linking mind, brain, and education to clinical practice: a proposal for transdisciplinary...

MIND, BRAIN, AND EDUCATION

Linking Mind, Brain, andEducation to Clinical Practice:A Proposal for TransdisciplinaryCollaborationKatie Ronstadt1 and Paul B. Yellin2

ABSTRACT—It has been suggested that the field of Mind,Brain, and Education (MBE) requires a stable infrastructurefor translating research into practice. Hinton and Fischer(2008) point to the academic medical center as a model forsimilar translational work and suggest a similar approach forlinking scientists to research schools. We propose expandingtheir model to include a formal role for clinicians. Includingclinicians who work with children with learning problemsbrings an important perspective to the translational work.For example, the integration of the concept of ‘‘differentialdiagnosis,’’ a core precept in clinical medicine, would bringneeded diagnostic specificity to the field of MBE. We describea virtual infrastructure for collaboration, or ‘‘collaboratory,’’consisting of research scientists, educators, and clinicians,linked to an academic institution. We anticipate that MBEgraduates can play a critical role in the collaboratory model.With additional training, they can become ‘‘neuroeducators’’capable of moving comfortably among the disciplines,building linkages, fostering communication, and facilitatingcollaboration.

Increasingly, neuroscientists are identifying the neural pro-cesses associated with brain development, the acquisition ofacademic skills, and disorders of learning. Integrating thisemerging knowledge into education has been difficult becauseit requires collaboration across disciplines. The field of Mind,Brain, and Education (MBE) has emerged as a transdisciplinary

1Lexia Learning Systems, Inc.2Associate Professor of Pediatrics, New York University School ofMedicine

Address correspondence to Katie Ronstadt, 3 Seventh Street, Cambridge,MA 02141; e-mail: [email protected]

collaboration among biologists, cognitive scientists, develop-mental scientists, and educators (della Chiesa, Christoph, &Hinton, 2009). This collaboration has the potential for funda-mentally transforming education by facilitating the integrationof research findings with curriculum development and edu-cational policy. However, realizing this potential will requirethe creation of a stable infrastructure to support the necessarylinkages, collaborations, and data sharing (Hinton & Fisher,2008; Fisher & Daniel, 2009). Hinton and Fischer identify theacademic medical center as an example of a stable model fortranslating basic research into clinical practice. In that regard,teaching hospitals and medical schools typically collaboratein research, practice, and education.

Extending that analogy, they propose formal link-ages between school-based educators and university-basedresearchers as the mechanism for achieving the needed collab-oration. Indeed, despite systemic problems in health care deliv-ery, academic medical centers do provide a fertile environmentfor translating research into clinical practice. In addition, clini-cal experience often helps to define, inform, and focus researchquestions and approaches. Therefore, applying elements ofthis model to transdisciplinary collaboration in MBE buildsupon an already successful model for such translational work.

A FORMAL ROLE FOR CLINICIANS

We believe that the collaborative framework should includea formal role for clinicians who provide care to individualchildren. Psychologists, pediatricians, and others engaged inthe diagnostic assessment of students with suspected learningdisorders already function in an ill-defined nexus betweenfamilies, schools, and research. Each clinical discipline tendsto view learning problems through its own lens. The per-spective of clinicians making diagnoses may be different fromthe view of educators who are responsible for acting upon

© 2010 the AuthorsVolume 4—Number 3 Journal Compilation © 2010 International Mind, Brain, and Education Society and Blackwell Publishing, Inc. 95

Linking MBE to Clinical Practice

these diagnostic findings. Additionally, clinical practice itselfis often divorced from emerging research. Diagnosis has tradi-tionally consisted of the administration of a series of specifictest batteries to comply with regulatory requirements to deter-mine eligibility for services. Diagnoses often resemble restate-ments of presenting complaints (e.g., Disorder of WrittenExpression) rather than reflecting emerging knowledge aboutbrain development and the acquisition of academic skills.

Traditional assessments, including IQ and achievementtesting, remain the mainstay of diagnosis and treatment recom-mendations despite data demonstrating their lack of diagnosticspecificity or sensitivity (Francis et al., 2005). In addition, theindividual disciplines often function in isolation, and childrenare frequently saddled with an array of labels and recom-mendations. In stark contrast to medical decision making,specific interventions and recommendations are rarely wellstudied. Assessing treatment outcomes is particularly chal-lenging because treatments may be prescribed by cliniciansand provided by educators, with no formal linkages betweenthe two to assess diagnostic accuracy, treatment fidelity, andoutcome.

In illustrating the benefit of a reciprocal relationshipbetween researchers and educators, Hinton and Fischer (2008)describe recent progress in understanding dyslexia. Specifi-cally, educators’ observations about variation in response tospecific interventions helped researchers reach a more nuancedunderstanding of mechanisms contributing to dyslexia (Hin-ton & Fisher, 2008). Thus, including clinicians in this earlycollaboration would provide an opportunity to ensure thatdiagnostic practices evolve in concert with emerging knowl-edge in neuroscience and educational practice. Ongoingcommunication will provide an opportunity to researchers andeducators to include clinical observations in their thinking.

DIFFERENTIAL DIAGNOSIS IN THE ANTIBIOTIC ERA

The current state of diagnosis and treatment of learning prob-lems can be compared with medicine just prior to the antibioticera. Prior to the discovery of antibiotics and other specific treat-ment modalities, medical practice was often limited to nonspe-cific, symptomatic treatments and supportive care. Becausetreatment choices were limited and nonspecific, diagnosticspecificity was neither possible nor critical. However, withthe development of specific and sophisticated treatments camethe recognition that patients with similar symptoms oftenresponded differently to identical treatment regimens becausetheir symptoms had different underlying causes. Selecting theappropriate treatment required increasingly sensitive and spe-cific diagnostic methods. The notion of differential diagnosisemerged as an approach for accurately diagnosing the causeof a problem by systematically considering all possible causes.Indeed, the notion of differential diagnosis is a core precept

in the practice of medicine, but has been largely absent in thediagnosis and treatment of learning problems. For example,labels like ‘‘disorder of written expression’’ and even dyslexia,while considered in diagnoses, are in fact little more thanrestatements of presenting symptoms. Consider how any rea-sonable person would feel if their physician diagnosed themwith a ‘‘cough’’ without identifying the underlying cause. Forexample, it has become increasingly clear that dyslexia is not asingle disorder, but rather a complex symptom with a numberof possible causes (Fischer, 2009; Heim et al., 2008; Schneps,Rose, & Fischer, 2007; Wolf & Bowers, 1999). As educatorsand neuroscientists increasingly examine the nature of vari-ation in response to specific educational interventions, it islikely that other current diagnostic labels will be found to con-sist of a number of possible underlying causes (i.e., differentialdiagnoses). Further, it is likely that response to specific inter-ventions will vary, based, at least in part, on the nature of theunderlying cause or etiology. As is the case in medicine, diag-nostic accuracy will increasingly emerge as a priority. Educa-tional diagnosis will need to move beyond traditional batteriesand labels to a process equivalent to differential diagnosis inmedicine.

A STABLE INFRASTRUCTURE

In the field of medicine, teaching hospitals and academic med-ical centers contain all of the parties necessary for linkingresearch, diagnosis, treatment, and data collection. However,in contrast, the educational system is currently fragmented.Ensuring that development of specific treatments, diagnosticcapabilities, treatment implementation, and data collectionrequires a collaboration that includes not only clinicians inaddition to researchers and educators but also individualsand organizations that are developing innovative treatments,approaches, and technology. At present, there is no physicalstructure to bring these disciplines together. Collaborationwill require the creation of a virtual infrastructure or ‘‘col-laboratory.’’ The term collaboratory has emerged from thefield of computer science and evolved to define the variousactions involved in research. For example, a collaboratorycan include ‘‘interacting with colleagues, accessing instru-mentation, sharing data and computational resources, [and]accessing information in digital libraries’’ (Wulf, 1993, p. 854).Such a virtual infrastructure can facilitate the blending of‘‘technologies into an information infrastructure’’ enabling‘‘applications beyond the traditional analysis’’ (Wulf, 1993,p. 854). Cogburn adds that a collaboratory can consist of morethan a network of technologies; it can also include ‘‘socialprocesses; collaboration techniques; formal and informal com-munication; and agreement on norms, principles, values, andrules’’ (Cogburn, 2003, p. 80). As such, the collaboratory frame-work could advance the MBE field.

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In our view, each collaboratory would include the followingprofessionals:

1. University-based research scientists2. Educators at research schools actively investigating

educational practice3. University-affiliated clinicians4. Neuroeducators and others developing innovative educa-

tional materials, interventions, and treatments

However, at present, collaboration is difficult becauseresearch scientists and educators do not share a commonvocabulary, conceptual framework, or set of priorities (Fis-cher, Goswami, & Geake, 2010; Coch, Michlovitz, Ansari,& Baird, 2009). Having broad exposure to all of these dis-ciplines as well as rigorous training in neuroscience andresearch, graduates of MBE programs can play a critical rolein overcoming these barriers. These neuroeducators would beexpected to have sufficient familiarity with the vocabulary,conceptual framework, and culture of each discipline as wellas the skills needed to help create a climate of collaboration,communication, and trust (Fisher et al., 2010; Gardner, 2008).

It has been observed that collaboration is most successfulwhen all of the participants feel that there is a mutualexchange of knowledge (della Chiesa et al., 2009). Therefore,it would be critical for neuroeducators to facilitate a ‘‘two-waydialogue in which practitioners and researchers work togetherto formulate research questions and methods so that they canbe connected’’ (Fischer et al., 2010, p. 68).

However, in our view, there is danger that the role ofthe neuroeducator in the schools could become marginalizedunless they are also viewed as integral members of the localteam. Therefore, within the school, they should provideongoing support to teachers, diagnosticians, and academicsupport teams. For example, they could mentor the educatorsthrough the process of considering ‘‘differential diagnoses’’for individual students’ struggles. They could also facilitatecollaboration among parents, school personnel, and individualclinicians to develop a shared understanding and plan forindividual students.

Finally, they would be expected to ensure that theseindividual experiences are integrated into the evolving bodyof knowledge to further inform research and practice.With clinicians, educators, and scientists participatingin these conversations, there would be opportunities toevaluate specific methods for diagnosing and treating learningproblems. In addition, they would be in a position to ensurethat individual students are assessed with a broader viewof their profiles of strengths as well as weaknesses, as it islikely that both will be relevant when considering specificeducational approaches (Immordino-Yang, 2008). We hopethat the following case presentation will describe how such aprofessional can support transdisciplinary collaboration.

CASE PRESENTATION

Jessica is a 7-year-old second-grader who has been strugglingwith decoding and reading comprehension, despite hervocabulary and listening comprehension being well aboveage expectations. Her mother reports that it takes her 3 hrto do homework that should require no more than 1 hr.Jessica complains of headaches and stomach aches on Sundayevenings and is having meltdowns each evening. Her classroomteacher suggested off the record that her mother contact theprincipal about Jessica’s difficulties. In response, the schoolpsychologist administered the Wechsler Intelligence Scale forChildren-Fourth Edition and Woodcock-Johnson III Tests ofAchievement. Based on this testing, it was determined thatthere was not sufficient discrepancy between her cognitive andachievement testing for her to qualify for services under theIndividual with Disabilities Education Act (IDEA). In short,Jessica’s mother was told that ‘‘she is doing too well’’ to needhelp. Because of ongoing concerns, Jessica’s parents soughtan independent assessment. Her medical, psychological, andacademic history were reviewed, as were results of previoustesting, work samples, and school reports. The educationalassessment revealed that Jessica made numerous errors whendecoding nonsense words. Although some of her errorssuggested confusion about sound–symbol associations, shewas also observed to transpose phonemes. Assessment of heracademic skills raised concerns that Jessica’s reading problemsmight not simply reflect weak phonemic awareness but alsorelative weakness in paired associate learning and sequencing.Error analysis of her math work revealed similar concerns.Specifically, Jessica had great difficulty continuing numberpatterns, sequencing numbers, and recalling math procedures.In addition, her math fact recall was not automatic. However,Jessica also displayed significant strengths. For example,despite her struggles with math facts and math procedures,she devised intricate solutions to complex problems. Further,her parents shared an impressive portfolio of paintings anddrawings. They also described her ability to independentlycare for her pet dogs. And as noted above, her vocabulary andlistening comprehension skills were advanced for her age.

Indeed, dynamic assessment of her cognitive abilities,including selected subtests of various standard batteries aswell as clinical observations, was also consistent with weakphonological awareness, sequencing, and paired associatelearning. However, other parts of long-term memory, activeworking memory, vocabulary, higher-order thinking includ-ing verbal conceptualization, and her motor skills appearedto be appropriately developed and, in some cases, advanced.The clinical team’s impressions of Jessica’s specific profile ofstrengths and weaknesses were shared with Jessica and herparents. Jessica visibly brightened after hearing her numerousstrengths and learning that her difficulties were limited toa number of specific areas of weakness. Strategies included

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recommendations to further develop her areas of strength, aswell as ways to use her strengths to bypass her areas of weak-ness and to focus on strengthening her areas of weakness.In addition, a follow-up visit was planned to monitor Jes-sica’s progress as well as her symptoms of emotional distressassociated with her academic difficulties.

Based on these additional findings, the school agreed toreconsider her eligibility for services and ultimately agreed thatshe did indeed qualify for services under IDEA. They developedan Individualized Educational Program that Jessica’s parentsagreed was an appropriate plan. Her parents also decidedto hire a private tutor to work on additional strategies afterschool. Over the course of the next 6 months, Jessica seemed toregain her enthusiasm for school and was making measurableprogress in all subjects.

THE STARK REALITY

Unfortunately, not every family is as fortunate as Jessica’swas. Assuming parents choose to share an independentclinician’s findings and recommendations with their school,what happens next will vary greatly, depending on thespecific school or school district. Quite commonly, theschool-based support team, accustomed to considering onlyIQ–achievement discrepancies or specific lags in grade level,will persist in their view that there is not ‘‘sufficientdiscrepancy’’ to justify the need for any academic support.Parents receiving this response from their school frequentlyexperience increasing confusion, frustration, and anger. Theymight consider retaining an attorney, knowing that this couldbe costly and that the ultimate outcome will be uncertain. Ofgreater concern, they know that going down that path willrisk undermining their ongoing relationship with the school,including those responsible for caring for their child on a dailybasis.

In short, the current system leads to serious uncouplingbetween diagnosis, treatment, and outcomes assessment,placing children and their families in the middle. Diagnosesand recommendations are often made by clinicians whoseinvolvement with a child frequently ends once they havecompleted their assessment. In fact, clinicians frequently referto themselves as ‘‘testers’’ as if their role is to generate data that,in large measure, will be interpreted by others charged withmaking educational decisions. As noted above, many schoolsand other organizations continue to play the numbers game,relying on IQ–achievement discrepancy or other arbitrarydefinitions of learning disabilities despite the fact that theseapproaches are no longer consistent with recent evidence ofthe brain development, learning pathways, and the limitationsof psychometric testing (Delis et al., 2007; Francis et al.,2005; Hall & Webster, 2008). Although frequently providingvaluable information, these traditional assessment batteriesare rarely sufficient for making decisions about appropriate

treatment and other interventions (Aaron, Joshi, Gooden, &Bentum, 2008; Heim et al., 2008).

In fact, had Jessica been seen by a different clinical team, itis very possible that her diagnosis would have been different ormight have focused on a different part of her complex picture.Students with academic difficulties commonly accumulate anarray of labels, including dyslexia, central auditory processingdisorder, convergence insufficiency, sensory integrationdisorder, and attention deficit disorder. These disorders arefrequently diagnosed by clinicians with a narrow perspectivewhose expertise maybe limited to a single organ system.Parents and teachers are left to make sense of diagnostic labelsand treatment recommendations that range from the mostgeneric (e.g., extended time for examinations and preferentialseating toward the front of the classroom) to the most specific(e.g., a sensory diet or vision therapy).

After a student is assessed, parents negotiate with theschool regarding the implementation of the clinician’s recom-mendations. Even when clinicians participate in this process,their involvement is typically limited to an isolated occurrencewhere various recommendations are presented to the school-based team ultimately responsible for developing, implement-ing, and monitoring the plan. Although these interactions aregenerally polite and collegial, there is often an adversarial ele-ment not far below the surface. Specifically, because of limitedresources, the school-based team must consider each student’sneeds while under pressure to regulate the allocation of lim-ited resources. Although fundamentally only responsible forthe child’s best interest, the independent clinician must alsocontend with parental wishes and expectations. After theseinitial conversations, ongoing communications are typicallysporadic and logistically challenging. Yet such collaborationwould be of great value to all parties.

In medicine, it is generally understood that diagnosis is adynamic process, where initial impressions are often refinedand revised based on the opportunity to observe response totreatment and other developments. However, because test-ing for academic skills and cognitive functions are frequentlyviewed as objective and definitive, follow-up is rarely per-ceived as important. Yet the issues involved in academicperformance are at least as complex and dynamic as otherclinical issues. Not only would ongoing communication helprefine diagnostic specificity and sensitivity but it would alsoprovide an opportunity to monitor and modify treatment(Coch et al., 2009). Together, educators and clinicians couldstudy newer methodologies for assessing individual students(Dawson, 2004). In addition, it is widely recognized that clin-ical quality is improved when clinicians have access to dataabout the accuracy of their diagnoses and the outcomes oftheir treatment recommendations.

In our view, there would be value in the presence of aneuroeducator to drive an open, collaborative process for con-sidering all findings, considering all the diagnostic possibilities



(i.e., differential diagnosis), and developing a treatment planthat includes ongoing progress monitoring. Additionally, theneuroeducator could become an important resource in theimplementation of Response to Intervention within the school.The neuroeducator would be expected to become a valuedmember of the local team while maintaining linkages to anacademic MBE program. In addition to sharing informationacross the collaboratory, the neuroeducator would be expectedto identify opportunities for investigation and facilitate sharedresearch projects. With ongoing collaboration, there wouldbe opportunities for diagnostic practices and treatment deci-sions to evolve in concert with emerging knowledge aboutbrain development and educational practice (Kuriloff, Richert,Stoudt, & Ravitch, 2009).

THE PROFESSIONALIZATION OF THENEUROEDUCATOR

If neuroeducators are to become successful leaders withincollaboratories, it will be critical to ensure that they havesufficient expertise, professional standing, and institutionalsupport to function as true peers within the collaboratory.Currently, master’s-level programs in MBE already focus onmany of the requisite skills. For example, they typically provideinstruction and experience synthesizing information from dis-parate sources, respecting discipline-specific approaches, andcommunicating across disciplines (Hinton & Fisher, 2008;Stein & Fischer, 2008). Prior to assuming the role that wedescribe, MBE graduates will likely require additional trainingas well as ongoing mentoring and support to have the exper-tise and credibility to function as peers and colleagues withthe other members of the collaboratory. Additionally and pos-sibly most importantly, neuroeducators would be expectedto have expertise in establishing a climate of trust amongthe participants of the collaboratory, including the ability toempower others to contribute (Leonard & Leonard, 2001). Forexample, educators may initially feel intimidated by researchscientists or skeptical about the entire enterprise. Therefore,the neuroeducator will need to ensure that educators havethe opportunity to contribute to the research agenda of thecollaboratory (Coch et al., 2009; Kuriloff et al., 2009).

The neuroeducators will need sufficient credibility toserve as a conduit of emerging knowledge to educators andclinicians. After all, advances in neuroscience are proceedingat such a rapid pace that clinicians and educators havedifficulty keeping up. Rather than having access to informationfrom reliable sources, they are frequently bombarded byorganizations and individuals marketing the latest ‘‘brain-based’’ products or programs. On the other hand, they arealso limited by existing practice and the narrow perspectiveof their respective disciplines and therefore may be unawareof products and processes that they ought to include in their

practices. Hence, they would benefit from regular access tobasic researchers and their findings, and they could facilitateconnecting findings to educational practice.

One such model of professional learning that has beenadopted by a number of schools is called ‘‘instructionalrounds.’’ Teaching through rounds is a long-standing traditionin medical education. Typically a group of interns, residents,and medical students accompanies a member of the medicalfaculty through a hospital ward to share information abouteach patient and discusses possible diagnoses and treatments.Building on this model, groups of educators, ‘‘instructionalnetworks,’’ systematically move through a school. Unliketraditional school walk-throughs, instructional rounds arebased on a process of nonjudgmental observation, description,and analysis of learning and teaching (City, Elmore, Fiarman,& Teitel, 2009; Teitel, 2009). Neuroeducators could facilitatethe development of a similar process among participants ofindividual collaboratories.

THE ARCHIVE OF EXPERIENCE

Grigorenko (2007) and Goswami (2006) both note that collab-orative models must incorporate technology to help improvecollaboration and communication so that outcomes, insights,and processes can be shared among educators. With this inmind, neuroeducators would be responsible for developing anonline archive of experience which will serve as a collectiontool to organize practical findings.

We anticipate beginning with a single pilot collaboratoryclosely linked to an established MBE program to ensure thatthe experience is closely monitored and shared. If successful,the model could be replicated elsewhere, ultimately leading tonetworks of collaboratories managed by university-affiliatedneuroeducators. While initially supporting the work of onecollaboratory, the archive of experience could be expandedto support a growing network of collaboratories. The ChildLanguage Data Exchange System is an example of such ashared database that has contributed greatly to the study ofearly language development (MacWhinney & Snow, 1990).

CONCLUSION: NEUROEDUCATORS ANDCOLLABORATORIES

The field of MBE has the potential for fundamentally trans-forming education by facilitating the integration of researchfindings into curriculum development and educational policy.Of course this potential will require the creation of a stableinfrastructure to support such ongoing collaboration. The aca-demic medical center is one model that has been proposed forthe needed infrastructure. It has been suggested that such aninfrastructure could be developed by formalizing collabora-tions between research scientists and research schools. We



believe that clinicians should be more formally included inthis collaboration because clinicians and those engaged inthe diagnostic assessment of students with suspected learn-ing disorders already function in an ill-defined nexus betweenfamilies, schools, and research. Among the benefits of includingclinicians are the potential for diagnostic practices to evolvein concert with emerging knowledge in neuroscience and edu-cational practice. Including a clinical perspective would alsoenrich the exchange among the participants. For example,looking more broadly at the underlying causes of learningproblems (i.e., differential diagnosis) would likely bring morespecificity to diagnosis and treatment.

We envision graduates of MBE programs emerging asneuroeducators; hybrid professionals capable of providingthe necessary linkages among the various participants inthe currently fragmented system. Within the school, theneuroeducator could be a resource to classroom teachersand school-based support teams by sharing information aboutbest practices in assessment and intervention. (S)he couldfacilitate the exchange of information between schools andindependent clinicians, as well as facilitate a collaborativeprocess to review findings and recommendations and developa cohesive plan, including specific interventions as well asoutcome measures. The neuroeducator would also facilitatecommunications between the basic neuroscientists and othermembers of the collaboratory to ensure that research isinformed by experience in the school and clinic and that clinicaland educational practice are informed by emerging knowledgein neuroscience. We believe that, through this processof collaboration and establishing trusting and reciprocalrelationships, the neuroeducator could then coordinate sharedresearch projects involving neuroscientists, clinicians, andeducators. If the initial pilot is successful, the collaboratorymodel would be one approach to building a collaborativeinfrastructure for advancing the MBE movement.

In stark contrast to medical decision making, specificinterventions and recommendations are rarely well studied.Assessing treatment outcomes is particularly challengingbecause treatments may be prescribed by clinicians andprovided by educators, with no formal linkages between thetwo to assess diagnostic accuracy, treatment fidelity, andoutcome. Because testing is frequently viewed as objectiveand definitive, follow-up is rarely perceived as important. Yetthe issues involved in academic performance are at least ascomplex and dynamic as other clinical issues.

In medicine, it is generally understood that diagnosis is adynamic process, where initial impressions are often refinedand revised based on the opportunity to observe responseto treatment and other developments. In our view, therewould be value in the presence of an individual whoserole is to drive an open, collaborative process for consid-ering all findings, a forum for advancing and consideringthe diagnostic possibilities (i.e., differential diagnoses), and

developing a treatment plan, including ongoing progressmonitoring.

Not only would ongoing communication help refine diag-nostic specificity and sensitivity but also it would provide anopportunity to monitor and modify treatment. In addition, it iswidely recognized that clinical quality is improved when clin-icians have access to data about the accuracy of their diagnosesand the outcomes of their treatment recommendations. In ourview, a neuroeducator would help address these concerns bymaintaining ongoing communication and data exchange.

In summary, we envision the neuroeducator acting in closeconnection with a university-based MBE program and takinga leadership role in piloting an initial collaboratory (i.e., col-laboration including scientists, clinicians, and educators). Ifthe pilot is successful, and if replicable, a network of collab-oratories might provide the kind of infrastructure needed foradvancing the MBE movement. The execution of a pilot collab-oratory could serve as the first step in the development of thekind of stable infrastructure described by Hinton and Fischer(2008).

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