Neural Circuit Level Research Articles

Hippocampal Network Connectivity and Activation Differentiates Post-Traumatic Stress Disorder From Generalized Anxiety Disorder

Anxiety disorders are a diverse group of clinical states. Post-traumatic stress disorder (PTSD) and generalized anxiety disorder (GAD), eg, share elevated anxiety symptoms, but differ with respect to fear-related memory dysregulation. As the hippocampus is implicated in both general anxiety and fear memory, it may be an important brain locus for mapping the similarities and differences among anxiety disorders. Anxiety and fear also functionally associate with different subdivisions of the hippocampus along its longitudinal axis: the human posterior (rodent dorsal) hippocampus is involved in memory, through connectivity with the medial prefrontal-medial parietal default-mode network, whereas the anterior (rodent ventral) hippocampus is involved in anxiety, through connectivity with limbic-prefrontal circuits. We examined whether differential hippocampal network functioning may help account for similarities and differences in symptoms in PTSD and GAD. Network-sensitive functional magnetic resonance imaging-based resting-state intrinsic connectivity methods, along with task-based assessment of posterior hippocampal/default-mode network function, were used. As predicted, in healthy subjects resting-state connectivity dissociated between posterior hippocampal connectivity with the default-mode network, and anterior hippocampal connectivity to limbic-prefrontal circuitry. The posterior hippocampus and the associated default-mode network, across both resting-state connectivity and task-based measures, were perturbed in PTSD relative to each of the other groups. By contrast, we found only modest support for similarly blunted anterior hippocampal connectivity across both patient groups. These findings provide new insights into the neural circuit-level dysfunctions that account for similar vs different features of two major anxiety disorders, through a translational framework built on animal work and carefully selected clinical disorders.

The application of nonlinear Dynamic Causal Modelling for fMRI in subjects at high genetic risk of schizophrenia

Nonlinear Dynamic Causal Modelling (DCM) for fMRI provides computational modelling of gating mechanisms at the neuronal population level. It allows for estimations of connection strengths with nonlinear modulation within task-dependent networks. This paper presents an application of nonlinear DCM in subjects at high familial risk of schizophrenia performing the Hayling Sentence Completion Task (HSCT). We analysed scans of 19 healthy controls and 46 subjects at high familial risk of schizophrenia, which included 26 high risk subjects without psychotic symptoms and 20 subjects with psychotic symptoms. The activity-dependent network consists of the intra parietal cortex (IPS), inferior frontal gyrus (IFG), middle temporal gyrus (MTG), anterior cingulate cortex (ACC) and the mediodorsal (MD) thalamus. The connections between the MD thalamus and the IFG were gated by the MD thalamus. We used DCM to investigate altered connection strength of these connections. Bayesian Model Selection (BMS) at the group and family level was used to compare the optimal bilinear and nonlinear models. Bayesian Model Averaging (BMA) was used to assess the connection strengths with the gating from the MD thalamus and the IFG. The nonlinear models provided the better explanation of the data. Furthermore, the BMA analysis showed significantly lower connection strength of the thalamocortical connection with nonlinear modulation from the MD thalamus in high risk subjects with psychotic symptoms and those who subsequently developed schizophrenia. These findings demonstrate that nonlinear DCM provides a method to investigate altered connectivity at the level of neural circuits. The reduced connection strength with thalamic gating may be a neurobiomarker implicated in the development of psychotic symptoms. This study suggests that nonlinear DCM could lead to new insights into functional and effective dysconnection at the network level in subjects at high familial risk.

CREB and neuronal selection for memory trace

Despite considerable progress over the past several decades, our understanding of the mechanisms underlying memory encoding, storage, and expression in a complex neural network are far from complete. In particular, how some neurons rather than others are selectively engaged to encode memory remains largely unknown. Using virus-mediated gene delivery into a small subset of neurons in a given network, molecular imaging of neuronal activity, pharmacological perturbation of specific neurons' activity and animal behavior assays, recent studies have begun to provide insight into molecular and cellular mechanisms responsible for the selection of neurons for inclusion into a memory trace. Here, we focus on a review of recent findings supporting the hypothesis that the level of the transcription factor CREB (cAMP/Ca2+-response element binding protein) is a key factor governing which neurons are recruited to a given memory trace. These recent findings open a new perspective on memory trace at the neural circuit level and also raise many important questions. Future studies employing more advanced neurobiological techniques for targeting defined populations of neurons and manipulating their activity in time and space in a complex neural network will give answers to these newly emerging questions and extend our understanding of the neurobiological basis of the memory trace.

Brain Enabled by Next-Generation Neurotechnology: Using Multiscale and Multimodal Models

As many articles in this issue of IEEE Pulse demonstrate, interfacing directly with the brain presents several fundamental challenges. These challenges reside at multiple levels and span many disciplines, ranging from the need to understand brain states at the level of neural circuits to creating technological innovations to facilitate new therapeutic options. The goal of our multiuniversity research team, composed of researchers from Stanford University, Brown University, the University of California at San Francisco (UCSF), and the University College London (UCL), is to substantially elevate the fundamental understanding of brain information processing and its relationship with sensation, behavior, and injury. Our team was assembled to provide expertise ranging from neuroscience to neuroengineering and to neurological and psychiatric clinical guidance, all of which are critical to the overarching research goal. By employing a suite of innovative experimental, computational, and theoretical approaches, the Defense Advanced Research Projects Agency (DARPA) Reorganization and Plasticity to Accelerate Injury Recovery (REPAIR) team has set its sights on learning how the brain and its microcircuitry react (e.g., to sudden physiological changes) and what can be done to encourage recovery from such (reversible) injury. In this article, we summarize some of the team's technical goals, approaches, and early illustrative results.

The Developing Human Brain: A Frontiers Research Topic

The field of developmental cognitive neuroscience (DCN) examines how the human brain and behavior change over the lifespan, in particular over infancy, childhood, and adolescence. DCN researchers conduct basic research on typical brain development, and/or research on pediatric populations with neurodevelopmental disorders. Developmental cognitive neuroscience is not child's play – it is a complex and challenging, but exciting, area of research. It is highly multidisciplinary, in that it builds on the fields of developmental, cognitive, affective/social, and clinical psychology and neuroscience. DCN research also relies on advances in computer science, physics, and mathematics. Increasingly, as we learn more about the developing human brain, findings from DCN have strong implications for medicine, education, law, public health, and social welfare. The story of this compendium begins with a highly successful conference on neurocognitive development held at UC Berkeley in 2009 – a 3-day event with over 200 attendees and over 60 scientific presentations from around the United States and Europe. I thank Brian Meyer, a graduate student in Psychology at UC Berkeley, for helping me to organize this conference. Following on the heels of this conference, postdoctoral fellow Dr. Elizabeth O'Hare and I solicited submissions to a special issue of Frontiers in Human Neuroscience focused on the developing human brain. Dr. O'Hare deserves my gratitude for helping to handle the peer review of these submissions. This Research Topic includes a selection of empirical and review papers from top DCN researchers, organized into six interrelated sections. Section I examines how our visual and auditory systems develop to support the perception of complex stimuli. Recent DCN research highlights the point that, contrary to common belief, perceptual development is not complete after the first few years of life. Face processing – both the recognition of individuals and of specific emotions – is a particularly challenging problem for the visual system, and continues to improve through adolescence. Section II extends the theme of Section I by exploring in more detail the perception of faces, which is critical for social functioning. This section ends with the exploration of deficits in social functioning after pediatric brain injury, which serves as a bridge from studies of perception to studies of action. Section III examines two key neural changes that underlie shifts in behavior over development. The first is a change in the processing of rewards and feedback, which are powerful motivators of behavior. The second is a change in the ability to control behavioral responses, known as cognitive control or executive function, or more generally as self-regulation. Developmental cognitive neuroscience researchers have begun to use sophisticated network analysis tools to examine developmental changes in the strength of interactions between brain regions in large-scale networks. Section IV explores how these brain networks are influenced by common genetic variation or by the presence of a disorder with a strong hereditary component. Section V features a relatively new area of research within DCN: the exploration of societal influences on brain development. Two of the papers in this section compare neurocognitive function in children from North American and Chinese families. The other two papers review what is known currently about the influences of childhood adversity and socioeconomic status on brain development. Finally, Section VI showcases several new ways of thinking about, and studying, the developing human brain. The first paper is an opinion piece highlighting the relevance to DCN of research at the level of neural circuits. The second paper shows how we can go beyond conventional fMRI imaging analyses to examine changes in brain function at a finer grain using multivariate pattern classification algorithms. In conclusion, this compendium shows us both where the field of DCN is currently, and where it is headed. The advances over the last few years have been breathtaking – and the best is yet to come.

A zebrafish model of glucocorticoid resistance shows serotonergic modulation of the stress response

One function of glucocorticoids is to restore homeostasis after an acute stress response by providing negative feedback to stress circuits in the brain. Loss of this negative feedback leads to elevated physiological stress and may contribute to depression, anxiety, and post-traumatic stress disorder. We investigated the early, developmental effects of glucocorticoid signaling deficits on stress physiology and related behaviors using a mutant zebrafish, grs357, with non-functional glucocorticoid receptors (GRs). These mutants are morphologically inconspicuous and adult-viable. A previous study of adult grs357 mutants showed loss of glucocorticoid-mediated negative feedback and elevated physiological and behavioral stress markers. Already at 5 days post-fertilization, mutant larvae had elevated whole body cortisol, increased expression of pro-opiomelanocortin (POMC), the precursor of adrenocorticotropic hormone (ACTH), and failed to show normal suppression of stress markers after dexamethasone treatment. Mutant larvae had larger auditory-evoked startle responses compared to wildtype sibling controls (grwt), despite having lower spontaneous activity levels. Fluoxetine (Prozac) treatment in mutants decreased startle responding and increased spontaneous activity, making them behaviorally similar to wildtype. This result mirrors known effects of selective serotonin reuptake inhibitors (SSRIs) in modifying glucocorticoid signaling and alleviating stress disorders in human patients. Our results suggest that larval grs357 zebrafish can be used to study behavioral, physiological, and molecular aspects of stress disorders. Most importantly, interactions between glucocorticoid and serotonin signaling appear to be highly conserved among vertebrates, suggesting deep homologies at the neural circuit level and opening up new avenues for research into psychiatric conditions.

Connectomic disturbances in schizophrenia

Event Abstract Back to Event Connectomic disturbances in schizophrenia Alex Fornito1, 2* 1 University of Melbourne, Melbourne Neuropsychiatry Centre and Centre for Neural Engineering, Australia 2 NICTA Victorian Research Laboratory, Australia Accumulating evidence indicates that schizophrenia is not caused by focal pathology in a single, specific brain region. Rather, it arises from disordered interactions within and between distributed neural circuits. In other words, it is a disorder of brain connectivity. A great deal of insight into the pathophysiology of the disorder can therefore be gained from recent attempts to map the human connectome–the complete set of neural elements and connections comprising the brain. This talk will overview some of the basic concepts and methods of the burgeoning field of human connectomics and illustrate how these techniques can be used to characterize disruptions at either the level of specific neural circuits or the entire brain in patients with schizophrenia. Many of these changes have a genetic basis, suggesting that they represent viable risk biomarkers for the disorder. Keywords: Schizophrenia, brain imaging, connectomics, biomarkers, brain connectivity Conference: ACNS-2012 Australasian Cognitive Neuroscience Conference, Brisbane, Australia, 29 Nov - 2 Dec, 2012. Presentation Type: Symposium Presentation Topic: Other Citation: Fornito A (2012). Connectomic disturbances in schizophrenia. Conference Abstract: ACNS-2012 Australasian Cognitive Neuroscience Conference. doi: 10.3389/conf.fnhum.2012.208.00009 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 17 Oct 2012; Published Online: 26 Oct 2012. * Correspondence: Dr. Alex Fornito, University of Melbourne, Melbourne Neuropsychiatry Centre and Centre for Neural Engineering, Melbourne, Australia, fornitoa@unimelb.edu.au Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Alex Fornito Google Alex Fornito Google Scholar Alex Fornito PubMed Alex Fornito Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

The future of schizophrenia pharmacotherapeutics: Not so bleak

Chlorpromazine efficacy in schizophrenia was observed 60 years ago. Advances in pharmacotherapy of this disorder have been modest with effectiveness still limited to the psychosis psychopathology and mechanism still dependent on dopamine antagonism. While a look backward may generate pessimism, future discovery may be far more robust. The near future will see significant changes in paradigms applied in discovery. Rather than viewing schizophrenia as a disease entity represented by psychosis, the construct will be deconstructed into component psychopathology domains. Each domain will represent a clinical target for aetiologic and therapeutic discovery. Research on pathophysiology will shift to the neural circuit level in relation to specific behavioural constructs. Progress at the molecular, genetic, cellular and network levels will be more robust. The behavioural paradigm will map on to the deconstructed clinical paradigm and in the process discovery will cut across current classification boundaries.

Mechanisms of gene-environment interaction in schizophrenia

Environmental factors and both common and rare genetic variants increasing risk for schizophrenia are being discovered, but the neural mechanisms that mediate their impact are only now coming into focus. We discuss work from a translational genetics approach, with a focus on neuroimaging, delineating mechanisms of genetic risk through interaction of prefrontal cortex with striatum, midbrain and hippocampus. Using social status as an example, we identify dissociable neural responses to perceived social rank using functional magnetic resonance imaging (fMRI) in an interactive, simulated social context. In both stable and unstable social hierarchies, viewing a superior individual differentially engaged perceptual-attentional, saliency, and cognitive systems, notably dorsolateral prefrontal cortex. In the unstable hierarchy setting, additional regions related to emotional processing (amygdala), social cognition (medial prefrontal cortex), and behavioral readiness were recruited. Furthermore, social hierarchical consequences of performance were neurally dissociable and of comparable salience to monetary reward, providing a neural basis for the high motivational value of status. Finally, we discuss GEI impacting on these circuits, with a focus on validating epidemiologically identified GEI on the neural circuit level.

Biophysical Characterization Of Duloxetine Activity On Voltage-gated Sodium Channels Involved In Pain Transmission

Duloxetine, an inhibitor of the serotonin-norepinephrine reuptake system, is widely used for the treatment of major depression and has also been found to be effective in reducing neuropathic pain. This latter effect is believed to be related to the role of the two neurotransmitters in inhibiting pain signals at the level of spinal and supraspinal neural circuits. However the possibility that duloxetine also acts through alternative mechanisms has not yet been investigated. In this study we focused on the potential effect of duloxetine on neuronal isoforms of voltage-gated sodium channels (NaV1.3 and NaV1.7) that have a pivotal role in the generation and propagation of pain signals. Conventional whole-cell patch-clamp recordings were performed on CHO-cells expressing hNaV1.3 and hNaV1.7. Duloxetine exerted a concentration-dependent resting block, measured by the reduction of the sodium current elicited by a single depolarizing step from -100mV to 0mV for 10 ms, with IC50 values of 5 and 16 microM for NaV1.3 and NaV1.7, respectively. These values were halved at holding potentials that reduce channel availability of both channels by 50%, indicating a preference for the inactivated state of sodium channels. Furthermore we observed that 10 microM duloxetine induced a 10mV negative shift of the steady state inactivation curves, and preliminary results indicate that this effect is correlated with stabilization of slow inactivation. Finally, for both sodium channel isoforms, an additional 20% inhibition over the resting block was observed at concentrations close to the IC50 when the stimulation frequency was increased up to 10Hz. Thus, the antidepressant duloxetine exhibits most of the state-dependent mechanisms of a classic sodium channel blocker. These results may add valuable information about the pharmacological spectrum of duloxetine, an issue of high clinical impact considering its increasingly widespread use.

Seasonal changes in brain serotonin transporter binding in short 5-HTTLPR-allele carriers but not in long-allele homozygotes

AbstractSeveral findings suggest seasonal variations in the serotonin (5-HT) system. We sought evidence for seasonal variation in the serotonin transporter (5-HTT). We found that length of daylight time in minutes correlates negatively with 5-HTT binding in the putamen and the caudate, with a similar tendency in the thalamus, but no such association in the midbrain. In the putamen, an anatomical region with a dense serotonin innervation that is implicated in processing of aversive stimuli, we found a significant gene*daylight effect with a negative correlation between the 5-HTT binding and daylight time in carriers of the short 5-HTTLPR allele, but not in carriers of the long allele. The neurobiological endophenotype identified here directly links activation studies, showing responses on the neural circuit level, with dynamic changes in transporter expression measured in vivo.

Commentary] CAN REPLACEMENT THERAPY WORK IN THE TREATMENT OF COCAINE DEPENDENCE? AND WHAT ARE WE REPLACING ANYWAY?

Commentary] CAN REPLACEMENT THERAPY WORK IN THE TREATMENT OF COCAINE DEPENDENCE? AND WHAT ARE WE REPLACING ANYWAY?

Which Brain Research Can Educators Trust?

Neurological research has discovered much about how the brain works, Dr. Willis writes. But educators need to be cautious when applying this research to teaching. ********** IN 1681 Thomas Willis coined the term And 300 years later I began my practice of child and adult neurology. When I subsequently moved into teaching, I found that the tools of neuroimaging, which show the brain actively processing information, helped me make connections between classroom strategies and neuroscience. Let me begin with a brief explanation of the three most important technological advances in brain research: Positron Emission Tomography (PET), Functional Magnetic Resonance Imaging (fMRI), and Quantitative Encephalography (qEEG). PET relies on the fact that the brain is extremely hungry for glucose and oxygen. PET scans measure the burning of glucose in the brain. In this technique, positron-emitting isotopes, which function as radioactive tracers, are injected into the arteries in combination with glucose. The rate at which specific regions of the brain metabolize the glucose is recorded while the subject is engaged in various sorts of cognitive activities. These recordings are then used to produce maps of areas of high brain activity during particular cognitive functions. A similar technology is employed in fMRI. However, fMRI takes advantage of a special property of hemoglobin, a blood protein that brings oxygen to body tissues. Hemoglobin that is carrying oxygen differs from hemoglobin that is not carrying oxygen. Active regions of the brain receive more blood and thus more oxygen than less-active regions. By detecting oxygen-containing hemoglobin, scientists use fMRI to assess changes in blood flow, and thereby metabolic activity, in specific areas of the brain while subjects are engaged in various activities. Finally, qEEG or brainwave monitoring provides brain-mapping data that are based on the very precise localization of brainwave patterns coming from the parts of the brain that are actively engaged in the processing of information. Through digital technology, qEEG records electrical patterns at the surface of the scalp that represent cortical electrical activity or brainwaves; qEEG recording as it is used in learning research measures the brain's responses to reading, listening, math, or other learning and thinking activities and provides visual summaries in topographic maps. Only in the past 20 years, with the ability to track the neural circuits that enable us to think and learn, have cognitive neuroscientists been able to study how our brain structures support our mental functions. Today, research in learning, thinking, and remembering is being conducted more and more at the level of neural circuits, synapses, and neurotransmitters, and the time for mind-blowing advances in classroom teaching strategies is at hand. Brain-based research in learning has given educational researchers the means to translate neuroimaging data into classroom strategies that are designed to stimulate parts of the brain seen to be metabolically activated during the stages of information processing, memory, and recall. And what has emerged from the neuroscience of learning over the past two decades is a body of highly suggestive evidence that successful strategies teach for meaning and understanding, that learning-conducive classrooms are low in threat and high in reasonable challenge, and that students who are actively engaged and motivated devote more brain activity (as measured by metabolic processes) to learning. BRAIN-BASED RESEARCH--A WARNING LABEL Good-quality, peer-reviewed brain research can provide solid biological data and explanations, but educators need to be cautious about the claims that are said to be based on brain research. Not all of them are valid. Subsequent reevaluation of some early research interpreting PET scans has given us reason to be careful about which research we judge to be valid enough to connect with actual learning. …

Molecular Physiology of the Neural Circuit for Calcineurin-Dependent Associative Learning inCaenorhabditis elegans

How learning and memory is controlled at the neural circuit level is a fundamental question in neuroscience. However, molecular and cellular dissection of the neural circuits underlying learning and memory is extremely complicated in higher animals. Here, we report a simple neural circuit for learning behavior in Caenorhabditis elegans, where the calcium-activated phosphatase, calcineurin, acts as an essential modulator. The calcineurin mutant tax-6 showed defective feeding state-dependent learning behavior for temperature and salt. Surprisingly, defective associative learning between temperature and feeding state was caused by malfunctions of two pairs of directly connected interneurons, AIZ and RIA, in the mature nervous system. Monitoring temperature-evoked Ca2+ concentration changes in the AIZ-RIA neural pathway revealed that starvation, a conditioning factor, downregulated AIZ activity through calcineurin during associative learning between temperature and feeding state. Our results demonstrate the molecular and physiological mechanisms of a simple neural circuit for calcineurin-mediated associative learning behavior.

Analyses of habituation in Caenorhabditis elegans.

Although the nonassociative form of learning, habituation, is often described as the simplest form of learning, remarkably little is known about the cellular processes underlying its behavioral expression. Here, we review research on habituation in the nematode Caenorhabditis elegans that addresses habituation at behavioral, neural circuit, and genetic levels. This work highlights the need to understand the dynamics of a behavior before attempting to determine its underlying mechanism. In many cases knowing the characteristics of a behavior can direct or guide a search for underlying cellular mechanisms. We have highlighted the importance of interstimulus interval (ISI) in both short- and long-term habituation and suggested that different cellular mechanisms might underlie habituation at different ISIs. Like other organisms, C. elegans shows both accumulation of habituation with repeated training blocks and long-term retention of spaced or distributed training, but not for massed training. Exposure to heat shock during the interblock intervals eliminates the long-term memory for habituation but not the accumulation of short-term habituation over blocks of training. Analyses using laser ablation of identified neurons, and of identified mutants have shown that there are multiple sites of plasticity for the response and that glutamate plays a role in long-term retention of habituation training.

Memory dynamics in the honeybee

Reward learning in honeybees initiates a sequence of events which leads to long-lasting memory passing through multiple phases of transient memories. The study of memory dynamics is performed at the behavioral (both natural foraging behavior and appetitive conditioning), neural circuit and molecular levels. The results of these combined efforts lead to a model which assumes five kinds of sequential memories, each characterized by a set of behavioral and mechanistic properties. It is argued that these properties, although reflecting general characteristics of step-wise memory formation, are adapted to the species-specific adaptations in natural behavior, here to foraging at scattered and unreliable food sources.

Convergence of common and specific sensory afferents to the cerebellar auricle (auricula cerebelli) in the teleost fish Gnathonemus demonstrated by HRP method

The capacity to predict the sensory consequences of movements is critical for sensory, motor, and cognitive function. Though it is hypothesized that internal signals related to motor commands, known as corollary discharge, serve to generate such predictions, this process remains poorly understood at the neural circuit level. Here we demonstrate that neurons in the electrosensory lobe (ELL) of weakly electric mormyrid fish generate negative images of the sensory consequences of the fish’s own movements based on ascending spinal corollary discharge signals. These results generalize previous findings describing mechanisms for generating negative images of the effects of the fish’s specialized electric organ discharge (EOD) and suggest that a cerebellum-like circuit endowed with associative synaptic plasticity acting on corollary discharge can solve the complex and ubiquitous problem of predicting sensory consequences of movements.