This presentation will present findings from studies based on Danish nationwide registers investigating the link between all treated infections and the risk of mental disorders. The studies were based on the entire Danish population (approximately 5.5million) and had detailed information on infections leading to hospital contacts and infections treated with anti-infective agents in the primary sector. The studies investigated the risk for severe mental disorders, ranging from childhood and adolescence mental disorders, affective disorders, schizophrenia, to suicidal behavior. Mechanisms potentially explaining the findings will be discussed and include direct effects of the infections and inflammatory processes on the brain, confounding aspects due to the observational study design, genetic factors or detrimental effects due to the anti-infective treatment.

Learning Objectives: 

1. Infections are associated with an increased risk of subsequent development of severe mental illness. 
2. These findings may be explained by direct and indirect effects of the infection on the brain, effects of the anti-infective treatment, genetics, or confounding factors due to the observational nature of our studies.

The immune system is linked to an increasing number of medical diseases, including lately also severe mental disorders. Hence, infections, autoimmunity and other immune responses could be involved in the pathogenesis of some patients with severe mental disorders.

Our large-scale epidemiological studies have consistently displayed that infections and autoimmune diseases increases the risk of developing severe mental disorders in a dose-response relationship, where the risk of severe mental disorders particularly increases with the amount of infections exposed to. It is a broad range of infections and autoimmune diseases that are associated with an increased risk of severe mental disorders, with the more severe infections increasing the risk the most. The risk of severe mental disorders is particularly increased with the temporal proximity to the infection. Furthermore, we have shown that the genetics for psychosis does not explain the association with infections but that the genetics and infections are additive risk factors for psychosis.  Moreover, at diagnosis there are elevated levels of inflammatory markers in the blood and studies on the cerebrospinal fluid surrounding the brain have shown some evidence for elevated immune markers in the brain and signs of disrupted blood-brain barrier in some of the patients, making them more vulnerable to potential detrimental effects of immune components. Our meta-analyses of randomized clinical trials have shown that anti-inflammatory treatment seems to be effective for depression and depressive symptoms and also for psychotic disorders in addition to antipsychotic treatment but intensive work is under way to identify subgroups that would be most likely to respond to anti-inflammatory add-on treatment, which might results in clinical impact.

Psychiatric symptoms can be directly triggered by infections reaching the brain, or be secondary to systemic inflammation indirectly affecting the brain through immune components, such as brain-reactive antibodies and cytokines. Nonetheless, shared genetic factor or other unmeasured environmental factors might account for some of this increased prevalence of immune-related diseases among individuals with psychosis; however, the common genetic variants associated with schizophrenia does not seem to increase the susceptibility for acquiring infections. Hence, a thorough differential diagnostic assessment of immune-related diseases, signs of neuroinflammation or other detectable physical diseases are of utmost importance in individuals with psychosis, particularly during onset of symptoms, to improve the psychiatric symptoms, survival rates and quality of life.

Learning Objectives: 

1. The association between infections and mental disorders
2. The association between autoimmune diseases and mental disorders

Batten disease or the Neuronal Ceroid Lipofuscinoses (NCLss) are each the result of inherited mutations that result in lysosomal dysfunction. Some of these disorders are due to deficiencies in lysosomal enzymes, while several others are the result of deficiencies in transmembrane proteins that are either directly or indirectly important for lysosomal function. An important step towards devising therapies for these fatal disorders is the characterization of animal models of NCL. These have been generated via gene manipulation or by identifying naturally occurring mutants that bear disease-causing mutations. These models have proved invaluable both for investigating disease mechanisms and testing how to deliver experimental therapies, and for assessing their efficacy. The majority of this work has been done in mice, but larger animal species with their more brains have proved especially important. We have been characterizing the onset and progression of neuropathological changes in multiple forms of NCL. This work has included identifying which brain regions and cell types are most affected, and their contribution to disease progression. Recently we have discovered that glia become dysfunctional in multiple forms of NCL, to the extent that they appear to harm neurons. However, how this happens differs markedly between forms of NCL. We have also recently identified spinal pathology in several NCLs, which contributes to disease outcome and also needs to be targeted therapeutically. Larger animal species are proving especially well suited for translating our work, with pre-clinical enzyme replacement studies in CLN2 deficient dogs in collaboration with BioMarin leading to a successful clinical trial, and the FDA approval of Brineura being the first treatment for any form of NCL. These studies highlight the importance of defining progressive neuropathological changes in informing the effective targeting of therapeutic approaches for the NCLs.

An actual way of understanding complex systems in psychology and psychiatry is by building mathematical models on the functioning of mental, behavioral, or neural systems (computational systems psychology). Applied to the field of psychotherapy, a newly developed model integrates available knowledge and empirical findings on the mechanisms of change. It formalizes circular causalities between order and control parameters into a set of nonlinear difference equations and shows how self-organized thresholds create critical instabilities and order-to-order transitions of dynamic patterns. The model explains many features of change dynamics which are known from psychotherapy research, e.g., sudden gains or losses. It can be validated by empirical time series data and allows for short term predictions of critical instabilities and perhaps also of the effects of interventions before these are applied in reality. Here we are at the crossroad of digitalization, personalization and complexity science on the way to intelligent systems in psychological medicine.

Internet- and app-based methods can be used for a continuous real-time monitoring of human change processes. One of these methods is the Synergetic Navigation System (SNS) which allows for the analysis and visualization of the assessed time series in real-time and by this provides substantial information on the dynamic features of human change processes, like dynamic complexity and critical instability, dynamic synchronization of treatment-related cognitions and emotions, phase-transitions between dynamic patterns and its precursors, and others. Therapists make use of these markers and features for continuous shared decision making together with their patients

The complex systems approach in psychiatry and psychology tries to integrate different levels of human functioning: the physiological level (e.g., brain dynamics), the mind (cognitions and emotions), behavior, and social interaction. An example will be provided how these levels can be investigated in a multi-level multi-methods project on psychotherapeutic change dynamics. The challenge is to integrate the different time scales of mind-brain dynamics (fMRI scans, immunological end endocrine parameters) and of the personal development during the whole period of psychotherapeutic treatment. The aim is to identify synchronized phase transitions in bio-psycho-social systems.

Late-onset Alzheimer’s disease (LOAD) is the most common form of dementia worldwide. To date, animal models of Alzheimer’s have focused on rare familial mutations, due to a lack of frank neuropathology from models based on common disease genes. Recent multi-cohort studies of postmortem human brain transcriptomes have identified a set of 30 gene co-expression modules associated with LOAD, providing a molecular catalog of relevant endophenotypes. This resource enables precise gene-based alignment between new animal models and human molecular signatures of disease. Here, we describe a new resource to efficiently screen mouse models for LOAD relevance. A new NanoString nCounter® Mouse AD Panel was designed to correlate key human disease processes and pathways with mRNA expression from mouse brains. Analysis of two mouse models based on LOAD genetics, carrying APOE4 and TREM2.R47H alleles, demonstrated overlaps with distinct human AD modules that, in turn, are functionally enriched in key disease-associated pathways. Comprehensive comparison with full transcriptome data from same-sample RNA-seq shows strong correlation between gene expression changes independent of experimental platform. Taken together, we show that the nCounter Mouse AD Panel offers a rapid, cost-effective and highly reproducible approach to assess disease relevance of potential LOAD mouse models.

Learning Objectives: 

1. Reproducibly screen potential LOAD mouse models to assess disease relevance
2. Understand design of a new resource, the Mouse AD Panel, to translate human disease processes and pathways to mouse models

The contemporary understanding of psychiatric disorders typically consists of a vast but often poorly interrelated set of facts and hypotheses that fail to coalesce into an integrated whole. This situation is due, in part, to the social dynamics in the scientific fields that study psychiatric disorders; it is, however, also due to the absence of rigorous theoretical tools that support the development of a more integrative understanding. This talk will show how theoretical tools from computational psychiatry can foster such integrative understanding, using Tourette syndrome (TS) as an illustrative example. Specifically, the talk will show how a computational understanding of the functions of dopamine, together with the likely nature of dopaminergic dysfunction in TS revealed in molecular-imaging studies, can provide an integrated understanding of the mechanisms of action of the various medications used to treat TS, the time course of the response to those medications, the findings of increased reward and habit learning in TS, and a vast array of functional and structural imaging findings in TS, while simultaneously explaining how and why tics arise and are expressed. This approach, combining formal rigor with substantial explanatory and predictive power, holds the promise to bring to psychiatry what has undoubtedly been one of the key drivers of success in fields such as physics (and, indeed, in the remarkable development of our technological society).

Learning Objectives: 

1. Understand how computational models can be used as theoretical tools to provide rigorous, integrative accounts of psychiatric disorders.
2. Understand how a computational understanding of the functions of dopamine, considered in conjunction with the likely nature of dopaminergic disturbances in Tourette syndrome, provides a cohesive explanation for a very broad range of findings in Tourette syndrome.

Substantial evidence demonstrates that schizophrenia involves a dysregulated dopamine system, potentially driven by overactivity in the hippocampus. Postmortem studies of schizophrenia brains show a substantial loss of parvalbumin GABAergic interneurons in the hippocampus; loss of this neuron likely drives hippocampal hyperactivity and dysrhythmic activity, leading to an over-responsive dopamine system. Our studies suggest that when the hippocampus is hyperactive and dysrhythmic, the dopamine system is hyper-responsive to stimuli, which can underlie the resultant hallucinations and delusions. A major question is why there is interneuron loss in the hippocampus. Parvalbumin interneurons early in life are susceptible to damage due to stress. In a developmental disruption model of schizophrenia in the rat, we found that prepubertally these rats are more anxious, are hyper-responsive to stress, and show hyperactivity in the amygdala; furthermore relieving the stress early in life prevents the transition to “psychosis” in these rats. This suggests that schizophrenia susceptibility may be due to heightened sensitivity to the deleterious effects of stress. Indeed, multiple stressors given during this sensitive period to normal rats can lead to the schizophrenia phenotype. Moreover, elimination of the ability of the medial prefrontal cortex to regulate stress causes minor stressors to yield the schizophrenia phenotype.  In contrast, multiple stressors given to adult rats result in a phenotype resembling models of depression.  However, if the critical developmental period is first re-opened in the adult rat via histone decarboxylase inhibition, the same stressors now yield a schizophrenia phenotype.This leads to the intriguing possibility that genetic predisposition does not cause schizophrenia, but instead like the developmental disruption model causes the individual to be hypersensitive to the deleterious effects of stress. Moreover, stress susceptibility may be a common link in familial risk for schizophrenia and depression. Therefore, controlling stress early in life in susceptible individuals may be an effective means to prevent transition to schizophrenia later in life.

Learning Objectives: 

1. To understand how stress during adolescence can lead to pathological changes in the brain and the emergence of psychosis in the adult
2. To understand how alterations in different regions of the dopamine system can underlie pathophysiological changes in schizophrenia and depression
3. To understand why parvalbumin interneurons are particularly sensitive to the deleterious impact of stress during adolescence but not adulthood

The size and burden of mental illness should ideally prompt a strategy of preemption and early intervention. On the neuroscientific side, this leads to the question of brain mechanisms of risk and resilience for these common and disabling disorder. The social environment plays an especially important role in risk, but the impact on the brain is just coming into focus. In this presentation, we review emerging evidence that combines epidemiology, social psychology and neuroscience to identify neural mechanisms of social risk factors for mental illness. In doing so, we discuss existing evidence on the effects of common genetic risk factors in social neural pathways and outline the need for integrative approaches to identify the converging mechanisms of social environmental and genetic risk in brain. On the environmental side, we focus on exposures that have a presumed social component such as urbanicity, migration/refugee status and social status. We propose a specific risk and resilience circuit mediating these effects that links perigenual cingulate cortex to subcortical structures such as ventral striatum and amygdala as well as dorsolateral and anterior medial prefrontal cortex. Social risk factors have a converging impact on structure and function of key nodes in this circuits, while resilience factors strengthen it. Understanding this neurobiology is helpful in designing preventive strategies through a better understanding of specific exposures contributing to resilience.
 
Ref.: Tost, H., Champagne, F. A., & Meyer-Lindenberg, A. (2015). Environmental influence in the brain, human welfare and mental health. Nat Neurosci, 18(10), 1421-1431. doi:10.1038/nn.4108

Learning Objectives: 

1. Participants should be able to name three environmental risk factors for psychiatric disorders that have been related to the social environment and describe the risk increase associated with them
2. Participants should be able to describe a key neural system for environmental risk and it’s relationship to social stress.

Deep brain stimulation (DBS) is an established therapy for cardinal motor signs and medication-related complications in Parkinson’s disease (PD). Current DBS therapy is limited to “open-loop” neurostimulation: the neurostimulator cannot sense the brain signals nor the behavior it is modulating. It applies continuous pulse trains of fixed frequency, amplitude, pulse width, and pattern, and cannot adjust such parameters in response to neural activity, or the patient’s state of activity or behavior. It applies a one size fits all set of stimulation parameters no matter what the dominant symptom of the patient. Adaptive or closed-loop (cl)DBS uses real time physiological signals to inform the neurostimulator when and how to change stimulation, to provide optimal therapy and minimize adverse effects.  Successful subthalamic (STN) clDBS in PD will require discovery of patient specific neural and behavioral features (control variables) that reflect the disease, state of activity and/or dominant symptom, along with control policy algorithms that will change stimulation parameters in a manner that modulates the variable and improves motor function in a patient specific manner.  In this talk I will discuss our research into relevant neural and physiological signals that may be useful for clDBS for specific PD motor symptoms, and how we have used a dual threshold control policy algorithm based on patient specific therapeutic windows in the first feasibility studies on clDBS for PD using a fully implanted neurostimulator.

Plasticity in the brain is very extensive due to the brain’s parallel architecture and synaptic reorganization capabilities.   Because neuronal populations are typically in stable low energy minimums, it is limited under normal circumstances. This can be challenged, however, under extreme conditions. Brain stimulation is one such example.  By inhibiting active areas while rehabilitating others, electrical stimulation induces state changes in the neuronal networks.

With the objective to achieve more aggressive resection of brain tumors affecting eloquent areas, we subjected a group of 5 patients to prehabilitation.  This was achieved by progressively inhibiting cortical activity with high frequency stimulation via implanted subdural electrodes while the patients performed intensive exercise of affected functions over an average of 30 days. Functional MR showed the reorganization of cortical activity away from the stimulated area, with adjacent or even contralateral areas activated instead of the original ones. This allowed us to perform a more extended resection of the tumors without compromising the eloquent functions.

This procedure can be applied to additional pathologies affecting eloquent areas as well, such as epileptic foci or arteriovenous malformations. Importantly, the concept of associating cortical stimulation with rehabilitation has next level applications, for example to the recovery of lost functions after brain injury. The possibility to enhance weakened neuronal activity has been shown by pairing cortical stimulation with external physical rehabilitation with brain-machine interfaces in patients with motor deficit due to stroke. Possibilities of enhancement of plasticity by cortical stimulation are wide, although they may be limited by the existing neural networks supported by the white matter interconnections.

Actions are not mediated solely by cortical processes but rely on communication within basal ganglia-thalamocortical loops. Speech is one example, although how the basal ganglia participate in this uniquely human behavior is not clear. Recognizing that deep brain stimulation (DBS) surgery offers the only opportunity to directly measure neural activity in the human basal ganglia, we initiated studies to understand how speech information is encoded within the subthalamic nucleus (STN)-sensorimotor cortical network. Our team works with patients undergoing deep brain stimulation for movement disorders like Parkinson's disease and essential tremor. We established a novel experimental paradigm, where electrocorticography (ECoG) is recorded simultaneously with STN single unit activity and local field potentials (LFP), during DBS surgery in which patients are awake and speaking. We discovered that STN neuron activity is dynamic during speech production, exhibiting behaviorally-selective inhibition and excitation of separate populations of neurons. At the population level, we found that STN activity tracks with specific articulatory motor features and with gain adjustment in articulatory movements. In addition, our data suggest a role for the STN in speech planning, in that STN activity appears to be modulated prior to speech onset. The goal of this work is to build a neurobiological framework that allows the development of interventions to treat speech disorders involving the basal ganglia.

Deep brain stimulation (DBS) represents one of the major clinical breakthroughs in the age of translational neuroscience. In 1987, Benabid and colleagues demonstrated that high-frequency stimulation can mimic the effects of ablative neurosurgery in Parkinson's disease (PD), while offering two key advantages to previous procedures: adjustability and reversibility. Deep brain stimulation is now an established therapeutic approach that robustly alleviates symptoms in patients with movement disorders, such as Parkinson's disease, essential tremor, and dystonia, who present with inadequate or adverse responses to medication. Currently, stimulation electrodes are implanted in specific target regions of the basal ganglia-thalamic circuit and stimulation pulses are delivered chronically. Next-generation stimulation strategies will capitalize on recent advances in recurrent artificial neural networks to inspire intelligent neural prosthetics that learn when patients sleep, walk, speak or exhibit symptoms such as tremor or bradykinesia. This talk will give detailed insight into potential biomarkers and discuss neurosurgical and computational strategies, implementing advances in artificial intelligence, to further elevate the therapeutic potential of DBS by capitalizing on its modifiable nature. Development of intelligent aDBS, with an ability to deliver highly personalized treatment regimens and to create symptom-specific therapeutic strategies in real-time, could allow for significant further improvements in the quality of life for movement disorders patients with DBS that ultimately could outperform traditional drug treatment.

Neurotechnology promises a way to repair the damaged nervous system that requires a merger of neuroscience, engineering and clinical knowledge.  Brain Computer Interfaces can now read out the intention to move through a tiny brain interface connected to a computer. Algorithms, based on our understanding of brain activity can decode patterns of neural activity into useful action commands. These commands can already  operate computers for communication, robots to act as a surrogate arm, or even reanimate a paralyzed limb, allowing people to type or reach and grasp with their own arm and hand.  Decoding is possible because of years of inquiry into the way non-human primate brains encode complex movements, and sensors can function years in the brain because of neuroengineering advances made in animal research.   Despite these advances control by people with paralysis is slow and less dexterous than in a typical person, because we lack an adequate 'theory of brain function'  and optimal electrodes for sampling neural activity.  BCIs are not yet capable of home use because we need to create novel implantable, miniaturized processors that can communicate large amounts of information at high speed from the brain to the body or machines.  But these obstacles are being overcome as well.  As these advances emerge, we are moving towards reaching a vision where a person paralyzed from stroke, spinal cord or brain injury, or neurodegenerative diseases like ALS, will be able to resume everyday, independent life.  

Localizing and identifying neuronal patterns that generate pathological brain signals may assist with tissue resection and intervention strategies in patients with neurological and psychiatric diseases. Precise localization requires high spatiotemporal recording from populations of neurons while minimizing invasiveness and adverse events. We are developing a large-scale, high-density, organic material–based, conformable neural interface device (“NeuroGrid”) capable of simultaneously recording local field potentials (LFPs) and action potentials from the cortical surface. Following work on experimental animals, we have demonstrated the feasibility and safety of intraoperative recording with NeuroGrids in anesthetized and awake subjects. Highly localized and propagating physiological and pathological LFP patterns were recorded, and correlated neural firing provided evidence about their local generation. Application of NeuroGrids to brain disorders, such as epilepsy, may improve diagnostic precision and therapeutic outcomes while reducing complications associated with invasive electrodes conventionally used to acquire high-resolution and spiking data.

Noninvasive brain stimulation techniques are used in experimental and clinical fields for their potential effects on brain network dynamics and behavior. Transcranial electrical stimulation (TES) has gained popularity because of its convenience and potential as a chronic therapy. However, a mechanistic understanding of TES has lagged behind its widespread adoption. We demonstrate that in rodents and human cadaver brains, ~75% of scalp-applied currents are attenuated by soft tissue and skull. Using intracellular and extracellular recordings in rats, we find that at least 1 mV/mm voltage gradient is necessary to affect neuronal spiking and subthreshold currents. We designed an ‘intersectional short pulse’ (ISP) stimulation method to inject sufficiently high current intensities into the brain, while keeping the charge density and sensation on the scalp surface relatively low. We verify the regional specificity of this novel method in rodents; in humans, we demonstrate how it affects the amplitude of simultaneously recorded EEG alpha waves. Our combined results establish that neuronal circuits are instantaneously affected by intensity currents that are higher than those used in conventional protocols. We propose that validated models of current flow should inform study design and potential indirect effects (e.g., peripheral stimulation) should be investigated in more detail and further explored in experimental designs.

Systems neuroscience offers new and powerful conceptual frameworks for testing the fundamental brain mechanisms that support behavior. More recently, modern neurotechnologies with translational potential are also emerging, offering new ways to precisely measure and manipulate human brain function. The intersection of these two domains is poised to create a new science of the human brain, Human Brain Science, that will connect the moment-by-moment changes in activity of billions of neurons to our mental experience and behavior. In this talk, I will explore the intersection of translational neurotechnology and systems neuroscience. First, I will present our work studying the uniquely human faculty of speech, drawing on systems neuroscience paradigms first developed in non-human primates. I will then discuss translational neurotechnology, focusing on our work to develop high-resolution, flexible thin-film electrode arrays in non-human primates, and concluding with our on-going efforts to deploy thin-film electrode arrays to study and treat the human brain.

Stimulation of human visual cortex is known to elicit visual perceptions that could potentially be used for restoring artificial vision to individuals who have lost their vision due to non-cortical etiologies. Although there have been attempts to build brain stimulators for the visual cortex in the past, fully implanted, chronic cortical visual prostheses have remained theoretical until recently. The Orion Visual Cortical Prosthesis System, which is currently being tested in a clinical trial, is a new device that is intended to restore some functional vision to blind patients.

This is a five-year, prospective, non-randomized, single-arm early feasibility study (clinicaltrials.gov NCT03344848) of subjects who are bilaterally blind with bare light or no light perception due to non-cortical etiology. The main objectives are to evaluate the safety of placing and activating an electrode array on the medial surface of the occipital lobe in blind patients; to evaluate the functionality of the device; to perform research to study the nature of the vision provided by the Orion; and to obtain input for future device design. There are five subjects between two study centers.

The Orion System comprises an implant (consisting of an electronics package, receiving antenna, and an electrode array with 60 non-penetrating electrodes); glasses with a video camera; headwear containing a transmitting antenna; and a video processing unit (VPU). The video camera collects real-time visual information, which is then processed by the VPU and converted to stimulation patterns on the electrode array. A radio frequency link between the transmitting and receiving antenna sends data and power to the implant.
Four subjects have been implanted at UCLA, three males and one female. As of January 30, 2019, average implant duration was 9.8 months. Average age at time of implant was 50.3 years. Cause of blindness included trauma (burn), trauma (car accident), infection, and pediatric glaucoma. All subjects had bare or no light perception at the time of implant, but were previously sighted.
All subjects reports seeing phosphenes with stimulation through virtually all electrodes implanted. Stimulation parameters are within expected ranges and generally stable over time. Despite similar implant techniques, spatial maps vary by subject but are generally stable within subjects. The field of view is larger than that seen with retinal prosthetics. Early testing with light localization and direction of motion testing reveal the ability to detect motion in most subjects. Real world use has shown the ability to use the device to navigate the environment. One serious adverse event of seizure has been noted. Future work will focus on maximizing stimulation parameters and working with visual rehabilitation specialists to maximize utility.

This talk provides a brief overview of funding opportunities for invasive device development for translation to clinical populations supported by the NIH BRAIN Initiative.

The implications of NIH BRAIN research stretch beyond traditional medical and research contexts. This LabRoots session will present recent developments at the intersection of neuroscience and law, with a focus on the introduction of neuroscientific evidence in United States courtrooms. Brain evidence has played a role in landmark U.S. Supreme Court cases; is being regularly considered in many types of criminal and civil cases, and touches on issues such as lie detection, addiction, brain injury, memory, trauma, and more. There is much promise for neuroscience and law. For example brain science might allow: criminal law to reduce recidivism and treat offenders more humanely; tort law to better differentiate between those in real pain and those who are faking; and insurance law to more accurately and adequately compensate those with mental illness. Yet the promise of brain science must be balanced against the perils of premature and inappropriate uses. There is an imperative to determine proper standards for the ethical use of neuroscience in law.

After this session, participants will be able to: Appreciate the emerging field of neurolaw, and the many ways in which neuroscience might affect law; Understand the ways in which neuroscience is being proffered as evidence in criminal and civil contexts; Recognize basic concerns about the use of neuroscientific evidence in courtroom proceedings; and Discuss the promises and limitations of future uses of neuroscience in law.

Developing new diagnostic and therapeutic tools for brain disorders is an ethical imperative and conducting human research with neural devices is a key step towards achieving that goal. Conducting this research ethically is vital. Various actors in the field have asked for more guidance on how to ethically conduct human research with neural devices. This LabRoots session will focus on three specific ethical challenges: 1) analysis of risk, 2) obtaining informed consent, and 3) post-trial responsibilities to research participants. This talk is based on a workshop of the NIH BRAIN Initiative and draws on, specifies, and interprets existing ethical frameworks.  The aim is to provide ethical guidance for researchers, Institutional Review Boards (IRBs), funders, and others engaged in human neural device research.

The NIH BRAIN Initiative aims to develop new tools and neurotechnologies to transform our understanding of brain function in health and disease. That knowledge is critical to enable novel therapies for brain disorders, which cause immense suffering and have a major economic impact worldwide. Our ability to intervene medically is hampered by limited understanding of how brain circuits go awry in disorders such as dementia, chronic pain, addiction, and autism. The powerful technological advances catalyzed by the BRAIN Initiative will allow us to record and modulate brain circuit function in unprecedented ways, which will pose a number of ethical questions. Neuroethics is essential for the success of the NIH BRAIN Initiative, and for neuroscience research more broadly, because it enables advance consideration of the ethical, legal, and societal implications of neuroscience research. This facilitates progress in neuroscience and helps ensure that neuroscientific advancements support human well-being. From its inception the NIH BRAIN Initiative has made a concerted effort to integrate neuroethics into its science. Integrating neuroethics into the Initiative serves the interests of all involved stakeholders, and requires collaborative input from many disciplines – neuroscience, medicine, bioethics, philosophy, law, and others. This talk will present a brief introduction to neuroethics and an overview of the NIH BRAIN Initiative’s neuroethics strategy and program, including funding for neuroethics research.

Neurological disorders present a worldwide multi-factorial burden. They affect as many as one billion people globally - and that number is predicted to increase in the next decades. The wide-range effects of this problem are both pervasive and staggering. As such, we are ethically compelled to carefully consider and address this crisis. Unfortunately, the biological basis of dysfunction for these disorders is largely unknown; furthermore, the diagnosis for psychiatric disorders remains subjective.

The development of new neurotechnologies can offer both therapeutic relief and the opportunity to better understand the underlying pathomechanisms of dysfunction. Deep brain stimulation (DBS) is a relatively new therapy which has enjoyed successful application and approval for several neurological disorders.  It is suggested that DBS substantially reduces refractory symptoms in these disorders via the modulation of dysregulated networks. This theory is supported by the reports of correlation between improved symptomatology and the observed changes in synchronization of oscillatory rhythms. Although these data consequently suggest an important role for oscillatory rhythms, the scope of these rhythms in the pathological network and the mechanism(s) which exact their modification in the improved disease state has not been elucidated. Such information would bear directly on the important issues, including that of target selection and the quest for biomarkers. Therefore, DBS serves as a powerful tool to better understand the neurodynamics of systems level dysfunction subserving neuropsychiatric disorders.

While DBS can provide therapeutic benefit in otherwise treatment-refractory cases, it is not without risk and must be a carefully considered option. Several ethical issues must be deliberated, including risk v. benefit, age, post-surgical follow-up, and patient profile.

This presentation will address both the opportunities that DBS offers as well as the ethical challenges that are inherent in the determination of candidacy for and application of DBS. Gilles de la Tourette syndrome will be the model used to express such variables.

Humans have a remarkable ability to flexibly interact with the environment. A compelling demonstration of this cognitive flexibility is our ability to perform complex, yet previously un-practiced tasks successfully on the first attempt. We refer to this ability as ‘ad hoc self-programming’: ‘ad hoc’ because these new behavioral repertoires are cobbled together on the fly, based on immediate demand, and then discarded when no longer necessary; ‘self-programming’ because the brain has to configure itself appropriately based on task demands and some combination of prior experience and/or instruction. This type of learning differs importantly from trial-and-error learning, in which responses are sculpted incrementally, based on feedback from previous attempts. In comparison to trial-and-error learning, much less is known about ad hoc self-programmed learning, but it clearly represents a fundamental feature of human intelligence. The overall goal of our research proposal is to understand the neurophysiological and computational basis for ad hoc self-programmed behavior. To do so, we leverage critical advances in neuroscience, neurosurgery, engineering, and computational modelling, including: 1) availability of a large-scale recording platform enabling simultaneous recordings of 100+ neurons from the cortical surface; 2) opportunities to record from lateral prefrontal cortex (lPFC) in human subjects engaged in a custom-designed behavioral task; 3) developments borrowed from the artificial intelligence community to create advanced neural network models of complex cognitive processes.

We expect that this innovative approach will revolutionize our understanding of this amazing capacity for immediate, configurable learning that characterizes our everyday lives. In doing so, we will develop new strategies to study mechanisms of rapid, flexible cognitive control in general. A better understanding of human cognitive control and its nuanced capacities will naturally translate into an appreciation of deficiencies in these processes, and how they manifest in the form of neuropsychiatric disorders. This appreciation can then lead to the development of rational, targeted therapies.

Humans interact with their environment in countless ways and can switch seamlessly between activities. Even for seemingly simple tasks, a variety of sensory inputs and contextual cues are integrated to create a motor plan to complete a task. In our work, we manipulate aspects of task context to study sensorimotor processing during grasping and object exploration tasks. Our experiments are conducted as part of an ongoing effort to develop intracortical-brain computer interface (BCI) devices for people with paralysis. This experimental paradigm allows us to study sensorimotor processing during complex tasks, which will ultimately lead to the development of improved neuroprosthetics. Study participants use the BCI to control a robotic arm and hand, which allows us to precisely control the mapping between neural activity and movement as well as the somatosensory inputs. Previous work supports the idea that neural activity generated during attempted movements in people with spinal cord injury exhibits the same relationship to movement variables as an able-bodied subject. Similarly, stimulation of somatosensory cortex in a person with chronic tetraplegia generates localized sensations that follow the expected spatial organization.

I will provide an overview of our approach to controlling a motor BCI, which is based on an understanding of motor cortical activity measured in non-human primates during overt reaching and grasping behavior. I will also discuss a primary motivation for our current work that is investigating the influence of task context on motor control. We observed that that motor cortical activity is fundamentally different when reaching to and grasping an object, versus reaching with identical kinematics in an empty workspace. In more recent experiments, we have focused on the motor control of grasping.  We have observed encoding of implicit grasp force representations associated with familiar objects at particular phases of object grasping and transport movements. Additionally, even when explicit force targets are instructed, we see transient periods of motor cortical activity that are most informative about grasp force control. Overall, our experiments have shown the motor cortical activity is dependent on the context of a task and is not simply communicating a task-invariant motor plan to the upper limb.  

The rapid formation of new memories and the recall of old memories to inform decisions is essential for human cognition, but the underlying neural mechanisms remain poorly understood. We utilize the opportunity to record in-vivo from human single neurons simultaneously in multiple brain areas in patients undergoing treatment for drug resistant epilepsy to study the underlying mechanisms. Supported by the BRAIN initiative, we formed a consortium among four institutions (Cedars-Sinai/Caltech, Johns Hopkins, U Toronto, and Children’s/Harvard) to maximize to use of these rare and precious opportunities for science. 

We are developing a circuit-level understanding of human memory by utilizing invasive in-vivo recordings together with behavior, focal electrical stimulation, and computational modeling. In this talk, I will provide a scientific overview that motivates the hypothesis we are exploring in this ongoing work.  I will describe a putative circuit for human recognition memory composed of cells in the medial temporal lobe (MTL), and the medial frontal cortex (MFC). In the MTL, this putative circuit is composed of two functional cell types, visually-and memory selective neurons, whose interaction is mediated by theta oscillations. Visually-selective neurons are tuned to high-level concepts, are sensitive to attention, and their activity forms attractors through persistent activity over several seconds while stimuli are held in working memory. Memory-selective neurons, on the other hand, signal whether a stimulus is novel or familiar, a property that changes after a single learning trial. In the MFC, on the other hand, memory-based choice cells represent a putative readout of memories to support memory-based recognition and confidence decisions. Together, these results begin to provide a circuit-level understanding of human memory at a level of detail that is needed for the development of new treatments for memory disorders.

The human brain has a remarkable ability to store and retrieve information. Detailed memories can be formed after as little as one exposure, and those memories can be retained for decades. Importantly, recent studies have demonstrated the critical role of a mental “schema”, or a learned cognitive structure, in supporting rapid memory formation. In essence, previously acquired knowledge provides a framework that shapes how ongoing experience is perceived and remembered. This resonates with the older idea from neuropsychology of “learning to learn” as a mechanism by which rapid learning might be accomplished. Learning to learn is thought to facilitate new learning by reducing the dimensionality of the space that the organism has to search to adapt to novel problems. The development of a schema that supports this kind of rapid learning is thought to involve interactions between the hippocampus and the neocortex. However, the neural circuitry that underlies this kind of rapid, one-trial, learning is not well-understood.

Here, using innovative techniques for large-scale recordings in monkeys and in human epilepsy patients, we capitalize on the unique opportunity to establish cross-species comparisons of hippocampal-neocortical interactions. We record single unit activity as well as the local field potential from homologous brain areas in humans and monkeys, and we investigate this neural activity as humans and monkeys perform identical behavioral tasks of rapid learning and schema formation. In parallel, computational modeling and theoretical work provides an important iterative loop for evaluating our experimental hypotheses. Recently, advances in the modeling of recurrent neural networks provide a very promising framework within which to interpret the kind of complex data we will be gathering. By training artificial networks to perform the same tasks as our experimental subjects, these learned dynamics serve as a plausible network implementation of the cognitive computation.  We can then examine these networks to discover the hidden dynamical structure of these computations, and to develop hypotheses for how the biological network may implement them. The overall goal of this U-19 Program is to develop a comprehensive theory of the circuit mechanisms that underlie the human brain’s ability to establish neural frameworks that enable rapid new learning.

Joshua Gordon, M.D., Ph.D., Director of the National Institute of Mental Health, will provide an overview of challenges and opportunities in mental health research. Dr. Gordon will present emerging approaches and technologies, and future directions for this multidisciplinary field that the BRAIN initiative has afforded. In this era of unprecedented opportunity, Dr. Gordon will highlight the importance of cross-disciplinary, integrative approaches to address the vast complexities associated with mental illnesses as we move closer to our goal of finding effective treatments and therapies.