results are comparable, and often higher, to those of the state of the art segmentation methods but with a considerably reduction of the segmentation time. Copyright © 2016 Elsevier Ltd. All rights reserved.

Development, Validation and Parametric study of a 3-Year-Old Child Head Finite Element Model

NASA Astrophysics Data System (ADS)

Cui, Shihai; Chen, Yue; Li, Haiyan; Ruan, ShiJie

2015-12-01

Traumatic brain injury caused by drop and traffic accidents is an important reason for children's death and disability. Recently, the computer finite element (FE) head model has been developed to investigate brain injury mechanism and biomechanical responses. Based on CT data of a healthy 3-year-old child head, the FE head model with detailed anatomical structure was developed. The deep brain structures such as white matter, gray matter, cerebral ventricle, hippocampus, were firstly created in this FE model. The FE model was validated by comparing the simulation results with that of cadaver experiments based on reconstructing the child and adult cadaver experiments. In addition, the effects of skull stiffness on the child head dynamic responses were further investigated. All the simulation results confirmed the good biofidelity of the FE model.

Essential Tremor

MedlinePlus

... individuals. Deep brain stimulation uses a surgically implanted, battery-operated medical device called a neurostimulator to delivery ... individuals. Deep brain stimulation uses a surgically implanted, battery-operated medical device called a neurostimulator to delivery ...

[Obsessive-compulsive disorder, a new model of basal ganglia dysfunction? Elements from deep brain stimulation studies].

PubMed

Haynes, W I A; Millet, B; Mallet, L

2012-01-01

Deep brain stimulation was first developed for movement disorders but is now being offered as a therapeutic alternative in severe psychiatric disorders after the failure of conventional therapies. One of such pathologies is obsessive-compulsive disorder. This disorder which associates intrusive thoughts (obsessions) and repetitive irrepressible rituals (compulsions) is characterized by a dysfunction of a cortico-subcortical loop. After having reviewed the pathophysiological evidence to show why deep brain stimulation was an interesting path to take for severe and resistant cases of obsessive-compulsive disorder, we will present the results of the different clinical trials. Finally, we will provide possible mechanisms for the effects of deep brain stimulation in this pathology. Copyright © 2012 Elsevier Masson SAS. All rights reserved.

The treatment of Parkinson's disease with deep brain stimulation: current issues

PubMed Central

Moldovan, Alexia-Sabine; Groiss, Stefan Jun; Elben, Saskia; Südmeyer, Martin; Schnitzler, Alfons; Wojtecki, Lars

2015-01-01

Deep brain stimulation has become a well-established symptomatic treatment for Parkinson's disease during the last 25 years. Besides improving motor symptoms and long-term motor complications, positive effects on patients’ mobility, activities of daily living, emotional well-being and health-related quality of life have been recognized. Apart from that, numerous clinical trials analyzed effects on non-motor symptoms and side effects of deep brain stimulation. Several technical issues and stimulation paradigms have been and are still being developed to optimize the therapeutic effects, minimize the side effects and facilitate handling. This review summarizes current therapeutic issues, i.e., patient and target selection, surgical procedure and programming paradigms. In addition it focuses on neuropsychological effects and side effects of deep brain stimulation. PMID:26330809

A comparative study of two prediction models for brain tumor progression

NASA Astrophysics Data System (ADS)

Zhou, Deqi; Tran, Loc; Wang, Jihong; Li, Jiang

2015-03-01

MR diffusion tensor imaging (DTI) technique together with traditional T1 or T2 weighted MRI scans supplies rich information sources for brain cancer diagnoses. These images form large-scale, high-dimensional data sets. Due to the fact that significant correlations exist among these images, we assume low-dimensional geometry data structures (manifolds) are embedded in the high-dimensional space. Those manifolds might be hidden from radiologists because it is challenging for human experts to interpret high-dimensional data. Identification of the manifold is a critical step for successfully analyzing multimodal MR images. We have developed various manifold learning algorithms (Tran et al. 2011; Tran et al. 2013) for medical image analysis. This paper presents a comparative study of an incremental manifold learning scheme (Tran. et al. 2013) versus the deep learning model (Hinton et al. 2006) in the application of brain tumor progression prediction. The incremental manifold learning is a variant of manifold learning algorithm to handle large-scale datasets in which a representative subset of original data is sampled first to construct a manifold skeleton and remaining data points are then inserted into the skeleton by following their local geometry. The incremental manifold learning algorithm aims at mitigating the computational burden associated with traditional manifold learning methods for large-scale datasets. Deep learning is a recently developed multilayer perceptron model that has achieved start-of-the-art performances in many applications. A recent technique named "Dropout" can further boost the deep model by preventing weight coadaptation to avoid over-fitting (Hinton et al. 2012). We applied the two models on multiple MRI scans from four brain tumor patients to predict tumor progression and compared the performances of the two models in terms of average prediction accuracy, sensitivity, specificity and precision. The quantitative performance metrics were calculated as average over the four patients. Experimental results show that both the manifold learning and deep neural network models produced better results compared to using raw data and principle component analysis (PCA), and the deep learning model is a better method than manifold learning on this data set. The averaged sensitivity and specificity by deep learning are comparable with these by the manifold learning approach while its precision is considerably higher. This means that the predicted abnormal points by deep learning are more likely to correspond to the actual progression region.

Constructing fine-granularity functional brain network atlases via deep convolutional autoencoder.

PubMed

Zhao, Yu; Dong, Qinglin; Chen, Hanbo; Iraji, Armin; Li, Yujie; Makkie, Milad; Kou, Zhifeng; Liu, Tianming

2017-12-01

State-of-the-art functional brain network reconstruction methods such as independent component analysis (ICA) or sparse coding of whole-brain fMRI data can effectively infer many thousands of volumetric brain network maps from a large number of human brains. However, due to the variability of individual brain networks and the large scale of such networks needed for statistically meaningful group-level analysis, it is still a challenging and open problem to derive group-wise common networks as network atlases. Inspired by the superior spatial pattern description ability of the deep convolutional neural networks (CNNs), a novel deep 3D convolutional autoencoder (CAE) network is designed here to extract spatial brain network features effectively, based on which an Apache Spark enabled computational framework is developed for fast clustering of larger number of network maps into fine-granularity atlases. To evaluate this framework, 10 resting state networks (RSNs) were manually labeled from the sparsely decomposed networks of Human Connectome Project (HCP) fMRI data and 5275 network training samples were obtained, in total. Then the deep CAE models are trained by these functional networks' spatial maps, and the learned features are used to refine the original 10 RSNs into 17 network atlases that possess fine-granularity functional network patterns. Interestingly, it turned out that some manually mislabeled outliers in training networks can be corrected by the deep CAE derived features. More importantly, fine granularities of networks can be identified and they reveal unique network patterns specific to different brain task states. By further applying this method to a dataset of mild traumatic brain injury study, it shows that the technique can effectively identify abnormal small networks in brain injury patients in comparison with controls. In general, our work presents a promising deep learning and big data analysis solution for modeling functional connectomes, with fine granularities, based on fMRI data. Copyright © 2017 Elsevier B.V. All rights reserved.

Detection of Alzheimer’s disease amyloid-beta plaque deposition by deep brain impedance profiling

NASA Astrophysics Data System (ADS)

Béduer, Amélie; Joris, Pierre; Mosser, Sébastien; Fraering, Patrick C.; Renaud, Philippe

2015-04-01

Objective. Alzheimer disease (AD) is the most common form of neurodegenerative disease in elderly people. Toxic brain amyloid-beta (Aß) aggregates and ensuing cell death are believed to play a central role in the pathogenesis of the disease. In this study, we investigated if we could monitor the presence of these aggregates by performing in situ electrical impedance spectroscopy measurements in AD model mice brains. Approach. In this study, electrical impedance spectroscopy measurements were performed post-mortem in APPPS1 transgenic mice brains. This transgenic model is commonly used to study amyloidogenesis, a pathological hallmark of AD. We used flexible probes with embedded micrometric electrodes array to demonstrate the feasibility of detecting senile plaques composed of Aß peptides by localized impedance measurements. Main results. We particularly focused on deep brain structures, such as the hippocampus. Ex vivo experiments using brains from young and old APPPS1 mice lead us to show that impedance measurements clearly correlate with the percentage of Aβ plaque load in the brain tissues. We could monitor the effects of aging in the AD APPPS1 mice model. Significance. We demonstrated that a localized electrical impedance measurement constitutes a valuable technique to monitor the presence of Aβ-plaques, which is complementary with existing imaging techniques. This method does not require prior Aβ staining, precluding the risk of variations in tissue uptake of dyes or tracers, and consequently ensuring reproducible data collection.

Dr. Robert G. Heath: a controversial figure in the history of deep brain stimulation.

PubMed

O'Neal, Christen M; Baker, Cordell M; Glenn, Chad A; Conner, Andrew K; Sughrue, Michael E

2017-09-01

The history of psychosurgery is filled with tales of researchers pushing the boundaries of science and ethics. These stories often create a dark historical framework for some of the most important medical and surgical advancements. Dr. Robert G. Heath, a board-certified neurologist, psychiatrist, and psychoanalyst, holds a debated position within this framework and is most notably remembered for his research on schizophrenia. Dr. Heath was one of the first physicians to implant electrodes in deep cortical structures as a psychosurgical intervention. He used electrical stimulation in an attempt to cure patients with schizophrenia and as a method of conversion therapy in a homosexual man. This research was highly controversial, even prior to the implementation of current ethics standards for clinical research and often goes unmentioned within the historical narrative of deep brain stimulation (DBS). While distinction between the modern practice of DBS and its controversial origins is necessary, it is important to examine Dr. Heath's work as it allows for reflection on current neurosurgical practices and questioning the ethical implication of these advancements.

Unilateral Postoperative Deep Cerebral Venous Thrombosis with Complete Recovery: A Report of 2 Cases.

PubMed

Benifla, Mony; Laughlin, Suzzanne; Tovar-Spinoza, Zulma S; Rutka, James T; Dirks, Peter B

2017-01-01

Postsurgical deep brain venous thrombosis has not been well described in children before. When approaching thalamic or intraventricular lesions, extra care should be taken to prevent injury to the internal cerebral veins (ICVs) and the vein of Galen. However, even when they are well preserved during surgery, postoperative hemodynamic changes, mainly in the first 24 h, or surgical manipulation can cause thrombosis of these veins. We report 2 children with unilateral postoperative ICV thrombosis; in 1 of the patients the vein of Galen was also thrombosed. Although both patients had altered sensorium initially, no anticoagulation therapy was given, and they both recovered well. When approaching thalamic or intraventricular lesions, extra care should be taken to prevent injury to the ICV and the vein of Galen. The surgeon should respect the deep brain venous system when approaching midline structures. Both the neurosurgeon and the neuroradiologist should be aware of this possible complication in order to make a prompt diagnosis and to offer proper treatment if needed. © 2017 S. Karger AG, Basel.

Acute in vivo testing of a conformal polymer microelectrode array for multi-region hippocampal recordings

NASA Astrophysics Data System (ADS)

Xu, Huijing; Weltman Hirschberg, Ahuva; Scholten, Kee; Berger, Theodore William; Song, Dong; Meng, Ellis

2018-02-01

Objective. The success of a cortical prosthetic device relies upon its ability to attain resolvable spikes from many neurons in particular neural networks over long periods of time. Traditionally, lifetimes of neural recordings are greatly limited by the body’s immune response against the foreign implant which causes neuronal death and glial scarring. This immune reaction is posited to be exacerbated by micromotion between the implant, which is often rigid, and the surrounding, soft brain tissue, and attenuates the quality of recordings over time. Approach. In an attempt to minimize the foreign body response to a penetrating neural array that records from multiple brain regions, Parylene C, a flexible, biocompatible polymer was used as the substrate material for a functional, proof-of-concept neural array with a reduced elastic modulus. This probe array was designed and fabricated to have 64 electrodes positioned to match the anatomy of the rat hippocampus and allow for simultaneous recordings between two cell-body layers of interest. A dissolvable brace was used for deep-brain penetration of the flexible array. Main results. Arrays were electrochemically characterized at the benchtop, and a novel insertion technique that restricts acute insertion injury enabled accurate target placement of four, bare, flexible arrays to greater than 4 mm deep into the rat brain. Arrays were tested acutely and in vivo recordings taken intra-operatively reveal spikes in both targeted regions of the hippocampus with spike amplitudes and noise levels similar to those recorded with microwires. Histological staining of a sham array implanted for one month reveals limited astrocytic scarring and neuronal death around the implant. Significance. This work represents one of the first examples of a penetrating polymer probe array that records from individual neurons in structures that lie deep within the brain.

75 FR 51467 - ASK (Assess Specific Kinds of CHILDREN Challenges for Neurologic Devices) Study Children Workshop...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-20

..., including cochlear implants, deep brain stimulators, hydrocephalus shunts, spinal cord stimulators, and... pediatric populations, including cochlear implants, deep brain stimulators, hydrocephalus shunts, spinal...

Delayed and lasting effects of deep brain stimulation on locomotion in Parkinson's disease

NASA Astrophysics Data System (ADS)

Beuter, Anne; Modolo, Julien

2009-06-01

Parkinson's disease (PD) is a neurodegenerative disorder characterized by a variety of motor signs affecting gait, postural stability, and tremor. These symptoms can be improved when electrodes are implanted in deep brain structures and electrical stimulation is delivered chronically at high frequency (>100 Hz). Deep brain stimulation (DBS) onset or cessation affects PD signs with different latencies, and the long-term improvements of symptoms affecting the body axis and those affecting the limbs vary in duration. Interestingly, these effects have not been systematically analyzed and modeled. We compare these timing phenomena in relation to one axial (i.e., locomotion) and one distal (i.e., tremor) signs. We suggest that during DBS, these symptoms are improved by different network mechanisms operating at multiple time scales. Locomotion improvement may involve a delayed plastic reorganization, which takes hours to develop, whereas rest tremor is probably alleviated by an almost instantaneous desynchronization of neural activity in subcortical structures. Even if all PD patients develop both distal and axial symptoms sooner or later, current computational models of locomotion and rest tremor are separate. Furthermore, a few computational models of locomotion focus on PD and none exploring the effect of DBS was found in the literature. We, therefore, discuss a model of a neuronal network during DBS, general enough to explore the subcircuits controlling locomotion and rest tremor simultaneously. This model accounts for synchronization and plasticity, two mechanisms that are believed to underlie the two types of symptoms analyzed. We suggest that a hysteretic effect caused by DBS-induced plasticity and synchronization modulation contributes to the different therapeutic latencies observed. Such a comprehensive, generic computational model of DBS effects, incorporating these timing phenomena, should assist in developing a more efficient, faster, durable treatment of distal and axial signs in PD.

Using ventricular modeling to robustly probe significant deep gray matter pathologies: Application to cerebral palsy.

PubMed

Pagnozzi, Alex M; Shen, Kaikai; Doecke, James D; Boyd, Roslyn N; Bradley, Andrew P; Rose, Stephen; Dowson, Nicholas

2016-11-01

Understanding the relationships between the structure and function of the brain largely relies on the qualitative assessment of Magnetic Resonance Images (MRIs) by expert clinicians. Automated analysis systems can support these assessments by providing quantitative measures of brain injury. However, the assessment of deep gray matter structures, which are critical to motor and executive function, remains difficult as a result of large anatomical injuries commonly observed in children with Cerebral Palsy (CP). Hence, this article proposes a robust surrogate marker of the extent of deep gray matter injury based on impingement due to local ventricular enlargement on surrounding anatomy. Local enlargement was computed using a statistical shape model of the lateral ventricles constructed from 44 healthy subjects. Measures of injury on 95 age-matched CP patients were used to train a regression model to predict six clinical measures of function. The robustness of identifying ventricular enlargement was demonstrated by an area under the curve of 0.91 when tested against a dichotomised expert clinical assessment. The measures also showed strong and significant relationships for multiple clinical scores, including: motor function (r 2  = 0.62, P < 0.005), executive function (r 2  = 0.55, P < 0.005), and communication (r 2  = 0.50, P < 0.005), especially compared to using volumes obtained from standard anatomical segmentation approaches. The lack of reliance on accurate anatomical segmentations and its resulting robustness to large anatomical variations is a key feature of the proposed automated approach. This coupled with its strong correlation with clinically meaningful scores, signifies the potential utility to repeatedly assess MRIs for clinicians diagnosing children with CP. Hum Brain Mapp 37:3795-3809, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Magnetothermal genetic deep brain stimulation of motor behaviors in awake, freely moving mice

PubMed Central

Zhang, Qian; Castellanos Rubio, Idoia; del Pino, Pablo

2017-01-01

Establishing how neurocircuit activation causes particular behaviors requires modulating the activity of specific neurons. Here, we demonstrate that magnetothermal genetic stimulation provides tetherless deep brain activation sufficient to evoke motor behavior in awake mice. The approach uses alternating magnetic fields to heat superparamagnetic nanoparticles on the neuronal membrane. Neurons, heat-sensitized by expressing TRPV1 are activated with magnetic field application. Magnetothermal genetic stimulation in the motor cortex evoked ambulation, deep brain stimulation in the striatum caused rotation around the body-axis, and stimulation near the ridge between ventral and dorsal striatum caused freezing-of-gait. The duration of the behavior correlated tightly with field application. This approach provides genetically and spatially targetable, repeatable and temporarily precise activation of deep-brain circuits without the need for surgical implantation of any device. PMID:28826470

Mood stability in Parkinson disease following deep brain stimulation: a 6-month prospective follow-up study.

PubMed

Chopra, Amit; Abulseoud, Osama A; Sampson, Shirlene; Lee, Kendall H; Klassen, Bryan T; Fields, Julie A; Matsumoto, Joseph Y; Adams, Andrea C; Stoppel, Cynthia J; Geske, Jennifer R; Frye, Mark A

2014-01-01

Deep brain stimulation for Parkinson disease has been associated with psychiatric adverse effects including anxiety, depression, mania, psychosis, and suicide. The purpose of this study was to evaluate the safety of deep brain stimulation in a large Parkinson disease clinical practice. Patients approved for surgery by the Mayo Clinic deep brain stimulation clinical committee participated in a 6-month prospective naturalistic follow-up study. In addition to the Unified Parkinson's Disease Rating Scale, stability and psychiatric safety were measured using the Beck Depression Inventory, Hamilton Depression Rating Scale, and Young Mania Rating scale. Outcomes were compared in patients with Parkinson disease who had a psychiatric history to those with no co-morbid psychiatric history. The study was completed by 49 of 54 patients. Statistically significant 6-month baseline to end-point improvement was found in motor and mood scales. No significant differences were found in psychiatric outcomes based on the presence or absence of psychiatric comorbidity. Our study suggests that patients with Parkinson disease who have a history of psychiatric co-morbidity can safely respond to deep brain stimulation with no greater risk of psychiatric adverse effect occurrence. A multidisciplinary team approach, including careful psychiatric screening ensuring mood stabilization and psychiatric follow-up, should be viewed as standard of care to optimize the psychiatric outcome in the course of deep brain stimulation treatment. © 2013 Published by The Academy of Psychosomatic Medicine on behalf of The Academy of Psychosomatic Medicine.

Transcranial magnetic stimulation: Improved coil design for deep brain investigation

NASA Astrophysics Data System (ADS)

Crowther, L. J.; Marketos, P.; Williams, P. I.; Melikhov, Y.; Jiles, D. C.; Starzewski, J. H.

2011-04-01

This paper reports on a design for a coil for transcranial magnetic stimulation. The design shows potential for improving the penetration depth of the magnetic field, allowing stimulation of subcortical structures within the brain. The magnetic and induced electric fields in the human head have been calculated with finite element electromagnetic modeling software and compared with empirical measurements. Results show that the coil design used gives improved penetration depth, but also indicates the likelihood of stimulation of additional tissue resulting from the spatial distribution of the magnetic field.

Getting signals into the brain: visual prosthetics through thalamic microstimulation.

PubMed

Pezaris, John S; Eskandar, Emad N

2009-07-01

Common causes of blindness are diseases that affect the ocular structures, such as glaucoma, retinitis pigmentosa, and macular degeneration, rendering the eyes no longer sensitive to light. The visual pathway, however, as a predominantly central structure, is largely spared in these cases. It is thus widely thought that a device-based prosthetic approach to restoration of visual function will be effective and will enjoy similar success as cochlear implants have for restoration of auditory function. In this article the authors review the potential locations for stimulation electrode placement for visual prostheses, assessing the anatomical and functional advantages and disadvantages of each. Of particular interest to the neurosurgical community is placement of deep brain stimulating electrodes in thalamic structures that has shown substantial promise in an animal model. The theory of operation of visual prostheses is discussed, along with a review of the current state of knowledge. Finally, the visual prosthesis is proposed as a model for a general high-fidelity machine-brain interface.

Composite technique for regional neurochemical studies: measurement of energy and neurotransmitter metabolites in single tissue sample.

PubMed

Djuricic, B M; Ueki, Y; Spatz, M

1985-06-01

A combined method is described for the determination of various metabolites from a single tissue sample of the brain. It comprises a quick inactivation of cerebral enzymes by microwave irradiation, easy separation of the desired brain regions, and perchloric acid extraction of tissue substances, which are assayed either by specific enzymatic techniques or by HPLC with electrochemical detection. The obtained values of most energy and neurotransmitter metabolites in the brain are in agreement with those reported using other methods. However, this technique, in contrast to the brain freezing in vitro or freeze-blowing, provides a more efficient procedure for rapid arrest of cerebral metabolism even in the deep brain structures and is therefore suitable for detection of early changes particularly those occurring in experimental pathological conditions such as ischemia.

Midsagittal brain variation and MRI shape analysis of the precuneus in adult individuals.

PubMed

Bruner, Emiliano; Rangel de Lázaro, Gizéh; de la Cuétara, José Manuel; Martín-Loeches, Manuel; Colom, Roberto; Jacobs, Heidi I L

2014-04-01

Recent analyses indicate that the precuneus is one of the main centres of integration in terms of functional and structural processes within the human brain. This neuroanatomical element is formed by different subregions, involved in visuo-spatial integration, memory and self-awareness. We analysed the midsagittal brain shape in a sample of adult humans (n = 90) to evidence the patterns of variability and geometrical organization of this area. Interestingly, the major brain covariance pattern within adult humans is strictly associated with the relative proportions of the precuneus. Its morphology displays a marked individual variation, both in terms of geometry (mostly in its longitudinal dimensions) and anatomy (patterns of convolution). No patent differences are evident between males and females, and the allometric effect of size is minimal. However, in terms of morphology, the precuneus does not represent an individual module, being influenced by different neighbouring structures. Taking into consideration the apparent involvement of the precuneus in higher-order human brain functions and evolution, its wide variation further stresses the important role of these deep parietal areas in modern neuroanatomical organization. © 2014 Anatomical Society.

TuMore: generation of synthetic brain tumor MRI data for deep learning based segmentation approaches

NASA Astrophysics Data System (ADS)

Lindner, Lydia; Pfarrkirchner, Birgit; Gsaxner, Christina; Schmalstieg, Dieter; Egger, Jan

2018-03-01

Accurate segmentation and measurement of brain tumors plays an important role in clinical practice and research, as it is critical for treatment planning and monitoring of tumor growth. However, brain tumor segmentation is one of the most challenging tasks in medical image analysis. Since manual segmentations are subjective, time consuming and neither accurate nor reliable, there exists a need for objective, robust and fast automated segmentation methods that provide competitive performance. Therefore, deep learning based approaches are gaining interest in the field of medical image segmentation. When the training data set is large enough, deep learning approaches can be extremely effective, but in domains like medicine, only limited data is available in the majority of cases. Due to this reason, we propose a method that allows to create a large dataset of brain MRI (Magnetic Resonance Imaging) images containing synthetic brain tumors - glioblastomas more specifically - and the corresponding ground truth, that can be subsequently used to train deep neural networks.

What makes deeply encoded items memorable? Insights into the levels of processing framework from neuroimaging and neuromodulation.

PubMed

Galli, Giulia

2014-01-01

When we form new memories, their mnestic fate largely depends upon the cognitive operations set in train during encoding. A typical observation in experimental as well as everyday life settings is that if we learn an item using semantic or "deep" operations, such as attending to its meaning, memory will be better than if we learn the same item using more "shallow" operations, such as attending to its structural features. In the psychological literature, this phenomenon has been conceptualized within the "levels of processing" framework and has been consistently replicated since its original proposal by Craik and Lockhart in 1972. However, the exact mechanisms underlying the memory advantage for deeply encoded items are not yet entirely understood. A cognitive neuroscience perspective can add to this field by clarifying the nature of the processes involved in effective deep and shallow encoding and how they are instantiated in the brain, but so far there has been little work to systematically integrate findings from the literature. This work aims to fill this gap by reviewing, first, some of the key neuroimaging findings on the neural correlates of deep and shallow episodic encoding and second, emerging evidence from studies using neuromodulatory approaches such as psychopharmacology and non-invasive brain stimulation. Taken together, these studies help further our understanding of levels of processing. In addition, by showing that deep encoding can be modulated by acting upon specific brain regions or systems, the reviewed studies pave the way for selective enhancements of episodic encoding processes.

Hemodynamic monitoring in different cortical layers with a single fiber optical system

NASA Astrophysics Data System (ADS)

Yu, Linhui; Noor, M. Sohail; Kiss, Zelma H. T.; Murari, Kartikeya

2018-02-01

Functional monitoring of highly-localized deep brain structures is of great interest. However, due to light scattering, optical methods have limited depth penetration or can only measure from a large volume. In this research, we demonstrate continuous measurement of hemodynamics in different cortical layers in response to thalamic deep brain stimulation (DBS) using a single fiber optical system. A 200-μm-core-diameter multimode fiber is used to deliver and collect light from tissue. The fiber probe can be stereotaxically implanted into the brain region of interest at any depth to measure the di use reflectance spectra from a tissue volume of 0.02-0.03 mm3 near the fiber tip. Oxygenation is then extracted from the reflectance spectra using an algorithm based on Monte Carlo simulations. Measurements were performed on the surface (cortical layer I) and at 1.5 mm depth (cortical layer VI) of the motor cortex in anesthetized rats with thalamic DBS. Preliminary results revealed the oxygenation changes in response to DBS. Moreover, the baseline as well as the stimulus-evoked change in oxygenation were different at the two depths of cortex.

Minimally invasive multimode optical fiber microendoscope for deep brain fluorescence imaging

PubMed Central

Ohayon, Shay; Caravaca-Aguirre, Antonio; Piestun, Rafael; DiCarlo, James J.

2018-01-01

A major open challenge in neuroscience is the ability to measure and perturb neural activity in vivo from well defined neural sub-populations at cellular resolution anywhere in the brain. However, limitations posed by scattering and absorption prohibit non-invasive multi-photon approaches for deep (>2mm) structures, while gradient refractive index (GRIN) endoscopes are relatively thick and can cause significant damage upon insertion. Here, we present a novel micro-endoscope design to image neural activity at arbitrary depths via an ultra-thin multi-mode optical fiber (MMF) probe that has 5–10X thinner diameter than commercially available micro-endoscopes. We demonstrate micron-scale resolution, multi-spectral and volumetric imaging. In contrast to previous approaches, we show that this method has an improved acquisition speed that is sufficient to capture rapid neuronal dynamics in-vivo in rodents expressing a genetically encoded calcium indicator (GCaMP). Our results emphasize the potential of this technology in neuroscience applications and open up possibilities for cellular resolution imaging in previously unreachable brain regions. PMID:29675297

A Programmable High-Voltage Compliance Neural Stimulator for Deep Brain Stimulation in Vivo

PubMed Central

Gong, Cihun-Siyong Alex; Lai, Hsin-Yi; Huang, Sy-Han; Lo, Yu-Chun; Lee, Nicole; Chen, Pin-Yuan; Tu, Po-Hsun; Yang, Chia-Yen; Lin, James Chang-Chieh; Chen, You-Yin

2015-01-01

Deep brain stimulation (DBS) is one of the most effective therapies for movement and other disorders. The DBS neurosurgical procedure involves the implantation of a DBS device and a battery-operated neurotransmitter, which delivers electrical impulses to treatment targets through implanted electrodes. The DBS modulates the neuronal activities in the brain nucleus for improving physiological responses as long as an electric discharge above the stimulation threshold can be achieved. In an effort to improve the performance of an implanted DBS device, the device size, implementation cost, and power efficiency are among the most important DBS device design aspects. This study aims to present preliminary research results of an efficient stimulator, with emphasis on conversion efficiency. The prototype stimulator features high-voltage compliance, implemented with only a standard semiconductor process, without the use of extra masks in the foundry through our proposed circuit structure. The results of animal experiments, including evaluation of evoked responses induced by thalamic electrical stimuli with our fabricated chip, were shown to demonstrate the proof of concept of our design. PMID:26029954

Using deep belief network modelling to characterize differences in brain morphometry in schizophrenia

PubMed Central

Pinaya, Walter H. L.; Gadelha, Ary; Doyle, Orla M.; Noto, Cristiano; Zugman, André; Cordeiro, Quirino; Jackowski, Andrea P.; Bressan, Rodrigo A.; Sato, João R.

2016-01-01

Neuroimaging-based models contribute to increasing our understanding of schizophrenia pathophysiology and can reveal the underlying characteristics of this and other clinical conditions. However, the considerable variability in reported neuroimaging results mirrors the heterogeneity of the disorder. Machine learning methods capable of representing invariant features could circumvent this problem. In this structural MRI study, we trained a deep learning model known as deep belief network (DBN) to extract features from brain morphometry data and investigated its performance in discriminating between healthy controls (N = 83) and patients with schizophrenia (N = 143). We further analysed performance in classifying patients with a first-episode psychosis (N = 32). The DBN highlighted differences between classes, especially in the frontal, temporal, parietal, and insular cortices, and in some subcortical regions, including the corpus callosum, putamen, and cerebellum. The DBN was slightly more accurate as a classifier (accuracy = 73.6%) than the support vector machine (accuracy = 68.1%). Finally, the error rate of the DBN in classifying first-episode patients was 56.3%, indicating that the representations learned from patients with schizophrenia and healthy controls were not suitable to define these patients. Our data suggest that deep learning could improve our understanding of psychiatric disorders such as schizophrenia by improving neuromorphometric analyses. PMID:27941946

Using deep belief network modelling to characterize differences in brain morphometry in schizophrenia

NASA Astrophysics Data System (ADS)

Pinaya, Walter H. L.; Gadelha, Ary; Doyle, Orla M.; Noto, Cristiano; Zugman, André; Cordeiro, Quirino; Jackowski, Andrea P.; Bressan, Rodrigo A.; Sato, João R.

2016-12-01

Neuroimaging-based models contribute to increasing our understanding of schizophrenia pathophysiology and can reveal the underlying characteristics of this and other clinical conditions. However, the considerable variability in reported neuroimaging results mirrors the heterogeneity of the disorder. Machine learning methods capable of representing invariant features could circumvent this problem. In this structural MRI study, we trained a deep learning model known as deep belief network (DBN) to extract features from brain morphometry data and investigated its performance in discriminating between healthy controls (N = 83) and patients with schizophrenia (N = 143). We further analysed performance in classifying patients with a first-episode psychosis (N = 32). The DBN highlighted differences between classes, especially in the frontal, temporal, parietal, and insular cortices, and in some subcortical regions, including the corpus callosum, putamen, and cerebellum. The DBN was slightly more accurate as a classifier (accuracy = 73.6%) than the support vector machine (accuracy = 68.1%). Finally, the error rate of the DBN in classifying first-episode patients was 56.3%, indicating that the representations learned from patients with schizophrenia and healthy controls were not suitable to define these patients. Our data suggest that deep learning could improve our understanding of psychiatric disorders such as schizophrenia by improving neuromorphometric analyses.

Differential effects of deep brain stimulation on verbal fluency.

PubMed

Ehlen, Felicitas; Schoenecker, Thomas; Kühn, Andrea A; Klostermann, Fabian

2014-07-01

We aimed at gaining insights into principles of subcortical lexical processing. Therefore, effects of deep brain stimulation (DBS) in different target structures on verbal fluency (VF) were tested. VF was assessed with active vs. inactivated DBS in 13 and 14 patients with DBS in the vicinity of the thalamic ventral intermediate nucleus (VIM) and, respectively, of the subthalamic nucleus (STN). Results were correlated to electrode localizations in postoperative MRI, and compared to those of 12 age-matched healthy controls. Patients' VF performance was generally below normal. However, while activation of DBS in the vicinity of VIM provoked marked VF decline, it induced subtle phonemic VF enhancement in the vicinity of STN. The effects correlated with electrode localizations in left hemispheric stimulation sites. The results show distinct dependencies of VF on DBS in the vicinity of VIM vs. STN. Particular risks for deterioration occur in patients with relatively ventromedial thalamic electrodes. Copyright © 2014 Elsevier Inc. All rights reserved.

Brain Stimulation in Alzheimer's Disease.

PubMed

Chang, Chun-Hung; Lane, Hsien-Yuan; Lin, Chieh-Hsin

2018-01-01

Brain stimulation techniques can modulate cognitive functions in many neuropsychiatric diseases. Pilot studies have shown promising effects of brain stimulations on Alzheimer's disease (AD). Brain stimulations can be categorized into non-invasive brain stimulation (NIBS) and invasive brain stimulation (IBS). IBS includes deep brain stimulation (DBS), and invasive vagus nerve stimulation (VNS), whereas NIBS includes transcranial magnetic stimulation (TMS), transcranial direct current stimulation (tDCS), transcranial alternating current stimulation (tACS), electroconvulsive treatment (ECT), magnetic seizure therapy (MST), cranial electrostimulation (CES), and non-invasive VNS. We reviewed the cutting-edge research on these brain stimulation techniques and discussed their therapeutic effects on AD. Both IBS and NIBS may have potential to be developed as novel treatments for AD; however, mixed findings may result from different study designs, patients selection, population, or samples sizes. Therefore, the efficacy of NIBS and IBS in AD remains uncertain, and needs to be further investigated. Moreover, more standardized study designs with larger sample sizes and longitudinal follow-up are warranted for establishing a structural guide for future studies and clinical application.

Parkinsonian gait improves with bilateral subthalamic nucleus deep brain stimulation during cognitive multi-tasking.

PubMed

Chenji, Gaurav; Wright, Melissa L; Chou, Kelvin L; Seidler, Rachael D; Patil, Parag G

2017-05-01

Gait impairment in Parkinson's disease reduces mobility and increases fall risk, particularly during cognitive multi-tasking. Studies suggest that bilateral subthalamic deep brain stimulation, a common surgical therapy, degrades motor performance under cognitive dual-task conditions, compared to unilateral stimulation. To measure the impact of bilateral versus unilateral subthalamic deep brain stimulation on walking kinematics with and without cognitive dual-tasking. Gait kinematics of seventeen patients with advanced Parkinson's disease who had undergone bilateral subthalamic deep brain stimulation were examined off medication under three stimulation states (bilateral, unilateral left, unilateral right) with and without a cognitive challenge, using an instrumented walkway system. Consistent with earlier studies, gait performance declined for all six measured parameters under cognitive dual-task conditions, independent of stimulation state. However, bilateral stimulation produced greater improvements in step length and double-limb support time than unilateral stimulation, and achieved similar performance for other gait parameters. Contrary to expectations from earlier studies of dual-task motor performance, bilateral subthalamic deep brain stimulation may assist in maintaining temporal and spatial gait performance under cognitive dual-task conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Automatic recognition of holistic functional brain networks using iteratively optimized convolutional neural networks (IO-CNN) with weak label initialization.

PubMed

Zhao, Yu; Ge, Fangfei; Liu, Tianming

2018-07-01

fMRI data decomposition techniques have advanced significantly from shallow models such as Independent Component Analysis (ICA) and Sparse Coding and Dictionary Learning (SCDL) to deep learning models such Deep Belief Networks (DBN) and Convolutional Autoencoder (DCAE). However, interpretations of those decomposed networks are still open questions due to the lack of functional brain atlases, no correspondence across decomposed or reconstructed networks across different subjects, and significant individual variabilities. Recent studies showed that deep learning, especially deep convolutional neural networks (CNN), has extraordinary ability of accommodating spatial object patterns, e.g., our recent works using 3D CNN for fMRI-derived network classifications achieved high accuracy with a remarkable tolerance for mistakenly labelled training brain networks. However, the training data preparation is one of the biggest obstacles in these supervised deep learning models for functional brain network map recognitions, since manual labelling requires tedious and time-consuming labours which will sometimes even introduce label mistakes. Especially for mapping functional networks in large scale datasets such as hundreds of thousands of brain networks used in this paper, the manual labelling method will become almost infeasible. In response, in this work, we tackled both the network recognition and training data labelling tasks by proposing a new iteratively optimized deep learning CNN (IO-CNN) framework with an automatic weak label initialization, which enables the functional brain networks recognition task to a fully automatic large-scale classification procedure. Our extensive experiments based on ABIDE-II 1099 brains' fMRI data showed the great promise of our IO-CNN framework. Copyright © 2018 Elsevier B.V. All rights reserved.

Relationship between brain function (aEEG) and brain structure (MRI) and their predictive value for neurodevelopmental outcome of preterm infants.

PubMed

Hüning, Britta; Storbeck, Tobias; Bruns, Nora; Dransfeld, Frauke; Hobrecht, Julia; Karpienski, Julia; Sirin, Selma; Schweiger, Bernd; Weiss, Christel; Felderhoff-Müser, Ursula; Müller, Hanna

2018-05-22

To improve the prediction of neurodevelopmental outcome in very preterm infants, this study used the combination of amplitude-integrated electroencephalography (aEEG) within the first 72 h of life and cranial magnetic resonance imaging (MRI) at term equivalent age. A single-center cohort of 38 infants born before 32 weeks of gestation was subjected to both investigations. Structural measurements were performed on MRI. Multiple regression analysis was used to identify independent factors including functional and structural brain measurements associated with outcome at a corrected age of 24 months. aEEG parameters significantly correlated with MRI measurements. Reduced deep gray matter volume was associated with low Burdjalov Score on day 3 (p < 0.0001) and day 1-3 (p = 0.0012). The biparietal width and the transcerebellar diameter were related to Burdjalov Score on day 1 (p = 0.0111; p = 0.0002). The final multiple regression analysis revealed independent predictors of neurodevelopmental outcome: intraventricular hemorrhage (p = 0.0060) and interhemispheric distance (p = 0.0052) for mental developmental index; Burdjalov Score day 1 (p = 0.0201) and interhemispheric distance (p = 0.0142) for psychomotor developmental index. Functional aEEG parameters were associated with altered brain maturation on MRI. The combination of aEEG and MRI contributes to the prediction of outcome at 24 months. What is Known: • Prematurity remains a risk factor for impaired neurodevelopment. • aEEG is used to measure brain activity in preterm infants and cranial MRI is performed to identify structural gray and white matter abnormalities with impact on neurodevelopmental outcome. What is New: • aEEG parameters observed within the first 72 h of life were associated with altered deep gray matter volumes, biparietal width, and transcerebellar diameter at term equivalent age. • The combination of aEEG and MRI contributes to the prediction of neurodevelopmental outcome at 2 years of corrected age in very preterm infants.

Human brain atlas for automated region of interest selection in quantitative susceptibility mapping: application to determine iron content in deep gray matter structures.

PubMed

Lim, Issel Anne L; Faria, Andreia V; Li, Xu; Hsu, Johnny T C; Airan, Raag D; Mori, Susumu; van Zijl, Peter C M

2013-11-15

The purpose of this paper is to extend the single-subject Eve atlas from Johns Hopkins University, which currently contains diffusion tensor and T1-weighted anatomical maps, by including contrast based on quantitative susceptibility mapping. The new atlas combines a "deep gray matter parcellation map" (DGMPM) derived from a single-subject quantitative susceptibility map with the previously established "white matter parcellation map" (WMPM) from the same subject's T1-weighted and diffusion tensor imaging data into an MNI coordinate map named the "Everything Parcellation Map in Eve Space," also known as the "EvePM." It allows automated segmentation of gray matter and white matter structures. Quantitative susceptibility maps from five healthy male volunteers (30 to 33 years of age) were coregistered to the Eve Atlas with AIR and Large Deformation Diffeomorphic Metric Mapping (LDDMM), and the transformation matrices were applied to the EvePM to produce automated parcellation in subject space. Parcellation accuracy was measured with a kappa analysis for the left and right structures of six deep gray matter regions. For multi-orientation QSM images, the Kappa statistic was 0.85 between automated and manual segmentation, with the inter-rater reproducibility Kappa being 0.89 for the human raters, suggesting "almost perfect" agreement between all segmentation methods. Segmentation seemed slightly more difficult for human raters on single-orientation QSM images, with the Kappa statistic being 0.88 between automated and manual segmentation, and 0.85 and 0.86 between human raters. Overall, this atlas provides a time-efficient tool for automated coregistration and segmentation of quantitative susceptibility data to analyze many regions of interest. These data were used to establish a baseline for normal magnetic susceptibility measurements for over 60 brain structures of 30- to 33-year-old males. Correlating the average susceptibility with age-based iron concentrations in gray matter structures measured by Hallgren and Sourander (1958) allowed interpolation of the average iron concentration of several deep gray matter regions delineated in the EvePM. Copyright © 2013 Elsevier Inc. All rights reserved.

Human brain atlas for automated region of interest selection in quantitative susceptibility mapping: application to determine iron content in deep gray matter structures

PubMed Central

Lim, Issel Anne L.; Faria, Andreia V.; Li, Xu; Hsu, Johnny T.C.; Airan, Raag D.; Mori, Susumu; van Zijl, Peter C. M.

2013-01-01

The purpose of this paper is to extend the single-subject Eve atlas from Johns Hopkins University, which currently contains diffusion tensor and T1-weighted anatomical maps, by including contrast based on quantitative susceptibility mapping. The new atlas combines a “deep gray matter parcellation map” (DGMPM) derived from a single-subject quantitative susceptibility map with the previously established “white matter parcellation map” (WMPM) from the same subject’s T1-weighted and diffusion tensor imaging data into an MNI coordinate map named the “Everything Parcellation Map in Eve Space,” also known as the “EvePM.” It allows automated segmentation of gray matter and white matter structures. Quantitative susceptibility maps from five healthy male volunteers (30 to 33 years of age) were coregistered to the Eve Atlas with AIR and Large Deformation Diffeomorphic Metric Mapping (LDDMM), and the transformation matrices were applied to the EvePM to produce automated parcellation in subject space. Parcellation accuracy was measured with a kappa analysis for the left and right structures of six deep gray matter regions. For multi-orientation QSM images, the Kappa statistic was 0.85 between automated and manual segmentation, with the inter-rater reproducibility Kappa being 0.89 for the human raters, suggesting “almost perfect” agreement between all segmentation methods. Segmentation seemed slightly more difficult for human raters on single-orientation QSM images, with the Kappa statistic being 0.88 between automated and manual segmentation, and 0.85 and 0.86 between human raters. Overall, this atlas provides a time-efficient tool for automated coregistration and segmentation of quantitative susceptibility data to analyze many regions of interest. These data were used to establish a baseline for normal magnetic susceptibility measurements for over 60 brain structures of 30- to 33-year-old males. Correlating the average susceptibility with age-based iron concentrations in gray matter structures measured by Hallgren and Sourander (1958) allowed interpolation of the average iron concentration of several deep gray matter regions delineated in the EvePM. PMID:23769915

Functional MRI during Hippocampal Deep Brain Stimulation in the Healthy Rat Brain.

PubMed

Van Den Berge, Nathalie; Vanhove, Christian; Descamps, Benedicte; Dauwe, Ine; van Mierlo, Pieter; Vonck, Kristl; Keereman, Vincent; Raedt, Robrecht; Boon, Paul; Van Holen, Roel

2015-01-01

Deep Brain Stimulation (DBS) is a promising treatment for neurological and psychiatric disorders. The mechanism of action and the effects of electrical fields administered to the brain by means of an electrode remain to be elucidated. The effects of DBS have been investigated primarily by electrophysiological and neurochemical studies, which lack the ability to investigate DBS-related responses on a whole-brain scale. Visualization of whole-brain effects of DBS requires functional imaging techniques such as functional Magnetic Resonance Imaging (fMRI), which reflects changes in blood oxygen level dependent (BOLD) responses throughout the entire brain volume. In order to visualize BOLD responses induced by DBS, we have developed an MRI-compatible electrode and an acquisition protocol to perform DBS during BOLD fMRI. In this study, we investigate whether DBS during fMRI is valuable to study local and whole-brain effects of hippocampal DBS and to investigate the changes induced by different stimulation intensities. Seven rats were stereotactically implanted with a custom-made MRI-compatible DBS-electrode in the right hippocampus. High frequency Poisson distributed stimulation was applied using a block-design paradigm. Data were processed by means of Independent Component Analysis. Clusters were considered significant when p-values were <0.05 after correction for multiple comparisons. Our data indicate that real-time hippocampal DBS evokes a bilateral BOLD response in hippocampal and other mesolimbic structures, depending on the applied stimulation intensity. We conclude that simultaneous DBS and fMRI can be used to detect local and whole-brain responses to circuit activation with different stimulation intensities, making this technique potentially powerful for exploration of cerebral changes in response to DBS for both preclinical and clinical DBS.

Functional MRI during Hippocampal Deep Brain Stimulation in the Healthy Rat Brain

PubMed Central

Van Den Berge, Nathalie; Vanhove, Christian; Descamps, Benedicte; Dauwe, Ine; van Mierlo, Pieter; Vonck, Kristl; Keereman, Vincent; Raedt, Robrecht; Boon, Paul; Van Holen, Roel

2015-01-01

Deep Brain Stimulation (DBS) is a promising treatment for neurological and psychiatric disorders. The mechanism of action and the effects of electrical fields administered to the brain by means of an electrode remain to be elucidated. The effects of DBS have been investigated primarily by electrophysiological and neurochemical studies, which lack the ability to investigate DBS-related responses on a whole-brain scale. Visualization of whole-brain effects of DBS requires functional imaging techniques such as functional Magnetic Resonance Imaging (fMRI), which reflects changes in blood oxygen level dependent (BOLD) responses throughout the entire brain volume. In order to visualize BOLD responses induced by DBS, we have developed an MRI-compatible electrode and an acquisition protocol to perform DBS during BOLD fMRI. In this study, we investigate whether DBS during fMRI is valuable to study local and whole-brain effects of hippocampal DBS and to investigate the changes induced by different stimulation intensities. Seven rats were stereotactically implanted with a custom-made MRI-compatible DBS-electrode in the right hippocampus. High frequency Poisson distributed stimulation was applied using a block-design paradigm. Data were processed by means of Independent Component Analysis. Clusters were considered significant when p-values were <0.05 after correction for multiple comparisons. Our data indicate that real-time hippocampal DBS evokes a bilateral BOLD response in hippocampal and other mesolimbic structures, depending on the applied stimulation intensity. We conclude that simultaneous DBS and fMRI can be used to detect local and whole-brain responses to circuit activation with different stimulation intensities, making this technique potentially powerful for exploration of cerebral changes in response to DBS for both preclinical and clinical DBS. PMID:26193653

Thoracic surgery in patients with an implanted neurostimulator device.

PubMed

Meyring, Kristina; Zehnder, Adrian; Schmid, Ralph A; Kocher, Gregor J

2017-10-01

Movement disorders such as Parkinson's disease are increasingly treated with deep brain stimulators. Being implanted in a subcutaneous pocket in the chest region, thoracic surgical procedures can interfere with such devices, as they are sensible to external electromagnetic forces. Monopolar electrocautery can lead to dysfunction of the device or damage of the brain tissue caused by heat. We report a series of 3 patients with deep brain stimulators who underwent thoracic surgery. By turning off the deep brain stimulators before surgery and avoiding the use of monopolar cautery, electromagnetic interactions were avoided in all patients. © The Author 2017. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

Exploring avian deep-brain photoreceptors and their role in activating the neuroendocrine regulation of gonadal development.

PubMed

Kuenzel, Wayne J; Kang, Seong W; Zhou, Z Jimmy

2015-04-01

In the eyes of mammals, specialized photoreceptors called intrinsically photosensitive retinal ganglion cells (ipRGC) have been identified that sense photoperiodic or daylight exposure, providing them over time with seasonal information. Detectors of photoperiods are critical in vertebrates, particularly for timing the onset of reproduction each year. In birds, the eyes do not appear to monitor photoperiodic information; rather, neurons within at least 4 different brain structures have been proposed to function in this capacity. Specialized neurons, called deep brain photoreceptors (DBP), have been found in the septum and 3 hypothalamic areas. Within each of the 4 brain loci, one or more of 3 unique photopigments, including melanopsin, neuropsin, and vertebrate ancient opsin, have been identified. An experiment was designed to characterize electrophysiological responses of neurons proposed to be avian DBP following light stimulation. A second study used immature chicks raised under short-day photoperiods and transferred to long day lengths. Gene expression of photopigments was then determined in 3 septal-hypothalamic regions. Preliminary electrophysiological data obtained from patch-clamping neurons in brain slices have shown that bipolar neurons in the lateral septal organ responded to photostimulation comparable with mammalian ipRGC, particularly by showing depolarization and a delayed, slow response to directed light stimulation. Utilizing real-time reverse-transcription PCR, it was found that all 3 photopigments showed significantly increased gene expression in the septal-hypothalamic regions in chicks on the third day after being transferred to long-day photoperiods. Each dissected region contained structures previously proposed to have DBP. The highly significant increased gene expression for all 3 photopigments on the third, long-day photoperiod in brain regions proposed to contain 4 structures with DBP suggests that all 3 types of DBP (melanopsin, neuropsin, and vertebrate ancient opsin) in more than one neural site in the septal-hypothalamic area are involved in reproductive function. The neural response to light of at least 2 of the proposed DBP in the septal/hypothalamic region resembles the primitive, functional, sensory ipRGC well characterized in mammals. ©2015 Poultry Science Association Inc.

Multiplexed aberration measurement for deep tissue imaging in vivo

PubMed Central

Wang, Chen; Liu, Rui; Milkie, Daniel E.; Sun, Wenzhi; Tan, Zhongchao; Kerlin, Aaron; Chen, Tsai-Wen; Kim, Douglas S.; Ji, Na

2014-01-01

We describe a multiplexed aberration measurement method that modulates the intensity or phase of light rays at multiple pupil segments in parallel to determine their phase gradients. Applicable to fluorescent-protein-labeled structures of arbitrary complexity, it allows us to obtain diffraction-limited resolution in various samples in vivo. For the strongly scattering mouse brain, a single aberration correction improves structural and functional imaging of fine neuronal processes over a large imaging volume. PMID:25128976

Red and NIR light dosimetry in the human deep brain

NASA Astrophysics Data System (ADS)

Pitzschke, A.; Lovisa, B.; Seydoux, O.; Zellweger, M.; Pfleiderer, M.; Tardy, Y.; Wagnières, G.

2015-04-01

Photobiomodulation (PBM) appears promising to treat the hallmarks of Parkinson’s Disease (PD) in cellular or animal models. We measured light propagation in different areas of PD-relevant deep brain tissue during transcranial, transsphenoidal illumination (at 671 and 808 nm) of a cadaver head and modeled optical parameters of human brain tissue using Monte-Carlo simulations. Gray matter, white matter, cerebrospinal fluid, ventricles, thalamus, pons, cerebellum and skull bone were processed into a mesh of the skull (158 × 201 × 211 voxels; voxel side length: 1 mm). Optical parameters were optimized from simulated and measured fluence rate distributions. The estimated μeff for the different tissues was in all cases larger at 671 than at 808 nm, making latter a better choice for light delivery in the deep brain. Absolute values were comparable to those found in the literature or slightly smaller. The effective attenuation in the ventricles was considerably larger than literature values. Optimization yields a new set of optical parameters better reproducing the experimental data. A combination of PBM via the sphenoid sinus and oral cavity could be beneficial. A 20-fold higher efficiency of light delivery to the deep brain was achieved with ventricular instead of transcranial illumination. Our study demonstrates that it is possible to illuminate deep brain tissues transcranially, transsphenoidally and via different application routes. This opens therapeutic options for sufferers of PD or other cerebral diseases necessitating light therapy.

Deep learning for medical image segmentation - using the IBM TrueNorth neurosynaptic system

NASA Astrophysics Data System (ADS)

Moran, Steven; Gaonkar, Bilwaj; Whitehead, William; Wolk, Aidan; Macyszyn, Luke; Iyer, Subramanian S.

2018-03-01

Deep convolutional neural networks have found success in semantic image segmentation tasks in computer vision and medical imaging. These algorithms are executed on conventional von Neumann processor architectures or GPUs. This is suboptimal. Neuromorphic processors that replicate the structure of the brain are better-suited to train and execute deep learning models for image segmentation by relying on massively-parallel processing. However, given that they closely emulate the human brain, on-chip hardware and digital memory limitations also constrain them. Adapting deep learning models to execute image segmentation tasks on such chips, requires specialized training and validation. In this work, we demonstrate for the first-time, spinal image segmentation performed using a deep learning network implemented on neuromorphic hardware of the IBM TrueNorth Neurosynaptic System and validate the performance of our network by comparing it to human-generated segmentations of spinal vertebrae and disks. To achieve this on neuromorphic hardware, the training model constrains the coefficients of individual neurons to {-1,0,1} using the Energy Efficient Deep Neuromorphic (EEDN)1 networks training algorithm. Given the 1 million neurons and 256 million synapses, the scale and size of the neural network implemented by the IBM TrueNorth allows us to execute the requisite mapping between segmented images and non-uniform intensity MR images >20 times faster than on a GPU-accelerated network and using <0.1 W. This speed and efficiency implies that a trained neuromorphic chip can be deployed in intra-operative environments where real-time medical image segmentation is necessary.

Deep brain stimulation of the subthalamic nucleus enhances emotional processing in Parkinson disease.

PubMed

Schneider, Frank; Habel, Ute; Volkmann, Jens; Regel, Sabine; Kornischka, Jürgen; Sturm, Volker; Freund, Hans-Joachim

2003-03-01

High-frequency electrical stimulation of the subthalamic nucleus is a new and highly effective therapy for complications of long-term levodopa therapy and motor symptoms in advanced Parkinson disease (PD). Clinical observations indicate additional influence on emotional behavior. Electrical stimulation of deep brain nuclei with pulse rates above 100 Hz provokes a reversible, lesioning-like effect. Here, the effect of deep brain stimulation of the subthalamic nucleus on emotional, cognitive, and motor performance in patients with PD (n = 12) was examined. The results were compared with the effects of a suprathreshold dose of levodopa intended to transiently restore striatal dopamine deficiency. Patients were tested during medication off/stimulation off (STIM OFF), medication off/stimulation on (STIM ON), and during the best motor state after taking levodopa without deep brain stimulation (MED). More positive self-reported mood and an enhanced mood induction effect as well as improvement in emotional memory during STIM ON were observed, while during STIM OFF, patients revealed reduced emotional performance. Comparable effects were revealed by STIM ON and MED. Cognitive performance was not affected by the different conditions and treatments. Deep brain stimulation of the subthalamic nucleus selectively enhanced affective processing and subjective well-being and seemed to be antidepressive. Levodopa and deep brain stimulation had similar effects on emotion. This finding may provide new clues about the neurobiologic bases of emotion and mood disorders, and it illustrates the important role of the basal ganglia and the dopaminergic system in emotional processing in addition to the well-known motor and cognitive functions.

Effect of brain shift on the creation of functional atlases for deep brain stimulation surgery

PubMed Central

Pallavaram, Srivatsan; Remple, Michael S.; Neimat, Joseph S.; Kao, Chris; Konrad, Peter E.; D’Haese, Pierre-François

2011-01-01

Purpose In the recent past many groups have tried to build functional atlases of the deep brain using intra-operatively acquired information such as stimulation responses or micro-electrode recordings. An underlying assumption in building such atlases is that anatomical structures do not move between pre-operative imaging and intra-operative recording. In this study, we present evidences that this assumption is not valid. We quantify the effect of brain shift between pre-operative imaging and intra-operative recording on the creation of functional atlases using intra-operative somatotopy recordings and stimulation response data. Methods A total of 73 somatotopy points from 24 bilateral subthalamic nucleus (STN) implantations and 52 eye deviation stimulation response points from 17 bilateral STN implantations were used. These points were spatially normalized on a magnetic resonance imaging (MRI) atlas using a fully automatic non-rigid registration algorithm. Each implantation was categorized as having low, medium or large brain shift based on the amount of pneumocephalus visible on post-operative CT. The locations of somatotopy clusters and stimulation maps were analyzed for each category. Results The centroid of the large brain shift cluster of the somatotopy data (posterior, lateral, inferior: 3.06, 11.27, 5.36 mm) was found posterior, medial and inferior to that of the medium cluster (2.90, 13.57, 4.53 mm) which was posterior, medial and inferior to that of the low shift cluster (1.94, 13.92, 3.20 mm). The coordinates are referenced with respect to the mid-commissural point. Euclidean distances between the centroids were 1.68, 2.44 and 3.59 mm, respectively for low-medium, medium-large and low-large shift clusters. We found similar trends for the positions of the stimulation maps. The Euclidian distance between the highest probability locations on the low and medium-large shift maps was 4.06 mm. Conclusion The effect of brain shift in deep brain stimulation (DBS) surgery has been demonstrated using intra-operative somatotopy recordings as well as stimulation response data. The results not only indicate that considerable brain shift happens before micro-electrode recordings in DBS but also that brain shift affects the creation of accurate functional atlases. Therefore, care must be taken when building and using such atlases of intra-operative data and also when using intra-operative data to validate anatomical atlases. PMID:20033503

Automatic detection and segmentation of brain metastases on multimodal MR images with a deep convolutional neural network.

PubMed

Charron, Odelin; Lallement, Alex; Jarnet, Delphine; Noblet, Vincent; Clavier, Jean-Baptiste; Meyer, Philippe

2018-04-01

Stereotactic treatments are today the reference techniques for the irradiation of brain metastases in radiotherapy. The dose per fraction is very high, and delivered in small volumes (diameter <1 cm). As part of these treatments, effective detection and precise segmentation of lesions are imperative. Many methods based on deep-learning approaches have been developed for the automatic segmentation of gliomas, but very little for that of brain metastases. We adapted an existing 3D convolutional neural network (DeepMedic) to detect and segment brain metastases on MRI. At first, we sought to adapt the network parameters to brain metastases. We then explored the single or combined use of different MRI modalities, by evaluating network performance in terms of detection and segmentation. We also studied the interest of increasing the database with virtual patients or of using an additional database in which the active parts of the metastases are separated from the necrotic parts. Our results indicated that a deep network approach is promising for the detection and the segmentation of brain metastases on multimodal MRI. Copyright © 2018 Elsevier Ltd. All rights reserved.

A Low Power Micro Deep Brain Stimulation Device for Murine Preclinical Research.

PubMed

Kouzani, Abbas Z; Abulseoud, Osama A; Tye, Susannah J; Hosain, M D Kamal; Berk, Michael

2013-01-01

Deep brain stimulation has emerged as an effective medical procedure that has therapeutic efficacy in a number of neuropsychiatric disorders. Preclinical research involving laboratory animals is being conducted to study the principles, mechanisms, and therapeutic effects of deep brain stimulation. A bottleneck is, however, the lack of deep brain stimulation devices that enable long term brain stimulation in freely moving laboratory animals. Most of the existing devices employ complex circuitry, and are thus bulky. These devices are usually connected to the electrode that is implanted into the animal brain using long fixed wires. In long term behavioral trials, however, laboratory animals often need to continuously receive brain stimulation for days without interruption, which is difficult with existing technology. This paper presents a low power and lightweight portable microdeep brain stimulation device for laboratory animals. Three different configurations of the device are presented as follows: 1) single piece head mountable; 2) single piece back mountable; and 3) two piece back mountable. The device can be easily carried by the animal during the course of a clinical trial, and that it can produce non-stop stimulation current pulses of desired characteristics for over 12 days on a single battery. It employs passive charge balancing to minimize undesirable effects on the target tissue. The results of bench, in-vitro, and in-vivo tests to evaluate the performance of the device are presented.

Targeting of deep-brain structures in nonhuman primates using MR and CT Images

NASA Astrophysics Data System (ADS)

Chen, Antong; Hines, Catherine; Dogdas, Belma; Bone, Ashleigh; Lodge, Kenneth; O'Malley, Stacey; Connolly, Brett; Winkelmann, Christopher T.; Bagchi, Ansuman; Lubbers, Laura S.; Uslaner, Jason M.; Johnson, Colena; Renger, John; Zariwala, Hatim A.

2015-03-01

In vivo gene delivery in central nervous systems of nonhuman primates (NHP) is an important approach for gene therapy and animal model development of human disease. To achieve a more accurate delivery of genetic probes, precise stereotactic targeting of brain structures is required. However, even with assistance from multi-modality 3D imaging techniques (e.g. MR and CT), the precision of targeting is often challenging due to difficulties in identification of deep brain structures, e.g. the striatum which consists of multiple substructures, and the nucleus basalis of meynert (NBM), which often lack clear boundaries to supporting anatomical landmarks. Here we demonstrate a 3D-image-based intracranial stereotactic approach applied toward reproducible intracranial targeting of bilateral NBM and striatum of rhesus. For the targeting we discuss the feasibility of an atlas-based automatic approach. Delineated originally on a high resolution 3D histology-MR atlas set, the NBM and the striatum could be located on the MR image of a rhesus subject through affine and nonrigid registrations. The atlas-based targeting of NBM was compared with the targeting conducted manually by an experienced neuroscientist. Based on the targeting, the trajectories and entry points for delivering the genetic probes to the targets could be established on the CT images of the subject after rigid registration. The accuracy of the targeting was assessed quantitatively by comparison between NBM locations obtained automatically and manually, and finally demonstrated qualitatively via post mortem analysis of slices that had been labelled via Evan Blue infusion and immunohistochemistry.

Identification of autism spectrum disorder using deep learning and the ABIDE dataset.

PubMed

Heinsfeld, Anibal Sólon; Franco, Alexandre Rosa; Craddock, R Cameron; Buchweitz, Augusto; Meneguzzi, Felipe

2018-01-01

The goal of the present study was to apply deep learning algorithms to identify autism spectrum disorder (ASD) patients from large brain imaging dataset, based solely on the patients brain activation patterns. We investigated ASD patients brain imaging data from a world-wide multi-site database known as ABIDE (Autism Brain Imaging Data Exchange). ASD is a brain-based disorder characterized by social deficits and repetitive behaviors. According to recent Centers for Disease Control data, ASD affects one in 68 children in the United States. We investigated patterns of functional connectivity that objectively identify ASD participants from functional brain imaging data, and attempted to unveil the neural patterns that emerged from the classification. The results improved the state-of-the-art by achieving 70% accuracy in identification of ASD versus control patients in the dataset. The patterns that emerged from the classification show an anticorrelation of brain function between anterior and posterior areas of the brain; the anticorrelation corroborates current empirical evidence of anterior-posterior disruption in brain connectivity in ASD. We present the results and identify the areas of the brain that contributed most to differentiating ASD from typically developing controls as per our deep learning model.

Multimodal and Multiscale Deep Neural Networks for the Early Diagnosis of Alzheimer's Disease using structural MR and FDG-PET images.

PubMed

Lu, Donghuan; Popuri, Karteek; Ding, Gavin Weiguang; Balachandar, Rakesh; Beg, Mirza Faisal

2018-04-09

Alzheimer's Disease (AD) is a progressive neurodegenerative disease where biomarkers for disease based on pathophysiology may be able to provide objective measures for disease diagnosis and staging. Neuroimaging scans acquired from MRI and metabolism images obtained by FDG-PET provide in-vivo measurements of structure and function (glucose metabolism) in a living brain. It is hypothesized that combining multiple different image modalities providing complementary information could help improve early diagnosis of AD. In this paper, we propose a novel deep-learning-based framework to discriminate individuals with AD utilizing a multimodal and multiscale deep neural network. Our method delivers 82.4% accuracy in identifying the individuals with mild cognitive impairment (MCI) who will convert to AD at 3 years prior to conversion (86.4% combined accuracy for conversion within 1-3 years), a 94.23% sensitivity in classifying individuals with clinical diagnosis of probable AD, and a 86.3% specificity in classifying non-demented controls improving upon results in published literature.

[Abscess at the implant site following apical parodontitis. Hardware-related complications of deep brain stimulation].

PubMed

Sixel-Döring, F; Trenkwalder, C; Kappus, C; Hellwig, D

2006-08-01

Deep brain stimulation of the subthalamic nucleus is an important treatment option for advanced stages of idiopathic Parkinson's disease, leading to significant improvement of motor symptoms in suited patients. Hardware-related complications such as technical malfunction, skin erosion, and infections however cause patient discomfort and additional expense. The patient presented here suffered a putrid infection of the impulse generator site following only local dental treatment of apical parodontitis. Therefore, prophylactic systemic antibiotic treatment is recommended for patients with implanted deep brain stimulation devices in case of operations, dental procedures, or infectious disease.

Linear-array based full-view high-resolution photoacoustic computed tomography of whole mouse brain functions in vivo

NASA Astrophysics Data System (ADS)

Li, Lei; Zhang, Pengfei; Wang, Lihong V.

2018-02-01

Photoacoustic computed tomography (PACT) is a non-invasive imaging technique offering high contrast, high resolution, and deep penetration in biological tissues. We report a photoacoustic computed tomography (PACT) system equipped with a high frequency linear array for anatomical and functional imaging of the mouse whole brain. The linear array was rotationally scanned in the coronal plane to achieve the full-view coverage. We investigated spontaneous neural activities in the deep brain by monitoring the hemodynamics and observed strong interhemispherical correlations between contralateral regions, both in the cortical layer and in the deep regions.

Brain networks modulated by subthalamic nucleus deep brain stimulation.

PubMed

Accolla, Ettore A; Herrojo Ruiz, Maria; Horn, Andreas; Schneider, Gerd-Helge; Schmitz-Hübsch, Tanja; Draganski, Bogdan; Kühn, Andrea A

2016-09-01

Deep brain stimulation of the subthalamic nucleus is an established treatment for the motor symptoms of Parkinson's disease. Given the frequent occurrence of stimulation-induced affective and cognitive adverse effects, a better understanding about the role of the subthalamic nucleus in non-motor functions is needed. The main goal of this study is to characterize anatomical circuits modulated by subthalamic deep brain stimulation, and infer about the inner organization of the nucleus in terms of motor and non-motor areas. Given its small size and anatomical intersubject variability, functional organization of the subthalamic nucleus is difficult to investigate in vivo with current methods. Here, we used local field potential recordings obtained from 10 patients with Parkinson's disease to identify a subthalamic area with an analogous electrophysiological signature, namely a predominant beta oscillatory activity. The spatial accuracy was improved by identifying a single contact per macroelectrode for its vicinity to the electrophysiological source of the beta oscillation. We then conducted whole brain probabilistic tractography seeding from the previously identified contacts, and further described connectivity modifications along the macroelectrode's main axis. The designated subthalamic 'beta' area projected predominantly to motor and premotor cortical regions additional to connections to limbic and associative areas. More ventral subthalamic areas showed predominant connectivity to medial temporal regions including amygdala and hippocampus. We interpret our findings as evidence for the convergence of different functional circuits within subthalamic nucleus' portions deemed to be appropriate as deep brain stimulation target to treat motor symptoms in Parkinson's disease. Potential clinical implications of our study are illustrated by an index case where deep brain stimulation of estimated predominant non-motor subthalamic nucleus induced hypomanic behaviour. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Brain reorganization, not relative brain size, primarily characterizes anthropoid brain evolution.

PubMed

Smaers, J B; Soligo, C

2013-05-22

Comparative analyses of primate brain evolution have highlighted changes in size and internal organization as key factors underlying species diversity. It remains, however, unclear (i) how much variation in mosaic brain reorganization versus variation in relative brain size contributes to explaining the structural neural diversity observed across species, (ii) which mosaic changes contribute most to explaining diversity, and (iii) what the temporal origin, rates and processes are that underlie evolutionary shifts in mosaic reorganization for individual branches of the primate tree of life. We address these questions by combining novel comparative methods that allow assessing the temporal origin, rate and process of evolutionary changes on individual branches of the tree of life, with newly available data on volumes of key brain structures (prefrontal cortex, frontal motor areas and cerebrocerebellum) for a sample of 17 species (including humans). We identify patterns of mosaic change in brain evolution that mirror brain systems previously identified by electrophysiological and anatomical tract-tracing studies in non-human primates and functional connectivity MRI studies in humans. Across more than 40 Myr of anthropoid primate evolution, mosaic changes contribute more to explaining neural diversity than changes in relative brain size, and different mosaic patterns are differentially selected for when brains increase or decrease in size. We identify lineage-specific evolutionary specializations for all branches of the tree of life covered by our sample and demonstrate deep evolutionary roots for mosaic patterns associated with motor control and learning.

Brain reorganization, not relative brain size, primarily characterizes anthropoid brain evolution

PubMed Central

Smaers, J. B.; Soligo, C.

2013-01-01

Comparative analyses of primate brain evolution have highlighted changes in size and internal organization as key factors underlying species diversity. It remains, however, unclear (i) how much variation in mosaic brain reorganization versus variation in relative brain size contributes to explaining the structural neural diversity observed across species, (ii) which mosaic changes contribute most to explaining diversity, and (iii) what the temporal origin, rates and processes are that underlie evolutionary shifts in mosaic reorganization for individual branches of the primate tree of life. We address these questions by combining novel comparative methods that allow assessing the temporal origin, rate and process of evolutionary changes on individual branches of the tree of life, with newly available data on volumes of key brain structures (prefrontal cortex, frontal motor areas and cerebrocerebellum) for a sample of 17 species (including humans). We identify patterns of mosaic change in brain evolution that mirror brain systems previously identified by electrophysiological and anatomical tract-tracing studies in non-human primates and functional connectivity MRI studies in humans. Across more than 40 Myr of anthropoid primate evolution, mosaic changes contribute more to explaining neural diversity than changes in relative brain size, and different mosaic patterns are differentially selected for when brains increase or decrease in size. We identify lineage-specific evolutionary specializations for all branches of the tree of life covered by our sample and demonstrate deep evolutionary roots for mosaic patterns associated with motor control and learning. PMID:23536600

Near-infrared deep brain stimulation via upconversion nanoparticle–mediated optogenetics

NASA Astrophysics Data System (ADS)

Chen, Shuo; Weitemier, Adam Z.; Zeng, Xiao; He, Linmeng; Wang, Xiyu; Tao, Yanqiu; Huang, Arthur J. Y.; Hashimotodani, Yuki; Kano, Masanobu; Iwasaki, Hirohide; Parajuli, Laxmi Kumar; Okabe, Shigeo; Teh, Daniel B. Loong; All, Angelo H.; Tsutsui-Kimura, Iku; Tanaka, Kenji F.; Liu, Xiaogang; McHugh, Thomas J.

2018-02-01

Optogenetics has revolutionized the experimental interrogation of neural circuits and holds promise for the treatment of neurological disorders. It is limited, however, because visible light cannot penetrate deep inside brain tissue. Upconversion nanoparticles (UCNPs) absorb tissue-penetrating near-infrared (NIR) light and emit wavelength-specific visible light. Here, we demonstrate that molecularly tailored UCNPs can serve as optogenetic actuators of transcranial NIR light to stimulate deep brain neurons. Transcranial NIR UCNP-mediated optogenetics evoked dopamine release from genetically tagged neurons in the ventral tegmental area, induced brain oscillations through activation of inhibitory neurons in the medial septum, silenced seizure by inhibition of hippocampal excitatory cells, and triggered memory recall. UCNP technology will enable less-invasive optical neuronal activity manipulation with the potential for remote therapy.

Finite difference time domain (FDTD) modeling of implanted deep brain stimulation electrodes and brain tissue.

PubMed

Gabran, S R I; Saad, J H; Salama, M M A; Mansour, R R

2009-01-01

This paper demonstrates the electromagnetic modeling and simulation of an implanted Medtronic deep brain stimulation (DBS) electrode using finite difference time domain (FDTD). The model is developed using Empire XCcel and represents the electrode surrounded with brain tissue assuming homogenous and isotropic medium. The model is created to study the parameters influencing the electric field distribution within the tissue in order to provide reference and benchmarking data for DBS and intra-cortical electrode development.

Evolving Agents: Communication and Cognition

DTIC Science & Technology

2005-06-01

systems [11] and the first Chomsky ideas concerning mechanisms of language grammar related to deep structure [12] encountered CC of rules. Model-based...Perennial (2000) 3. Jackendoff, R.: Foundations of Language: Brain, Meaning, Grammar , Evolution. Oxford University Press, New York, NY (2002) 4. Pinker, S... University Press, Princeton, NJ (1961) 11. Minsky, M.L.: Semantic Information Processing. The MIT Press, Cambridge, MA (1968) 12. Chomsky , N

Low-dose x-ray tomography through a deep convolutional neural network

DOE PAGES

Yang, Xiaogang; De Andrade, Vincent; Scullin, William; ...

2018-02-07

Synchrotron-based X-ray tomography offers the potential of rapid large-scale reconstructions of the interiors of materials and biological tissue at fine resolution. However, for radiation sensitive samples, there remain fundamental trade-offs between damaging samples during longer acquisition times and reducing signals with shorter acquisition times. We present a deep convolutional neural network (CNN) method that increases the acquired X-ray tomographic signal by at least a factor of 10 during low-dose fast acquisition by improving the quality of recorded projections. Short exposure time projections enhanced with CNN show similar signal to noise ratios as compared with long exposure time projections and muchmore » lower noise and more structural information than low-dose fats acquisition without CNN. We optimized this approach using simulated samples and further validated on experimental nano-computed tomography data of radiation sensitive mouse brains acquired with a transmission X-ray microscopy. We demonstrate that automated algorithms can reliably trace brain structures in datasets collected with low dose-CNN. As a result, this method can be applied to other tomographic or scanning based X-ray imaging techniques and has great potential for studying faster dynamics in specimens.« less

Integrated one- and two-photon scanned oblique plane illumination (SOPi) microscopy for rapid volumetric imaging

NASA Astrophysics Data System (ADS)

Kumar, Manish; Kishore, Sandeep; Nasenbeny, Jordan; McLean, David L.; Kozorovitskiy, Yevgenia

2018-05-01

Versatile, sterically accessible imaging systems capable of in vivo rapid volumetric functional and structural imaging deep in the brain continue to be a limiting factor in neuroscience research. Towards overcoming this obstacle, we present integrated one- and two-photon scanned oblique plane illumination (SOPi) microscopy which uses a single front-facing microscope objective to provide light-sheet scanning based rapid volumetric imaging capability at subcellular resolution. Our planar scan-mirror based optimized light-sheet architecture allows for non-distorted scanning of volume samples, simplifying accurate reconstruction of the imaged volume. Integration of both one-photon (1P) and two-photon (2P) light-sheet microscopy in the same system allows for easy selection between rapid volumetric imaging and higher resolution imaging in scattering media. Using SOPi, we demonstrate deep, large volume imaging capability inside scattering mouse brain sections and rapid imaging speeds up to 10 volumes per second in zebrafish larvae expressing genetically encoded fluorescent proteins GFP or GCaMP6s. SOPi flexibility and steric access makes it adaptable for numerous imaging applications and broadly compatible with orthogonal techniques for actuating or interrogating neuronal structure and activity.

Integrated one- and two-photon scanned oblique plane illumination (SOPi) microscopy for rapid volumetric imaging.

PubMed

Kumar, Manish; Kishore, Sandeep; Nasenbeny, Jordan; McLean, David L; Kozorovitskiy, Yevgenia

2018-05-14

Versatile, sterically accessible imaging systems capable of in vivo rapid volumetric functional and structural imaging deep in the brain continue to be a limiting factor in neuroscience research. Towards overcoming this obstacle, we present integrated one- and two-photon scanned oblique plane illumination (SOPi, /sōpī/) microscopy which uses a single front-facing microscope objective to provide light-sheet scanning based rapid volumetric imaging capability at subcellular resolution. Our planar scan-mirror based optimized light-sheet architecture allows for non-distorted scanning of volume samples, simplifying accurate reconstruction of the imaged volume. Integration of both one-photon (1P) and two-photon (2P) light-sheet microscopy in the same system allows for easy selection between rapid volumetric imaging and higher resolution imaging in scattering media. Using SOPi, we demonstrate deep, large volume imaging capability inside scattering mouse brain sections and rapid imaging speeds up to 10 volumes per second in zebrafish larvae expressing genetically encoded fluorescent proteins GFP or GCaMP6s. SOPi's flexibility and steric access makes it adaptable for numerous imaging applications and broadly compatible with orthogonal techniques for actuating or interrogating neuronal structure and activity.

Low-dose x-ray tomography through a deep convolutional neural network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Xiaogang; De Andrade, Vincent; Scullin, William

Synchrotron-based X-ray tomography offers the potential of rapid large-scale reconstructions of the interiors of materials and biological tissue at fine resolution. However, for radiation sensitive samples, there remain fundamental trade-offs between damaging samples during longer acquisition times and reducing signals with shorter acquisition times. We present a deep convolutional neural network (CNN) method that increases the acquired X-ray tomographic signal by at least a factor of 10 during low-dose fast acquisition by improving the quality of recorded projections. Short exposure time projections enhanced with CNN show similar signal to noise ratios as compared with long exposure time projections and muchmore » lower noise and more structural information than low-dose fats acquisition without CNN. We optimized this approach using simulated samples and further validated on experimental nano-computed tomography data of radiation sensitive mouse brains acquired with a transmission X-ray microscopy. We demonstrate that automated algorithms can reliably trace brain structures in datasets collected with low dose-CNN. As a result, this method can be applied to other tomographic or scanning based X-ray imaging techniques and has great potential for studying faster dynamics in specimens.« less

Stereotactically Standard Areas: Applied Mathematics in the Service of Brain Targeting in Deep Brain Stimulation.

PubMed

Mavridis, Ioannis N

2017-12-11

The concept of stereotactically standard areas (SSAs) within human brain nuclei belongs to the knowledge of the modern field of stereotactic brain microanatomy. These are areas resisting the individual variability of the nuclear location in stereotactic space. This paper summarizes the current knowledge regarding SSAs. A mathematical formula of SSAs was recently invented, allowing for their robust, reproducible, and accurate application to laboratory studies and clinical practice. Thus, SSAs open new doors for the application of stereotactic microanatomy to highly accurate brain targeting, which is mainly useful for minimally invasive neurosurgical procedures, such as deep brain stimulation.

'Being in it together': living with a partner receiving deep brain stimulation for advanced Parkinson's disease--a hermeneutic phenomenological study.

PubMed

Haahr, Anita; Kirkevold, Marit; Hall, Elisabeth O C; Østergaard, Karen

2013-02-01

This article is a report of an exploration of the lived experience of being a spouse to a person living with advanced Parkinson's disease, before and during the first year of deep brain stimulation. Parkinson's disease is a chronic progressive neurodegenerative disease. It has a profound impact on the everyday life for patients and spouses. Deep brain stimulation is offered with the aim of reducing symptoms of Parkinson's disease. The treatment is known to improve quality of life for patients, but little is known of how spouses experience life following their partners' treatment. A longitudinal interview study with a hermeneutic phenomenological approach. Ten spouses were included in the study. Data were gathered in 2007-2008, through qualitative in-depth interviews with spouses once before and three times during the first year of their partners' treatment with Deep Brain Stimulation. Data collection and data analysis were influenced by the hermeneutic phenomenological methodology of van Manen. The uniting theme 'Solidarity - the base for joined responsibility and concern' was the foundation for the relationship between spouses and their partners. Before treatment, the theme 'Living in partnership' was dominant. After treatment two dichotomous courses were described 'A sense of freedom embracing life' and 'The challenge of changes and constraint'. Spouses are deeply involved in their partners' illness and their experience of life is highly affected by their partners' illness, both before and after deep brain stimulation. The relationship is founded on solidarity and responsibility, which emphasizes spouses' need to be informed and involved in the process following Deep Brain Stimulation. © 2012 Blackwell Publishing Ltd.

Effects of deep brain stimulation in dyskinetic cerebral palsy: a meta-analysis.

PubMed

Koy, Anne; Hellmich, Martin; Pauls, K Amande M; Marks, Warren; Lin, Jean-Pierre; Fricke, Oliver; Timmermann, Lars

2013-05-01

Secondary dystonia encompasses a heterogeneous group with different etiologies. Cerebral palsy is the most common cause. Pharmacological treatment is often unsatisfactory. There are only limited data on the therapeutic outcomes of deep brain stimulation in dyskinetic cerebral palsy. The published literature regarding deep brain stimulation and secondary dystonia was reviewed in a meta-analysis to reevaluate the effect on cerebral palsy. The Burke-Fahn-Marsden Dystonia Rating Scale movement score was chosen as the primary outcome measure. Outcome over time was evaluated and summarized by mixed-model repeated-measures analysis, paired Student t test, and Pearson's correlation coefficient. Twenty articles comprising 68 patients with cerebral palsy undergoing deep brain stimulation assessed by the Burke-Fahn-Marsden Dystonia Rating Scale were identified. Most articles were case reports reflecting great variability in the score and duration of follow-up. The mean Burke-Fahn-Marsden Dystonia Rating Scale movement score was 64.94 ± 25.40 preoperatively and dropped to 50.5 ± 26.77 postoperatively, with a mean improvement of 23.6% (P < .001) at a median follow-up of 12 months. The mean Burke-Fahn-Marsden Dystonia Rating Scale disability score was 18.54 ± 6.15 preoperatively and 16.83 ± 6.42 postoperatively, with a mean improvement of 9.2% (P < .001). There was a significant negative correlation between severity of dystonia and clinical outcome (P < .05). Deep brain stimulation can be an effective treatment option for dyskinetic cerebral palsy. In view of the heterogeneous data, a prospective study with a large cohort of patients in a standardized setting with a multidisciplinary approach would be helpful in further evaluating the role of deep brain stimulation in cerebral palsy. © 2013 Movement Disorder Society. Copyright © 2013 Movement Disorder Society.

EKG-based detection of deep brain stimulation in fMRI studies.

PubMed

Fiveland, Eric; Madhavan, Radhika; Prusik, Julia; Linton, Renee; Dimarzio, Marisa; Ashe, Jeffrey; Pilitsis, Julie; Hancu, Ileana

2018-04-01

To assess the impact of synchronization errors between the assumed functional MRI paradigm timing and the deep brain stimulation (DBS) on/off cycling using a custom electrocardiogram-based triggering system METHODS: A detector for measuring and predicting the on/off state of cycling deep brain stimulation was developed and tested in six patients in office visits. Three-electrode electrocardiogram measurements, amplified by a commercial bio-amplifier, were used as input for a custom electronics box (e-box). The e-box transformed the deep brain stimulation waveforms into transistor-transistor logic pulses, recorded their timing, and propagated it in time. The e-box was used to trigger task-based deep brain stimulation functional MRI scans in 5 additional subjects; the impact of timing accuracy on t-test values was investigated in a simulation study using the functional MRI data. Following locking to each patient's individual waveform, the e-box was shown to predict stimulation onset with an average absolute error of 112 ± 148 ms, 30 min after disconnecting from the patients. The subsecond accuracy of the e-box in predicting timing onset is more than adequate for our slow varying, 30-/30-s on/off stimulation paradigm. Conversely, the experimental deep brain stimulation onset prediction accuracy in the absence of the e-box, which could be off by as much as 4 to 6 s, could significantly decrease activation strength. Using this detector, stimulation can be accurately synchronized to functional MRI acquisitions, without adding any additional hardware in the MRI environment. Magn Reson Med 79:2432-2439, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Theory of feedback controlled brain stimulations for Parkinson's disease

NASA Astrophysics Data System (ADS)

Sanzeni, A.; Celani, A.; Tiana, G.; Vergassola, M.

2016-01-01

Limb tremor and other debilitating symptoms caused by the neurodegenerative Parkinson's disease are currently treated by administering drugs and by fixed-frequency deep brain stimulation. The latter interferes directly with the brain dynamics by delivering electrical impulses to neurons in the subthalamic nucleus. While deep brain stimulation has shown therapeutic benefits in many instances, its mechanism is still unclear. Since its understanding could lead to improved protocols of stimulation and feedback control, we have studied a mathematical model of the many-body neural network dynamics controlling the dynamics of the basal ganglia. On the basis of the results obtained from the model, we propose a new procedure of active stimulation, that depends on the feedback of the network and that respects the constraints imposed by existing technology. We show by numerical simulations that the new protocol outperforms the standard ones for deep brain stimulation and we suggest future experiments that could further improve the feedback procedure.

Scientific and ethical issues related to deep brain stimulation for disorders of mood, behavior, and thought.

PubMed

Rabins, Peter; Appleby, Brian S; Brandt, Jason; DeLong, Mahlon R; Dunn, Laura B; Gabriëls, Loes; Greenberg, Benjamin D; Haber, Suzanne N; Holtzheimer, Paul E; Mari, Zoltan; Mayberg, Helen S; McCann, Evelyn; Mink, Sallie P; Rasmussen, Steven; Schlaepfer, Thomas E; Vawter, Dorothy E; Vitek, Jerrold L; Walkup, John; Mathews, Debra J H

2009-09-01

A 2-day consensus conference was held to examine scientific and ethical issues in the application of deep brain stimulation for treating mood and behavioral disorders, such as major depression, obsessive-compulsive disorder, and Tourette syndrome. The primary objectives of the conference were to (1) establish consensus among participants about the design of future clinical trials of deep brain stimulation for disorders of mood, behavior, and thought and (2) develop standards for the protection of human subjects participating in such studies. Conference participants identified 16 key points for guiding research in this growing field. The adoption of the described guidelines would help to protect the safety and rights of research subjects who participate in clinical trials of deep brain stimulation for disorders of mood, behavior, and thought and have further potential to benefit other stakeholders in the research process, including clinical researchers and device manufactures. That said, the adoption of the guidelines will require broad and substantial commitment from many of these same stakeholders.

Primary experimental study on safety of deep brain stimulation in RF electromagnetic field.

PubMed

Jun, Xu; Luming, Li; Hongwei, Hao

2009-01-01

With the rapid growth of clinical application of Deep Brain Stimulation, its safety and functional concern in the electromagnetic field, another pollution becoming much more serious, has become more and more significant. Meanwhile, the measuring standards on Electromagnetic Compatibility (EMC) for DBS are still incomplete. Particularly, the knowledge of the electromagnetic field induced signals on the implanted lead is ignorant while some informal reports some side effects. This paper briefly surmised the status of EMC standards on implantable medical devices. Based on the EMC experiments of DBS device we developed, two experiments for measuring the induced voltage of the deep brain stimulator in RF electromagnetic field were reported. The measured data showed that the induced voltage in some frequency was prominent, for example over 2V. As a primary research, we think these results would be significant to cause researcher to pay more attention to the EMC safety problem and biological effects of the induced voltage in deep brain stimulation and other implantable devices.

Body and brain temperature coupling: the critical role of cerebral blood flow

PubMed Central

Ackerman, Joseph J. H.; Yablonskiy, Dmitriy A.

2010-01-01

Direct measurements of deep-brain and body-core temperature were performed on rats to determine the influence of cerebral blood flow (CBF) on brain temperature regulation under static and dynamic conditions. Static changes of CBF were achieved using different anesthetics (chloral hydrate, CH; α-chloralose, αCS; and isoflurane, IF) with αCS causing larger decreases in CBF than CH and IF; dynamic changes were achieved by inducing transient hypercapnia (5% CO2 in 40% O2 and 55% N2). Initial deep-brain/body-core temperature differentials were anesthetic-type dependent with the largest differential observed with rats under αCS anesthesia (ca. 2°C). Hypercapnia induction raised rat brain temperature under all three anesthesia regimes, but by different anesthetic-dependent amounts correlated with the initial differentials—αCS anesthesia resulted in the largest brain temperature increase (0.32 ± 0.08°C), while CH and IF anesthesia lead to smaller increases (0.12 ± 0.03 and 0.16 ± 0.05°C, respectively). The characteristic temperature transition time for the hypercapnia-induced temperature increase was 2–3 min under CH and IF anesthesia and ~4 min under αCS anesthesia. We conclude that both, the deep-brain/body-core temperature differential and the characteristic temperature transition time correlate with CBF: a lower CBF promotes higher deep-brain/body-core temperature differentials and, upon hypercapnia challenge, longer characteristic transition times to increased temperatures. PMID:19277681

Body and brain temperature coupling: the critical role of cerebral blood flow.

PubMed

Zhu, Mingming; Ackerman, Joseph J H; Yablonskiy, Dmitriy A

2009-08-01

Direct measurements of deep-brain and body-core temperature were performed on rats to determine the influence of cerebral blood flow (CBF) on brain temperature regulation under static and dynamic conditions. Static changes of CBF were achieved using different anesthetics (chloral hydrate, CH; alpha-chloralose, alphaCS; and isoflurane, IF) with alphaCS causing larger decreases in CBF than CH and IF; dynamic changes were achieved by inducing transient hypercapnia (5% CO(2) in 40% O(2) and 55% N(2)). Initial deep-brain/body-core temperature differentials were anesthetic-type dependent with the largest differential observed with rats under alphaCS anesthesia (ca. 2 degrees C). Hypercapnia induction raised rat brain temperature under all three anesthesia regimes, but by different anesthetic-dependent amounts correlated with the initial differentials--alphaCS anesthesia resulted in the largest brain temperature increase (0.32 +/- 0.08 degrees C), while CH and IF anesthesia lead to smaller increases (0.12 +/- 0.03 and 0.16 +/- 0.05 degrees C, respectively). The characteristic temperature transition time for the hypercapnia-induced temperature increase was 2-3 min under CH and IF anesthesia and approximately 4 min under alphaCS anesthesia. We conclude that both, the deep-brain/body-core temperature differential and the characteristic temperature transition time correlate with CBF: a lower CBF promotes higher deep-brain/body-core temperature differentials and, upon hypercapnia challenge, longer characteristic transition times to increased temperatures.

Chaos in the heart: the interaction between body and mind

NASA Astrophysics Data System (ADS)

Redington, Dana

1993-11-01

A number of factors influence the chaotic dynamics of heart function. Genetics, age, sex, disease, the environment, experience, and of course the mind, play roles in influencing cardiovascular dynamics. The mind is of particular interest because it is an emergent phenomenon of the body admittedly seated and co-occurrent in the brain. The brain serves as the body's controller, and commands the heart through complex multipathway feedback loops. Structures deep within the brain, the hypothalamus and other centers in the brainstem, modulate heart function, partially as a result of afferent input from the body but also a result of higher mental processes. What can chaos in the body, i.e., the nonlinear dynamics of the heart, tell of the mind? This paper presents a brief overview of the spectral structure of heart rate activity followed by a summary of experimental results based on phase space analysis of data from semi-structured interviews. This paper then describes preliminary quantification of cardiovascular dynamics during different stressor conditions in an effort to apply more quantitative methods to clinical data.

Computational Modeling and Neuroimaging Techniques for Targeting during Deep Brain Stimulation

PubMed Central

Sweet, Jennifer A.; Pace, Jonathan; Girgis, Fady; Miller, Jonathan P.

2016-01-01

Accurate surgical localization of the varied targets for deep brain stimulation (DBS) is a process undergoing constant evolution, with increasingly sophisticated techniques to allow for highly precise targeting. However, despite the fastidious placement of electrodes into specific structures within the brain, there is increasing evidence to suggest that the clinical effects of DBS are likely due to the activation of widespread neuronal networks directly and indirectly influenced by the stimulation of a given target. Selective activation of these complex and inter-connected pathways may further improve the outcomes of currently treated diseases by targeting specific fiber tracts responsible for a particular symptom in a patient-specific manner. Moreover, the delivery of such focused stimulation may aid in the discovery of new targets for electrical stimulation to treat additional neurological, psychiatric, and even cognitive disorders. As such, advancements in surgical targeting, computational modeling, engineering designs, and neuroimaging techniques play a critical role in this process. This article reviews the progress of these applications, discussing the importance of target localization for DBS, and the role of computational modeling and novel neuroimaging in improving our understanding of the pathophysiology of diseases, and thus paving the way for improved selective target localization using DBS. PMID:27445709

A General Method for Evaluating Deep Brain Stimulation Effects on Intravenous Methamphetamine Self-Administration

PubMed Central

Batra, Vinita; Guerin, Glenn F.; Goeders, Nicholas E.; Wilden, Jessica A.

2016-01-01

Substance use disorders, particularly to methamphetamine, are devastating, relapsing diseases that disproportionally affect young people. There is a need for novel, effective and practical treatment strategies that are validated in animal models. Neuromodulation, including deep brain stimulation (DBS) therapy, refers to the use of electricity to influence pathological neuronal activity and has shown promise for psychiatric disorders, including drug dependence. DBS in clinical practice involves the continuous delivery of stimulation into brain structures using an implantable pacemaker-like system that is programmed externally by a physician to alleviate symptoms. This treatment will be limited in methamphetamine users due to challenging psychosocial situations. Electrical treatments that can be delivered intermittently, non-invasively and remotely from the drug-use setting will be more realistic. This article describes the delivery of intracranial electrical stimulation that is temporally and spatially separate from the drug-use environment for the treatment of IV methamphetamine dependence. Methamphetamine dependence is rapidly developed in rodents using an operant paradigm of intravenous (IV) self-administration that incorporates a period of extended access to drug and demonstrates both escalation of use and high motivation to obtain drug. PMID:26863392

Deep transcranial magnetic stimulation (dTMS) - beyond depression.

PubMed

Tendler, Aron; Barnea Ygael, Noam; Roth, Yiftach; Zangen, Abraham

2016-10-01

Deep transcranial magnetic stimulation (dTMS) utilizes different H-coils to study and treat a variety of psychiatric and neurological conditions with identifiable brain targets. The availability of this technology is dramatically changing the practice of psychiatry and neurology as it provides a safe and effective way to treat even drug-resistant patients. However, up until now, no effort was made to summarize the different types of H-coils that are available, and the conditions for which they were tested. Areas covered: Here we assembled all peer reviewed publication that used one of the H-coils, together with illustrations of the effective field they generate within the brain. Currently, the technology has FDA clearance for depression and European clearance for additional disorders, and multi-center trials are exploring its safety and effectiveness for OCD, PTSD, bipolar depression and nicotine addiction. Expert commentary: Taken together with positive results in smaller scale experiments, dTMS coils represent a non-invasive way to manipulate pathological activity in different brain structures and circuits. Advances in stimulation and imaging methods can now lead to efficacious and logical treatments. This should reduce the stigma associated with mental disorders, and improve access to psychiatric treatment.

Camptocormia and deep brain stimulation: The interesting overlapping etiologies and the therapeutic role of subthalamic nucleus-deep brain stimulation in Parkinson disease with camptocormia.

PubMed

Ekmekci, Hakan; Kaptan, Hulagu

2016-01-01

Camptocormia is known as "bent spine syndrome" and defined as a forward hyperflexion. The most common etiologic factor is related with the movement disorders, mainly in Parkinson's disease (PD). We present the case of a 51-year-old woman who has been followed with PD for the last 10 years, and also under the therapy for PD. An unappreciated correlation low back pain with camptocormia developed. She underwent deep brain stimulation (DBS) in the subthalamic nucleus bilaterally and improved her bending posture. The relationship between the DBS and camptocormia is discussed in this unique condition.

Deep Brain Stimulation for Essential Vocal Tremor: A Technical Report.

PubMed

Ho, Allen L; Choudhri, Omar; Sung, C Kwang; DiRenzo, Elizabeth E; Halpern, Casey H

2015-03-01

Essential vocal tremor (EVT) is the presence of a tremulous voice that is commonly associated with essential tremor. Patients with EVT often report a necessary increase in vocal effort that significantly worsens with stress and anxiety and can significantly impact quality of life despite optimal medical and behavioral treatment options. Deep brain stimulation (DBS) has been proposed as an effective therapy for vocal tremor, but very few studies exist in the literature that comprehensively evaluate the efficacy of DBS for specifically addressing EVT. We present a technical report on our multidisciplinary, comprehensive operative methodology for treatment of EVT with frameless, awake deep brain stimulation (DBS).

Deep Brain Stimulation for Essential Vocal Tremor: A Technical Report

PubMed Central

Choudhri, Omar; Sung, C. Kwang; DiRenzo, Elizabeth E; Halpern, Casey H

2015-01-01

Essential vocal tremor (EVT) is the presence of a tremulous voice that is commonly associated with essential tremor. Patients with EVT often report a necessary increase in vocal effort that significantly worsens with stress and anxiety and can significantly impact quality of life despite optimal medical and behavioral treatment options. Deep brain stimulation (DBS) has been proposed as an effective therapy for vocal tremor, but very few studies exist in the literature that comprehensively evaluate the efficacy of DBS for specifically addressing EVT. We present a technical report on our multidisciplinary, comprehensive operative methodology for treatment of EVT with frameless, awake deep brain stimulation (DBS). PMID:26180680

Perylene-diimide-based nanoparticles as highly efficient photoacoustic agents for deep brain tumor imaging in living mice

DOE PAGES

Fan, Quli; Cheng, Kai; Yang, Zhen; ...

2014-11-06

In order to promote preclinical and clinical applications of photoacoustic imaging, novel photoacoustic contrast agents are highly desired for molecular imaging of diseases, especially for deep tumor imaging. In this paper, perylene-3,4,9,10-tetracarboxylic diiimide-based near-infrared-absorptive organic nanoparticles are reported as an efficient agent for photoacoustic imaging of deep brain tumors in living mice with enhanced permeability and retention effect

Learning implicit brain MRI manifolds with deep learning

NASA Astrophysics Data System (ADS)

Bermudez, Camilo; Plassard, Andrew J.; Davis, Larry T.; Newton, Allen T.; Resnick, Susan M.; Landman, Bennett A.

2018-03-01

An important task in image processing and neuroimaging is to extract quantitative information from the acquired images in order to make observations about the presence of disease or markers of development in populations. Having a low-dimensional manifold of an image allows for easier statistical comparisons between groups and the synthesis of group representatives. Previous studies have sought to identify the best mapping of brain MRI to a low-dimensional manifold, but have been limited by assumptions of explicit similarity measures. In this work, we use deep learning techniques to investigate implicit manifolds of normal brains and generate new, high-quality images. We explore implicit manifolds by addressing the problems of image synthesis and image denoising as important tools in manifold learning. First, we propose the unsupervised synthesis of T1-weighted brain MRI using a Generative Adversarial Network (GAN) by learning from 528 examples of 2D axial slices of brain MRI. Synthesized images were first shown to be unique by performing a cross-correlation with the training set. Real and synthesized images were then assessed in a blinded manner by two imaging experts providing an image quality score of 1-5. The quality score of the synthetic image showed substantial overlap with that of the real images. Moreover, we use an autoencoder with skip connections for image denoising, showing that the proposed method results in higher PSNR than FSL SUSAN after denoising. This work shows the power of artificial networks to synthesize realistic imaging data, which can be used to improve image processing techniques and provide a quantitative framework to structural changes in the brain.

Magnetic resonance imaging DTI-FT study on schizophrenic patients with typical negative first symptoms.

PubMed

Gu, Chengyu; Zhang, Ying; Wei, Fuquan; Cheng, Yougen; Cao, Yulin; Hou, Hongtao

2016-09-01

Magnetic resonance imaging (MRI) with diffusion-tensor imaging (DTI) together with a white matter fiber tracking (FT) technique was used to assess different brain white matter structures and functionalities in schizophrenic patients with typical first negative symptoms. In total, 30 schizophrenic patients with typical first negative symptoms, comprising an observation group were paired 1:1 according to gender, age, right-handedness, and education, with 30 healthy individuals in a control group. Individuals in each group underwent routine MRI and DTI examination of the brain, and diffusion-tensor tractography (DTT) data were obtained through whole brain analysis based on voxel and tractography. The results were expressed by fractional anisotropy (FA) values. The schizophrenic patients were evaluated using a positive and negative symptom scale (PANSS) as well as a Global Assessment Scale (GAS). The results of the study showed that routine MRIs identified no differences between the two groups. However, compared with the control group, the FA values obtained by DTT from the deep left prefrontal cortex, the right deep temporal lobe, the white matter of the inferior frontal gyrus and part of the corpus callosum were significantly lower in the observation group (P<0.05). The PANSS positive scale value in the observation group averaged 7.7±1.5, and the negative scale averaged 46.6±5.9, while the general psychopathology scale averaged 65.4±10.3, and GAS averaged 53.8±19.2. The Pearson statistical analysis, the left deep prefrontal cortex, the right deep temporal lobe, the white matter of the inferior frontal gyrus and the FA value of part of the corpus callosum in the observation group was negatively correlated with the negative scale (P<0.05), and positively correlated with GAS (P<0.05). In conclusion, a decrease in the FA values of the left deep prefrontal cortex, the right deep temporal lobe, the white matter of the inferior frontal gyrus and part of the corpus callosum may be associated with schizophrenia with typical first negative symptoms and the application of MRI DTI-FT can improve diagnostic accuracy.

Complex Trajectories of Brain Development in the Healthy Human Fetus.

PubMed

Andescavage, Nickie N; du Plessis, Adre; McCarter, Robert; Serag, Ahmed; Evangelou, Iordanis; Vezina, Gilbert; Robertson, Richard; Limperopoulos, Catherine

2017-11-01

This study characterizes global and hemispheric brain growth in healthy human fetuses during the second half of pregnancy using three-dimensional MRI techniques. We studied 166 healthy fetuses that underwent MRI between 18 and 39 completed weeks gestation. We created three-dimensional high-resolution reconstructions of the brain and calculated volumes for left and right cortical gray matter (CGM), fetal white matter (FWM), deep subcortical structures (DSS), and the cerebellum. We calculated the rate of growth for each tissue class according to gestational age and described patterns of hemispheric growth. Each brain region demonstrated major increases in volume during the second half of gestation, the most pronounced being the cerebellum (34-fold), followed by FWM (22-fold), CGM (21-fold), and DSS (10-fold). The left cerebellar hemisphere, CGM, and DSS had larger volumes early in gestation, but these equalized by term. It has been increasingly recognized that brain asymmetry evolves throughout the human life span. Advanced quantitative MRI provides noninvasive measurements of early structural asymmetry between the left and right fetal brain that may inform functional and behavioral laterality differences seen in children and young adulthood. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Populations of subplate and interstitial neurons in fetal and adult human telencephalon.

PubMed

Judaš, Miloš; Sedmak, Goran; Pletikos, Mihovil; Jovanov-Milošević, Nataša

2010-10-01

In the adult human telencephalon, subcortical (gyral) white matter contains a special population of interstitial neurons considered to be surviving descendants of fetal subplate neurons [Kostovic & Rakic (1980) Cytology and the time of origin of interstitial neurons in the white matter in infant and adult human and monkey telencephalon. J Neurocytol9, 219]. We designate this population of cells as superficial (gyral) interstitial neurons and describe their morphology and distribution in the postnatal and adult human cerebrum. Human fetal subplate neurons cannot be regarded as interstitial, because the subplate zone is an essential part of the fetal cortex, the major site of synaptogenesis and the 'waiting' compartment for growing cortical afferents, and contains both projection neurons and interneurons with distinct input-output connectivity. However, although the subplate zone is a transient fetal structure, many subplate neurons survive postnatally as superficial (gyral) interstitial neurons. The fetal white matter is represented by the intermediate zone and well-defined deep periventricular tracts of growing axons, such as the corpus callosum, anterior commissure, internal and external capsule, and the fountainhead of the corona radiata. These tracts gradually occupy the territory of transient fetal subventricular and ventricular zones.The human fetal white matter also contains distinct populations of deep fetal interstitial neurons, which, by virtue of their location, morphology, molecular phenotypes and advanced level of dendritic maturation, remain distinct from subplate neurons and neurons in adjacent structures (e.g. basal ganglia, basal forebrain). We describe the morphological, histochemical (nicotinamide-adenine dinucleotide phosphate-diaphorase) and immunocytochemical (neuron-specific nuclear protein, microtubule-associated protein-2, calbindin, calretinin, neuropeptide Y) features of both deep fetal interstitial neurons and deep (periventricular) interstitial neurons in the postnatal and adult deep cerebral white matter (i.e. corpus callosum, anterior commissure, internal and external capsule and the corona radiata/centrum semiovale). Although these deep interstitial neurons are poorly developed or absent in the brains of rodents, they represent a prominent feature of the significantly enlarged white matter of human and non-human primate brains. © 2010 The Authors. Journal of Anatomy © 2010 Anatomical Society of Great Britain and Ireland.

A spherical aberration-free microscopy system for live brain imaging.

PubMed

Ue, Yoshihiro; Monai, Hiromu; Higuchi, Kaori; Nishiwaki, Daisuke; Tajima, Tetsuya; Okazaki, Kenya; Hama, Hiroshi; Hirase, Hajime; Miyawaki, Atsushi

2018-06-02

The high-resolution in vivo imaging of mouse brain for quantitative analysis of fine structures, such as dendritic spines, requires objectives with high numerical apertures (NAs) and long working distances (WDs). However, this imaging approach is often hampered by spherical aberration (SA) that results from the mismatch of refractive indices in the optical path and becomes more severe with increasing depth of target from the brain surface. Whereas a revolving objective correction collar has been designed to compensate SA, its adjustment requires manual operation and is inevitably accompanied by considerable focal shift, making it difficult to acquire the best image of a given fluorescent object. To solve the problems, we have created an objective-attached device and formulated a fast iterative algorithm for the realization of an automatic SA compensation system. The device coordinates the collar rotation and the Z-position of an objective, enabling correction collar adjustment while stably focusing on a target. The algorithm provides the best adjustment on the basis of the calculated contrast of acquired images. Together, they enable the system to compensate SA at a given depth. As proof of concept, we applied the SA compensation system to in vivo two-photon imaging with a 25 × water-immersion objective (NA, 1.05; WD, 2 mm). It effectively reduced SA regardless of location, allowing quantitative and reproducible analysis of fine structures of YFP-labeled neurons in the mouse cerebral cortical layers. Interestingly, although the cortical structure was optically heterogeneous along the z-axis, the refractive index of each layer could be assessed on the basis of the compensation degree. It was also possible to make fully corrected three-dimensional reconstructions of YFP-labeled neurons in live brain samples. Our SA compensation system, called Deep-C, is expected to bring out the best in all correction-collar-equipped objectives for imaging deep regions of heterogeneous tissues. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

A giant intradiploic epidermoid cyst with perforation of the dura and brain parenchymal involvement.

PubMed

Cho, Jong-Ho; Jung, Tae-Young; Kim, In-Young; Jung, Shin; Kang, Sam-Suk; Kim, Soo-Han

2007-05-01

A patient with a long-standing intradiploic epidermoid cyst with perforation of the dura and brain parenchymal involvement is reported. A 69-year-old man, who had previously presented with a subcutaneous mass on the left frontoparietal scalp, developed a sudden grand mal seizure. Magnetic resonance imaging showed a well-defined mass in the frontoparietal scalp with destruction of the skull. Penetration of the dura allowed for communication with the intracranial structures. Surgical resection and cranioplasty were performed. There were no well-defined margins in the deep portion and the mass was subtotally removed. Histological examination showed that the cystic structure was lined by squamous epithelium containing laminated keratin material. The pathologic findings were consistent with the diagnosis of an epidermoid cyst.

Laser scattering by transcranial rat brain illumination

NASA Astrophysics Data System (ADS)

Sousa, Marcelo V. P.; Prates, Renato; Kato, Ilka T.; Sabino, Caetano P.; Suzuki, Luis C.; Ribeiro, Martha S.; Yoshimura, Elisabeth M.

2012-06-01

Due to the great number of applications of Low-Level-Laser-Therapy (LLLT) in Central Nervous System (CNS), the study of light penetration through skull and distribution in the brain becomes extremely important. The aim is to analyze the possibility of precise illumination of deep regions of the rat brain, measure the penetration and distribution of red (λ = 660 nm) and Near Infra-Red (NIR) (λ = 808 nm) diode laser light and compare optical properties of brain structures. The head of the animal (Rattus Novergicus) was epilated and divided by a sagittal cut, 2.3 mm away from mid plane. This section of rat's head was illuminated with red and NIR lasers in points above three anatomical structures: hippocampus, cerebellum and frontal cortex. A high resolution camera, perpendicularly positioned, was used to obtain images of the brain structures. Profiles of scattered intensities in the laser direction were obtained from the images. There is a peak in the scattered light profile corresponding to the skin layer. The bone layer gives rise to a valley in the profile indicating low scattering coefficient, or frontal scattering. Another peak in the region related to the brain is an indication of high scattering coefficient (μs) for this tissue. This work corroborates the use of transcranial LLLT in studies with rats which are subjected to models of CNS diseases. The outcomes of this study point to the possibility of transcranial LLLT in humans for a large number of diseases.

Toward sophisticated basal ganglia neuromodulation: Review on basal ganglia deep brain stimulation.

PubMed

Da Cunha, Claudio; Boschen, Suelen L; Gómez-A, Alexander; Ross, Erika K; Gibson, William S J; Min, Hoon-Ki; Lee, Kendall H; Blaha, Charles D

2015-11-01

This review presents state-of-the-art knowledge about the roles of the basal ganglia (BG) in action-selection, cognition, and motivation, and how this knowledge has been used to improve deep brain stimulation (DBS) treatment of neurological and psychiatric disorders. Such pathological conditions include Parkinson's disease, Huntington's disease, Tourette syndrome, depression, and obsessive-compulsive disorder. The first section presents evidence supporting current hypotheses of how the cortico-BG circuitry works to select motor and emotional actions, and how defects in this circuitry can cause symptoms of the BG diseases. Emphasis is given to the role of striatal dopamine on motor performance, motivated behaviors and learning of procedural memories. Next, the use of cutting-edge electrochemical techniques in animal and human studies of BG functioning under normal and disease conditions is discussed. Finally, functional neuroimaging studies are reviewed; these works have shown the relationship between cortico-BG structures activated during DBS and improvement of disease symptoms. Copyright © 2015 Elsevier Ltd. All rights reserved.

Toward sophisiticated basal ganglia neuromodulation: review on basal gaglia deep brain stimulation

PubMed Central

Da Cunha, Claudio; Boschen, Suelen L.; Gómez-A, Alexander; Ross, Erika K.; Gibson, William S. J.; Min, Hoon-Ki; Lee, Kendall H.; Blaha, Charles D.

2015-01-01

This review presents state-of-the-art knowledge about the roles of the basal ganglia (BG) in action-selection, cognition, and motivation, and how this knowledge has been used to improve deep brain stimulation (DBS) treatment of neurological and psychiatric disorders. Such pathological conditions include Parkinson’s disease, Huntington’s disease, Tourette syndrome, depression, and obsessive-compulsive disorder. The first section presents evidence supporting current hypotheses of how the cortico-BG circuitry works to select motor and emotional actions, and how defects in this circuitry can cause symptoms of the BG diseases. Emphasis is given to the role of striatal dopamine on motor performance, motivated behaviors and learning of procedural memories. Next, the use of cutting-edge electrochemical techniques in animal and human studies of BG functioning under normal and disease conditions is discussed. Finally, functional neuroimaging studies are reviewed; these works have shown the relationship between cortico-BG structures activated during DBS and improvement of disease symptoms. PMID:25684727

Deep brain stimulation for trigeminal autonomic cephalalgias.

PubMed

Messina, Giuseppe; Broggi, Giovanni; Levi, Vincenzo; Franzini, Angelo

2018-04-19

Deep brain stimulation (DBS) of the posterior hypothalamic region (pHyr) has been shown to be efficacious for more than a half of patients suffering from trigeminal autonomic cephalalgias (TACs); nonetheless, controversies about the mechanisms of action and the actual site of stimulation have arisen in recent years. Areas covered: Firstly, a review of the most recent literature on the subject is presented, stressing the critical points that could, in the future, make a difference for optimal management of patients afflicted by these life-threating diseases. Hypothalamic functional anatomy, experimental data and pathophysiological hypotheses are reported. Expert commentary: About 32% of patients who underwent DBS for TACs are pain-free. The determination of the pHyr region seems to be crucial for the generation of pain attack in these pathologies, although other structures are involved in complex mechanisms and circuits that interact with each other. Neurophysiological data, combined with more advanced experimental models, are of primary importance regarding our understanding of what the real target is, and how to overcome the issue of refractory patients.

Subthalamic Nucleus Deep Brain Stimulation Changes Velopharyngeal Control in Parkinson's Disease

ERIC Educational Resources Information Center

Hammer, Michael J.; Barlow, Steven M.; Lyons, Kelly E.; Pahwa, Rajesh

2011-01-01

Purpose: Adequate velopharyngeal control is essential for speech, but may be impaired in Parkinson's disease (PD). Bilateral subthalamic nucleus deep brain stimulation (STN DBS) improves limb function in PD, but the effects on velopharyngeal control remain unknown. We tested whether STN DBS would change aerodynamic measures of velopharyngeal…

Cognitive Functioning in Children with Pantothenate-Kinase-Associated Neurodegeneration Undergoing Deep Brain Stimulation

ERIC Educational Resources Information Center

Mahoney, Rachel; Selway, Richard; Lin, Jean-Pierre

2011-01-01

Aim: To examine the cognitive functioning of young people with pantothenate-kinase-associated neurodegeneration (PKAN) after pallidal deep brain stimulation (DBS). PKAN is characterized by progressive generalized dystonia and has historically been associated with cognitive decline. With growing evidence that DBS can improve motor function in…

The Effect of Deep Brain Stimulation on the Speech Motor System

ERIC Educational Resources Information Center

Mücke, Doris; Becker, Johannes; Barbe, Michael T.; Meister, Ingo; Liebhart, Lena; Roettger, Timo B.; Dembek, Till; Timmermann, Lars; Grice, Martine

2014-01-01

Purpose: Chronic deep brain stimulation of the nucleus ventralis intermedius is an effective treatment for individuals with medication-resistant essential tremor. However, these individuals report that stimulation has a deleterious effect on their speech. The present study investigates one important factor leading to these effects: the…

Affect of deep brain stimulation on limb paresis after stroke.

PubMed

Phillips, N I; Bhakta, B B

2000-07-15

A deep brain stimulator was implanted in the periventricular grey matter of the third ventricle for pain after stroke in a man aged 48 years. As well as a beneficial analgesic effect, the patient reported improved function in the contralateral paretic arm, which was confirmed on formal testing.

Concussion classification via deep learning using whole-brain white matter fiber strains

PubMed Central

Cai, Yunliang; Wu, Shaoju; Zhao, Wei; Li, Zhigang; Wu, Zheyang

2018-01-01

Developing an accurate and reliable injury predictor is central to the biomechanical studies of traumatic brain injury. State-of-the-art efforts continue to rely on empirical, scalar metrics based on kinematics or model-estimated tissue responses explicitly pre-defined in a specific brain region of interest. They could suffer from loss of information. A single training dataset has also been used to evaluate performance but without cross-validation. In this study, we developed a deep learning approach for concussion classification using implicit features of the entire voxel-wise white matter fiber strains. Using reconstructed American National Football League (NFL) injury cases, leave-one-out cross-validation was employed to objectively compare injury prediction performances against two baseline machine learning classifiers (support vector machine (SVM) and random forest (RF)) and four scalar metrics via univariate logistic regression (Brain Injury Criterion (BrIC), cumulative strain damage measure of the whole brain (CSDM-WB) and the corpus callosum (CSDM-CC), and peak fiber strain in the CC). Feature-based machine learning classifiers including deep learning, SVM, and RF consistently outperformed all scalar injury metrics across all performance categories (e.g., leave-one-out accuracy of 0.828–0.862 vs. 0.690–0.776, and .632+ error of 0.148–0.176 vs. 0.207–0.292). Further, deep learning achieved the best cross-validation accuracy, sensitivity, AUC, and .632+ error. These findings demonstrate the superior performances of deep learning in concussion prediction and suggest its promise for future applications in biomechanical investigations of traumatic brain injury. PMID:29795640

Concussion classification via deep learning using whole-brain white matter fiber strains.

PubMed

Cai, Yunliang; Wu, Shaoju; Zhao, Wei; Li, Zhigang; Wu, Zheyang; Ji, Songbai

2018-01-01

Developing an accurate and reliable injury predictor is central to the biomechanical studies of traumatic brain injury. State-of-the-art efforts continue to rely on empirical, scalar metrics based on kinematics or model-estimated tissue responses explicitly pre-defined in a specific brain region of interest. They could suffer from loss of information. A single training dataset has also been used to evaluate performance but without cross-validation. In this study, we developed a deep learning approach for concussion classification using implicit features of the entire voxel-wise white matter fiber strains. Using reconstructed American National Football League (NFL) injury cases, leave-one-out cross-validation was employed to objectively compare injury prediction performances against two baseline machine learning classifiers (support vector machine (SVM) and random forest (RF)) and four scalar metrics via univariate logistic regression (Brain Injury Criterion (BrIC), cumulative strain damage measure of the whole brain (CSDM-WB) and the corpus callosum (CSDM-CC), and peak fiber strain in the CC). Feature-based machine learning classifiers including deep learning, SVM, and RF consistently outperformed all scalar injury metrics across all performance categories (e.g., leave-one-out accuracy of 0.828-0.862 vs. 0.690-0.776, and .632+ error of 0.148-0.176 vs. 0.207-0.292). Further, deep learning achieved the best cross-validation accuracy, sensitivity, AUC, and .632+ error. These findings demonstrate the superior performances of deep learning in concussion prediction and suggest its promise for future applications in biomechanical investigations of traumatic brain injury.

Novel Intrinsic Ignition Method Measuring Local-Global Integration Characterizes Wakefulness and Deep Sleep

PubMed Central

Tagliazucchi, Enzo; Sanjuán, Ana

2017-01-01

Abstract A precise definition of a brain state has proven elusive. Here, we introduce the novel local-global concept of intrinsic ignition characterizing the dynamical complexity of different brain states. Naturally occurring intrinsic ignition events reflect the capability of a given brain area to propagate neuronal activity to other regions, giving rise to different levels of integration. The ignitory capability of brain regions is computed by the elicited level of integration for each intrinsic ignition event in each brain region, averaged over all events. This intrinsic ignition method is shown to clearly distinguish human neuroimaging data of two fundamental brain states (wakefulness and deep sleep). Importantly, whole-brain computational modelling of this data shows that at the optimal working point is found where there is maximal variability of the intrinsic ignition across brain regions. Thus, combining whole brain models with intrinsic ignition can provide novel insights into underlying mechanisms of brain states. PMID:28966977

Novel Intrinsic Ignition Method Measuring Local-Global Integration Characterizes Wakefulness and Deep Sleep.

PubMed

Deco, Gustavo; Tagliazucchi, Enzo; Laufs, Helmut; Sanjuán, Ana; Kringelbach, Morten L

2017-01-01

A precise definition of a brain state has proven elusive. Here, we introduce the novel local-global concept of intrinsic ignition characterizing the dynamical complexity of different brain states. Naturally occurring intrinsic ignition events reflect the capability of a given brain area to propagate neuronal activity to other regions, giving rise to different levels of integration. The ignitory capability of brain regions is computed by the elicited level of integration for each intrinsic ignition event in each brain region, averaged over all events. This intrinsic ignition method is shown to clearly distinguish human neuroimaging data of two fundamental brain states (wakefulness and deep sleep). Importantly, whole-brain computational modelling of this data shows that at the optimal working point is found where there is maximal variability of the intrinsic ignition across brain regions. Thus, combining whole brain models with intrinsic ignition can provide novel insights into underlying mechanisms of brain states.

Ethics of the electrified mind: Defining issues and perspectives on the principled use of brain stimulation in medical research and clinical care

PubMed Central

Cabrera, Laura Y.; Evans, Emily L.; Hamilton, Roy H.

2013-01-01

In recent years, non-pharmacologic approaches to modifying human neural activity have gained increasing attention. One of these approaches is brain stimulation, which involves either the direct application of electrical current to structures in the nervous system or the indirect application of current by means of electromagnetic induction. Interventions that manipulate the brain have generally been regarded as having both the potential to alleviate devastating brain-related conditions and the capacity to create unforeseen and unwanted consequences. Hence, although brain stimulation techniques offer considerable benefits to society, they also raise a number of ethical concerns. In this paper we will address various dilemmas related to brain stimulation in the context of clinical practice and biomedical research. We will survey current work involving deep brain stimulation (DBS), transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS). We will reflect upon relevant similarities and differences between them, and consider some potentially problematic issues that may arise within the framework of established principles of medical ethics: nonmaleficence and beneficence, autonomy, and justice. PMID:23733209

Sparsity enables estimation of both subcortical and cortical activity from MEG and EEG

PubMed Central

Krishnaswamy, Pavitra; Obregon-Henao, Gabriel; Ahveninen, Jyrki; Khan, Sheraz; Iglesias, Juan Eugenio; Hämäläinen, Matti S.; Purdon, Patrick L.

2017-01-01

Subcortical structures play a critical role in brain function. However, options for assessing electrophysiological activity in these structures are limited. Electromagnetic fields generated by neuronal activity in subcortical structures can be recorded noninvasively, using magnetoencephalography (MEG) and electroencephalography (EEG). However, these subcortical signals are much weaker than those generated by cortical activity. In addition, we show here that it is difficult to resolve subcortical sources because distributed cortical activity can explain the MEG and EEG patterns generated by deep sources. We then demonstrate that if the cortical activity is spatially sparse, both cortical and subcortical sources can be resolved with M/EEG. Building on this insight, we develop a hierarchical sparse inverse solution for M/EEG. We assess the performance of this algorithm on realistic simulations and auditory evoked response data, and show that thalamic and brainstem sources can be correctly estimated in the presence of cortical activity. Our work provides alternative perspectives and tools for characterizing electrophysiological activity in subcortical structures in the human brain. PMID:29138310

Reversible Holmes' tremor due to spontaneous intracranial hypotension.

PubMed

Iyer, Rajesh Shankar; Wattamwar, Pandurang; Thomas, Bejoy

2017-07-27

Holmes' tremor is a low-frequency hand tremor and has varying amplitude at different phases of motion. It is usually unilateral and does not respond satisfactorily to drugs and thus considered irreversible. Structural lesions in the thalamus and brainstem or cerebellum are usually responsible for Holmes' tremor. We present a 23-year-old woman who presented with unilateral Holmes' tremor. She also had hypersomnolence and headache in the sitting posture. Her brain imaging showed brain sagging and deep brain swelling due to spontaneous intracranial hypotension (SIH). She was managed conservatively and had a total clinical and radiological recovery. The brain sagging with the consequent distortion of the midbrain and diencephalon was responsible for this clinical presentation. SIH may be considered as one of the reversible causes of Holmes' tremor. © BMJ Publishing Group Ltd (unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Structural and functional connectivity of the subthalamic nucleus during vocal emotion decoding

PubMed Central

Frühholz, Sascha; Ceravolo, Leonardo; Grandjean, Didier

2016-01-01

Our understanding of the role played by the subthalamic nucleus (STN) in human emotion has recently advanced with STN deep brain stimulation, a neurosurgical treatment for Parkinson’s disease and obsessive-compulsive disorder. However, the potential presence of several confounds related to pathological models raises the question of how much they affect the relevance of observations regarding the physiological function of the STN itself. This underscores the crucial importance of obtaining evidence from healthy participants. In this study, we tested the structural and functional connectivity between the STN and other brain regions related to vocal emotion in a healthy population by combining diffusion tensor imaging and psychophysiological interaction analysis from a high-resolution functional magnetic resonance imaging study. As expected, we showed that the STN is functionally connected to the structures involved in emotional prosody decoding, notably the orbitofrontal cortex, inferior frontal gyrus, auditory cortex, pallidum and amygdala. These functional results were corroborated by probabilistic fiber tracking, which revealed that the left STN is structurally connected to the amygdala and the orbitofrontal cortex. These results confirm, in healthy participants, the role played by the STN in human emotion and its structural and functional connectivity with the brain network involved in vocal emotions. PMID:26400857

Deep brain stimulation as a functional scalpel.

PubMed

Broggi, G; Franzini, A; Tringali, G; Ferroli, P; Marras, C; Romito, L; Maccagnano, E

2006-01-01

Since 1995, at the Istituto Nazionale Neurologico "Carlo Besta" in Milan (INNCB,) 401 deep brain electrodes were implanted to treat several drug-resistant neurological syndromes (Fig. 1). More than 200 patients are still available for follow-up and therapeutical considerations. In this paper our experience is reviewed and pioneered fields are highlighted. The reported series of patients extends the use of deep brain stimulation beyond the field of Parkinson's disease to new fields such as cluster headache, disruptive behaviour, SUNCt, epilepsy and tardive dystonia. The low complication rate, the reversibility of the procedure and the available image guided surgery tools will further increase the therapeutic applications of DBS. New therapeutical applications are expected for this functional scalpel.

Deep brain stimulation of the internal pallidum in multiple system atrophy.

PubMed

Santens, Patrick; Patrick, Santens; Vonck, Kristl; Kristl, Vonck; De Letter, Miet; Miet, De Letter; Van Driessche, Katya; Katya, Van Driessche; Sieben, Anne; Anne, Sieben; De Reuck, Jacques; Jacques, De Reuck; Van Roost, Dirk; Dirk, Van Roost; Boon, Paul; Paul, Boon

2006-04-01

We describe the outcome of deep brain stimulation of the internal pallidum in a 57-year old patient with multiple system atrophy. Although the prominent dystonic features of this patient were markedly attenuated post-operatively, the outcome was to be considered unfavourable. There was a severe increase in akinesia resulting in overall decrease of mobility in limbs as well as in the face. As a result, the patient was anarthric and displayed dysphagia. A laterality effect of stimulation on oro-facial movements was demonstrated. The patient died 7 months post-operatively. This report adds to the growing consensus that multiple system atrophy patients are unsuitable candidates for deep brain stimulation.

Chinese expert consensus on programming deep brain stimulation for patients with Parkinson's disease.

PubMed

Chen, Shengdi; Gao, Guodong; Feng, Tao; Zhang, Jianguo

2018-01-01

Deep Brain Stimulation (DBS) therapy for the treatment of Parkinson's Disease (PD) is now a well-established option for some patients. Postoperative standardized programming processes can improve the level of postoperative management and programming, relieve symptoms and improve quality of life. In order to improve the quality of the programming, the experts on DBS and PD in neurology and neurosurgery in China reviewed the relevant literatures and combined their own experiences and developed this expert consensus on the programming of deep brain stimulation in patients with PD in China. This Chinese expert consensus on postoperative programming can standardize and improve postoperative management and programming of DBS for PD.

Focal epidural cooling reduces the infarction volume of permanent middle cerebral artery occlusion in swine.

PubMed

Zhang, Lihua; Cheng, Huilin; Shi, Jixin; Chen, Jun

2007-02-01

The protective effect against ischemic stroke by systemic hypothermia is limited by the cooling rate and it has severe complications. This study was designed to evaluate the effect of SBH induced by epidural cooling on infarction volume in a swine model of PMCAO. Permanent middle cerebral artery occlusion was performed in 12 domestic swine assigned to groups A and B. In group A, the cranial and rectal temperatures were maintained at normal range (37 degrees C-39 degrees C) for 6 hours after PMCAO. In group B, cranial temperature was reduced to moderate (deep brain, <30 degrees C) and deep (brain surface, <20 degrees C) temperature and maintained at that level for 5 hours after 1 hour after PMCAO, by the epidural cooling method. All animals were euthanized 6 hours after MCAO; their brains were sectioned and stained with 2,3,5-triphenyltetrazolium chloride and their infarct volumes were calculated. The moderate and deep brain temperature (at deep brain and brain surface) can be induced by rapid epidural cooling, whereas the rectal temperature was maintained within normal range. The infarction volume after PMCAO was significantly reduced by epidural cooling compared with controls (13.73% +/- 1.82% vs 5.62% +/- 2.57%, P < .05). The present study has demonstrated, with histologic confirmation, that epidural cooling may be a useful strategy for reducing infarct volume after the onset of ischemia.

Closed loop deep brain stimulation: an evolving technology.

PubMed

Hosain, Md Kamal; Kouzani, Abbas; Tye, Susannah

2014-12-01

Deep brain stimulation is an effective and safe medical treatment for a variety of neurological and psychiatric disorders including Parkinson's disease, essential tremor, dystonia, and treatment resistant obsessive compulsive disorder. A closed loop deep brain stimulation (CLDBS) system automatically adjusts stimulation parameters by the brain response in real time. The CLDBS continues to evolve due to the advancement in the brain stimulation technologies. This paper provides a study on the existing systems developed for CLDBS. It highlights the issues associated with CLDBS systems including feedback signal recording and processing, stimulation parameters setting, control algorithm, wireless telemetry, size, and power consumption. The benefits and limitations of the existing CLDBS systems are also presented. Whilst robust clinical proof of the benefits of the technology remains to be achieved, it has the potential to offer several advantages over open loop DBS. The CLDBS can improve efficiency and efficacy of therapy, eliminate lengthy start-up period for programming and adjustment, provide a personalized treatment, and make parameters setting automatic and adaptive.

Improvement of both dystonia and tics with 60 Hz pallidal deep brain stimulation.

PubMed

Hwynn, Nelson; Tagliati, Michele; Alterman, Ron L; Limotai, Natlada; Zeilman, Pamela; Malaty, Irene A; Foote, Kelly D; Morishita, Takashi; Okun, Michael S

2012-09-01

Deep brain stimulation has been utilized in both dystonia and in medication refractory Tourette syndrome. We present an interesting case of a patient with a mixture of disabling dystonia and Tourette syndrome whose coexistent dystonia and tics were successfully treated with 60 Hz-stimulation of the globus pallidus region.

Two-step tunneling technique of deep brain stimulation extension wires-a description.

PubMed

Fontaine, Denys; Vandersteen, Clair; Saleh, Christian; von Langsdorff, Daniel; Poissonnet, Gilles

2013-12-01

While a significant body of literature exists on the intracranial part of deep brain stimulation surgery, the equally important second part of the intervention related to the subcutaneous tunneling of deep brain stimulation extension wires is rarely described. The tunneling strategy can consist of a single passage of the extension wires from the frontal incision site to the subclavicular area, or of a two-step approach that adds a retro-auricular counter-incision. Each technique harbors the risk of intraoperative and postoperative complications. At our center, we perform a two-step tunneling procedure that we developed based on a cadaveric study. In 125 consecutive patients operated since 2002, we did not encounter any complication related to our tunneling method. Insufficient data exist to fully evaluate the advantages and disadvantages of each tunneling technique. It is of critical importance that authors detail their tunneling modus operandi and report the presence or absence of complications. This gathered data pool may help to formulate a definitive conclusions on the safest method for subcutaneous tunneling of extension wires in deep brain stimulation.

From Nose to Brain: Un-Sensed Electrical Currents Applied in the Nose Alter Activity in Deep Brain Structures

PubMed Central

Weiss, Tali; Shushan, Sagit; Ravia, Aharon; Hahamy, Avital; Secundo, Lavi; Weissbrod, Aharon; Ben-Yakov, Aya; Holtzman, Yael; Cohen-Atsmoni, Smadar; Roth, Yehudah; Sobel, Noam

2016-01-01

Rules linking patterns of olfactory receptor neuron activation in the nose to activity patterns in the brain and ensuing odor perception remain poorly understood. Artificially stimulating olfactory neurons with electrical currents and measuring ensuing perception may uncover these rules. We therefore inserted an electrode into the nose of 50 human volunteers and applied various currents for about an hour in each case. This induced assorted non-olfactory sensations but never once the perception of odor. To validate contact with the olfactory path, we used functional magnetic resonance imaging to measure resting-state brain activity in 18 subjects before and after un-sensed stimulation. We observed stimulation-induced neural decorrelation specifically in primary olfactory cortex, implying contact with the olfactory path. These results suggest that indiscriminate olfactory activation does not equate with odor perception. Moreover, this effort serendipitously uncovered a novel path for minimally invasive brain stimulation through the nose. PMID:27591145

The mediodorsal thalamic nucleus and schizophrenia

PubMed Central

Alelú-Paz, Raúl; Giménez-Amaya, José Manuel

2008-01-01

The mediodorsal nucleus of the human thalamus is in a crucial position that allows it to establish connections with diverse cerebral structures, particularly the prefrontal cortex. The present review examines existing neurobiologic studies of the brains of people with and without schizophrenia that indicate a possible involvement of the mediodorsal nucleus in this psychiatric disorder. Studies at synaptic and cellular levels of the neurobiology of the mediodorsal nucleus, together with a better anatomic understanding of this diencephalic structure owing to neuroimaging studies, should help to establish a more deep and solid pathophysiologic model of schizophrenia. PMID:18982171

Fos expression in the rat brain and spinal cord evoked by noxious stimulation to low back muscle and skin.

PubMed

Ohtori, S; Takahashi, K; Chiba, T; Takahashi, Y; Yamagata, M; Sameda, H; Moriya, H

2000-10-01

Acute noxious stimulation delivered to lumbar muscles and skin of rats was used to study Fos expression patterns in the brain and spinal cord. The present study was conducted to determine the differences in Fos expression in the brain and spinal cord as evoked by stimuli delivered to lumbar muscles and skin in rats. Patients with low back pain sometimes show psychological symptoms, such as quiescence, loss of interest, decreased activities, appetite loss, and restlessness. The pathway of deep somatic pain to the brain has been reported to be different from that of cutaneous pain. However, Fos expression has not been studied in the central nervous systems after stimulation of low back muscles. Rats were injected with 100 L of 5% formalin into the multifidus muscle (deep pain group; n = 10) and into the back skin of the L5 dermatome (cutaneous pain group; n = 10). Two hours after injection, the distribution of Fos-immunoreactive neurons was studied in the brain and spinal cord. Fos-immunoreactive neurons were observed in laminae I-V in the spinal cord in the cutaneous pain group, but they were not seen in lamina II in the deep pain group. In the brain, Fos-immunoreactive neurons were significantly more numerous in the deep pain group than in the cutaneous pain group in the piriform cortex, the accumbens nucleus core, the basolateral nucleus of amygdala, the paraventricular hypothalamic nucleus, the ventral tegmental area, and the ventrolateral periaqueductal gray. The finding that Fos-immunoreactive neurons were absent from lamina II of the spinal cord in the deep pain group is similar to that of the projection pattern of the visceral pain pathway. Fos expression in the ventrolateral periaqueductal gray in the deep pain group may represent a reaction of quiescence and a loss of interest, activities, or appetite. Furthermore, the detection of large numbers of Fos-immunoreactive neurons in the core of accumbens nucleus, basolateral nucleus of amygdala, paraventricular hypothalamic nucleus, and ventral tegmental area in the deep pain group may suggest a dominant reaction of dopaminergic neurons to stress, and a different information processing pathway than from that of cutaneous pain.

The clinical outcomes of deep gray matter injury in children with cerebral palsy in relation with brain magnetic resonance imaging.

PubMed

Choi, Ja Young; Choi, Yoon Seong; Rha, Dong-Wook; Park, Eun Sook

2016-08-01

In the present study we investigated the nature and extent of clinical outcomes using various classifications and analyzed the relationship between brain magnetic resonance imaging (MRI) findings and the extent of clinical outcomes in children with cerebral palsy (CP) with deep gray matter injury. The deep gray matter injuries of 69 children were classified into hypoxic ischemic encephalopathy (HIE) and kernicterus patterns. HIE patterns were divided into four groups (I-IV) based on severity. Functional classification was investigated using the gross motor function classification system-expanded and revised, manual ability classification system, communication function classification system, and tests of cognitive function, and other associated problems. The severity of HIE pattern on brain MRI was strongly correlated with the severity of clinical outcomes in these various domains. Children with a kernicterus pattern showed a wide range of clinical outcomes in these areas. Children with severe HIE are at high risk of intellectual disability (ID) or epilepsy and children with a kernicterus pattern are at risk of hearing impairment and/or ID. Grading severity of HIE pattern on brain MRI is useful for predicting overall outcomes. The clinical outcomes of children with a kernicterus pattern range widely from mild to severe. Delineation of the clinical outcomes of children with deep gray matter injury, which are a common abnormal brain MRI finding in children with CP, is necessary. The present study provides clinical outcomes for various domains in children with deep gray matter injury on brain MRI. The deep gray matter injuries were divided into two major groups; HIE and kernicterus patterns. Our study showed that severity of HIE pattern on brain MRI was strongly associated with the severity of impairments in gross motor function, manual ability, communication function, and cognition. These findings suggest that severity of HIE pattern can be useful for predicting the severity of impairments. Conversely, children with a kernicterus pattern showed a wide range of clinical outcomes in various domains. Children with severe HIE pattern are at high risk of ID or epilepsy and children with kernicterus pattern are at risk of hearing impairment or ID. The strength of our study was the assessment of clinical outcomes after 3 years of age using standardized classification systems in various domains in children with deep gray matter injury. Copyright © 2016 Elsevier Ltd. All rights reserved.

Characterizing Deep Brain Stimulation effects in computationally efficient neural network models.

PubMed

Latteri, Alberta; Arena, Paolo; Mazzone, Paolo

2011-04-15

Recent studies on the medical treatment of Parkinson's disease (PD) led to the introduction of the so called Deep Brain Stimulation (DBS) technique. This particular therapy allows to contrast actively the pathological activity of various Deep Brain structures, responsible for the well known PD symptoms. This technique, frequently joined to dopaminergic drugs administration, replaces the surgical interventions implemented to contrast the activity of specific brain nuclei, called Basal Ganglia (BG). This clinical protocol gave the possibility to analyse and inspect signals measured from the electrodes implanted into the deep brain regions. The analysis of these signals led to the possibility to study the PD as a specific case of dynamical synchronization in biological neural networks, with the advantage to apply the theoretical analysis developed in such scientific field to find efficient treatments to face with this important disease. Experimental results in fact show that the PD neurological diseases are characterized by a pathological signal synchronization in BG. Parkinsonian tremor, for example, is ascribed to be caused by neuron populations of the Thalamic and Striatal structures that undergo an abnormal synchronization. On the contrary, in normal conditions, the activity of the same neuron populations do not appear to be correlated and synchronized. To study in details the effect of the stimulation signal on a pathological neural medium, efficient models of these neural structures were built, which are able to show, without any external input, the intrinsic properties of a pathological neural tissue, mimicking the BG synchronized dynamics.We start considering a model already introduced in the literature to investigate the effects of electrical stimulation on pathologically synchronized clusters of neurons. This model used Morris Lecar type neurons. This neuron model, although having a high level of biological plausibility, requires a large computational effort to simulate large scale networks. For this reason we considered a reduced order model, the Izhikevich one, which is computationally much lighter. The comparison between neural lattices built using both neuron models provided comparable results, both without traditional stimulation and in presence of all the stimulation protocols. This was a first result toward the study and simulation of the large scale neural networks involved in pathological dynamics.Using the reduced order model an inspection on the activity of two neural lattices was also carried out at the aim to analyze how the stimulation in one area could affect the dynamics in another area, like the usual medical treatment protocols require.The study of population dynamics that was carried out allowed us to investigate, through simulations, the positive effects of the stimulation signals in terms of desynchronization of the neural dynamics. The results obtained constitute a significant added value to the analysis of synchronization and desynchronization effects due to neural stimulation. This work gives the opportunity to more efficiently study the effect of stimulation in large scale yet computationally efficient neural networks. Results were compared both with the other mathematical models, using Morris Lecar and Izhikevich neurons, and with simulated Local Field Potentials (LFP).

Neuronal inhibition and synaptic plasticity of basal ganglia neurons in Parkinson's disease

PubMed Central

Milosevic, Luka; Kalia, Suneil K; Hodaie, Mojgan; Lozano, Andres M; Fasano, Alfonso; Popovic, Milos R; Hutchison, William D

2018-01-01

Abstract Deep brain stimulation of the subthalamic nucleus is an effective treatment for Parkinson’s disease symptoms. The therapeutic benefits of deep brain stimulation are frequency-dependent, but the underlying physiological mechanisms remain unclear. To advance deep brain stimulation therapy an understanding of fundamental mechanisms is critical. The objectives of this study were to (i) compare the frequency-dependent effects on cell firing in subthalamic nucleus and substantia nigra pars reticulata; (ii) quantify frequency-dependent effects on short-term plasticity in substantia nigra pars reticulata; and (iii) investigate effects of continuous long-train high frequency stimulation (comparable to conventional deep brain stimulation) on synaptic plasticity. Two closely spaced (600 µm) microelectrodes were advanced into the subthalamic nucleus (n = 27) and substantia nigra pars reticulata (n = 14) of 22 patients undergoing deep brain stimulation surgery for Parkinson’s disease. Cell firing and evoked field potentials were recorded with one microelectrode during stimulation trains from the adjacent microelectrode across a range of frequencies (1–100 Hz, 100 µA, 0.3 ms, 50–60 pulses). Subthalamic firing attenuated with ≥20 Hz (P < 0.01) stimulation (silenced at 100 Hz), while substantia nigra pars reticulata decreased with ≥3 Hz (P < 0.05) (silenced at 50 Hz). Substantia nigra pars reticulata also exhibited a more prominent increase in transient silent period following stimulation. Patients with longer silent periods after 100 Hz stimulation in the subthalamic nucleus tended to have better clinical outcome after deep brain stimulation. At ≥30 Hz the first evoked field potential of the stimulation train in substantia nigra pars reticulata was potentiated (P < 0.05); however, the average amplitude of the subsequent potentials was rapidly attenuated (P < 0.01). This is suggestive of synaptic facilitation followed by rapid depression. Paired pulse ratios calculated at the beginning of the train revealed that 20 Hz (P < 0.05) was the minimum frequency required to induce synaptic depression. Lastly, the average amplitude of evoked field potentials during 1 Hz pulses showed significant inhibitory synaptic potentiation after long-train high frequency stimulation (P < 0.001) and these increases were coupled with increased durations of neuronal inhibition (P < 0.01). The subthalamic nucleus exhibited a higher frequency threshold for stimulation-induced inhibition than the substantia nigra pars reticulata likely due to differing ratios of GABA:glutamate terminals on the soma and/or the nature of their GABAergic inputs (pallidal versus striatal). We suggest that enhancement of inhibitory synaptic plasticity, and frequency-dependent potentiation and depression are putative mechanisms of deep brain stimulation. Furthermore, we foresee that future closed-loop deep brain stimulation systems (with more frequent off stimulation periods) may benefit from inhibitory synaptic potentiation that occurs after high frequency stimulation. PMID:29236966

Functional and clinical neuroanatomy of morality.

PubMed

Fumagalli, Manuela; Priori, Alberto

2012-07-01

Morality is among the most sophisticated features of human judgement, behaviour and, ultimately, mind. An individual who behaves immorally may violate ethical rules and civil rights, and may threaten others' individual liberty, sometimes becoming violent and aggressive. In recent years, neuroscience has shown a growing interest in human morality, and has advanced our understanding of the cognitive and emotional processes involved in moral decisions, their anatomical substrates and the neurology of abnormal moral behaviour. In this article, we review research findings that have provided a key insight into the functional and clinical neuroanatomy of the brain areas involved in normal and abnormal moral behaviour. The 'moral brain' consists of a large functional network including both cortical and subcortical anatomical structures. Because morality is a complex process, some of these brain structures share their neural circuits with those controlling other behavioural processes, such as emotions and theory of mind. Among the anatomical structures implicated in morality are the frontal, temporal and cingulate cortices. The prefrontal cortex regulates activity in subcortical emotional centres, planning and supervising moral decisions, and when its functionality is altered may lead to impulsive aggression. The temporal lobe is involved in theory of mind and its dysfunction is often implicated in violent psychopathy. The cingulate cortex mediates the conflict between the emotional and the rational components of moral reasoning. Other important structures contributing to moral behaviour include the subcortical nuclei such as the amygdala, hippocampus and basal ganglia. Brain areas participating in moral processing can be influenced also by genetic, endocrine and environmental factors. Hormones can modulate moral behaviour through their effects on the brain. Finally, genetic polymorphisms can predispose to aggressivity and violence, arguing for a genetic-based predisposition to morality. Because abnormal moral behaviour can arise from both functional and structural brain abnormalities that should be diagnosed and treated, the neurology of moral behaviour has potential implications for clinical practice and raises ethical concerns. Last, since research has developed several neuromodulation techniques to improve brain dysfunction (deep brain stimulation, transcranial magnetic stimulation and transcranial direct current stimulation), knowing more about the 'moral brain' might help to develop novel therapeutic strategies for neurologically based abnormal moral behaviour.

Association of Deep Gray Matter Damage With Cortical and Spinal Cord Degeneration in Primary Progressive Multiple Sclerosis.

PubMed

Ruggieri, Serena; Petracca, Maria; Miller, Aaron; Krieger, Stephen; Ghassemi, Rezwan; Bencosme, Yadira; Riley, Claire; Howard, Jonathan; Lublin, Fred; Inglese, Matilde

2015-12-01

The investigation of cortical gray matter (GM), deep GM nuclei, and spinal cord damage in patients with primary progressive multiple sclerosis (PP-MS) provides insights into the neurodegenerative process responsible for clinical progression of MS. To investigate the association of magnetic resonance imaging measures of cortical, deep GM, and spinal cord damage and their effect on clinical disability. Cross-sectional analysis of 26 patients with PP-MS (mean age, 50.9 years; range, 31-65 years; including 14 women) and 20 healthy control participants (mean age, 51.1 years; range, 34-63 years; including 11 women) enrolled at a single US institution. Clinical disability was measured with the Expanded Disability Status Scale, 9-Hole Peg Test, and 25-Foot Walking Test. We collected data from January 1, 2012, through December 31, 2013. Data analysis was performed from January 21 to April 10, 2015. Cortical lesion burden, brain and deep GM volumes, spinal cord area and volume, and scores on the Expanded Disability Status Scale (score range, 0 to 10; higher scores indicate greater disability), 9-Hole Peg Test (measured in seconds; longer performance time indicates greater disability), and 25-Foot Walking Test (test covers 7.5 m; measured in seconds; longer performance time indicates greater disability). The 26 patients with PP-MS showed significantly smaller mean (SD) brain and spinal cord volumes than the 20 control group patients (normalized brain volume, 1377.81 [65.48] vs 1434.06 [53.67] cm3 [P = .003]; normalized white matter volume, 650.61 [46.38] vs 676.75 [37.02] cm3 [P = .045]; normalized gray matter volume, 727.20 [40.74] vs 757.31 [38.95] cm3 [P = .02]; normalized neocortical volume, 567.88 [85.55] vs 645.00 [42.84] cm3 [P = .001]; normalized spinal cord volume for C2-C5, 72.71 [7.89] vs 82.70 [7.83] mm3 [P < .001]; and normalized spinal cord volume for C2-C3, 64.86 [7.78] vs 72.26 [7.79] mm3 [P =.002]). The amount of damage in deep GM structures, especially with respect to the thalamus, was correlated with the number and volume of cortical lesions (mean [SD] thalamus volume, 8.89 [1.10] cm3; cortical lesion number, 12.6 [11.7]; cortical lesion volume, 0.65 [0.58] cm3; r = -0.52; P < .01). Thalamic atrophy also showed an association with cortical lesion count in the frontal cortex (mean [SD] thalamus volume, 8.89 [1.1] cm3; cortical lesion count in the frontal lobe, 5.0 [5.7]; r = -0.60; P < .01). No association was identified between magnetic resonance imaging measures of the brain and spinal cord damage. In this study, the neurodegenerative process occurring in PP-MS appeared to spread across connected structures in the brain while proceeding independently in the spinal cord. These results support the relevance of anatomical connectivity for the propagation of MS damage in the PP phenotype.

Sonographic alteration of lenticular nucleus in focal task-specific dystonia of musicians.

PubMed

Walter, Uwe; Buttkus, Franziska; Benecke, Reiner; Grossmann, Annette; Dressler, Dirk; Altenmüller, Eckart

2012-01-01

In distinct movement disorders, transcranial sonography detects alterations of deep brain structures with higher sensitivity than other neuroimaging methods. Lenticular nucleus hyperechogenicity on transcranial sonography, thought to be caused by increased local copper content, has been reported as a characteristic finding in primary spontaneous dystonia. Here, we wanted to find out whether deep brain structures are altered in task-specific dystonia. The frequency of sonographic brainstem and basal ganglia changes was studied in an investigator-blinded setting in 15 musicians with focal task-specific hand dystonia, 15 musicians without dystonia, and 15 age- and sex-matched nonmusicians without dystonia. Lenticular nucleus hyperechogenicity was found in 12 musicians with task-specific dystonia, but only in 3 nondystonic musicians (Fisher's exact test, p = 0.001) and 2 nonmusicians (p < 0.001). The degree of lenticular nucleus hyperechogenicity in affected musicians correlated with age, but not with duration of music practice or duration of dystonia. In 2 of 3 affected musicians with normal echogenic lenticular nucleus, substantia nigra hyperechogenicity was found. Our findings support the idea of a pathogenetic link between primary spontaneous and task-specific dystonia. Sonographic basal ganglia alteration might indicate a risk factor that in combination with extensive fine motor training promotes the manifestation of task-specific dystonia. Copyright © 2011 S. Karger AG, Basel.

Automatic Semantic Segmentation of Brain Gliomas from MRI Images Using a Deep Cascaded Neural Network.

PubMed

Cui, Shaoguo; Mao, Lei; Jiang, Jingfeng; Liu, Chang; Xiong, Shuyu

2018-01-01

Brain tumors can appear anywhere in the brain and have vastly different sizes and morphology. Additionally, these tumors are often diffused and poorly contrasted. Consequently, the segmentation of brain tumor and intratumor subregions using magnetic resonance imaging (MRI) data with minimal human interventions remains a challenging task. In this paper, we present a novel fully automatic segmentation method from MRI data containing in vivo brain gliomas. This approach can not only localize the entire tumor region but can also accurately segment the intratumor structure. The proposed work was based on a cascaded deep learning convolutional neural network consisting of two subnetworks: (1) a tumor localization network (TLN) and (2) an intratumor classification network (ITCN). The TLN, a fully convolutional network (FCN) in conjunction with the transfer learning technology, was used to first process MRI data. The goal of the first subnetwork was to define the tumor region from an MRI slice. Then, the ITCN was used to label the defined tumor region into multiple subregions. Particularly, ITCN exploited a convolutional neural network (CNN) with deeper architecture and smaller kernel. The proposed approach was validated on multimodal brain tumor segmentation (BRATS 2015) datasets, which contain 220 high-grade glioma (HGG) and 54 low-grade glioma (LGG) cases. Dice similarity coefficient (DSC), positive predictive value (PPV), and sensitivity were used as evaluation metrics. Our experimental results indicated that our method could obtain the promising segmentation results and had a faster segmentation speed. More specifically, the proposed method obtained comparable and overall better DSC values (0.89, 0.77, and 0.80) on the combined (HGG + LGG) testing set, as compared to other methods reported in the literature. Additionally, the proposed approach was able to complete a segmentation task at a rate of 1.54 seconds per slice.

What Makes Deeply Encoded Items Memorable? Insights into the Levels of Processing Framework from Neuroimaging and Neuromodulation

PubMed Central

Galli, Giulia

2014-01-01

When we form new memories, their mnestic fate largely depends upon the cognitive operations set in train during encoding. A typical observation in experimental as well as everyday life settings is that if we learn an item using semantic or “deep” operations, such as attending to its meaning, memory will be better than if we learn the same item using more “shallow” operations, such as attending to its structural features. In the psychological literature, this phenomenon has been conceptualized within the “levels of processing” framework and has been consistently replicated since its original proposal by Craik and Lockhart in 1972. However, the exact mechanisms underlying the memory advantage for deeply encoded items are not yet entirely understood. A cognitive neuroscience perspective can add to this field by clarifying the nature of the processes involved in effective deep and shallow encoding and how they are instantiated in the brain, but so far there has been little work to systematically integrate findings from the literature. This work aims to fill this gap by reviewing, first, some of the key neuroimaging findings on the neural correlates of deep and shallow episodic encoding and second, emerging evidence from studies using neuromodulatory approaches such as psychopharmacology and non-invasive brain stimulation. Taken together, these studies help further our understanding of levels of processing. In addition, by showing that deep encoding can be modulated by acting upon specific brain regions or systems, the reviewed studies pave the way for selective enhancements of episodic encoding processes. PMID:24904444

A novel tetrode microdrive for simultaneous multi-neuron recording from different regions of primate brain.

PubMed

Santos, Lucas; Opris, Ioan; Fuqua, Joshua; Hampson, Robert E; Deadwyler, Sam A

2012-04-15

A unique custom-made tetrode microdrive for recording from large numbers of neurons in several areas of primate brain is described as a means for assessing simultaneous neural activity in cortical and subcortical structures in nonhuman primates (NHPs) performing behavioral tasks. The microdrive device utilizes tetrode technology with up to six ultra-thin microprobe guide tubes (0.1mm) that can be independently positioned, each containing reduced diameter tetrode and/or hexatrode microwires (0.02 mm) for recording and isolating single neuron activity. The microdrive device is mounted within the standard NHP cranial well and allows traversal of brain depths up to 40.0 mm. The advantages of this technology are demonstrated via simultaneously recorded large populations of neurons with tetrode type probes during task performance from a) primary motor cortex and deep brain structures (caudate-putamen and hippocampus) and b) multiple layers within the prefrontal cortex. The means to characterize interactions of well-isolated ensembles of neurons recorded simultaneously from different regions, as shown with this device, has not been previously available for application in primate brain. The device has extensive application to primate models for the detection and study of inoperative or maladaptive neural circuits related to human neurological disorders. Published by Elsevier B.V.

Brain tumor classification of microscopy images using deep residual learning

NASA Astrophysics Data System (ADS)

Ishikawa, Yota; Washiya, Kiyotada; Aoki, Kota; Nagahashi, Hiroshi

2016-12-01

The crisis rate of brain tumor is about one point four in ten thousands. In general, cytotechnologists take charge of cytologic diagnosis. However, the number of cytotechnologists who can diagnose brain tumors is not sufficient, because of the necessity of highly specialized skill. Computer-Aided Diagnosis by computational image analysis may dissolve the shortage of experts and support objective pathological examinations. Our purpose is to support a diagnosis from a microscopy image of brain cortex and to identify brain tumor by medical image processing. In this study, we analyze Astrocytes that is a type of glia cell of central nerve system. It is not easy for an expert to discriminate brain tumor correctly since the difference between astrocytes and low grade astrocytoma (tumors formed from Astrocyte) is very slight. In this study, we present a novel method to segment cell regions robustly using BING objectness estimation and to classify brain tumors using deep convolutional neural networks (CNNs) constructed by deep residual learning. BING is a fast object detection method and we use pretrained BING model to detect brain cells. After that, we apply a sequence of post-processing like Voronoi diagram, binarization, watershed transform to obtain fine segmentation. For classification using CNNs, a usual way of data argumentation is applied to brain cells database. Experimental results showed 98.5% accuracy of classification and 98.2% accuracy of segmentation.

Perturbation and Nonlinear Dynamic Analysis of Acoustic Phonatory Signal in Parkinsonian Patients Receiving Deep Brain Stimulation

ERIC Educational Resources Information Center

Lee, Victoria S.; Zhou, Xiao Ping; Rahn, Douglas A., III; Wang, Emily Q.; Jiang, Jack J.

2008-01-01

Nineteen PD patients who received deep brain stimulation (DBS), 10 non-surgical (control) PD patients, and 11 non-pathologic age- and gender-matched subjects performed sustained vowel phonations. The following acoustic measures were obtained on the sustained vowel phonations: correlation dimension (D[subscript 2]), percent jitter, percent shimmer,…

Practical considerations and nuances in anesthesia for patients undergoing deep brain stimulation implantation surgery.

PubMed

Scharpf, Danielle Teresa; Sharma, Mayur; Deogaonkar, Milind; Rezai, Ali; Bergese, Sergio D

2015-08-01

The field of functional neurosurgery has expanded in last decade to include newer indications, new devices, and new methods. This advancement has challenged anesthesia providers to adapt to these new requirements. This review aims to discuss the nuances and practical issues that are faced while administering anesthesia for deep brain stimulation surgery.

Designing a deep brain stimulator to suppress pathological neuronal synchrony.

PubMed

Montaseri, Ghazal; Yazdanpanah, Mohammad Javad; Bahrami, Fariba

2015-03-01

Some of neuropathologies are believed to be related to abnormal synchronization of neurons. In the line of therapy, designing effective deep brain stimulators to suppress the pathological synchrony among neuronal ensembles is a challenge of high clinical relevance. The stimulation should be able to disrupt the synchrony in the presence of latencies due to imperfect knowledge about parameters of a neuronal ensemble and stimulation impacts on the ensemble. We propose an adaptive desynchronizing deep brain stimulator capable of dealing with these uncertainties. We analyze the collective behavior of the stimulated neuronal ensemble and show that, using the designed stimulator, the resulting asynchronous state is stable. Simulation results reveal the efficiency of the proposed technique. Copyright © 2014 Elsevier Ltd. All rights reserved.

Indian-Ink Perfusion Based Method for Reconstructing Continuous Vascular Networks in Whole Mouse Brain

PubMed Central

Xue, Songchao; Gong, Hui; Jiang, Tao; Luo, Weihua; Meng, Yuanzheng; Liu, Qian; Chen, Shangbin; Li, Anan

2014-01-01

The topology of the cerebral vasculature, which is the energy transport corridor of the brain, can be used to study cerebral circulatory pathways. Limited by the restrictions of the vascular markers and imaging methods, studies on cerebral vascular structure now mainly focus on either observation of the macro vessels in a whole brain or imaging of the micro vessels in a small region. Simultaneous vascular studies of arteries, veins and capillaries have not been achieved in the whole brain of mammals. Here, we have combined the improved gelatin-Indian ink vessel perfusion process with Micro-Optical Sectioning Tomography for imaging the vessel network of an entire mouse brain. With 17 days of work, an integral dataset for the entire cerebral vessels was acquired. The voxel resolution is 0.35×0.4×2.0 µm3 for the whole brain. Besides the observations of fine and complex vascular networks in the reconstructed slices and entire brain views, a representative continuous vascular tracking has been demonstrated in the deep thalamus. This study provided an effective method for studying the entire macro and micro vascular networks of mouse brain simultaneously. PMID:24498247

Deep Artificial Neural Networks and Neuromorphic Chips for Big Data Analysis: Pharmaceutical and Bioinformatics Applications.

PubMed

Pastur-Romay, Lucas Antón; Cedrón, Francisco; Pazos, Alejandro; Porto-Pazos, Ana Belén

2016-08-11

Over the past decade, Deep Artificial Neural Networks (DNNs) have become the state-of-the-art algorithms in Machine Learning (ML), speech recognition, computer vision, natural language processing and many other tasks. This was made possible by the advancement in Big Data, Deep Learning (DL) and drastically increased chip processing abilities, especially general-purpose graphical processing units (GPGPUs). All this has created a growing interest in making the most of the potential offered by DNNs in almost every field. An overview of the main architectures of DNNs, and their usefulness in Pharmacology and Bioinformatics are presented in this work. The featured applications are: drug design, virtual screening (VS), Quantitative Structure-Activity Relationship (QSAR) research, protein structure prediction and genomics (and other omics) data mining. The future need of neuromorphic hardware for DNNs is also discussed, and the two most advanced chips are reviewed: IBM TrueNorth and SpiNNaker. In addition, this review points out the importance of considering not only neurons, as DNNs and neuromorphic chips should also include glial cells, given the proven importance of astrocytes, a type of glial cell which contributes to information processing in the brain. The Deep Artificial Neuron-Astrocyte Networks (DANAN) could overcome the difficulties in architecture design, learning process and scalability of the current ML methods.

Roadmap on neurophotonics

NASA Astrophysics Data System (ADS)

Cho, Yong Ku; Zheng, Guoan; Augustine, George J.; Hochbaum, Daniel; Cohen, Adam; Knöpfel, Thomas; Pisanello, Ferruccio; Pavone, Francesco S.; Vellekoop, Ivo M.; Booth, Martin J.; Hu, Song; Zhu, Jiang; Chen, Zhongping; Hoshi, Yoko

2016-09-01

Mechanistic understanding of how the brain gives rise to complex behavioral and cognitive functions is one of science’s grand challenges. The technical challenges that we face as we attempt to gain a systems-level understanding of the brain are manifold. The brain’s structural complexity requires us to push the limit of imaging resolution and depth, while being able to cover large areas, resulting in enormous data acquisition and processing needs. Furthermore, it is necessary to detect functional activities and ‘map’ them onto the structural features. The functional activity occurs at multiple levels, using electrical and chemical signals. Certain electrical signals are only decipherable with sub-millisecond timescale resolution, while other modes of signals occur in minutes to hours. For these reasons, there is a wide consensus that new tools are necessary to undertake this daunting task. Optical techniques, due to their versatile and scalable nature, have great potentials to answer these challenges. Optical microscopy can now image beyond the diffraction limit, record multiple types of brain activity, and trace structural features across large areas of tissue. Genetically encoded molecular tools opened doors to controlling and detecting neural activity using light in specific cell types within the intact brain. Novel sample preparation methods that reduce light scattering have been developed, allowing whole brain imaging in rodent models. Adaptive optical methods have the potential to resolve images from deep brain regions. In this roadmap article, we showcase a few major advances in this area, survey the current challenges, and identify potential future needs that may be used as a guideline for the next steps to be taken.

Roadmap on neurophotonics

PubMed Central

Cho, Yong Ku; Zheng, Guoan; Augustine, George J; Hochbaum, Daniel; Cohen, Adam; Knöpfel, Thomas; Pisanello, Ferruccio; Pavone, Francesco S; Vellekoop, Ivo M; Booth, Martin J; Hu, Song; Zhu, Jiang; Chen, Zhongping; Hoshi, Yoko

2017-01-01

Mechanistic understanding of how the brain gives rise to complex behavioral and cognitive functions is one of science’s grand challenges. The technical challenges that we face as we attempt to gain a systems-level understanding of the brain are manifold. The brain’s structural complexity requires us to push the limit of imaging resolution and depth, while being able to cover large areas, resulting in enormous data acquisition and processing needs. Furthermore, it is necessary to detect functional activities and ‘map’ them onto the structural features. The functional activity occurs at multiple levels, using electrical and chemical signals. Certain electrical signals are only decipherable with sub-millisecond timescale resolution, while other modes of signals occur in minutes to hours. For these reasons, there is a wide consensus that new tools are necessary to undertake this daunting task. Optical techniques, due to their versatile and scalable nature, have great potentials to answer these challenges. Optical microscopy can now image beyond the diffraction limit, record multiple types of brain activity, and trace structural features across large areas of tissue. Genetically encoded molecular tools opened doors to controlling and detecting neural activity using light in specific cell types within the intact brain. Novel sample preparation methods that reduce light scattering have been developed, allowing whole brain imaging in rodent models. Adaptive optical methods have the potential to resolve images from deep brain regions. In this roadmap article, we showcase a few major advances in this area, survey the current challenges, and identify potential future needs that may be used as a guideline for the next steps to be taken. PMID:28386392

Cross-frequency coupling in deep brain structures upon processing the painful sensory inputs.

PubMed

Liu, C C; Chien, J H; Kim, J H; Chuang, Y F; Cheng, D T; Anderson, W S; Lenz, F A

2015-09-10

Cross-frequency coupling has been shown to be functionally significant in cortical information processing, potentially serving as a mechanism for integrating functionally relevant regions in the brain. In this study, we evaluate the hypothesis that pain-related gamma oscillatory responses are coupled with low-frequency oscillations in the frontal lobe, amygdala and hippocampus, areas known to have roles in pain processing. We delivered painful laser pulses to random locations on the dorsal hand of five patients with uncontrolled epilepsy requiring depth electrode implantation for seizure monitoring. Two blocks of 40 laser stimulations were delivered to each subject and the pain-intensity was controlled at five in a 0-10 scale by adjusting the energy level of the laser pulses. Local-field-potentials (LFPs) were recorded through bilaterally implanted depth electrode contacts to study the oscillatory responses upon processing the painful laser stimulations. Our results show that painful laser stimulations enhanced low-gamma (LH, 40-70 Hz) and high-gamma (HG, 70-110 Hz) oscillatory responses in the amygdala and hippocampal regions on the right hemisphere and these gamma responses were significantly coupled with the phases of theta (4-7 Hz) and alpha (8-1 2 Hz) rhythms during pain processing. Given the roles of these deep brain structures in emotion, these findings suggest that the oscillatory responses in these regions may play a role in integrating the affective component of pain, which may contribute to our understanding of the mechanisms underlying the affective information processing in humans. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

Pre-stimulus thalamic theta power predicts human memory formation.

PubMed

Sweeney-Reed, Catherine M; Zaehle, Tino; Voges, Jürgen; Schmitt, Friedhelm C; Buentjen, Lars; Kopitzki, Klaus; Richardson-Klavehn, Alan; Hinrichs, Hermann; Heinze, Hans-Jochen; Knight, Robert T; Rugg, Michael D

2016-09-01

Pre-stimulus theta (4-8Hz) power in the hippocampus and neocortex predicts whether a memory for a subsequent event will be formed. Anatomical studies reveal thalamus-hippocampal connectivity, and lesion, neuroimaging, and electrophysiological studies show that memory processing involves the dorsomedial (DMTN) and anterior thalamic nuclei (ATN). The small size and deep location of these nuclei have limited real-time study of their activity, however, and it is unknown whether pre-stimulus theta power predictive of successful memory formation is also found in these subcortical structures. We recorded human electrophysiological data from the DMTN and ATN of 7 patients receiving deep brain stimulation for refractory epilepsy. We found that greater pre-stimulus theta power in the right DMTN was associated with successful memory encoding, predicting both behavioral outcome and post-stimulus correlates of successful memory formation. In particular, significant correlations were observed between right DMTN theta power and both frontal theta and right ATN gamma (32-50Hz) phase alignment, and frontal-ATN theta-gamma cross-frequency coupling. We draw the following primary conclusions. Our results provide direct electrophysiological evidence in humans of a role for the DMTN as well as the ATN in memory formation. Furthermore, prediction of subsequent memory performance by pre-stimulus thalamic oscillations provides evidence that post-stimulus differences in thalamic activity that index successful and unsuccessful encoding reflect brain processes specifically underpinning memory formation. Finally, the findings broaden the understanding of brain states that facilitate memory encoding to include subcortical as well as cortical structures. Copyright © 2016 Elsevier Inc. All rights reserved.

Mapping the Cortical Network Arising From Up-Regulated Amygdaloidal Activation Using -Louvain Algorithm.

PubMed

Liu, Ning; Yu, Xueli; Yao, Li; Zhao, Xiaojie

2018-06-01

The amygdala plays an important role in emotion processing. Several studies have proved that its activation can be regulated by real-time functional magnetic resonance imaging (rtfMRI)-based neurofeedback training. However, although studies have found brain regions that are functionally closely connected to the amygdala in the cortex, it is not clear whether these brain regions and the amygdala are structurally closely connected, and if they show the same training effect as the amygdala in the process of emotional regulation. In this paper, we instructed subjects to up-regulate the activation of the left amygdala (LA) through rtfMRI-based neurofeedback training. In order to fuse multimodal imaging data, we introduced a network analysis method called the -Louvain clustering algorithm. This method was used to integrate multimodal data from the training experiment and construct an LA-cortical network. Correlation analysis and main-effect analysis were conducted to determine the signal covariance associated with the activation of the target area; ultimately, we identified the left temporal pole superior as the amygdaloidal-cortical network region. As a deep nucleus in the brain, the treatment and stimulation of the amygdala remains challenging. Our results provide new insights for the regulation of activation in a deep nucleus using more neurofeedback techniques.

Automated Grading of Gliomas using Deep Learning in Digital Pathology Images: A modular approach with ensemble of convolutional neural networks.

PubMed

Ertosun, Mehmet Günhan; Rubin, Daniel L

2015-01-01

Brain glioma is the most common primary malignant brain tumors in adults with different pathologic subtypes: Lower Grade Glioma (LGG) Grade II, Lower Grade Glioma (LGG) Grade III, and Glioblastoma Multiforme (GBM) Grade IV. The survival and treatment options are highly dependent of this glioma grade. We propose a deep learning-based, modular classification pipeline for automated grading of gliomas using digital pathology images. Whole tissue digitized images of pathology slides obtained from The Cancer Genome Atlas (TCGA) were used to train our deep learning modules. Our modular pipeline provides diagnostic quality statistics, such as precision, sensitivity and specificity, of the individual deep learning modules, and (1) facilitates training given the limited data in this domain, (2) enables exploration of different deep learning structures for each module, (3) leads to developing less complex modules that are simpler to analyze, and (4) provides flexibility, permitting use of single modules within the framework or use of other modeling or machine learning applications, such as probabilistic graphical models or support vector machines. Our modular approach helps us meet the requirements of minimum accuracy levels that are demanded by the context of different decision points within a multi-class classification scheme. Convolutional Neural Networks are trained for each module for each sub-task with more than 90% classification accuracies on validation data set, and achieved classification accuracy of 96% for the task of GBM vs LGG classification, 71% for further identifying the grade of LGG into Grade II or Grade III on independent data set coming from new patients from the multi-institutional repository.

Automated Grading of Gliomas using Deep Learning in Digital Pathology Images: A modular approach with ensemble of convolutional neural networks

PubMed Central

Ertosun, Mehmet Günhan; Rubin, Daniel L.

2015-01-01

Brain glioma is the most common primary malignant brain tumors in adults with different pathologic subtypes: Lower Grade Glioma (LGG) Grade II, Lower Grade Glioma (LGG) Grade III, and Glioblastoma Multiforme (GBM) Grade IV. The survival and treatment options are highly dependent of this glioma grade. We propose a deep learning-based, modular classification pipeline for automated grading of gliomas using digital pathology images. Whole tissue digitized images of pathology slides obtained from The Cancer Genome Atlas (TCGA) were used to train our deep learning modules. Our modular pipeline provides diagnostic quality statistics, such as precision, sensitivity and specificity, of the individual deep learning modules, and (1) facilitates training given the limited data in this domain, (2) enables exploration of different deep learning structures for each module, (3) leads to developing less complex modules that are simpler to analyze, and (4) provides flexibility, permitting use of single modules within the framework or use of other modeling or machine learning applications, such as probabilistic graphical models or support vector machines. Our modular approach helps us meet the requirements of minimum accuracy levels that are demanded by the context of different decision points within a multi-class classification scheme. Convolutional Neural Networks are trained for each module for each sub-task with more than 90% classification accuracies on validation data set, and achieved classification accuracy of 96% for the task of GBM vs LGG classification, 71% for further identifying the grade of LGG into Grade II or Grade III on independent data set coming from new patients from the multi-institutional repository. PMID:26958289

Language context modulates reading route: an electrical neuroimaging study

PubMed Central

Buetler, Karin A.; de León Rodríguez, Diego; Laganaro, Marina; Müri, René; Spierer, Lucas; Annoni, Jean-Marie

2014-01-01

Introduction: The orthographic depth hypothesis (Katz and Feldman, 1983) posits that different reading routes are engaged depending on the type of grapheme/phoneme correspondence of the language being read. Shallow orthographies with consistent grapheme/phoneme correspondences favor encoding via non-lexical pathways, where each grapheme is sequentially mapped to its corresponding phoneme. In contrast, deep orthographies with inconsistent grapheme/phoneme correspondences favor lexical pathways, where phonemes are retrieved from specialized memory structures. This hypothesis, however, lacks compelling empirical support. The aim of the present study was to investigate the impact of orthographic depth on reading route selection using a within-subject design. Method: We presented the same pseudowords (PWs) to highly proficient bilinguals and manipulated the orthographic depth of PW reading by embedding them among two separated German or French language contexts, implicating respectively, shallow or deep orthography. High density electroencephalography was recorded during the task. Results: The topography of the ERPs to identical PWs differed 300–360 ms post-stimulus onset when the PWs were read in different orthographic depth context, indicating distinct brain networks engaged in reading during this time window. The brain sources underlying these topographic effects were located within left inferior frontal (German > French), parietal (French > German) and cingular areas (German > French). Conclusion: Reading in a shallow context favors non-lexical pathways, reflected in a stronger engagement of frontal phonological areas in the shallow versus the deep orthographic context. In contrast, reading PW in a deep orthographic context recruits less routine non-lexical pathways, reflected in a stronger engagement of visuo-attentional parietal areas in the deep versus shallow orthographic context. These collective results support a modulation of reading route by orthographic depth. PMID:24600377

Hippocampus in health and disease: An overview

PubMed Central

Anand, Kuljeet Singh; Dhikav, Vikas

2012-01-01

Hippocampus is a complex brain structure embedded deep into temporal lobe. It has a major role in learning and memory. It is a plastic and vulnerable structure that gets damaged by a variety of stimuli. Studies have shown that it also gets affected in a variety of neurological and psychiatric disorders. In last decade or so, lot has been learnt about conditions that affect hippocampus and produce changes ranging from molecules to morphology. Progresses in radiological delineation, electrophysiology, and histochemical characterization have made it possible to study this archicerebral structure in greater detail. Present paper attempts to give an overview of hippocampus, both in health and diseases. PMID:23349586

Deep brain stimulation of the pedunculopontine nucleus for treatment of gait and balance disorder in progressive supranuclear palsy: Effects of frequency modulations and clinical outcome.

PubMed

Galazky, Imke; Kaufmann, Jörn; Lorenzl, Stefan; Ebersbach, Georg; Gandor, Florin; Zaehle, Tino; Specht, Sylke; Stallforth, Sabine; Sobieray, Uwe; Wirkus, Edyta; Casjens, Franziska; Heinze, Hans-Jochen; Kupsch, Andreas; Voges, Jürgen

2018-05-01

The pedunculopontine nucleus has been suggested as a potential deep brain stimulation target for axial symptoms such as gait and balance impairment in idiopathic Parkinson's disease as well as atypical Parkinsonian disorders. Seven consecutive patients with progressive supranuclear palsy received bilateral pedunculopontine nucleus deep brain stimulation. Inclusion criteria comprised of the clinical diagnosis of progressive supranuclear palsy, a levodopa-resistant gait and balance disorder, age <75 years, and absence of dementia or major psychiatric co-morbidities. Effects of stimulation frequencies at 8, 20, 60 and 130 Hz on motor scores and gait were assessed. Motor scores were followed up for two years postoperatively. Activities of daily living, frequency of falls, health-related quality of life, cognition and mood at 12 months were compared to baseline parameters. Surgical and stimulation related adverse events were assessed. Bilateral pedunculopontine nucleus deep brain stimulation at 8 Hz significantly improved axial motor symptoms and cyclic gait parameters, while high frequency stimulation did not ameliorate gait and balance but improved hypokinesia. This improvement however did not translate into clinically relevant benefits. Frequency of falls was not reduced. Activities of daily living, quality of life and frontal cognitive functions declined, while mood remained unchanged. Bilateral pedunculopontine nucleus deep brain stimulation in progressive supranuclear palsy generates frequency-dependent effects with improvement of cyclic gait parameters at low frequency and amelioration of hypokinesia at high frequency stimulation. However, these effects do not translate into a clinically important improvement. Copyright © 2018. Published by Elsevier Ltd.

The MDS-UPDRS tracks motor and non-motor improvement due to subthalamic nucleus deep brain stimulation in Parkinson disease.

PubMed

Chou, Kelvin L; Taylor, Jennifer L; Patil, Parag G

2013-11-01

The Movement Disorders Society revision of the Unified Parkinson Disease Rating Scale (MDS-UPDRS) improves upon the original UPDRS by adding more non-motor items, making it a more robust tool to evaluate the severity of motor and non-motor symptoms of Parkinson disease. Previous studies on deep brain stimulation have not used the MDS-UPDRS. To determine if the MDS-UPDRS could detect improvement in both motor and non-motor symptoms after bilateral subthalamic nucleus deep brain stimulation for Parkinson disease. We compared scores on the entire MDS-UPDRS prior to surgery (baseline) and approximately six months following the initial programming visit in twenty subjects (12M/8F) with Parkinson disease undergoing bilateral subthalamic nucleus deep brain stimulation. STN DBS significantly improved the scores for every section of the MDS-UPDRS at the 6 month follow-up. Part I improved by 3.1 points (22%), Part II by 5.3 points (29%), Part III by 13.1 points (29%) with stimulation alone, and Part IV by 7.1 points (74%). Individual non-motor items in Part I that improved significantly were constipation, light-headedness, and fatigue. Both motor and non-motor symptoms, as assessed by the MDS-UPDRS, improve with bilateral subthalamic nucleus stimulation six months after the stimulator is turned on. We recommend that the MDS-UPDRS be utilized in future deep brain stimulation studies because of the advantage of detecting change in non-motor symptoms. Copyright © 2013 Elsevier Ltd. All rights reserved.

Resting state cortical oscillations of patients with Parkinson disease and with and without subthalamic deep brain stimulation: a magnetoencephalography study.

PubMed

Cao, Chunyan; Li, Dianyou; Jiang, Tianxiao; Ince, Nuri Firat; Zhan, Shikun; Zhang, Jing; Sha, Zhiyi; Sun, Bomin

2015-04-01

In this study, we investigate the modification to cortical oscillations of patients with Parkinson disease (PD) by subthalamic deep brain stimulation (STN-DBS). Spontaneous cortical oscillations of patients with PD were recorded with magnetoencephalography during on and off subthalamic nucleus deep brain stimulation states. Several features such as average frequency, average power, and relative subband power in regions of interest were extracted in the frequency domain, and these features were correlated with Unified Parkinson Disease Rating Scale III evaluation. The same features were also investigated in patients with PD without surgery and healthy controls. Patients with Parkinson disease without surgery compared with healthy controls had a significantly lower average frequency and an increased average power in 1 to 48 Hz range in whole cortex. Higher relative power in theta and simultaneous decrease in beta and gamma over temporal and occipital were also observed in patients with PD. The Unified Parkinson Disease Rating Scale III rigidity score correlated with the average frequency and with the relative power of beta and gamma in frontal areas. During subthalamic nucleus deep brain stimulation, the average frequency increased significantly when stimulation was on compared with off state. In addition, the relative power dropped in delta, whereas it rose in beta over the whole cortex. Through the course of stimulation, the Unified Parkinson Disease Rating Scale III rigidity and tremor scores correlated with the relative power of alpha over left parietal. Subthalamic nucleus deep brain stimulation improves the symptoms of PD by suppressing the synchronization of alpha rhythm in somatomotor region.

Intensive Voice Treatment (LSVT[R]LOUD) for Parkinson's Disease Following Deep Brain Stimulation of the Subthalamic Nucleus

ERIC Educational Resources Information Center

Spielman, Jennifer; Mahler, Leslie; Halpern, Angela; Gilley, Phllip; Klepitskaya, Olga; Ramig, Lorraine

2011-01-01

Purpose: Intensive voice therapy (LSVT[R]LOUD) can effectively manage voice and speech symptoms associated with idiopathic Parkinson disease (PD). This small-group study evaluated voice and speech in individuals with and without deep brain stimulation of the subthalamic nucleus (STN-DBS) before and after LSVT LOUD, to determine whether outcomes…

Update on Deep Brain Stimulation for Dyskinesia and Dystonia: A Literature Review

PubMed Central

TODA, Hiroki; SAIKI, Hidemoto; NISHIDA, Namiko; IWASAKI, Koichi

2016-01-01

Deep brain stimulation (DBS) has been an established surgical treatment option for dyskinesia from Parkinson disease and for dystonia. The present article deals with the timing of surgical intervention, selecting an appropriate target, and minimizing adverse effects. We provide an overview of current evidences and issues for dyskinesia and dystonia as well as emerging DBS technology. PMID:27053331

Implementation of a smartphone wireless accelerometer platform for establishing deep brain stimulation treatment efficacy of essential tremor with machine learning.

PubMed

LeMoyne, Robert; Tomycz, Nestor; Mastroianni, Timothy; McCandless, Cyrus; Cozza, Michael; Peduto, David

2015-01-01

Essential tremor (ET) is a highly prevalent movement disorder. Patients with ET exhibit a complex progressive and disabling tremor, and medical management often fails. Deep brain stimulation (DBS) has been successfully applied to this disorder, however there has been no quantifiable way to measure tremor severity or treatment efficacy in this patient population. The quantified amelioration of kinetic tremor via DBS is herein demonstrated through the application of a smartphone (iPhone) as a wireless accelerometer platform. The recorded acceleration signal can be obtained at a setting of the subject's convenience and conveyed by wireless transmission through the Internet for post-processing anywhere in the world. Further post-processing of the acceleration signal can be classified through a machine learning application, such as the support vector machine. Preliminary application of deep brain stimulation with a smartphone for acquisition of a feature set and machine learning for classification has been successfully applied. The support vector machine achieved 100% classification between deep brain stimulation in `on' and `off' mode based on the recording of an accelerometer signal through a smartphone as a wireless accelerometer platform.

Unilateral pedunculopontine stimulation improves falls in Parkinson's disease.

PubMed

Moro, Elena; Hamani, Clement; Poon, Yu-Yan; Al-Khairallah, Thamar; Dostrovsky, Jonathan O; Hutchison, William D; Lozano, Andres M

2010-01-01

Postural instability and falls are a major source of disability in patients with advanced Parkinson's disease. These problems are currently not well addressed by either pharmacotherapy nor by subthalamic nucleus deep-brain stimulation surgery. The neuroanatomical substrates of posture and gait are poorly understood but a number of important observations suggest a major role for the pedunculopontine nucleus and adjacent areas in the brainstem. We conducted a double-blinded evaluation of unilateral pedunculopontine nucleus deep-brain stimulation in a pilot study in six advanced Parkinson's disease patients with significant gait and postural abnormalities. There was no significant difference in the double-blinded on versus off stimulation Unified Parkinson's Disease Rating Scale motor scores after 3 or 12 months of continuous stimulation and no improvements in the Unified Parkinson's Disease Rating Scale part III scores compared to baseline. In contrast, patients reported a significant reduction in falls in the on and off medication states both at 3 and 12 months after pedunculopontine nucleus deep-brain stimulation as captured in the Unified Parkinson's Disease Rating Scale part II scores. Our results suggest that pedunculopontine nucleus deep-brain stimulation may be effective in preventing falls in patients with advanced Parkinson's disease but that further evaluation of this procedure is required.

Performance on an episodic encoding task yields further insight into functional brain development.

PubMed

McAuley, Tara; Brahmbhatt, Shefali; Barch, Deanna M

2007-01-15

To further characterize changes in functional brain development that are associated with the emergence of cognitive control, participants 14 to 28 years of age were scanned while performing an episodic encoding task with a levels-of-processing manipulation. Using data from the 12 youngest and oldest participants (endpoint groups), 18 regions were identified that showed group differences in task-related activity as a function of processing depth. One region, located in left inferior frontal gyrus, showed enhanced activity in deep relative to shallow encoding that was larger in magnitude for the older group. Seventeen regions showed enhanced activity in shallow relative to deep encoding that was larger in magnitude for the youngest group. These regions were distributed across a broad network that included both cortical and subcortical areas. Regression analyses using the entire sample showed that age made a significant contribution to the difference in beta weights between deep and shallow encoding for 17 of the 18 identified regions in the direction predicted by the endpoint analysis. We conclude that the patterns of brain activation associated with deep and shallow encoding differ between adolescents and young adults in a manner that is consistent with the interactive specialization account of functional brain development.

Real-Time Ultrasound-Guided Catheter Navigation for Approaching Deep-Seated Brain Lesions: Role of Intraoperative Neurosonography with and without Fusion with Magnetic Resonance Imaging.

PubMed

Manjila, Sunil; Karhade, Aditya; Phi, Ji Hoon; Scott, R Michael; Smith, Edward R

2017-01-01

Brain shift during the exposure of cranial lesions may reduce the accuracy of frameless stereotaxy. We describe a rapid, safe, and effective method to approach deep-seated brain lesions using real-time intraoperative ultrasound placement of a catheter to mark the dissection trajectory to the lesion. With Institutional Review Board approval, we retrospectively reviewed the radiographic, pathologic, and intraoperative data of 11 pediatric patients who underwent excision of 12 lesions by means of this technique. Full data sets were available for 12 lesions in 11 patients. Ten lesions were tumors and 2 were cavernous malformations. Lesion locations included the thalamus (n = 4), trigone (n = 3), mesial temporal lobe (n = 3), and deep white matter (n = 2). Catheter placement was successful in all patients, and the median time required for the procedure was 3 min (range 2-5 min). There were no complications related to catheter placement. The median diameter of surgical corridors on postresection magnetic resonance imaging was 6.6 mm (range 3.0-12.1 mm). Use of real-time ultrasound guidance to place a catheter to aid in the dissection to reach a deep-seated brain lesion provides advantages complementary to existing techniques, such as frameless stereotaxy. The catheter insertion technique described here provides a quick, accurate, and safe method for reaching deep-seated lesions. © 2017 S. Karger AG, Basel.

Deep learning and texture-based semantic label fusion for brain tumor segmentation

NASA Astrophysics Data System (ADS)

Vidyaratne, L.; Alam, M.; Shboul, Z.; Iftekharuddin, K. M.

2018-02-01

Brain tumor segmentation is a fundamental step in surgical treatment and therapy. Many hand-crafted and learning based methods have been proposed for automatic brain tumor segmentation from MRI. Studies have shown that these approaches have their inherent advantages and limitations. This work proposes a semantic label fusion algorithm by combining two representative state-of-the-art segmentation algorithms: texture based hand-crafted, and deep learning based methods to obtain robust tumor segmentation. We evaluate the proposed method using publicly available BRATS 2017 brain tumor segmentation challenge dataset. The results show that the proposed method offers improved segmentation by alleviating inherent weaknesses: extensive false positives in texture based method, and the false tumor tissue classification problem in deep learning method, respectively. Furthermore, we investigate the effect of patient's gender on the segmentation performance using a subset of validation dataset. Note the substantial improvement in brain tumor segmentation performance proposed in this work has recently enabled us to secure the first place by our group in overall patient survival prediction task at the BRATS 2017 challenge.

Violence, mental illness, and the brain – A brief history of psychosurgery: Part 2 – From the limbic system and cingulotomy to deep brain stimulation

PubMed Central

Faria, Miguel A.

2013-01-01

Knowledge of neuroscience flourished during and in the wake of the era of frontal lobotomy, as a byproduct of psychosurgery in the late 1930s and 1940s, revealing fascinating neural pathways and neurophysiologic mechanisms of the limbic system for the formulation of emotions, memory, and human behavior. The creation of the Klüver-Bucy syndrome in monkeys opened new horizons in the pursuit of knowledge in human behavior and neuropathology. In the 1950s specialized functional neurosurgery was developed in association with stereotactic neurosurgery; deep brain electrodes were implanted for more precise recording of brain electrical activity in the evaluation and treatment of intractable mental disorders, including schizophrenia, “pathologic aggression,” and psychomotor seizures in temporal lobe epilepsy. Psychosurgical procedures involved deep brain stimulation of the limbic system, as well as ablative procedures, such as cingulotomy and thalamotomy. The history of these developments up to the 21st century will continue in this three-part essay-editorial, exclusively researched and written for the readers of Surgical Neurology International. PMID:23776761

Deep Learning and Texture-Based Semantic Label Fusion for Brain Tumor Segmentation.

PubMed

Vidyaratne, L; Alam, M; Shboul, Z; Iftekharuddin, K M

2018-01-01

Brain tumor segmentation is a fundamental step in surgical treatment and therapy. Many hand-crafted and learning based methods have been proposed for automatic brain tumor segmentation from MRI. Studies have shown that these approaches have their inherent advantages and limitations. This work proposes a semantic label fusion algorithm by combining two representative state-of-the-art segmentation algorithms: texture based hand-crafted, and deep learning based methods to obtain robust tumor segmentation. We evaluate the proposed method using publicly available BRATS 2017 brain tumor segmentation challenge dataset. The results show that the proposed method offers improved segmentation by alleviating inherent weaknesses: extensive false positives in texture based method, and the false tumor tissue classification problem in deep learning method, respectively. Furthermore, we investigate the effect of patient's gender on the segmentation performance using a subset of validation dataset. Note the substantial improvement in brain tumor segmentation performance proposed in this work has recently enabled us to secure the first place by our group in overall patient survival prediction task at the BRATS 2017 challenge.

Identification and Characterization of Novel FMRP-Associated miRNAs

DTIC Science & Technology

2013-10-01

Dependent Synaptic Structure at the Drosophila melanogaster Neuromuscular Junction. Plos One 8: e68385. 11. Adams CM, Anderson MG, Motto DG, Price MP...extension towards the end of the funding period in order to complete the all proposed experiments. Aim 1. Purification and deep sequencing of FMRP...First, when expression of transgenic PrA-tagged FMRP was driven in the adult Drosophila brain, we did not observe an expected shift in size when

Deep Learning MR Imaging-based Attenuation Correction for PET/MR Imaging.

PubMed

Liu, Fang; Jang, Hyungseok; Kijowski, Richard; Bradshaw, Tyler; McMillan, Alan B

2018-02-01

Purpose To develop and evaluate the feasibility of deep learning approaches for magnetic resonance (MR) imaging-based attenuation correction (AC) (termed deep MRAC) in brain positron emission tomography (PET)/MR imaging. Materials and Methods A PET/MR imaging AC pipeline was built by using a deep learning approach to generate pseudo computed tomographic (CT) scans from MR images. A deep convolutional auto-encoder network was trained to identify air, bone, and soft tissue in volumetric head MR images coregistered to CT data for training. A set of 30 retrospective three-dimensional T1-weighted head images was used to train the model, which was then evaluated in 10 patients by comparing the generated pseudo CT scan to an acquired CT scan. A prospective study was carried out for utilizing simultaneous PET/MR imaging for five subjects by using the proposed approach. Analysis of covariance and paired-sample t tests were used for statistical analysis to compare PET reconstruction error with deep MRAC and two existing MR imaging-based AC approaches with CT-based AC. Results Deep MRAC provides an accurate pseudo CT scan with a mean Dice coefficient of 0.971 ± 0.005 for air, 0.936 ± 0.011 for soft tissue, and 0.803 ± 0.021 for bone. Furthermore, deep MRAC provides good PET results, with average errors of less than 1% in most brain regions. Significantly lower PET reconstruction errors were realized with deep MRAC (-0.7% ± 1.1) compared with Dixon-based soft-tissue and air segmentation (-5.8% ± 3.1) and anatomic CT-based template registration (-4.8% ± 2.2). Conclusion The authors developed an automated approach that allows generation of discrete-valued pseudo CT scans (soft tissue, bone, and air) from a single high-spatial-resolution diagnostic-quality three-dimensional MR image and evaluated it in brain PET/MR imaging. This deep learning approach for MR imaging-based AC provided reduced PET reconstruction error relative to a CT-based standard within the brain compared with current MR imaging-based AC approaches. © RSNA, 2017 Online supplemental material is available for this article.

Neural stimulation for Parkinson's disease: current therapies and future directions.

PubMed

Neimat, Joseph S; Hamani, Clement; Lozano, Andres M

2006-01-01

Neural stimulation has rapidly become an integral tool in the treatment of Parkinson's disease and other movement disorders. Today it serves as an important adjunct to medical therapy that continues to gain applicability to patients in whom the disease has progressed significantly. Studies have demonstrated efficacy in several deep-brain targets, with prolonged benefit exceeding 5-year follow-up times. Continuing study is teaching us more about the mechanism of deep-brain stimulation effect. New targets, which may treat the disease more successfully, are being examined. In this review, the history of deep-brain stimulation, the rationale for the known targets of stimulation; the clinical evidence demonstrating their benefit and, finally, future perspectives on new treatments that are being investigated and may have an impact on the field are discussed.

Subthalamic nucleus deep brain stimulation affects distractor interference in auditory working memory.

PubMed

Camalier, Corrie R; Wang, Alice Y; McIntosh, Lindsey G; Park, Sohee; Neimat, Joseph S

2017-03-01

Computational and theoretical accounts hypothesize the basal ganglia play a supramodal "gating" role in the maintenance of working memory representations, especially in preservation from distractor interference. There are currently two major limitations to this account. The first is that supporting experiments have focused exclusively on the visuospatial domain, leaving questions as to whether such "gating" is domain-specific. The second is that current evidence relies on correlational measures, as it is extremely difficult to causally and reversibly manipulate subcortical structures in humans. To address these shortcomings, we examined non-spatial, auditory working memory performance during reversible modulation of the basal ganglia, an approach afforded by deep brain stimulation of the subthalamic nucleus. We found that subthalamic nucleus stimulation impaired auditory working memory performance, specifically in the group tested in the presence of distractors, even though the distractors were predictable and completely irrelevant to the encoding of the task stimuli. This study provides key causal evidence that the basal ganglia act as a supramodal filter in working memory processes, further adding to our growing understanding of their role in cognition. Copyright © 2017 Elsevier Ltd. All rights reserved.

Implementation of a Peltier-based cooling device for localized deep cortical deactivation during in vivo object recognition testing

NASA Astrophysics Data System (ADS)

Marra, Kyle; Graham, Brett; Carouso, Samantha; Cox, David

2012-02-01

While the application of local cortical cooling has recently become a focus of neurological research, extended localized deactivation deep within brain structures is still unexplored. Using a wirelessly controlled thermoelectric (Peltier) device and water-based heat sink, we have achieved inactivating temperatures (<20 C) at greater depths (>8 mm) than previously reported. After implanting the device into Long Evans rats' basolateral amygdala (BLA), an inhibitory brain center that controls anxiety and fear, we ran an open field test during which anxiety-driven behavioral tendencies were observed to decrease during cooling, thus confirming the device's effect on behavior. Our device will next be implanted in the rats' temporal association cortex (TeA) and recordings from our signal-tracing multichannel microelectrodes will measure and compare activated and deactivated neuronal activity so as to isolate and study the TeA signals responsible for object recognition. Having already achieved a top performing computational face-recognition system, the lab will utilize this TeA activity data to generalize its computational efforts of face recognition to achieve general object recognition.

Aggravated stuttering following subthalamic deep brain stimulation in Parkinson's disease - two cases

PubMed Central

2011-01-01

Stuttering is a speech disorder with disruption of verbal fluency which is occasionally present in patients with Parkinson's disease (PD). Long-term medical management of PD is frequently complicated by fluctuating motor functions and dyskinesias. High-frequency deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment of motor fluctuations and is the most common surgical procedure in PD. Here we report the re-occurrence and aggravation of stuttering following STN-DBS in two male patients treated for advanced PD. In both patients the speech fluency improved considerably when the neurostimulator was turned off, indicating that stuttering aggravation was related to neurostimulation of the STN itself, its afferent or efferent projections and/or to structures localized in the immediate proximity. This report supports previous studies demonstrating that lesions of the basal ganglia-thalamocortical motor circuit, including the STN, is involved in the development of stuttering. In advanced PD STN-DBS is generally an effective and safe treatment. However, patients with PD and stuttering should be informed about the risk of aggravated symptoms following surgical therapy. PMID:21477305

Hearing assessment during deep brain stimulation of the central nucleus of the inferior colliculus and dentate cerebellar nucleus in rat.

PubMed

Smit, Jasper V; Jahanshahi, Ali; Janssen, Marcus L F; Stokroos, Robert J; Temel, Yasin

2017-01-01

Recently it has been shown in animal studies that deep brain stimulation (DBS) of auditory structures was able to reduce tinnitus-like behavior. However, the question arises whether hearing might be impaired when interfering in auditory-related network loops with DBS. The auditory brainstem response (ABR) was measured in rats during high frequency stimulation (HFS) and low frequency stimulation (LFS) in the central nucleus of the inferior colliculus (CIC, n  = 5) or dentate cerebellar nucleus (DCBN, n  = 5). Besides hearing thresholds using ABR, relative measures of latency and amplitude can be extracted from the ABR. In this study ABR thresholds, interpeak latencies (I-III, III-V, I-V) and V/I amplitude ratio were measured during off-stimulation state and during LFS and HFS. In both the CIC and the CNBN groups, no significant differences were observed for all outcome measures. DBS in both the CIC and the CNBN did not have adverse effects on hearing measurements. These findings suggest that DBS does not hamper physiological processing in the auditory circuitry.

Nanowires precisely grown on the ends of microwire electrodes permit the recording of intracellular action potentials within deeper neural structures

PubMed Central

Ferguson, John E; Boldt, Christopher; Puhl, Joshua G; Stigen, Tyler W; Jackson, Jadin C; Crisp, Kevin M; Mesce, Karen A; Netoff, Theoden I; Redish, A David

2012-01-01

Aims Nanoelectrodes are an emerging biomedical technology that can be used to record intracellular membrane potentials from neurons while causing minimal damage during membrane penetration. Current nanoelectrode designs, however, have low aspect ratios or large substrates and thus are not suitable for recording from neurons deep within complex natural structures, such as brain slices. Materials & methods We describe a novel nanoelectrode design that uses nanowires grown on the ends of microwire recording electrodes similar to those frequently used in vivo. Results & discussion We demonstrate that these nanowires can record intracellular action potentials in a rat brain slice preparation and in isolated leech ganglia. Conclusion Nanoelectrodes have the potential to revolutionize intracellular recording methods in complex neural tissues, to enable new multielectrode array technologies and, ultimately, to be used to record intracellular signals in vivo. PMID:22475650

Ventromedial Hypothalamus and the Generation of Aggression

PubMed Central

Hashikawa, Yoshiko; Hashikawa, Koichi; Falkner, Annegret L.; Lin, Dayu

2017-01-01

Aggression is a costly behavior, sometimes with severe consequences including death. Yet aggression is prevalent across animal species ranging from insects to humans, demonstrating its essential role in the survival of individuals and groups. The question of how the brain decides when to generate this costly behavior has intrigued neuroscientists for over a century and has led to the identification of relevant neural substrates. Various lesion and electric stimulation experiments have revealed that the hypothalamus, an ancient structure situated deep in the brain, is essential for expressing aggressive behaviors. More recently, studies using precise circuit manipulation tools have identified a small subnucleus in the medial hypothalamus, the ventrolateral part of the ventromedial hypothalamus (VMHvl), as a key structure for driving both aggression and aggression-seeking behaviors. Here, we provide an updated summary of the evidence that supports a role of the VMHvl in aggressive behaviors. We will consider our recent findings detailing the physiological response properties of populations of VMHvl cells during aggressive behaviors and provide new understanding regarding the role of the VMHvl embedded within the larger whole-brain circuit for social sensation and action. PMID:29375329

Linking white matter and deep gray matter alterations in premanifest Huntington disease.

PubMed

Faria, Andreia V; Ratnanather, J Tilak; Tward, Daniel J; Lee, David Soobin; van den Noort, Frieda; Wu, Dan; Brown, Timothy; Johnson, Hans; Paulsen, Jane S; Ross, Christopher A; Younes, Laurent; Miller, Michael I

2016-01-01

Huntington disease (HD) is a fatal progressive neurodegenerative disorder for which only symptomatic treatment is available. A better understanding of the pathology, and identification of biomarkers will facilitate the development of disease-modifying treatments. HD is potentially a good model of a neurodegenerative disease for development of biomarkers because it is an autosomal-dominant disease with complete penetrance, caused by a single gene mutation, in which the neurodegenerative process can be assessed many years before onset of signs and symptoms of manifest disease. Previous MRI studies have detected abnormalities in gray and white matter starting in premanifest stages. However, the understanding of how these abnormalities are related, both in time and space, is still incomplete. In this study, we combined deep gray matter shape diffeomorphometry and white matter DTI analysis in order to provide a better mapping of pathology in the deep gray matter and subcortical white matter in premanifest HD. We used 296 MRI scans from the PREDICT-HD database. Atrophy in the deep gray matter, thalamus, hippocampus, and nucleus accumbens was analyzed by surface based morphometry, and while white matter abnormalities were analyzed in (i) regions of interest surrounding these structures, using (ii) tractography-based analysis, and using (iii) whole brain atlas-based analysis. We detected atrophy in the deep gray matter, particularly in putamen, from early premanifest stages. The atrophy was greater both in extent and effect size in cases with longer exposure to the effects of the CAG expansion mutation (as assessed by greater CAP-scores), and preceded detectible abnormalities in the white matter. Near the predicted onset of manifest HD, the MD increase was widespread, with highest indices in the deep and posterior white matter. This type of in-vivo macroscopic mapping of HD brain abnormalities can potentially indicate when and where therapeutics could be targeted to delay the onset or slow the disease progression.

Brain MRI analysis for Alzheimer's disease diagnosis using an ensemble system of deep convolutional neural networks.

PubMed

Islam, Jyoti; Zhang, Yanqing

2018-05-31

Alzheimer's disease is an incurable, progressive neurological brain disorder. Earlier detection of Alzheimer's disease can help with proper treatment and prevent brain tissue damage. Several statistical and machine learning models have been exploited by researchers for Alzheimer's disease diagnosis. Analyzing magnetic resonance imaging (MRI) is a common practice for Alzheimer's disease diagnosis in clinical research. Detection of Alzheimer's disease is exacting due to the similarity in Alzheimer's disease MRI data and standard healthy MRI data of older people. Recently, advanced deep learning techniques have successfully demonstrated human-level performance in numerous fields including medical image analysis. We propose a deep convolutional neural network for Alzheimer's disease diagnosis using brain MRI data analysis. While most of the existing approaches perform binary classification, our model can identify different stages of Alzheimer's disease and obtains superior performance for early-stage diagnosis. We conducted ample experiments to demonstrate that our proposed model outperformed comparative baselines on the Open Access Series of Imaging Studies dataset.

Effects of Medication and Subthalamic Nucleus Deep Brain Stimulation on Tongue Movements in Speakers with Parkinson's Disease Using Electropalatography: A Pilot Study

ERIC Educational Resources Information Center

Hartinger, Mariam; Tripoliti, Elina; Hardcastle, William J.; Limousin, Patricia

2011-01-01

Parkinson's disease (PD) affects speech in the majority of patients. Subthalamic nucleus deep brain stimulation (STN-DBS) is particularly effective in reducing tremor and rigidity. However, its effect on speech is variable. The aim of this pilot study was to quantify the effects of bilateral STN-DBS and medication on articulation, using…

Deep Brain Stimulation of the Subthalamic Nucleus Parameter Optimization for Vowel Acoustics and Speech Intelligibility in Parkinson's Disease

ERIC Educational Resources Information Center

Knowles, Thea; Adams, Scott; Abeyesekera, Anita; Mancinelli, Cynthia; Gilmore, Greydon; Jog, Mandar

2018-01-01

Purpose: The settings of 3 electrical stimulation parameters were adjusted in 12 speakers with Parkinson's disease (PD) with deep brain stimulation of the subthalamic nucleus (STN-DBS) to examine their effects on vowel acoustics and speech intelligibility. Method: Participants were tested under permutations of low, mid, and high STN-DBS frequency,…

Pitch Variability in Patients with Parkinson's Disease: Effects of Deep Brain Stimulation of Caudal Zona Incerta and Subthalamic Nucleus

ERIC Educational Resources Information Center

Karlsson, Fredrik; Olofsson, Katarina; Blomstedt, Patric; Linder, Jan; van Doorn, Jan

2013-01-01

Purpose: The purpose of the present study was to examine the effect of deep brain stimulation (DBS) of the subthalamic nucleus (STN) and the caudal zona incerta (cZi) pitch characteristics of connected speech in patients with Parkinson's disease (PD). Method: The authors evaluated 16 patients preoperatively and 12 months after DBS surgery. Eight…

Articulatory Closure Proficiency in Patients with Parkinson's Disease Following Deep Brain Stimulation of the Subthalamic Nucleus and Caudal Zona Incerta

ERIC Educational Resources Information Center

Karlsson, Fredrik; Olofsson, Katarina; Blomstedt, Patric; Linder, Jan; Nordh, Erik; van Doorn, Jan

2014-01-01

Purpose: The present study aimed at comparing the effects of deep brain stimulation (DBS) treatment of the subthalamic nucleus (STN) and the caudal zona incerta (cZi) on the proficiency in achieving oral closure and release during plosive production of people with Parkinson's disease. Method: Nineteen patients participated preoperatively and…

Sentiment analysis: a comparison of deep learning neural network algorithm with SVM and naϊve Bayes for Indonesian text

NASA Astrophysics Data System (ADS)

Calvin Frans Mariel, Wahyu; Mariyah, Siti; Pramana, Setia

2018-03-01

Deep learning is a new era of machine learning techniques that essentially imitate the structure and function of the human brain. It is a development of deeper Artificial Neural Network (ANN) that uses more than one hidden layer. Deep Learning Neural Network has a great ability on recognizing patterns from various data types such as picture, audio, text, and many more. In this paper, the authors tries to measure that algorithm’s ability by applying it into the text classification. The classification task herein is done by considering the content of sentiment in a text which is also called as sentiment analysis. By using several combinations of text preprocessing and feature extraction techniques, we aim to compare the precise modelling results of Deep Learning Neural Network with the other two commonly used algorithms, the Naϊve Bayes and Support Vector Machine (SVM). This algorithm comparison uses Indonesian text data with balanced and unbalanced sentiment composition. Based on the experimental simulation, Deep Learning Neural Network clearly outperforms the Naϊve Bayes and SVM and offers a better F-1 Score while for the best feature extraction technique which improves that modelling result is Bigram.

Deep learning enables reduced gadolinium dose for contrast-enhanced brain MRI.

PubMed

Gong, Enhao; Pauly, John M; Wintermark, Max; Zaharchuk, Greg

2018-02-13

There are concerns over gadolinium deposition from gadolinium-based contrast agents (GBCA) administration. To reduce gadolinium dose in contrast-enhanced brain MRI using a deep learning method. Retrospective, crossover. Sixty patients receiving clinically indicated contrast-enhanced brain MRI. 3D T 1 -weighted inversion-recovery prepped fast-spoiled-gradient-echo (IR-FSPGR) imaging was acquired at both 1.5T and 3T. In 60 brain MRI exams, the IR-FSPGR sequence was obtained under three conditions: precontrast, postcontrast images with 10% low-dose (0.01mmol/kg) and 100% full-dose (0.1 mmol/kg) of gadobenate dimeglumine. We trained a deep learning model using the first 10 cases (with mixed indications) to approximate full-dose images from the precontrast and low-dose images. Synthesized full-dose images were created using the trained model in two test sets: 20 patients with mixed indications and 30 patients with glioma. For both test sets, low-dose, true full-dose, and the synthesized full-dose postcontrast image sets were compared quantitatively using peak-signal-to-noise-ratios (PSNR) and structural-similarity-index (SSIM). For the test set comprised of 20 patients with mixed indications, two neuroradiologists scored blindly and independently for the three postcontrast image sets, evaluating image quality, motion-artifact suppression, and contrast enhancement compared with precontrast images. Results were assessed using paired t-tests and noninferiority tests. The proposed deep learning method yielded significant (n = 50, P < 0.001) improvements over the low-dose images (>5 dB PSNR gains and >11.0% SSIM). Ratings on image quality (n = 20, P = 0.003) and contrast enhancement (n = 20, P < 0.001) were significantly increased. Compared to true full-dose images, the synthesized full-dose images have a slight but not significant reduction in image quality (n = 20, P = 0.083) and contrast enhancement (n = 20, P = 0.068). Slightly better (n = 20, P = 0.039) motion-artifact suppression was noted in the synthesized images. The noninferiority test rejects the inferiority of the synthesized to true full-dose images for image quality (95% CI: -14-9%), artifacts suppression (95% CI: -5-20%), and contrast enhancement (95% CI: -13-6%). With the proposed deep learning method, gadolinium dose can be reduced 10-fold while preserving contrast information and avoiding significant image quality degradation. 3 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2018. © 2018 International Society for Magnetic Resonance in Medicine.

Segmentation of the Globus Pallidus Internus Using Probabilistic Diffusion Tractography for Deep Brain Stimulation Targeting in Parkinson Disease.

PubMed

Middlebrooks, E H; Tuna, I S; Grewal, S S; Almeida, L; Heckman, M G; Lesser, E R; Foote, K D; Okun, M S; Holanda, V M

2018-06-01

Although globus pallidus internus deep brain stimulation is a widely accepted treatment for Parkinson disease, there is persistent variability in outcomes that is not yet fully understood. In this pilot study, we aimed to investigate the potential role of globus pallidus internus segmentation using probabilistic tractography as a supplement to traditional targeting methods. Eleven patients undergoing globus pallidus internus deep brain stimulation were included in this retrospective analysis. Using multidirection diffusion-weighted MR imaging, we performed probabilistic tractography at all individual globus pallidus internus voxels. Each globus pallidus internus voxel was then assigned to the 1 ROI with the greatest number of propagated paths. On the basis of deep brain stimulation programming settings, the volume of tissue activated was generated for each patient using a finite element method solution. For each patient, the volume of tissue activated within each of the 10 segmented globus pallidus internus regions was calculated and examined for association with a change in the Unified Parkinson Disease Rating Scale, Part III score before and after treatment. Increasing volume of tissue activated was most strongly correlated with a change in the Unified Parkinson Disease Rating Scale, Part III score for the primary motor region (Spearman r = 0.74, P = .010), followed by the supplementary motor area/premotor cortex (Spearman r = 0.47, P = .15). In this pilot study, we assessed a novel method of segmentation of the globus pallidus internus based on probabilistic tractography as a supplement to traditional targeting methods. Our results suggest that our method may be an independent predictor of deep brain stimulation outcome, and evaluation of a larger cohort or prospective study is warranted to validate these findings. © 2018 by American Journal of Neuroradiology.

Longitudinal relaxographic imaging of white matter hyperintensities in the elderly

PubMed Central

2014-01-01

Background Incidental white matter hyperintensities (WMHs) are common findings on T2-weighted magnetic resonance images of the aged brain and have been associated with cognitive decline. While a variety of pathogenic mechanisms have been proposed, the origin of WMHs and the extent to which lesions in the deep and periventricular white matter reflect distinct etiologies remains unclear. Our aim was to quantify the fractional blood volume (vb) of small WMHs in vivo using a novel magnetic resonance imaging (MRI) approach and examine the contribution of blood–brain barrier disturbances to WMH formation in the deep and periventricular white matter. Methods Twenty-three elderly volunteers (aged 59–82 years) underwent 7 Tesla relaxographic imaging and fluid-attenuated inversion recovery (FLAIR) MRI. Maps of longitudinal relaxation rate constant (R1) were prepared before contrast reagent (CR) injection and throughout CR washout. Voxelwise estimates of vb were determined by fitting temporal changes in R1 values to a two-site model that incorporates the effects of transendothelial water exchange. Average vb values in deep and periventricular WMHs were determined after semi-automated segmentation of FLAIR images. Ventricular permeability was estimated from the change in CSF R1 values during CR washout. Results In the absence of CR, the total water fraction in both deep and periventricular WMHs was increased compared to normal appearing white matter (NAWM). The vb of deep WMHs was 1.8 ± 0.6 mL/100 g and was significantly reduced compared to NAWM (2.4 ± 0.8 mL/100 g). In contrast, the vb of periventricular WMHs was unchanged compared to NAWM, decreased with ventricular volume and showed a positive association with ventricular permeability. Conclusions Hyperintensities in the deep WM appear to be driven by vascular compromise, while those in the periventricular WM are most likely the result of a compromised ependyma in which the small vessels remain relatively intact. These findings support varying contributions of blood–brain barrier and brain-CSF interface disturbances in the pathophysiology of deep and periventricular WMHs in the aged human brain. PMID:25379172

Improvement of two-photon microscopic imaging in deep regions of living mouse brains by utilizing a light source based on an electrically controllable gain-switched laser diode

NASA Astrophysics Data System (ADS)

Sawada, Kazuaki; Kawakami, Ryosuke; Fang, Yi-Cheng; Hung, Jui-Hung; Kozawa, Yuichi; Otomo, Kohei; Sato, Shunichi; Yokoyama, Hiroyuki; Nemoto, Tomomi

2018-02-01

In vivo two-photon microscopy is an advantageous technique for observing living mouse brains at high spatial resolutions. We previously used a 1064 nm high-power light source based on an electrically controllable gain-switched laser diode (maximum power: 4 W, repetition rate: 10 MHz, pulse width: 7.5 picoseconds) and successfully visualized EYFP expressing neurons at deeper regions in H-line mouse brains under living conditions. However, severe damages were frequently observed when the laser power after the objective lens was over 600 mW, suggesting that a higher average power might not be suitable for visualizing neural structures and functions at deep regions. To increase fluorescent signals as a strategy to avoid such invasions, here, we evaluated the effects of the excitation laser parameters such as the repetition rate (5 - 10 MHz), or the peak power, at the moderate average powers (10 - 500 mW), by taking the advantage that this electrically controllable light source could be used to change the repetition rate independently from the average power or the pulse width. The fluorescent signals of EYFP at layer V of the cerebral cortex were increased by approximately twofold when the repetition rate was decreased from 10 MHz to 5 MHz at the same average power. We also confirmed similar effects in the EYFP solution (335 μM) and fixed brain slices. These results suggest that in vivo two-photon microscopic imaging might be improved by increasing the peak power at the same average power while avoiding the severe damages in living brains.

[Deep brain stimulation in movement disorders: evidence and therapy standards].

PubMed

Parpaley, Yaroslav; Skodda, Sabine

2017-07-01

The deep brain stimulation (DBS) in movement disorders is well established and in many aspects evidence-based procedure. The treatment indications are very heterogeneous and very specific in their course and therapy. The deep brain stimulation plays very important, but usually not the central role in this conditions. The success in the application of DBS is essentially associated with the correct, appropriate and timely indication of the therapy in the course of these diseases. Thanks to the good standardization of the DBS procedure and sufficient published data, the recommendations for indication, diagnosis and operative procedures can be generated. The following article attempts to summarize the most important decision-making criteria and current therapy standards in this fairly comprehensive subject and to present them in close proximity to practice. Georg Thieme Verlag KG Stuttgart · New York.

Deep brain stimulation in the bed nucleus of the stria terminalis and medial forebrain bundle in a patient with major depressive disorder and anorexia nervosa.

PubMed

Blomstedt, Patric; Naesström, Matilda; Bodlund, Owe

2017-05-01

Deep brain stimulation (DBS) may be considered in severe cases of therapy-refractory major depressive disorder (MDD). However, DBS for MDD is still an experimental therapy. Therefore, it should only be administered in clinical studies driven by multidisciplinary teams, including surgeons with substantial experience of DBS in the treatment of other conditions.

Integration of sparse electrophysiological measurements with preoperative MRI using 3D surface estimation in deep brain stimulation surgery

NASA Astrophysics Data System (ADS)

Husch, Andreas; Gemmar, Peter; Thunberg, Johan; Hertel, Frank

2017-03-01

Intraoperative microelectrode recordings (MER) have been used for several decades to guide neurosurgeons during the implantation of Deep Brain Stimulation (DBS) electrodes, especially when targeting the subthalamic nucleus (STN) to suppress the symptoms of Parkinson's Disease. The standard approach is to use an array of up to five MER electrodes in a fixed configuration. Interpretation of the recorded signals yields a spatially very sparse set of information about the morphology of the respective brain structures in the targeted area. However, no aid is currently available for surgeons to intraoperatively integrate this information with other data available on the patient's individual morphology (e.g. MR imaging data used for surgical planning). This integration might allow surgeons to better determine the most probable position of the electrodes within the target structure during surgery. This paper suggests a method for reconstructing a surface patch from the sparse MER dataset utilizing additional a priori knowledge about the geometrical configuration of the measurement electrodes. The conventional representation of MER measurements as intervals of target region/non-target region is therefore transformed into an equivalent boundary set representation, allowing ecient point-based calculations. Subsequently, the problem is to integrate the resulting patch with a preoperative model of the target structure, which can be formulated as registration problem minimizing a distance measure between the two surfaces. When restricting this registration procedure to translations, which is reasonable given certain geometric considerations, the problem can be solved globally by employing an exhaustive search with arbitrary precision in polynomial time. The proposed method is demonstrated using bilateral STN/Substantia Nigra segmentation data from preoperative MRIs of 17 Patients with simulated MER electrode placement. When using simulated data of heavily perturbed electrodes and subsequent MER measurements, our optimization resulted in an improvement of the electrode position within 1 mm of the ground truth in 80.29% of the cases.

Reliability of temperatures measured at standard monitoring sites as an index of brain temperature during deep hypothermic cardiopulmonary bypass conducted for thoracic aortic reconstruction.

PubMed

Akata, Takashi; Setoguchi, Hidekazu; Shirozu, Kazuhiro; Yoshino, Jun

2007-06-01

It is essential to estimate the brain temperature of patients during deliberate deep hypothermia. Using jugular bulb temperature as a standard for brain temperature, we evaluated the accuracy and precision of 5 standard temperature monitoring sites (ie, pulmonary artery, nasopharynx, forehead deep-tissue, urinary bladder, and fingertip skin-surface tissue) during deep hypothermic cardiopulmonary bypass conducted for thoracic aortic reconstruction. In 20 adult patients with thoracic aortic aneurysms, the 5 temperature monitoring sites were recorded every 1 minute during deep hypothermic (<20 degrees C) cardiopulmonary bypass. The accuracy was evaluated by the difference from jugular bulb temperature, and the precision was evaluated by its standard deviation, as well as by the correlation with jugular bulb temperature. Pulmonary artery temperature and jugular bulb temperature began to change immediately after the start of cooling or rewarming, closely matching each other, and the other temperatures lagged behind these two temperatures. During either situation, the accuracy of pulmonary artery temperature measurement (0.3 degrees C-0.5 degrees C) was much superior to the other measurements, and its precision (standard deviation of the difference from jugular bulb temperature = 1.5 degrees C-1.8 degrees C; correlation coefficient = 0.94-0.95) was also best among the measurements, with its rank order being pulmonary artery > or = nasopharynx > forehead > bladder > fingertip. However, the accuracy and precision of pulmonary artery temperature measurement was significantly impaired during and for several minutes after infusion of cold cardioplegic solution. Pulmonary artery temperature measurement is recommended to estimate brain temperature during deep hypothermic cardiopulmonary bypass, even if it is conducted with the sternum opened; however, caution needs to be exercised in interpreting its measurements during periods of the cardioplegic solution infusion.

Fiber-based tissue identification for electrode placement in deep brain stimulation neurosurgery (Conference Presentation)

NASA Astrophysics Data System (ADS)

DePaoli, Damon T.; Lapointe, Nicolas; Goetz, Laurent; Parent, Martin; Prudhomme, Michel; Cantin, Léo.; Galstian, Tigran; Messaddeq, Younès.; Côté, Daniel C.

2016-03-01

Deep brain stimulation's effectiveness relies on the ability of the stimulating electrode to be properly placed within a specific target area of the brain. Optical guidance techniques that can increase the accuracy of the procedure, without causing any additional harm, are therefore of great interest. We have designed a cheap optical fiber-based device that is small enough to be placed within commercially available DBS stimulating electrodes' hollow cores and that is capable of sensing biological information from the surrounding tissue, using low power white light. With this probe we have shown the ability to distinguish white and grey matter as well as blood vessels, in vitro, in human brain samples and in vivo, in rats. We have also repeated the in vitro procedure with the probe inserted in a DBS stimulating electrode and found the results were in good agreement. We are currently validating a second fiber optic device, with micro-optical components, that will result in label free, molecular level sensing capabilities, using CARS spectroscopy. The final objective will be to use this data in real time, during deep brain stimulation neurosurgery, to increase the safety and accuracy of the procedure.

Left temporal and temporoparietal brain activity depends on depth of word encoding: a magnetoencephalographic study in healthy young subjects.

PubMed

Walla, P; Hufnagl, B; Lindinger, G; Imhof, H; Deecke, L; Lang, W

2001-03-01

Using a 143-channel whole-head magnetoencephalograph (MEG) we recorded the temporal changes of brain activity from 26 healthy young subjects (14 females) related to shallow perceptual and deep semantic word encoding. During subsequent recognition tests, the subjects had to recognize the previously encoded words which were interspersed with new words. The resulting mean memory performances across all subjects clearly mirrored the different levels of encoding. The grand averaged event-related fields (ERFs) associated with perceptual and semantic word encoding differed significantly between 200 and 550 ms after stimulus onset mainly over left superior temporal and left superior parietal sensors. Semantic encoding elicited higher brain activity than perceptual encoding. Source localization procedures revealed that neural populations of the left temporal and temporoparietal brain areas showed different activity strengths across the whole group of subjects depending on depth of word encoding. We suggest that the higher brain activity associated with deep encoding as compared to shallow encoding was due to the involvement of more neural systems during the processing of visually presented words. Deep encoding required more energy than shallow encoding but for all that led to a better memory performance. Copyright 2001 Academic Press.

Comparative Methylome Analyses Identify Epigenetic Regulatory Loci of Human Brain Evolution

PubMed Central

Mendizabal, Isabel; Shi, Lei; Keller, Thomas E.; Konopka, Genevieve; Preuss, Todd M.; Hsieh, Tzung-Fu; Hu, Enzhi; Zhang, Zhe; Su, Bing; Yi, Soojin V.

2016-01-01

How do epigenetic modifications change across species and how do these modifications affect evolution? These are fundamental questions at the forefront of our evolutionary epigenomic understanding. Our previous work investigated human and chimpanzee brain methylomes, but it was limited by the lack of outgroup data which is critical for comparative (epi)genomic studies. Here, we compared whole genome DNA methylation maps from brains of humans, chimpanzees and also rhesus macaques (outgroup) to elucidate DNA methylation changes during human brain evolution. Moreover, we validated that our approach is highly robust by further examining 38 human-specific DMRs using targeted deep genomic and bisulfite sequencing in an independent panel of 37 individuals from five primate species. Our unbiased genome-scan identified human brain differentially methylated regions (DMRs), irrespective of their associations with annotated genes. Remarkably, over half of the newly identified DMRs locate in intergenic regions or gene bodies. Nevertheless, their regulatory potential is on par with those of promoter DMRs. An intriguing observation is that DMRs are enriched in active chromatin loops, suggesting human-specific evolutionary remodeling at a higher-order chromatin structure. These findings indicate that there is substantial reprogramming of epigenomic landscapes during human brain evolution involving noncoding regions. PMID:27563052

MRI-induced heating of deep brain stimulation leads

NASA Astrophysics Data System (ADS)

Mohsin, Syed A.; Sheikh, Noor M.; Saeed, Usman

2008-10-01

The radiofrequency (RF) field used in magnetic resonance imaging is scattered by medical implants. The scattered field of a deep brain stimulation lead can be very intense near the electrodes stimulating the brain. The effect is more pronounced if the lead behaves as a resonant antenna. In this paper, we examine the resonant length effect. We also use the finite element method to compute the near field for (i) the lead immersed in inhomogeneous tissue (fat, muscle, and brain tissues) and (ii) the lead connected to an implantable pulse generator. Electric field, specific absorption rate and induced temperature rise distributions have been obtained in the brain tissue surrounding the electrodes. The worst-case scenario has been evaluated by neglecting the effect of blood perfusion. The computed values are in good agreement with in vitro measurements made in the laboratory.

Design and optimization of an ultra wideband and compact microwave antenna for radiometric monitoring of brain temperature.

PubMed

Rodrigues, Dario B; Maccarini, Paolo F; Salahi, Sara; Oliveira, Tiago R; Pereira, Pedro J S; Limao-Vieira, Paulo; Snow, Brent W; Reudink, Doug; Stauffer, Paul R

2014-07-01

We present the modeling efforts on antenna design and frequency selection to monitor brain temperature during prolonged surgery using noninvasive microwave radiometry. A tapered log-spiral antenna design is chosen for its wideband characteristics that allow higher power collection from deep brain. Parametric analysis with the software HFSS is used to optimize antenna performance for deep brain temperature sensing. Radiometric antenna efficiency (η) is evaluated in terms of the ratio of power collected from brain to total power received by the antenna. Anatomical information extracted from several adult computed tomography scans is used to establish design parameters for constructing an accurate layered 3-D tissue phantom. This head phantom includes separate brain and scalp regions, with tissue equivalent liquids circulating at independent temperatures on either side of an intact skull. The optimized frequency band is 1.1-1.6 GHz producing an average antenna efficiency of 50.3% from a two turn log-spiral antenna. The entire sensor package is contained in a lightweight and low-profile 2.8 cm diameter by 1.5 cm high assembly that can be held in place over the skin with an electromagnetic interference shielding adhesive patch. The calculated radiometric equivalent brain temperature tracks within 0.4 °C of the measured brain phantom temperature when the brain phantom is lowered 10 °C and then returned to the original temperature (37 °C) over a 4.6-h experiment. The numerical and experimental results demonstrate that the optimized 2.5-cm log-spiral antenna is well suited for the noninvasive radiometric sensing of deep brain temperature.

Deep two-photon microscopic imaging through brain tissue using the second singlet state from fluorescent agent chlorophyll α in spinach leaf

NASA Astrophysics Data System (ADS)

Shi, Lingyan; Rodríguez-Contreras, Adrián; Budansky, Yury; Pu, Yang; An Nguyen, Thien; Alfano, Robert R.

2014-06-01

Two-photon (2P) excitation of the second singlet (S) state was studied to achieve deep optical microscopic imaging in brain tissue when both the excitation (800 nm) and emission (685 nm) wavelengths lie in the "tissue optical window" (650 to 950 nm). S2 state technique was used to investigate chlorophyll α (Chl α) fluorescence inside a spinach leaf under a thick layer of freshly sliced rat brain tissue in combination with 2P microscopic imaging. Strong emission at the peak wavelength of 685 nm under the 2P S state of Chl α enabled the imaging depth up to 450 μm through rat brain tissue.

Deep two-photon microscopic imaging through brain tissue using the second singlet state from fluorescent agent chlorophyll α in spinach leaf.

PubMed

Shi, Lingyan; Rodríguez-Contreras, Adrián; Budansky, Yury; Pu, Yang; Nguyen, Thien An; Alfano, Robert R

2014-06-01

Two-photon (2P) excitation of the second singlet (S₂) state was studied to achieve deep optical microscopic imaging in brain tissue when both the excitation (800 nm) and emission (685 nm) wavelengths lie in the "tissue optical window" (650 to 950 nm). S₂ state technique was used to investigate chlorophyll α (Chl α) fluorescence inside a spinach leaf under a thick layer of freshly sliced rat brain tissue in combination with 2P microscopic imaging. Strong emission at the peak wavelength of 685 nm under the 2P S₂ state of Chl α enabled the imaging depth up to 450 μm through rat brain tissue.

Volumetric Radiosurgery for 1 to 10 Brain Metastases: A Multicenter, Single-Arm, Phase 2 Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nichol, Alan, E-mail: anichol@bccancer.bc.ca; University of British Columbia, Vancouver, British Columbia; Ma, Roy

Purpose: Interest is growing in treating multiple brain metastases with radiosurgery. We report on the effectiveness and tolerability of volumetric radiosurgery (VRS). Methods and Materials: We enrolled patients with a ≥6-month estimated life expectancy and 1 to 10 brain metastases with a diameter of ≤3 cm at 5 cancer centers. Volumetric radiosurgery was delivered in 5 fractions with 98% target coverage, prescribed as 95% of 50 Gy (47.5 Gy in 5 fractions) to the metastases with no margin and 95% of 40 Gy (38 Gy in 5 fractions) to their 2-mm planning target volumes, concurrent with 20 Gy to the whole brain planning target volume. The treatmentmore » was delivered with daily image guidance using conventional linear accelerators and volumetric modulated arc therapy. A magnetic resonance imaging scan was obtained every 3 months. The primary endpoint was the 3-month objective response in the brain according to the Response Evaluation Criteria in Solid Tumors, version 1.1. The principal secondary endpoint was 1-year actuarial control of treated metastases. Toxicities were graded using the Common Terminology Criteria for Adverse Events, version 4.0. The present study is registered with (ClinicalTrials.gov) ( (clinicaltrials.gov) identifier (NCT01046123)). Results: From July 2010 to May 2013, 60 patients underwent VRS with 47.5 Gy in 5 fractions for 12 metastases in the thalamus and basal ganglia (deep metastases) and 207 non-deep metastases. The median follow-up period was 30.5 months, and the median survival was 10.1 months. For the 43 patients assessable at 3 months, the objective response in the brain was 56%. The treated metastases were controlled in 88% of patients at 1 year and 84% at 3 years. Overall survival did not differ for patients with 4 to 10 versus 1 to 3 metastases (hazard ratio 1.18, P=.6). The crude incidence of severe radionecrosis (grade 3-5) was 25% (3 of 12) per deep metastasis, 1.9% (4 of 219) per non-deep metastasis, and 10% (6 of 60) per patient. Conclusions: For non-deep brain metastases, 47.5 Gy in 5 fractions was tolerable. Volumetric radiosurgery was effective for long-term control of treated brain metastases.« less

Optical clearing of the eye using the See Deep Brain technique.

PubMed

Hohberger, B; Baumgart, C; Bergua, A

2017-10-01

PurposeTissue clearing has been used in anatomy for the first time in Germany over a century ago. Neuronal tissue, like cortex, was investigated in mice using a water-based optical clearing method termed See Deep Brain (SeeDB). However, although the eye belongs to the central nervous system, this histological technique was not applied in the eye up to date. We applied SeeDB for the visualization of intraocular structures.Patients and methodsFour eyes of cornea donors (two male, two female: 73-84 years) obtained from the Cornea Bank of the Department of Ophthalmology Erlangen, four chicken eyes and two mices' optic nerve were used. Bulbi were fixed in 4% paraformaldehyde in phosphate-buffered saline and treated with increasing concentrations of aqueous fructose solution with 0.5% α-thioglycerol. After SeeDB, transscleral macrophotographs of the choroid were performed.ResultsComplete transparency of the sclera was obtained in enucleated human and chicken eyes after SeeDB treatment. Macroscopical anatomy of the choroid (partially transparent due to the remaining retinal pigment epithelium and melanocytes) showing vessels and other related structures was possible without preparing slides. Mice optic nerves were also transparent after SeeDB treatment.ConclusionThe SeeDB method allows visualization of intraocular structures through a completely translucent sclera. This innovative processing technique could facilitate comprehensive qualitative and quantitative topographical anatomical studies of human and animal eyes, preserving their 3D architecture. Supra- and intrachoroidal ganglionic plexus could potentially be visualized transsclerally. Finally, clinical-pathological correlations of intraocular diseases-for example, retinal tumors-will be possible in non-dissected eyes.

Characterization of oscillatory changes in hippocampus and amygdala after deep brain stimulation of the infralimbic prefrontal cortex.

PubMed

Cervera-Ferri, Ana; Teruel-Martí, Vicent; Barceló-Molina, Moises; Martínez-Ricós, Joana; Luque-García, Aina; Martínez-Bellver, Sergio; Adell, Albert

2016-07-01

Deep brain stimulation (DBS) is a new investigational therapy that has generated positive results in refractory depression. Although the neurochemical and behavioral effects of DBS have been examined, less attention has been paid to the influence of DBS on the network dynamics between different brain areas, which could contribute to its therapeutic effects. Herein, we set out to identify the effects of 1 h DBS in the infralimbic cortex (IL) on the oscillatory network dynamics between hippocampus and basolateral amygdala (BLA), two regions implicated in depression and its treatment. Urethane-anesthetized rats with bilaterally implanted electrodes in the IL were exposed to 1 h constant stimulation of 130 Hz of frequency, 60 μA of constant current intensity and biphasic pulse width of 80 μsec. After a period of baseline recording, local field potentials (LFP) were recorded with formvar-insulated stainless steel electrodes. DBS of the IL increased the power of slow wave (SW, <1.5 Hz) and theta (3-12 Hz) frequencies in the hippocampus and BLA Furthermore, IL DBS caused a precise coupling in different frequency bands between both brain structures. The increases in SW band synchronization in hippocampus and BLA after DBS suggest that these changes may be important for the improvement of depressive behavior. In addition, the augmentation in theta synchrony might contribute to improvement in emotional and cognitive processes. © 2016 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of the American Physiological Society and The Physiological Society.

Graph Theoretical Analysis Reveals: Women's Brains Are Better Connected than Men's.

PubMed

Szalkai, Balázs; Varga, Bálint; Grolmusz, Vince

2015-01-01

Deep graph-theoretic ideas in the context with the graph of the World Wide Web led to the definition of Google's PageRank and the subsequent rise of the most popular search engine to date. Brain graphs, or connectomes, are being widely explored today. We believe that non-trivial graph theoretic concepts, similarly as it happened in the case of the World Wide Web, will lead to discoveries enlightening the structural and also the functional details of the animal and human brains. When scientists examine large networks of tens or hundreds of millions of vertices, only fast algorithms can be applied because of the size constraints. In the case of diffusion MRI-based structural human brain imaging, the effective vertex number of the connectomes, or brain graphs derived from the data is on the scale of several hundred today. That size facilitates applying strict mathematical graph algorithms even for some hard-to-compute (or NP-hard) quantities like vertex cover or balanced minimum cut. In the present work we have examined brain graphs, computed from the data of the Human Connectome Project, recorded from male and female subjects between ages 22 and 35. Significant differences were found between the male and female structural brain graphs: we show that the average female connectome has more edges, is a better expander graph, has larger minimal bisection width, and has more spanning trees than the average male connectome. Since the average female brain weighs less than the brain of males, these properties show that the female brain has better graph theoretical properties, in a sense, than the brain of males. It is known that the female brain has a smaller gray matter/white matter ratio than males, that is, a larger white matter/gray matter ratio than the brain of males; this observation is in line with our findings concerning the number of edges, since the white matter consists of myelinated axons, which, in turn, roughly correspond to the connections in the brain graph. We have also found that the minimum bisection width, normalized with the edge number, is also significantly larger in the right and the left hemispheres in females: therefore, the differing bisection widths are independent from the difference in the number of edges.

Graph Theoretical Analysis Reveals: Women’s Brains Are Better Connected than Men’s

PubMed Central

Szalkai, Balázs; Varga, Bálint; Grolmusz, Vince

2015-01-01

Deep graph-theoretic ideas in the context with the graph of the World Wide Web led to the definition of Google’s PageRank and the subsequent rise of the most popular search engine to date. Brain graphs, or connectomes, are being widely explored today. We believe that non-trivial graph theoretic concepts, similarly as it happened in the case of the World Wide Web, will lead to discoveries enlightening the structural and also the functional details of the animal and human brains. When scientists examine large networks of tens or hundreds of millions of vertices, only fast algorithms can be applied because of the size constraints. In the case of diffusion MRI-based structural human brain imaging, the effective vertex number of the connectomes, or brain graphs derived from the data is on the scale of several hundred today. That size facilitates applying strict mathematical graph algorithms even for some hard-to-compute (or NP-hard) quantities like vertex cover or balanced minimum cut. In the present work we have examined brain graphs, computed from the data of the Human Connectome Project, recorded from male and female subjects between ages 22 and 35. Significant differences were found between the male and female structural brain graphs: we show that the average female connectome has more edges, is a better expander graph, has larger minimal bisection width, and has more spanning trees than the average male connectome. Since the average female brain weighs less than the brain of males, these properties show that the female brain has better graph theoretical properties, in a sense, than the brain of males. It is known that the female brain has a smaller gray matter/white matter ratio than males, that is, a larger white matter/gray matter ratio than the brain of males; this observation is in line with our findings concerning the number of edges, since the white matter consists of myelinated axons, which, in turn, roughly correspond to the connections in the brain graph. We have also found that the minimum bisection width, normalized with the edge number, is also significantly larger in the right and the left hemispheres in females: therefore, the differing bisection widths are independent from the difference in the number of edges. PMID:26132764

Glioblastoma recurrence correlates with NLGN3 levels.

PubMed

Liu, Rui; Qin, Xing-Ping; Zhuang, Yang; Zhang, Ya; Liao, Hua-Bao; Tang, Jun-Chun; Pan, Meng-Xian; Zeng, Fei-Fei; Lei, Yang; Lei, Rui-Xue; Wang, Shu; Liu, An-Chun; Chen, Juan; Zhang, Zhi-Feng; Zhao, Dan; Wu, Song-Lin; Liu, Ren-Zhong; Wang, Ze-Fen; Wan, Qi

2018-05-18

Glioblastoma (GBM) is the most aggressive glioma in the brain. Recurrence of GBM is almost inevitable within a short term after tumor resection. In a retrospective study of 386 cases of GBM collected between 2013 and 2016, we found that recurrence of GBM mainly occurs in the deep brain regions, including the basal ganglia, thalamus, and corpus callosum. But the mechanism underlying this phenomenon is not clear. Previous studies suggest that neuroligin-3 (NLGN3) is necessary for GBM growth. Our results show that the levels of NLGN3 in the cortex are higher than those in the deep regions in a normal human brain, and similar patterns are also found in a normal mouse brain. In contrast, NLGN3 levels in the deep brain regions of GBM patients are high. We also show that an increase in NLGN3 concentration promotes the growth of U251 cells and U87-MG cells. Respective use of the cortex neuron culture medium (C-NCM) and basal ganglia neuron culture medium (BG-NCM) with DMEM to cultivate U251, U87-MG and GBM cells isolated from patients, we found that these cells grew faster after treatment with C-NCM and BG-NCM in which the cells treated with C-NCM grew faster than the ones treated with BG-NCM group. Inhibition of NLGN3 release by ADAM10i prevents NCM-induced cell growth. Together, this study suggests that increased levels of NLGN3 in the deep brain region under the GBM pathological circumstances may contribute to GBM recurrence in the basal ganglia, thalamus, and corpus callosum. © 2018 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Technical nuances to minimize common complications of deep brain stimulation.

PubMed

House, Paul

2017-04-01

The implantation of deep brain stimulator electrodes is associated with infrequent complications. These complications are consistent across prospective trials and include infection, skin erosion, hemorrhage, and lead misplacement. Nuances of surgical technique can be used to minimize the risk of these commonly noted complications. Several of these technical nuances are highlighted in this video submission. The video can be found here: https://youtu.be/GL09W9p013g .

Confocal multispot microscope for fast and deep imaging in semicleared tissues

NASA Astrophysics Data System (ADS)

Adam, Marie-Pierre; Müllenbroich, Marie Caroline; Di Giovanna, Antonino Paolo; Alfieri, Domenico; Silvestri, Ludovico; Sacconi, Leonardo; Pavone, Francesco Saverio

2018-02-01

Although perfectly transparent specimens are imaged faster with light-sheet microscopy, less transparent samples are often imaged with two-photon microscopy leveraging its robustness to scattering; however, at the price of increased acquisition times. Clearing methods that are capable of rendering strongly scattering samples such as brain tissue perfectly transparent specimens are often complex, costly, and time intensive, even though for many applications a slightly lower level of tissue transparency is sufficient and easily achieved with simpler and faster methods. Here, we present a microscope type that has been geared toward the imaging of semicleared tissue by combining multispot two-photon excitation with rolling shutter wide-field detection to image deep and fast inside semicleared mouse brain. We present a theoretical and experimental evaluation of the point spread function and contrast as a function of shutter size. Finally, we demonstrate microscope performance in fixed brain slices by imaging dendritic spines up to 400-μm deep.

Brain Tumor Segmentation Using Deep Belief Networks and Pathological Knowledge.

PubMed

Zhan, Tianming; Chen, Yi; Hong, Xunning; Lu, Zhenyu; Chen, Yunjie

2017-01-01

In this paper, we propose an automatic brain tumor segmentation method based on Deep Belief Networks (DBNs) and pathological knowledge. The proposed method is targeted against gliomas (both low and high grade) obtained in multi-sequence magnetic resonance images (MRIs). Firstly, a novel deep architecture is proposed to combine the multi-sequences intensities feature extraction with classification to get the classification probabilities of each voxel. Then, graph cut based optimization is executed on the classification probabilities to strengthen the spatial relationships of voxels. At last, pathological knowledge of gliomas is applied to remove some false positives. Our method was validated in the Brain Tumor Segmentation Challenge 2012 and 2013 databases (BRATS 2012, 2013). The performance of segmentation results demonstrates our proposal providing a competitive solution with stateof- the-art methods. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Cognitive assessment instruments in Parkinson's disease patients undergoing deep brain stimulation

PubMed Central

Romann, Aline Juliane; Dornelles, Silvia; Maineri, Nicole de Liz; Rieder, Carlos Roberto de Mello; Olchik, Maira Rozenfeld

2012-01-01

Deep Brain Stimulation (DBS) is a widely used surgical technique in individuals with Parkinson's disease (PD) that can lead to significant reductions in motor symptoms. Objectives To determine, from publications, the most commonly used instruments for cognitive evaluation of individuals with PD undergoing DBS. Methods A systematic review of the databases: PubMed, Medline, EBECS, Scielo and LILACS was conducted, using the descriptors "Deep Brain Stimulation", "Verbal Fluency", "Parkinson Disease", "Executive Function", "Cognition" and "Cognitive Assessment" in combination. Results The Verbal Fluency test was found to be the most used instrument for this investigation in the studies, followed by the Boston Naming Test. References to the Stroop Test, Trail Making Test, and Rey's Auditory Verbal Learning Test were also found. Conclusions The validation of instruments for this population is needed as is the use of batteries offering greater specificity and sensitivity for the detection of cognitive impairment. PMID:29213766

A PC-based system for predicting movement from deep brain signals in Parkinson's disease.

PubMed

Loukas, Constantinos; Brown, Peter

2012-07-01

There is much current interest in deep brain stimulation (DBS) of the subthalamic nucleus (STN) for the treatment of Parkinson's disease (PD). This type of surgery has enabled unprecedented access to deep brain signals in the awake human. In this paper we present an easy-to-use computer based system for recording, displaying, archiving, and processing electrophysiological signals from the STN. The system was developed for predicting self-paced hand-movements in real-time via the online processing of the electrophysiological activity of the STN. It is hoped that such a computerised system might have clinical and experimental applications. For example, those sites within the STN most relevant to the processing of voluntary movement could be identified through the predictive value of their activities with respect to the timing of future movement. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Automated deep-phenotyping of the vertebrate brain

PubMed Central

Allalou, Amin; Wu, Yuelong; Ghannad-Rezaie, Mostafa; Eimon, Peter M; Yanik, Mehmet Fatih

2017-01-01

Here, we describe an automated platform suitable for large-scale deep-phenotyping of zebrafish mutant lines, which uses optical projection tomography to rapidly image brain-specific gene expression patterns in 3D at cellular resolution. Registration algorithms and correlation analysis are then used to compare 3D expression patterns, to automatically detect all statistically significant alterations in mutants, and to map them onto a brain atlas. Automated deep-phenotyping of a mutation in the master transcriptional regulator fezf2 not only detects all known phenotypes but also uncovers important novel neural deficits that were overlooked in previous studies. In the telencephalon, we show for the first time that fezf2 mutant zebrafish have significant patterning deficits, particularly in glutamatergic populations. Our findings reveal unexpected parallels between fezf2 function in zebrafish and mice, where mutations cause deficits in glutamatergic neurons of the telencephalon-derived neocortex. DOI: http://dx.doi.org/10.7554/eLife.23379.001 PMID:28406399

Effects of One Year of Spaceflight on Neurocognitive Function

NASA Technical Reports Server (NTRS)

Seidler, R. D.; Mulavara, A. P.; Koppelmans, V.; Kofman, I. S.; Cassady, K.; Yuan , P.; De Dios, Y. E.; Gadd, N.; Riascos, R. F.; Wood, S. J.;

Shielded battery syndrome: a new hardware complication of deep brain stimulation.

PubMed

Chelvarajah, Ramesh; Lumsden, Daniel; Kaminska, Margaret; Samuel, Michael; Hulse, Natasha; Selway, Richard P; Lin, Jean-Pierre; Ashkan, Keyoumars

2012-01-01

Deep brain stimulation hardware is constantly advancing. The last few years have seen the introduction of rechargeable cell technology into the implanted pulse generator design, allowing for longer battery life and fewer replacement operations. The Medtronic® system requires an additional pocket adaptor when revising a non-rechargeable battery such as their Kinetra® to their rechargeable Activa® RC. This additional hardware item can, if it migrates superficially, become an impediment to the recharging of the battery and negate the intended technological advance. To report the emergence of the 'shielded battery syndrome', which has not been previously described. We reviewed our deep brain stimulation database to identify cases of recharging difficulties reported by patients with Activa RC implanted pulse generators. Two cases of shielded battery syndrome were identified. The first required surgery to reposition the adaptor to the deep aspect of the subcutaneous pocket. In the second case, it was possible to perform external manual manipulation to restore the adaptor to its original position deep to the battery. We describe strategies to minimise the occurrence of the shielded battery syndrome and advise vigilance in all patients who experience difficulty with recharging after replacement surgery of this type for the implanted pulse generator. Copyright © 2012 S. Karger AG, Basel.

Targeting the brain: considerations in 332 consecutive patients treated by deep brain stimulation (DBS) for severe neurological diseases.

PubMed

Franzini, Angelo; Cordella, Roberto; Messina, Giuseppe; Marras, Carlo Efisio; Romito, Luigi Michele; Albanese, Alberto; Rizzi, Michele; Nardocci, Nardo; Zorzi, Giovanna; Zekaj, Edvin; Villani, Flavio; Leone, Massimo; Gambini, Orsola; Broggi, Giovanni

2012-12-01

Deep brain stimulation (DBS) extends the treatment of some severe neurological diseases beyond pharmacological and conservative therapy. Our experience extends the field of DBS beyond the treatment of Parkinson disease and dystonia, including several other diseases such as cluster headache and disruptive behavior. Since 1993, at the Istituto Nazionale Neurologico "Carlo Besta" in Milan, 580 deep brain electrodes were implanted in 332 patients. The DBS targets include Stn, GPi, Voa, Vop, Vim, CM-pf, pHyp, cZi, Nacc, IC, PPN, and Brodmann areas 24 and 25. Three hundred patients are still available for follow-up and therapeutic considerations. DBS gave a new therapeutic chance to these patients affected by severe neurological diseases and in some cases controlled life-threatening pathological conditions, which would otherwise result in the death of the patient such as in status dystonicus, status epilepticus and post-stroke hemiballismus. The balance of DBS in severe neurological disease is strongly positive even if further investigations and studies are needed to search for new applications and refine the selection criteria for the actual indications.

Deep brain stimulation mechanisms: beyond the concept of local functional inhibition.

PubMed

Deniau, Jean-Michel; Degos, Bertrand; Bosch, Clémentine; Maurice, Nicolas

2010-10-01

Deep brain electrical stimulation has become a recognized therapy in the treatment of a variety of motor disorders and has potentially promising applications in a wide range of neurological diseases including neuropsychiatry. Behavioural observation that electrical high-frequency stimulation of a given brain area induces an effect similar to a lesion suggested a mechanism of functional inhibition. In vitro and in vivo experiments as well as per operative recordings in patients have revealed a variety of effects involving local changes of neuronal excitability as well as widespread effects throughout the connected network resulting from activation of axons, including antidromic activation. Here we review current data regarding the local and network activity changes induced by high-frequency stimulation of the subthalamic nucleus and discuss this in the context of motor restoration in Parkinson's disease. Stressing the important functional consequences of axonal activation in deep brain stimulation mechanisms, we highlight the importance of developing anatomical knowledge concerning the fibre connections of the putative therapeutic targets. © 2010 The Authors. European Journal of Neuroscience © 2010 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Deep learning with convolutional neural networks for EEG decoding and visualization.

PubMed

Schirrmeister, Robin Tibor; Springenberg, Jost Tobias; Fiederer, Lukas Dominique Josef; Glasstetter, Martin; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank; Burgard, Wolfram; Ball, Tonio

2017-11-01

Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end-to-end learning, that is, learning from the raw data. There is increasing interest in using deep ConvNets for end-to-end EEG analysis, but a better understanding of how to design and train ConvNets for end-to-end EEG decoding and how to visualize the informative EEG features the ConvNets learn is still needed. Here, we studied deep ConvNets with a range of different architectures, designed for decoding imagined or executed tasks from raw EEG. Our results show that recent advances from the machine learning field, including batch normalization and exponential linear units, together with a cropped training strategy, boosted the deep ConvNets decoding performance, reaching at least as good performance as the widely used filter bank common spatial patterns (FBCSP) algorithm (mean decoding accuracies 82.1% FBCSP, 84.0% deep ConvNets). While FBCSP is designed to use spectral power modulations, the features used by ConvNets are not fixed a priori. Our novel methods for visualizing the learned features demonstrated that ConvNets indeed learned to use spectral power modulations in the alpha, beta, and high gamma frequencies, and proved useful for spatially mapping the learned features by revealing the topography of the causal contributions of features in different frequency bands to the decoding decision. Our study thus shows how to design and train ConvNets to decode task-related information from the raw EEG without handcrafted features and highlights the potential of deep ConvNets combined with advanced visualization techniques for EEG-based brain mapping. Hum Brain Mapp 38:5391-5420, 2017. © 2017 Wiley Periodicals, Inc. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Multimodal Approaches to Define Network Oscillations in Depression

PubMed Central

Smart, Otis Lkuwamy; Tiruvadi, Vineet Ravi; Mayberg, Helen S.

2018-01-01

The renaissance in the use of encephalography-based research methods to probe the pathophysiology of neuropsychiatric disorders is well afoot and continues to advance. Building on the platform of neuroimaging evidence on brain circuit models, magnetoencephalography, scalp electroencephalography, and even invasive electroencephalography are now being used to characterize brain network dysfunctions that underlie major depressive disorder using brain oscillation measurements and associated treatment responses. Such multiple encephalography modalities provide avenues to study pathologic network dynamics with high temporal resolution and over long time courses, opportunities to complement neuroimaging methods and findings, and new approaches to identify quantitative biomarkers that indicate critical targets for brain therapy. Such goals have been facilitated by the ongoing testing of novel invasive neuromodulation therapies, notably, deep brain stimulation, where clinically relevant treatment effects can be monitored at multiple brain sites in a time-locked causal manner. We review key brain rhythms identified in major depressive disorder as foundation for development of putative biomarkers for objectively evaluating neuromodulation success and for guiding deep brain stimulation or other target-based neuromodulation strategies for treatment-resistant depression patients. PMID:25681871

Automatic Semantic Segmentation of Brain Gliomas from MRI Images Using a Deep Cascaded Neural Network

PubMed Central

Mao, Lei; Liu, Chang; Xiong, Shuyu

2018-01-01

Brain tumors can appear anywhere in the brain and have vastly different sizes and morphology. Additionally, these tumors are often diffused and poorly contrasted. Consequently, the segmentation of brain tumor and intratumor subregions using magnetic resonance imaging (MRI) data with minimal human interventions remains a challenging task. In this paper, we present a novel fully automatic segmentation method from MRI data containing in vivo brain gliomas. This approach can not only localize the entire tumor region but can also accurately segment the intratumor structure. The proposed work was based on a cascaded deep learning convolutional neural network consisting of two subnetworks: (1) a tumor localization network (TLN) and (2) an intratumor classification network (ITCN). The TLN, a fully convolutional network (FCN) in conjunction with the transfer learning technology, was used to first process MRI data. The goal of the first subnetwork was to define the tumor region from an MRI slice. Then, the ITCN was used to label the defined tumor region into multiple subregions. Particularly, ITCN exploited a convolutional neural network (CNN) with deeper architecture and smaller kernel. The proposed approach was validated on multimodal brain tumor segmentation (BRATS 2015) datasets, which contain 220 high-grade glioma (HGG) and 54 low-grade glioma (LGG) cases. Dice similarity coefficient (DSC), positive predictive value (PPV), and sensitivity were used as evaluation metrics. Our experimental results indicated that our method could obtain the promising segmentation results and had a faster segmentation speed. More specifically, the proposed method obtained comparable and overall better DSC values (0.89, 0.77, and 0.80) on the combined (HGG + LGG) testing set, as compared to other methods reported in the literature. Additionally, the proposed approach was able to complete a segmentation task at a rate of 1.54 seconds per slice. PMID:29755716

Single Subject Prediction of Brain Disorders in Neuroimaging: Promises and Pitfalls

PubMed Central

Arbabshirani, Mohammad R.; Plis, Sergey; Sui, Jing; Calhoun, Vince D.

2016-01-01

Neuroimaging-based single subject prediction of brain disorders has gained increasing attention in recent years. Using a variety of neuroimaging modalities such as structural, functional and diffusion MRI, along with machine learning techniques, hundreds of studies have been carried out for accurate classification of patients with heterogeneous mental and neurodegenerative disorders such as schizophrenia and Alzheimer's disease. More than 500 studies have been published during the past quarter century on single subject prediction focused on a multiple brain disorders. In the first part of this study, we provide a survey of more than 200 reports in this field with a focus on schizophrenia, mild cognitive impairment (MCI), Alzheimer's disease (AD), depressive disorders, autism spectrum disease (ASD) and attention-deficit hyperactivity disorder (ADHD). Detailed information about those studies such as sample size, type and number of extracted features and reported accuracy are summarized and discussed. To our knowledge, this is by far the most comprehensive review of neuroimaging-based single subject prediction of brain disorders. In the second part, we present our opinion on major pitfalls of those studies from a machine learning point of view. Common biases are discussed and suggestions are provided. Moreover, emerging trends such as decentralized data sharing, multimodal brain imaging, differential diagnosis, disease subtype classification and deep learning are also discussed. Based on this survey, there are extensive evidences showing the great potential of neuroimaging data for single subject prediction of various disorders. However, the main bottleneck of this exciting field is still the limited sample size, which could be potentially addressed by modern data sharing models such as the ones discussed in this paper. Emerging big data technologies and advanced data-intensive machine learning methodologies such as deep learning have coincided with an increasing need for accurate, robust and generalizable single subject prediction of brain disorders during an exciting time. In this report, we survey the past and offer some opinions regarding the road ahead. PMID:27012503

Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls.

PubMed

Arbabshirani, Mohammad R; Plis, Sergey; Sui, Jing; Calhoun, Vince D

2017-01-15

Neuroimaging-based single subject prediction of brain disorders has gained increasing attention in recent years. Using a variety of neuroimaging modalities such as structural, functional and diffusion MRI, along with machine learning techniques, hundreds of studies have been carried out for accurate classification of patients with heterogeneous mental and neurodegenerative disorders such as schizophrenia and Alzheimer's disease. More than 500 studies have been published during the past quarter century on single subject prediction focused on a multiple brain disorders. In the first part of this study, we provide a survey of more than 200 reports in this field with a focus on schizophrenia, mild cognitive impairment (MCI), Alzheimer's disease (AD), depressive disorders, autism spectrum disease (ASD) and attention-deficit hyperactivity disorder (ADHD). Detailed information about those studies such as sample size, type and number of extracted features and reported accuracy are summarized and discussed. To our knowledge, this is by far the most comprehensive review of neuroimaging-based single subject prediction of brain disorders. In the second part, we present our opinion on major pitfalls of those studies from a machine learning point of view. Common biases are discussed and suggestions are provided. Moreover, emerging trends such as decentralized data sharing, multimodal brain imaging, differential diagnosis, disease subtype classification and deep learning are also discussed. Based on this survey, there is extensive evidence showing the great potential of neuroimaging data for single subject prediction of various disorders. However, the main bottleneck of this exciting field is still the limited sample size, which could be potentially addressed by modern data sharing models such as the ones discussed in this paper. Emerging big data technologies and advanced data-intensive machine learning methodologies such as deep learning have coincided with an increasing need for accurate, robust and generalizable single subject prediction of brain disorders during an exciting time. In this report, we survey the past and offer some opinions regarding the road ahead. Copyright © 2016 Elsevier Inc. All rights reserved.

Deep learning predictions of survival based on MRI in amyotrophic lateral sclerosis.

PubMed

van der Burgh, Hannelore K; Schmidt, Ruben; Westeneng, Henk-Jan; de Reus, Marcel A; van den Berg, Leonard H; van den Heuvel, Martijn P

2017-01-01

Amyotrophic lateral sclerosis (ALS) is a progressive neuromuscular disease, with large variation in survival between patients. Currently, it remains rather difficult to predict survival based on clinical parameters alone. Here, we set out to use clinical characteristics in combination with MRI data to predict survival of ALS patients using deep learning, a machine learning technique highly effective in a broad range of big-data analyses. A group of 135 ALS patients was included from whom high-resolution diffusion-weighted and T1-weighted images were acquired at the first visit to the outpatient clinic. Next, each of the patients was monitored carefully and survival time to death was recorded. Patients were labeled as short, medium or long survivors, based on their recorded time to death as measured from the time of disease onset. In the deep learning procedure, the total group of 135 patients was split into a training set for deep learning (n = 83 patients), a validation set (n = 20) and an independent evaluation set (n = 32) to evaluate the performance of the obtained deep learning networks. Deep learning based on clinical characteristics predicted survival category correctly in 68.8% of the cases. Deep learning based on MRI predicted 62.5% correctly using structural connectivity and 62.5% using brain morphology data. Notably, when we combined the three sources of information, deep learning prediction accuracy increased to 84.4%. Taken together, our findings show the added value of MRI with respect to predicting survival in ALS, demonstrating the advantage of deep learning in disease prognostication.

Subthalamic stimulation differentially modulates declarative and nondeclarative memory.

PubMed

Hälbig, Thomas D; Gruber, Doreen; Kopp, Ute A; Scherer, Peter; Schneider, Gerd-Helge; Trottenberg, Thomas; Arnold, Guy; Kupsch, Andreas

2004-03-01

Declarative memory has been reported to rely on the medial temporal lobe system, whereas non-declarative memory depends on basal ganglia structures. We investigated the functional role of the subthalamic nucleus (STN), a structure closely connected with the basal ganglia for both types of memory. Via deep brain high frequency stimulation (DBS) we manipulated neural activity of the STN in humans. We found that DBS-STN differentially modulated memory performance: declarative memory was impaired, whereas non-declarative memory was improved in the presence of STN-DBS indicating a specific role of the STN in the activation of memory systems. Copyright 2004 Lippincott Williams & Wilkins

[Stereotactic biopsy in the accurate diagnosis of lesions in the brain stem and deep brain].

PubMed

Qin, F; Huang, Z C; Cai, M Q; Xu, X F; Lu, T T; Dong, Q; Wu, A M; Lu, Z Z; Zhao, C; Guo, Y

2018-06-12

Objective: To investigate the value of stereotactic biopsy in the accurate diagnosis of lesions in the brain stem and deep brain. Methods: A total of 29 consecutive patients who underwent stereotactic biopsy of brainstem and deep brain lesions between May 2012 and January 2018 were retrospectively reviewed. The Cosman-Roberts-Wells (CRW) stereotactic frame was installed under local anesthesia. Thin-layer CT and MRI scanning were performed. Target coordinates were calculated by inputting CT-MRI data into the radionics surgical planning system. The individualized puncture path was designed according to the location of the lesions and the characteristics of the image. Target distributions were as follows: 12 cases of midbrain or pons, 2 cases of internal capsule, 3 cases of thalamus, 12 cases of basal ganglia. The biopsy samples were used for further pathological and/or genetic diagnosis. Results: Twenty-eight of the 29 cases (96.6%) were diagnosed accurately by histopathology and genomic examination following stereotactic biopsy. Pathological results were as follows: 8 cases of lymphoma, 7 cases of glioma, 4 cases of demyelination, 2 cases of germ cell tumor, 2 cases of metastatic tumor, 1 cases of cerebral sparganosis, 1 case of tuberculous granuloma, 1 case of hereditary prion disease, 1 case of glial hyperplasia, 1 case of leukemia. The accurate diagnosis of one case required a combination of histopathology and genomic examination. Undefined diagnosis was still made in 1 cases (3.45%) after biopsy. After biopsy, there were 2 cases (6.9%) with symptomatic slight hemorrhage, 1 case (3.45%) with symptomatic severe hemorrhage, and 1 cass (3.45%) with permanent neurological dysfunction. No one died because of surgery or surgical complications. Conclusions: Stereotactic biopsy is fast, safe and minimally invasive. It is an ideal strategy for accurate diagnosis of lesions in brain stem and deep brain.

Treatment of Pain and Autonomic Dysreflexia in Spinal Cord Injury with Deep Brain Stimulation

DTIC Science & Technology

2015-10-01

currently investigating the effects of CG stimulation in subjects with debilitating pain due to cervical or thoracic SCI. This study stemmed from...had a low thoracic injury and pain in lumbar dermatomes, whereas Subject 1 had mainly mid- cervical pain that responded minimally to DBS and matched...AWARD NUMBER: W81XWH-12-1-0559 TITLE: Treatment of Pain and Autonomic Dysreflexia in Spinal Cord Injury with Deep Brain Stimulation PRINCIPAL

Analysis of EEG activity during sleep - brain hemisphere symmetry of two classes of sleep spindles

NASA Astrophysics Data System (ADS)

Smolen, Magdalena M.

2009-01-01

This paper presents automatic analysis of some selected human electroencephalographic patterns during deep sleep using the Matching Pursuit (MP) algorithm. The periodicity of deep sleep EEG patterns was observed by calculating autocorrelation functions of their percentage contributions. The study confirmed the increasing trend of amplitude-weighted average frequency of sleep spindles from frontal to posterior derivations. The dominant frequencies from the left and the right brain hemisphere were strongly correlated.

Deep learning for hybrid EEG-fNIRS brain-computer interface: application to motor imagery classification.

PubMed

Chiarelli, Antonio Maria; Croce, Pierpaolo; Merla, Arcangelo; Zappasodi, Filippo

2018-06-01

Brain-computer interface (BCI) refers to procedures that link the central nervous system to a device. BCI was historically performed using electroencephalography (EEG). In the last years, encouraging results were obtained by combining EEG with other neuroimaging technologies, such as functional near infrared spectroscopy (fNIRS). A crucial step of BCI is brain state classification from recorded signal features. Deep artificial neural networks (DNNs) recently reached unprecedented complex classification outcomes. These performances were achieved through increased computational power, efficient learning algorithms, valuable activation functions, and restricted or back-fed neurons connections. By expecting significant overall BCI performances, we investigated the capabilities of combining EEG and fNIRS recordings with state-of-the-art deep learning procedures. We performed a guided left and right hand motor imagery task on 15 subjects with a fixed classification response time of 1 s and overall experiment length of 10 min. Left versus right classification accuracy of a DNN in the multi-modal recording modality was estimated and it was compared to standalone EEG and fNIRS and other classifiers. At a group level we obtained significant increase in performance when considering multi-modal recordings and DNN classifier with synergistic effect. BCI performances can be significantly improved by employing multi-modal recordings that provide electrical and hemodynamic brain activity information, in combination with advanced non-linear deep learning classification procedures.

Determination of subthalamic nucleus location by quantitative analysis of despiked background neural activity from microelectrode recordings obtained during deep brain stimulation surgery.

PubMed

Danish, Shabbar F; Baltuch, Gordon H; Jaggi, Jurg L; Wong, Stephen

2008-04-01

Microelectrode recording during deep brain stimulation surgery is a useful adjunct for subthalamic nucleus (STN) localization. We hypothesize that information in the nonspike background activity can help identify STN boundaries. We present results from a novel quantitative analysis that accomplishes this goal. Thirteen consecutive microelectrode recordings were retrospectively analyzed. Spikes were removed from the recordings with an automated algorithm. The remaining "despiked" signals were converted via root mean square amplitude and curve length calculations into "feature profile" time series. Subthalamic nucleus boundaries determined by inspection, based on sustained deviations from baseline for each feature profile, were compared against those determined intraoperatively by the clinical neurophysiologist. Feature profile activity within STN exhibited a sustained rise in 10 of 13 tracks (77%). The sensitivity of STN entry was 60% and 90% for curve length and root mean square amplitude, respectively, when agreement within 0.5 mm of the neurophysiologist's prediction was used. Sensitivities were 70% and 100% for 1 mm accuracy. Exit point sensitivities were 80% and 90% for both features within 0.5 mm and 1.0 mm, respectively. Reproducible activity patterns in deep brain stimulation microelectrode recordings can allow accurate identification of STN boundaries. Quantitative analyses of this type may provide useful adjunctive information for electrode placement in deep brain stimulation surgery.

Bimanual Force Coordination in Parkinson’s Disease Patients with Bilateral Subthalamic Deep Brain Stimulation

PubMed Central

Gorniak, Stacey L.; McIntyre, Cameron C.; Alberts, Jay L.

2013-01-01

Objective Studies of bimanual actions similar to activities of daily living (ADLs) are currently lacking in evaluating fine motor control in Parkinson’s disease patients implanted with bilateral subthalamic deep brain stimulators. We investigated basic time and force characteristics of a bimanual task that resembles performance of ADLs in a group of bilateral subthalamic deep brain stimulation (DBS) patients. Methods Patients were evaluated in three different DBS parameter conditions off stimulation, on clinically derived stimulation parameters, and on settings derived from a patient-specific computational model. Model-based parameters were computed as a means to minimize spread of current to non-motor regions of the subthalamic nucleus via Cicerone Deep Brain Stimulation software. Patients were evaluated off parkinsonian medications in each stimulation condition. Results The data indicate that DBS parameter state does not affect most aspects of fine motor control in ADL-like tasks; however, features such as increased grip force and grip symmetry varied with the stimulation state. In the absence of DBS parameters, patients exhibited significant grip force asymmetry. Overall UPDRS-III and UPDRS-III scores associated with hand function were lower while patients were experiencing clinically-derived or model-based parameters, as compared to the off-stimulation condition. Conclusion While bilateral subthalamic DBS has been shown to alleviate gross motor dysfunction, our results indicate that DBS may not provide the same magnitude of benefit to fine motor coordination. PMID:24244388

Neuroprotection for the new millennium. Matchmaking pharmacology and technology

NASA Technical Reports Server (NTRS)

Andrews, R. J.

2001-01-01

A major theme of the 1990s in the pathophysiology of nervous system injury has been the multifactorial etiology of irreversible injury. Multiple causes imply multiple opportunities for therapeutic intervention--hence the abandonment of the "magic bullet" single pharmacologic agent for neuroprotection in favor of pharmacologic "cocktails". A second theme of the 1990s has been the progress in technology for neuroprotection, minimally- or non-invasive monitoring as well as treatment. Cardiac stenting has eliminated the need, in many cases, for open heart surgery; deep brain stimulation for Parkinson's disease has offered significant improvement in quality of life for many who had exhausted cocktail drug treatment for their disease. Deep brain stimulation of the subthalamic nucleus offers a novel treatment for Parkinson's disease where a technological advance may actually be an intervention with effects that are normally expected from pharmacologic agents. Rather than merely "jamming" the nervous system circuits involved in Parkinson's disease, deep brain stimulation of the subthalamic nucleus appears to improve the neurotransmitter imbalance that lies at the heart of Parkinson's disease. It may also slow the progression of the disease. Given the example of deep brain stimulation of the subthalamic nucleus for Parkinson's disease, in future one may expect other technological or "hardware" interventions to influence the programming or "software" of the nervous system's physiologic response in certain disease states.

[High-Definition Exoscope System for Microneurosurgery:Use of an Exoscope in Combination with Tubular Retraction and Frameless Neuronavigation for Microsurgical Resection of Deep Brain Lesions].

PubMed

Nagatani, Kimihiro; Takeuchi, Satoru; Feng, Dongxia; Mori, Kentaro; Day, J Diaz

2015-07-01

The high-definition exoscope (VITOM®, Karl Storz GmbH & Co., Tuttlingen, Germany) is a new equipment that can be used as an alternative to the operating microscope in neurosurgery. Several neurosurgeons have recently reported that the exoscope allows for long working distances and great depth of field. Herein, we review reported cases of exoscope use in neurosurgery. We also describe the advantages of the exoscope compared to the operating microscope and endoscope. Furthermore, we introduce a novel technique for microsurgical resection of deep brain lesions, in which the exoscope is used along with tubular retraction and frameless neuronavigation. Before the operation, neuronavigation is registered and the surgical trajectory is planned to avoid damaging the functional cortex and eloquent white matter tracts. By using intraoperative neuronavigation, the tubular retractor (NICO BrainPath®, NICO Corporation, Indianapolis, US), which is designed to split the white matter when gently inserted, is inserted transcortically into the brain to reach the lesion, along the preplanned trajectory. After insertion, the tubular retractor is fixed in place using a self-retaining arm. This creates a narrow corridor that enables the use of the exoscope (for optimum visualization), bimanual dissection technique, and long bayoneted surgical instruments. The large focal distance of the exoscope allows it to be placed sufficiently further away from the surgical site, permitting the passage of long surgical instruments under the scope. Although obtaining surgical access to deep-seated brain lesions is challenging, we consider that this technique facilitates a safe surgical approach for lesions in deep locations.

Volumetric multimodality neural network for brain tumor segmentation

NASA Astrophysics Data System (ADS)

Silvana Castillo, Laura; Alexandra Daza, Laura; Carlos Rivera, Luis; Arbeláez, Pablo

2017-11-01

Brain lesion segmentation is one of the hardest tasks to be solved in computer vision with an emphasis on the medical field. We present a convolutional neural network that produces a semantic segmentation of brain tumors, capable of processing volumetric data along with information from multiple MRI modalities at the same time. This results in the ability to learn from small training datasets and highly imbalanced data. Our method is based on DeepMedic, the state of the art in brain lesion segmentation. We develop a new architecture with more convolutional layers, organized in three parallel pathways with different input resolution, and additional fully connected layers. We tested our method over the 2015 BraTS Challenge dataset, reaching an average dice coefficient of 84%, while the standard DeepMedic implementation reached 74%.

Electrical engram: how deep brain stimulation affects memory.

PubMed

Lee, Hweeling; Fell, Jürgen; Axmacher, Nikolai

2013-11-01

Deep brain stimulation (DBS) is a surgical procedure involving implantation of a pacemaker that sends electric impulses to specific brain regions. DBS has been applied in patients with Parkinson's disease, depression, and obsessive-compulsive disorder (among others), and more recently in patients with Alzheimer's disease to improve memory functions. Current DBS approaches are based on the concept that high-frequency stimulation inhibits or excites specific brain regions. However, because DBS entails the application of repetitive electrical stimuli, it primarily exerts an effect on extracellular field-potential oscillations similar to those recorded with electroencephalography. Here, we suggest a new perspective on how DBS may ameliorate memory dysfunction: it may enhance normal electrophysiological patterns underlying long-term memory processes within the medial temporal lobe. Copyright © 2013 Elsevier Ltd. All rights reserved.

Voxel-based measurement sensitivity of spatially resolved near-infrared spectroscopy in layered tissues

NASA Astrophysics Data System (ADS)

Niwayama, Masatsugu

2018-03-01

We quantitatively investigated the measurement sensitivity of spatially resolved spectroscopy (SRS) across six tissue models: cerebral tissue, a small animal brain, the forehead of a fetus, an adult brain, forearm muscle, and thigh muscle. The optical path length in the voxel of the model was analyzed using Monte Carlo simulations. It was found that the measurement sensitivity can be represented as the product of the change in the absorption coefficient and the difference in optical path length in two states with different source-detector distances. The results clarified the sensitivity ratio between the surface layer and the deep layer at each source-detector distance for each model and identified changes in the deep measurement area when one of the detectors was close to the light source. A comparison was made with the results from continuous-wave spectroscopy. The study also identified measurement challenges that arise when the surface layer is inhomogeneous. Findings on the measurement sensitivity of SRS at each voxel and in each layer can support the correct interpretation of measured values when near-infrared oximetry or functional near-infrared spectroscopy is used to investigate different tissue structures.

Network effects of deep brain stimulation

PubMed Central

Alhourani, Ahmad; McDowell, Michael M.; Randazzo, Michael J.; Wozny, Thomas A.; Kondylis, Efstathios D.; Lipski, Witold J.; Beck, Sarah; Karp, Jordan F.; Ghuman, Avniel S.

2015-01-01

The ability to differentially alter specific brain functions via deep brain stimulation (DBS) represents a monumental advance in clinical neuroscience, as well as within medicine as a whole. Despite the efficacy of DBS in the treatment of movement disorders, for which it is often the gold-standard therapy when medical management becomes inadequate, the mechanisms through which DBS in various brain targets produces therapeutic effects is still not well understood. This limited knowledge is a barrier to improving efficacy and reducing side effects in clinical brain stimulation. A field of study related to assessing the network effects of DBS is gradually emerging that promises to reveal aspects of the underlying pathophysiology of various brain disorders and their response to DBS that will be critical to advancing the field. This review summarizes the nascent literature related to network effects of DBS measured by cerebral blood flow and metabolic imaging, functional imaging, and electrophysiology (scalp and intracranial electroencephalography and magnetoencephalography) in order to establish a framework for future studies. PMID:26269552

Towards deep brain monitoring with superficial EEG sensors plus neuromodulatory focused ultrasound

PubMed Central

Darvas, F; Mehić, E; Caler, CJ; Ojemann, JG; Mourad, PD

2017-01-01

Noninvasive recordings of electrophysiological activity have limited anatomical specificity and depth. We hypothesized that spatially tagging a small volume of brain with a unique electroencephalogram (EEG) signal induced by pulsed focused ultrasound (pFU) could overcome those limitations. As a first step towards testing this hypothesis, we applied transcranial ultrasound (2 MHz, 200 microsecond-long pulses applied at 1050 Hz for one second at a spatial peak temporal average intensity of 1.4 W/cm2) to the brains of anesthetized rats while simultaneously recording EEG signals. We observed a significant 1050 Hz electrophysiological signal only when ultrasound was applied to living brain. Moreover, amplitude demodulation of the EEG signal at 1050 Hz yielded measurement of gamma band (>30 Hz) brain activity consistent with direct measurements of that activity. These results represent preliminary support for use of pFU as a spatial tagging mechanism for non-invasive EEG-based mapping of deep brain activity with high spatial resolution. PMID:27181686

A deep convolutional neural network-based automatic delineation strategy for multiple brain metastases stereotactic radiosurgery.

PubMed

Liu, Yan; Stojadinovic, Strahinja; Hrycushko, Brian; Wardak, Zabi; Lau, Steven; Lu, Weiguo; Yan, Yulong; Jiang, Steve B; Zhen, Xin; Timmerman, Robert; Nedzi, Lucien; Gu, Xuejun

2017-01-01

Accurate and automatic brain metastases target delineation is a key step for efficient and effective stereotactic radiosurgery (SRS) treatment planning. In this work, we developed a deep learning convolutional neural network (CNN) algorithm for segmenting brain metastases on contrast-enhanced T1-weighted magnetic resonance imaging (MRI) datasets. We integrated the CNN-based algorithm into an automatic brain metastases segmentation workflow and validated on both Multimodal Brain Tumor Image Segmentation challenge (BRATS) data and clinical patients' data. Validation on BRATS data yielded average DICE coefficients (DCs) of 0.75±0.07 in the tumor core and 0.81±0.04 in the enhancing tumor, which outperformed most techniques in the 2015 BRATS challenge. Segmentation results of patient cases showed an average of DCs 0.67±0.03 and achieved an area under the receiver operating characteristic curve of 0.98±0.01. The developed automatic segmentation strategy surpasses current benchmark levels and offers a promising tool for SRS treatment planning for multiple brain metastases.

Sing the mind electric - principles of deep brain stimulation.

PubMed

Kringelbach, Morten L; Green, Alexander L; Owen, Sarah L F; Schweder, Patrick M; Aziz, Tipu Z

2010-10-01

The remarkable efficacy of deep brain stimulation (DBS) for a range of treatment-resistant disorders is still not matched by a comparable understanding of the underlying neural mechanisms. Some progress has been made using translational research with a range of neuroscientific techniques, and here we review the most promising emerging principles. On balance, DBS appears to work by restoring normal oscillatory activity between a network of key brain regions. Further research using this causal neuromodulatory tool may provide vital insights into fundamental brain function, as well as guide targets for future treatments. In particular, DBS could have an important role in restoring the balance of the brain's default network and thus repairing the malignant brain states associated with affective disorders, which give rise to serious disabling problems such as anhedonia, the lack of pleasure. At the same time, it is important to proceed with caution and not repeat the errors from the era of psychosurgery. © 2010 The Authors. European Journal of Neuroscience © 2010 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Help With Depression

MedlinePlus

... techniques that focus on neuromodulation, which incorporates electrical, magnetic or other forms of energy to stimulate brain ... electroconvulsive therapy (ECT), vagus-nerve stimulation (VNS), transcranial magnetic stimulation (TMS) and the experimental deep-brain stimulation ( ...

Information dynamics of brain-heart physiological networks during sleep

NASA Astrophysics Data System (ADS)

Faes, L.; Nollo, G.; Jurysta, F.; Marinazzo, D.

2014-10-01

This study proposes an integrated approach, framed in the emerging fields of network physiology and information dynamics, for the quantitative analysis of brain-heart interaction networks during sleep. With this approach, the time series of cardiac vagal autonomic activity and brain wave activities measured respectively as the normalized high frequency component of heart rate variability and the EEG power in the δ, θ, α, σ, and β bands, are considered as realizations of the stochastic processes describing the dynamics of the heart system and of different brain sub-systems. Entropy-based measures are exploited to quantify the predictive information carried by each (sub)system, and to dissect this information into a part actively stored in the system and a part transferred to it from the other connected systems. The application of this approach to polysomnographic recordings of ten healthy subjects led us to identify a structured network of sleep brain-brain and brain-heart interactions, with the node described by the β EEG power acting as a hub which conveys the largest amount of information flowing between the heart and brain nodes. This network was found to be sustained mostly by the transitions across different sleep stages, as the information transfer was weaker during specific stages than during the whole night, and vanished progressively when moving from light sleep to deep sleep and to REM sleep.

The integration of brain dissection within the medical neuroscience laboratory enhances learning.

PubMed

Rae, Guenevere; Cork, R John; Karpinski, Aryn C; Swartz, William J

2016-11-01

The purpose of this study was to design a one-hour brain dissection protocol for a medical neuroscience course and evaluate the short and long-term effects of its implementation on medical students. First-year medical students (n = 166) participated in a brain dissection activity that included dissection of the basal nuclei and associated deep brain structures. Short-term retention was assessed by administering identical pre- and post-activity tests involving identification of brain structures. Following the brain dissection, the students' posttest scores were significantly higher (68.8% ± 17.8%; mean percent score ± SD) than their pretest scores (35.8% ± 20.0%) (P ≤ 0.0001). Long-term retention was evaluated by conducting an identical assessment five months after completion of the course. Students who participated in the dissection activity (n = 80) had significantly higher scores (46.6% ± 23.8%) than the students who did not participate in the dissection activity (n = 85) (38.1% ± 23.9%) (P ≤ 0.05). In addition to the long-term retention assessment, the NBME ® Subject Examination scores of students who participated in the dissection activity were significantly higher than the students who did not participate in the dissection activity (P ≤ 0.01). Results suggest that this succinct brain dissection activity may be a practical addition to an undergraduate medical neuroscience course for increasing the effectiveness of neuroanatomy training. This effect may have long-term benefits on knowledge retention and may be correlated with higher performance levels on standardized subject examinations. Anat Sci Educ 9: 565-574. © 2016 American Association of Anatomists. © 2016 American Association of Anatomists.

Does processing a shallow and a deep orthography produce different brain activity patterns? An ERP study conducted in Hebrew.

PubMed

Bar-Kochva, Irit

2011-01-01

Orthographies range from shallow orthographies with transparent grapheme-phoneme relations, to deep orthographies, in which these relations are opaque. Two forms of script transcribe the Hebrew language: the shallow pointed script (with diacritics) and the deep unpointed script (without diacritics). This study was set out to examine whether the reading of these scripts evokes distinct brain activity. Preliminary results indicate distinct Event-related-potentials (ERPs). As an equivalent finding was absent when ERPs of non-orthographic stimuli with and without meaningless diacritics were compared, the results imply that print-specific aspects of processing account for the distinct activity elicited by the pointed and unpointed scripts.

Bayesian convolutional neural network based MRI brain extraction on nonhuman primates.

PubMed

Zhao, Gengyan; Liu, Fang; Oler, Jonathan A; Meyerand, Mary E; Kalin, Ned H; Birn, Rasmus M

2018-07-15

Brain extraction or skull stripping of magnetic resonance images (MRI) is an essential step in neuroimaging studies, the accuracy of which can severely affect subsequent image processing procedures. Current automatic brain extraction methods demonstrate good results on human brains, but are often far from satisfactory on nonhuman primates, which are a necessary part of neuroscience research. To overcome the challenges of brain extraction in nonhuman primates, we propose a fully-automated brain extraction pipeline combining deep Bayesian convolutional neural network (CNN) and fully connected three-dimensional (3D) conditional random field (CRF). The deep Bayesian CNN, Bayesian SegNet, is used as the core segmentation engine. As a probabilistic network, it is not only able to perform accurate high-resolution pixel-wise brain segmentation, but also capable of measuring the model uncertainty by Monte Carlo sampling with dropout in the testing stage. Then, fully connected 3D CRF is used to refine the probability result from Bayesian SegNet in the whole 3D context of the brain volume. The proposed method was evaluated with a manually brain-extracted dataset comprising T1w images of 100 nonhuman primates. Our method outperforms six popular publicly available brain extraction packages and three well-established deep learning based methods with a mean Dice coefficient of 0.985 and a mean average symmetric surface distance of 0.220 mm. A better performance against all the compared methods was verified by statistical tests (all p-values < 10 -4 , two-sided, Bonferroni corrected). The maximum uncertainty of the model on nonhuman primate brain extraction has a mean value of 0.116 across all the 100 subjects. The behavior of the uncertainty was also studied, which shows the uncertainty increases as the training set size decreases, the number of inconsistent labels in the training set increases, or the inconsistency between the training set and the testing set increases. Copyright © 2018 Elsevier Inc. All rights reserved.

Causal mapping of emotion networks in the human brain: Framework and initial findings.

PubMed

Dubois, Julien; Oya, Hiroyuki; Tyszka, J Michael; Howard, Matthew; Eberhardt, Frederick; Adolphs, Ralph

2017-11-13

Emotions involve many cortical and subcortical regions, prominently including the amygdala. It remains unknown how these multiple network components interact, and it remains unknown how they cause the behavioral, autonomic, and experiential effects of emotions. Here we describe a framework for combining a novel technique, concurrent electrical stimulation with fMRI (es-fMRI), together with a novel analysis, inferring causal structure from fMRI data (causal discovery). We outline a research program for investigating human emotion with these new tools, and provide initial findings from two large resting-state datasets as well as case studies in neurosurgical patients with electrical stimulation of the amygdala. The overarching goal is to use causal discovery methods on fMRI data to infer causal graphical models of how brain regions interact, and then to further constrain these models with direct stimulation of specific brain regions and concurrent fMRI. We conclude by discussing limitations and future extensions. The approach could yield anatomical hypotheses about brain connectivity, motivate rational strategies for treating mood disorders with deep brain stimulation, and could be extended to animal studies that use combined optogenetic fMRI. Copyright © 2017 Elsevier Ltd. All rights reserved.

Prenatal β-catenin/Brn2/Tbr2 transcriptional cascade regulates adult social and stereotypic behaviors

PubMed Central

Belinson, H; Nakatani, J; Babineau, BA; Birnbaum, RY; Ellegood, J; Bershteyn, M; McEvilly, RJ; Long, JM; Willert, K; Klein, OD; Ahituv, N; Lerch, JP; Rosenfeld, GM; Wynshaw-Boris, A

2015-01-01

Social interaction is a fundamental behavior in all animal species, but the developmental timing of the social neural circuit formation and the cellular and molecular mechanisms governing its formation are poorly understood. We generated a mouse model with mutations in two Dishevelled genes, Dvl1 and Dvl3, that displays adult social and repetitive behavioral abnormalities associated with transient embryonic brain enlargement during deep layer cortical neuron formation. These phenotypes were mediated by the embryonic expansion of basal neural progenitor cells (NPCs) via deregulation of a β-catenin/Brn2/Tbr2 transcriptional cascade. Transient pharmacological activation of the canonical Wnt pathway during this period of early corticogenesis rescued the β-catenin/Brn2/Tbr2 transcriptional cascade and the embryonic brain phenotypes. Remarkably, this embryonic treatment prevented adult behavioral deficits and partially rescued abnormal brain structure in Dvl mutant mice. Our findings define a mechanism that links fetal brain development and adult behavior, demonstrating a fetal origin for social and repetitive behavior deficits seen in disorders such as autism. PMID:26830142

History of functional neurosurgery.

PubMed

Iskandar, B J; Nashold, B S

1995-01-01

Whereas in the early days of evil spirits, electric catfish, and phrenology, functional neurosurgery was based on crude observations and dogma, the progress made in neurophysiology at the turn of the century gave the field a strong scientific foundation. Subsequently, the advent of stereotaxis allowed access to deep brain regions and contributed an element of precision. Future directions include the development of frameless stereotaxy; the use of MRI-generated anatomic data, which would circumvent the serious problem of individual variations seen with standard brain atlases; the introduction of various chemicals into brain structures, in an attempt to influence neurochemically mediated disease processes; and finally, the use of the promising techniques of neural transplantation. On hearing of Penfield's intraoperative brain stimulations, Sherrington commented: "It must be great fun to have the physiological preparation speak to you." The idea of therapeutic neurophysiologic interventions is appealing, especially because many disorders show no obvious treatable pathologic cause (e.g., tumor, vascular malformation). As stereotactic technology becomes less cumbersome and more precise, more sophisticated in vivo neurophysiologic preparations become possible. In turn, as our understanding of nervous system physiology grows, our ability to understand pathophysiology and treat disease processes increases.

Prenatal β-catenin/Brn2/Tbr2 transcriptional cascade regulates adult social and stereotypic behaviors.

PubMed

Belinson, H; Nakatani, J; Babineau, B A; Birnbaum, R Y; Ellegood, J; Bershteyn, M; McEvilly, R J; Long, J M; Willert, K; Klein, O D; Ahituv, N; Lerch, J P; Rosenfeld, M G; Wynshaw-Boris, A

2016-10-01

Social interaction is a fundamental behavior in all animal species, but the developmental timing of the social neural circuit formation and the cellular and molecular mechanisms governing its formation are poorly understood. We generated a mouse model with mutations in two Disheveled genes, Dvl1 and Dvl3, that displays adult social and repetitive behavioral abnormalities associated with transient embryonic brain enlargement during deep layer cortical neuron formation. These phenotypes were mediated by the embryonic expansion of basal neural progenitor cells (NPCs) via deregulation of a β-catenin/Brn2/Tbr2 transcriptional cascade. Transient pharmacological activation of the canonical Wnt pathway during this period of early corticogenesis rescued the β-catenin/Brn2/Tbr2 transcriptional cascade and the embryonic brain phenotypes. Remarkably, this embryonic treatment prevented adult behavioral deficits and partially rescued abnormal brain structure in Dvl mutant mice. Our findings define a mechanism that links fetal brain development and adult behavior, demonstrating a fetal origin for social and repetitive behavior deficits seen in disorders such as autism.

The Role of a Neuropsychologist on a Movement Disorders Deep Brain Stimulation Team.

PubMed

Kubu, Cynthia S

2018-05-01

The term movement disorders is misleading in the implication that the symptoms are limited to motor problems. Most movement disorders include a variety of neurobehavioral and neurocognitive symptoms that require neuropsychological expertise. The goal of this paper is to provide a rationale and practical roadmap for neuropsychologists' involvement in a Movement Disorders team with a specific focus on pre-operative deep brain stimulation (DBS) evaluations. Pragmatic recommendations regarding requisite skills, clinical practice, recommendations, communication, and benefits are outlined.

Deep learning for brain tumor classification

NASA Astrophysics Data System (ADS)

Paul, Justin S.; Plassard, Andrew J.; Landman, Bennett A.; Fabbri, Daniel

2017-03-01

Recent research has shown that deep learning methods have performed well on supervised machine learning, image classification tasks. The purpose of this study is to apply deep learning methods to classify brain images with different tumor types: meningioma, glioma, and pituitary. A dataset was publicly released containing 3,064 T1-weighted contrast enhanced MRI (CE-MRI) brain images from 233 patients with either meningioma, glioma, or pituitary tumors split across axial, coronal, or sagittal planes. This research focuses on the 989 axial images from 191 patients in order to avoid confusing the neural networks with three different planes containing the same diagnosis. Two types of neural networks were used in classification: fully connected and convolutional neural networks. Within these two categories, further tests were computed via the augmentation of the original 512×512 axial images. Training neural networks over the axial data has proven to be accurate in its classifications with an average five-fold cross validation of 91.43% on the best trained neural network. This result demonstrates that a more general method (i.e. deep learning) can outperform specialized methods that require image dilation and ring-forming subregions on tumors.

MEG Can Map Short and Long-Term Changes in Brain Activity following Deep Brain Stimulation for Chronic Pain

PubMed Central

Mohseni, Hamid R.; Smith, Penny P.; Parsons, Christine E.; Young, Katherine S.; Hyam, Jonathan A.; Stein, Alan; Stein, John F.; Green, Alexander L.; Aziz, Tipu Z.; Kringelbach, Morten L.

2012-01-01

Deep brain stimulation (DBS) has been shown to be clinically effective for some forms of treatment-resistant chronic pain, but the precise mechanisms of action are not well understood. Here, we present an analysis of magnetoencephalography (MEG) data from a patient with whole-body chronic pain, in order to investigate changes in neural activity induced by DBS for pain relief over both short- and long-term. This patient is one of the few cases treated using DBS of the anterior cingulate cortex (ACC). We demonstrate that a novel method, null-beamforming, can be used to localise accurately brain activity despite the artefacts caused by the presence of DBS electrodes and stimulus pulses. The accuracy of our source localisation was verified by correlating the predicted DBS electrode positions with their actual positions. Using this beamforming method, we examined changes in whole-brain activity comparing pain relief achieved with deep brain stimulation (DBS ON) and compared with pain experienced with no stimulation (DBS OFF). We found significant changes in activity in pain-related regions including the pre-supplementary motor area, brainstem (periaqueductal gray) and dissociable parts of caudal and rostral ACC. In particular, when the patient reported experiencing pain, there was increased activity in different regions of ACC compared to when he experienced pain relief. We were also able to demonstrate long-term functional brain changes as a result of continuous DBS over one year, leading to specific changes in the activity in dissociable regions of caudal and rostral ACC. These results broaden our understanding of the underlying mechanisms of DBS in the human brain. PMID:22675503

Comparative Methylome Analyses Identify Epigenetic Regulatory Loci of Human Brain Evolution.

PubMed

Mendizabal, Isabel; Shi, Lei; Keller, Thomas E; Konopka, Genevieve; Preuss, Todd M; Hsieh, Tzung-Fu; Hu, Enzhi; Zhang, Zhe; Su, Bing; Yi, Soojin V

2016-11-01

How do epigenetic modifications change across species and how do these modifications affect evolution? These are fundamental questions at the forefront of our evolutionary epigenomic understanding. Our previous work investigated human and chimpanzee brain methylomes, but it was limited by the lack of outgroup data which is critical for comparative (epi)genomic studies. Here, we compared whole genome DNA methylation maps from brains of humans, chimpanzees and also rhesus macaques (outgroup) to elucidate DNA methylation changes during human brain evolution. Moreover, we validated that our approach is highly robust by further examining 38 human-specific DMRs using targeted deep genomic and bisulfite sequencing in an independent panel of 37 individuals from five primate species. Our unbiased genome-scan identified human brain differentially methylated regions (DMRs), irrespective of their associations with annotated genes. Remarkably, over half of the newly identified DMRs locate in intergenic regions or gene bodies. Nevertheless, their regulatory potential is on par with those of promoter DMRs. An intriguing observation is that DMRs are enriched in active chromatin loops, suggesting human-specific evolutionary remodeling at a higher-order chromatin structure. These findings indicate that there is substantial reprogramming of epigenomic landscapes during human brain evolution involving noncoding regions. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Is there evidence for neurodegenerative change following traumatic brain injury in children and youth? A scoping review.

PubMed

Keightley, Michelle L; Sinopoli, Katia J; Davis, Karen D; Mikulis, David J; Wennberg, Richard; Tartaglia, Maria C; Chen, Jen-Kai; Tator, Charles H

2014-01-01

While generalized cerebral atrophy and neurodegenerative change following traumatic brain injury (TBI) is well recognized in adults, it remains comparatively understudied in the pediatric population, suggesting that research should address the potential for neurodegenerative change in children and youth following TBI. This focused review examines original research findings documenting evidence for neurodegenerative change following TBI of all severities in children and youth. Our relevant inclusion and exclusion criteria identified a total of 16 articles for review. Taken together, the studies reviewed suggest there is evidence for long-term neurodegenerative change following TBI in children and youth. In particular both cross-sectional and longitudinal studies revealed volume loss in selected brain regions including the hippocampus, amygdala, globus pallidus, thalamus, periventricular white matter, cerebellum, and brain stem as well as overall decreased whole brain volume and increased CSF and ventricular space. Diffusion Tensor Imaging (DTI) studies also report evidence for decreased cellular integrity, particularly in the corpus callosum. Sensitivity of the hippocampus and deep limbic structures in pediatric populations are similar to findings in the adult literature and we consider the data supporting these changes as well as the need to investigate the possibility of neurodegenerative onset in childhood associated with mild traumatic brain injury (mTBI).

White Matter Hyperintensities Are Under Strong Genetic Influence.

PubMed

Sachdev, Perminder S; Thalamuthu, Anbupalam; Mather, Karen A; Ames, David; Wright, Margaret J; Wen, Wei

2016-06-01

The genetic basis of white matter hyperintensities (WMH) is still unknown. This study examines the heritability of WMH in both sexes and in different brain regions, and the influence of age. Participants from the Older Australian Twins Study were recruited (n=320; 92 monozygotic and 68 dizygotic pairs) who volunteered for magnetic resonance imaging scans and medical assessments. Heritability, that is, the ratio of the additive genetic variance to the total phenotypic variance, was estimated using the twin design. Heritability was high for total WMH volume (0.76), and for periventricular WMH (0.64) and deep WMH (0.77), and varied from 0.18 for the cerebellum to 0.76 for the occipital lobe. The genetic correlation between deep and periventricular WMH regions was 0.85, with one additive genetics factor accounting for most of the shared variance. Heritability was consistently higher in women in the cerebral regions. Heritability in deep but not periventricular WMH declined with age, in particular after the age of 75. WMH have a strong genetic influence but this is not uniform through the brain, being higher for deep than periventricular WMH and in the cerebral regions. The genetic influence is higher in women, and there is an age-related decline, most markedly for deep WMH. The data suggest some heterogeneity in the pathogenesis of WMH for different brain regions and for men and women. © 2016 American Heart Association, Inc.

Reward Circuitry in Addiction.

PubMed

Cooper, Sarah; Robison, A J; Mazei-Robison, Michelle S

2017-07-01

Understanding the brain circuitry that underlies reward is critical to improve treatment for many common health issues, including obesity, depression, and addiction. Here we focus on insights into the organization and function of reward circuitry and its synaptic and structural adaptations in response to cocaine exposure. While the importance of certain circuits, such as the mesocorticolimbic dopamine pathway, are well established in drug reward, recent studies using genetics-based tools have revealed functional changes throughout the reward circuitry that contribute to different facets of addiction, such as relapse and craving. The ability to observe and manipulate neuronal activity within specific cell types and circuits has led to new insight into not only the basic connections between brain regions, but also the molecular changes within these specific microcircuits, such as neurotrophic factor and GTPase signaling or α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor function, that underlie synaptic and structural plasticity evoked by drugs of abuse. Excitingly, these insights from preclinical rodent work are now being translated into the clinic, where transcranial magnetic simulation and deep brain stimulation therapies are being piloted in human cocaine dependence. Thus, this review seeks to summarize current understanding of the major brain regions implicated in drug-related behaviors and the molecular mechanisms that contribute to altered connectivity between these regions, with the postulation that increased knowledge of the plasticity within the drug reward circuit will lead to new and improved treatments for addiction.

Semi-Automated Trajectory Analysis of Deep Ballistic Penetrating Brain Injury

PubMed Central

Folio, Les; Solomon, Jeffrey; Biassou, Nadia; Fischer, Tatjana; Dworzak, Jenny; Raymont, Vanessa; Sinaii, Ninet; Wassermann, Eric M.; Grafman, Jordan

2016-01-01

Background Penetrating head injuries (PHIs) are common in combat operations and most have visible wound paths on computed tomography (CT). Objective We assess agreement between an automated trajectory analysis-based assessment of brain injury and manual tracings of encephalomalacia on CT. Methods We analyzed 80 head CTs with ballistic PHI from the Institutional Review Board approved Vietnam head injury registry. Anatomic reports were generated from spatial coordinates of projectile entrance and terminal fragment location. These were compared to manual tracings of the regions of encephalomalacia. Dice’s similarity coefficients, kappa, sensitivities, and specificities were calculated to assess agreement. Times required for case analysis were also compared. Results Results show high specificity of anatomic regions identified on CT with semiautomated anatomical estimates and manual tracings of tissue damage. Radiologist’s and medical students’ anatomic region reports were similar (Kappa 0.8, t-test p < 0.001). Region of probable injury modeling of involved brain structures was sensitive (0.7) and specific (0.9) compared with manually traced structures. Semiautomated analysis was 9-fold faster than manual tracings. Conclusion Our region of probable injury spatial model approximates anatomical regions of encephalomalacia from ballistic PHI with time-saving over manual methods. Results show potential for automated anatomical reporting as an adjunct to current practice of radiologist/neurosurgical review of brain injury by penetrating projectiles. PMID:23707123

The Brain Rotation and Brain Diffusion Strategies of Small Islanders: Considering "Movement" in Lieu of "Place"

ERIC Educational Resources Information Center

Baldacchino, Godfrey

2006-01-01

The "brain drain" phenomenon is typically seen as a zero-sum game, where one party's gain is presumed to be another's drain. This corresponds to deep-seated assumptions about what is "home" and what is "away". This article challenges the view, driven by much "brain drain" literature, that the dynamic is an…

Influence of the implanted pulse generator as reference electrode in finite element model of monopolar deep brain stimulation.

PubMed

Walckiers, Grégoire; Fuchs, Benjamin; Thiran, Jean-Philippe; Mosig, Juan R; Pollo, Claudio

2010-01-30

Electrical deep brain stimulation (DBS) is an efficient method to treat movement disorders. Many models of DBS, based mostly on finite elements, have recently been proposed to better understand the interaction between the electrical stimulation and the brain tissues. In monopolar DBS, clinically widely used, the implanted pulse generator (IPG) is used as reference electrode (RE). In this paper, the influence of the RE model of monopolar DBS is investigated. For that purpose, a finite element model of the full electric loop including the head, the neck and the superior chest is used. Head, neck and superior chest are made of simple structures such as parallelepipeds and cylinders. The tissues surrounding the electrode are accurately modelled from data provided by the diffusion tensor magnetic resonance imaging (DT-MRI). Three different configurations of RE are compared with a commonly used model of reduced size. The electrical impedance seen by the DBS system and the potential distribution are computed for each model. Moreover, axons are modelled to compute the area of tissue activated by stimulation. Results show that these indicators are influenced by the surface and position of the RE. The use of a RE model corresponding to the implanted device rather than the usually simplified model leads to an increase of the system impedance (+48%) and a reduction of the area of activated tissue (-15%). (c) 2009 Elsevier B.V. All rights reserved.

And Then There Was Light: Perspectives of Optogenetics for Deep Brain Stimulation and Neuromodulation

PubMed Central

Delbeke, Jean; Hoffman, Luis; Mols, Katrien; Braeken, Dries; Prodanov, Dimiter

2017-01-01

Deep Brain Stimulation (DBS) has evolved into a well-accepted add-on treatment for patients with severe Parkinsons disease as well as for other chronic neurological conditions. The focal action of electrical stimulation can yield better responses and it exposes the patient to fewer side effects compared to pharmaceuticals distributed throughout the body toward the brain. On the other hand, the current practice of DBS is hampered by the relatively coarse level of neuromodulation achieved. Optogenetics, in contrast, offers the perspective of much more selective actions on the various physiological structures, provided that the stimulated cells are rendered sensitive to the action of light. Optogenetics has experienced tremendous progress since its first in vivo applications about 10 years ago. Recent advancements of viral vector technology for gene transfer substantially reduce vector-associated cytotoxicity and immune responses. This brings about the possibility to transfer this technology into the clinic as a possible alternative to DBS and neuromodulation. New paths could be opened toward a rich panel of clinical applications. Some technical issues still limit the long term use in humans but realistic perspectives quickly emerge. Despite a rapid accumulation of observations about patho-physiological mechanisms, it is still mostly serendipity and empiric adjustments that dictate clinical practice while more efficient logically designed interventions remain rather exceptional. Interestingly, it is also very much the neuro technology developed around optogenetics that offers the most promising tools to fill in the existing knowledge gaps about brain function in health and disease. The present review examines Parkinson's disease and refractory epilepsy as use cases for possible optogenetic stimulation therapies. PMID:29311765

Propofol disrupts functional interactions between sensory and high-order processing of auditory verbal memory.

PubMed

Liu, Xiaolin; Lauer, Kathryn K; Ward, Barney D; Rao, Stephen M; Li, Shi-Jiang; Hudetz, Anthony G

2012-10-01

Current theories suggest that disrupting cortical information integration may account for the mechanism of general anesthesia in suppressing consciousness. Human cognitive operations take place in hierarchically structured neural organizations in the brain. The process of low-order neural representation of sensory stimuli becoming integrated in high-order cortices is also known as cognitive binding. Combining neuroimaging, cognitive neuroscience, and anesthetic manipulation, we examined how cognitive networks involved in auditory verbal memory are maintained in wakefulness, disrupted in propofol-induced deep sedation, and re-established in recovery. Inspired by the notion of cognitive binding, an functional magnetic resonance imaging-guided connectivity analysis was utilized to assess the integrity of functional interactions within and between different levels of the task-defined brain regions. Task-related responses persisted in the primary auditory cortex (PAC), but vanished in the inferior frontal gyrus (IFG) and premotor areas in deep sedation. For connectivity analysis, seed regions representing sensory and high-order processing of the memory task were identified in the PAC and IFG. Propofol disrupted connections from the PAC seed to the frontal regions and thalamus, but not the connections from the IFG seed to a set of widely distributed brain regions in the temporal, frontal, and parietal lobes (with exception of the PAC). These later regions have been implicated in mediating verbal comprehension and memory. These results suggest that propofol disrupts cognition by blocking the projection of sensory information to high-order processing networks and thus preventing information integration. Such findings contribute to our understanding of anesthetic mechanisms as related to information and integration in the brain. Copyright © 2011 Wiley Periodicals, Inc.

Deep Brain Stimulation for Parkinson's Disease

MedlinePlus

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Therapeutic deep brain stimulation reduces cortical phase-amplitude coupling in Parkinson's disease

PubMed Central

de Hemptinne, Coralie; Swann, Nicole; Ostrem, Jill L.; Ryapolova-Webb, Elena S.; Luciano, Marta San; Galifianakis, Nicholas; Starr, Philip A.

2015-01-01

Deep brain stimulation (DBS) is increasingly applied to the treatment of brain disorders, but its mechanism of action remains unknown. Here, we evaluate the effect of basal ganglia DBS on cortical function using invasive cortical recordings in Parkinson's disease (PD) patients undergoing DBS implantation surgery. In the primary motor cortex of PD patients neuronal population spiking is excessively synchronized to the phase of network oscillations. This manifests in brain surface recordings as exaggerated coupling between the phase of the β rhythm and the amplitude of broadband activity. We show that acute therapeutic DBS reversibly reduces phase-amplitude interactions over a similar time course as reduction in parkinsonian motor signs. We propose that DBS of the basal ganglia improves cortical function by alleviating excessive β phase locking of motor cortex neurons. PMID:25867121

A deep learning model integrating FCNNs and CRFs for brain tumor segmentation.

PubMed

Zhao, Xiaomei; Wu, Yihong; Song, Guidong; Li, Zhenye; Zhang, Yazhuo; Fan, Yong

2018-01-01

Accurate and reliable brain tumor segmentation is a critical component in cancer diagnosis, treatment planning, and treatment outcome evaluation. Build upon successful deep learning techniques, a novel brain tumor segmentation method is developed by integrating fully convolutional neural networks (FCNNs) and Conditional Random Fields (CRFs) in a unified framework to obtain segmentation results with appearance and spatial consistency. We train a deep learning based segmentation model using 2D image patches and image slices in following steps: 1) training FCNNs using image patches; 2) training CRFs as Recurrent Neural Networks (CRF-RNN) using image slices with parameters of FCNNs fixed; and 3) fine-tuning the FCNNs and the CRF-RNN using image slices. Particularly, we train 3 segmentation models using 2D image patches and slices obtained in axial, coronal and sagittal views respectively, and combine them to segment brain tumors using a voting based fusion strategy. Our method could segment brain images slice-by-slice, much faster than those based on image patches. We have evaluated our method based on imaging data provided by the Multimodal Brain Tumor Image Segmentation Challenge (BRATS) 2013, BRATS 2015 and BRATS 2016. The experimental results have demonstrated that our method could build a segmentation model with Flair, T1c, and T2 scans and achieve competitive performance as those built with Flair, T1, T1c, and T2 scans. Copyright © 2017 Elsevier B.V. All rights reserved.

Tourette syndrome and other chronic tic disorders: an update on clinical management.

PubMed

Martino, Davide; Pringsheim, Tamara M

2018-02-01

The management of Tourette syndrome (TS) and other chronic tic disorders occurs in multiple stages and begins with comprehensive assessment and complex psychoeducation. Behavioral and pharmacological interventions (second stage) are needed when tics cause physical or psychosocial impairment. Deep brain stimulation surgery or experimental therapies represent the third stage. Areas covered: Discussed are recent advances in assessment and therapy of chronic tic disorders, encompassing the three stages of intervention, with the addition of experimental, non-invasive brain stimulation strategies. A PubMed search was performed using as keywords: 'tic disorders', 'Tourette syndrome', 'assessment', 'rating scales', 'behavioral treatment', 'pharmacological treatment', 'deep brain stimulation', 'transcranial magnetic (or current) stimulation', and 'transcranial current stimulation'. More than 300 peer-reviewed articles were evaluated. The studies discussed have been selected on the basis of novelty and impact. Expert commentary: Comprehensive assessment of tic disorders and psychoeducation are crucial to a correct active management approach. Behavioral treatments represent first line of active interventions, with increasing potential offered by telehealth. Antipsychotics and alpha agonists remain first line pharmacological interventions for tics, although VMAT-2 inhibitors appear promising. Deep brain stimulation is a potential option for medically refractory, severely disabled patients with tics, but age and target selection require further investigation.

Deep brain stimulation for the treatment of uncommon tremor syndromes.

PubMed

Ramirez-Zamora, Adolfo; Okun, Michael S

2016-08-01

Deep brain stimulation (DBS) has become a standard therapy for the treatment of select cases of medication refractory essential tremor and Parkinson's disease however the effectiveness and long-term outcomes of DBS in other uncommon and complex tremor syndromes has not been well established. Traditionally, the ventralis intermedius nucleus (VIM) of the thalamus has been considered the main target for medically intractable tremors; however alternative brain regions and improvements in stereotactic techniques and hardware may soon change the horizon for treatment of complex tremors. In this article, we conducted a PubMed search using different combinations between the terms 'Uncommon tremors', 'Dystonic tremor', 'Holmes tremor' 'Midbrain tremor', 'Rubral tremor', 'Cerebellar tremor', 'outflow tremor', 'Multiple Sclerosis tremor', 'Post-traumatic tremor', 'Neuropathic tremor', and 'Deep Brain Stimulation/DBS'. Additionally, we examined and summarized the current state of evolving interventions for treatment of complex tremor syndromes. Expert commentary: Recently reported interventions for rare tremors include stimulation of the posterior subthalamic area, globus pallidus internus, ventralis oralis anterior/posterior thalamic subnuclei, and the use of dual lead stimulation in one or more of these targets. Treatment should be individualized and dictated by tremor phenomenology and associated clinical features.

Our first decade of experience in deep brain stimulation of the brainstem: elucidating the mechanism of action of stimulation of the ventrolateral pontine tegmentum.

PubMed

Mazzone, Paolo; Vilela Filho, Osvaldo; Viselli, Fabio; Insola, Angelo; Sposato, Stefano; Vitale, Flora; Scarnati, Eugenio

2016-07-01

The region of the pedunculopontine tegmental nucleus (PPTg) has been proposed as a novel target for deep brain stimulation (DBS) to treat levodopa resistant symptoms in motor disorders. Recently, the anatomical organization of the brainstem has been revised and four new distinct structures have been represented in the ventrolateral pontine tegmentum area in which the PPTg was previously identified. Given this anatomical reassessment, and considering the increasing of our experience, in this paper we revisit the value of DBS applied to that area. The reappraisal of clinical outcomes in the light of this revisitation may also help to understand the consequences of DBS applied to structures located in the ventrolateral pontine tegmentum, apart from the PPTg. The implantation of 39 leads in 32 patients suffering from Parkinson's disease (PD, 27 patients) and progressive supranuclear palsy (PSP, four patients) allowed us to reach two major conclusions. The first is that the results of the advancement of our technique in brainstem DBS matches the revision of brainstem anatomy. The second is that anatomical and functional aspects of our findings may help to explain how DBS acts when applied in the brainstem and to identify the differences when it is applied either in the brainstem or in the subthalamic nucleus. Finally, in this paper we discuss how the loss of neurons in brainstem nuclei occurring in both PD and PSP, the results of intraoperative recording of somatosensory evoked potentials, and the improvement of postural control during DBS point toward the potential role of ascending sensory pathways and/or other structures in mediating the effects of DBS applied in the ventrolateral pontine tegmentum region.

Mechanisms for pattern specificity of deep-brain stimulation in Parkinson’s disease

PubMed Central

Mato, Germán; Dellavale, Damián

2017-01-01

Deep brain stimulation (DBS) has become a widely used technique for treating advanced stages of neurological and psychiatric illness. In the case of motor disorders related to basal ganglia (BG) dysfunction, several mechanisms of action for the DBS therapy have been identified which might be involved simultaneously or in sequence. However, the identification of a common key mechanism underlying the clinical relevant DBS configurations has remained elusive due to the inherent complexity related to the interaction between the electrical stimulation and the neural tissue, and the intricate circuital structure of the BG-thalamocortical network. In this work, it is shown that the clinically relevant range for both, the frequency and intensity of the electrical stimulation pattern, is an emergent property of the BG anatomy at the system-level that can be addressed using mean-field descriptive models of the BG network. Moreover, it is shown that the activity resetting mechanism elicited by electrical stimulation provides a natural explanation to the ineffectiveness of irregular (i.e., aperiodic) stimulation patterns, which has been commonly observed in previously reported pathophysiology models of Parkinson’s disease. Using analytical and numerical techniques, these results have been reproduced in both cases: 1) a reduced mean-field model that can be thought as an elementary building block capable to capture the underlying fundamentals of the relevant loops constituting the BG-thalamocortical network, and 2) a detailed model constituted by the direct and hyperdirect loops including one-dimensional spatial structure of the BG nuclei. We found that the optimal ranges for the essential parameters of the stimulation patterns can be understood without taking into account biophysical details of the relevant structures. PMID:28813460

Dynamics of scene representations in the human brain revealed by magnetoencephalography and deep neural networks

PubMed Central

Cichy, Radoslaw Martin; Khosla, Aditya; Pantazis, Dimitrios; Oliva, Aude

2017-01-01

Human scene recognition is a rapid multistep process evolving over time from single scene image to spatial layout processing. We used multivariate pattern analyses on magnetoencephalography (MEG) data to unravel the time course of this cortical process. Following an early signal for lower-level visual analysis of single scenes at ~100 ms, we found a marker of real-world scene size, i.e. spatial layout processing, at ~250 ms indexing neural representations robust to changes in unrelated scene properties and viewing conditions. For a quantitative model of how scene size representations may arise in the brain, we compared MEG data to a deep neural network model trained on scene classification. Representations of scene size emerged intrinsically in the model, and resolved emerging neural scene size representation. Together our data provide a first description of an electrophysiological signal for layout processing in humans, and suggest that deep neural networks are a promising framework to investigate how spatial layout representations emerge in the human brain. PMID:27039703

Electromagnetic interference of GSM mobile phones with the implantable deep brain stimulator, ITREL-III

PubMed Central

Kainz, Wolfgang; Alesch, François; Chan, Dulciana Dias

2003-01-01

Background The purpose was to investigate mobile phone interference with implantable deep brain stimulators by means of 10 different 900 Mega Hertz (MHz) and 10 different 1800 MHz GSM (Global System for Mobile Communications) mobile phones. Methods All tests were performed in vitro using a phantom especially developed for testing with deep brain stimulators. The phantom was filled with liquid phantom materials simulating brain and muscle tissue. All examinations were carried out inside an anechoic chamber on two implants of the same type of deep brain stimulator: ITREL-III from Medtronic Inc., USA. Results Despite a maximum transmitted peak power of mobile phones of 1 Watt (W) at 1800 MHz and 2 W at 900 MHz respectively, no influence on the ITREL-III was found. Neither the shape of the pulse form changed nor did single pulses fail. Tests with increased transmitted power using CW signals and broadband dipoles have shown that inhibition of the ITREL-III occurs at frequency dependent power levels which are below the emissions of GSM mobile phones. The ITREL-III is essentially more sensitive at 1800 MHz than at 900 MHz. Particularly the frequency range around 1500 MHz shows a very low interference threshold. Conclusion These investigations do not indicate a direct risk for ITREL-III patients using the tested GSM phones. Based on the interference levels found with CW signals, which are below the mobile phone emissions, we recommend similar precautions as for patients with cardiac pacemakers: 1. The phone should be used at the ear at the opposite side of the implant and 2. The patient should avoid carrying the phone close to the implant. PMID:12773204

Simulation and assessment of cerebrovascular damage in deep brain stimulation using a stereotactic atlas of vasculature and structure derived from multiple 3- and 7-tesla scans.

PubMed

Nowinski, Wieslaw L; Chua, Beng Choon; Volkau, Ihar; Puspitasari, Fiftarina; Marchenko, Yevgen; Runge, Val M; Knopp, Michael V

2010-12-01

The most severe complication of deep brain stimulation (DBS) is intracranial hemorrhage. Detailed knowledge of the cerebrovasculature could reduce the rate of this disorder. Morphological scans typically acquired in stereotactic and functional neurosurgery (SFN) by using 1.5-T (or sometimes even 3-T) imaging units poorly depict the vasculature. Advanced angiographic imaging, including 3- and 7-T 3D time-of-flight and susceptibility weighted imaging as well as 320-slice CT angiography, depict the vessels in great detail. However, these acquisitions are not used in SFN clinical practice, and robust methods for their processing are not available yet. Therefore, the authors proposed the use of a detailed 3D stereotactic cerebrovascular atlas to assist in SFN planning and to potentially reduce DBS-induced hemorrhage. A very detailed 3D cerebrovascular atlas of arteries, veins, and dural sinuses was constructed from multiple 3- and 7-T scans. The atlas contained>900 vessels, each labeled with a name and diameter with the smallest having a 90-μm diameter. The cortical areas, ventricular system, and subcortical structures were fully segmented and labeled, including the main stereotactic target structures: subthalamic nucleus, ventral intermediate nucleus of the thalamus, and internal globus pallidus. The authors also developed a computer simulator with the embedded atlas that was able to compute the effective electrode trajectory by minimizing penetration of the cerebrovascular system and vital brain structures by a DBS electrode. The simulator provides the neurosurgeon with functions for atlas manipulation, target selection, trajectory planning and editing, 3D display and manipulation, and electrode-brain penetration calculation. This simulation demonstrated that a DBS electrode inserted in the middle frontal gyrus may intersect several arteries and veins including 1) the anteromedial frontal artery of the anterior cerebral artery as well as the prefrontal artery and the precentral sulcus artery of the middle cerebral artery (range of diameters 0.4-0.6 mm); and 2) the prefrontal, anterior caudate, and medullary veins (range of diameters 0.1-2.3 mm). This work also shows that field strength and pulse sequence have a substantial impact on vessel depiction. The numbers of 3D vascular segments are 215, 363, and 907 for 1.5-, 3-, and 7-T scans, respectively. Inserting devices into the brain during microrecording and stimulation may cause microbleeds not discernible on standard scans. A small change in the location of the DBS electrode can result in a major change for the patient. The described simulation increases the neurosurgeon's awareness of this phenomenon. The simulator enables the neurosurgeon to analyze the spatial relationships between the track and the cerebrovasculature, ventricles, subcortical structures, and cortical areas, which allows the DBS electrode to be placed more effectively, and thus potentially reducing the invasiveness of the stimulation procedure for the patient.

Brain hyperintensity location determines outcome in the triad of impaired cognition, physical health and depressive symptoms: A cohort study in late life.

PubMed

Murray, Alison; McNeil, Chris; Salarirad, Sima; Deary, Ian; Phillips, Louise; Whalley, Lawrence; Staff, Roger

2016-01-01

Brain hyperintensities, detectable with MRI, increase with age. They are associated with a triad of impairment in cognitive ability, depression and physical health. Here we test the hypothesis that the association between hyperintensities and cognitive ability, physical health and depressive symptoms depends on lesion location. 244 members of the Aberdeen 1936 Birth Cohort were recruited to this study. 227 participants completed brain MRI and their hyperintensities were scored using Scheltens's scale. 205 had complete imaging, cognitive, physical health and depressive symptom score data. The relationships between hyperintensity location and depressive symptoms, cognitive ability and physical health were examined by correlation and structural equation analysis. We found that depressive symptoms correlated with hyperintensity burden in the grey matter (r=0.14, p=0.04) and infratentorial regions (r=0.17, p=0.01). Infratentorial hyperintensities correlated with reduced peak expiratory flow rate (r=-0.26, p<0.001) and impaired gait (r=0.13, p=0.05). No relationship was found between white matter and periventricular (supratentoral) hyperintensities and depressive symptoms. Hyperintensities in the supratentorial and infratentorial regions were associated with reduced cognitive performance. Using structural equation modelling we found that the association between hyperintensities and depressive symptoms was mediated by negative effects on physical health and cognitive ability. Hyperintensities in deep brain structures are associated with depressive symptoms, mediated via impaired physical health and cognitive ability. Participants with higher cognitive ability and better physical health are at lower risk of depressive symptoms. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Neuroimaging effects of prenatal alcohol exposure on the developing human brain: a magnetic resonance imaging review.

PubMed

Donald, Kirsten Ann; Eastman, Emma; Howells, Fleur Margaret; Adnams, Colleen; Riley, Edward Patrick; Woods, Roger Paul; Narr, Katherine Louise; Stein, Dan Joseph

2015-10-01

This paper reviews the magnetic resonance imaging (MRI) literature on the effects of prenatal alcohol exposure on the developing human brain. A literature search was conducted through the following databases: PubMed, PsycINFO and Google Scholar. Combinations of the following search terms and keywords were used to identify relevant studies: 'alcohol', 'fetal alcohol spectrum disorders', 'fetal alcohol syndrome', 'FAS', 'FASD', 'MRI', 'DTI', 'MRS', 'neuroimaging', 'children' and 'infants'. A total of 64 relevant articles were identified across all modalities. Overall, studies reported smaller total brain volume as well as smaller volume of both the white and grey matter in specific cortical regions. The most consistently reported structural MRI findings were alterations in the shape and volume of the corpus callosum, as well as smaller volume in the basal ganglia and hippocampi. The most consistent finding from diffusion tensor imaging studies was lower fractional anisotropy in the corpus callosum. Proton magnetic resonance spectroscopy studies are few to date, but showed altered neurometabolic profiles in the frontal and parietal cortex, thalamus and dentate nuclei. Resting-state functional MRI studies reported reduced functional connectivity between cortical and deep grey matter structures. Discussion There is a critical gap in the literature of MRI studies in alcohol-exposed children under 5 years of age across all MRI modalities. The dynamic nature of brain maturation and appreciation of the effects of alcohol exposure on the developing trajectory of the structural and functional network argue for the prioritisation of studies that include a longitudinal approach to understanding this spectrum of effects and potential therapeutic time points.

Deep ensemble learning of sparse regression models for brain disease diagnosis.

PubMed

Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

2017-04-01

Recent studies on brain imaging analysis witnessed the core roles of machine learning techniques in computer-assisted intervention for brain disease diagnosis. Of various machine-learning techniques, sparse regression models have proved their effectiveness in handling high-dimensional data but with a small number of training samples, especially in medical problems. In the meantime, deep learning methods have been making great successes by outperforming the state-of-the-art performances in various applications. In this paper, we propose a novel framework that combines the two conceptually different methods of sparse regression and deep learning for Alzheimer's disease/mild cognitive impairment diagnosis and prognosis. Specifically, we first train multiple sparse regression models, each of which is trained with different values of a regularization control parameter. Thus, our multiple sparse regression models potentially select different feature subsets from the original feature set; thereby they have different powers to predict the response values, i.e., clinical label and clinical scores in our work. By regarding the response values from our sparse regression models as target-level representations, we then build a deep convolutional neural network for clinical decision making, which thus we call 'Deep Ensemble Sparse Regression Network.' To our best knowledge, this is the first work that combines sparse regression models with deep neural network. In our experiments with the ADNI cohort, we validated the effectiveness of the proposed method by achieving the highest diagnostic accuracies in three classification tasks. We also rigorously analyzed our results and compared with the previous studies on the ADNI cohort in the literature. Copyright © 2017 Elsevier B.V. All rights reserved.

Deep ensemble learning of sparse regression models for brain disease diagnosis

PubMed Central

Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

2018-01-01

Recent studies on brain imaging analysis witnessed the core roles of machine learning techniques in computer-assisted intervention for brain disease diagnosis. Of various machine-learning techniques, sparse regression models have proved their effectiveness in handling high-dimensional data but with a small number of training samples, especially in medical problems. In the meantime, deep learning methods have been making great successes by outperforming the state-of-the-art performances in various applications. In this paper, we propose a novel framework that combines the two conceptually different methods of sparse regression and deep learning for Alzheimer’s disease/mild cognitive impairment diagnosis and prognosis. Specifically, we first train multiple sparse regression models, each of which is trained with different values of a regularization control parameter. Thus, our multiple sparse regression models potentially select different feature subsets from the original feature set; thereby they have different powers to predict the response values, i.e., clinical label and clinical scores in our work. By regarding the response values from our sparse regression models as target-level representations, we then build a deep convolutional neural network for clinical decision making, which thus we call ‘ Deep Ensemble Sparse Regression Network.’ To our best knowledge, this is the first work that combines sparse regression models with deep neural network. In our experiments with the ADNI cohort, we validated the effectiveness of the proposed method by achieving the highest diagnostic accuracies in three classification tasks. We also rigorously analyzed our results and compared with the previous studies on the ADNI cohort in the literature. PMID:28167394

Deep brain stimulation and treatment-resistant obsessive-compulsive disorder: A systematic review.

PubMed

Vázquez-Bourgon, Javier; Martino, Juan; Sierra Peña, María; Infante Ceberio, Jon; Martínez Martínez, M Ángeles; Ocón, Roberto; Menchón, José Manuel; Crespo Facorro, Benedicto; Vázquez-Barquero, Alfonso

2017-07-01

At least 10% of patients with Obsessive-compulsive Disorder (OCD) are refractory to psychopharmacological treatment. The emergence of new technologies for the modulation of altered neuronal activity in Neurosurgery, deep brain stimulation (DBS), has enabled its use in severe and refractory OCD cases. The objective of this article is to review the current scientific evidence on the effectiveness and applicability of this technique to refractory OCD. We systematically reviewed the literature to identify the main characteristics of deep brain stimulation, its use and applicability as treatment for obsessive-compulsive disorder. Therefore, we reviewed PubMed/Medline, Embase and PsycINFO databases, combining the key-words 'Deep brain stimulation', 'DBS' and 'Obsessive-compulsive disorder' 'OCS'. The articles were selected by two of the authors independently, based on the abstracts, and if they described any of the main characteristics of the therapy referring to OCD: applicability; mechanism of action; brain therapeutic targets; efficacy; side-effects; co-therapies. All the information was subsequently extracted and analysed. The critical analysis of the evidence shows that the use of DBS in treatment-resistant OCD is providing satisfactory results regarding efficacy, with assumable side-effects. However, there is insufficient evidence to support the use of any single brain target over another. Patient selection has to be done following analyses of risks/benefits, being advisable to individualize the decision of continuing with concomitant psychopharmacological and psychological treatments. The use of DBS is still considered to be in the field of research, although it is increasingly used in refractory-OCD, producing in the majority of studies significant improvements in symptomatology, and in functionality and quality of life. It is essential to implement random and controlled studies regarding its long-term efficacy, cost-risk analyses and cost/benefit. Copyright © 2017 SEP y SEPB. Publicado por Elsevier España, S.L.U. All rights reserved.

Longitudinal atlas for normative human brain development and aging over the lifespan using quantitative susceptibility mapping.

PubMed

Zhang, Yuyao; Wei, Hongjiang; Cronin, Matthew J; He, Naying; Yan, Fuhua; Liu, Chunlei

2018-05-01

Longitudinal brain atlases play an important role in the study of human brain development and cognition. Existing atlases are mainly based on anatomical features derived from T1-and T2-weighted MRI. A 4D developmental quantitative susceptibility mapping (QSM) atlas may facilitate the estimation of age-related iron changes in deep gray matter nuclei and myelin changes in white matter. To this end, group-wise co-registered QSM templates were generated over various age intervals from age 1-83 years old. Registration was achieved by combining both T1-weighted and QSM images. Based on the proposed template, we created an accurate deep gray matter nuclei parcellation map (DGM map). Notably, we segmented thalamus into 5 sub-regions, i.e. the anterior nuclei, the median nuclei, the lateral nuclei, the pulvinar and the internal medullary lamina. Furthermore, we built a "whole brain QSM parcellation map" by combining existing cortical parcellation and white-matter atlases with the proposed DGM map. Based on the proposed QSM atlas, the segmentation accuracy of iron-rich nuclei using QSM is significantly improved, especially for children and adolescent subjects. The age-related progression of magnetic susceptibility in each of the deep gray matter nuclei, the hippocampus, and the amygdala was estimated. Our automated atlas-based analysis provided a systematic confirmation of previous findings on susceptibility progression with age resulting from manual ROI drawings in deep gray matter nuclei. The susceptibility development in the hippocampus and the amygdala follow an iron accumulation model; while in the thalamus sub-regions, the susceptibility development exhibits a variety of trends. It is envisioned that the newly developed 4D QSM atlas will serve as a template for studying brain iron deposition and myelination/demyelination in both normal aging and various brain diseases. Copyright © 2018 Elsevier Inc. All rights reserved.

MRI assessment of whole-brain structural changes in aging.

PubMed

Guo, Hui; Siu, William; D'Arcy, Ryan Cn; Black, Sandra E; Grajauskas, Lukas A; Singh, Sonia; Zhang, Yunting; Rockwood, Kenneth; Song, Xiaowei

2017-01-01

One of the central features of brain aging is the accumulation of multiple age-related structural changes, which occur heterogeneously in individuals and can have immediate or potential clinical consequences. Each of these deficits can coexist and interact, producing both independent and additive impacts on brain health. Many of the changes can be visualized using MRI. To collectively assess whole-brain structural changes, the MRI-based Brain Atrophy and Lesion Index (BALI) has been developed. In this study, we validate this whole-brain health assessment approach using several clinical MRI examinations. Data came from three independent studies: the Alzheimer's Disease Neuroimaging Initiative Phase II (n=950; women =47.9%; age =72.7±7.4 years); the National Alzheimer's Coordinating Center (n=722; women =55.1%; age =72.7±9.9 years); and the Tianjin Medical University General Hospital Research database on older adults (n=170; women =60.0%; age =62.9±9.3 years). The 3.0-Tesla MRI scans were evaluated using the BALI rating scheme on the basis of T1-weighted (T1WI), T2-weighted (T2WI), T2-weighted fluid-attenuated inversion recovery (T2-FLAIR), and T2*-weighted gradient-recalled echo (T2*GRE) images. Atrophy and lesion changes were commonly seen in each MRI test. The BALI scores based on different sequences were highly correlated (Spearman r 2 >0.69; P <0.00001). They were associated with age ( r 2 >0.29; P <0.00001) and differed by cognitive status ( χ 2 >26.48, P <0.00001). T2-FLAIR revealed a greater level of periventricular ( χ 2 =29.09) and deep white matter ( χ 2 =26.65, P <0.001) lesions than others, but missed revealing certain dilated perivascular spaces that were seen in T2WI ( P <0.001). Microhemorrhages occurred in 15.3% of the sample examined and were detected using only T2*GRE. The T1WI- and T2WI-based BALI evaluations consistently identified the burden of aging and dementia-related decline of structural brain health. Inclusion of additional MRI tests increased lesion differentiation. Further research is to integrate MRI tests for a clinical tool to aid the diagnosis and intervention of brain aging.

Monitoring brain temperature by time-resolved near-infrared spectroscopy: pilot study

NASA Astrophysics Data System (ADS)

Bakhsheshi, Mohammad Fazel; Diop, Mamadou; St. Lawrence, Keith; Lee, Ting-Yim

2014-05-01

Mild hypothermia (HT) is an effective neuroprotective strategy for a variety of acute brain injuries. However, the wide clinical adaptation of HT has been hampered by the lack of a reliable noninvasive method for measuring brain temperature, since core measurements have been shown to not always reflect brain temperature. The goal of this work was to develop a noninvasive optical technique for measuring brain temperature that exploits both the temperature dependency of water absorption and the high concentration of water in brain (80%-90%). Specifically, we demonstrate the potential of time-resolved near-infrared spectroscopy (TR-NIRS) to measure temperature in tissue-mimicking phantoms (in vitro) and deep brain tissue (in vivo) during heating and cooling, respectively. For deep brain tissue temperature monitoring, experiments were conducted on newborn piglets wherein hypothermia was induced by gradual whole body cooling. Brain temperature was concomitantly measured by TR-NIRS and a thermocouple probe implanted in the brain. Our proposed TR-NIRS method was able to measure the temperature of tissue-mimicking phantoms and brain tissues with a correlation of 0.82 and 0.66 to temperature measured with a thermometer, respectively. The mean difference between the TR-NIRS and thermometer measurements was 0.15°C±1.1°C for the in vitro experiments and 0.5°C±1.6°C for the in vivo measurements.

Sensing deep extreme environments: the receptor cell types, brain centers, and multi-layer neural packaging of hydrothermal vent endemic worms.

PubMed

Shigeno, Shuichi; Ogura, Atsushi; Mori, Tsukasa; Toyohara, Haruhiko; Yoshida, Takao; Tsuchida, Shinji; Fujikura, Katsunori

2014-01-01

Deep-sea alvinellid worm species endemic to hydrothermal vents, such as Alvinella and Paralvinella, are considered to be among the most thermotolerant animals known with their adaptability to toxic heavy metals, and tolerance of highly reductive and oxidative stressful environments. Despite the number of recent studies focused on their overall transcriptomic, proteomic, and metabolic stabilities, little is known regarding their sensory receptor cells and electrically active neuro-processing centers, and how these can tolerate and function in such harsh conditions. We examined the extra- and intracellular organizations of the epidermal ciliated sensory cells and their higher centers in the central nervous system through immunocytochemical, ultrastructural, and neurotracing analyses. We observed that these cells were rich in mitochondria and possessed many electron-dense granules, and identified specialized glial cells and serial myelin-like repeats in the head sensory systems of Paralvinella hessleri. Additionally, we identified the major epidermal sensory pathways, in which a pair of distinct mushroom bodies-like or small interneuron clusters was observed. These sensory learning and memory systems are commonly found in insects and annelids, but the alvinellid inputs are unlikely derived from the sensory ciliary cells of the dorsal head regions. Our evidence provides insight into the cellular and system-wide adaptive structure used to sense, process, and combat the deep-sea hydrothermal vent environment. The alvinellid sensory cells exhibit characteristics of annelid ciliary types, and among the most unique features were the head sensory inputs and structure of the neural cell bodies of the brain, which were surrounded by multiple membranes. We speculated that such enhanced protection is required for the production of normal electrical signals, and to avoid the breakdown of the membrane surrounding metabolically fragile neurons from oxidative stress. Such pivotal acquisition is not broadly found in the all body parts, suggesting the head sensory inputs are specific, and these heterogenetic protection mechanisms may be present in alvinellid worms.

Brain activity monitoring by compressed spectral array during deep hypothermic circulatory arrest in acute aortic dissection surgery.

PubMed

Urbanowicz, Tomasz K; Budniak, Wiktor; Buczkowski, Piotr; Perek, Bartłomiej; Walczak, Maciej; Tomczyk, Jadwiga; Katarzyński, Sławomir; Jemielity, Marek

2014-12-01

Monitoring the central nervous system during aortic dissection repair may improve the understanding of the intraoperative changes related to its bioactivity. The aim of the study was to evaluate the influence of deep hypothermia on intraoperative brain bioactivity measured by the compressed spectral array (CSA) method and to assess the influence of the operations on postoperative cognitive function. The study enrolled 40 patients (31 men and 9 women) at the mean age of 60.2 ± 8.6 years, diagnosed with acute aortic dissection. They underwent emergency operations in deep hypothermic circulatory arrest (DHCA). During the operations, brain bioactivity was monitored with the compressed spectral array method. There were no intraoperative deaths. Electrocerebral silence during DHCA was observed in 31 patients (74%). The lowest activity was observed during DHCA: it was 0.01 ± 0.05 nW in the left hemisphere and 0.01 ± 0.03 nW in the right hemisphere. The postoperative results of neurological tests deteriorated statistically significantly (26.9 ± 1.7 points vs. 22.0 ± 1.7 points; p < 0.001), especially among patients who exhibited brain activity during DHCA. The compressed spectral array method is clinically useful in monitoring brain bioactivity during emergency operations of acute aortic dissections. Electrocerebral silence occurs in 75% of patients during DHCA. The cognitive function of patients deteriorates significantly after operations with DHCA.

Deep brain stimulation reveals emotional impact processing in ventromedial prefrontal cortex.

PubMed

Gjedde, Albert; Geday, Jacob

2009-12-07

We tested the hypothesis that modulation of monoaminergic tone with deep-brain stimulation (DBS) of subthalamic nucleus would reveal a site of reactivity in the ventromedial prefrontal cortex that we previously identified by modulating serotonergic and noradrenergic mechanisms by blocking serotonin-noradrenaline reuptake sites. We tested the hypothesis in patients with Parkinson's disease in whom we had measured the changes of blood flow everywhere in the brain associated with the deep brain stimulation of the subthalamic nucleus. We determined the emotional reactivity of the patients as the average impact of emotive images rated by the patients off the DBS. We then searched for sites in the brain that had significant correlation of the changes of blood flow with the emotional impact rated by the patients. The results indicate a significant link between the emotional impact when patients are not stimulated and the change of blood flow associated with the DBS. In subjects with a low emotional impact, activity measured as blood flow rose when the electrode was turned on, while in subjects of high impact, the activity at this site in the ventromedial prefrontal cortex declined when the electrode was turned on. We conclude that changes of neurotransmission in the ventromedial prefrontal cortex had an effect on the tissue that depends on changes of monoamine concentration interacting with specific combinations of inhibitory and excitatory monoamine receptors.

Deep brain stimulation for psychiatric disorders: where we are now.

PubMed

Cleary, Daniel R; Ozpinar, Alp; Raslan, Ahmed M; Ko, Andrew L

2015-06-01

Fossil records showing trephination in the Stone Age provide evidence that humans have sought to influence the mind through physical means since before the historical record. Attempts to treat psychiatric disease via neurosurgical means in the 20th century provided some intriguing initial results. However, the indiscriminate application of these treatments, lack of rigorous evaluation of the results, and the side effects of ablative, irreversible procedures resulted in a backlash against brain surgery for psychiatric disorders that continues to this day. With the advent of psychotropic medications, interest in invasive procedures for organic brain disease waned. Diagnosis and classification of psychiatric diseases has improved, due to a better understanding of psychiatric patho-physiology and the development of disease and treatment biomarkers. Meanwhile, a significant percentage of patients remain refractory to multiple modes of treatment, and psychiatric disease remains the number one cause of disability in the world. These data, along with the safe and efficacious application of deep brain stimulation (DBS) for movement disorders, in principle a reversible process, is rekindling interest in the surgical treatment of psychiatric disorders with stimulation of deep brain sites involved in emotional and behavioral circuitry. This review presents a brief history of psychosurgery and summarizes the development of DBS for psychiatric disease, reviewing the available evidence for the current application of DBS for disorders of the mind.

Long-range correlation properties in timing of skilled piano performance: the influence of auditory feedback and deep brain stimulation.

PubMed

Herrojo Ruiz, María; Hong, Sang Bin; Hennig, Holger; Altenmüller, Eckart; Kühn, Andrea A

2014-01-01

Unintentional timing deviations during musical performance can be conceived of as timing errors. However, recent research on humanizing computer-generated music has demonstrated that timing fluctuations that exhibit long-range temporal correlations (LRTC) are preferred by human listeners. This preference can be accounted for by the ubiquitous presence of LRTC in human tapping and rhythmic performances. Interestingly, the manifestation of LRTC in tapping behavior seems to be driven in a subject-specific manner by the LRTC properties of resting-state background cortical oscillatory activity. In this framework, the current study aimed to investigate whether propagation of timing deviations during the skilled, memorized piano performance (without metronome) of 17 professional pianists exhibits LRTC and whether the structure of the correlations is influenced by the presence or absence of auditory feedback. As an additional goal, we set out to investigate the influence of altering the dynamics along the cortico-basal-ganglia-thalamo-cortical network via deep brain stimulation (DBS) on the LRTC properties of musical performance. Specifically, we investigated temporal deviations during the skilled piano performance of a non-professional pianist who was treated with subthalamic-deep brain stimulation (STN-DBS) due to severe Parkinson's disease, with predominant tremor affecting his right upper extremity. In the tremor-affected right hand, the timing fluctuations of the performance exhibited random correlations with DBS OFF. By contrast, DBS restored long-range dependency in the temporal fluctuations, corresponding with the general motor improvement on DBS. Overall, the present investigations demonstrate the presence of LRTC in skilled piano performances, indicating that unintentional temporal deviations are correlated over a wide range of time scales. This phenomenon is stable after removal of the auditory feedback, but is altered by STN-DBS, which suggests that cortico-basal ganglia-thalamocortical circuits play a role in the modulation of the serial correlations of timing fluctuations exhibited in skilled musical performance.

What is dorso-lateral in the subthalamic Nucleus (STN)?--a topographic and anatomical consideration on the ambiguous description of today's primary target for deep brain stimulation (DBS) surgery.

PubMed

Coenen, Volker A; Prescher, Andreas; Schmidt, Thorsten; Picozzi, Piero; Gielen, Frans L H

2008-11-01

The most frequently used target for DBS in advanced Parkinson Disease (PD) is the sensorimotor subthalamic nucleus (STN), anatomically referred to as dorso-lateral STN [3]. Ambiguities arise, regarding the true meaning of this description in the STN. Does "dorsal" indicate posterior or superior? At its best, this definition assigns two directions in space to a three-dimensional structure. This paper evaluates the ambiguity and describes the sensorimotor part of the STN in stereotactic space.

Literature-Related Discovery (LRD)

DTIC Science & Technology

2007-11-01

accepted) water purification literature. The annular region between the inner and outer circles represents literatures related directly and...procedures (thalamotomy and pallidotomy) destroy regions of the brain that produce the uncontrolled spasmodic movements in PD patients [11]. A...more recent procedure, deep brain stimulation, sends electricity through a probe to normalize electrical activity in the brain region , reversing the

75 FR 4407 - The Neurological Devices Panel of the Medical Devices Advisory Committee; Notice of Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-27

... premarket approval application for the Deep Brain Stimulation System for Epilepsy sponsored by Medtronic...-onset seizures (affecting only a part of the brain when they begin), with or without secondary... a partial-onset seizure that later spreads to the whole brain. ``Refractory'' to antiepileptic...

A deep convolutional neural network-based automatic delineation strategy for multiple brain metastases stereotactic radiosurgery

PubMed Central

Stojadinovic, Strahinja; Hrycushko, Brian; Wardak, Zabi; Lau, Steven; Lu, Weiguo; Yan, Yulong; Jiang, Steve B.; Zhen, Xin; Timmerman, Robert; Nedzi, Lucien

2017-01-01

Accurate and automatic brain metastases target delineation is a key step for efficient and effective stereotactic radiosurgery (SRS) treatment planning. In this work, we developed a deep learning convolutional neural network (CNN) algorithm for segmenting brain metastases on contrast-enhanced T1-weighted magnetic resonance imaging (MRI) datasets. We integrated the CNN-based algorithm into an automatic brain metastases segmentation workflow and validated on both Multimodal Brain Tumor Image Segmentation challenge (BRATS) data and clinical patients' data. Validation on BRATS data yielded average DICE coefficients (DCs) of 0.75±0.07 in the tumor core and 0.81±0.04 in the enhancing tumor, which outperformed most techniques in the 2015 BRATS challenge. Segmentation results of patient cases showed an average of DCs 0.67±0.03 and achieved an area under the receiver operating characteristic curve of 0.98±0.01. The developed automatic segmentation strategy surpasses current benchmark levels and offers a promising tool for SRS treatment planning for multiple brain metastases. PMID:28985229

Brain tumor segmentation in multi-spectral MRI using convolutional neural networks (CNN).

PubMed

Iqbal, Sajid; Ghani, M Usman; Saba, Tanzila; Rehman, Amjad

2018-04-01

A tumor could be found in any area of the brain and could be of any size, shape, and contrast. There may exist multiple tumors of different types in a human brain at the same time. Accurate tumor area segmentation is considered primary step for treatment of brain tumors. Deep Learning is a set of promising techniques that could provide better results as compared to nondeep learning techniques for segmenting timorous part inside a brain. This article presents a deep convolutional neural network (CNN) to segment brain tumors in MRIs. The proposed network uses BRATS segmentation challenge dataset which is composed of images obtained through four different modalities. Accordingly, we present an extended version of existing network to solve segmentation problem. The network architecture consists of multiple neural network layers connected in sequential order with the feeding of Convolutional feature maps at the peer level. Experimental results on BRATS 2015 benchmark data thus show the usability of the proposed approach and its superiority over the other approaches in this area of research. © 2018 Wiley Periodicals, Inc.

'I'm worried about getting water in the holes in my head': A phenomenological psychology case study of the experience of undergoing deep brain stimulation surgery for Parkinson's disease.

PubMed

Eatough, Virginia; Shaw, Karen

2017-02-01

Deep brain stimulation (DBS) is a form of biotechnological surgery which has had considerable success for the motor improvement of Parkinson's disease and related disorders. Paradoxically, this observed motor improvement is not matched with improved psychosocial adjustment. This study contributes to a small but growing body of research aiming to understand this paradox. We conclude by discussing these aspects from a phenomenological and health psychology understanding of decision-making, human affectivity, and embodiment. A hermeneutic phenomenological case study. Semi-structured interviews with one woman with Parkinson's disease were carried out paying particular attention to (1) how the decision to have the procedure was made and (2) the affective experience in the time periods immediately prior to the procedure, shortly after and 1 month later. The thematic structure derived from the hermeneutic phenomenological analysis comprises the following experiential aspects: Making the decision: 'I was feeling rather at a dead end with my Parkinson's'; Shifting emotions and feelings: 'Terrified, excited, disappointed, overjoyed'; Embodied meaning: 'This extraordinary procedure where they were going to drill holes in my head'. This research has elucidated the complexity of decision-making, the emotional landscape, and specific bodily nature of the experience of DBS. It has suggested implications for practice informed by both existential-phenomenological theory and health psychology. Statement of contribution What is already known on this subject? Deep brain stimulation (DBS) is a newly developed form of biotechnological surgery and research indicates a mismatch between motor success and psychosocial adjustment. Most studies focuses on life post-DBS and there is relatively little research on how people make the decision to have the procedure, what their experience is of undergoing it including its emotional aspects. What does this study add? This study demonstrates that making decisions with respect to health and illness is complex and best understood as a form of embodied cognition. Findings indicate that the experience of undergoing DBS surgery is one of multiple emotions, especially fear and feelings of 'unhomelikeness'. This study highlights the relevance of a lifeworld, people-centered and humanizing approach to helping health care professionals support people through an illness/treatment trajectory. © 2016 The British Psychological Society.

Detailed Magnetic Resonance Imaging (MRI) Analysis in Infantile Spasms.

PubMed

Harini, Chellamani; Sharda, Sonal; Bergin, Ann Marie; Poduri, Annapurna; Yuskaitis, Christopher J; Peters, Jurriaan M; Rakesh, Kshitiz; Kapur, Kush; Pearl, Phillip L; Prabhu, Sanjay P

2018-05-01

To evaluate initial magnetic resonance imaging (MRI) abnormalities in infantile spasms, correlate them to clinical characteristics, and describe repeat imaging findings. A retrospective review of infantile spasm patients was conducted, classifying abnormal MRI into developmental, acquired, and nonspecific subgroups. MRIs were abnormal in 52 of 71 infantile spasm patients (23 developmental, 23 acquired, and 6 nonspecific) with no correlation to the clinical infantile spasm characteristics. Both developmental and acquired subgroups exhibited cortical gray and/or white matter abnormalities. Additional abnormalities of deep gray structures, brain stem, callosum, and volume loss occurred in the structural acquired subgroup. Repeat MRI showed better definition of the extent of existing malformations. In structural infantile spasms, developmental/acquired subgroups showed differences in pattern of MRI abnormalities but did not correlate with clinical characteristics.

Closed geometric models in medical applications

NASA Astrophysics Data System (ADS)

Jagannathan, Lakshmipathy; Nowinski, Wieslaw L.; Raphel, Jose K.; Nguyen, Bonnie T.

1996-04-01

Conventional surface fitting methods give twisted surfaces and complicates capping closures. This is a typical character of surfaces that lack rectangular topology. We suggest an algorithm which overcomes these limitations. The analysis of the algorithm is presented with experimental results. This algorithm assumes the mass center lying inside the object. Both capping closure and twisting are results of inadequate information on the geometric proximity of the points and surfaces which are proximal in the parametric space. Geometric proximity at the contour level is handled by mapping the points along the contour onto a hyper-spherical space. The resulting angular gradation with respect to the centroid is monotonic and hence avoids the twisting problem. Inter-contour geometric proximity is achieved by partitioning the point set based on the angle it makes with the respective centroids. Avoidance of capping complications is achieved by generating closed cross curves connecting curves which are reflections about the abscissa. The method is of immense use for the generation of the deep cerebral structures and is applied to the deep structures generated from the Schaltenbrand- Wahren brain atlas.

In vivo mapping of current density distribution in brain tissues during deep brain stimulation (DBS)

NASA Astrophysics Data System (ADS)

Sajib, Saurav Z. K.; Oh, Tong In; Kim, Hyung Joong; Kwon, Oh In; Woo, Eung Je

2017-01-01

New methods for in vivo mapping of brain responses during deep brain stimulation (DBS) are indispensable to secure clinical applications. Assessment of current density distribution, induced by internally injected currents, may provide an alternative method for understanding the therapeutic effects of electrical stimulation. The current flow and pathway are affected by internal conductivity, and can be imaged using magnetic resonance-based conductivity imaging methods. Magnetic resonance electrical impedance tomography (MREIT) is an imaging method that can enable highly resolved mapping of electromagnetic tissue properties such as current density and conductivity of living tissues. In the current study, we experimentally imaged current density distribution of in vivo canine brains by applying MREIT to electrical stimulation. The current density maps of three canine brains were calculated from the measured magnetic flux density data. The absolute current density values of brain tissues, including gray matter, white matter, and cerebrospinal fluid were compared to assess the active regions during DBS. The resulting current density in different tissue types may provide useful information about current pathways and volume activation for adjusting surgical planning and understanding the therapeutic effects of DBS.

Symptoms and Treatment | NIH MedlinePlus the Magazine

MedlinePlus

... of this page please turn JavaScript on. Feature: Parkinson's Disease Symptoms and Treatment Past Issues / Winter 2016 Table ... study to identify abnormal brain rhythms associated with Parkinson's disease. Photo courtesy of Coralie de Hemptinne Deep Brain ...

Recurrent, Delayed Hemorrhage Associated with Edoxaban after Deep Brain Stimulation Lead Placement

PubMed Central

Garber, Sarah T.; Schrock, Lauren E.; House, Paul A.

2013-01-01

Factor-Xa inhibitors like edoxaban have been shown to have comparable or superior rates of stroke and systemic embolization prevention to warfarin while exhibiting lower clinically significant bleeding rates. The authors report a case of a man who presented with delayed, recurrent intracranial hemorrhage months after successful deep brain stimulator placement for Parkinson disease while on edoxaban for atrial fibrillation. Further reports on the use of novel anticoagulants after intracranial surgery are acutely needed to help assess the true relative risk they pose. PMID:23365773

Current Topics in Deep Brain Stimulation for Parkinson Disease

PubMed Central

UMEMURA, Atsushi; OYAMA, Genko; SHIMO, Yasushi; NAKAJIMA, Madoka; NAKAJIMA, Asuka; JO, Takayuki; SEKIMOTO, Satoko; ITO, Masanobu; MITSUHASHI, Takumi; HATTORI, Nobutaka; ARAI, Hajime

2016-01-01

There is a long history of surgical treatment for Parkinson disease (PD). After pioneering trials and errors, the current primary surgical treatment for PD is deep brain stimulation (DBS). DBS is a promising treatment option for patients with medically refractory PD. However, there are still many problems and controversies associated with DBS. In this review, we discuss current issues in DBS for PD, including patient selection, clinical outcomes, complications, target selection, long-term outcomes, management of axial symptoms, timing of surgery, surgical procedures, cost-effectiveness, and new technology. PMID:27349658

Stridor and dysphagia associated with subthalamic nucleus stimulation in Parkinson disease.

PubMed

Fagbami, Oluwakemi Y; Donato, Anthony A

2011-11-01

Refractory symptoms in Parkinson disease show good response to deep brain stimulation (DBS). This procedure improves United Parkinson's Disease Rating Scale scores and reduces dyskinesias, whereas speech and swallowing dysfunction typically do not improve and may even worsen. Rarely, DBS can cause idiosyncratic dystonias of muscle groups, including those of the neck and throat. The authors describe a patient experiencing stridor and dysphagia with confirmed pulmonary restriction and aspiration following subthalamic nucleus deep brain stimulator adjustment, with a resolution of symptoms and signs when the stimulator was switched off.

Deep Brain Stimulation using Magnetic Fields

NASA Astrophysics Data System (ADS)

Jiles, David; Williams, Paul; Crowther, Lawrence; Iowa State University Team; Wolfson CentreMagnetics Team

2011-03-01

New applications for transcranial magnetic stimulation are developing rapidly for both diagnostic and therapeutic purposes. Therefore so is the demand for improved performance, particularly in terms of their ability to stimulate deeper regions of the brain and to do so selectively. The coil designs that are used presently are limited in their ability to stimulate the brain at depth and with high spatial focality. Consequently, any improvement in coil performance would have a significant impact in extending the usefulness of TMS in both clinical applications and academic research studies. New and improved coil designs have then been developed, modeled and tested as a result of this work. A large magnetizing coil, 300mm in diameter and compatible with a commercial TMS system has been constructed to determine its feasibility for use as a deep brain stimulator. The results of this work have suggested directions that could be pursued in order to further improve the coil designs.

Deep sequencing reveals persistence of cell-associated mumps vaccine virus in chronic encephalitis.

PubMed

Morfopoulou, Sofia; Mee, Edward T; Connaughton, Sarah M; Brown, Julianne R; Gilmour, Kimberly; Chong, W K 'Kling'; Duprex, W Paul; Ferguson, Deborah; Hubank, Mike; Hutchinson, Ciaran; Kaliakatsos, Marios; McQuaid, Stephen; Paine, Simon; Plagnol, Vincent; Ruis, Christopher; Virasami, Alex; Zhan, Hong; Jacques, Thomas S; Schepelmann, Silke; Qasim, Waseem; Breuer, Judith

2017-01-01

Routine childhood vaccination against measles, mumps and rubella has virtually abolished virus-related morbidity and mortality. Notwithstanding this, we describe here devastating neurological complications associated with the detection of live-attenuated mumps virus Jeryl Lynn (MuV JL5 ) in the brain of a child who had undergone successful allogeneic transplantation for severe combined immunodeficiency (SCID). This is the first confirmed report of MuV JL5 associated with chronic encephalitis and highlights the need to exclude immunodeficient individuals from immunisation with live-attenuated vaccines. The diagnosis was only possible by deep sequencing of the brain biopsy. Sequence comparison of the vaccine batch to the MuV JL5 isolated from brain identified biased hypermutation, particularly in the matrix gene, similar to those found in measles from cases of SSPE. The findings provide unique insights into the pathogenesis of paramyxovirus brain infections.

Temporally Coordinated Deep Brain Stimulation in the Dorsal and Ventral Striatum Synergistically Enhances Associative Learning.

PubMed

Katnani, Husam A; Patel, Shaun R; Kwon, Churl-Su; Abdel-Aziz, Samer; Gale, John T; Eskandar, Emad N

2016-01-04

The primate brain has the remarkable ability of mapping sensory stimuli into motor behaviors that can lead to positive outcomes. We have previously shown that during the reinforcement of visual-motor behavior, activity in the caudate nucleus is correlated with the rate of learning. Moreover, phasic microstimulation in the caudate during the reinforcement period was shown to enhance associative learning, demonstrating the importance of temporal specificity to manipulate learning related changes. Here we present evidence that extends upon our previous finding by demonstrating that temporally coordinated phasic deep brain stimulation across both the nucleus accumbens and caudate can further enhance associative learning. Monkeys performed a visual-motor associative learning task and received stimulation at time points critical to learning related changes. Resulting performance revealed an enhancement in the rate, ceiling, and reaction times of learning. Stimulation of each brain region alone or at different time points did not generate the same effect.

Deep Brain Stimulation

PubMed Central

Lyketsos, Constantine G.; Pendergrass, Jo Cara; Lozano, Andres M.

2012-01-01

Recent studies have identified an association between memory deficits and defects of the integrated neuronal cortical areas known collectively as the default mode network. It is conceivable that the amyloid deposition or other molecular abnormalities seen in patients with Alzheimer’s disease may interfere with this network and disrupt neuronal circuits beyond the localized brain areas. Therefore, Alzheimer’s disease may be both a degenerative disease and a broader system-level disorder affecting integrated neuronal pathways involved in memory. In this paper, we describe the rationale and provide some evidence to support the study of deep brain stimulation of the hippocampal fornix as a novel treatment to improve neuronal circuitry within these integrated networks and thereby sustain memory function in early Alzheimer’s disease. PMID:23346514

Sapphire implant based neuro-complex for deep-lying brain tumors phototheranostics

NASA Astrophysics Data System (ADS)

Sharova, A. S.; Maklygina, YU S.; Yusubalieva, G. M.; Shikunova, I. A.; Kurlov, V. N.; Loschenov, V. B.

2018-01-01

The neuro-complex as a combination of sapphire implant optical port and osteoplastic biomaterial "Collapan" as an Aluminum phthalocyanine nanoform photosensitizer (PS) depot was developed within the framework of this study. The main goals of such neuro-complex are to provide direct access of laser radiation to the brain tissue depth and to transfer PS directly to the pathological tissue location that will allow multiple optical phototheranostics of the deep-lying tumor region without repeated surgical intervention. The developed complex spectral-optical properties research was carried out by photodiagnostics method using the model sample: a brain tissue phantom. The optical transparency of sapphire implant allows obtaining a fluorescent signal with high accuracy, comparable to direct measurement "in contact" with the tissue.

Deep brain stimulation of nucleus accumbens region in alcoholism affects reward processing.

PubMed

Heldmann, Marcus; Berding, Georg; Voges, Jürgen; Bogerts, Bernhard; Galazky, Imke; Müller, Ulf; Baillot, Gunther; Heinze, Hans-Jochen; Münte, Thomas F

2012-01-01

The influence of bilateral deep brain stimulation (DBS) of the nucleus nucleus (NAcc) on the processing of reward in a gambling paradigm was investigated using H(2)[(15)O]-PET (positron emission tomography) in a 38-year-old man treated for severe alcohol addiction. Behavioral data analysis revealed a less risky, more careful choice behavior under active DBS compared to DBS switched off. PET showed win- and loss-related activations in the paracingulate cortex, temporal poles, precuneus and hippocampus under active DBS, brain areas that have been implicated in action monitoring and behavioral control. Except for the temporal pole these activations were not seen when DBS was deactivated. These findings suggest that DBS of the NAcc may act partially by improving behavioral control.

Deep intracerebral (basal ganglia) haematomas in fatal non-missile head injury in man.

PubMed Central

Adams, J H; Doyle, D; Graham, D I; Lawrence, A E; McLellan, D R

1986-01-01

Deep intracerebral (basal ganglia) haematomas were found post mortem in 63 of 635 fatal non-missile head injuries. In patients with a basal ganglia haematoma, contusions were more severe, there was a reduced incidence of a lucid interval, and there was an increased incidence of road traffic accidents, gliding contusions and diffuse axonal injury than in patients without this type of haematoma. Intracranial haematoma is usually thought to be a secondary event, that is a complication of the original injury, but these results suggest that a deep intracerebral haematoma is a primary event. If a deep intracerebral haematoma is identified on an early CT scan it is likely that the patient has sustained severe diffuse brain damage at the time of injury. In the majority of head injuries damage to blood vessels or axons predominates. In patients with a traumatic deep intracerebral haematoma, it would appear that the deceleration/acceleration forces are such that both axons and blood vessels within the brain are damaged at the time of injury. Images PMID:3760892

Schaltenbrand-Wahren-Talairach-Tournoux brain atlas registration

NASA Astrophysics Data System (ADS)

Nowinski, Wieslaw L.; Fang, Anthony; Nguyen, Bonnie T.

1995-04-01

The CIeMed electronic brain atlas system contains electronic versions of multiple paper brain atlases with 3D extensions; some other 3D brain atlases are under development. Its primary goal is to provide automatic labeling and quantification of brains. The atlas data are digitized, enhanced, color coded, labeled, and organized into volumes. The atlas system provides several tools for registration, 3D display and real-time manipulation, object extraction/editing, quantification, image processing and analysis, reformatting, anatomical index operations, and file handling. The two main stereotactic atlases provided by the system are electronic and enhanced versions of Atlas of Stereotaxy of the Human Brain by Schaltenbrand and Wahren and Co-Planar Stereotactic Atlas of the Human Brain by Talairach and Tournoux. Each of these atlases has its own strengths and their combination has several advantages. First, a complementary information is merged and provided to the user. Second, the user can register data with a single atlas only, as the Schaltenbrand-Wahren-Talairach-Tournoux registration is data-independent. And last but not least, a direct registration of the Schaltenbrand-Wahren microseries with MRI data may not be feasible, since cerebral deep structures are usually not clearly discernible on MRI images. This paper addresses registration of the Schaltenbrand- Wahren and Talairach-Tournoux brain atlases. A modified proportional grid system transformation is introduced and suitable sets of landmarks identifiable in both atlases are defined. The accuracy of registration is discussed. A continuous navigation in the multi- atlas/patient data space is presented.

Perioperative Brain Shift and Deep Brain Stimulating Electrode Deformation Analysis: Implications for rigid and non-rigid devices

PubMed Central

Sillay, Karl A.; Kumbier, L. M.; Ross, C.; Brady, M.; Alexander, A.; Gupta, A.; Adluru, N.; Miranpuri, G. S.; Williams, J. C.

2016-01-01

Deep brain stimulation (DBS) efficacy is related to optimal electrode placement. Several authors have quantified brain shift related to surgical targeting; yet, few reports document and discuss the effects of brain shift after insertion. Objective: To quantify brain shift and electrode displacement after device insertion. Twelve patients were retrospectively reviewed, and one post-operative MRI and one time-delayed CT were obtained for each patient and their implanted electrodes modeled in 3D. Two competing methods were employed to measure the electrode tip location and deviation from the prototypical linear implant after the resolution of acute surgical changes, such as brain shift and pneumocephalus. In the interim between surgery and a pneumocephalus free postoperative scan, electrode deviation was documented in all patients and all electrodes. Significant shift of the electrode tip was identified in rostral, anterior, and medial directions (p < 0.05). Shift was greatest in the rostral direction, measuring an average of 1.41 mm. Brain shift and subsequent electrode displacement occurs in patients after DBS surgery with the reversal of intraoperative brain shift. Rostral displacement is on the order of the height of one DBS contact. Further investigation into the time course of intraoperative brain shift and its potential effects on procedures performed with rigid and non-rigid devices in supine and semi-sitting surgical positions is needed. PMID:23010803

Evidence of Neurobiological Changes in the Presymptomatic PINK1 Knockout Rat.

PubMed

Ferris, Craig F; Morrison, Thomas R; Iriah, Sade; Malmberg, Samantha; Kulkarni, Praveen; Hartner, Jochen C; Trivedi, Malav

2018-01-01

Genetic models of Parkinson's disease (PD) coupled with advanced imaging techniques can elucidate neurobiological disease progression, and can help identify early biomarkers before clinical signs emerge. PTEN-induced putative kinase 1 (PINK1) helps protect neurons from mitochondrial dysfunction, and a mutation in the associated gene is a risk factor for recessive familial PD. The PINK1 knockout (KO) rat is a novel model for familial PD that has not been neuroradiologically characterized for alterations in brain structure/function, alongside behavior, prior to 4 months of age. To identify biomarkers of presymptomatic PD in the PINK1 -/- rat at 3 months using magnetic resonance imaging techniques. At postnatal weeks 12-13; one month earlier than previously reported signs of motor and cognitive dysfunction, this study combined imaging modalities, including assessment of quantitative anisotropy across 171 individual brain areas using an annotated MRI rat brain atlas to identify sites of gray matter alteration between wild-type and PINK1 -/- rats. The olfactory system, hypothalamus, thalamus, nucleus accumbens, and cerebellum showed differences in anisotropy between experimental groups. Molecular analyses revealed reduced levels of glutathione, ATP, and elevated oxidative stress in the substantia nigra, striatum and deep cerebellar nuclei. Mitochondrial genes encoding proteins in Complex IV, along with mRNA levels associated with mitochondrial function and genes involved in glutathione synthesis were reduced. Differences in brain structure did not align with any cognitive or motor impairment. These data reveal early markers, and highlight novel brain regions involved in the pathology of PD in the PINK1 -/- rat before behavioral dysfunction occurs.

Music mnemonics aid Verbal Memory and Induce Learning – Related Brain Plasticity in Multiple Sclerosis

PubMed Central

Thaut, Michael H.; Peterson, David A.; McIntosh, Gerald C.; Hoemberg, Volker

2014-01-01

Recent research on music and brain function has suggested that the temporal pattern structure in music and rhythm can enhance cognitive functions. To further elucidate this question specifically for memory, we investigated if a musical template can enhance verbal learning in patients with multiple sclerosis (MS) and if music-assisted learning will also influence short-term, system-level brain plasticity. We measured systems-level brain activity with oscillatory network synchronization during music-assisted learning. Specifically, we measured the spectral power of 128-channel electroencephalogram (EEG) in alpha and beta frequency bands in 54 patients with MS. The study sample was randomly divided into two groups, either hearing a spoken or a musical (sung) presentation of Rey’s auditory verbal learning test. We defined the “learning-related synchronization” (LRS) as the percent change in EEG spectral power from the first time the word was presented to the average of the subsequent word encoding trials. LRS differed significantly between the music and the spoken conditions in low alpha and upper beta bands. Patients in the music condition showed overall better word memory and better word order memory and stronger bilateral frontal alpha LRS than patients in the spoken condition. The evidence suggests that a musical mnemonic recruits stronger oscillatory network synchronization in prefrontal areas in MS patients during word learning. It is suggested that the temporal structure implicit in musical stimuli enhances “deep encoding” during verbal learning and sharpens the timing of neural dynamics in brain networks degraded by demyelination in MS. PMID:24982626

Staging of cortical and deep grey matter functional connectivity changes in multiple sclerosis.

PubMed

Meijer, Kim A; Eijlers, Anand J C; Geurts, Jeroen J G; Schoonheim, Menno M

2018-02-01

Functional connectivity is known to increase as well as decrease throughout the brain in multiple sclerosis (MS), which could represent different stages of the disease. In addition, functional connectivity changes could follow the atrophy pattern observed with disease progression, that is, moving from the deep grey matter towards the cortex. This study investigated when and where connectivity changes develop and explored their clinical and cognitive relevance across different MS stages. A cohort of 121 patients with early relapsing-remitting MS (RRMS), 122 with late RRMS and 53 with secondary progressive MS (SPMS) as well as 96 healthy controls underwent MRI and neuropsychological testing. Functional connectivity changes were investigated for (1) within deep grey matter connectivity, (2) connectivity between the deep grey matter and cortex and (3) within-cortex connectivity. A post hoc regional analysis was performed to identify which regions were driving the connectivity changes. Patients with late RRMS and SPMS showed increased connectivity of the deep grey matter, especially of the putamen and palladium, with other deep grey matter structures and with the cortex. Within-cortex connectivity was decreased, especially for temporal, occipital and frontal regions, but only in SPMS relative to early RRMS. Deep grey matter connectivity alterations were related to cognition and disability, whereas within-cortex connectivity was only related to disability. Increased connectivity of the deep grey matter became apparent in late RRMS and further increased in SPMS. The additive effect of cortical network degeneration, which was only seen in SPMS, may explain the sudden clinical deterioration characteristic to this phase of the disease. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

MR-Guided Unfocused Ultrasound Disruption of the Rat Blood-Brain Barrier

NASA Astrophysics Data System (ADS)

Townsend, Kelly A.; King, Randy L.; Zaharchuk, Greg; Pauly, Kim Butts

2011-09-01

Therapeutic ultrasound with microbubbles can temporarily disrupt the blood-brain barrier (BBB) for drug delivery. Contrast-enhanced MRI (CE-MRI) can visualize gadolinium passage into the brain, indicating BBB opening. Previous studies used focused ultrasound, which is appropriate for the targeted delivery of drugs. The purpose of this study was to investigate unfocused ultrasound for BBB opening across the whole brain. In 10 rats, gadolinium-based MR contrast agent (Gd; 0.25 ml) was administered concurrent with ultrasound microbubbles (Optison, 0.25 ml) and circulated for 20 sec before sonication. A 753 kHz planar PZT transducer, diameter 1.8 cm, sonicated each rat brain with supplied voltage of 300, 400, or 500 mVpp for 10 sec in continuous wave mode, or at 500 mVpp at 20% duty cycle at 10 Hz for 30-300 sec. After sonication, coronal T1-weighted FSE CE-MRI images were acquired with a 3in surface coil. The imaging protocol was repeated 3-5 times after treatment. One control animal was given Gd and microbubbles, but not sonicated, and the other was given Gd and sonicated without microbubbles. Signal change in ROIs over the muscle, mesencephalon/ventricles, and the cortex/striatum were measured at 3-5 time points up to 36 min after sonication. Signal intensity was converted to % signal change compared to the initial image. In the controls, CE-MRI showed brightening of surrounding structures, but not the brain. In the continuous wave subjects, cortex/striatum signal did not increase, but ventricle/mesenchephalon signal did. Those that received pulsed sonications showed signal increases in both the cortex/striatum and ventricles/mesenchephalon. In conclusion, after pulsed unfocused ultrasound sonication, the BBB is disrupted across the whole brain, including cortex and deep grey matter, while continuous wave sonication affects only the ventricles and possibly deeper structures, without opening the cortex BBB. As time passes, the timeline of Gd passage into the brain can be visualized.

Cavitation of deep lacunar infarcts in patients with first-ever lacunar stroke: a 2-year follow-up study with MR.

PubMed

Loos, Caroline M J; Staals, Julie; Wardlaw, Joanna M; van Oostenbrugge, Robert J

2012-08-01

Studies in patients with lacunar stroke often assess the number of lacunes. However, data on how many symptomatic lacunar infarcts cavitate into a lacune are limited. We assessed the evolution of symptomatic lacunar infarcts over 2-year follow-up. In 82 patients with first-ever lacunar stroke with a lacunar infarct in the deep brain regions (excluding the centrum semiovale), we performed a brain MR at presentation and 2 years later. We classified cavitation of lacunar infarcts at baseline and on follow-up MR as absent, incomplete, or complete. We recorded time to imaging, infarct size, and vascular risk factors. On baseline MR, 38 (46%) index infarcts showed complete or incomplete cavitation. Median time to imaging was 8 (0-73) days in noncavitated and 63 (1-184) days in cavitated lesions (P<0.05). On follow-up imaging, 94% of the lacunar infarcts were completely or incompletely cavitated, most had reduced in diameter, and 5 (6%) had disappeared. Vascular risk factors were not associated with cavitation. Cavitation and lesion shrinkage were seen in almost all symptomatic lacunar infarcts in the deep brain regions over 2-year follow-up. Counting lacunes in these specific regions at a random moment might slightly, however not substantially, underestimate the burden of deep lacunar infarction.

Human hippocampus associates information in memory

PubMed Central

Henke, Katharina; Weber, Bruno; Kneifel, Stefan; Wieser, Heinz Gregor; Buck, Alfred

1999-01-01

The hippocampal formation, one of the most complex and vulnerable brain structures, is recognized as a crucial brain area subserving human long-term memory. Yet, its specific functions in memory are controversial. Recent experimental results suggest that the hippocampal contribution to human memory is limited to episodic memory, novelty detection, semantic (deep) processing of information, and spatial memory. We measured the regional cerebral blood flow by positron-emission tomography while healthy volunteers learned pairs of words with different learning strategies. These led to different forms of learning, allowing us to test the degree to which they challenge hippocampal function. Neither novelty detection nor depth of processing activated the hippocampal formation as much as semantically associating the primarily unrelated words in memory. This is compelling evidence for another function of the human hippocampal formation in memory: establishing semantic associations. PMID:10318979

Spectrally Resolved Fiber Photometry for Multi-component Analysis of Brain Circuits.

PubMed

Meng, Chengbo; Zhou, Jingheng; Papaneri, Amy; Peddada, Teja; Xu, Karen; Cui, Guohong

2018-04-25

To achieve simultaneous measurement of multiple cellular events in molecularly defined groups of neurons in vivo, we designed a spectrometer-based fiber photometry system that allows for spectral unmixing of multiple fluorescence signals recorded from deep brain structures in behaving animals. Using green and red Ca 2+ indicators differentially expressed in striatal direct- and indirect-pathway neurons, we were able to simultaneously monitor the neural activity in these two pathways in freely moving animals. We found that the activities were highly synchronized between the direct and indirect pathways within one hemisphere and were desynchronized between the two hemispheres. We further analyzed the relationship between the movement patterns and the magnitude of activation in direct- and indirect-pathway neurons and found that the striatal direct and indirect pathways coordinately control the dynamics and fate of movement. Published by Elsevier Inc.

Does the use of thiopental provide added cerebral protection during deep hypothermic circulatory arrest?

PubMed Central

Al-Hashimi, Sara; Zaman, Mahvash; Waterworth, Paul; Bilal, Haris

2013-01-01

A best evidence topic in cardiac surgery was written according to a structured protocol. The question addressed was: Does the use of thiopental provide added cerebral protection during deep hypothermic circulatory arrest (DHCA)? Altogether, more than 62 papers were found using the reported search, of which 7 represented the best evidence to answer the clinical question. The authors, journal, date and country of publication, patient group studied, study type, relevant outcomes and results of these papers are tabulated. Four of the seven papers used thiopental alongside other neuroprotective methods and agents. The methods included the use of ice packs to the head and core systemic hypothermia. Agents used alongside thiopental included nicardipine and mannitol. Thiopental was found to have the ability to lower oxygen consumption, where oxygen consumption was measured using the phosphocreatinine and adenosine triphosphate ratio. The neuroprotective effect of thiopental was evaluated by assessing the electrical activity of the brain during circulatory arrest, by which it was shown to be advantageous. However, other trials suggested that adding thiopental during circulatory arrest did not provide any extra protection to the brain. The timing of thiopental administration is of importance in order to gain positive outcomes, as it's ability to lower the cerebral energy state may result in unfavourable results if added before hypothermic circulatory arrest, where this may lead to an ischaemic event. We conclude that the use of thiopental during deep hypothermic circulatory arrest is beneficial, but if administered too early, it may replete the cerebral energy state before arrest and prove to be detrimental. PMID:23644730

Does the use of thiopental provide added cerebral protection during deep hypothermic circulatory arrest?

PubMed

Al-Hashimi, Sara; Zaman, Mahvash; Waterworth, Paul; Bilal, Haris

2013-08-01

A best evidence topic in cardiac surgery was written according to a structured protocol. The question addressed was: Does the use of thiopental provide added cerebral protection during deep hypothermic circulatory arrest (DHCA)? Altogether, more than 62 papers were found using the reported search, of which 7 represented the best evidence to answer the clinical question. The authors, journal, date and country of publication, patient group studied, study type, relevant outcomes and results of these papers are tabulated. Four of the seven papers used thiopental alongside other neuroprotective methods and agents. The methods included the use of ice packs to the head and core systemic hypothermia. Agents used alongside thiopental included nicardipine and mannitol. Thiopental was found to have the ability to lower oxygen consumption, where oxygen consumption was measured using the phosphocreatinine and adenosine triphosphate ratio. The neuroprotective effect of thiopental was evaluated by assessing the electrical activity of the brain during circulatory arrest, by which it was shown to be advantageous. However, other trials suggested that adding thiopental during circulatory arrest did not provide any extra protection to the brain. The timing of thiopental administration is of importance in order to gain positive outcomes, as it's ability to lower the cerebral energy state may result in unfavourable results if added before hypothermic circulatory arrest, where this may lead to an ischaemic event. We conclude that the use of thiopental during deep hypothermic circulatory arrest is beneficial, but if administered too early, it may replete the cerebral energy state before arrest and prove to be detrimental.

Reconfigurable visible nanophotonic switch for optogenetic applications (Conference Presentation)

NASA Astrophysics Data System (ADS)

Mohanty, Aseema; Li, Qian; Tadayon, Mohammad Amin; Bhatt, Gaurang R.; Cardenas, Jaime; Miller, Steven A.; Kepecs, Adam; Lipson, Michal

2017-02-01

High spatiotemporal resolution deep-brain optical excitation for optogenetics would enable activation of specific neural populations and in-depth study of neural circuits. Conventionally, a single fiber is used to flood light into a large area of the brain with limited resolution. The scalability of silicon photonics could enable neural excitation over large areas with single-cell resolution similar to electrical probes. However, active control of these optical circuits has yet to be demonstrated for optogenetics. Here we demonstrate the first active integrated optical switch for neural excitation at 473 nm, enabling control of multiple beams for deep-brain neural stimulation. Using a silicon nitride waveguide platform, we develop a cascaded Mach-Zehnder interferometer (MZI) network located outside the brain to direct light to 8 different grating emitters located at the tip of the neural probe. We use integrated platinum microheaters to induce a local thermo-optic phase shift in the MZI to control the switch output. We measure an ON/OFF extinction ratio of >8dB for a single switch and a switching speed of 20 microseconds. We characterize the optical output of the switch by imaging its excitation of fluorescent dye. Finally, we demonstrate in vivo single-neuron optical activation from different grating emitters using a fully packaged device inserted into a mouse brain. Directly activated neurons showed robust spike firing activities with low first-spike latency and small jitter. Active switching on a nanophotonic platform is necessary for eventually controlling highly-multiplexed reconfigurable optical circuits, enabling high-resolution optical stimulation in deep-brain regions.

Deep Convolutional Neural Networks for Multi-Modality Isointense Infant Brain Image Segmentation

PubMed Central

Zhang, Wenlu; Li, Rongjian; Deng, Houtao; Wang, Li; Lin, Weili; Ji, Shuiwang; Shen, Dinggang

2015-01-01

The segmentation of infant brain tissue images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) plays an important role in studying early brain development in health and disease. In the isointense stage (approximately 6–8 months of age), WM and GM exhibit similar levels of intensity in both T1 and T2 MR images, making the tissue segmentation very challenging. Only a small number of existing methods have been designed for tissue segmentation in this isointense stage; however, they only used a single T1 or T2 images, or the combination of T1 and T2 images. In this paper, we propose to use deep convolutional neural networks (CNNs) for segmenting isointense stage brain tissues using multi-modality MR images. CNNs are a type of deep models in which trainable filters and local neighborhood pooling operations are applied alternatingly on the raw input images, resulting in a hierarchy of increasingly complex features. Specifically, we used multimodality information from T1, T2, and fractional anisotropy (FA) images as inputs and then generated the segmentation maps as outputs. The multiple intermediate layers applied convolution, pooling, normalization, and other operations to capture the highly nonlinear mappings between inputs and outputs. We compared the performance of our approach with that of the commonly used segmentation methods on a set of manually segmented isointense stage brain images. Results showed that our proposed model significantly outperformed prior methods on infant brain tissue segmentation. In addition, our results indicated that integration of multi-modality images led to significant performance improvement. PMID:25562829

Multimodal investigation of epileptic networks: The case of insular cortex epilepsy.

PubMed

Zerouali, Y; Ghaziri, J; Nguyen, D K

2016-01-01

The insula is a deep cortical structure sharing extensive synaptic connections with a variety of brain regions, including several frontal, temporal, and parietal structures. The identification of the insular connectivity network is obviously valuable for understanding a number of cognitive processes, but also for understanding epilepsy since insular seizures involve a number of remote brain regions. Ultimately, knowledge of the structure and causal relationships within the epileptic networks associated with insular cortex epilepsy can offer deeper insights into this relatively neglected type of epilepsy enabling the refining of the clinical approach in managing patients affected by it. In the present chapter, we first review the multimodal noninvasive tests performed during the presurgical evaluation of epileptic patients with drug refractory focal epilepsy, with particular emphasis on their value for the detection of insular cortex epilepsy. Second, we review the emerging multimodal investigation techniques in the field of epilepsy, that aim to (1) enhance the detection of insular cortex epilepsy and (2) unveil the architecture and causal relationships within epileptic networks. We summarize the results of these approaches with emphasis on the specific case of insular cortex epilepsy. © 2016 Elsevier B.V. All rights reserved.

Anatomical and Functional Images of in vitro and in vivo Tissues by NIR Time-domain Diffuse Optical Tomography

NASA Astrophysics Data System (ADS)

Zhao, Huijuan; Gao, Feng; Tanikawa, Yukari; Homma, Kazuhiro; Onodera, Yoichi; Yamada, Yukio

Near infra-red (NIR) diffuse optical tomography (DOT) has gained much attention and it will be clinically applied to imaging breast, neonatal head, and the hemodynamics of the brain because of its noninvasiveness and deep penetration in biological tissue. Prior to achieving the imaging of infant brain using DOT, the developed methodologies need to be experimentally justified by imaging some real organs with simpler structures. Here we report our results of an in vitro chicken leg and an in vivo exercising human forearm from the data measured by a multi-channel time-resolved NIR system. Tomographic images were reconstructed by a two-dimensional image reconstruction algorithm based on a modified generalized pulse spectrum technique for simultaneous reconstruction of the µa and µs´. The absolute µa- and µs´-images revealed the inner structures of the chicken leg and the forearm, where the bones were clearly distinguished from the muscle. The Δµa-images showed the blood volume changes during the forearm exercise, proving that the system and the image reconstruction algorithm could potentially be used for imaging not only the anatomic structure but also the hemodynamics in neonatal heads.

Role of deep brain stimulation in modulating memory formation and recall

PubMed Central

Hu, Rollin; Eskandar, Emad; Williams, Ziv

2010-01-01

Deep brain stimulation (DBS) has become an increasingly popular tool for treating a variety of medically refractory neurological and psychiatric disorders such as Parkinson disease, essential tremor, depression, and obsessive-compulsive disorder. Several targets have been identified for ablation or stimulation based on their anatomical location and presumed function. Areas such as the subthalamic nucleus, globus pallidus, and thalamus, for example, are believed to play a key role in motor control and execution, and they are commonly used in the treatment of motor disorders. Limbic structures such as the cingulate cortex and ventral striatum, believed to be important in motivation, emotion, and higher cognition, have also been targeted for treatment of a number of psychiatric disorders. In all of these settings, DBS is largely aimed at addressing the deleterious aspects of these diseases. In Parkinson disease, for example, DBS has been used to reduce rigidity and tremor, whereas in obsessive-compulsive disorder it has been used to limit compulsive behavior. More recently, however, attention has also turned to the potential use of DBS for enhancing or improving otherwise nonpathological aspects of cognitive function. This review explores the potential role of DBS in augmenting memory formation and recall, and the authors discuss recent studies and future trends in this emerging field. PMID:19569891

Effect of socioeconomic status (SES) disparity on neural development in female African-American infants at age 1 month.

PubMed

Betancourt, Laura M; Avants, Brian; Farah, Martha J; Brodsky, Nancy L; Wu, Jue; Ashtari, Manzar; Hurt, Hallam

2016-11-01

There is increasing interest in both the cumulative and long-term impact of early life adversity on brain structure and function, especially as the brain is both highly vulnerable and highly adaptive during childhood. Relationships between SES and neural development have been shown in children older than age 2 years. Less is known regarding the impact of SES on neural development in children before age 2. This paper examines the effect of SES, indexed by income-to-needs (ITN) and maternal education, on cortical gray, deep gray, and white matter volumes in term, healthy, appropriate for gestational age, African-American, female infants. At 5 weeks postnatal age, unsedated infants underwent MRI (3.0T Siemens Verio scanner, 32-channel head coil). Images were segmented based on a locally constructed template. Utilizing hierarchical linear regression, SES effects on MRI volumes were examined. In this cohort of healthy African-American female infants of varying SES, lower SES was associated with smaller cortical gray and deep gray matter volumes. These SES effects on neural outcome at such a young age build on similar studies of older children, suggesting that the biological embedding of adversity may occur very early in development. © 2015 John Wiley & Sons Ltd.

Assessing neurosurgical non-technical skills: an exploratory study of a new behavioural marker system.

PubMed

Michinov, Estelle; Jamet, Eric; Dodeler, Virginie; Haegelen, Claire; Jannin, Pierre

2014-10-01

The management of non-technical skills is a major factor affecting teamwork quality and patient safety. This article presents a behavioural marker system for assessing neurosurgical non-technical skills (BMS-NNTS). We tested the BMS during deep brain stimulation surgery. We developed the BMS in three stages. First, we drew up a provisional assessment tool based on the literature and observation tools developed for other surgical specialties. We then analysed videos made in an operating room (OR) during deep brain stimulation operations in order to ensure there were no significant omissions from the skills list. Finally, we used five videos of operations to identify the behavioural markers of non-technical skills in verbal communications. Analyses of more than six hours of observations revealed 3515 behaviours from which we determined the neurosurgeon's non-technical skills behaviour pattern. The neurosurgeon frequently engaged in explicit coordination, situation awareness and leadership behaviours. In addition, the neurosurgeon's behaviours differed according to the stage of the operation and the OR staff members with whom she was communicating. Our behavioural marker system provides a structured approach to assessing non-technical skills in the field of neurosurgery. It can also be transferred to other surgical specialties and used in surgeon training curricula. © 2014 John Wiley & Sons, Ltd.

Deep brain stimulation of the dorsal anterior cingulate cortex for the treatment of chronic neuropathic pain.

PubMed

Russo, Jennifer F; Sheth, Sameer A

2015-06-01

Chronic neuropathic pain is estimated to affect 3%-4.5% of the worldwide population. It is associated with significant loss of productive time, withdrawal from the workforce, development of mood disorders such as depression and anxiety, and disruption of family and social life. Current medical therapeutics often fail to adequately treat chronic neuropathic pain. Deep brain stimulation (DBS) targeting subcortical structures such as the periaqueductal gray, the ventral posterior lateral and medial thalamic nuclei, and the internal capsule has been investigated for the relief of refractory neuropathic pain over the past 3 decades. Recent work has identified the dorsal anterior cingulate cortex (dACC) as a new potential neuromodulation target given its central role in cognitive and affective processing. In this review, the authors briefly discuss the history of DBS for chronic neuropathic pain in the United States and present evidence supporting dACC DBS for this indication. They review existent literature on dACC DBS and summarize important findings from imaging and neurophysiological studies supporting a central role for the dACC in the processing of chronic neuropathic pain. The available neurophysiological and empirical clinical evidence suggests that dACC DBS is a viable therapeutic option for the treatment of chronic neuropathic pain and warrants further investigation.

Fiber-based tunable repetition rate source for deep tissue two-photon fluorescence microscopy.

PubMed

Charan, Kriti; Li, Bo; Wang, Mengran; Lin, Charles P; Xu, Chris

2018-05-01

Deep tissue multiphoton imaging requires high peak power to enhance signal and low average power to prevent thermal damage. Both goals can be advantageously achieved through laser repetition rate tuning instead of simply adjusting the average power. We show that the ideal repetition rate for deep two-photon imaging in the mouse brain is between 1 and 10 MHz, and we present a fiber-based source with an arbitrarily tunable repetition rate within this range. The performance of the new source is compared to a mode-locked Ti:Sapphire (Ti:S) laser for in vivo imaging of mouse brain vasculature. At 2.5 MHz, the fiber source requires 5.1 times less average power to obtain the same signal as a standard Ti:S laser operating at 80 MHz.

An electrophysiological investigation of memory encoding, depth of processing, and word frequency in humans.

PubMed

Guo, Chunyan; Zhu, Ying; Ding, Jinhong; Fan, Silu; Paller, Ken A

2004-02-12

Memory encoding can be studied by monitoring brain activity correlated with subsequent remembering. To understand brain potentials associated with encoding, we compared multiple factors known to affect encoding. Depth of processing was manipulated by requiring subjects to detect animal names (deep encoding) or boldface (shallow encoding) in a series of Chinese words. Recognition was more accurate with deep than shallow encoding, and for low- compared to high-frequency words. Potentials were generally more positive for subsequently recognized versus forgotten words; for deep compared to shallow processing; and, for remembered words only, for low- than for high-frequency words. Latency and topographic differences between these potentials suggested that several factors influence the effectiveness of encoding and can be distinguished using these methods, even with Chinese logographic symbols.

Brain changes due to hypoxia during light anaesthesia can be prevented by deepening anaesthesia; a study in rats

PubMed Central

Kalmar, Alain F.; Doorduin, Janine; Struys, Michel M. R. F.; Schoemaker, Regien G.; Absalom, Anthony R.

2018-01-01

In anaesthetic practice the risk of cerebral ischemic/hypoxic damage is thought to be attenuated by deep anaesthesia. The rationale is that deeper anaesthesia reduces cerebral oxygen demand more than light anaesthesia, thereby increasing the tolerance to ischemia or hypoxia. However, evidence to support this is scarce. We thus investigated the influence of light versus deep anaesthesia on the responses of rat brains to a period of hypoxia. In the first experiment we exposed adult male Wistar rats to deep or light propofol anaesthesia and then performed [18F]- Fludeoxyglucose (FDG) Positron Emission Tomography (PET) scans to verify the extent of cerebral metabolic suppression. In subsequent experiments, rats were subjected to light/deep propofol anaesthesia and then exposed to a period of hypoxia or ongoing normoxia (n = 9–11 per group). A further 5 rats, not exposed to anaesthesia or hypoxia, served as controls. Four days later a Novel Object Recognition (NOR) test was performed to assess mood and cognition. After another 4 days, the animals were sacrificed for later immunohistochemical analyses of neurogenesis/neuroplasticity (Doublecortin; DCX), Brain Derived Neurotrophic Factor (BDNF) expression and neuroinflammation (Ionized calcium-binding adaptor protein-1; Iba-1) in hippocampal and piriform cortex slices. The hippocampi of rats subjected to hypoxia during light anaesthesia showed lower DCX positivity, and therefore lower neurogenesis, but higher BDNF levels and microglia hyper-ramification. Exploration was reduced, but no significant effect on NOR was observed. In the piriform cortex, higher DCX positivity was observed, associated with neuroplasticity. All these effects were attenuated by deep anaesthesia. Deepening anaesthesia attenuated the brain changes associated with hypoxia. Hypoxia during light anaesthesia had a prolonged effect on the brain, but no impairment in cognitive function was observed. Although reduced hippocampal neurogenesis may be considered unfavourable, higher BDNF expression, associated with microglia hyper-ramification may suggest activation of repair mechanisms. Increased neuroplasticity observed in the piriform cortex supports this, and might reflect a prolonged state of alertness rather than damage. PMID:29451906

Distinct roles of dopamine and subthalamic nucleus in learning and probabilistic decision making.

PubMed

Coulthard, Elizabeth J; Bogacz, Rafal; Javed, Shazia; Mooney, Lucy K; Murphy, Gillian; Keeley, Sophie; Whone, Alan L

2012-12-01

Even simple behaviour requires us to make decisions based on combining multiple pieces of learned and new information. Making such decisions requires both learning the optimal response to each given stimulus as well as combining probabilistic information from multiple stimuli before selecting a response. Computational theories of decision making predict that learning individual stimulus-response associations and rapid combination of information from multiple stimuli are dependent on different components of basal ganglia circuitry. In particular, learning and retention of memory, required for optimal response choice, are significantly reliant on dopamine, whereas integrating information probabilistically is critically dependent upon functioning of the glutamatergic subthalamic nucleus (computing the 'normalization term' in Bayes' theorem). Here, we test these theories by investigating 22 patients with Parkinson's disease either treated with deep brain stimulation to the subthalamic nucleus and dopaminergic therapy or managed with dopaminergic therapy alone. We use computerized tasks that probe three cognitive functions-information acquisition (learning), memory over a delay and information integration when multiple pieces of sequentially presented information have to be combined. Patients performed the tasks ON or OFF deep brain stimulation and/or ON or OFF dopaminergic therapy. Consistent with the computational theories, we show that stopping dopaminergic therapy impairs memory for probabilistic information over a delay, whereas deep brain stimulation to the region of the subthalamic nucleus disrupts decision making when multiple pieces of acquired information must be combined. Furthermore, we found that when participants needed to update their decision on the basis of the last piece of information presented in the decision-making task, patients with deep brain stimulation of the subthalamic nucleus region did not slow down appropriately to revise their plan, a pattern of behaviour that mirrors the impulsivity described clinically in some patients with subthalamic nucleus deep brain stimulation. Thus, we demonstrate distinct mechanisms for two important facets of human decision making: first, a role for dopamine in memory consolidation, and second, the critical importance of the subthalamic nucleus in successful decision making when multiple pieces of information must be combined.

Decoding of Human Movements Based on Deep Brain Local Field Potentials Using Ensemble Neural Networks

PubMed Central

2017-01-01

Decoding neural activities related to voluntary and involuntary movements is fundamental to understanding human brain motor circuits and neuromotor disorders and can lead to the development of neuromotor prosthetic devices for neurorehabilitation. This study explores using recorded deep brain local field potentials (LFPs) for robust movement decoding of Parkinson's disease (PD) and Dystonia patients. The LFP data from voluntary movement activities such as left and right hand index finger clicking were recorded from patients who underwent surgeries for implantation of deep brain stimulation electrodes. Movement-related LFP signal features were extracted by computing instantaneous power related to motor response in different neural frequency bands. An innovative neural network ensemble classifier has been proposed and developed for accurate prediction of finger movement and its forthcoming laterality. The ensemble classifier contains three base neural network classifiers, namely, feedforward, radial basis, and probabilistic neural networks. The majority voting rule is used to fuse the decisions of the three base classifiers to generate the final decision of the ensemble classifier. The overall decoding performance reaches a level of agreement (kappa value) at about 0.729 ± 0.16 for decoding movement from the resting state and about 0.671 ± 0.14 for decoding left and right visually cued movements. PMID:29201041

Deep brain stimulation for the treatment of uncommon tremor syndromes

PubMed Central

Ramirez-Zamora, Adolfo; Okun, Michael S.

2016-01-01

ABSTRACT Introduction: Deep brain stimulation (DBS) has become a standard therapy for the treatment of select cases of medication refractory essential tremor and Parkinson’s disease however the effectiveness and long-term outcomes of DBS in other uncommon and complex tremor syndromes has not been well established. Traditionally, the ventralis intermedius nucleus (VIM) of the thalamus has been considered the main target for medically intractable tremors; however alternative brain regions and improvements in stereotactic techniques and hardware may soon change the horizon for treatment of complex tremors. Areas covered: In this article, we conducted a PubMed search using different combinations between the terms ‘Uncommon tremors’, ‘Dystonic tremor’, ‘Holmes tremor’ ‘Midbrain tremor’, ‘Rubral tremor’, ‘Cerebellar tremor’, ‘outflow tremor’, ‘Multiple Sclerosis tremor’, ‘Post-traumatic tremor’, ‘Neuropathic tremor’, and ‘Deep Brain Stimulation/DBS’. Additionally, we examined and summarized the current state of evolving interventions for treatment of complex tremor syndromes. Expert c ommentary: Recently reported interventions for rare tremors include stimulation of the posterior subthalamic area, globus pallidus internus, ventralis oralis anterior/posterior thalamic subnuclei, and the use of dual lead stimulation in one or more of these targets. Treatment should be individualized and dictated by tremor phenomenology and associated clinical features. PMID:27228280

[Intervening in the neural basis of one's personality: a practice-oriented ethical analysis of neuropharmacology and deep-brain stimulation].

PubMed

Synofzik, M

2007-12-01

Through the rapid progress in neuropharmacology it seems to become possible to effectively improve our cognitive capacities and emotional states by easily applicable means. Moreover, deep-brain stimulation may allow an effective therapeutic option for those neurological and psychiatric diseases which still can not be sufficiently treated by pharmacological measures. So far, however, both the benefit and the harm of these techniques are only insufficiently understood by neuroscience and detailed ethical analyses are still missing. In this article ethical criteria and most recent empirical evidence are systematically brought together for the first time. This analysis shows that it is irrelevant for an ethical evaluation whether a drug or a brain-machine interface is categorized as "enhancement" or "treatment" or whether it changes "human nature". The only decisive criteria are whether the intervention (1.) benefits the patient, (2.) does not harm the patient and (3.) is desired by the patient. However, current empirical data in both fields, neuropharmacology and deep-brain stimulation are still too sparse to adequately evaluate these criteria. Moreover, the focus in both fields has been strongly misled by neglecting the distinction between "benefit" and "efficacy": In past years research and clinical practice have only focused on physiological effects, but not on the actual benefit to the patient.

Monitoring of deep brain temperature in infants using multi-frequency microwave radiometry and thermal modelling.

PubMed

Han, J W; Van Leeuwen, G M; Mizushina, S; Van de Kamer, J B; Maruyama, K; Sugiura, T; Azzopardi, D V; Edwards, A D

2001-07-01

In this study we present a design for a multi-frequency microwave radiometer aimed at prolonged monitoring of deep brain temperature in newborn infants and suitable for use during hypothermic neural rescue therapy. We identify appropriate hardware to measure brightness temperature and evaluate the accuracy of the measurements. We describe a method to estimate the tissue temperature distribution from measured brightness temperatures which uses the results of numerical simulations of the tissue temperature as well as the propagation of the microwaves in a realistic detailed three-dimensional infant head model. The temperature retrieval method is then used to evaluate how the statistical fluctuations in the measured brightness temperatures limit the confidence interval for the estimated temperature: for an 18 degrees C temperature differential between cooled surface and deep brain we found a standard error in the estimated central brain temperature of 0.75 degrees C. Evaluation of the systematic errors arising from inaccuracies in model parameters showed that realistic deviations in tissue parameters have little impact compared to uncertainty in the thickness of the bolus between the receiving antenna and the infant's head or in the skull thickness. This highlights the need to pay particular attention to these latter parameters in future practical implementation of the technique.

Gradient-based reliability maps for ACM-based segmentation of hippocampus.

PubMed

Zarpalas, Dimitrios; Gkontra, Polyxeni; Daras, Petros; Maglaveras, Nicos

2014-04-01

Automatic segmentation of deep brain structures, such as the hippocampus (HC), in MR images has attracted considerable scientific attention due to the widespread use of MRI and to the principal role of some structures in various mental disorders. In this literature, there exists a substantial amount of work relying on deformable models incorporating prior knowledge about structures' anatomy and shape information. However, shape priors capture global shape characteristics and thus fail to model boundaries of varying properties; HC boundaries present rich, poor, and missing gradient regions. On top of that, shape prior knowledge is blended with image information in the evolution process, through global weighting of the two terms, again neglecting the spatially varying boundary properties, causing segmentation faults. An innovative method is hereby presented that aims to achieve highly accurate HC segmentation in MR images, based on the modeling of boundary properties at each anatomical location and the inclusion of appropriate image information for each of those, within an active contour model framework. Hence, blending of image information and prior knowledge is based on a local weighting map, which mixes gradient information, regional and whole brain statistical information with a multi-atlas-based spatial distribution map of the structure's labels. Experimental results on three different datasets demonstrate the efficacy and accuracy of the proposed method.

Confocal microscopy for astrocyte in vivo imaging: Recycle and reuse in microscopy

PubMed Central

Pérez-Alvarez, Alberto; Araque, Alfonso; Martín, Eduardo D.

2013-01-01

In vivo imaging is one of the ultimate and fundamental approaches for the study of the brain. Two-photon laser scanning microscopy (2PLSM) constitutes the state-of-the-art technique in current neuroscience to address questions regarding brain cell structure, development and function, blood flow regulation and metabolism. This technique evolved from laser scanning confocal microscopy (LSCM), which impacted the field with a major improvement in image resolution of live tissues in the 1980s compared to widefield microscopy. While nowadays some of the unparalleled features of 2PLSM make it the tool of choice for brain studies in vivo, such as the possibility to image deep within a tissue, LSCM can still be useful in this matter. Here we discuss the validity and limitations of LSCM and provide a guide to perform high-resolution in vivo imaging of the brain of live rodents with minimal mechanical disruption employing LSCM. We describe the surgical procedure and experimental setup that allowed us to record intracellular calcium variations in astrocytes evoked by sensory stimulation, and to monitor intact neuronal dendritic spines and astrocytic processes as well as blood vessel dynamics. Therefore, in spite of certain limitations that need to be carefully considered, LSCM constitutes a useful, convenient, and affordable tool for brain studies in vivo. PMID:23658537

Assessing cortical and subcortical changes in a western diet mouse model using spectral/Fourier domain OCT (Conference Presentation)

NASA Astrophysics Data System (ADS)

Bernucci, Marcel T.; Norman, Jennifer E.; Merkle, Conrad W.; Aung, Hnin H.; Rutkowsky, Jennifer; Rutledge, John C.; Srinivasan, Vivek J.

2017-02-01

The Western diet, causative in the development of atherosclerotic cardiovascular disease, has recently been associated with the development of diffuse white matter disease (WMD) and other subcortical changes. Yet, little is known about the pathophysiological mechanisms by which a high-fat diet can cause WMD. Mechanistic studies of deep brain regions in mice have been challenging due to a lack of non-invasive, high-resolution, and deep imaging technologies. Here we used Optical Coherence Tomography to study mouse cortical/subcortical structures noninvasively and in vivo. To better understand the role of Western Diet in the development of WMD, intensity and Doppler flow OCT images, obtained using a 1300 nm spectral / Fourier domain OCT system, were used to observe the structural and functional alterations in the cortex and corpus callosum of Western Diet and control diet mouse models. Specifically, we applied segmentation to the OCT images to identify the boundaries of the cortex/corpus callosum, and further quantify the layer thicknesses across animals between the two diet groups. Furthermore, microvasculature alterations such as changes in spatiotemporal flow profiles within diving arterioles, arteriole diameter, and collateral tortuosity were analyzed. In the current study, while the arteriole vessel diameters between the two diet groups was comparable, we show that collateral tortuosity was significantly higher in the Western diet group, compared to control diet group, possibly indicating remodeling of brain vasculature due to dietary changes. Moreover, there is evidence showing that the corpus callosum is thinner in Western diet mice, indicative of tissue atrophy.

Potential subjects' responses to an ethics questionnaire in a phase I study of deep brain stimulation in early Parkinson's disease.

PubMed

Finder, Stuart G; Bliton, Mark J; Gill, Chandler E; Davis, Thomas L; Konrad, Peter E; Charles, P David

2012-01-01

Central to ethically justified clinical trial design is the need for an informed consent process responsive to how potential subjects actually comprehend study participation, especially study goals, risks, and potential benefits. This will be particularly challenging when studying deep brain stimulation and whether it impedes symptom progression in Parkinson's disease, since potential subjects will be Parkinson's patients for whom deep brain stimulation will likely have therapeutic value in the future as their disease progresses. As part of an expanded informed consent process for a pilot Phase I study of deep brain stimulation in early stage Parkinson's disease, an ethics questionnaire composed of 13 open-ended questions was distributed to potential subjects. The questionnaire was designed to guide potential subjects in thinking about their potential participation. While the purpose of the study (safety and tolerability) was extensively presented during the informed consent process, in returned responses 70 percent focused on effectiveness and 91 percent included personal benefit as poten- tial benefit from enrolling. However, 91 percent also indicated helping other Parkinson's patients as motivation when considering whether or not to enroll. This combination of responses highlights two issues to which investigators need to pay close attention in future trial designs: (1) how, and in what ways, informed consent processes reinforce potential subjects' preconceived understandings of benefit, and (2) that potential subjects see themselves as part of a community of Parkinson's sufferers with responsibilities extending beyond self-interest. More importantly, it invites speculation that a different paradigm for informed consent may be needed.

Deep Artificial Neural Networks and Neuromorphic Chips for Big Data Analysis: Pharmaceutical and Bioinformatics Applications

PubMed Central

Pastur-Romay, Lucas Antón; Cedrón, Francisco; Pazos, Alejandro; Porto-Pazos, Ana Belén

2016-01-01

Over the past decade, Deep Artificial Neural Networks (DNNs) have become the state-of-the-art algorithms in Machine Learning (ML), speech recognition, computer vision, natural language processing and many other tasks. This was made possible by the advancement in Big Data, Deep Learning (DL) and drastically increased chip processing abilities, especially general-purpose graphical processing units (GPGPUs). All this has created a growing interest in making the most of the potential offered by DNNs in almost every field. An overview of the main architectures of DNNs, and their usefulness in Pharmacology and Bioinformatics are presented in this work. The featured applications are: drug design, virtual screening (VS), Quantitative Structure–Activity Relationship (QSAR) research, protein structure prediction and genomics (and other omics) data mining. The future need of neuromorphic hardware for DNNs is also discussed, and the two most advanced chips are reviewed: IBM TrueNorth and SpiNNaker. In addition, this review points out the importance of considering not only neurons, as DNNs and neuromorphic chips should also include glial cells, given the proven importance of astrocytes, a type of glial cell which contributes to information processing in the brain. The Deep Artificial Neuron–Astrocyte Networks (DANAN) could overcome the difficulties in architecture design, learning process and scalability of the current ML methods. PMID:27529225

Toward an Integration of Deep Learning and Neuroscience

PubMed Central

Marblestone, Adam H.; Wayne, Greg; Kording, Konrad P.

2016-01-01

Neuroscience has focused on the detailed implementation of computation, studying neural codes, dynamics and circuits. In machine learning, however, artificial neural networks tend to eschew precisely designed codes, dynamics or circuits in favor of brute force optimization of a cost function, often using simple and relatively uniform initial architectures. Two recent developments have emerged within machine learning that create an opportunity to connect these seemingly divergent perspectives. First, structured architectures are used, including dedicated systems for attention, recursion and various forms of short- and long-term memory storage. Second, cost functions and training procedures have become more complex and are varied across layers and over time. Here we think about the brain in terms of these ideas. We hypothesize that (1) the brain optimizes cost functions, (2) the cost functions are diverse and differ across brain locations and over development, and (3) optimization operates within a pre-structured architecture matched to the computational problems posed by behavior. In support of these hypotheses, we argue that a range of implementations of credit assignment through multiple layers of neurons are compatible with our current knowledge of neural circuitry, and that the brain's specialized systems can be interpreted as enabling efficient optimization for specific problem classes. Such a heterogeneously optimized system, enabled by a series of interacting cost functions, serves to make learning data-efficient and precisely targeted to the needs of the organism. We suggest directions by which neuroscience could seek to refine and test these hypotheses. PMID:27683554

Developmental synchrony of thalamocortical circuits in the neonatal brain.

PubMed

Poh, Joann S; Li, Yue; Ratnarajah, Nagulan; Fortier, Marielle V; Chong, Yap-Seng; Kwek, Kenneth; Saw, Seang-Mei; Gluckman, Peter D; Meaney, Michael J; Qiu, Anqi

2015-08-01

The thalamus is a deep gray matter structure and consists of axonal fibers projecting to the entire cortex, which provide the anatomical support for its sensorimotor and higher-level cognitive functions. There is limited in vivo evidence on the normal thalamocortical development, especially in early life. In this study, we aimed to investigate the developmental patterns of the cerebral cortex, the thalamic substructures, and their connectivity with the cortex in the first few weeks of the postnatal brain. We hypothesized that there is developmental synchrony of the thalamus, its cortical projections, and corresponding target cortical structures. We employed diffusion tensor imaging (DTI) and divided the thalamus into five substructures respectively connecting to the frontal, precentral, postcentral, temporal, and parietal and occipital cortex. T2-weighted magnetic resonance imaging (MRI) was used to measure cortical thickness. We found age-related increases in cortical thickness of bilateral frontal cortex and left temporal cortex in the early postnatal brain. We also found that the development of the thalamic substructures was synchronized with that of their respective thalamocortical connectivity in the first few weeks of the postnatal life. In particular, the right thalamo-frontal substructure had the fastest growth in the early postnatal brain. Our study suggests that the distinct growth patterns of the thalamic substructures are in synchrony with those of the cortex in early life, which may be critical for the development of the cortical and subcortical functional specialization. Copyright © 2015 Elsevier Inc. All rights reserved.

Representational Distance Learning for Deep Neural Networks

PubMed Central

McClure, Patrick; Kriegeskorte, Nikolaus

2016-01-01

Deep neural networks (DNNs) provide useful models of visual representational transformations. We present a method that enables a DNN (student) to learn from the internal representational spaces of a reference model (teacher), which could be another DNN or, in the future, a biological brain. Representational spaces of the student and the teacher are characterized by representational distance matrices (RDMs). We propose representational distance learning (RDL), a stochastic gradient descent method that drives the RDMs of the student to approximate the RDMs of the teacher. We demonstrate that RDL is competitive with other transfer learning techniques for two publicly available benchmark computer vision datasets (MNIST and CIFAR-100), while allowing for architectural differences between student and teacher. By pulling the student's RDMs toward those of the teacher, RDL significantly improved visual classification performance when compared to baseline networks that did not use transfer learning. In the future, RDL may enable combined supervised training of deep neural networks using task constraints (e.g., images and category labels) and constraints from brain-activity measurements, so as to build models that replicate the internal representational spaces of biological brains. PMID:28082889

Stimulation of the bilateral anterior nuclei of the thalamus in the treatment of refractory epilepsy: two cases of subcortical band heterotopia.

PubMed

Franco, Ana; Pimentel, José; Campos, Alexandre Rainha; Morgado, Carlos; Pinelo, Sara; Ferreira, António Gonçalves; Bentes, Carla

2016-12-01

Subcortical band heterotopia is a neuronal migration disorder that may cause refractory epilepsy. In these patients, resective surgery has yielded inadequate results. Deep brain stimulation of the anterior nuclei of the thalamus has been used for the treatment of refractory epilepsy with good results. We describe the first two patients with subcortical band heterotopia who were submitted to deep brain stimulation of the anterior nuclei of the thalamus, with evaluation of seizure outcome after 12 and 18 months of follow-up. At these times, both showed a >50% decrease in seizure frequency and an increase in seizure freedom. Both patients had a depressive syndrome after surgery that responded fully to anti-depressive medication in one patient and partly in the other. In both, deep brain stimulation of the anterior nuclei of the thalamus was associated with good seizure outcome. This procedure can therefore be considered in the treatment of patients with subcortical band heterotopia and refractory epilepsy. Depression may be a transient adverse event of the surgery or stimulation, however, its aetiology is probably multifactorial.

Representational Distance Learning for Deep Neural Networks.

PubMed

McClure, Patrick; Kriegeskorte, Nikolaus

2016-01-01

Deep neural networks (DNNs) provide useful models of visual representational transformations. We present a method that enables a DNN (student) to learn from the internal representational spaces of a reference model (teacher), which could be another DNN or, in the future, a biological brain. Representational spaces of the student and the teacher are characterized by representational distance matrices (RDMs). We propose representational distance learning (RDL), a stochastic gradient descent method that drives the RDMs of the student to approximate the RDMs of the teacher. We demonstrate that RDL is competitive with other transfer learning techniques for two publicly available benchmark computer vision datasets (MNIST and CIFAR-100), while allowing for architectural differences between student and teacher. By pulling the student's RDMs toward those of the teacher, RDL significantly improved visual classification performance when compared to baseline networks that did not use transfer learning. In the future, RDL may enable combined supervised training of deep neural networks using task constraints (e.g., images and category labels) and constraints from brain-activity measurements, so as to build models that replicate the internal representational spaces of biological brains.

Neurostimulation for Drug-Resistant Epilepsy

PubMed Central

DeGiorgio, Christopher M.; Krahl, Scott E.

2013-01-01

Purpose of Review: The purpose of this review is to provide an evidence-based update on the neurostimulation options available for patients with drug-resistant epilepsy in the United States and in European countries. Recent Findings: The field of neurostimulation for epilepsy has grown dramatically since 1997, when vagus nerve stimulation became the first device to be approved for epilepsy by the US Food and Drug Administration (FDA). New data from recently completed randomized controlled trials are available for deep brain stimulation of the anterior thalamus, responsive neurostimulation, and trigeminal nerve stimulation. Although vagus nerve stimulation is the only device currently approved in the United States, deep brain stimulation and responsive neurostimulation devices are awaiting FDA approval. Deep brain stimulation, trigeminal nerve stimulation, and transcutaneous vagus nerve stimulation are now approved for epilepsy in the European Union. In this article, the mechanisms of action, safety, and efficacy of new neurostimulation devices are reviewed, and the key advantages and disadvantages of each are discussed. Summary: The exponential growth of the field of neuromodulation for epilepsy is an exciting development; these new devices provide physicians with new options for patients with drug-resistant epilepsy. PMID:23739108

Dynamics of scene representations in the human brain revealed by magnetoencephalography and deep neural networks.

PubMed

Martin Cichy, Radoslaw; Khosla, Aditya; Pantazis, Dimitrios; Oliva, Aude

2017-06-01

Human scene recognition is a rapid multistep process evolving over time from single scene image to spatial layout processing. We used multivariate pattern analyses on magnetoencephalography (MEG) data to unravel the time course of this cortical process. Following an early signal for lower-level visual analysis of single scenes at ~100ms, we found a marker of real-world scene size, i.e. spatial layout processing, at ~250ms indexing neural representations robust to changes in unrelated scene properties and viewing conditions. For a quantitative model of how scene size representations may arise in the brain, we compared MEG data to a deep neural network model trained on scene classification. Representations of scene size emerged intrinsically in the model, and resolved emerging neural scene size representation. Together our data provide a first description of an electrophysiological signal for layout processing in humans, and suggest that deep neural networks are a promising framework to investigate how spatial layout representations emerge in the human brain. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Three-Category Classification of Magnetic Resonance Hearing Loss Images Based on Deep Autoencoder.

PubMed

Jia, Wenjuan; Yang, Ming; Wang, Shui-Hua

2017-09-11

Hearing loss, a partial or total inability to hear, is known as hearing impairment. Untreated hearing loss can have a bad effect on normal social communication, and it can cause psychological problems in patients. Therefore, we design a three-category classification system to detect the specific category of hearing loss, which is beneficial to be treated in time for patients. Before the training and test stages, we use the technology of data augmentation to produce a balanced dataset. Then we use deep autoencoder neural network to classify the magnetic resonance brain images. In the stage of deep autoencoder, we use stacked sparse autoencoder to generate visual features, and softmax layer to classify the different brain images into three categories of hearing loss. Our method can obtain good experimental results. The overall accuracy of our method is 99.5%, and the time consuming is 0.078 s per brain image. Our proposed method based on stacked sparse autoencoder works well in classification of hearing loss images. The overall accuracy of our method is 4% higher than the best of state-of-the-art approaches.

Encoding-related brain activity during deep processing of verbal materials: a PET study.

PubMed

Fujii, Toshikatsu; Okuda, Jiro; Tsukiura, Takashi; Ohtake, Hiroya; Suzuki, Maki; Kawashima, Ryuta; Itoh, Masatoshi; Fukuda, Hiroshi; Yamadori, Atsushi

2002-12-01

The recent advent of neuroimaging techniques provides an opportunity to examine brain regions related to a specific memory process such as episodic memory encoding. There is, however, a possibility that areas active during an assumed episodic memory encoding task, compared with a control task, involve not only areas directly relevant to episodic memory encoding processes but also areas associated with other cognitive processes for on-line information. We used positron emission tomography (PET) to differentiate these two kinds of regions. Normal volunteers were engaged in deep (semantic) or shallow (phonological) processing of new or repeated words during PET. Results showed that deep processing, compared with shallow processing, resulted in significantly better recognition performance and that this effect was associated with activation of various brain areas. Further analyses revealed that there were regions directly relevant to episodic memory encoding in the anterior part of the parahippocampal gyrus, inferior frontal gyrus, supramarginal gyrus, anterior cingulate gyrus, and medial frontal lobe in the left hemisphere. Our results demonstrated that several regions, including the medial temporal lobe, play a role in episodic memory encoding.

Common and unique responses to dopamine agonist therapy and deep brain stimulation in Parkinson's disease: an H(2)(15)O PET study.

PubMed

Bradberry, Trent J; Metman, Leonard Verhagen; Contreras-Vidal, José L; van den Munckhof, Pepijn; Hosey, Lara A; Thompson, Jennifer L W; Schulz, Geralyn M; Lenz, Fredrick; Pahwa, Rajesh; Lyons, Kelly E; Braun, Allen R

2012-10-01

Dopamine agonist therapy and deep brain stimulation (DBS) of the subthalamic nucleus (STN) are antiparkinsonian treatments that act on a different part of the basal ganglia-thalamocortical motor circuitry, yet produce similar symptomatic improvements. The purpose of this study was to identify common and unique brain network features of these standard treatments. We analyzed images produced by H(2)(15)O positron emission tomography (PET) of patients with Parkinson's disease (PD) at rest. Nine patients were scanned before and after injection of apomorphine, and 11 patients were scanned while bilateral stimulators were off and while they were on. Both treatments produced common deactivations of the neocortical sensorimotor areas, including the supplementary motor area, precentral gyrus, and postcentral gyrus, and in subcortical structures, including the putamen and cerebellum. We observed concomitant activations of the superior parietal lobule and the midbrain in the region of the substantia nigra/STN. We also detected unique, treatment-specific changes with possible motor-related consequences in the basal ganglia, thalamus, neocortical sensorimotor cortex, and posterolateral cerebellum. Unique changes in nonmotor regions may reflect treatment-specific effects on verbal fluency and limbic functions. Many of the common effects of these treatments are consistent with the standard pathophysiologic model of PD. However, the common effects in the cerebellum are not readily explained by the model. Consistent deactivation of the cerebellum is interesting in light of recent reports of synaptic pathways directly connecting the cerebellum and basal ganglia, and may warrant further consideration for incorporation into the model. Published by Elsevier Inc.

Reduction of susceptibility-induced signal losses in multi-gradient-echo images: application to improved visualization of the subthalamic nucleus.

PubMed

Volz, Steffen; Hattingen, Elke; Preibisch, Christine; Gasser, Thomas; Deichmann, Ralf

2009-05-01

T2-weighted gradient echo (GE) images yield good contrast of iron-rich structures like the subthalamic nuclei due to microscopic susceptibility induced field gradients, providing landmarks for the exact placement of deep brain stimulation electrodes in Parkinson's disease treatment. An additional advantage is the low radio frequency (RF) exposure of GE sequences. However, T2-weighted images are also sensitive to macroscopic field inhomogeneities, resulting in signal losses, in particular in orbitofrontal and temporal brain areas, limiting anatomical information from these areas. In this work, an image correction method for multi-echo GE data based on evaluation of phase information for field gradient mapping is presented and tested in vivo on a 3 Tesla whole body MR scanner. In a first step, theoretical signal losses are calculated from the gradient maps and a pixelwise image intensity correction is performed. In a second step, intensity corrected images acquired at different echo times TE are combined using optimized weighting factors: in areas not affected by macroscopic field inhomogeneities, data acquired at long TE are weighted more strongly to achieve the contrast required. For large field gradients, data acquired at short TE are favored to avoid signal losses. When compared to the original data sets acquired at different TE and the respective intensity corrected data sets, the resulting combined data sets feature reduced signal losses in areas with major field gradients, while intensity profiles and a contrast-to-noise (CNR) analysis between subthalamic nucleus, red nucleus and the surrounding white matter demonstrate good contrast in deep brain areas.

Sequencing of a Patient with Balanced Chromosome Abnormalities and Neurodevelopmental Disease Identifies Disruption of Multiple High Risk Loci by Structural Variation

PubMed Central

Blake, Jonathon; Riddell, Andrew; Theiss, Susanne; Gonzalez, Alexis Perez; Haase, Bettina; Jauch, Anna; Janssen, Johannes W. G.; Ibberson, David; Pavlinic, Dinko; Moog, Ute; Benes, Vladimir; Runz, Heiko

2014-01-01

Balanced chromosome abnormalities (BCAs) occur at a high frequency in healthy and diseased individuals, but cost-efficient strategies to identify BCAs and evaluate whether they contribute to a phenotype have not yet become widespread. Here we apply genome-wide mate-pair library sequencing to characterize structural variation in a patient with unclear neurodevelopmental disease (NDD) and complex de novo BCAs at the karyotype level. Nucleotide-level characterization of the clinically described BCA breakpoints revealed disruption of at least three NDD candidate genes (LINC00299, NUP205, PSMD14) that gave rise to abnormal mRNAs and could be assumed as disease-causing. However, unbiased genome-wide analysis of the sequencing data for cryptic structural variation was key to reveal an additional submicroscopic inversion that truncates the schizophrenia- and bipolar disorder-associated brain transcription factor ZNF804A as an equally likely NDD-driving gene. Deep sequencing of fluorescent-sorted wild-type and derivative chromosomes confirmed the clinically undetected BCA. Moreover, deep sequencing further validated a high accuracy of mate-pair library sequencing to detect structural variants larger than 10 kB, proposing that this approach is powerful for clinical-grade genome-wide structural variant detection. Our study supports previous evidence for a role of ZNF804A in NDD and highlights the need for a more comprehensive assessment of structural variation in karyotypically abnormal individuals and patients with neurocognitive disease to avoid diagnostic deception. PMID:24625750

In vivo optoacoustic monitoring of calcium activity in the brain (Conference Presentation)

NASA Astrophysics Data System (ADS)

Deán-Ben, Xose Luís.; Gottschalk, Sven; Sela, Gali; Lauri, Antonella; Kneipp, Moritz; Ntziachristos, Vasilis; Westmeyer, Gil G.; Shoham, Shy; Razansky, Daniel

2017-03-01

Non-invasive observation of spatio-temporal neural activity of large neural populations distributed over the entire brain of complex organisms is a longstanding goal of neuroscience [1,2]. Recently, genetically encoded calcium indicators (GECIs) have revolutionized neuroimaging by enabling mapping the activity of entire neuronal populations in vivo [3]. Visualization of these powerful sensors with fluorescence microscopy has however been limited to superficial regions while deep brain areas have so far remained unreachable [4]. We have developed a volumetric multispectral optoacoustic tomography platform for imaging neural activation deep in scattering brains [5]. The developed methodology can render 100 volumetric frames per second across scalable fields of view ranging between 50-1000 mm3 with respective spatial resolution of 35-150µm. Experiments performed in immobilized and freely swimming larvae and in adult zebrafish brains expressing the genetically-encoded calcium indicator GCaMP5G demonstrated, for the first time, the fundamental ability to directly track neural dynamics using optoacoustics while overcoming the depth barrier of optical imaging in scattering brains [6]. It was further possible to monitor calcium transients in a scattering brain of a living adult transgenic zebrafish expressing GCaMP5G calcium indicator [7]. Fast changes in optoacoustic traces associated to GCaMP5G activity were detectable in the presence of other strongly absorbing endogenous chromophores, such as hemoglobin. The results indicate that the optoacoustic signal traces generally follow the GCaMP5G fluorescence dynamics and further enable overcoming the longstanding optical-diffusion penetration barrier associated to scattering in biological tissues [6]. The new functional optoacoustic neuroimaging method can visualize neural activity at penetration depths and spatio-temporal resolution scales not covered with the existing neuroimaging techniques. Thus, in addition to the well-established capacity of optoacoustics to resolve vascular anatomy and multiple hemodynamic parameters deep in scattering tissues, the newly developed methodology offers unprecedented capabilities for functional whole brain observations of fast calcium dynamics.

Fully integrated silicon probes for high-density recording of neural activity.

PubMed

Jun, James J; Steinmetz, Nicholas A; Siegle, Joshua H; Denman, Daniel J; Bauza, Marius; Barbarits, Brian; Lee, Albert K; Anastassiou, Costas A; Andrei, Alexandru; Aydın, Çağatay; Barbic, Mladen; Blanche, Timothy J; Bonin, Vincent; Couto, João; Dutta, Barundeb; Gratiy, Sergey L; Gutnisky, Diego A; Häusser, Michael; Karsh, Bill; Ledochowitsch, Peter; Lopez, Carolina Mora; Mitelut, Catalin; Musa, Silke; Okun, Michael; Pachitariu, Marius; Putzeys, Jan; Rich, P Dylan; Rossant, Cyrille; Sun, Wei-Lung; Svoboda, Karel; Carandini, Matteo; Harris, Kenneth D; Koch, Christof; O'Keefe, John; Harris, Timothy D

2017-11-08

Sensory, motor and cognitive operations involve the coordinated action of large neuronal populations across multiple brain regions in both superficial and deep structures. Existing extracellular probes record neural activity with excellent spatial and temporal (sub-millisecond) resolution, but from only a few dozen neurons per shank. Optical Ca 2+ imaging offers more coverage but lacks the temporal resolution needed to distinguish individual spikes reliably and does not measure local field potentials. Until now, no technology compatible with use in unrestrained animals has combined high spatiotemporal resolution with large volume coverage. Here we design, fabricate and test a new silicon probe known as Neuropixels to meet this need. Each probe has 384 recording channels that can programmably address 960 complementary metal-oxide-semiconductor (CMOS) processing-compatible low-impedance TiN sites that tile a single 10-mm long, 70 × 20-μm cross-section shank. The 6 × 9-mm probe base is fabricated with the shank on a single chip. Voltage signals are filtered, amplified, multiplexed and digitized on the base, allowing the direct transmission of noise-free digital data from the probe. The combination of dense recording sites and high channel count yielded well-isolated spiking activity from hundreds of neurons per probe implanted in mice and rats. Using two probes, more than 700 well-isolated single neurons were recorded simultaneously from five brain structures in an awake mouse. The fully integrated functionality and small size of Neuropixels probes allowed large populations of neurons from several brain structures to be recorded in freely moving animals. This combination of high-performance electrode technology and scalable chip fabrication methods opens a path towards recording of brain-wide neural activity during behaviour.

Fully Integrated Silicon Probes for High-Density Recording of Neural Activity

PubMed Central

Jun, James J.; Steinmetz, Nicholas A.; Siegle, Joshua H.; Denman, Daniel J.; Bauza, Marius; Barbarits, Brian; Lee, Albert K.; Anastassiou, Costas A.; Andrei, Alexandru; Aydın, Çağatay; Barbic, Mladen; Blanche, Timothy J.; Bonin, Vincent; Couto, João; Dutta, Barundeb; Gratiy, Sergey L.; Gutnisky, Diego A.; Häusser, Michael; Karsh, Bill; Ledochowitsch, Peter; Lopez, Carolina Mora; Mitelut, Catalin; Musa, Silke; Okun, Michael; Pachitariu, Marius; Putzeys, Jan; Rich, P. Dylan; Rossant, Cyrille; Sun, Wei-lung; Svoboda, Karel; Carandini, Matteo; Harris, Kenneth D.; Koch, Christof; O'Keefe, John; Harris, Timothy D.

2018-01-01

Summary Paragraph Sensory, motor, and cognitive operations involve the coordinated action of large neuronal populations across multiple brain regions in both superficial and deep structures1,2. Existing extracellular probes record neural activity with excellent spatial and temporal (sub-millisecond) resolution but from only a few dozen neurons per shank. Optical Ca2+ imaging3–5 offers more coverage but lacks the temporal resolution to reliably distinguish individual spikes and does not measure local field potentials. To date, no technology compatible with unrestrained animals has combined high spatiotemporal resolution with large volume coverage. To satisfy this need, we designed, fabricated, and tested a new silicon probe called Neuropixels. Each probe has 384 recording channels that can programmably address 960 CMOS processing-compatible low-impedance TiN6 sites that tile a single 10 mm long, 70x20 µm cross section shank. The 6x9 mm probe base is fabricated with the shank on a single chip. Voltage signals are filtered, amplified, multiplexed, and digitized on the base, allowing noise-free digital data transmission directly from the probe. The combination of dense recording sites and high channel count yielded well-isolated spiking activity from hundreds of neurons per probe implanted in mice and rats. Using two probes, more than 700 well-isolated single neurons were simultaneously recorded from five brain structures in an awake mouse. The fully integrated functionality and small size of Neuropixels probes allowed recording large populations of neurons from multiple brain structures in freely moving animals. This combination of high-performance electrode technology and scalable chip fabrication methods opens the path to record brain-wide neural activity during behavior. PMID:29120427

Brain Structural Changes in Obstructive Sleep Apnea

PubMed Central

Macey, Paul M.; Kumar, Rajesh; Woo, Mary A.; Valladares, Edwin M.; Yan-Go, Frisca L.; Harper, Ronald M.

2008-01-01

Study Objectives: Determine whether obstructive sleep apnea (OSA) subjects show indications of axonal injury. Design: We assessed fiber integrity in OSA and control subjects with diffusion tensor imaging (DTI). We acquired four whole-brain DTI series from each subject. The four series were realigned, and the diffusion tensor calculated at each voxel. Fractional anisotropy (FA), a measure of fiber integrity, was derived from the diffusion tensor, resulting in a whole brain FA “map.” The FA maps were spatially normalized, smoothed, and compared using voxel-based statistics to determine differences between OSA and control groups, with age as a covariate (P < 0.05, corrected for multiple comparisons). Setting: University medical center. Subjects: We studied 41 patients with untreated OSA (mean age ± SD: 46.3 ± 8.9 years; female/male: 7/34) with apnea-hypopnea index 15 to 101 (mean ± SD: 35.7 ± 18.1 events/hour), and 69 control subjects (mean age ± SD: 47.5 ± 8.79 years; female/male: 25/44). Measurements and Results: Multiple regions of lower FA appeared within white matter in the OSA group, and included fibers of the anterior corpus callosum, anterior and posterior cingulate cortex and cingulum bundle, right column of the fornix, portions of the frontal, ventral prefrontal, parietal and insular cortices, bilateral internal capsule, left cerebral peduncle, middle cerebellar peduncle and corticospinal tract, and deep cerebellar nuclei. Conclusions: White matter is extensively affected in OSA patients; the alterations include axons linking major structures within the limbic system, pons, frontal, temporal and parietal cortices, and projections to and from the cerebellum. Citation: Macey PM; Kumar R; Woo MA; Valladares EM; Yan-Go FL; Harper RM. Brain structural changes in obstructive sleep apnea. SLEEP 2008;31(7):967-977. PMID:18652092

Mapping human preictal and ictal haemodynamic networks using simultaneous intracranial EEG-fMRI

PubMed Central

Chaudhary, Umair J.; Centeno, Maria; Thornton, Rachel C.; Rodionov, Roman; Vulliemoz, Serge; McEvoy, Andrew W.; Diehl, Beate; Walker, Matthew C.; Duncan, John S.; Carmichael, David W.; Lemieux, Louis

2016-01-01

Accurately characterising the brain networks involved in seizure activity may have important implications for our understanding of epilepsy. Intracranial EEG-fMRI can be used to capture focal epileptic events in humans with exquisite electrophysiological sensitivity and allows for identification of brain structures involved in this phenomenon over the entire brain. We investigated ictal BOLD networks using the simultaneous intracranial EEG-fMRI (icEEG-fMRI) in a 30 year-old male undergoing invasive presurgical evaluation with bilateral depth electrode implantations in amygdalae and hippocampi for refractory temporal lobe epilepsy. One spontaneous focal electrographic seizure was recorded. The aims of the data analysis were firstly to map BOLD changes related to the ictal activity identified on icEEG and secondly to compare different fMRI modelling approaches. Visual inspection of the icEEG showed an onset dominated by beta activity involving the right amygdala and hippocampus lasting 6.4 s (ictal onset phase), followed by gamma activity bilaterally lasting 14.8 s (late ictal phase). The fMRI data was analysed using SPM8 using two modelling approaches: firstly, purely based on the visually identified phases of the seizure and secondly, based on EEG spectral dynamics quantification. For the visual approach the two ictal phases were modelled as ‘ON’ blocks convolved with the haemodynamic response function; in addition the BOLD changes during the 30 s preceding the onset were modelled using a flexible basis set. For the quantitative fMRI modelling approach two models were evaluated: one consisting of the variations in beta and gamma bands power, thereby adding a quantitative element to the visually-derived models, and another based on principal components analysis of the entire spectrogram in attempt to reduce the bias associated with the visual appreciation of the icEEG. BOLD changes related to the visually defined ictal onset phase were revealed in the medial and lateral right temporal lobe. For the late ictal phase, the BOLD changes were remote from the SOZ and in deep brain areas (precuneus, posterior cingulate and others). The two quantitative models revealed BOLD changes involving the right hippocampus, amygdala and fusiform gyrus and in remote deep brain structures and the default mode network-related areas. In conclusion, icEEG-fMRI allowed us to reveal BOLD changes within and beyond the SOZ linked to very localised ictal fluctuations in beta and gamma activity measured in the amygdala and hippocampus. Furthermore, the BOLD changes within the SOZ structures were better captured by the quantitative models, highlighting the interest in considering seizure-related EEG fluctuations across the entire spectrum. PMID:27114897

Mapping human preictal and ictal haemodynamic networks using simultaneous intracranial EEG-fMRI.

PubMed

Chaudhary, Umair J; Centeno, Maria; Thornton, Rachel C; Rodionov, Roman; Vulliemoz, Serge; McEvoy, Andrew W; Diehl, Beate; Walker, Matthew C; Duncan, John S; Carmichael, David W; Lemieux, Louis

2016-01-01

Accurately characterising the brain networks involved in seizure activity may have important implications for our understanding of epilepsy. Intracranial EEG-fMRI can be used to capture focal epileptic events in humans with exquisite electrophysiological sensitivity and allows for identification of brain structures involved in this phenomenon over the entire brain. We investigated ictal BOLD networks using the simultaneous intracranial EEG-fMRI (icEEG-fMRI) in a 30 year-old male undergoing invasive presurgical evaluation with bilateral depth electrode implantations in amygdalae and hippocampi for refractory temporal lobe epilepsy. One spontaneous focal electrographic seizure was recorded. The aims of the data analysis were firstly to map BOLD changes related to the ictal activity identified on icEEG and secondly to compare different fMRI modelling approaches. Visual inspection of the icEEG showed an onset dominated by beta activity involving the right amygdala and hippocampus lasting 6.4 s (ictal onset phase), followed by gamma activity bilaterally lasting 14.8 s (late ictal phase). The fMRI data was analysed using SPM8 using two modelling approaches: firstly, purely based on the visually identified phases of the seizure and secondly, based on EEG spectral dynamics quantification. For the visual approach the two ictal phases were modelled as 'ON' blocks convolved with the haemodynamic response function; in addition the BOLD changes during the 30 s preceding the onset were modelled using a flexible basis set. For the quantitative fMRI modelling approach two models were evaluated: one consisting of the variations in beta and gamma bands power, thereby adding a quantitative element to the visually-derived models, and another based on principal components analysis of the entire spectrogram in attempt to reduce the bias associated with the visual appreciation of the icEEG. BOLD changes related to the visually defined ictal onset phase were revealed in the medial and lateral right temporal lobe. For the late ictal phase, the BOLD changes were remote from the SOZ and in deep brain areas (precuneus, posterior cingulate and others). The two quantitative models revealed BOLD changes involving the right hippocampus, amygdala and fusiform gyrus and in remote deep brain structures and the default mode network-related areas. In conclusion, icEEG-fMRI allowed us to reveal BOLD changes within and beyond the SOZ linked to very localised ictal fluctuations in beta and gamma activity measured in the amygdala and hippocampus. Furthermore, the BOLD changes within the SOZ structures were better captured by the quantitative models, highlighting the interest in considering seizure-related EEG fluctuations across the entire spectrum.

Combination of rs-fMRI and sMRI Data to Discriminate Autism Spectrum Disorders in Young Children Using Deep Belief Network.

PubMed

Akhavan Aghdam, Maryam; Sharifi, Arash; Pedram, Mir Mohsen

2018-05-07

In recent years, the use of advanced magnetic resonance (MR) imaging methods such as functional magnetic resonance imaging (fMRI) and structural magnetic resonance imaging (sMRI) has recorded a great increase in neuropsychiatric disorders. Deep learning is a branch of machine learning that is increasingly being used for applications of medical image analysis such as computer-aided diagnosis. In a bid to classify and represent learning tasks, this study utilized one of the most powerful deep learning algorithms (deep belief network (DBN)) for the combination of data from Autism Brain Imaging Data Exchange I and II (ABIDE I and ABIDE II) datasets. The DBN was employed so as to focus on the combination of resting-state fMRI (rs-fMRI), gray matter (GM), and white matter (WM) data. This was done based on the brain regions that were defined using the automated anatomical labeling (AAL), in order to classify autism spectrum disorders (ASDs) from typical controls (TCs). Since the diagnosis of ASD is much more effective at an early age, only 185 individuals (116 ASD and 69 TC) ranging in age from 5 to 10 years were included in this analysis. In contrast, the proposed method is used to exploit the latent or abstract high-level features inside rs-fMRI and sMRI data while the old methods consider only the simple low-level features extracted from neuroimages. Moreover, combining multiple data types and increasing the depth of DBN can improve classification accuracy. In this study, the best combination comprised rs-fMRI, GM, and WM for DBN of depth 3 with 65.56% accuracy (sensitivity = 84%, specificity = 32.96%, F1 score = 74.76%) obtained via 10-fold cross-validation. This result outperforms previously presented methods on ABIDE I dataset.

Proceedings of the Second Annual Deep Brain Stimulation Think Tank: What's in the Pipeline.

PubMed

Gunduz, Aysegul; Morita, Hokuto; Rossi, P Justin; Allen, William L; Alterman, Ron L; Bronte-Stewart, Helen; Butson, Christopher R; Charles, David; Deckers, Sjaak; de Hemptinne, Coralie; DeLong, Mahlon; Dougherty, Darin; Ellrich, Jens; Foote, Kelly D; Giordano, James; Goodman, Wayne; Greenberg, Benjamin D; Greene, David; Gross, Robert; Judy, Jack W; Karst, Edward; Kent, Alexander; Kopell, Brian; Lang, Anthony; Lozano, Andres; Lungu, Codrin; Lyons, Kelly E; Machado, Andre; Martens, Hubert; McIntyre, Cameron; Min, Hoon-Ki; Neimat, Joseph; Ostrem, Jill; Pannu, Sat; Ponce, Francisco; Pouratian, Nader; Reymers, Donnie; Schrock, Lauren; Sheth, Sameer; Shih, Ludy; Stanslaski, Scott; Steinke, G Karl; Stypulkowski, Paul; Tröster, Alexander I; Verhagen, Leo; Walker, Harrison; Okun, Michael S

2015-01-01

The proceedings of the 2nd Annual Deep Brain Stimulation Think Tank summarize the most contemporary clinical, electrophysiological, and computational work on DBS for the treatment of neurological and neuropsychiatric disease and represent the insights of a unique multidisciplinary ensemble of expert neurologists, neurosurgeons, neuropsychologists, psychiatrists, scientists, engineers and members of industry. Presentations and discussions covered a broad range of topics, including advocacy for DBS, improving clinical outcomes, innovations in computational models of DBS, understanding of the neurophysiology of Parkinson's disease (PD) and Tourette syndrome (TS) and evolving sensor and device technologies.

Deep brain stimulation for movement disorders.

PubMed

Thevathasan, Wesley; Gregory, Ralph

2010-02-01

Deep brain stimulation is now considered a routine treatment option for selected patients with advanced Parkinson's disease, primary segmental and generalised dystonia, and essential tremor. The neurosurgeon is responsible for the accurate and safe placement of the electrodes and the neurologist for the careful selection of patients and titration of medication against the effects of stimulation. A multidisciplinary team approach involving specialist nurses, neuropsychologists and neurophysiologists is required for a successful outcome. In this article we will summarise the key points in patient selection, provide an overview of the surgical technique, and discuss the beneficial and adverse outcomes that can occur.

Proceedings of the Second Annual Deep Brain Stimulation Think Tank: What's in the Pipeline

PubMed Central

Gunduz, Aysegul; Morita, Hokuto; Rossi, P. Justin; Allen, William L.; Alterman, Ron L.; Bronte-Stewart, Helen; Butson, Christopher R.; Charles, David; Deckers, Sjaak; de Hemptinne, Coralie; DeLong, Mahlon; Dougherty, Darin; Ellrich, Jens; Foote, Kelly D.; Giordano, James; Goodman, Wayne; Greenberg, Benjamin D.; Greene, David; Gross, Robert; Judy, Jack W.; Karst, Edward; Kent, Alexander; Kopell, Brian; Lang, Anthony; Lozano, Andres; Lungu, Codrin; Lyons, Kelly E.; Machado, Andre; Martens, Hubert; McIntyre, Cameron; Min, Hoon-Ki; Neimat, Joseph; Ostrem, Jill; Pannu, Sat; Ponce, Francisco; Pouratian, Nader; Reymers, Donnie; Schrock, Lauren; Sheth, Sameer; Shih, Ludy; Stanslaski, Scott; Steinke, G. Karl; Stypulkowski, Paul; Tröster, Alexander I.; Verhagen, Leo; Walker, Harrison; Okun, Michael S.

2015-01-01

The proceedings of the 2nd Annual Deep Brain Stimulation Think Tank summarize the most contemporary clinical, electrophysiological, and computational work on DBS for the treatment of neurological and neuropsychiatric disease and represent the insights of a unique multidisciplinary ensemble of expert neurologists, neurosurgeons, neuropsychologists, psychiatrists, scientists, engineers and members of industry. Presentations and discussions covered a broad range of topics, including advocacy for DBS, improving clinical outcomes, innovations in computational models of DBS, understanding of the neurophysiology of Parkinson's disease (PD) and Tourette syndrome (TS) and evolving sensor and device technologies. PMID:25526555

Positive clinical effects of gamma knife capsulotomy in a patient with deep brain stimulation-refractory Tourette Syndrome and Obsessive Compulsive Disorder.

PubMed

Richieri, Raphaëlle; Blackman, Graham; Musil, Richard; Spatola, Giorgio; Cavanna, Andrea E; Lançon, Christophe; Régis, Jean

2018-04-26

We report the first case of a patient with severe, intractable Tourette Syndrome with comorbid Obsessive Compulsive disorder, who recovered from both disorders with gamma-knife (GK) stereotactic radiosurgery following deep brain stimulation (DBS). This case highlights the possible role of the internal capsule within the neural circuitries underlying both TS and OCD, and suggests that in cases of treatment-refractory TS and comorbid OCD, bilateral anterior capsulotomy using stereotactic radiosurgery may be a viable treatment option. Copyright © 2018 Elsevier B.V. All rights reserved.

Clinical efficacy of deep brain stimulation for the treatment of medically refractory epilepsy.

PubMed

Klinger, Neil V; Mittal, Sandeep

2016-01-01

Epilepsy affects 50 million people worldwide and about 30% of these patients will not be adequately controlled with antiepileptic drugs (AEDs) alone. For patients where resective surgery is not indicated, deep brain stimulation (DBS) may be an effective alternative. The majority of available literature targets the thalamic nuclei (anterior; centromedian), subthalamic nucleus, hippocampus, and cerebellum. Here, we review patient outcomes and adverse events related to DBS to these various targets. Data show DBS may be a safe and effective treatment option for refractory epilepsy. Copyright © 2015. Published by Elsevier B.V.

Proceedings of the second annual deep brain stimulation think tank: What's in the pipeline

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gunduz, Aysegul; Morita, Hokuto; Rossi, P. Justin

Here the proceedings of the 2nd Annual Deep Brain Stimulation Think Tank summarize the most contemporary clinical, electrophysiological, and computational work on DBS for the treatment of neurological and neuropsychiatric disease and represent the insights of a unique multidisciplinary ensemble of expert neurologists, neurosurgeons, neuropsychologists, psychiatrists, scientists, engineers and members of industry. Presentations and discussions covered a broad range of topics, including advocacy for DBS, improving clinical outcomes, innovations in computational models of DBS, understanding of the neurophysiology of Parkinson's disease (PD) and Tourette syndrome (TS) and evolving sensor and device technologies.

Proceedings of the second annual deep brain stimulation think tank: What's in the pipeline

DOE PAGES

Gunduz, Aysegul; Morita, Hokuto; Rossi, P. Justin; ...

2015-05-25

Here the proceedings of the 2nd Annual Deep Brain Stimulation Think Tank summarize the most contemporary clinical, electrophysiological, and computational work on DBS for the treatment of neurological and neuropsychiatric disease and represent the insights of a unique multidisciplinary ensemble of expert neurologists, neurosurgeons, neuropsychologists, psychiatrists, scientists, engineers and members of industry. Presentations and discussions covered a broad range of topics, including advocacy for DBS, improving clinical outcomes, innovations in computational models of DBS, understanding of the neurophysiology of Parkinson's disease (PD) and Tourette syndrome (TS) and evolving sensor and device technologies.

Thalamic Ventral Intermediate Nucleus Deep Brain Stimulation for Orthostatic Tremor.

PubMed

Lehn, Alexander C; O'Gorman, Cullen; Olson, Sarah; Salari, Mehri

2017-01-01

Orthostatic tremor (OT) was first described in 1977. It is characterized by rapid tremor of 13-18 Hz and can be recorded in the lower limbs and trunk muscles. OT remains difficult to treat, although some success has been reported with deep brain stimulation (DBS). We report a 68-year-old male with OT who did not improve significantly after bilateral thalamic stimulation. Although some patients were described who improved after DBS surgery, more information is needed about the effect of these treatment modalities on OT, ideally in the form of randomized trial data.

Deep brain transcranial magnetic stimulation using variable "Halo coil" system

NASA Astrophysics Data System (ADS)

Meng, Y.; Hadimani, R. L.; Crowther, L. J.; Xu, Z.; Qu, J.; Jiles, D. C.

2015-05-01

Transcranial Magnetic Stimulation has the potential to treat various neurological disorders non-invasively and safely. The "Halo coil" configuration can stimulate deeper regions of the brain with lower surface to deep-brain field ratio compared to other coil configurations. The existing "Halo coil" configuration is fixed and is limited in varying the site of stimulation in the brain. We have developed a new system based on the current "Halo coil" design along with a graphical user interface system that enables the larger coil to rotate along the transverse plane. The new system can also enable vertical movement of larger coil. Thus, this adjustable "Halo coil" configuration can stimulate different regions of the brain by adjusting the position and orientation of the larger coil on the head. We have calculated magnetic and electric fields inside a MRI-derived heterogeneous head model for various positions and orientations of the coil. We have also investigated the mechanical and thermal stability of the adjustable "Halo coil" configuration for various positions and orientations of the coil to ensure safe operation of the system.

Blood-brain barrier dysfunction and cerebral small vessel disease (arteriolosclerosis) in brains of older people.

PubMed

Bridges, Leslie R; Andoh, Joycelyn; Lawrence, Andrew J; Khoong, Cheryl H L; Poon, Wayne; Esiri, Margaret M; Markus, Hugh S; Hainsworth, Atticus H

2014-11-01

The blood-brain barrier protects brain tissue from potentially harmful plasma components. Small vessel disease (SVD; also termed arteriolosclerosis) is common in the brains of older people and is associated with lacunar infarcts, leukoaraiosis, and vascular dementia. To determine whether plasma extravasation is associated with SVD, we immunolabeled the plasma proteins fibrinogen and immunoglobulin G, which are assumed to reflect blood-brain barrier dysfunction, in deep gray matter (DGM; anterior caudate-putamen) and deep subcortical white matter (DWM) in the brains of a well-characterized cohort of donated brains with minimal Alzheimer disease pathology (Braak Stages 0-II) (n = 84; aged 65 years or older). Morphometric measures of fibrinogen labeling were compared between people with neuropathologically defined SVD and aged control subjects. Parenchymal cellular labeling with fibrinogen and immunoglobulin G was detectable in DGM and DWM in many subjects (>70%). Quantitative measures of fibrinogen were not associated with SVD in DGM or DWM; SVD severity was correlated between DGM and DWM (p < 0.0001). Fibrinogen in DGM showed a modest association with a history of hypertension; DWM fibrinogen was associated with dementia and cerebral amyloid angiopathy (all p < 0.05). In DWM, SVD was associated with leukoaraiosis identified in life (p < 0.05), but fibrinogen was not. Our data suggest that, in aged brains, plasma extravasation and hence local blood-brain barrier dysfunction are common but do not support an association with SVD.

Atlas-based segmentation of 3D cerebral structures with competitive level sets and fuzzy control.

PubMed

Ciofolo, Cybèle; Barillot, Christian

2009-06-01

We propose a novel approach for the simultaneous segmentation of multiple structures with competitive level sets driven by fuzzy control. To this end, several contours evolve simultaneously toward previously defined anatomical targets. A fuzzy decision system combines the a priori knowledge provided by an anatomical atlas with the intensity distribution of the image and the relative position of the contours. This combination automatically determines the directional term of the evolution equation of each level set. This leads to a local expansion or contraction of the contours, in order to match the boundaries of their respective targets. Two applications are presented: the segmentation of the brain hemispheres and the cerebellum, and the segmentation of deep internal structures. Experimental results on real magnetic resonance (MR) images are presented, quantitatively assessed and discussed.

Fiber-based tunable repetition rate source for deep tissue two-photon fluorescence microscopy

PubMed Central

Charan, Kriti; Li, Bo; Wang, Mengran; Lin, Charles P.; Xu, Chris

2018-01-01

Deep tissue multiphoton imaging requires high peak power to enhance signal and low average power to prevent thermal damage. Both goals can be advantageously achieved through laser repetition rate tuning instead of simply adjusting the average power. We show that the ideal repetition rate for deep two-photon imaging in the mouse brain is between 1 and 10 MHz, and we present a fiber-based source with an arbitrarily tunable repetition rate within this range. The performance of the new source is compared to a mode-locked Ti:Sapphire (Ti:S) laser for in vivo imaging of mouse brain vasculature. At 2.5 MHz, the fiber source requires 5.1 times less average power to obtain the same signal as a standard Ti:S laser operating at 80 MHz. PMID:29760989

Trans-venous embolization of a basal ganglia ruptured arteriovenous malformation with open surgical arterial control: A hybrid technique.

PubMed

Kulcsár, Zsolt; Machi, Paolo; Schaller, Karl; Lovblad, Karl Olof; Bijlenga, Philippe

2018-05-01

Treatment of ruptured deep-seated arteriovenous malformations is challenging and associated with elevated risks. This is due to the proximity or involvement of critical brain structures and the specifically fine and delicate angioarchitecture of these lesions, making both endovascular and surgical access technically complicated. We present the advantages of a true combined, open surgical and endovascular transvenous approach in a hybrid operating room. The technique may overcome in part the difficulties and may improve safety and risk related concerns. Copyright © 2018. Published by Elsevier Masson SAS.

Use of Tubular Retractor for Resection of Deep-Seated Cerebral Tumors and Colloid Cysts: Single Surgeon Experience and Review of the Literature.

PubMed

Eichberg, Daniel G; Buttrick, Simon; Brusko, G Damian; Ivan, Michael; Starke, Robert M; Komotar, Ricardo J

2018-04-01

Brain retraction is often required to develop a surgical corridor during the resection of deep-seated intracranial lesions. Traditional blade retractors distribute pressure asymmetrically and may case local tissue damage. Tubular retractors minimize this pitfall by distributing pressure evenly, which has been shown to translate to significant safety and efficacy data. Further qualified reports regarding the use of tubular retractors are of interest. We performed a retrospective analysis of 1 surgeon's experience with 20 cases of minimally invasive resection with the ViewSite Brain Access System (n = 7) and BrainPath (n = 13) systems. In addition, a comprehensive review of all published cases of tubular retractor systems used for resection of subcortical neoplastic, cystic, infectious, vascular, and hemorrhagic lesions was conducted. Of the 20 cases analyzed, gross total resection was achieved in 18, with an associated 10% immediate postoperative complication rate and 5% long-term complication rate. A comprehensive review of the literature showed 30 articles describing 536 cases of resection of deep neoplastic or colloid cysts with an overall complication rate of 9.1%. Tubular retractor systems have a favorable safety profile and are an important tool in the armamentarium of a neurosurgeon for the resection of deep intracranial lesions. Copyright © 2017 Elsevier Inc. All rights reserved.

Single-shot T2 mapping using overlapping-echo detachment planar imaging and a deep convolutional neural network.

PubMed

Cai, Congbo; Wang, Chao; Zeng, Yiqing; Cai, Shuhui; Liang, Dong; Wu, Yawen; Chen, Zhong; Ding, Xinghao; Zhong, Jianhui

2018-04-24

An end-to-end deep convolutional neural network (CNN) based on deep residual network (ResNet) was proposed to efficiently reconstruct reliable T 2 mapping from single-shot overlapping-echo detachment (OLED) planar imaging. The training dataset was obtained from simulations that were carried out on SPROM (Simulation with PRoduct Operator Matrix) software developed by our group. The relationship between the original OLED image containing two echo signals and the corresponding T 2 mapping was learned by ResNet training. After the ResNet was trained, it was applied to reconstruct the T 2 mapping from simulation and in vivo human brain data. Although the ResNet was trained entirely on simulated data, the trained network was generalized well to real human brain data. The results from simulation and in vivo human brain experiments show that the proposed method significantly outperforms the echo-detachment-based method. Reliable T 2 mapping with higher accuracy is achieved within 30 ms after the network has been trained, while the echo-detachment-based OLED reconstruction method took approximately 2 min. The proposed method will facilitate real-time dynamic and quantitative MR imaging via OLED sequence, and deep convolutional neural network has the potential to reconstruct maps from complex MRI sequences efficiently. © 2018 International Society for Magnetic Resonance in Medicine.

A review of brain circuitries involved in stuttering

PubMed Central

Craig-McQuaide, Anna; Akram, Harith; Zrinzo, Ludvic; Tripoliti, Elina

2014-01-01

Stuttering has been the subject of much research, nevertheless its etiology remains incompletely understood. This article presents a critical review of the literature on stuttering, with particular reference to the role of the basal ganglia (BG). Neuroimaging and lesion studies of developmental and acquired stuttering, as well as pharmacological and genetic studies are discussed. Evidence of structural and functional changes in the BG in those who stutter indicates that this motor speech disorder is due, at least in part, to abnormal BG cues for the initiation and termination of articulatory movements. Studies discussed provide evidence of a dysfunctional hyperdopaminergic state of the thalamocortical pathways underlying speech motor control in stuttering. Evidence that stuttering can improve, worsen or recur following deep brain stimulation for other indications is presented in order to emphasize the role of BG in stuttering. Further research is needed to fully elucidate the pathophysiology of this speech disorder, which is associated with significant social isolation. PMID:25452719

Brain Development in Fetuses of Mothers with Diabetes: A Case-Control MR Imaging Study.

PubMed

Denison, F C; Macnaught, G; Semple, S I K; Terris, G; Walker, J; Anblagan, D; Serag, A; Reynolds, R M; Boardman, J P

2017-05-01

Offspring exposed to maternal diabetes are at increased risk of neurocognitive impairment, but its origins are unknown. With MR imaging, we investigated the feasibility of comprehensive assessment of brain metabolism ( 1 H-MRS), microstructure (DWI), and macrostructure (structural MRI) in third-trimester fetuses in women with diabetes and determined normal ranges for the MR imaging parameters measured. Women with singleton pregnancies with diabetes ( n = 26) and healthy controls ( n = 26) were recruited prospectively for MR imaging studies between 34 and 38 weeks' gestation. Data suitable for postprocessing were obtained from 79%, 71%, and 46% of women for 1 H-MRS, DWI, and structural MRI, respectively. There was no difference in the NAA/Cho and NAA/Cr ratios (mean [SD]) in the fetal brain in women with diabetes compared with controls (1.74 [0.79] versus 1.79 [0.64], P = .81; and 0.78 [0.28] versus 0.94 [0.36], P = .12, respectively), but the Cho/Cr ratio was marginally lower (0.46 [0.11] versus 0.53 [0.10], P = .04). There was no difference in mean [SD] anterior white, posterior white, and deep gray matter ADC between patients and controls (1.16 [0.12] versus 1.16 [0.08], P = .96; 1.54 [0.16] versus 1.59 [0.20], P = .56; and 1.49 [0.23] versus 1.52 [0.23], P = .89, respectively) or volume of the cerebrum (243.0 mL [22.7 mL] versus 253.8 mL [31.6 mL], P = .38). Acquiring multimodal MR imaging of the fetal brain at 3T from pregnant women with diabetes is feasible. Further study of fetal brain metabolism in maternal diabetes is warranted. © 2017 by American Journal of Neuroradiology.