Barbara Schildkrout, MD

A complete, accurate, and timely diagnosis is the cornerstone around which effective treatment is constructed. Yet, the complex skills involved in the art and science of diagnosing have only been the focus of investigation for less than a decade.

While the process of diagnosing is common to all fields of medicine, this article specifically addresses missed “medical” diagnoses in patients who present to or are being followed by psychiatrists and other mental health clinicians. It is hoped that by learning about vulnerabilities within the diagnostic process, readers will have the opportunities to reduce diagnostic error rates in their own practices and institutions.

Diagnostic errors and delays are so widespread that most individuals will experience a diagnostic error during their lifetime.

 And surely, every physician has had the experience of missing a diagnosis or coming to the correct diagnosis only after too long a delay. Memories of missed opportunities for earlier intervention weigh heavily upon us.

What Is the Correct Diagnostic Formulation In Neuropsychiatric Practice?

Recent studies have found that any individual with a “psychiatric history” or with “presenting symptoms in the sphere of mental functioning and behavior” is especially prone to experiencing a diagnostic error.

 This should alert all psychiatrists, since these are the very patients we are called upon to see. Rare diseases might be misdiagnosed, but, more often, common diseases are missed, especially if they present atypically.

In 2015, an Institute of Medicine report-

-concluded that, “. . . improving the diagnostic process is not only possible, but presents a moral, professional, and public health imperative.”

How do doctors make a diagnosis? As you read the following vignette of a referral, try to be aware of your diagnostic hypotheses.

According to his primary care physician (PCP) who referred him, Mr O has a long history of psychosomatic complaints. Mr O is a 63-year-old accountant who recently retired. He’s been sleeping restlessly and waking up depressed each morning. He jogs a few miles a day, most days, but says that lately he’s been feeling stiff and somewhat unsteady on his feet. Also, he says he’s “plagued by” constipation. The patient told the PCP that he can’t tell whether these physical problems are “all in my head” or whether there’s really something to worry about.

When you get a referral, you are presented with a great deal of information, and it isn’t clear which information will be relevant to your eventual understanding of the patient’s health problems. Some of the material that is contained in the referral will be explicit, some implied, details may be inaccurate, and surely, much will be left out.

Now consider that once you greet a patient in the waiting room, you will have even more information. You will notice how the patient is dressed and what he’s been doing while waiting; you will observe his facial expression, level of social comfort, his gestures and gait. And, before you even hear the patient’s voice or ask a single question, all of these experiences will affect you and have an influence on how you are inclined to think about the diagnosis.

Diagnostic problem solving is extremely engaging for physicians, but it is not the defined type of problem solving one encounters with something like a crossword or Sudoku puzzle in which there are 26 letters or 9 numbers that are manipulated to form one unique solution. Making a diagnosis is complex problem solving in an uncertain domain. Any particular information or observation might be relevant; and any particular information or observation might be irrelevant (noise). The patient might leave out crucial parts of the illness story, perhaps not realizing that they are important. Or the physician–problem-solver may have insufficient knowledge, perhaps never having heard of the diagnosis that actually explains the patient’s symptoms. There also could be more than one diagnosis; and these diagnoses might be interacting with one another.

The reigning theory about diagnostic problem solving is that it involves two interacting cognitive systems-system 1 and system 2.

System 1 cognition is illustrated by the experience of seeing a patient for the first time and “knowing” immediately that the patient has, for example, schizophrenia. System 1 is based on mental pattern-recognition; it is intuitive, but honed and refined by experience; it is fast, effortless, and operates outside of awareness. While this system is extraordinarily efficient, processing large amounts of information very rapidly, it is also highly error-prone and open to biases (predispositions to think and act a certain way) of which the clinician is generally not aware.

System 2 cognition is exemplified by the generation of a differential diagnosis list and examining the evidence for and against each diagnosis. System 2 utilizes explicit rules of logic; it is slow, effortful, entirely conscious, and analytical. Clinicians naturally favor the use of system 1 cognition because it is effortless. But the most effective clinical reasoning involves going back and forth iteratively between system 1 and system 2 cognition.

Now let’s return to the case vignette. The patient’s story is in your mind when you go into the waiting room. Depending upon your fund of knowledge and your experience, you might have what turns out to be an accurate diagnostic impression from the referral information. But perhaps you don’t. To get to the correct diagnosis, you might have to overcome the “framing effect” in which your cognition has been biased by the way the patient’s problem was first presented to you.

 In the case of Mr O, your intuition may have been biased toward thinking that the patient is depressed with somatic complaints precipitated by his recent retirement.

Now you escort the patient from the waiting room and by the time you and the patient have settled into the chairs in your office you have new information to include in your diagnostic formulation. Your system 1 cognition immediately registered that Mr O had parkinsonian features. His affect was somewhat flat and he walked slowly, with a diminished arm-swing.

Now you use system 2 logic in an effort to piece together the information you have so far. Does the narrative presentation fit with your observations? You interview the patient, carefully framing your questions to better understand the patient’s symptoms and the arc of his illness over time.

Knowledge and experience are both crucial in making the diagnosis of Parkinson disease in Mr O’s case. In addition to the blunting of facial expression and “feeling stiff and somewhat unsteady on his feet,” you learn that Mr O has been worried about falling, especially when he walks down a staircase. This is consistent with a shift in the center of gravity and forward propulsion associated with Parkinson disease.

Mr O also has had depression, prominent constipation, and fatigue-these symptoms are often prodromal in Parkinson disease, Lewy-body dementia, multiple systems atrophy and other, less common parkinsonian syndromes. If you know the symptoms for Parkinson disease, you ask Mr O whether his handwriting has gotten smaller. It has. Then you inquire about his sleep. He has had restless sleep for several years; on a number of occasions he has fallen out of bed. In addition, he has hit his wife in the middle of the night more than once, although he doesn’t remember doing this.

You might recognize that this is the classic presentation of rapid eye movement (REM) sleep behavior disorder, which is strongly associated with the subsequent development of Parkinson disease and related syndromes. In REM sleep behavior disorder, there is a failure of the usual inhibition of muscle tone that accompanies REM sleep. This allows the sleeper to move about during REM sleep and to act on dream content, including “fending off attackers” by lashing out.

To get to a correct diagnosis, clinicians must navigate a wide variety of inherent cognitive biases. For example, with Mr O, if you hadn’t realized from the referral that he might have had Parkinson disease, you had to overcome the impact of “anchoring,” the tendency to stick with your first diagnostic impression. You also had to overcome “availability bias,” the tendency to think that a diagnosis that readily comes to mind is likely to be the correct diagnosis.

For psychiatrists, major depression or dysthymia with somatic concerns is a diagnostic formulation that is commonly seen and readily comes to mind. Parkinson disease comes less readily to mind.

Cognitive biases are ubiquitous; they reflect the flow of nonconscious predictions we make, based on past experiences, as we move through the world. The influence of cognitive biases on diagnostic reasoning has been well described by Croskerry

 who has studied diagnostic errors in emergency department settings where physicians have to make quick decisions with little information about the patient and are forced to rely heavily on error-prone systems.

In the case of Mr O, it would have been a cognitive error to believe that the etiology of his symptoms was the difficulty he was having adjusting to retirement, along with his tendency to focus on somatic concerns. This would have been an “attribution error” in which you held the patient responsible for his or her disease. All physicians are prone to making attribution errors, especially when making a diagnosis in patients who have behavioral symptoms.

Another common bias is a tendency to look for confirming evidence-“confirmation bias”-rather than disconfirming evidence, although disconfirming evidence is much more powerful. It turns out that Mr O’s symptoms of restless sleep, constipation, fatigue, and depression actually began before he retired, not after.

Furthermore, it is helpful for clinicians to be aware of the possibility of “premature closure,” the tendency to stop investigating once you have come upon a diagnostic hypothesis but before that hypothesis has been fully proven. This is an especially easy error to make when a medical condition has a long prodromal period without symptoms that are specific enough to make a clear medical diagnosis. As psychiatrists, we often encounter diseases of this type; Parkinson disease is but one example. Others include: multiple sclerosis, Wilson disease, Alzheimer disease, Cushing disease, fronto-temporal dementia, Huntington disease, and more. Periodically reviewing a patient’s condition while maintaining diagnostic uncertainty forces the clinician to rely more on system 2 cognition.

Non-specific behavioral and mood alterations often represent the very first and, occasionally for prolonged periods of time, the one single and exclusive sign of an undetected physical illness. Flagrantly and convincingly “psychological” in nature on presentation, such masked physical conditions frequently mislead the examiner and obliterate any further medical consideration, resulting in misdiagnosis and thus, inevitably, in treatment gone astray.

Recent studies of diagnostic error have not focused on patients who are being treated in mental health clinics or inpatient psychiatric units; however, past studies of psychiatric patients found that, important medical diagnoses were missed in these patients as often as 40% of the time, depending upon the setting.

 Moreover, these medical diagnoses were not uncommonly the sole cause or a significant contributing factor to the patients’ presentations.

How can you contribute to decreasing diagnostic error rates? Expert opinion emphasizes: expand your knowledge; cultivate good clinical habits of mind, including expanding your knowledge and experience, self-care, humility, persistence, and the use of feedback; and utilize the use of metacognition-thinking about thinking, and work to improve the institutions within which you work.

There is much for psychiatrists to learn in the realm of neuropsychiatric disease. Often patients with medical conditions will first present to psychiatrists thinking they have a psychological problem or a mental illness. Many will have common diseases: focal seizure disorders; neurodegenerative diseases in addition to Parkinson disease, such as Alzheimer disease, vascular dementia, or Lewy-body dementia; the long-term consequences of traumatic brain injury; autoimmune diseases such as multiple sclerosis; or sleep disorders. Some patients will have diseases that are less common: anti-

-methyl-D-aspartate receptor encephalitis, Wilson disease, Huntington disease, frontotemporal dementia. Familiarize yourself with the clinical presentations of these and other neuropsychiatric conditions.

 And remember to keep this question in the front of your mind: Could this patient have a medical condition that I am missing?

Diagnosing is a high-level creative process; as such it relies on reflective practices that allow time for you to think about your reactions to patients and about your diagnostic process.

 Even with a few moments of mentally stepping back to get perspective are important. In addition, actively employ strategies that force you to use the conscious, analytic system 2 cognition. Ask yourself, “What could this be?” Make a differential diagnosis list. Work against premature closure in the face of doubt and uncertainty. Remember that keeping a diagnosis “open” forces your “problem-solving mind” to keep working on what the diagnosis might be.

Improving health care systems in support of diagnosing

Psychiatrists rely on hospital systems to support the diagnostic endeavor. Health care institutions may provide effective communication systems that allow collaboration with the patient and his or her family, health information technology, reliable laboratory services, access to library resources, expert second opinions, collaboration across disciplines, and specialties, and a culture that values reduction of diagnostic error rates while, at the same time, avoiding shaming and blaming.

Dr Schildkrout is Assistant Professor of Psychiatry, part time, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA. She is the author of two books:

 Unmasking Psychological Symptoms: How Therapists Can Learn to Recognize the Psychological Presentation of Medical Disorders 

 Masquerading Symptoms: Uncovering Physical Illnesses That Present as Psychological Problems.

. Washington, DC: National Academies Press; 2015.

 Croskerry P. The importance of cognitive errors in diagnosis and strategies to minimize them. 

 Croskerry P. Clinical cognition and diagnostic error: applications of a dual process model of reasoning. 

 Yates BL, Koran LM. Epidemiology and recognition of neuropsychiatric disorders in mental health settings. Ovsiew F, Ed. 

Neuropsychiatry and Mental Health Services

. Washington, DC: American Psychiatric Press; 1999: 23-67.

 Koranyi EK. Morbidity and rate of undiagnosed physical illness in a psychiatric clinic population. 

 Schildkrout B. Complexities of the diagnostic process. 

Masquerading Symptoms: Uncovering Physical Illnesses That Present as Psychological Problems

Articles

While the process of diagnosing is common to all fields of medicine, this article specifically addresses missed “medical” diagnoses in patients who present to or are being followed by psychiatrists and other mental health clinicians.

Diagnostic Errors in Neuropsychiatry

MyCopy [3], Printed eBook for just $24.99

In medical publishing, the casebook format has become increasingly popular-and for good reason. A memorable clinical vignette facilitates learning.

 As clinicians, we assimilate information best from case examples. We can imagine ourselves in the story, especially when the cases are drawn from real life and the authors do not edit out the confusions and uncertainties of actual psychiatric practice-the patient whose history is hard to follow; the individual with multiple diagnoses, or someone with an atypical presentation.

Pediatric Neuropsychiatry: A Case-Based Approach

 is a new casebook that focuses on the overlap of neurology and psychiatry in child practice.

 The co-editors, Aaron J. Hauptman and Jay A. Salpekar, two neuropsychiatry colleagues of mine, have called upon 65 contributing scholars to present a comprehensive, clinically relevant, and very readable text.

Psychiatrists are increasingly aware that the boundary between psychiatric disease and neurological disease is arbitrary.

 This book is written with the goal of presenting an integrated conceptualization of neurology/psychiatry and brain/behavior in the realm of pediatric neuropsychiatry practice.

Child and adolescent psychiatrists are on the front lines of neuropsychiatry. Everyday considerations in the practice of child and adolescent psychiatry include: brain development, genetic diseases, the influence of prenatal exposure to alcohol or drugs, nutritional influences on brain health, family dynamics, and educational opportunities that shape neurodevelopment. Many neuropsychiatric diseases that adult psychiatrists treat are first seen in children: autism spectrum disorders, ADHD, lead poisoning, fetal alcohol syndrome, sleep disorders, Tourette syndrome, epilepsy. 

 covers all of these topics and more-pediatric traumatic brain injury, anoxic brain injury, non-epileptic seizures, childhood multiple sclerosis, autoimmune limbic encephalitis, PANS [pediatric acute-onset neuropsychiatric syndrome] and PANDAS [pediatric autoimmune neuropsychiatric disorder associated with streptococcal infection], hypothalamic tumors.

The book contains 26 chapters that focus on case examples. The case descriptions are followed by a discussion of diagnostic impressions, a succinct summary of the relevant neuroanatomy and pathophysiology, treatment strategies, and neuropsychiatric “lessons learned.” An additional chapter discusses the pediatric neuropsychiatric exam.

Throughout the book there are unique features such as: personal reflections written by patients or family members, “Clinical Pearls,” and summaries of educational materials or available resources like rating scales for ADHD. There is a substantial section on complementary and alternative medicine strategies for patients who have epilepsy. It is clear that the authors were writing with the needs of clinicians in mind.

While there are now 33 accredited fellowships open to psychiatrists who seek post-graduate training in Behavioral Neurology & Neuropsychiatry, no such formal programs are available in pediatric neuropsychiatry.

 For child and adolescent psychiatrists who are interested in learning more about neuropsychiatric thinking, this latest casebook is an excellent resource. There is also much material here that would appeal to psychiatrists with adult patients.

I spoke with Jay and Aaron about their book. Jay Salpekar is a Child and Adolescent Psychiatrist who runs a Neuropsychiatry in Epilepsy Program at Kennedy Krieger Institute, an institution specializing in brain and spinal cord diseases and developmental disabilities in children and young adults. He is also on the full-time neurology and psychiatry faculty at Johns Hopkins University School of Medicine.

When we first came up with the idea for this book, we knew that we wanted it to be different. We wanted to include patient and family stories and also their personal reflections; we think these are as important as the scientific background for enlightening our understanding of cases.

We were so gratified by the reception we got from chapter authors, all experts in their fields. We wanted cases that would illustrate brain and behavior relationships. It didn’t have to be the most rare case or a neat and tidy case. The contributors understood the concept and were totally on-board.

Aaron Hauptman is a Child and Adolescent Psychiatrist at Boston Children’s Hospital who is also in a Behavioral Neurology and Neuropsychiatry fellowship program at Brigham and Women’s Hospital. He works with individuals with developmental and acquired CNS injuries across the lifespan. According to Aaron,

In addition to providing accurate diagnoses, one of our main goals as clinicians is to be able to offer to the children and families who are struggling with neuropsychiatric illnesses an integrated formulation of their experiences. It’s not an either/or situation. And in fact, to try to pigeonhole what’s going on as either uniquely neurological or psychiatric is both invalidating and often inaccurate. A large part of why we wrote the book was to help give other clinicians a sense of this integrated approach.

A one-to-one correlation between brain and behavior is much less certain in children because they adapt so quickly. Despite the fact that prognostication and localization are so different for pediatric patients, still attention to neuroanatomical correlates of cognition, behavior, and emotion can be tremendously valuable.

Working with these patients and families has been an unparalleled experience. I’m optimistic about shifts in the field toward increasing integration of neurology and psychiatry. We hope that our book helps more clinicians to take part in the discussion.

Dr Schildkrout is Assistant Professor of Psychiatry, part time, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA. She is the author of two books: Unmasking Psychological Symptoms: How Therapists Can Learn to Recognize the Psychological Presentation of Medical Disorders and Masquerading Symptoms: Uncovering Physical Illnesses That Present as Psychological Problems.

 Benjamin S, MacGillivray L, Schildkrout B, et al. Six landmark case reports essential for neuropsychiatric literacy. 

 Perez DL, Keshavan MS, Scharf JM, et al. Bridging the Great Divide: What Can Neurology Learn From Psychiatry? 

 United Council for Neurologic Subspecialties. 

https://www.ucns.org/apps/directory/index.cfm?event=public.program.searchResults&subspecialty_ids=1&inst_state=&submit=Start+Search

In medical publishing, the casebook format has become increasingly popular-and for good reason. A new casebook focuses on the overlap of neurology and psychiatry in child practice.

Child Psychiatrists: On the Front-lines of Neuropsychiatry

Thoughts After Attending the American Neuropsychiatric Association Annual Meeting

Attending a professional conference is not easy. There’s the disruption to your schedule and the responsibility for finding clinical coverage. If the meeting is out of town, substantial financial costs and advanced planning are involved. Many of us also have to negotiate the extra burden placed on family members who care for children and households while we’re away. Then there’s the packing, traveling, and, for some, managing social anxiety, especially around unscheduled meals at the conference itself. It’s not a vacation. Why do we bother?

The recent 29th Annual Meeting of the American Neuropsychiatric Association (ANPA) reminded me of the reasons that I do bother to make the effort every year. This article present some of the highlights from talks and presentations at this year’s ANPA meeting (

However, even outstanding content does not propel attendance: content is only the focal point around which other, important aspects of a conference experience unfold. After all, excellent and up-to-date information is available online 24/7, from home, and perusing that material on your computer may be a more efficient use of your time than sitting through a lecture that might be boring or offer you little new information. Moreover, it is possible to purchase continuing education credits for much less money than the cost of traveling to a professional conference. Once again, why do we bother?

The benefits of attending professional conferences extend beyond the program. My experience at the ANPA conference is surely similar to what others feel when they attend well-planned conferences sponsored by organizations in their areas of interest. There is a sense of excitement, the “thrill of the crowd,” as those who are passionate about a subject gather and devote time to a shared experience away from the ordinary day-to-day. Contributing to this thrill is the opportunity to interact informally with the field’s thought-leaders during breaks in the program, social hours, or poster sessions. In addition, the expected gratification that comes from hearing an outstanding scientific talk is multiplied when well-informed audience members ask probing questions and animated discussions spill out of the auditorium into the coffee break. Learning new ways of thinking often requires this kind of deeper, more active engagement with material.

For me, one of the best things was that fellow attendees didn’t seem to tire of talking about the brain and behavior, which allowed me to indulge my enthusiasm for the subject. Whenever I stopped to notice, I could see small groups of people gathering to chat. Catching bits of their conversations, I heard discussions about challenging patient situations, plans for collaboration being formulated, information being shared. “I’ll send you that paper.” “I have a student who might be interested in working with you.” “You ought to talk with . . . .”

One only needed to walk a few steps to find an expert who could help you sort out some confusion or answer a question. Gathered in one room were remarkably experienced clinicians, researchers, teachers, writers, and editors in areas of interest to many psychiatrists: traumatic brain injury, functional movement disorders, both common and rare forms of dementia, the role of the cerebellum in cognition, anti-NMDA receptor encephalitis, neuropsychiatric manifestations of epilepsy, the genetics of autism spectrum disorder, in short-topics from Alzheimer disease to neuropsychiatric rare diseases -“the Zebras.”

Enrico Fermi is reputed to have said, “Never underestimate the joy people derive from hearing some thing they already know.” We all appreciate hearing presentations that reinforce our fund of knowledge and validate our experiences with patients. There is added benefit when a speaker is able to expand that knowledge into new territory or when the talk helps us to see current information from a different perspective, be that an historical panorama or the view from another field of study such as law, rehabilitation medicine, data science. On the other hand, there is a case to be made for sitting through some talks that we can’t quite follow. This is like a “good mental-stretch.” It reminds us that science is wide and deep, and there’s always more to learn.

In attending any conference, our fondest hope is that we might encounter a truly inspiring lecture. Talks of this nature are in a class of their own, bestowing upon the listener a personal feeling of exhilaration; they leave each audience member feeling re-energized, uplifted, aware of expanded possibilities, and back in touch with the deeply meaningful aspects of one’s own work.

Presentations like this are rare, but Lucia Willadino Braga, PhD, from the SARAH Network of Rehabilitation Hospitals in Brazilia, Brazil, delivered one. Using several remarkable case examples, Dr. Braga demonstrated how education and neurorehabilitation harness the brain’s neuroplasticity, resulting in changes in structural and functional connectivity.

One of her patients was a popular Brazilian music star who had suffered a traumatic brain injury and spinal cord lesion. It seemed unlikely that he would ever be able to sing or play guitar again given that he had post-traumatic memory deficits and paraplegia. Yet, after one year and 9 months of intensive rehabilitation he was back to performing. The professionals from the SARAH network had worked with the patient and his band; together they had formulated strategies for helping the musician. For example, when he forgot lyrics while on stage, he would turn his back to the audience momentarily in a way that seemed entirely natural, and this gave other band members the opportunity to remind him of the words.

Another case involved a healthy, 45-year old man from a remote Brazilian villageThis gentleman had never been exposed to written language. At the SARAH hospital, he was taught to read and write. Functional imaging and diffusion tensor imaging (DTI) were used to track the changes in his brain as he went through this process of first learning to identify letters, then learning to read syllables, then simple sentences, and so on.

Initially, before any instruction had begun, looking at written language did not elicit a different response in the patient’s visual cortex than looking at non-linguistic, visual stimuli. However, in sync with the various phases of language acquisition, the specific areas of the brain that are generally associated with these aspects of language became activated. There also was substantial enlargement of the arcuate fasciculus that connects brain regions involved in language function.

What made this talk so extraordinary? The SARAH network hospitals are guided by Dr. Braga’s powerful vision, which she has made into a reality. All individuals are treated with equal attention and respect. From the very first encounter, the patient, the family, and specialists from diverse professional backgrounds meet to create a working team. Their goal is to help each patient attain his or her maximal level of functioning. The SARAH team utilizes an ecological method that persists outside the treatment center and involves real-life situations.

The SARAH network is also devoted to innovation. For example, they developed a program that trains high school students to work with individual patients outside the hospital setting. The students take patients to sporting events and other activities, thereby harnessing the power of peer learning. To help overcome stigma, a “wheelchair” for children was created that looks more like a colorful plastic toy than a medical appliance for the disabled.

Some of SARAH’s financial support comes from Brazilian congressional discretionary health care funding. Also innovative is the funders know exactly which specific project they are supporting (eg, the production of a training video, the development of a new rehabilitation program, research that will lead to a scientific publication). The funders are then given specific feedback about the progress and outcome of “their” project.

Dr. Braga is doing what we all aim for-to help patients by harnessing the synergistic power of scientific knowledge and human relationships. She left her audience with a feeling that it is possible to raise the bar in one’s own practice and be more effective, creative, and generative. This kind of hopefulness is long remembered.

The benefits of attending a professional conference extend far beyond the content itself, and these benefits accrue if you attend year after year. The meetings help you nurture a deepening knowledge in the topic area. Repeat attendance also adds the pleasure of reconnecting each year with colleagues from around the country or around the world. Becoming actively involved in the organization (such as serving on a committee) might take little extra time over the course of a year but can add a sense of belonging; this transforms the experience of simply “going to a conference” into the experience of “being part of the organization.”

Like many professional organizations, the ANPA looks to the future and works to advance the field. The ANPA committee for research is developing clinical recommendations specifically for neuropsychiatric disorders. These go-to guides to best practices will be evidence-based whenever possible and they will reflect expert consensus. Recommendations are currently being developed for the following topics: assessment of psychogenic non-epileptic seizures; assessment of functional movement disorders and weakness; treatment of functional neurological disorders; assessment and treatment of neuropsychiatric aspects of fronto-temporal dementia.

In addition, ANPA honors individuals who have made important scientific, educational, and/or clinical contributions. Groups such as ANPA foster the careers of talented young people by hosting poster presentations and bestowing awards that recognize early career accomplishments. As a member of the organization, you become part of this generous spirit-grateful to those who have truly devoted themselves to making a difference and encouraging those who will influence the future of medicine.

 Braga LW, Amemiya E, Tauil A, et al. Tracking adult literacy acquisition with functional MRI: a single case study. Mind Brain Ed. 2017;11:121-132.

 Dehaene S. Pegado F, Braga LW, et al. How learning to read changes the cortical networks for vision and language. Science. 2010;330:1359-1364.

This article present some of the highlights from talks and presentations at this year’s American Neuropsychiatric Association Annual Meeting.

Why Attend a Professional Conference?

One of the greatest scientific challenges for 21st century medicine is to illuminate the relationship between the brain and what we call “mind.” Psychiatrists want to know how we get from neurons and synapses to mental suffering. How do learning, development, and cognitive flexibility arise? What accounts for the uniqueness of every human self? What goes wrong in psychiatric disease? Within the psychiatric community, brain science has generally been regarded as being still too elementary to explain such complex phenomena.

In this article I describe how analysis of the brain’s intrinsic functional connectivity has become an important approach for expanding our understanding of the astounding complexity of the human brain. Utilizing this new paradigm, it is possible to explore questions that earlier seemed virtually unfathomable; many of these are relevant, even pivotal, to psychiatry.

In news parlance, functional connectivity is a “rapidly developing scientific story.” And for psychiatrists, it is a story worth following.

Functional “imaging” measures physiological factors that are considered to be a gauge of neuronal functioning (such as changes in regional oxygen utilization); the accumulated data are then transformed into “human readable” images. Functional “connectivity” utilizes functional imaging data and analyzes the statistical associations between measurements of neurophysiological activity in 2 or more spatially remote areas of the brain. Functional connectivity studies are a mathematical, non-theoretical look at activity over the whole brain, in an attempt to discern in which areas the activity is either correlated or anti-correlated. For example, do areas A and X display increased metabolic activity when area D exhibits decreased metabolic activity?

Traditional functional connectivity methods do not tell us about the direction of connectivity-which region is influencing which. Functional connectivity also does not tell us whether 2 regions are simultaneously being influenced by a third. Nor does functional connectivity say anything about the way in which various brain areas might be structurally connected. Functional connectivity takes a purely statistical look at larger patterns of neurophysiologic activity that emerge from the brain’s hundreds of billions of neurons, reciprocally interacting over both short and long distances at microsecond speed.

Early functional connectivity research was designed to study the brain while an individual was performing a task or interacting with the environment-termed “psychophysiological interactions.” More recent work has shifted to a focus on the brain’s intrinsic neural activity while the subject is at “rest” or engaged in undirected thought.

It was not until the early 1800s that modern scientific notions about the brain began to take precedence.

 Franz Joseph Gall promoted the idea that various mental capacities were localized to different brain regions; he also believed that the strength of these qualities could be measured by looking at protrusions in the skull overlying these areas. This notion was at the heart of phrenology, extremely popular in the 19th century.

Gall assumed that the brain was symmetrically organized. His categorization of what constituted fundamental, functional capacities of the brain drew on cultural values of his day, including vanity, guile, kindness, and pride. Although scientific advances have discredited many of these claims, Gall’s fundamental insight about localization was profound.

Localization was a powerful new idea at the time; it exhibited the 2 fundamental attributes of a paradigm as first defined by the science historian Thomas S. Kuhn as “. . . sufficiently unprecedented to attract an enduring group of adherents away from competing modes of scientific activity. Simultaneously, it was sufficiently open-ended to leave all sorts of problems for the redefined group of practitioners to resolve.”

The localization paradigm opened new questions for legitimate scientific inquiry; neurological investigators became the Lewis and Clark of neuro-anatomic territories. More than 200 years of explorations in neurology have been spent mapping the localization of various functional elements within the brain and simultaneously parsing brain activity into its most fundamental capabilities.

For example, until the mid-1950s, memory was considered to be a widely distributed, unitary function of the brain. Then, studies of patient H. M. elucidated a central role for the hippocampus in memory formation. In addition, episodic and procedural memory processes were differentiated.

While the concept of localization drove much of the work of scientific exploration during this time, there also were global, overarching theories of brain function. The eminent British neurologist John Hughlings Jackson posited that the more evolutionarily developed regions of the brain exerted control over primitive brain areas; he articulated how disturbances in this organization were evident in disease states. Indeed, many scientists who are well known for their work on localization (Wernicke, Penfield) also were aware that the brain was extraordinarily complex and that the parts had to work together, like an astoundingly accomplished orchestra.

An important step in expanding the localization concept and focusing on how various parts of the brain communicated was the recognition of disconnection syndromes in the 1960s.

 Disconnection syndromes did not result from lesions in the cortical gray matter itself but rather from interruptions in the white matter fibers and tracts running to and from cell bodies in gray matter-the lines of communication within the brain. If a lesion in white matter isolates or “disconnects” a crucial cortical region, this could lead to a clinical picture similar to one seen with a lesion in the cortical area itself. In other words, now neurologists were turning their attention to structural connectivity, the so-called wiring diagram of the brain.

Astoundingly, all of this work was accomplished by utilizing only clinical observation, scientific reasoning, and post-mortem findings. The only imaging available was pneumoencephalography, a painful technique that allowed clinicians to visualize the shape of the ventricles in the brain of a living patient by using x-rays after injecting air into the spinal column.

Until computed tomography (CT) came into clinical use in 1973, it was not possible to visualize brain parenchyma during life. Not until 1994 was there a technique that spared radiation exposure-magnetic resonance imaging (MRI). CT, MRI, and other brain imaging approaches have allowed us to make remarkable advances in mapping human brain structures and in diagnosing human disease, but these modalities also have inherent limitations. An MRI scan is not a “picture” in the usual sense but rather a computer-generated readout of summary information into a digital image. One voxel (essentially a 3-dimensional pixel) in brain imaging contains information from approximately 1 cubic millimeter. Within 1 cubic millimeter of gray matter are perhaps a million neurons plus glia cells, blood vessels, and extracellular space.

In other words, none of these structural imaging techniques approaches the level of the individual neuron. Also, a structure-alone perspective of the human brain has other inherent limitations. For example, even if we take into account ongoing remodeling of neuronal connections (neuroplasticity), how can we account for the brain’s astounding moment-to-moment flexibility?

Functional imaging techniques measure fluctuations over time in factors that gauge neuronal activity such as regional glucose utilization, blood flow, or oxygen consumption. The most widely used functional imaging techniques are positron emission tomography (PET), which utilizes radioactively tagged molecules, and functional MRI (fMRI), which differentiates molecules by their behavioral responses within a magnetic field.

One important functional imaging approach is based on the observation that, in a magnetic field, oxygenated blood behaves differently than de-oxygenated blood. This allows researchers to track fluctuations in blood-oxygen levels in human subjects in the scanner without the use of radiation. This blood-oxygen level dependent (BOLD) signal has become a major investigative tool.

Functional imaging techniques allow clinicians to evaluate patients who may have deficits in neuronal functioning even when structural deficits are not apparent. For example, early in the disease course of frontal dementias, patients may have decreased functioning in frontal regions before any changes are seen on structural imaging.

Functional imaging also has made it possible for investigators to pursue a myriad of fundamental questions. One line of such inquiry examines which parts of the brain are active as someone performs a carefully designed task. For instance, how is viewing a familiar face different from viewing an unfamiliar one? Which parts of the brain are involved in moral decision-making? Also, for a given task, are normal individuals functionally different from people who have specific psychiatric conditions?

A serious obstacle for functional imaging research has been distinguishing a “task signal” of significance from background “noise.” The brain is metabolically very active, utilizing approximately 20% of body energy resources even though it represents only 2% of body mass.

 Most of this energy utilization is from ongoing neuronal metabolism. When performing a demanding cognitive task, the brain’s energy utilization increases by less than 5%. Furthermore, differences that might exist between the normal and the study populations are even smaller.6 These factors make the task signal difficult to detect.

Also, individuals vary in their level of effort, degree of anxiety associations related to the task that come to consciousness, movement during the study, and so on. Although these brain-based activities are not the focus of the study, the metabolic activity they produce shows up in the scanner. Therefore, to amplify the task signal and also draw broad conclusions, a widely used approach to studying task-related questions has been to pool the findings from numerous individuals and average the results onto a standard anatomical brain atlas.

Along with these technical challenges, functional imaging studies also have a theoretical limitation built into their fundamental design. Task-based functional connectivity studies focus on the brain correlates of the task and assume the brain’s ever-present background neuronal metabolic activity is simply “noise.”

Resting state connectivity and its importance

In 2001, an important observation changed the field of functional imaging. Marcus Raichle compared PET and, later, fMRI BOLD signal findings from research subjects who had been engaged in task-based studies with those who were in control groups. Dr. Raichle’s laboratory routinely used the “rest condition” as a control rather than using, for example, a neutral task as a control for an emotional one.

At some point in our work, and I do not recall the motivation, I began to look at the resting state scans minus the task scans. What immediately caught my attention was the fact that regardless of the task under investigation, activity decreases were clearly present and almost always included the posterior cingulate and the adjacent precuneus. . . . Initially puzzled by the meaning of this observation, I began collecting examples from our work and placed them in a folder which I labelled [sic] MMPA for mystery medial parietal area.

Further analysis of data by Marcus Raichle and his colleagues led to the identification of a network of specific brain regions in which activity was anti-correlated with task-based activity no matter what the task was. This network was named the Default Mode Network (DMN) by Michael D. Greicius.

 The work of Raichle and others was consistent with the first published report of intrinsic resting state functional connectivity by Biswal and colleagues in 1995 that “functionally related brain regions exhibited correlation of low frequency fluctuations in the resting state.”

The importance of these discoveries has been far-reaching

Consider that previously, in task-based functional imaging studies, the challenge had been to find the signal within the experimental background “noise.” Now it had become clear that this “noise” was data. The fluctuating BOLD signal could be mathematically mined as a source of information about the intrinsic functional organization of the brain. Moreover, the data could be obtained relatively easily by placing a person in a scanner and instructing him or her to “rest” or to visually fixate on 1 spot: this made it possible to study some patients who had difficulty cooperating with other protocols.

Moreover, using functional connectivity did not require patient averaging. Subjects could be studied individually, making it possible to compare different individuals or 1 individual at different times. These advantages made the prospect of utilizing functional connectivity as a clinical tool more viable.

For researchers, “. . . functional brain connectivity . . . [had] become one of the most influential concepts in modern cognitive neuroscience, especially given the current shift in emphasis from studies of functional segregation to studies of functional integration.”

 We had long appreciated that detailing the synapse-to-synapse, structural organization of the brain would not capture the brain’s vast neuronal networks at work, operating as a dynamic system at speeds that would support the myriad manifestations of complex human behavior. Now “. . . task-free analysis of intrinsic connectivity networks may help elucidate the neural architectures that support fundamental aspects of human behavior.”

What neuroscience has learned from studies of functional connectivity

The DMN is only one of numerous large-scale, intrinsically synchronized, dynamic and interacting, functionally organized networks in the brain. These intrinsic functional networks and important nodes or hubs in those networks are consistent with synaptic maps of the brain. In other words, these networks do not violate our previous understanding of the anatomical organization of the brain into systems for motor behavior, perception, cognition, and so on.

The intrinsic functional networks can be found during cognitive tasks and in the rest condition, even when the systems for motor behavior, perception of various kinds, cognition, etc, are not being consciously engaged. Indeed, these networks persist during sedation, sleep, and under anesthesia.

While the intrinsic functional networks agree with earlier understanding of anatomical organization, the networks are not restricted to neuroanatomical regions with single synapse connections. The astounding degree of structural neural-network complexity in the brain likely explains how regions of the brain might be “functionally connected” even when their “structural connections” are not clear.

There is rapid coordination and interaction among the intrinsic brain networks and their hub regions. The brain is constantly switching connectivity patterns and reorganizing according to demands of the moment. Although the brain is a massively complex dynamic system, it can be studied by utilizing advanced imaging techniques and innovative mathematical and computational approaches. The importance of collaboration between experts in different fields cannot be overstated.

The most studied networks that relate to cognition are the Central Executive Network (CEN), a Salience Network (SN), and the DMN. The rapid interplay of these and perhaps other networks underpins behavioral changes that are based on the individual’s homeostatic needs, given that conditions (both internal and external) shift rapidly. The CEN is most active during cognitive tasks. The SN is activated in response to salient stimuli and plays a role in emotional processing and in switching from the DMN to the CEN. These networks are found in everyone; however, there is individual variation in features such as the strength of connectivity within each network.

The most far-reaching question we posed was whether regional functional connectivity within the salience and executive-control networks in the task-free setting would correlate with subject attributes measured outside the scanner. In other words, do individual differences in intrinsic connectivity strength correlate with how one feels and thinks in daily life?

This idea has been used to look at a large variety of traits and conditions. Indeed, individual variations in the coherence of these intrinsic networks appear to correlate with patient capabilities (eg, fluid intelligence, stressor-associated anticipatory anxiety, executive task performance).

 Should studies confirm that variations in functional connectivity are reliable indicators of specific behavioral variations outside the scanner, the potential clinical uses of this technology are staggering.

Theoretically, the mechanisms by which genetic variation, maturation, and experience affect an individual may be understood within this paradigm of intrinsic functional network organization in the brain. Early variations in neural development as well as experiences over time have an impact on synaptic strength and network functioning; these individual variations, in turn, have far-reaching effects on information processing within these networks over a lifetime.

Functional networks are differentially affected in various disease states. This has been intensively studied in the neurodegenerative diseases. There is mounting evidence, for example, that the pattern of disruption found in the coherence of various intrinsic brain networks is different for Alzheimer disease than for behavioral variant frontotemporal dementia.

Many psychiatric conditions have also been studied using functional connectivity approaches, including autism spectrum disease, PTSD, ADHD, bipolar disorder, and others.

 However, the heterogeneity of these disorders has made them difficult to study.

In MDD, there appear to be changes in connectivity within nodes of the anterior and posterior sub-networks of the DMN and altered connectivity between these areas and the SN as well as the CEN. The anterior sub-network of the DMN is believed to be involved in emotional and self-referential processing while the posterior sub-network of the DMN is more involved in memory and consciousness. 

 that alterations in functional connectivity associated with MDD “. . . reflect a state of increased interaction between self-referential and emotional networks, and the dominance of negative self-referential over cognitive processing which corresponds to the clinical symptoms of depression.”

Some of the potential applications for functional connectivity in clinical situations include as an aid in diagnosing, measuring disease severity, providing prognostic information, or monitoring disease progress and treatment effectiveness. For psychiatry, functional connectivity studies may help to differentiate subtypes within heterogeneous populations for disorders such as depression or schizophrenia.

Some neuropsychiatric “mysteries” are being solved through functional connectivity studies. For example, how do single lesions (as from a stroke) in different parts of the brain produce similar, complex neuropsychiatric syndromes in different individuals? 

 were interested in this question as applied to the emergence of delusional misidentification syndromes after single lesions. Capgras syndrome is perhaps the best known of the delusional misidentification syndromes, exemplified by: “You look like my wife, but I know you are not my real wife; you are an imposter; my real wife is somewhere else.”

Darby found that the disparate lesions that had led to delusional misidentification were functionally connected to brain regions involved in familiarity assessment and in belief evaluation. This finding supports earlier theories about what goes wrong in delusional misidentification: first, the patient recognizes the individual or place but fails to experience that person or place as familiar; and second, there is a failure in “belief evaluation,” namely a failure to realize that it defies logic to believe that this is anything but the real person or place.

Extremely promising work by Emily S. Finn has shown that functional connectivity profiles are specific enough to distinguish individuals, including across different sessions in the scanner and across task and resting states.

 This identification of individuals is referred to as functional connectome fingerprinting. The ability to capture an individual’s uniqueness from data in the scanner is a truly remarkable achievement.

We have come a long way. It took centuries for the scientific world to understand the fundamentals of brain anatomy and neuro-cellular architecture. Even as progress was being made in mapping the brain’s neural circuitry, the goal of truly probing the complexity of human behavior felt like a distant star we would likely never reach. Yet, in the mere 25 years since MRI was first introduced into medicine, we have made astounding progress in probing the brain’s complexity. As psychiatrists, we feel a pressing need for new light to be shed on what goes wrong in mental disease. Powerful new scientific paradigms, advancing technology, and cross-discipline collaborations give us reason to be hopeful.

 Pawela C, Biswal B. Brain connectivity: a new journal emerges. 

The Intentional Brain: Motion, Emotion, and the Development of Modern Neuropsychiatry.

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Disconnexion syndromes in animals and man

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 Weinberger DR, Radulescu E. Finding the elusive psychiatric “lesion” with 21st-century neuroanatomy: a note of caution. 

 Fox MD, Greicius M. Clinical applications of resting state functional connectivity. 

 Raichle ME. The restless brain: how intrinsic activity organizes brain function. 

 Greicius MD, Krasnow B, Reiss AL, Menon V. Functional connectivity in the resting brain: a network analysis of the default more hypothesis. 

 Biswal B, Yetkin FZ, Haughton VM, Hyde JS. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. 

 Fingelkurts AA, Fingelkurts AA, KÃ¤hkÃ¶nen S. Functional connectivity in the brain-is it an elusive concept? 

 Seeley WW, Menon V, Schatzberg AF, et al. Dissociable intrinsic connectivity networks for salience processing and executive control. 

 Finn ES, Shen X, Scheinost D, et al. Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity. 

 Mulders PC, van Eijndhoven PF, Schene AH, et al. Resting-state functional connectivity in major depressive disorder: a review. 

 Darby RR, Laganiere S, Pascual-Leone A, et al. Finding the imposter: brain connectivity of lesions causing delusional misidentifications. 

Functional connectivity is a “rapidly developing scientific story.” And for psychiatrists, it is a story worth following.

Functional Connectivity: Probing the Brain’s Astounding Complexity

Every practicing psychiatrist has seen a patient whose presentation resembles Chad’s. Chad consulted me almost 2 decades ago, but I remember him well. It was a few months before his 60th birthday. He was “facing mortality” and thought he might be getting depressed. Chad complained of trouble concentrating and said that simple tasks like balancing his checkbook had become more difficult. His legal work no longer engaged him, and he was spending more time on the Internet.

Chad still enjoyed working in his garden and was busy preparing the flowerbeds for a late-summer celebration of his wedding anniversary. He dearly loved his wife, but he was living with a long-standing conflict. He had “always known” that he was gay, and he had kept this a secret for his entire marriage. Now that he was turning 60, he had regrets. It was in this context that he had discovered gay pornography on the Internet. He told me that he was “becoming addicted to the porn,” and that sometimes he even watched while in his law office.

The changes in Chad seemed psychologically understandable and, yet, I had a nagging feeling that this was not an ordinary depression or “late-in-life crisis.” Chad seemed to be lacking in motivation more than suffering from a depressive mood. I also worried that perhaps his judgment was becoming impaired. In other words, Chad was an almost 60-year-old man who was reflecting on his life, rethinking choices he had made, and feeling mildly depressed; but it was possible that, in addition, Chad had a covert medical condition such as a sleep disorder or perhaps an early dementia.

Psychiatrists are the most intensively trained in the diagnosis of discrete, well-described medical/neurological conditions that might be masquerading as primary psychiatric disorders.

A medical work-up, including a neurology consultation, found no evidence of dementia. The patient’s symptoms were attributed to depression, and reassurance was recommended.

Chad stopped seeing me after 8 months. He felt somewhat better after talking about his life in psychotherapy and taking an SSRI. But his sexual preoccupations continued, and he planned to seek help from a psychologist who specialized in “sexual addiction.”

Chad’s story does not end well. He was suffering from a disease that would end his life, but it took 2 years of declining functioning before MRI evidence of his disorder became clear. Chad’s wife wrote to tell me that Chad had received a diagnosis of frontotemporal dementia (FTD). I always think of Chad when I learn of new findings about FTD. Much has been discovered about this disorder in the years since I saw him.

FTD is the second most common cause of dementia (after Alzheimer disease) in the population 

 The age of onset is usually between ages 45 and 65 but can range from 30 years to over 80. 

 is estimated to be about 15 to 22 per 100,000.

Chad had the most common subtype of FTD, now called the behavioral variant (bvFTD). Patients with bvFTD frequently present with psychiatric symptoms, often years before other features of the disease emerge.

 These individuals may look like they have late-onset major depression, psychosis, bipolar disorder, or OCD. Mental health professionals are very likely to be consulted, either by the patient or by family members. This, in and of itself, makes it important for psychiatrists to be familiar with FTD.

FTD is a brain disorder. But, in masquerading as what psychiatrists call primary psychiatric disorders, FTD challenges us to re-examine how we think about the relationship between “mental illness” and “brain disease.” Indeed, FTD inspires us to expand our knowledge-base and our clinical acumen into realms beyond the usual boundaries of our field.

In this article I will present a summary of what psychiatrists need to know about FTD. I have included summaries of case examples from the literature to convey the wide variety of possible psychiatric presentations of bvFTD.

In 1892, the Czech psychiatrist Arnold Pick described the first case of what would today be classified as a FTD. The term FTD actually refers to a large class of neurodegenerative disorders that vary in both clinical presentation and underlying pathology, but all of these disorders manifest with cortical degeneration in the frontal and temporal lobes.

Here: what psychiatrists need to know about frontotemporal dementia. Case examples convey the variety of possible psychiatric presentations of behavioral variant FTD. 

Barbara Schildkrout, MD

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