is a research professor and Director of Chambers-Grundy Center for Transformative Neuroscience at the University of Nevada, Las Vegas.

Jeffrey L. Cummings, MD, ScD

The world is in the midst of an unfolding cognition crisis, with devastating personal, societal, and economic implications. The expanding elderly population requires better cognitive care; we are also coming to understand the importance of cognitive interventions and support in early childhood. Furthermore, the COVID-19 pandemic has brought global attention to cognitive issues, with over 50% of individuals recovering from the infection experiencing fatigue and brain fog. Initial studies indicate lasting deficits in executive function, impaired cognitive control, and reduction in global cognition leading to disability or reduced function.

 There are fears that COVID-induced deficits may last for years beyond the infection.

—such as attention, memory, perception, language, and reasoning

—are declining across the whole population. Beyond the effects of COVID-19, there is an alarming increase in the number of individuals around the world with serious cognitive impairments. These impairments co-occur with disorders including depression, anxiety, schizophrenia, autism, posttraumatic stress disorder, dyslexia, obsessive-compulsive disorder, bipolar disorder, attention-deficit/hyperactivity disorder (ADHD), addiction, dementias, and more.

 The severity, type, duration, and course of cognitive dysfunction differ between these disorders. The aging world population will heighten the cognition crisis. By 2060, the 

number of individuals aged 65 and older is projected to double

 is often only assessed when there is a specific, subjective complaint from patients, family members, or caregivers. In this context, there are many factors which suboptimize the value. For example, there are lengthy waiting lists to see neuropsychologists or cognitive neurologists, and various modalities used to assess cognitive dysfunction in later life are inaccessible to most (eg, positron emission tomography and advanced magnetic resonance imaging scans). Furthermore, there is no consistent clinical assessment algorithm for how to use cognitive assessment tools (eg, when to use pencil and paper tests, digital, blood-based, or neuroimaging). When there is no specific, subjective cognitive complaint, cognition is not assessed. This means more subtle and slow-onset forms of cognitive dysfunction may be missed. This can delay treatment and mean more progressive brain changes. If cognition is assessed, it is often not addressed, supported, or followed up in the long-term. Further, in many developing countries, cognition is rarely—if ever—screened, resulting in complications such as high rates of undiagnosed dementia.

 across the lifespan, it is critical that cognition is assessed and monitored across disorders and throughout life. Addressing and building cognition is especially crucial during early childhood, when cognitive difficulties can be caught before they have too much detrimental impact on a child’s developmental trajectory.

Examples of Cognitive Decline in Psychiatric Conditions

Consider depression: More than 264 million individuals around the world suffer from depression, making it the 

 and a major contributor to the overall global burden of disease.

 Depression is commonly associated with a lowering of a patient’s mood and energy for long periods of time. Depression also impairs cognition, including affecting attention, memory, information processing, decision-making skills, cognitive flexibility, and executive functioning.

 Indeed, 85 to 94% of individuals with acute depression experience significant cognitive impairments.

 Even when depression has remitted, around 40 to 45% of patients report dysfunction in one cognitive domain.

 Cognitive impairments are not addressed by first-line 

is now proposed as a novel treatment target for depression.

 Cognitive remediation therapy has provided encouraging results for the management of cognitive deficits in major depressive disorder (MDD).

 The incorporation of biobehavioral strategies (eg, exercise) and multimodal treatment approaches (eg, cognitive training, antidepressant therapy, and neuromodulation) is likely to generate therapeutic benefit.

Another example is cancer. It is estimated that at the end of 2020 there were over 70 million cancer survivors worldwide.

 Cognitive impairments—including deficits in visual working memory, sustained attention, new learning, and more—are commonly observed in patients with cancer and those in remission.

 Though cancer- and chemotherapy-related cognitive impairments (eg, confusion, lapses in memory and attention, difficulty concentrating, etc) are often known colloquially as chemo brain or chemo fog, up to 30% of patients with cancer exhibit subtle cognitive impairments prior to treatment, suggesting the body’s physiological response to a tumor (eg, inflammatory processes or vascular changes around the tumor) may be disruptive to cognition.

 Neuroimaging and neuropsychological studies have validated the role of chemotherapy contributing to cognitive issues, with chemotherapy patients having a more difficult time during memory recall than those cancer patients who did not receive the drugs, which suggests that their neural networks had been altered.

 Indeed, 75% of cancer patients have cognitive impairments during treatment, and 35% of survivors have cognitive impairments that continue in the months and years after treatment.

In addition to depression and cancer, there are many other disorders across the lifespan that have been shown to cause cognitive impairments, including ADHD,

 chronic obstructive pulmonary disease (COPD),

 depicts a small subset of disorders with associated cognitive problems.

Figure 1: Subset of Disorders With Associated Cognitive Impairments33

Innovative measurement-based approaches need to be leveraged to better understand and treat the impacts of cognitive impairments from disorders across the lifespan. Measurement-based care can be defined as the practice of basing clinical care on client data collected throughout treatment. Measurement-based cognitive care, therefore, includes ensuring that cognition is assessed and monitored at all stages of the treatment process across a multitude of disorders—not merely Alzheimer disease (AD) and late-life cognitive decline.

For example, with cancer patients, cognition needs to be assessed before treatment begins and then regularly during and after treatment. Cognitive assessments must also be easy for the patient to access. Since these patients will already be saturated with physical and mental health interventions, it is critical that any cognitive assessments and additional interventions are able to fit into their lives as seamlessly as possible.

Regular assessment and monitoring of cognitive health is also critical across the entire spectrum of health, including those who do not have a present health concern. Innovative delivery systems—such as at-home digital technologies—can ensure accessibility and awareness that these assessments exist. Regularly assessing cognition throughout the lifespan will enable cognition to be used as a new vital sign. Further, it will provide the opportunity to establish an individual’s cognitive baseline; identify changes that may suggest prodromal stages of disease and allow for early intervention. Cognitive care will adopt a more proactive, preventative, and personalized approach to one’s cognitive lifespan. Psychometric quality is clearly critical (ie, robust assessments of performance norms, reliability, validity, sensitivity, and specificity).

 Ensuring cognitive assessments include quality of life and activities of daily living is also important. 

New technologies and tools will help make measurement-based cognitive care a reality. New, predictive tools in cognition include 

 Tracking eye-movement has been found to offer a window into cognitive processes and impairments. Preliminary data indicate that eye-tracking tests may detect early stages of AD

; characterize cognitive impairments in patients with other neurological disorders, including amyotrophic lateral sclerosis, Parkinson disease, multiple sclerosis, autism spectrum disorders,

; and identify and access brain dysfunction in patients—including children—with mental health conditions such as depression.

 When implemented in a digital setting, some novel tools have been found to have a myriad of benefits.

For example, Akili Interactive developed the first and only 

 that has been cleared by the US Food and Drug Administration to treat adolescent ADHD and improves attention impairments.

 Akili’s digital therapeutic for adolescent ADHD has been found to improve objectively measured inattention as determined by the Test of Variable Attention Attention Performance Index (API) in adolescent patients with ADHD.

 Other digital therapeutics have been found to reduce cognitive impairments in adults living with MDD

 Tools are also being developed to promote the development of cognitive skills during childhood.

 Some smart phone-based technologies may be deployed worldwide including to low- and middle-income countries, allowing greater equity in cognitive care.

The necessity of validated remote evaluations—enabled by many of these new biomarkers—is apparent, underscored by the recent limitations on in-person visits secondary to the COVID-19 pandemic. Digital technologies are well positioned for a role in remote evaluation to be used synchronously or asynchronously and over telemedicine platforms.

We must re-engineer the modern health care team when moving towards measurement-based cognitive care. Just as genetic counselling was established as a new field in 1969 to help individuals navigate genetic risk and testing, a new field needs to be established to help patients navigate cognitive risk and testing. Many new cognition biomarkers provide a risk score or predictive analytic, which like predictive genetics can bring a host of new questions and worries: What does my score mean? How do you interpret a black-box algorithm? What can I do about my risk for cognitive impairment after chemotherapy? Am I developing AD or am I experiencing cognitive problems due to depression? Will these results create issues for my health or life insurance policies?

Cognition counselors are needed as part of the modern care team to 1) ensure that cognition is addressed in disorders where it is commonly overlooked (eg, postsurgery, cancer, diabetes, depression, etc); 2) help patients navigate the new anxieties and questions that arise from new technologies, cognitive assessment, and risk scores; and 3) discuss and coordinate care options and provide referrals to educational services, advocacy and support groups, novel technologies, other health professionals, and community or state services. Cognition counselors will also help overcome the barriers of implementing digital technology in both a clinical and educational setting, increasing acceptance and compliance. Further, existing care team members—such as clinical neuropsychologists—could also be trained or upskilled to fulfill the role of cognition counselors, helping to rethink and 

To optimize the likelihood that measurement-based cognitive care can be instituted, leveraged tools should be brief (≤ 10 minutes), highly scalable, able to be administered by the patient or trained clinical staff, and able to automatically generate an interpretative report with instant electronic medical record integration.

 To further help realize measurement-based cognitive care, health systems must be prepared to move quickly when a new biomarker is seen to add clinical value. We applaud the work of the 

 for proposed frameworks to accelerate such preparedness.

Finally, design thinking principles must be strictly adhered to in the development of novel biomarkers given these tools can be deployed across disorder type and the lifespan.

 For example, elderly individuals may experience changes and challenges that span disability segments, including visual, cognitive, speech, mobility, and neural impairments. From deterioration in vision to difficulty touching screens to everything in between, novel biomarkers and tools must account for these changes and be designed to be accessible to all. The fields of disability studies and assistive technologies will likely be 

 Further, measures must be taken to mitigate practice effects from repeated use of measurement-based cognitive care tools, ensuring that increasing familiarity and exposure to cognitive tests does not become a confounding factor in scores.

Measurement-based cognitive care is the urgently needed to address to the unfolding cognition crisis. Measurement-based cognitive care will bring an era of medicine where cognition is proactively addressed and better understood for disorders across the lifespan; technologies and tools underpin advancements in cognitive assessment and monitoring; and care teams are equipped to help patients navigate the new uncertainties that arise and receive proper care. In doing so, individuals will be able to improve their quality of life and have their capacity to thrive increased. Placing measurement-based cognitive care as a critical component of medicine will bring widespread personal, medical, and societal benefits.

a member of the Steering Committee of the Organization for Economic Co-operation and Development (OECD)-PRODEO Institute Neuroscience-inspired Policy Initiative, and an Atlantic Fellow for Brain Equity at the Global Brain Health Institute at UC San Francisco (UCSF).

Joy Chambers-Grundy Professor of Brain Science and Director of the Chambers-Grundy Center for Transformative Neuroscience, University of Nevada Las Vegas (UNLV).

is a Professor in Cognitive Neuroscience and Director of Research in the Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Australia.

T. Boone Pickens Distinguished Scientist at the Center for BrainHealth, a codirector at Global Brain Health Institute, professor emeritus at Trinity College Dublin, and founding director of its Institute of Neuroscience.

a Senior Clinical Advisor for Cohen Veterans Bioscience’s Trauma Research Programs. She serves as Strategic Advisor co-leading CVB’s Suicide Strategy Initiative.

Turner Institute for Brain and Mental Health, Neurodevelopment Program School of Psychological Sciences, Monash University.

is the professor of psychiatry, Director, Late-life Mood, Stress and Wellness, and Integrative Psychiatry research programs UCLA Semel Institute for Neuroscience and Human Behavior.

cofounder of the PRODEO Institute, co-lead of the OECD-PRODEO Institute Neuroscience-inspired Policy Initiative,

instructor in brain health diplomacy at the Global Brain Health Institute. He holds adjunct positions with IMPACT at Deakin University and Baylor College of Medicine.

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Articles

The world is facing a cognition crisis. Here’s how to face it with measurement-based cognitive care.

Addressing the Cognition Crisis in Our COVID-19 World

“Brain health conditions are a key contributor to the global burden of disease and disability. The devastating impact of these conditions is even more apparent as the world faces global challenges such as the COVID-19 pandemic, climate change, societal inequity, and more. To make progress, we need a fundamental shift in our approach. Convergence Brain Health deftly makes the case that a convergence approach is urgently needed to tackle the global brain health crisis and provides a roadmap for change.”

— Victor Dzau MD, President, National Academy of Medicine

Even before the COVID-19 pandemic, the world was in the midst of an escalating global brain health crisis with severe physical, social, and economic ramifications. According to a recent World Health Organization report, around 450 million individuals were suffering from mental health conditions, marking mental health disorders among the leading causes of ill-health and disability worldwide.

 The Organisation for Economic Co-operation and Development (OECD) estimates that the consequences of mental ill health cost up to 

Due to social and physical distancing, unemployment and underemployment, stress and other factors, there have been significant increases in issues such as depression, anxiety, social isolation, substance abuse, loneliness, and cognitive decline in older adults.

 In addition, as observed after the SARS pandemic, it is expected that COVID-19 survivors may endure long term cognitive and psychiatric consequences, including suicide, posttraumatic stress disorders, and depression.

 Furthermore, brain health is a prototypical 

 in that it is extremely complex and textured by innumerable variables from biology, sociology, genetics, psychology, and the natural environment to economics and beyond.

 Compounding these issues are challenges at all levels of innovation around brain health, listed in 

Table 1. Challenges and Opportunities for the Brain Health Field

Progress in the 21st century will be molded by our collective response to the global brain health crisis.

 Fortunately, beacons of hope are beginning to shine. Stigma has been reduced in high-income country settings, allowing individuals to overcome the barriers to seeking care.

 The COVID-19 pandemic has—in a positive sense—lowered the perceived and actual barriers to technology adoption, ushering in a new era of technology-driven brain health care. Some governments are beginning to increase spending on brain health, and venture capital funding for brain health start-ups has never been more in vogue. PitchBook data shows that 146 deals generated nearly $1.6 billion in venture capital investments as of December 10th, 2020. A decade ago, there were only 3 deals, worth $6.6 million, whereas last year saw a total of 

However, these advances on their own cannot solve the myriad global challenges posed by the brain health emergency. A paradigm shift is needed to address the unprecedented complexities associated with the current global brain health crisis—a crisis now inextricably linked to concurrent interacting crises surrounding discrimination and inequality, mass misinformation, environmental catastrophes, accelerated climate change, entrenched economic models, population displacements and immigrant status, and more.

 Governments, employers, and healthcare systems around the world need to acknowledge the scope of the problem and embrace solutions to empower consumers to take charge of their own brain health and to protect existing levels of health, well-being, and social inclusion.

In response to the evolving issues, convergence science integrates knowledge, tools, and thought strategies from diverse fields to address challenges that exist at the interface of 

 Convergence science not only recognizes the need to respond to apparent societal problems, but also emphasizes approaches which allow us to consider a myriad of the known unknowns and improves the odds of us quickly adapting to newly identified gaps.

 Acknowledging the serendipity of accidentally obtained knowledge permits 

 Taking these approaches when investigating solutions to brain health challenges permits greater flexibility and utility when unforeseen challenges are inevitably met.

Brains are the indispensable drivers of human progress. Why not invest more heavily in them? There are currently 

 allocated to Environment, Sustainability, and Governance investing around the world.

 If only a portion of this amount were invested in brain health, we could produce major improvements for our society.

 note that this present moment is a clarion call for the philanthropic community, which is uniquely positioned to lead an approach in 2 distinct ways. In the short term, the immediate mental health crisis can be mitigated by supporting interventions for the most vulnerable, the development and deployment of rapidly available mental health tools and technologies, and research to drive evidence-based responses to COVID-19-related mental health challenges. Much work is needed to address the long-term mental health impacts caused by the pandemic. There is an ongoing and urgent need for targeted investment in research to better understand and treat mental health conditions, build capacity and diversity within the mental health system, and advocate for social and policy solutions to improve the ecosystem of mental health care.

Given the critical need to nurture healthier, more resilient, and increasingly flexible brains worldwide, we have introduced the concept of Brain Capital—broadly defined as a form of capital which prioritizes brain skills and brain health.

The OECD Neuroscience-inspired Policy Initiative seeks to place Brain Capital at the center of a new narrative to fuel societal resilience in mitigating economic shocks, and to create preparedness should future societies fundamentally transform, for instance through irreversible damage to the environment. The OECD’s New Approaches to Economic Challenges Unit has created the Neuroscience-inspired Policy Initiative. This initiative seeks to reconceptualize and revitalize the economy, laying the groundwork to identify relevant metrics while building a transdisciplinary network of stakeholders. The initiative will rapidly refine and advance the concept of Brain Capital via a series of research projects, economic modelling, seminars, and clear policy analyses and recommendations.

In this context, our Brain Capital Grand Strategy supports the focus of the OECD initiative. The Grand Strategy has 3 main components: considering Brain Capital in all policies, developing a comprehensive investment plan to support Brain Capital, and generating a Brain Capital Index.

Brain health issues should be addressed in the context of improving performance within the fields of innovation and entrepreneurship. Because most 

 are created by firms less than 5 years old,

 creative and innovative entrepreneurs are needed to drive social and economic growth at the regional and national levels. In many ways, together with unprecedented government investment in many countries, entrepreneurs stand as a critical firewall against recession and deprivation. They serve as economic first responders when (exogenous) catastrophic events produce national and global economic shocks. 

In the United States, deaths due to suicide, opioid overdoses, and other addictions and poisonings (deaths of despair) are a barrier to complete economic recovery from COVID-19.

 Approximately 20% of prime-aged males who have dropped out of the labor force are 

 in these deaths, and many of them will not take up jobs even when available due to the severity of their addiction.

A senior economist at The Brookings Institution is leading an initiative to coordinate the many efforts to deal with this crisis. An important role for the task force would be to coordinate with the many burgeoning local level efforts to address addiction and despair, and these local organizations could greatly benefit from ties to a federal-level coordinating agency. Among other things, this agency could serve as an 

 Without addressing the linked issues of mental health and labor market drop-out simultaneously, it will be difficult to solve the tragic mental health crisis or achieve the goal of widely shared economic prosperity.

It is also essential that, given the complexity of the challenges being addressed, freedom to fail is offered liberally. Flat organizational structures, which are agile and empower individuals to make decisions in their specific areas and roles without need to constantly consult with managers at higher levels, are important. However, these decisions should be aligned with the mission and not deviate from the already traced goals and strategy. In 

, we provide examples of organizations and buildings which foster Convergence Brain Health activities.

Table 2. Infusing Convergence Brain Health Practices Into Various Levels of Innovation

Existing models of innovation are not adequate—suffering from siloing and a lack of speed. There are now a number of more contemporary models which may propel the brain health field forward more quickly and effectively. 

For example, The Davos Alzheimer Collaborative (DAC) is a public-private partnership committed to a collective global response against the challenges Alzheimer disease presents to millions of families around the world.

 The DAC aims to raise around USD $700 million for a 6-year plan to accelerate and diversify innovation in Alzheimer disease research. The 3 main components of DAC include a global cohort developed to identify new targets for potential treatments, a global clinical trial support platform to reduce the cost and time to bring new treatments to market, and a healthcare system prepared to get new treatments to patients. The DAC project will enable novel biomarker development, connect global researchers using the data platform provided by the Alzheimer Disease Data Initiative, and keep individuals with the lived experience of Alzheimer disease at the center of its efforts.

The first big data wave occurred over a decade ago, fueled by the reduced cost of -omics techniques (eg, genomics, transcriptomics), increased access to neuroimaging equipment, and the transition to electronic medical records. Insights from this data, however, have not translated into dramatically improved outcomes for patients. Diagnostic clarity is often elusive and treatment selection remains primarily trial-and-error. A second wave of big data proliferation is already underway with the increased implementation of mobile applications and wearable devices.

 Solutions are desperately needed to resolve current bottlenecks in transforming data into insights and action. 

Furthermore, according to economist Klaus Schwab, PhD, we are on the verge of the Fourth Industrial Revolution, which will see a rise in cyber-physical systems that blur “the lines between the physical, digital, and biological spheres.”

 Virtual reality environments, brain-computer interfaces, wearable or implantable devices, and mobile applications will continue to contribute to the current data explosion. Artificial intelligence integrates knowledge from a myriad of disciplines, including computer science, data science, mathematics, engineering, physics, statistics, linguistics, signal processing, ethics, and philosophy. Artificial intelligence is no longer a novelty, but a requisite set of convergence tools for navigating the future.

As psychological disorders are mediated by complex interactions between genetic and environmental factors it will be imperative to dedicate significant effort to understanding the modifiable risk factors emerging from the environment.

 Since the environment includes biological, psychosocial, and ecological components, it is likely to be more complex than the genes, proteins, and metabolites that are currently analyzed by a variety of tools. Therefore, within the framework of convergence brain health it will be necessary to develop highly powerful and complex tools that record, measure, and analyze the myriad environmental factors. This effort will be pursued as it has been with the omics technologies but with a much larger scope, ranging from psychophysiological data collected from millions of individual smartphones to satellite tracking of air pollution in big cities. Important ethical issues, however, will have to be addressed with some urgency.

Operationalizing a convergent clinical framework will require effective direction and utilization of the continuing data explosion.

 The role of digital clinical operating systems is therefore critical for allowing effective patient care, as well as ongoing research. These clinical operating systems house data from clinical encounters, imaging, pathology, personal medical devices, wearables, and finance. Analytics methods include the use of mathematical and algorithmic-based processing of data resources, including subfields of artificial intelligence, such as machine learning, natural language processing, and visual analytics to generate descriptive, predictive, and prescriptive models to analyze and derive insight from data. Machine learning has been utilized in predictive risk assessment, clinical decision support, home health monitoring, finance, and resource allocation.

Convergent approaches often require consideration of many different data types. Data harmonization involves creating a single consistent macro-data source from multiple, potentially disparate micro-datasets. Contributing datasets are structured to remove inconsistencies, creating harmony, such that the final dataset provides a cohesive view of a subject from many different perspectives. Machine learning enables automatization of this process, permitting integration of clinical, behavioral, -omic, imaging, neurosignals, and other datatypes for data mining and predictive modelling. Deep learning in combination with multidimensional biological data (eg, genomics, proteomics) enables examination of the impact of genetic variation or other system disturbances on transcription, translation, signaling, and resultant phenotypic variation. 

Perioperative brain health is an emerging example of the need for a convergence approach in brain health science. The average individual undergoes 9 surgical procedures in his or her lifetime, typically at an older age when the brain is more vulnerable to perioperative insults such as stress, illness, and immobility.

 As such, the perioperative period is a very high-risk period for older adults, and brain health impairments are abundant with considerable negative impacts. For example, the US National Health and Aging Trends Study found clinically significant depressive and anxiety symptoms in 39% and 24% older adults in rehabilitation facilities, respectively, in older adults recently in rehabilitation facilities (vs. 10% and 9% for older adults in the community).

Similarly, a study in the UK of postoperative Intensive Care Unit patients found rates of 40% and 46%, respectively.

 Depression and anxiety are connected to poor postoperative outcomes, including persistent pain, delirium, longer hospital stays, poor functional recovery, lower quality of life, and increased chance of both falls and rehospitalization.

A new field of perioperative mental health is responding to the need to integrate mental and cognitive healthcare with surgical and postsurgical care. The increasing number of older adults undergoing surgery creates high demand for this innovation, so that care can move beyond an emphasis only on surgical success and anesthetic safety, to a convergent brain health view of outcomes, such as improved functional recovery, reduced rehospitalization, and decreased long-term morbidity. These innovations are further driven by bundled care models, which include preoperative optimization, in-hospital care, and postoperative rehabilitation. With the recent genesis of the Center for Perioperative Mental Health, funded by the National Institute of Mental Health (P50MH122351), surgeons, anesthesiologists, nurses, physical and occupational therapists, and surgical patients will work together with psychiatrists in an accelerated laboratory for translating scientific advances to practical clinical care that improves the lives of older adults.

With the emergence of so many digital innovations, care providers are presented with more tools than ever. However, such a crowd of novel options adds complexity and uncertainty. To be clinically useful, such point solutions must first be vetted and then clustered into symphonies shown to play well together to optimize collective benefit for specific conditions. In the dementia field, for example, it is encouraging to see multidomain interventions being deployed.39 In the future, a therapeutic guidance system may make sense, similar to those used to advance precision medicine, such as oncology and neurosurgery.

To develop a workforce that can harness and deploy a convergence brain health framework, increased inclusion and empowerment of women and other traditionally under-represented populations is required. Building institutions that are both inclusive and meritocratic is health promoting in its own right. But more importantly, it is a powerful mechanism for producing the additional talent, fresh perspectives, and new ideas that are needed.

Meanwhile, certain behavioral characteristics among individual innovators should be cultivated. MacRae and Furnham

 articulated 3 dimensions of a high-potential individual suited to convergent teamwork building on Silzer and Church’s model of potential.

 There are 3 core dimensions: foundational, growth, and career dimensions. These dimensions explain how personality traits are foundational to potential because they represent fundamental and stable individual differences. Personality traits, especially conscientiousness and adjustment, contribute to success in nearly any type of work and have, “higher predictive ability of potential in roles that are more complex, challenging, and demanding such as that of the convergence practitioner.”

Career dimensions are the unique and specific skills, expertise, and occupational knowledge required for success in a specific career or role: “Convergence practice requires sublimating one’s own objectives into the vision and the objectives of the team.”

 MacRae and Furnham explain in detail how personality traits fit within a model of convergence practitioner potential and expand on 10 behaviors that are related to career dimensions of potential.

 These behavioral and workplace cultural characteristics allow us to formulate screening criteria for potential new entrants into convergent brain health work, identify those who are high potential convergence practitioners, as well as consider training approaches for those within our existing brain health structures.

Leaders must assume a critical role in optimizing transdisciplinary collaboration and facilitating the emergence of discoveries from these endeavors.

 Gray outlined 3 responsibilities of transdisciplinary leaders: cognitive leadership, structural leadership, and processual leadership:

. Effective cognitive leadership provides a vision that links and motivates transdisciplinary researchers to step beyond their disciplinary lens, relax old assumptions, and search for creative frame-breaking solutions.

. Effective structural leadership adds value by creating bridges and links among unconnected individuals, labs, groups, or departments.

- Processual Leadership: Effective processual leadership encourages trust and turns conflict into constructive interactions.

These leadership approaches should be kept in mind when fostering Convergence Brain Health within an organization. Other 

 of a convergence workplace include a flat organizational structure with minimal discipline silos, a culture of trust and mutual respect, and an open acceptance of the need to respectfully challenge entrenched ways of thinking.

 Teams should be humble in acknowledging that nobody has cracked the many complex problems to date, and likely never will due to unsolvable uncertainty. However, being open to novel and seemingly eccentric ideas may help navigate such problems and identify ways for their best possible management.

Teams in a convergence workplace must embrace the three somehow radical tenets outlined in Jim Dator, PhD’s 

: 1) The future cannot be predicted because the future does not exist; 2) Any useful idea about the future should appear to be ridiculous; and 3) We shape our tools and thereafter our tools shape us.

 An optimal convergence science environment should have a strong guiding vision, will be capable of identifying myriad possible alternative futures, and better guide the organization toward the desired future.

Convergence Brain Health provides direction for transformational change in how teams could work and how organizations need to be built and operated. As we embark on building the new normal of our post-COVID-19 world, Convergence Brain Health will play a key role in this rapidly unfolding change. Indeed, Convergence Brain Health provides an opportunity to grow global Brain Capital and enter a new era of innovation and progress, leading to greater health justice for all people and preparing for the unprecedented brain health challenges of the 21st century.

is cofounder of the PRODEO Institute, adjunct associate professor with IMPACT at Deakin University, instructor in brain health diplomacy at the Global Brain Health Institute, and co-lead of the OECD Neuroscience-inspired Policy Initiative.

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