\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
\\n"}]',published:!0,mainMedia:null},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 179 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 252 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
\n'}],latestNews:[{slug:"stanford-university-identifies-top-2-scientists-over-1-000-are-intechopen-authors-and-editors-20210122",title:"Stanford University Identifies Top 2% Scientists, Over 1,000 are IntechOpen Authors and Editors"},{slug:"intechopen-authors-included-in-the-highly-cited-researchers-list-for-2020-20210121",title:"IntechOpen Authors Included in the Highly Cited Researchers List for 2020"},{slug:"intechopen-maintains-position-as-the-world-s-largest-oa-book-publisher-20201218",title:"IntechOpen Maintains Position as the World’s Largest OA Book Publisher"},{slug:"all-intechopen-books-available-on-perlego-20201215",title:"All IntechOpen Books Available on Perlego"},{slug:"oiv-awards-recognizes-intechopen-s-editors-20201127",title:"OIV Awards Recognizes IntechOpen's Editors"},{slug:"intechopen-joins-crossref-s-initiative-for-open-abstracts-i4oa-to-boost-the-discovery-of-research-20201005",title:"IntechOpen joins Crossref's Initiative for Open Abstracts (I4OA) to Boost the Discovery of Research"},{slug:"intechopen-hits-milestone-5-000-open-access-books-published-20200908",title:"IntechOpen hits milestone: 5,000 Open Access books published!"},{slug:"intechopen-books-hosted-on-the-mathworks-book-program-20200819",title:"IntechOpen Books Hosted on the MathWorks Book Program"}]},book:{item:{type:"book",id:"6967",leadTitle:null,fullTitle:"Prebiotics and Probiotics - Potential Benefits in Nutrition and Health",title:"Prebiotics and Probiotics",subtitle:"Potential Benefits in Nutrition and Health",reviewType:"peer-reviewed",abstract:"Probiotic bacteria are found in the intestinal microbiota of the host and favor multiple metabolic reactions. Prebiotics provide food for probiotic bacteria and have an effect on their own performance in favor of host health. Numerous metabolic and immunological mechanisms are involved in its effects. Probiotics have been studied for several decades and their use for human consumption is still unclear. However, new types of molecules with prebiotic functions and components of probiotic bacteria with therapeutic potential are still being studied. The versatility of these molecules makes their incorporation into human food and animal diets feasible. This book is a compendium of recent scientific information on the use of probiotics and prebiotics for the benefit of human and animal health.",isbn:"978-1-78985-922-5",printIsbn:"978-1-78985-921-8",pdfIsbn:"978-1-78985-644-6",doi:"10.5772/intechopen.73714",price:119,priceEur:129,priceUsd:155,slug:"prebiotics-and-probiotics-potential-benefits-in-nutrition-and-health",numberOfPages:272,isOpenForSubmission:!1,isInWos:null,hash:"11781d6b1c070edcf204518e632033be",bookSignature:"Elena Franco-Robles and Joel Ramírez-Emiliano",publishedDate:"March 4th 2020",coverURL:"https://cdn.intechopen.com/books/images_new/6967.jpg",numberOfDownloads:5135,numberOfWosCitations:0,numberOfCrossrefCitations:4,numberOfDimensionsCitations:6,hasAltmetrics:1,numberOfTotalCitations:10,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"March 15th 2019",dateEndSecondStepPublish:"May 3rd 2019",dateEndThirdStepPublish:"July 2nd 2019",dateEndFourthStepPublish:"September 20th 2019",dateEndFifthStepPublish:"November 19th 2019",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,editors:[{id:"219102",title:"Dr.",name:"Elena",middleName:null,surname:"Franco-Robles",slug:"elena-franco-robles",fullName:"Elena Franco-Robles",profilePictureURL:"https://mts.intechopen.com/storage/users/219102/images/system/219102.jpeg",biography:"Dr. Elena Franco Robles is Professor in the Department of Veterinary and Zootechnics, Division of Life Sciences, Irapuato-Salamanca Campus, University of Guanajuato, Mexico, and is member of the National System of Investigators (SNI I). She graduated from Faculty of Chemistry, Universidad de Guanajuato, México, in 2006. She obtained her M.S. degree in Medical Science from the same University in 2010. She obtained her Ph.D from the same University. She obtained a Posdoctoral Position in Biotechnology in Center for Research and Advanced Studies of the National Polytechnic Institute in 2014-2016. \nDr. Elena Franco Robles has done research mainly in immunology of the intestine and oxidative stress in murine models with various pathologies. Her research focused on the role of nutraceutical and functional ingredients as immunomodulators for the prevention and / or treatment of diseases in animals. In addition, the study of toll-like receptors and gut microbiota as new therapeutic targets in zoonotic infections.",institutionString:"Universidad de Guanajuato",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"Universidad de Guanajuato",institutionURL:null,country:{name:"Mexico"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:{id:"219380",title:"Dr.",name:"Joel",middleName:null,surname:"Ramírez-Emiliano",slug:"joel-ramirez-emiliano",fullName:"Joel Ramírez-Emiliano",profilePictureURL:"https://mts.intechopen.com/storage/users/219380/images/system/219380.jpeg",biography:"Dr. Joel Ramírez-Emiliano graduated from Universidad Michoacana de San Nicolás de Hidalgo, México in 1996. He obtained his M.Sc. degree in Experimental Biology in 1999 from the same university. In 2004 he obtained his Ph.D. in Experimental Biology from University of Guanajuato, Mexico. He has been a Postdoctoral fellow at CINVESTAV-Mexico (2005). Currently, Dr. Joel is a Professor-Investigator in the Department of Medical Sciences, Division of Health Sciences, Leon Campus, University of Guanajuato, Mexico, and is member of the National System of Investigators (SNI I).\nHe is currently studying the pathophysiology of oxidative stress in animal models and in humans suffering from metabolic diseases. His interest is studying the effect of antioxidants (polyphenols, and some prebiotics and probiotics with antioxidant functions) on the control and / or treatment of oxidative damage caused by metabolic disorders.",institutionString:"Universidad de Guanajuato",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"0",institution:null},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"894",title:"Food Microbiology",slug:"immunology-and-microbiology-applied-microbiology-food-microbiology"}],chapters:[{id:"68845",title:"Probiotics and Prebiotics in Infant Formulae",doi:"10.5772/intechopen.88609",slug:"probiotics-and-prebiotics-in-infant-formulae",totalDownloads:413,totalCrossrefCites:1,totalDimensionsCites:1,signatures:"José Maldonado",downloadPdfUrl:"/chapter/pdf-download/68845",previewPdfUrl:"/chapter/pdf-preview/68845",authors:[null],corrections:null},{id:"68503",title:"Comparision of Antioxidant Activity of Cow and Goat Milk During Fermentation with Lactobacillus acidophilus LA-5",doi:"10.5772/intechopen.88212",slug:"comparision-of-antioxidant-activity-of-cow-and-goat-milk-during-fermentation-with-em-lactobacillus-a",totalDownloads:268,totalCrossrefCites:0,totalDimensionsCites:0,signatures:"Jessica Dayara Álvarez-Rosales, César Ozuna, Rubén Salcedo-Hernández and Gabriela Rodríguez-Hernández",downloadPdfUrl:"/chapter/pdf-download/68503",previewPdfUrl:"/chapter/pdf-preview/68503",authors:[null],corrections:null},{id:"70223",title:"Prebiotics and Probiotics - Potential Benefits in Human Nutrition and Health",doi:"10.5772/intechopen.89155",slug:"prebiotics-and-probiotics-potential-benefits-in-human-nutrition-and-health",totalDownloads:263,totalCrossrefCites:0,totalDimensionsCites:0,signatures:"Maria Inês Sucupira Maciel and Michelle Maria Barreto de Souza",downloadPdfUrl:"/chapter/pdf-download/70223",previewPdfUrl:"/chapter/pdf-preview/70223",authors:[null],corrections:null},{id:"69385",title:"Functional Attributes and Health Benefits of Novel Prebiotic Oligosaccharides Derived from Xylan, Arabinan, and Mannan",doi:"10.5772/intechopen.89484",slug:"functional-attributes-and-health-benefits-of-novel-prebiotic-oligosaccharides-derived-from-xylan-ara",totalDownloads:359,totalCrossrefCites:0,totalDimensionsCites:1,signatures:"Bradley A. 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Rapid eye movements, dreams, skeletal muscle atonia, and autonomous-sympathetic nervous system questions the brain and its importance, and what it really means again and again with EEG signals. Therefore repeating REM waves in the brain, REM physiology and pathophysiology should be studied more in depth. We can regard narcolepsy as a type of REM physiology abnormality due to two important conditions: sleep paralysis, and dreaming phenomenon. A narcoleptic patient experiences both conditions while asleep or waking up from sleep during REM. Narcolepsy can be conceptualized as blurring of the borders of the brain while awake, sleeping or dreaming. An awake narcoleptic can feel as if sleepy and can even see dreams. In the classical sense, narcolepsy is characterized by hypersomnolence during the day associated with REM sleep phenomenon and cataplexy encompassing sleep paralysis and hypnogogic hallucinations. The fundamental pathophysiology of narcolepsy is related to a deficiency of hypocretine (orexine) which is an important component of the hypothalamic neuropeptide system.
\r\n\tHistorically the word narcolepsy was first used by Ge´lineau in 1880 to describe irresistible episodes of sleep that were repetitive with short intervals. In 1950s Kleitman was the first individual to discover REM. Since then, laboratories that can record electrophysiological signals have been developed and possibilities for diagnosing, treating and monitoring sleep disorders have increased. However, narcolepsy can still be mixed with sleep disorders and neuropsychiatric disorders.
\r\n\tThis book aims at tackling narcolepsy from both basic science and clinical science perspectives. The reader will be able to grasp physiological mechanisms on one hand while associating narcolepsy with clinical diseases on the other. In narcolepsy there are disrupted night-day and sleep-wakefulness rhythms. Once this rhythm is hindered, the individual is confronted with biological, psychological and social problems. Narcoleptics are faced with the risk of collapsing and being knocked down to the floor while in kitchen or at the park, when driving in the traffic or walking down the stairs at any given moment.
\r\n\tThis book will not only provide a resource for physicians who will be helping this group of patients, but will at the same time contribute to the pathophysiology of the disease as it contains up to date information for researchers focusing on innovations in this field.
",isbn:null,printIsbn:"979-953-307-X-X",pdfIsbn:null,doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,hash:"5b19c98934802d13418f734de27786cd",bookSignature:"Associate Prof. Murat Kayabekir",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/9780.jpg",keywords:"HLA types, Hypocretin System, Orexin Deficiency, REM Sleep, Familial Aspects, HLA-peptide, HLA DQB1*0602, Twin Studies, Sleepiness, Cataplexy, Sleep Paralysis, Hallucinations, Epworth Sleepiness Scale, SOREMPs, MSLT, CSF Hypocretin (Orexin), Behavioral Approaches, Pharmacologic, Children, Medication Side Effects",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"November 13th 2019",dateEndSecondStepPublish:"March 24th 2020",dateEndThirdStepPublish:"May 23rd 2020",dateEndFourthStepPublish:"August 11th 2020",dateEndFifthStepPublish:"October 10th 2020",remainingDaysToSecondStep:"a year",secondStepPassed:!0,currentStepOfPublishingProcess:5,editedByType:null,kuFlag:!1,biosketch:null,coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"265598",title:"Associate Prof.",name:"Murat",middleName:null,surname:"Kayabekir",slug:"murat-kayabekir",fullName:"Murat Kayabekir",profilePictureURL:"https://mts.intechopen.com/storage/users/265598/images/system/265598.jpg",biography:"Murat Kayabekir is an Associate Professor in the Department of Physiology at Atatürk University Medical School. He has completed Physiology training at Hacettepe University Medical School. He worked as a physiology specialist at the Sleep Disorders Centers and Electrophysiology Laboratory as a founder and director. His scientific fields of study are: neurophysiology, electrophysiology, sleep physiology and disorders, PSG and computer engineering, snoring sound analysis, sleep EEG and sleep spindles, innovative products, REM behavior disorders, narcolepsy, sleep apnea, bruxism, insomnia, and epilepsy during sleep.",institutionString:"Atatürk University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Atatürk University",institutionURL:null,country:{name:"Turkey"}}}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"16",title:"Medicine",slug:"medicine"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"252211",firstName:"Sara",lastName:"Debeuc",middleName:null,title:"Ms.",imageUrl:"https://mts.intechopen.com/storage/users/252211/images/7239_n.png",email:"sara.d@intechopen.com",biography:"As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. From chapter submission and review, to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. 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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"878",title:"Phytochemicals",subtitle:"A Global Perspective of Their Role in Nutrition and Health",isOpenForSubmission:!1,hash:"ec77671f63975ef2d16192897deb6835",slug:"phytochemicals-a-global-perspective-of-their-role-in-nutrition-and-health",bookSignature:"Venketeshwer Rao",coverURL:"https://cdn.intechopen.com/books/images_new/878.jpg",editedByType:"Edited by",editors:[{id:"82663",title:"Dr.",name:"Venketeshwer",surname:"Rao",slug:"venketeshwer-rao",fullName:"Venketeshwer Rao"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"4816",title:"Face Recognition",subtitle:null,isOpenForSubmission:!1,hash:"146063b5359146b7718ea86bad47c8eb",slug:"face_recognition",bookSignature:"Kresimir Delac and Mislav Grgic",coverURL:"https://cdn.intechopen.com/books/images_new/4816.jpg",editedByType:"Edited by",editors:[{id:"528",title:"Dr.",name:"Kresimir",surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"46090",title:"A Systematic Approach to Visual System Rehabilitation — Population Receptive Field Analysis and Real-time Functional Magnetic Resonance Imaging Neurofeedback Methods",doi:"10.5772/58258",slug:"a-systematic-approach-to-visual-system-rehabilitation-population-receptive-field-analysis-and-real-t",body:'Visual information transmission flows from the retinal ganglion cells to the lateral geniculate nucleus and then to the primary visual cortex (V1), the chief cortical relay of visual information and in turn, to “higher” extrastriate areas. Beyond area V1, visual processing is distributed across multiple interconnected brain areas, the precise role of which and their interactions are not yet, completely understood. To add to the dynamic complexity of the system, feedback from higher areas and modulation by top-down processes, such as attention are often critical in the formation of visual percepts (Deco and Lee; 2004; Olhausen, 2003; Kastner and Ungerleider, 2000; Mumford, 1994; Hubel and Weisel, 1977).
Impairment of visual function can occur at any point along the visual pathway from the eye to the cortex. We focus our discussion here on V1 lesions, which result in dense contralateral visual field defects known as “scotomas”. Scotomas as a consequence of area V1 lesions often involve the contralateral half of the visual field resulting in hemianopia, or a contralateral visual field quadrant the consequence of which is quadrantanopia. V1 lesions are the most prevalent injury of the visual cortex, often occurring as a result of posterior cerebral artery (PCA) stroke, hemorrhage, or traumatic brain injury (TBI) (Pambakian and Kennard, 1997; Zhang et al., 2006; Ajina and Kennard, 2012). Twenty to thirty percent of stroke survivors experience visual disability (Taylor, 1997; Gilhotra et al., 2002; Giorgi et al., 2009), while the incidence of significant visual perceptual impairment in TBI victims exceeds 50% in some studies (McKenna et al., 2006; Lew et al., 2007; Elisevich et al., 1984). The loss of visual perception inside a large scotoma can significantly affect the patient’s ability to perform daily tasks, navigate in unknown environments, and function independently (Ajina and Kennard, 2012; Rizzo and Robin, 1996; Riggs, et al., 2007). Visual rehabilitation is clearly necessary for the daily living function of these patients. The literature describing visual rehabilitation efforts is extensive and doing justice to it all is beyond the scope of this chapter. We should mention at the outset that we will not discuss, the large literature on practicing eye movement strategies or, using prisms to remap the unseen onto the seen part of the visual field. Instead, we focus on novel approaches that aim to enhance perception inside the visual field scotoma.
To date, no established method exists to rehabilitate visual perception in adult patients with lesions of the primary visual cortex. The lack of effective methods for rehabilitation has led to the general perception that the adult visual cortex has decreased capacity to compensate after injury. This engenders diminished hope that successful strategies can be established to promote the recovery of visual perception after cortical injury. This is partly justified, as several attempts claiming to have achieved significant results have failed. The most notable recent example is an effort by Nova Vision claiming that a rehabilitative paradigm based on a “saccade-to-target” task could significantly shrink dense visual field scotomas (Kasten et al.; 1998, 1999; 2000, 2001, 2006; Poggel et al., 2001, 2004, 2006; Sabel et al., 2000, 2004; Werth and Moehrenschlager, 1999; Zihl and VonCramon, 1979; Zihl and Von Carmon, 1985; Jobke et al., 2009). Albeit early psychophysical training methods and Nova Vision studies were seen as promising (Kerkhoff et al., 1992; Kerkhoff et al., 1994; Julkunen, 2003; Kasten et al., 1995; 1998a, b, 1999; 2000, 2001; Poggel et al., 2001, 2004, 2006; Sabel et al., 2000, 2004; Werth and Moehrenschlager, 1999; Zihl and VonCramon, 1979; Zihl, 1990), later studies implementing rigorous eye movement controls failed to find a reduction in the visual field scotoma in patients with V1 lesions (Reinhard et al., 2005; Horton, 2005a; Horton, 2005b; Pleger et al., 2003).
Although these efforts are disappointing, the rehabilitation of scotomas resulting from V1 injuries is not altogether a cause without hope (Kasten et al., 1998; Huxlin et al., 2009; Schmid et al., 2010; Poggel et al., 2010; Sahraie et al., 2010; Schmid et al., 2009; Alexander and Cowey, 2009). On one hand, patchy injuries to area V1 or its inputs in the optic radiation seem to be amenable to rehabilitation, as training can help recruit and strengthen surviving connections. In support of this, Sabel and colleagues (Kasten et al., 1999) showed that ~74% of patients with partial optic nerve involvement showed significant recovery with training, compared to 29% of patients with post-chiasmatic lesions. This is likely the result of increased recruitment of partially-lesioned fiber pathways or islands of residual vision (Fendrich et al., 1992). On the other hand, recent evidence suggests that even when lesions to area V1 or, its proximal inputs are dense, it may be possible to some extent to functionally bypass the area of the injury:
First, there exist anatomical pathways that bypass the area of V1 injury (fig. 1). One such pathway projects from the retina to the koniocellular (intercalated) layers of the lateral geniculate nucleus directly, or to the superior colliculus and from there to extrastriate cortex. This pathway originates in the retinal Pγ class of ganglion cells, which comprises ~10% of the total ganglion cell number is particularly dense near the fovea (Henry and Reid, 2000), and is known to survive retrograde degeneration following V1 lesions (Cowey and Stoerig, 1989). Another V1-bypassing pathway projects from the retina to the pulvinar directly or via the superior colliculus and from there to the extrastriate visual areas. Notably, although parvocellular and magnocellular projections to the lateral geniculate nucleus and beyond markedly atrophy following striate cortical lesions (Vanburen, 1963; Mihailovic et alo., 1971), superior collicular (Dineen et al., 1982) and pulvinar (Cowey, 1974) projections remain unchanged.
Overview of relevant anatomical visual pathways (Modified with permission from Stoerig and Cowey, 1997): Possible extra-geniculostriate pathways contributing to blindsight behavior, and residual extrastriate cortex activity, adapted from Stoerig and Cowey (Stoerig and Cowey, 1997). This diagram shows known retinofugal inputs, and some of the subsequent projections. On the right, the pathways are shown with intact V1. On the left V1 has been lesioned. Two pathways stand out as potentially mediating the residual activity observed in extrastriate cortex (Rodman et al., 1989; Schmid et al., 2009; Schmid et al., 2010), as well as related aspects of blindsight behavior: 1) The koniocellular pathway (dotted lines) from the K (intercalated) layers of the thalamus directly to areas V2, V3, V4, V5/MT. This pathway originates in the retinal Pγ class of ganglion cells, comprising ~10% of total ganglion cells, survives retrograde degeneration following V1 lesions, and is particularly dense near the fovea (Cowey and Stoerig, 1989; Henry and Reid, 2000). This pathway receives both direct retinal and superior collicular input. 2) The projection from the inferior pulvinar to V2, V3, V4, V5/MT, which also receives direct input from the retina, as well as input from the retinotectal (superior colliculus) pathway. PGN: pre-geniculate nucleus, ON: olivary nucleus, NOT: nucleus of optic tract, MTN, LTN, DTN: medial, lateral, dorsal terminal accessory optic nuclei, SCN: suprachiasmatic nucleus, SC: superior colliculus, PI: inferior pulvinar.
Second, these pathways have been shown to be functional under certain conditions. Lesions of area V1 or its post-chiasmatic afferents deprive the extrastriate visual cortex of its main input and result in a dense contralateral visual field scotoma, in which conscious visual perception is thought to be irreversibly lost (Cowey and Stoerig, 1991; Stoerig and Barth, 2001). Remarkably, despite the absence of a conscious visual percept, a capacity to process certain attributes of the visual stimulus persists inside the scotoma, the phenomenon known as "blindsight" (Kluver, 1936; Poppel et al., 1973; Weiskrantz, 1974). The blindsight phenomenon implies that at least some extra-geniculo-striate retinofugal pathways (Cowey, 2010; Schmid et al., 2010; Weiskrantz, 2004; Schoenfeld et al, 2002; Moore et al., 2001; Goebel et al., 2001; Stoerig and Cowey, 1997; Moore et al., 1995; Cowey and Stoerig, 1991; Girard et al., 1991; Pasik and Pasik, 1971) can functionally bypass area V1. This is corroborated by experiments in humans and primates, which have directly demonstrated that extrastriate areas can be modulated by the visual stimulus in the absence of V1 input (Rodman et al., 1989; Baseler et al., 1999; Goebel et al., 2001; Schmid et al., 2009; Schmid et al., 2010). For example, Rodman and Gross demonstrated that area V5/MT can be directly activated through the pathway bypassing area V1 via the superior colliculus (Rodman et al., 1989; Rodman et al., 1990), while Schmid et al. (Schmid et al., 2009; Schmid et al., 2010) showed that early extrastriate areas V2, V3 can be visually modulated by the LGN in the absence of V1 input. Schmid et al. further elucidated that transiently inactivating LGN in V1 lesioned animals not only abolishes visual modulation in areas V2, V3 but also, returns the monkey’s blindsight performance to chance. Unfortunately, the V1-bypassing pathways that mediate the blindsight phenomenon are weak and of limited practical value. The potential of these pathways to induce recovery remains unrealized. This underscores the need to examine the mechanisms underlying the recovery reported in recent studies (Huxlin et al., 2008; Huxlin et al., 2009; Sahraie et al., 2006) in order to understand how to develop effective rehabilitative paradigms. It remains to be examined whether novel neuro-rehabilitative training algorithms can strengthen V1-bypassing pathways to derive practical benefit.
Third, training can improve performance inside the scotoma of subjects with area V1 lesions. Behavioral training in healthy subjects can improve visual performance by inducing plasticity and reorganization in the physiology of visual networks (Karni and Sagi, 1991; Liu et al., 2000; Yang and Maunsell, 2004; Ahissar and Hochstein, 1997). Perceptual learning is retinotopically specific, suggesting it involves a use-dependent synaptic enhancement induced by pre-and postsynaptic activity (Brown et al., 1988). Studies in humans (Pleger et al., 2003; Taub et al., 2002; Weiller, C. 1998; Lindberg et al., 2003, Takeuchi et al., 2005) and animals (Rudolph et al., 1994; Rudolph and Pasternak, 1999; Rudolph and Delay, 1993, Fabre-Thorpe et al., 1994; Friel et al., 2000; Huxlin and Pasternak, 2004) with V1 lesions, as well as behavioral studies of “blindsight” (Chokron et al., 2008; Stoerig and Cowey, 1997; Sahraie et al., 2006; Overgaard, 2011) suggest that visual performance in the scotoma can also improve with training (Raninen et al., 2007; Henriksson et al., 2007). More recently, Huxlin et al. (2006)-following their work on cats-trained V1+lesioned patients to perform a two-alternative forced choice random dot kinematogram (RDK) direction of motion discrimination task in their blind hemifield (Huxlin et al., 2009). Remarkably, direction of motion discrimination thresholds recovered from chance to normal at trained locations (Huxlin et al., 2009). Eye movements were strictly controlled, and there were no obvious artifacts that could confound the findings. Recovery was retinotopically specific, but could be extended by training consecutively adjacent locations that lay progressively deeper inside the scotoma, inducing recovery up to ~20° from the scotoma border in one subject. Furthermore, recovery in this task appeared to carry some practical significance, as the subjects’ ability to dodge basketballs “thrown” at them from the blind hemifield in a virtual reality environment, improved (Iorizzo et al., 2011). These findings sparked renewed interest in studying visual rehabilitation strategies. This is encouraging, but it is necessary to note that visual rehabilitation results appear more variable across the literature (see table 1, in a recent review by Sabel et al. (Sabel et al., 2011), and (Horton, 2005a; Horton, 2005b) for a critical review of the field). Three important questions remain to be answered regarding scotomas resulting from V1 lesions: i) can visual rehabilitative training result in improved visual performance of practical significance? ii) what is the underlying mechanism of recovery? and 3) what is the optimal method for visual rehabilitative training?
In summary, even though visual rehabilitation following area V1+lesions is a difficult problem, it is not a hopeless endeavor. Anatomical pathways bypassing the area of the lesion exist, and they have been demonstrated to be functional in certain situations. Although early trials have been inconclusive, a recent report by Huxlin et al. (Huxlin et al., 2009), suggests that some recovery is possible, at least in the domain of visual motion perception. Further studies are needed: (i) to independently corroborate the results of Huxlin et al. (Huxlin et al., 2009); (ii) to understand what visual attributes and types of lesions are amenable to recovery; and (iii) to study the mechanism of recovery. It is important to note that we do not expect even successful rehabilitation methods to restore vision to pre-lesion levels. For one, the quality of the restored visual percept will most likely differ from normal. The reason is that, following V1 lesions, the magnocellular and parvocellular pathways largely degenerate (fig. 1), shifting the balance towards the koniocellular pathway, which is spared. Nevertheless, successful visual rehabilitation can train patients to use the qualitatively and quantitatively different form of visual perception mediated by appropriately strengthened V1-bypassing pathways. The design of such a neuro-rehabilitative approach will confer considerable practical significance.
To design effective visual rehabilitation strategies for cortical scotomas, we have to grapple with the issue of lesion variability. Cortical lesions differ from individual to individual, and this impacts whether or not the resulting scotoma is amenable to rehabilitation. Consequently, some patients show good recovery following visual rehabilitative training (Kasten et al., 1998; Huxlin, 2009) and others no recovery at all (Reinhard et al., 2005; Horton et al., 2005a; Horton et al., 2005b; and our personal observation). It remains unclear what criteria one may use to select patients more likely to recover. Scotomas are mapped using visual field perimetry to determine the part of the visual field where visual perception is impaired. A problem faced in studies of visual rehabilitation is that patients often have heterogeneous lesions, even though the extent and density of their perceptual visual scotomas, measured by perimetry, match. Conversely, the anatomical characterization of the lesion is not always a reliable indication of the properties or, the extent of the resulting scotoma. Consequently, neither visual field perimetry maps nor, purely anatomical information are sufficient indicators of the capacity for rehabilitation.
A measure of the ability of visual stimuli presented inside the scotoma to elicit perceptually sub-threshold activity in spared visual cortex would add valuable information. Functional magnetic resonance imaging (fMRI) can be used to identify which sectors of the visual field scotoma remain able to transmit visual information to spared regions of the visual cortex (fig. 3), downstream from the lesion. This can help to classify functionally different types of lesions that yield similar scotomas, and to identify regions of the scotoma that elicit different patterns of functional activation and may therefore, have different capacity for rehabilitation. The underlying hypothesis is that parts of the scotoma that can still convey visual information to higher areas, bypassing the cortical lesion, will be more amenable to rehabilitation. Moreover, the extrastriate areas that become activated may reveal clues about the attributes of the visual stimulus that will be more amenable to rehabilitation.
We propose to apply state-of-the-art fMRI methods to characterize voxel by voxel, how population receptive fields (pRF; Wandell et al., 2007; Dumoulin and Wandell, 2008; Amano et al., 2009; Lee et al., 2013) in spared visual areas are organized to cover the visual field following cortical visual pathway injuries (see figs. 2, and 3) (Baseler et al., 2011). The pRF of a voxel refers to the region of visual space that elicits a visually-induced modulation of the BOLD (Blood-Oxygen-Level-Dependent) signal in that voxel. Various pRF models have been proposed in the literature (Dumoulin and Wandell, 2008; Zuiderbaan et al., 2012; Lee et al., 2013). The simplest and most commonly used is a circularly symmetric, 2D Gaussian model with center (x,y) and radius (σ) (Dumoulin and Wandell, 2008). The BOLD time series predicted by this model is derived by convolving the pRF model with the stimulus sequence and the BOLD hemodynamic response function (HRF; Boynton et al., 1996; Worsley et al., 2002). The pRF’s parameters are then estimated by fitting the BOLD signal predicted by the model to the actual BOLD signal measurement obtained from each voxel.
The population receptive field (pRF) model. This model estimates the region of the visual field that elicits a response in a small region (voxel) of the visual cortex. One implementation of the pRF model is a circularly symmetric Gaussian receptive field in visual space whose center and radius are estimated by fitting the BOLD signal responses to the estimated responses elicited by convolving the model with the moving bar stimulus and the hemodynamic response. (a) shows the estimated position and size of the pRF in the visual field of a voxel located in V1. (b) shows the BOLD time-series (dashed line) and the model prediction (solid line) from the same voxel. The model explains a large amount of variance in the time course data. Below, we illustrate the position and direction of motion of the stimulus bar that elicited the peaks in the BOLD signal.
Early methods of retinotopic mapping, such as ring and wedge stimuli (DeYoe et al., 1996; Dougherty et al., 2003; Engel et al., 1994; Sereno et al., 1995), as well as moving bar stimuli (Wandell et al., 2007), which traverse the visual field in different directions can usually provide robust pRF estimates (see fig. 2) rendering them useful for studying cortical reorganization. One limitation of direct-fit pRF estimation methods is that these can result in estimation biases at the scotoma border (Lee et al., 2013). Recently, a 2-step pRF estimation method based on first estimating the pRF topography, thresholding it, and then fitting an appropriate pRF model has been introduced to largely circumvent this problem (Lee et al., 2013). This is the preferred method to use near the scotoma border.
Population receptive field analysis can measure the residual capacity of areas controlling vision to process visual information following V1+injuries. Plotting the pRFs from all voxels of a given area together as a color map reveals the “visual field coverage map” of that area. This represents the part of the visual field that can visually modulate the area. Note that visual field coverage maps of extrastriate areas often overlap with the area of the dense perceptual scotoma, measured by visual field perimetry. This is illustrated in the second panel of figure 3 for the human middle temporal cortex (hV5/MT+), an area important for visual motion perception (Zeki et al., 2004; ffytche et al., 2000; Zeki and ffytche et al., 1998). Note that the pRF maps of many hV5/MT+voxels lie inside the perceptual scotoma (left upper quadrant in fig. 3). In fact, in this specific case (fig. 3), they cover the whole extent of the scotoma. This implies that hV5/MT+is activated by visual stimuli presented in the left upper quadrant even though the subject does not perceive these stimuli. This suggests that there is a functional V1-bypassing pathway to area hV5/MT+that may promote recovery, if appropriately rehabilitated. Therefore, a promising rehabilitation strategy is to strengthen this pathway. It is likely, that it will be easier to rehabilitate visual motion perception inside parts of the scotoma that are covered by the pRF maps of area hV5/MT+. It is also, likely that rehabilitation will be even easier in parts of the scotoma that are also covered by the pRF maps of spared, earlier, visual areas. The third panel of fig. 3 illustrates the visual field coverage map of the spared portion of area V1. Note, that this extends above the horizontal meridian to partly overlap with the area of the scotoma. This defines two regions where visual rehabilitation may be different, according to the above hypothesis. The region of the scotoma indicated by the green arrow is represented in the coverage maps of both area hV5/MT+and the spared area V1, and is expected to have higher potential for rehabilitation. The region of the scotoma indicated by the blue arrow is represented only in the coverage map of area hV5/MT+and is expected to present a more difficult challenge for rehabilitation. Visual field coverage maps (Amano et al., 2009) obtained by fMRI are an important adjunct to perimetric maps as they often provide complementary information (personal observation) and will likely be useful in tailoring therapy to appropriate visual field locations.
Visual Field Coverage Maps of spared visual areas with significant overlap with the region of the scotoma, define visual field locations that may be more amenable to rehabilitation. Humphreys VF Map panel: Humphreys 10-2 visual field map, illustrating that the subject had a dense left upper quadrantanopia. Area hV5/MT± panel: The visual field coverage map (Amano et al., 2009) of the right hV5/MT+shows visual field locations that evoke significant activity from hV5/MT+of the lesioned hemisphere. At each visual field location, the highest pRF value of all pRFs that cover this location is plotted. PRF normalization limits the range of values between 0-1. Large values indicate significant visual modulation. Note, that although the subject is blind in the left upper quadrant, the subject\'s hV5/MT+responds to stimuli presented in the left upper quadrant. A potential advantage of using visual field coverage maps is that therapy can be individualized to each patient\'s appropriate visual field locations, which are not necessarily predictable from perimetric maps. Area V1 Panel: Visual field coverage map of the spared right area V1 extends above the left horizontal meridian into the dense area of the scotoma seen in the Humphreys map. This activity may be induced in orthotopic voxels that survive and are partially active following the V1 lesion (Kasten et al., 1998), or in anatomically ectopic V1 voxels that belong to the upper occipital lobe, which would ordinarily have had receptive fields in the left lower visual field quadrant. Note, that this area does not cover the entire quadrant, as is the case of the coverage map in area hV5/MT+. This mismatch will likely have implications for rehabilitation. For example, it may be easier to rehabilitate regions of the scotoma where the visual field coverage maps of spared V1 and hV5/MT± are congruent (green arrow), as opposed to incongruent (blue arrow). Control with AS (artificial scotoma) Panel: Visual field coverage map from the entire area V1 of a normal subject with an “artificial scotoma” simulating left upper quadrantanopia. By artificial scotoma we mean an area of the stimulus being excluded, in order to simulate the patient’s scotoma. Note, that the visual field coverage map in this control case is as expected, i.e. it does not encroach into the left upper quadrant.
Fig. 4 illustrates that pRF measurements in area hV5/MT+ipsilateral to a chronic V1+lesion differ from those in the normal hemisphere. Specifically, pRFs in hV5/MT+voxels of the lesioned hemisphere are smaller on average, and pRF-centers cluster near the vertical meridian (x=0; fig. 4C). Training may further change the pRF topography. Changes in the pRF topography before and after training can be a potentially useful biomarker for evaluating different rehabilitation paradigms before perceptual recovery becomes evident. Applying this approach systematically can help to formulate new hypotheses guiding future neuro-rehabilitation attempts. One hypothesis is that following visual motion rehabilitation training the sensitivity to motion stimuli of hV5/MT+ will increase, which will positively correlate with behavioral recovery. Alternatively, attentional networks or, other “higher” areas that receive input from hV5/MT+may reorganize to process visual motion information more effectively. Analyzing pRF maps obtained from visually responsive areas before and after training, will allow us to investigate the above hypotheses and to adopt appropriate rehabilitation strategies.
hV5/MT± pRF mapping in a hemianopic patient: (A) Inflated occipital lobe of the normal (left) and lesioned (right) hemisphere with hV5/MT+outlined on the eccentricity map. Mid-inset is a 30-2 Humphrey perimeter showing dense left hemianopia. (B) Illustrates the method used to calculate pRF parameters (same as in fig. 2). The pRF model parameters are optimized to fit the BOLD signal, voxel by voxel. Note the close fit between the BOLD time-series (dashed line) and the pRF model prediction (solid line). The position and direction of motion of the stimulus bar that elicited each response is illustrated (bottom). (C) The X coordinate of the pRF centers in hV5/MT+of the normal (left) hemisphere is evenly distributed while in the lesioned (right) hemisphere it clusters near the vertical meridian (x=0). Note however, that the pRF centers still lie within the scotoma (negative X values). (D): Distribution of pRF radii of hV5/MT+voxels in the intact (left) and in the lesioned (right) hemisphere. The distribution of pRF radii shifts to smaller values in area hV5/MT+of the lesioned hemisphere. This may be because ipsilesional hV5/MT+voxels are driven by a V1-bypassing pathway that drives visual periphery less effectively.
In summary, pRF measurements:
Classify subregions of the perimetric scotoma depending on how they are covered by spared visual areas; different regions will likely have different potential for rehabilitation.
Allow us to study the mechanism by which rehabilitation strategies improve visual performance.
Serve as quantitative biomarkers to evaluate the effects of training before perceptual recovery becomes evident, accelerating the pursuit of a rational strategy for visual rehabilitation.
Other methods of analysis can be applied here, but we do not have the space to do them justice. We mention briefly the promise of recent developments in effective connectivity analysis (Fuji et al., 2009; Stilla et al., 2008; Hinrichs et al., 2006) and diffusion tensor imaging (Wedeen et al., 2012; Yeatman et al., 2012; Van den Stock et al., 2011; Sherbondy et al., 2008; Fields, 2008; Okada et al., 2007; Schoth et al., 2006; Kikuta et al., 2006; Dougherty et al., 2005; Taoka et al., 2005; de Gelder et al., 2005; Reinges et al., 2004; Morris et al., 2001) for studying inter-area pathways that survive post-lesion, and whether they can become stronger by training. Population receptive field and effective connectivity analysis can be used to explore visual system reorganization and recovery following injury, and to generate concrete hypotheses on how to enhance and accelerate recovery of visual function by the application of cutting-edge rehabilitative strategies.
To date, we have little understanding of how the visual cortex reorganizes after injury, and no proven effective treatment strategies to rehabilitate the recovery of visual perception in the affected portion of the visual field in V1-lesioned patients. Understanding how to manipulate the brain’s capacity for plasticity is an important step in the long-term effort to design treatments aiming to enhance the ability of the nervous system to recover after injury. To make progress along this front, we need to: i) study the mechanisms by which the adult brain adapts and reorganizes after injury; and ii) devise approaches that will allow us to manipulate the process of reorganization to induce visual recovery.
The network of visual areas can be viewed as a heavily interconnected circuit subject to a series of hierarchy rules. Early areas usually process sensory information initially, by passing it on to higher areas, and in turn, extract “higher” order features and control the flow of information through feedback loops. Increased performance following training can therefore be the result of changes that occur in early areas (Schoups et al., 2001; Yotsumoto et al., 2008; Censor and Sagi, 2009; Karni and Sagi, 2008), or the result of changes that occur in “higher” visual areas and attentional networks (Law and Gold, 2008; Yang and Maunsell, 2004; Lewis et al., 2009). Area V1 injuries, interrupt the cardinal feed-forward pathway but, as discussed above, visually driven information can still activate surviving extrastriate areas through bypassing routes (Cowey, 1974; Dineen et al., 1982; Rodman et al., 1989; Cowey and Stoerig, 1997; Baseler et al., 1999; Goebel et al., 2001; Schmid et al., 2009; Schmid et al., 2010). The pattern of activity elicited in surviving visual areas interacts with higher “centers” in frontal, parietal and temporal areas but, in the absence of V1 input, fails to generate a strong visual percept. We suggest here two general, non-mutually exclusive approaches to visual rehabilitation:
“Bottom-up” approach: Visual rehabilitation strengthens V1-bypassing pathways to increase the response elicited in surviving extrastriate areas.
“Top-down” approach: Visual rehabilitation reorganizes higher “centers” to learn to process the modulated patterns of activity elicited in extrastriate areas by V1-bypassing inputs.
Non-invasive approaches to visual rehabilitation aim to enhance these pathways by recruiting the mechanisms of plasticity the brain uses for learning. Various behavioral approaches have been used. They usually involve performing a visual task that directs attention to a sub-threshold stimulus, requires a choice, and then provides feedback about correct and incorrect choices (see fig. 5). Although such methods are effective for perceptual learning in general (Yotsumoto et al., 2008; Law and Gold, 2008; Yang and Maunsell, 2004), in the domain of rehabilitation of a dense perceptual scotoma results have been at best variable (Huxlin et al., 2009; Raninen et al., 2007\n\t\t\t\tSahraie, et al., 2006; Reinhard et al., 2005; Horton et al., 2005a; Horton et al., 2005b; Pleger et al., 2003). The most notable exception has been a recent well-controlled report by Huxlin and co-workers (Huxlin et al., 2009), which demonstrated strong recovery of direction of visual motion perception inside the scotoma of 5 hemianopic subjects (Huxlin et al., 2009; Huxlin, 2006). Two other groups independently, Sahraie et al. and Raninen et al., report that visual sensitivity can improve with training in humans with homonymous scotomas (Sahraie, 2006; Henriksson et al., 2007; Raninen et al., 2007). Encouraging results were also obtained by Pleger and co-workers, who showed that visual cortex reorganization was possible via daily visual stimulation training over a period of 6 months in 3 subjects with partial cortical blindness (Pleger et al., 2003). Although these are encouraging reports, the issue remains far from settled (Horton et al., 2005a; Horton et al., 2005b). Additional studies corroborating recent results and probing the mechanism of recovery are clearly needed to guide the implementation of new, more effective rehabilitation strategies. In what follows, we discuss the promise and challenges of a new visual rehabilitation approach, which aims to use “real time” fMRI neurofeedback to train subjects to promote plasticity in V1-bypassing pathways relevant to recovery.
Less than two decades ago, the real-time functional magnetic resonance (rt-fMRI) method has been introduced (Cox, 1995) in the field of neuro-rehabilitation, which extracts the BOLD (Blood-Oxygen-Level-Dependent) signal from the subject\'s brain in real-time and uses it to provide feedback to the subject. Since the BOLD signal reflects neural activity this approach is called real-time fMRI neurofeedback (rt-fMRI nFb). Multiple studies have shown that rt-fMRI nFb, can train subjects to modulate the magnitude and spatial extent of the activity elicited in various cortical and subcortical areas (Berman et al., 2011; Bray et al., 2007; Caria et al., 2007; Caria et al., 2010; Chiew et al., 2012; deCharms et al., 2004; deCharms et al., 2005; Frank et al., 2012; Haller et al., 2010; Hamilton et al., 2011; Hinds et al., 2011; Johnson et al., 2012; Johnson et al., 2011; Johnson et al; 2010; Lee et al., 2012; Li et al., 2012; McCaig et al., 2011; Papageorgiou et al., 2009a; Papageorgiou et al., 2009b; Papageorgiou et al., 2013; Posse et al., 2003; Rota et al., 2009; Ruiz et al., 2013; Scharnowski et al., 2012; Shibata et al., 2011; Subramanian et al., 2011; Sulzer et al., 2013; Veit et al., 2012; Weiskopf et al., 2007; Weiskopf et al., 2004; Weiskopf et al., 2003; Yoo and Jolesz, 2002; Yoo et al., 2008; Zotev et al., 2011). The goal of this approach is to train subjects to control the pattern of their brain activity in a way that promotes a desired behavior. It can also be used to boost the neural capacity for learning and plasticity (Shibata et al., 2012; Scharnowski et al., 2012; Shibata et al., 2011; Weiskopf et al., 2004; deCharms et al., 2004; deCharms et al., 2005). If this is applied effectively, it could serve as a useful tool to promote neuro-rehabilitation.
The ability of rt-fMRI nFb to induce a behavioral change was first shown by Weiskopf et al. (Weiskopf et al., 2003) and deCharms et al. (deCharms et al., 2005). In the deCharms et al. study, chronic-pain patients were coached to decrease their pain by learning to control the BOLD signal intensity of the rostral anterior cingulate cortex (rACC), a region known to be involved in pain perception (Apkarian et al., 2005; Peyron et al., 2000). After training, subjects were able to voluntarily increase or decrease the rACC BOLD signal intensity, which was correlated with an increased or decreased level of pain, respectively; i.e., a 50% decrease in the rACC activity of chronic pain subjects corresponded approximately to a 64% decrease in their pain. This effect was specific to rtfMRI nFb training applied to rACC; i.e., no effect was seen after similar training conducted without rtfMRI NFb or, after sham rtfMRI nFb training derived from the activity of another subject\'s rACC.
Similar results have been obtained in other cortical and subcortical domains (Posse et al., 2003; Lee et al., 2011; Hamilton et al., 2011; Ruiz et al., 2013). A recent study showed that healthy volunteers were able to volitionally regulate the activity of their insula when given rt-fMRI nFb (Lee et al., 2011). Posse and his team (Posse et al., 2003) trained subjects to upregulate their amygdala, an area whose level of activity is associated with sad affect and depression (Wang et al., 2012; Anand et al., 2007; Liu et al., 2011). Amygdala upregulation induced by rt-fMRI feedback was positively correlated with self-ratings of sadness across repeated fMRI sessions (Posse et al., 2003). Conversely, Hamilton et al. used rt-fMRI nFb to train subjects to downregulate subgenual ACC and posterior cingulate cortex, resulting in positive mood induction (Hamilton et al., 2011). Sham rt-fMRI nFb showed no effect. Ruiz et al. showed that schizophrenic patients can be trained by rt-fMRI nFb to voluntarily control their anterior insula bilaterally (Ruiz et al., 2013). The effect of bilateral anterior insula activation is reflected on their ability to recognize face emotion, a known deficit in schizophrenia. These findings collectively, suggest that: 1) rt-fMRI nFb can be used to train subjects to voluntarily control specific areas; 2) changes in the activity of certain areas can be associated with significant behavioral changes; 3) rt-fMRI nFb training can achieve stronger behavioral results than similar training without nFb; and 4) rt-fMRI training can induce reorganization that can outlast the period of the training inside the magnet and even induce visual perceptual learning (Shibata et al. 2011).
Shibata et al. in a seminal study used rt-fMRI nFb to induce perceptual learning (Shibata et al., 2011). Rt-fMRI nFb methods were used to enable subjects to induce activity patterns in their early visual cortex corresponding to one particular orientation. Initially, the subjects performed an orientation discrimination task and a decoder of area V1/V2 activity was constructed to classify a pattern of the measured fMRI signals into one of three orientations. Once the decoder was constructed, each subject participated in a 5 to 10-day rt-fMRI nFb stage, during which they learned to induce patterns of activity in areas V1/V2 corresponding to the target orientation. During this stage, subjects were instructed to maximize the signal delivered to them via feedback, but were not told how to induce the desired patterns of activity that would result in increased activity. Subjects did not know what was to be learned. Using this strategy they were able to induce visual perceptual learning specific to the target orientation in areas V1/V2. Learning occurred as a function of the subject’s ability to elicit the particular pattern of activation corresponding to the target orientation in early visual areas. Remarkably, subjects were able to generate this pattern simply by being given the instruction to maximize feedback, without being aware that the pattern to be elicited was related to orientation. This demonstrated that the rt-fMRI nFb method can be used to induce highly specific activity patterns within a brain region and that repeatedly eliciting the desired pattern of activity is sufficient to induce plasticity in early visual areas. These findings suggest that rt-fMRI nFb training can be used to induce targeted and individualized plasticity in the visual system.
The studies described above (Ruiz et al., 2013; Linden et al., 2012; Subramanian et al., 2011; Shibata et al., 2011; Lee et al., 2011; Hamilton et al., 2011; deCharms et al., 2004; Posse et al., 2003) show that manipulating the activity in select brain areas can induce plasticity. Modified paradigms can also be designed to increase plasticity along specific pathways, by co-activating input and recipient neuronal populations. For example, a projection from area A to recipient area B in the brain can increase or, decrease in strength, depending on the relative activity between input projections from A and recipient neurons in B. Rt-fMRI nFb does not have the temporal resolution necessary to precisely implement Hebbian mechanisms of plasticity. Nevertheless it can be used to train the subject to voluntarily manipulate the activity level of select neuronal populations in area B while their input from A is presented. The hypothesis is that “top-down” activation of area B enhanced by nFb judiciously paired with “bottom-up” presentation of inputs that activate A, can increase the strength of the projection A->B either by their interaction or additive effect. Below, we discuss an example outlining how this proposal might work for the rehabilitation of visual motion perception following area V1 lesions (see also fig. 5).
Rt-fMRI nFb paradigm for neurorehabiliation of visual motion perception: The subject lies supine inside the scanner, while s/he is presented with a 0% coherent RDK stimulus. Brain volumes are acquired every 2sec (TR). hV5/MT+(circled) is selected as our ROI. Turbo Brain Voyager software (Brain Innovation) is used to deliver nFb. The BOLD signal in hV5/MT+is estimated in real time (every TR), normalized, and “fed” back, via the length of a horizontal arrow at fixation, to train the subject to upregulate area hV5/MT+. Subjects are instructed to attend to the RDK they are cued towards, either right (R) or left (L) and imagine that it is coherent (when in fact it is not). This increases the level of activity in the contralateral hV5/MT+: (i) superimposing coherent motion via imagery on the right RDK increases left hV5/MT+activity, which is color-coded in red; (ii) superimposing coherent motion via imagery on the left RDK increases right hV5/MT+activity, which is color-coded in blue. The subject uses the length of the arrow to determine the degree of effort and success of his/her strategy. When the rt-fMRI\n\t\t\t\t\t\tnFb driven, “top-down,” hV5/MT+activation crosses a threshold,\n\t\t\t\t\t\tsub-threshold RDK stimuli are presented. The association between “top-down” and “bottom-up” activation will engage Hebbian-like\n\t\t\t\t\t\tlearning mechanisms aiming to strengthen the response of\n\t\t\t\t\t\thV5/MT+to sub-threshold stimuli. The hypothesis is that once these pathways are strengthened, the presentation of sub-threshold stimuli will elicit enough activity in area hV5/MT+to improve performance in the direction of motion discrimination task. We note that hV5/MT+can be upregulated via rt-fMRI nFb enhanced imagery even when it has lost its V1 input. Once the subject learns how to upregulate hV5/MT+inside the magnet over the period of training, we hypothesize that s/he will also be able to transfer this learned voluntary ability during training outside the MRI environment.
Area hV5/MT+is associated with global coherent visual motion perception. The goal is to use rt-fMRI nFb methods to strengthen the neural pathways bypassing the V1 lesion and project to area hV5/MT+in order to improve visual motion perception of random dot kinematogram (RDK) stimuli (see fig. 5). The first step is to train the subject to voluntarily upregulate their hV5/MT+activity. To do this, we ask the subject to practice mental imagery of fully coherent visual motion stimuli in their blind hemifield, moving in the direction of the anticipated stimulus. During mental imagery, the subject receives rt-fMRI nFb proportional to the activity in their hV5/MT+via a visual interface at fixation (red arrow in fig. 5). Subjects are trained to maximize ipsi-lesional hV5/MT+activity using the imagery task. This nFb mediated, “top-down” increase in hV5/MT+activity will then be paired with the presentation of visual motion stimuli that are invisible (sub-threshold) to subjects with V1+lesions. We hypothesize that, by repeatedly presenting sub-threshold visual motion stimuli while hV5/MT+is activated in a “top-down” fashion by nFb, we will engage Hebbian-like association learning mechanisms (Hebb, 1946; Rebesco and Miller, 2011; Gallistel and Matzel, 2013). These mechanisms will promote plasticity in the surviving, V1-bypassing pathways that become activated by the stimulus presentation and project to area hV5/MT+. In other words, we hypothesize that after nFb training, regions of area hV5/MT+deprived of V1 input will respond more strongly to visual stimuli presented inside the scotoma, improving performance. If successful, this strategy will induce a “neural bypass” of V1 function with respect to visual motion perception.
The support vector machine (SVM) algorithm defines area hV5/MT+when it is trained on coherent motion RDKs. Subjects fixated while two RDKs were presented simultaneously on symmetric locations in the right (red color-coded activation) and left (blue color-coded activation) visual hemifields. The RDK presented in the left visual field was always kept at 0% coherence (no global motion direction), while the RDK in the right visual field alternated between 0% coherence and 100% coherence. A support vector machine algorithm was trained on the whole brain to classify when the coherent RDK (right visual field/red-color coded activation) was presented. The color map indicates the region that was important in classifying the presentation of a 100% coherent versus a 0% coherent RDK in the right visual field. As expected, the area underlined by the green crosshairs corresponds to area hV5/MT+. Five subjects tested gave consistent results (3dANOVA2 performed in AFNI, p=0.05).
One advantage that rt-fMRI nFb methods have over behavioral feedback approaches is that specific brain pathways or areas can be selectively trained. It is then, feasible to train targeted components of the neural circuit that are likely to contribute to recovery. One example, is strengthening neural pathways that bypass the region of injury to promote recovery. Thus far, we have been discussing a univariate rt-fMRI nFb approach, where the nFb provided is proportional to the activity of a specific region of interest (in the above example, area hV5/MT+) or, pattern of activity (Shibata et al., 2011). An alternative to the univariate nFb method is the multivariate classification approach (Papageorgiou et al., 2013; Papageorgiou et al., 2009; LaConte et al., 2007; Mourao-Miranda et al., 2005). In this approach, a classification algorithm, usually, the support vector machine (Vapnik, 1995) is trained on a set of relevant data in order to identify the brain networks that are involved in a specific computation (task). This is akin to the localizer that is used to identify the region of interest in the univariate approach. In fact, in the case of presentation of RDK stimuli, the multivariate SVM approach picks out chiefly area hV5/MT+, as expected (see fig. 6 below). However, in other cases, this approach may reveal different patterns of activity than expected, helping to formulate new hypotheses about the networks that might contribute to rehabilitation. Once the parameters of the classification algorithm are trained, the algorithm can be used to provide neuro-feedback to the subject in separate sessions. This approach may be effective in cases where the pathways that need to be modulated to induce recovery are not known a-priori.
Rt-fMRI nFb can be used to selectively upregulate hV5/MT+in a top-down manner during a mental imagery task. In the absence of a coherent moving stimulus, subjects (n=5) were able to use imagery of coherent motion to selectively upregulate hV5/MT+via rt-fMRI nFb training. (A) Non-coherent RDKs were presented symmetrically in the Left (L) and the (R) hemifield and subjects were cued to imagine that the Lor the R RDK contained coherent motion. The level of contralateral hV5/MT+activity was delivered via the length of an arrow at the fixation point. (A1) Red/blue regions correspond to voxels upregulated when the subject is instructed to imagine coherent motion in the right/left visual field, respectively. Similar results are obtained when using a standard GLM (left panel), versus plotting the weight vector of the support vector machine (SVM) algorithm that classifies whether subjects imagined coherent motion to the left versus the right hemifield (right panel). The regions identified correspond to area hV5/MT+in both hemispheres (color red, blue). Therefore,\n\t\t\t\t\t\tsubjects can be trained via rt-fMRI nFb to modulate their\n\t\t\t\t\t\thV5/MT+activity even in the absence of a coherently\n\t\t\t\t\t\tmoving stimulus; (A2) Output (red curve) of a support vector machine classifier indicating the side of the visual field where the subject imagined coherent motion. The correct choice indicated by the black curve; the prediction of the classifier by the red curve. Positive values indicate the subject was instructed to imagine coherent motion on the right, negative on the left. Note that area hV5/MT+activity can predict the subject’s perceptual state. (B1) Eccentricity maps of a subject with left hemianopia illustrating that area hV5/MT+(outlined) of the lesioned (right) hemisphrere can be visually driven. Only the posterior lateral aspect of the two inflated hemispheres is presented. (B2) Illustrates that hV5/MT+can also be upregulated via rt-fMRI nFb training in a V1+lesioned patient.\n\t\t\t\t\t\tLeft Panel: Right (R) PCA lesion, resulting in left (L) hemianopia (inset). Right Panel: Red color-coded areas represent the activity elicited by the subject’s coherent motion imagery in the left (hemianopic) visual field, while blue color-coded area represents non-coherent motion presentation, as generated by GLM. Left hemianopic visual field imagery of coherent motion activated hV5/MT+bilaterally. Preliminary data for implementing the proposal we outlined above are encouraging as they suggest that ipsilesional hV5/MT+activity: (1) conveys information about the stimulus (B1), and (2) can be upregulated using rt-fmri nFb imagery in V1+lesioned patients (B2).
In summary, emerging strategies based on rt-fMRI nFb hold considerable promise, as they can be: 1) used to enhance plasticity in a number of systems (Berman et al., 2011; Bray et al., 2007; Caria et al., 2010; deCharms et al., 2004; Haller et al., 2010; Johnson et al., 2012; Johnston et al., 2010; Lee et al., 2012; Li et al., 2012; McCaig et al., 2011; Papageorgiou et al., 2013; Posse et al., 2003; Ruiz et al., 2013; Subramanian et al., 2011; Sulzer et al., 2013; Veit al., 2012; Yoo and Jolesz, 2002; Yoo et al., 2008; Zotev et al., 2011) including in the visual system of healthy participants (Scharnowski et al., 2012; Shibata et al., 2011); 2) superior to normal behavioral methods (deCharms et al., 2005); 3) tailored to induce perceptual learning (plasticity) in a highly specific fashion (Shibata et al., 2011); 4) used to identify pathways relevant to recovery via multivariate computational methods; and 5) used to induce long-lasting learning effects reported to persist outside the magnet, after the end of training (Ruiz et al., 2013; Sulzer et al., 2013). In the long-term, rtfMRI nFb methods promise to induce cortical plasticity that is efficient, robust and targeted for each patient. Lessons learned are likely to apply beyond the visual system to disorders of motor function, cognition, speech, language and emotion.
Many challenges need to be overcome in order to study the efficacy of rt-fMRI nFb methods in visual rehabilitation. Primarily, we need to develop effective rt-fMRI nFb paradigms in subjects with V1 lesions. The challenge is to implement rt-fMRI nFb training protocols to strengthen specific pathways that are hypothesized to play a role in visual performance. It is important to understand which visual pathways are more amenable to rehabilitation and what is the best rt-fMRI nFb paradigm to use. This requires elucidating which factors are "necessary and sufficient variables for learning" (Weiskopf, 2012). The answers to these questions will in general depend on the specifics of the visual function that requires rehabilitation, as well as on other factors such as the subject’s motivation.
Quantifying the degree of induced reorganization using population receptive field (pRF) methods is complementary to behavioral performance measures and represents a valuable neuroimaging biomarker for studying the mechanism of recovery induced by nFb rehabilitation methods. Information obtained will then, allow us to refine future rehabilitative approaches. Several different pathways may be able to contribute to recovery. For example, in the case of the visual motion rehabilitation example, the focus was on strengthening “bottom-up” pathways to enhance the response of the ipsilesional area hV5/MT+to the visual motion stimulus. One can hypothesize other strategies that focus instead on reorganizing higher areas, such as frontal eye fields (FEF), supplementary eye fields (SEF) areas involved in the generation of visual motion percepts downstream of hV5/MT+by “reading out” the weak activity that persists in extrastriate cortex following V1+lesions. Or, one can focus on strategies that reorganize attentional networks, such as middle frontal gyrus (mFG), intraparietal sulcus (IPS), superior parietal lobule (SPL), and anterior cingulate cortex (ACC) that enhance the weakened responses elicited in surviving areas following V1+lesions.
There are important technical challenges. One criticism is that rt-fMRI nFb approaches are impractical because they require large amounts of magnet time. Although this may have some truth in it, preliminary studies reveal that time spent inside the magnet is much less than what pure behavioral methods, require. Deciding how many rt-fMRI nFb sessions are needed to induce plasticity is a question that still needs to be answered. Preliminary evidence suggests that as few as 5-10 sessions can be sufficient to induce a strong perceptual learning effect in normal subjects (Shibata et al., 2011, and unpublished data of ours), but this will need to be validated specifically in patients with V1 lesions. Healthy participants and patients undergoing rt-fMRI nFb training sessions inside the magnet can learn to voluntarily elicit the desired pattern of activity. Subjects can then, gradually learn to implement this process outside the magnet, transferring their experience from rt-fMRI nFb sessions to ordinary behavioral sessions. We do not have adequate evidence yet, to determine under what conditions training accomplished inside the rt-fMRI environment can be transferred outside the magnet, but there is reason to be hopeful (Ruiz et al., 2013; Sulzer et al., 2013). The clinical applicability of rt-fMRI nFb training will become significantly broader if it becomes feasible to decouple the patient’s training sessions from the rt-fMRI nFb environment. Another important question is how long the effects of rt-fMRI nFb training are expected to last and whether this depends on the number of rt-fMRI nFb sessions used for training. Here too, there is reason for optimism given the results of Shibata et al. who managed to induce perceptual learning within 5 sessions of rtfMRI nFb (Shibata et al., 2011).
Many important challenges remain. However, it is now possible to lay the foundation of a systematic approach to visual rehabilitation using novel rt-fMRI nFb methods guided by pRF analysis of spared visual areas. This approach promises to teach us a lot about the visual system\'s capacity for plasticity after injury, and offers hope that effective, and robust visual rehabilitation methods, such as the novel rt-fMRI nFb approach will be used in the field of visual neuro-rehabilitation.
Neurorehabiliation of visual loss that occurs as a result of primary visual cortex injury is a difficult problem. To date, we have little understanding of the plasticity and reorganization mechanisms operating in the adult visual system following V1 injury. Consequently, no reliable method exists to effectively rehabilitate V1-lesioned patients who experience loss of visual perception in the contralateral hemifield (Horton, 2005a; Horton, 2005b; Pambakian and Kennard, 1997). Interestingly, recent results have shown that visually driven activity persists in extrastriate cortex following chronic area V1+lesions (Schmid, 2010; Schmid, 2009; Rodman, 1989; Rodman, 1990; Baseler, 1999), and that it is possible in some cases to rehabilitate visual motion perception (Das, 2010; Huxlin, 2009; Raninen et al., 2007; Henriksson et al., 2007; Sahraie et al., 2010). This confirms the existence of functional pathways that bypass the V1+lesion, providing direct input to spared extrastriate cortex. Such pathways are generally too weak to result in practical benefit. However, appropriate training strategies may be able to strengthen them sufficiently to induce recovery.
Real-time fMRI neuro-feedback strategies allow subjects to voluntarily modulate activity in certain brain areas or, neural pathways. These methods can be used to promote plasticity (Shibata et al., 2011). For example, we hypothesize that rt-fMRI nFb may be used to strengthen pathways that bypass the region of V1 injury to transmit visual motion information to area hV5/MT+. One paradigm that could, in theory, be used to accomplish this is the following: Subjects are trained by rt-fMRI nFb to voluntarily upregulate their hV5/MT+activity. Whenever hV5/MT+activity crosses a pre-set threshold, sub-threshold visual stimuli are presented. Repeated pairing of the “top-down” nFb-driven activation with the “bottom-up” stimulus-driven activation will engage Hebbian-like, association learning mechanisms, strengthening the response of hV5/MT+to visual motion stimuli. Visual motion stimuli that were previously sub-threshold may then, rise above threshold following training, improving performance.
Rehabilitating dense visual field scotomas requires adopting a systematic approach. Plasticity changes induced by new rehabilitation strategies should be mapped and their mechanism studied. We have presented evidence that pRF analysis is an excellent tool for this purpose, quantifying changes and providing rich data for formulating hypotheses about what regions of the visual field may be more amenable to rehabilitation and what pathways contribute to recovery.
We conclude that, even though rt-fMRI nFb methods are currently in their infancy, they hold considerable promise for inducing plasticity in targeted pathways promoting successful rehabilitation. Although here, we have focused on the visual system, principles discussed apply to the neuro-rehabilitation of several other domains of brain function, such as motor control, language, speech (Papageorgiou et al., 2009a; Papageorgiou et al., 2009b; Papageorgiou et al., 2013), emotion and cognition.
Part of the work that is presented here was supported by: (i) a McNair Foundation award, a McNair Medical Institute (MMI) award and a Fight for Sight Grant to T.D. Papageorgiou; and (ii) an NEI RO1 (EY019272), DoD (W81XWH-08-2-0146), and an HHMI Early Career Award to S. M. Smirnakis.
Our planet, the earth, is a wonderful place and has been suitable to live on its surface for thousands of years; it obliges us to preserve and nurture it. As investment volumes continue to grow in the globalized economy, environmental shadows are intersecting more and more on this planet. The concept of sustainable development, which generally means meeting the needs of the present without assaulting the rights of future generations, is addressed and implemented by many countries to manage the environment in an equal manner. However, there are some nations that achieve growth for their economies without regard to the adverse effects on the open environment. Nuclear and related applications became available everywhere to solve many problems of humanity. These applications, if not managed correctly, may lead to adverse effects of contaminating our environment by adding radioactive materials to already existing radioactivity of natural origin. So that our future generations and we will not be the victims of the various contaminations with hazards, we must preserve our environment. Many models arise when large companies offer their products without paying attention to long-term effects on human health or environmental stability. Some states allow the export of banned products or remainders inside the country because they are not safe in domestic use. In that regard, there are some talk about agreements to bury dangerous waste (e.g., radioactive waste in deserts). We recognize this by developing appropriate solutions and standards to perform the required tasks. These procedures often require the availability of accurate information and must be much easier to facilitate making decisions. The environmental radiation monitoring, for example, requires a variety of measurements, so it needs development of equipment capable of performing fast and accurate measurements on demand in addition to training of people that deals with radioactive materials.
In nature, there are important components that cast a shadow over the existing development of humankind such as uranium, which contributed greatly to the generation of electricity around the world. This element, in addition to other natural radionuclides, believed to be originated during the supernova explosion millions of years ago and/or alien to the earth where it was formed in the fusion of neutron stars, eventually makes its way into the earth crust. Natural radioactivity is a term used to describe the levels of naturally occurring radionuclides in different environmental compartments, originated either from cosmic (e.g., 14C and 3H) or terrestrial radiation. In addition to radioactive potassium (40K), the terrestrial radionuclides include those contained in four known decays series, namely, uranium, thorium, actinium, and neptunium, which start with 238U, 232Th, 235U, and 237Np, respectively. They comprise 18, 11, 16, and 12 radionuclides, respectively. The most abundant in significant levels in our environment are those from 238U and 232Th series. It is believed that in the history of the earth, the crust was enriched in uranium in the beginning; then, the rise of oxygen had oxidized uranium leading to the transfer of huge amount to the oceans and by some natural processes back to the mantle [1, 2]. The processes involved led to spatial distribution of uranium and its decay products. No matter how these theories and assumptions are exact, they give a picture of the approach we can only prove their validity by experiments.
Natural environmental radioactivity arises primarily not only from uranium, as mentioned above, but includes also other nuclides, such as thorium series and potassium, which occur at trace levels in all formations. These radionuclides are believed to be formed by the process of nucleosynthesis in stars and are characterized by half-lives that are comparable to the age of the earth.
It has been recognized that there are some places with large inhabitants that encompass high levels of background radiation in environmental compartments. Great interest given worldwide for the study of naturally occurring radionuclides has led to the performance of broad investigations in many countries [3, 4, 5, 6, 7, 8, 9, 10]. Investigators attempted to correlate the distributions of natural radionuclides with some settings such as geology, soil characteristics, etc. Such surveys can be useful for both the assessment of dose rates and the exploit of epidemiological studies, as well as to keep reference-data histories and to determine possible changes in the environmental radioactivity due to nuclear, industrial, or any other practices. What matters to us is to deal with the current reality of taking advantage of natural resources without disruption and tampering with our environment. The accurate determination of isotopes in environmental media presents a significant contest. Thanks to the technology that offered today many nuclear and related techniques for evaluating isotopes in the environment in efficient manner. Depending on the isotope, the analytical technique is selected (alpha, beta, or gamma emitter).
Gamma radiation emitted from naturally occurring radioisotopes, also called terrestrial background radiation, represents the main external source of irradiation of the human body. Natural environmental radioactivity and the associated external exposure due to gamma radiation depend primarily on the geological and geographical conditions, as reported at different levels in the soils of different regions around the world [11, 12, 13]. The specific levels of terrestrial environmental radiation are related to the geological composition of each lithologically separated area and to the content in thorium (Th), uranium (U), and potassium (K) of the rock from which the soils originate in each area.
This topic received some interests by many researchers in the field. Regardless of the general situation of safety and exposures, there are a number of conceptual issues, which remain open. That may include better revision of the protection concepts to cope with conditions of long-term chronic exposure resulting from natural sources. Developing real-world methodologies for the assessment and regulation of situations where there is a potential of exposure and addressing long-term safety aspects of radioactive waste of natural origin deem necessary. For decades, several studies have been conducted on the behavior of radionuclides in the environment and their transfer to humans through ecological and food chains. Most research focused on the contamination of the food chain release to the environment and development of mathematical models to describe environmental transport and assessment of general exposure. Continuing basic biological research is of particular importance to progress in protecting human, animal, and the environment from the hazards of radiation, so it should be strongly supported. However, it is also important to allow epidemiology, especially studies of low-dose populations, and to improve understanding of environmental phenomena as they relate to radiation protection, so as not to throw our hands at risk.
Many practices nowadays may increase the risk of surface contamination by radioactivity which needs control, such as oil exploration leading to NORMs, phosphate fertilizers, and illegal disposal of radioactive wastes in remote areas. Environmental monitoring can afford valuable means for understanding the distribution of natural worries of the ecological system. It is therefore importantly needed to increase our knowledge of the system by better means and offer adequate information to regulators, decision-makers, and the public. Authorities and investigators make baseline data such as risk maps to identify areas with low or high concentrations of certain radioactive and nonradioactive elements.
Environmental sample includes anything on the earth (soil, rocks, plants, water, sediments, air, etc.). It is important that samples taken from any place have to be representative to that place and care necessity be taken not to cross-contaminate samples. These precautions include also storing samples in a safe place to prevent conditions that could change the properties of the sample. Samples shall be kept sealed during long-term storing or transport. Before sampling a protocol, sampling strategy has to be set and all records of field sampling are written in a certain logbook. Simple logbook contains basic information of samples and sampling (date/time, coordinates, climate conditions, dose rate readings, etc.) It may contain additional information such as where and how samples are taken. As an example, soil samples can be taken using auger with depths up to 20 cm (after removing the top 2–3 cm). Locations of samples have to be pre-defined on approximate map, and from each location, a set of triplicate samples (as shown in Figure 1) could be taken. Samples are then prepared for measurements in standard procedures (drying, grinding, sieving, etc.). Details about sample preparation are described elsewhere such as the IAEA Technical Report Series No. 295 [14].
Part of soil sampling area where triplicate samples are found from each location in the area.
Among other types of radiation, gamma rays are the most penetrating radiation that are emitted from natural and manufactured sources. This property made gamma rays easy to detect and measure. Measurements can be made in two manners: total measurements that record gamma rays emitted at different energies from various sources. These modes are generally used to evaluate the gross levels of the gamma radiation in fields and to detect the presence of abnormalities in the environment. Laboratory analyses, on the other hand, measure both the intensity and energy of radiation, which enables identification of the source of the radiation.
Gamma radiation monitoring is applied in several fields of science including geological, geochemical, and mineral exploration, related epidemiological studies, and environmental science. It allows the interpretation of regional features over large areas. The monitoring is useful to estimate and assess the terrestrial radiation dose to the human population and to recognize regions of probable natural radiation hazard. Radioactive potassium and the uranium and thorium decay series are relatively abundant in the natural environment. They produce gamma rays of sufficient energies and intensities to be detected by a simple gamma ray spectrometry. Average crustal abundances of these elements quoted in the literature are in the range 2–2.5%, 2–3 ppm, and 8–12 ppm for potassium, uranium, and thorium, respectively [12].
Regional monitoring provides a base against which contamination from artificial sources be estimated. For example, regular measurements are conducted around nuclear facilities such as power plants, hospitals, and mining, industrial, and even radiowaste sites to provide a baseline against which any unintentional release of radioactive material can be detected. The gamma ray techniques have been fruitfully applied to mapping the fallout from nuclear accidents [15].
Gamma spectrometry is a system that is equipped with various types of detectors (HPGe, BEGe, LEGe, NaI, etc.), which characterized its specifications for radioactivity measurements. Germanium detectors are powerful systems used to measure the radioactivity in environmental samples. They have many advantages compared to other techniques as, for example, they distinguish many radionuclides in one single measurement without destruction or chemical modification of the sample. Simultaneous identification of many radionuclides with specific gamma energy and high-energy resolution of the germanium detectors allows measurements of complex combinations of gamma emitters. Figure 2 shows typical gamma spectrum taken for environmental sample.
A typical gamma measurement spectrum obtained using HPGe system.
It is important to know what counting statistics is used to optimize counting times in view of the influence of background. Depending on detector characteristics, the minimum detectable activity (MDA) at specific energy E is an important parameter to be calculated for field measurements; this may be given using Eq. (1):
where R(E), B(E), and ε(E) are resolution of the detector (keV), background (counts/keV), and total efficiency at the specific energy E, respectively.
Measurements are generally carried out using various radiation survey meters that can have different detection abilities. The choice of field measuring devices usually depends on how sensitive these devices are to different energies of different concentrations of radionuclides in the environment. Quality control has to be conducted by researcher and investigators to make sure these devices are reliable, accurate, and precise.
An example of the reliability of field, compared to the laboratory measurements, will be given here. In a recent survey, a portable dose rate meter device (Radiogem2000 with probe [16]) was set to measure dose rates, DF (μSv/h) at 1 meter above the ground while at the same time taking soil samples from the same locations for laboratory analyses of 238U, 232Th, and 40K in the collected samples. Ambient dose rates (DC) are calculated from the measurements using Eq. (2):
where AU, ATh, and AK are the activity concentrations (Bq/kg) of 238U, 232Th, and 40K, respectively [11].
As shown in Figure 3, a very good linear relationship between field and laboratory measurements (calculated absorbed dose) was clearly perceived for about 100 data points with moderate dose rates (DC ≈ 0.7DF, R2 = 0.97). Of course, this result could be validated with more measurements. The most important outcome of that investigation is that at normal situations where the absorbed dose is up to 300 nGy/h, the field measurements have good agreement with laboratory measurements. It is therefore safe to rely on the portable devices for routine monitoring. The implication of that is that many measurements could be performed in a field mission (as the measurement takes only few minutes long). If levels are high, then sampling and laboratory measurements force itself.
Relationship between field (ambient dose) and laboratory measurements (absorbed dose).
The level of background radiation can be used as a consideration in remedial actions if contamination occurs. If measured constantly, it gives info about the trends with time and impact of man-made activities. Hence, it is important to carry out systematic investigations on ambient gamma dose throughout to establish a baseline database for future control assessment where it acts as early warning system.
The early warning system is composed of detectors installed at different locations and connected to central server over available communication system. Any type of detector or survey meters could be installed and used to fulfill the requirements. The advantage of this system is that the authority can create a national radiation map, showing environmental radiation levels (gross count of the radioactivity) throughout certain area updated in real time. It allows the citizen (or anyone) to see what radiation levels are within that specific area at any instance.
In a simple form, GIS is defined as a set of computer hardware and software designed to acquire, store, manipulate, display, and report geographically referenced information for a particular purpose in space. The space is presented by geographic coordinate systems. Therefore, GIS defines the relationships between various database information and geographical locations within the location system. Together with geostatistical tools, GIS is useful to interpolate scatter data by converting measured points into continuous surfaces. There are several methods available, the choice of which depends on the data itself. Among these methods it is worth to mention two methods, namely, inverse distance weighting (IDW) and kriging.
In this interpolator, the data points are weighted during process so that the impact of points relative to each other is a function of inverse distance. Weighting is calculated to data via the use of a weighting power and the radius object. Larger power means that the adjacent points have the larger influence. Searching radius could be fixed or variable (with typical values of power around two). This flexibility allows controlling the interpolation, which may depend on the number of samples and how they are spatially distributed. One of the drawbacks using this method is that maxima and minima are always among data points since the inverse distance weighted interpolation is a smoothing technique by definition. On the other hand, it is a powerful interpolation technique which leads to reasonable predictions with no problem with results exceeding the range of meaningful values. Simple or advance GIS software could be employed to interpolate and validate the results. Validations are normally expressed as root mean squares error in the correlation between the predicted and actual values.
This is an advance method that makes a surface from scattered points. It is sometimes called weighted moving averaging method because it is derived from regionalized variable theory. It assumes that the variation of a parameter is statistically correlated all over the area. Kriging derives weights from semivariogram functions that depict the degree of spatial correlation between data points as a function of distance and directions between points. The semivariogram adjusts the way kriging weights are allocated to each data point during interpolation. The semivariogram γ(h) function is given by Eq. (3):
where xi + h and xi are sampling position separated by a vector h, Z(xi) is a random variable at fixed position xi, and N(h) is the number of data pairs separated by a vector h. Ordinary kriging is a type of kriging that uses the sampled main variable to estimate values at unsampled locations. Cokriging, on the other hand, allows secondary variables to be incorporated in the model assuming that both primary and secondary variables are correlated [17, 18].
Figure 4 shows a typical example to predict unsampled places from randomly scattered data points of measured ambient dose (figure to the left). Both interpolator methods IDW and kriging were used to create continuous surface of this parameter as shown in middle and right figures, respectively. These maps (easy to visualize if there are trends) could be used as a guide for any future studies; it can be improved and updated.
Converting scattered measured ambient dose to continuous surface using inverse distance weighting (IDW) and kriging geostatistical methods.
Radon is a naturally occurring radionuclide that is found in the environment as a member of the natural decay series of uranium. The 222Rn, including its progeny, is one of the most significant natural sources from a viewpoint of human radiation exposure to the population. Exposure to high concentrations of radon has been correlated to lung cancers, although the effect of low radiation doses is not well defined. The importance of environmental 222Rn data were pointed out in the UNSCEAR reports [11, 12, 13]. As an alpha emitter, the indoor 222Rn can be measured using detectors that estimate alpha particles or via its decay products that emit alpha, beta, or gamma rays. Many techniques have been developed to measure radon in the environment. Charcoal canister technique and solid-state nuclear track detector (SSNTD) are common methods in use to evaluate radon in passive mode. The radiation doses due to radon inhalation are calculated according to the ICRP assumption of equilibrium factor (the quotient of the equilibrium equivalent concentration to the 222Rn concentration) of 0.4 and assuming 5700 h spent indoors annually.
In addition to absorbed dose calculated from Eq. (2), the following additional hazard index parameters are, generally, evaluated using field or laboratory measurements to assess the risk of exposure due to natural radioactivity.
The annual effective dose is a quantity that is introduced in the field of radiation protection for dose limitation, defined as organ or tissue weighted sum of equivalent dose in 1 year (averaged for the whole body) considering type of radiation. It represents the stochastic risk (probability of getting cancer [estimated as 5 × 10−2 per sievert] and genetic defects). For people living in a certain area, the annual effective dose could be calculated using Eq. (4) [12]:
where 0.7 is the absorbed/ambient dose conversion factor and 0.2 is the outdoor occupancy.
Example 1: About 100 soil samples were collected from an area, measured by gamma spectrometry which showed the following average results: 80 ± 7, 91 ± 21, and 573 ± 89 (Bq/kg) for 238U, 232Th, and 40K, respectively. Estimate the annual effective dose for people living in this area spending 60% of their time indoor.
Solution: First we calculate the absorbed dose using Eq. (2):
D = 0.461x80 + 0.623x91 + 0.0414x573 = 117 nGy/h
This can then be converted into annual effective dose using Eq. (4):
E ≈ 0.3 mSv/y
This index is calculated using Eq. (5) [19]:
Example 2: In example 1 above, calculate the external hazard index.
Solution:
less than unity (the recommended limit for external exposure).
Cancer risk can be estimated using Eq. (6) [12, 20]:
where DL is the life expectancy (in years) and RF is the cancer risk factor for each sievert [21], which is of order 0.05 for the public.
Example 3: In example 1 above, estimate cancer risk for a person living in that area.
Solution:
Assuming the average life expectancy of people in this area is 65 years, then using Eq. (6) the lifetime cancer risk is calculated as
ELCR = 0.3 × 10−3 × 65 × 5 × 10−2 = 9.8 × 10−4 ≈ 10−3
The chapter describes the importance of radioactivity monitoring to preserve our environment. It sheds the light on methods designated for the measurement of natural radionuclides in the environment and assessment of radiation exposure to human in different situations. In addition to measurements and surveys, the chapter presents a summary of some methods of radiation dose calculations that the individual may be exposed to. As is difficult to measure everywhere, the chapter also presents methods for estimating and predicting the spatial distribution of radiological quantities. The use of a geographical information system, GIS, and geostatistical methods to create maps facilitates the evaluation and assessment of radioactivity in the environment. Environmental measurements may be costly and time-consuming practices; hence, thoughts to reduce time and efforts are given in this chapter where at normal levels portable simple equipment proved useful.
Part of the data presented in this chapter is prepared with the support of the “Environmental group of Sudan Atomic Energy Commission.” The author would like to thank all members of this group for their collaboration during field missions, laboratory analyses, and reporting.
The author discloses no potential conflicts of interest.
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\\n"}]'},components:[{type:"htmlEditorComponent",content:'Copyright is the term used to describe the rights related to the publication and distribution of original Works. Most importantly from a publisher's perspective, copyright governs how Authors, publishers and the general public can use, publish, and distribute publications.
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