Optogenetic dissection of neural circuits underlying emotional valence and motivated behaviors

PubMed Central

Nieh, Edward H.; Kim, Sung-Yon; Namburi, Praneeth; Tye, Kay M.

2014-01-01

The neural circuits underlying emotional valence and motivated behaviors are several synapses away from both defined sensory inputs and quantifiable motor outputs. Electrophysiology has provided us with a suitable means for observing neural activity during behavior, but methods for controlling activity for the purpose of studying motivated behaviors have been inadequate: electrical stimulation lacks cellular specificity and pharmacological manipulation lacks temporal resolution. The recent emergence of optogenetic tools provides a new means for establishing causal relationships between neural activity and behavior. Optogenetics, the use of genetically-encodable light-activated proteins, permits the modulation of specific neural circuit elements with millisecond precision. The ability to control individual cell types, and even projections between distal regions, allows us to investigate functional connectivity in a causal manner. The greatest consequence of controlling neural activity with finer precision has been the characterization of individual neural circuits within anatomical brain regions as defined functional units. Within the mesolimbic dopamine system, optogenetics has helped separate subsets of dopamine neurons with distinct functions for reward, aversion and salience processing, elucidated GABA neuronal effects on behavior, and characterized connectivity with forebrain and cortical structures. Within the striatum, optogenetics has confirmed the opposing relationship between direct and indirect pathway medium spiny neurons (MSNs), in addition to characterizing the inhibition of MSNs by cholinergic interneurons. Within the hypothalamus, optogenetics has helped overcome the heterogeneity in neuronal cell-type and revealed distinct circuits mediating aggression and feeding. Within the amygdala, optogenetics has allowed the study of intra-amygdala microcircuitry as well as interconnections with distal regions involved in fear and anxiety. In this review, we will present the body of optogenetic studies that has significantly enhanced our understanding of emotional valence and motivated behaviors. PMID:23142759

A Role of Phase-Resetting in Coordinating Large Scale Neural Networks During Attention and Goal-Directed Behavior

PubMed Central

Voloh, Benjamin; Womelsdorf, Thilo

2016-01-01

Short periods of oscillatory activation are ubiquitous signatures of neural circuits. A broad range of studies documents not only their circuit origins, but also a fundamental role for oscillatory activity in coordinating information transfer during goal directed behavior. Recent studies suggest that resetting the phase of ongoing oscillatory activity to endogenous or exogenous cues facilitates coordinated information transfer within circuits and between distributed brain areas. Here, we review evidence that pinpoints phase resetting as a critical marker of dynamic state changes of functional networks. Phase resets: (1) set a “neural context” in terms of narrow band frequencies that uniquely characterizes the activated circuits; (2) impose coherent low frequency phases to which high frequency activations can synchronize, identifiable as cross-frequency correlations across large anatomical distances; (3) are critical for neural coding models that depend on phase, increasing the informational content of neural representations; and (4) likely originate from the dynamics of canonical E-I circuits that are anatomically ubiquitous. These multiple signatures of phase resets are directly linked to enhanced information transfer and behavioral success. We survey how phase resets re-organize oscillations in diverse task contexts, including sensory perception, attentional stimulus selection, cross-modal integration, Pavlovian conditioning, and spatial navigation. The evidence we consider suggests that phase-resets can drive changes in neural excitability, ensemble organization, functional networks, and ultimately, overt behavior. PMID:27013986

Implantable neurotechnologies: bidirectional neural interfaces--applications and VLSI circuit implementations.

PubMed

Greenwald, Elliot; Masters, Matthew R; Thakor, Nitish V

2016-01-01

A bidirectional neural interface is a device that transfers information into and out of the nervous system. This class of devices has potential to improve treatment and therapy in several patient populations. Progress in very large-scale integration has advanced the design of complex integrated circuits. System-on-chip devices are capable of recording neural electrical activity and altering natural activity with electrical stimulation. Often, these devices include wireless powering and telemetry functions. This review presents the state of the art of bidirectional circuits as applied to neuroprosthetic, neurorepair, and neurotherapeutic systems.

The Zebrafish Brain in Research and Teaching: A Simple in Vivo and in Vitro Model for the Study of Spontaneous Neural Activity

ERIC Educational Resources Information Center

Vargas, R.; Johannesdottir, I. P.; Sigurgeirsson, B.; Porsteinsson, H.; Karlsson, K. AE.

2011-01-01

Recently, the zebrafish ("Danio rerio") has been established as a key animal model in neuroscience. Behavioral, genetic, and immunohistochemical techniques have been used to describe the connectivity of diverse neural circuits. However, few studies have used zebrafish to understand the function of cerebral structures or to study neural circuits.…

Conic section function neural network circuitry for offline signature recognition.

PubMed

Erkmen, Burcu; Kahraman, Nihan; Vural, Revna A; Yildirim, Tulay

2010-04-01

In this brief, conic section function neural network (CSFNN) circuitry was designed for offline signature recognition. CSFNN is a unified framework for multilayer perceptron (MLP) and radial basis function (RBF) networks to make simultaneous use of advantages of both. The CSFNN circuitry architecture was developed using a mixed mode circuit implementation. The designed circuit system is problem independent. Hence, the general purpose neural network circuit system could be applied to various pattern recognition problems with different network sizes on condition with the maximum network size of 16-16-8. In this brief, CSFNN circuitry system has been applied to two different signature recognition problems. CSFNN circuitry was trained with chip-in-the-loop learning technique in order to compensate typical analog process variations. CSFNN hardware achieved highly comparable computational performances with CSFNN software for nonlinear signature recognition problems.

Efficient Digital Implementation of The Sigmoidal Function For Artificial Neural Network

NASA Astrophysics Data System (ADS)

Pratap, Rana; Subadra, M.

2011-10-01

An efficient piecewise linear approximation of a nonlinear function (PLAN) is proposed. This uses simulink environment design to perform a direct transformation from X to Y, where X is the input and Y is the approximated sigmoidal output. This PLAN is then used within the outputs of an artificial neural network to perform the nonlinear approximation. In This paper, is proposed a method to implement in FPGA (Field Programmable Gate Array) circuits different approximation of the sigmoid function.. The major benefit of the proposed method resides in the possibility to design neural networks by means of predefined block systems created in System Generator environment and the possibility to create a higher level design tools used to implement neural networks in logical circuits.

Architecture of enteric neural circuits involved in intestinal motility.

PubMed

Costa, M; Brookes, S H

2008-08-01

This short review describes the conceptual development in the search for the enteric neural circuits with the initial identifications of the classes of enteric neurons on the bases of their morphology, neurochemistry, biophysical properties, projections and connectivity. The discovery of the presence of multiple neurochemicals in the same nerve cells in specific combinations led to the concept of "chemical coding" and of "plurichemical transmission". The proposal that enteric reflexes are largely responsible for the propulsion of contents led to investigations of polarised reflex pathways and how these may be activated to generate the coordinated propulsive behaviour of the intestine. The research over the past decades attempted to integrate information of chemical neuroanatomy with functional studies, with the development of methods combining anatomical, functional and pharmacological techniques. This multidisciplinary strategy led to a full accounting of all functional classes of enteric neurons in the guinea-pig, and advanced wiring diagrams of the enteric neural circuits have been proposed. In parallel, investigations of the actual behaviour of the intestine during physiological motor activity have advanced with the development of spatio-temporal analysis from video recordings. The relation between neural pathways, their activities and the generation of patterns of motor activity remain largely unexplained. The enteric neural circuits appear not set in rigid programs but respond to different physico-chemical contents in an adaptable way (neuromechanical hypothesis). The generation of the complex repertoire of motor patterns results from the interplay of myogenic and neuromechanical mechanisms with spontaneous generation of migratory motor activity by enteric circuits.

Inter-progenitor pool wiring: An evolutionarily conserved strategy that expands neural circuit diversity.

PubMed

Suzuki, Takumi; Sato, Makoto

2017-11-15

Diversification of neuronal types is key to establishing functional variations in neural circuits. The first critical step to generate neuronal diversity is to organize the compartmental domains of developing brains into spatially distinct neural progenitor pools. Neural progenitors in each pool then generate a unique set of diverse neurons through specific spatiotemporal specification processes. In this review article, we focus on an additional mechanism, 'inter-progenitor pool wiring', that further expands the diversity of neural circuits. After diverse types of neurons are generated in one progenitor pool, a fraction of these neurons start migrating toward a remote brain region containing neurons that originate from another progenitor pool. Finally, neurons of different origins are intermingled and eventually form complex but precise neural circuits. The developing cerebral cortex of mammalian brains is one of the best examples of inter-progenitor pool wiring. However, Drosophila visual system development has revealed similar mechanisms in invertebrate brains, suggesting that inter-progenitor pool wiring is an evolutionarily conserved strategy that expands neural circuit diversity. Here, we will discuss how inter-progenitor pool wiring is accomplished in mammalian and fly brain systems. Copyright © 2017 Elsevier Inc. All rights reserved.

Frank Beach Award Winner: Steroids as Neuromodulators of Brain Circuits and Behavior

PubMed Central

Remage-Healey, Luke

2014-01-01

Neurons communicate primarily via action potentials that transmit information on the timescale of milliseconds. Neurons also integrate information via alterations in gene transcription and protein translation that are sustained for hours to days after initiation. Positioned between these two signaling timescales are the minute-by-minute actions of neuromodulators. Over the course of minutes, the classical neuromodulators (such as serotonin, dopamine, octopamine, and norepinephrine) can alter and/or stabilize neural circuit patterning as well as behavioral states. Neuromodulators allow many flexible outputs from neural circuits and can encode information content into the firing state of neural networks. The idea that steroid molecules can operate as genuine behavioral neuromodulators - synthesized by and acting within brain circuits on a minute-by-minute timescale - has gained traction in recent years. Evidence for brain steroid synthesis at synaptic terminals has converged with evidence for the rapid actions of brain-derived steroids on neural circuits and behavior. The general principle emerging from this work is that the production of steroid hormones within brain circuits can alter their functional connectivity and shift sensory representations by enhancing their information coding. Steroids produced in the brain can therefore change the information content of neuronal networks to rapidly modulate sensory experience and sensorimotor functions. PMID:25110187

Hox Genes: Choreographers in Neural Development, Architects of Circuit Organization

PubMed Central

Philippidou, Polyxeni; Dasen, Jeremy S.

2013-01-01

Summary The neural circuits governing vital behaviors, such as respiration and locomotion, are comprised of discrete neuronal populations residing within the brainstem and spinal cord. Work over the past decade has provided a fairly comprehensive understanding of the developmental pathways that determine the identity of major neuronal classes within the neural tube. However, the steps through which neurons acquire the subtype diversities necessary for their incorporation into a particular circuit are still poorly defined. Studies on the specification of motor neurons indicate that the large family of Hox transcription factors has a key role in generating the subtypes required for selective muscle innervation. There is also emerging evidence that Hox genes function in multiple neuronal classes to shape synaptic specificity during development, suggesting a broader role in circuit assembly. This review highlights the functions and mechanisms of Hox gene networks, and their multifaceted roles during neuronal specification and connectivity. PMID:24094100

Defining biotypes for depression and anxiety based on large-scale circuit dysfunction: A theoretical review of the evidence and future directions for clinical translation

PubMed Central

Williams, Leanne M

2016-01-01

Complex emotional, cognitive and self-reflective functions rely on the activation and connectivity of large-scale neural circuits. These circuits offer a relevant scale of focus for conceptualizing a taxonomy for depression and anxiety based on specific profiles (or biotypes) of neural circuit dysfunction. Here, the theoretical review first outlined the current consensus as to what constitutes the organization of large-scale circuits in the human brain identified using parcellation and meta-analysis. The focus is on neural circuits implicated in resting reflection (“default mode”), detection of “salience”, affective processing (“threat” and “reward”), “attention” and “cognitive control”. Next, the current evidence regarding which type of dysfunctions in these circuits characterize depression and anxiety disorders was reviewed, with an emphasis on published meta-analyses and reviews of circuit dysfunctions that have been identified in at least two well-powered case:control studies. Grounded in the review of these topics, a conceptual framework is proposed for considering neural circuit-defined “biotypes”. In this framework, biotypes are defined by profiles of extent of dysfunction on each large-scale circuit. The clinical implications of a biotype approach for guiding classification and treatment of depression and anxiety is considered. Future research directions will develop the validity and clinical utility of a neural circuit biotype model that spans diagnostic categories and helps to translate neuroscience into clinical practice in the real world. PMID:27653321

A network model of behavioural performance in a rule learning task.

PubMed

Hasselmo, Michael E; Stern, Chantal E

2018-04-19

Humans demonstrate differences in performance on cognitive rule learning tasks which could involve differences in properties of neural circuits. An example model is presented to show how gating of the spread of neural activity could underlie rule learning and the generalization of rules to previously unseen stimuli. This model uses the activity of gating units to regulate the pattern of connectivity between neurons responding to sensory input and subsequent gating units or output units. This model allows analysis of network parameters that could contribute to differences in cognitive rule learning. These network parameters include differences in the parameters of synaptic modification and presynaptic inhibition of synaptic transmission that could be regulated by neuromodulatory influences on neural circuits. Neuromodulatory receptors play an important role in cognitive function, as demonstrated by the fact that drugs that block cholinergic muscarinic receptors can cause cognitive impairments. In discussions of the links between neuromodulatory systems and biologically based traits, the issue of mechanisms through which these linkages are realized is often missing. This model demonstrates potential roles of neural circuit parameters regulated by acetylcholine in learning context-dependent rules, and demonstrates the potential contribution of variation in neural circuit properties and neuromodulatory function to individual differences in cognitive function.This article is part of the theme issue 'Diverse perspectives on diversity: multi-disciplinary approaches to taxonomies of individual differences'. © 2018 The Author(s).

From Whole-Brain Data to Functional Circuit Models: The Zebrafish Optomotor Response.

PubMed

Naumann, Eva A; Fitzgerald, James E; Dunn, Timothy W; Rihel, Jason; Sompolinsky, Haim; Engert, Florian

2016-11-03

Detailed descriptions of brain-scale sensorimotor circuits underlying vertebrate behavior remain elusive. Recent advances in zebrafish neuroscience offer new opportunities to dissect such circuits via whole-brain imaging, behavioral analysis, functional perturbations, and network modeling. Here, we harness these tools to generate a brain-scale circuit model of the optomotor response, an orienting behavior evoked by visual motion. We show that such motion is processed by diverse neural response types distributed across multiple brain regions. To transform sensory input into action, these regions sequentially integrate eye- and direction-specific sensory streams, refine representations via interhemispheric inhibition, and demix locomotor instructions to independently drive turning and forward swimming. While experiments revealed many neural response types throughout the brain, modeling identified the dimensions of functional connectivity most critical for the behavior. We thus reveal how distributed neurons collaborate to generate behavior and illustrate a paradigm for distilling functional circuit models from whole-brain data. Copyright © 2016 Elsevier Inc. All rights reserved.

Complexity and Competition in Appetitive and Aversive Neural Circuits

PubMed Central

Barberini, Crista L.; Morrison, Sara E.; Saez, Alex; Lau, Brian; Salzman, C. Daniel

2012-01-01

Decision-making often involves using sensory cues to predict possible rewarding or punishing reinforcement outcomes before selecting a course of action. Recent work has revealed complexity in how the brain learns to predict rewards and punishments. Analysis of neural signaling during and after learning in the amygdala and orbitofrontal cortex, two brain areas that process appetitive and aversive stimuli, reveals a dynamic relationship between appetitive and aversive circuits. Specifically, the relationship between signaling in appetitive and aversive circuits in these areas shifts as a function of learning. Furthermore, although appetitive and aversive circuits may often drive opposite behaviors – approaching or avoiding reinforcement depending upon its valence – these circuits can also drive similar behaviors, such as enhanced arousal or attention; these processes also may influence choice behavior. These data highlight the formidable challenges ahead in dissecting how appetitive and aversive neural circuits interact to produce a complex and nuanced range of behaviors. PMID:23189037

The Topographical Mapping in Drosophila Central Complex Network and Its Signal Routing

PubMed Central

Chang, Po-Yen; Su, Ta-Shun; Shih, Chi-Tin; Lo, Chung-Chuan

2017-01-01

Neural networks regulate brain functions by routing signals. Therefore, investigating the detailed organization of a neural circuit at the cellular levels is a crucial step toward understanding the neural mechanisms of brain functions. To study how a complicated neural circuit is organized, we analyzed recently published data on the neural circuit of the Drosophila central complex, a brain structure associated with a variety of functions including sensory integration and coordination of locomotion. We discovered that, except for a small number of “atypical” neuron types, the network structure formed by the identified 194 neuron types can be described by only a few simple mathematical rules. Specifically, the topological mapping formed by these neurons can be reconstructed by applying a generation matrix on a small set of initial neurons. By analyzing how information flows propagate with or without the atypical neurons, we found that while the general pattern of signal propagation in the central complex follows the simple topological mapping formed by the “typical” neurons, some atypical neurons can substantially re-route the signal pathways, implying specific roles of these neurons in sensory signal integration. The present study provides insights into the organization principle and signal integration in the central complex. PMID:28443014

Increasing Spontaneous Retinal Activity before Eye Opening Accelerates the Development of Geniculate Receptive Fields

PubMed Central

Davis, Zachary W.; Chapman, Barbara

2015-01-01

Visually evoked activity is necessary for the normal development of the visual system. However, little is known about the capacity for patterned spontaneous activity to drive the maturation of receptive fields before visual experience. Retinal waves provide instructive retinotopic information for the anatomical organization of the visual thalamus. To determine whether retinal waves also drive the maturation of functional responses, we increased the frequency of retinal waves pharmacologically in the ferret (Mustela putorius furo) during a period of retinogeniculate development before eye opening. The development of geniculate receptive fields after receiving these increased neural activities was measured using single-unit electrophysiology. We found that increased retinal waves accelerate the developmental reduction of geniculate receptive field sizes. This reduction is due to a decrease in receptive field center size rather than an increase in inhibitory surround strength. This work reveals an instructive role for patterned spontaneous activity in guiding the functional development of neural circuits. SIGNIFICANCE STATEMENT Patterned spontaneous neural activity that occurs during development is known to be necessary for the proper formation of neural circuits. However, it is unknown whether the spontaneous activity alone is sufficient to drive the maturation of the functional properties of neurons. Our work demonstrates for the first time an acceleration in the maturation of neural function as a consequence of driving patterned spontaneous activity during development. This work has implications for our understanding of how neural circuits can be modified actively to improve function prematurely or to recover from injury with guided interventions of patterned neural activity. PMID:26511250

Dissociable attentional and affective circuits in medication-naïve children with attention-deficit/hyperactivity disorder.

PubMed

Posner, Jonathan; Rauh, Virginia; Gruber, Allison; Gat, Inbal; Wang, Zhishun; Peterson, Bradley S

2013-07-30

Current neurocognitive models of attention-deficit/hyperactivity disorder (ADHD) suggest that neural circuits involving both attentional and affective processing make independent contributions to the phenomenology of the disorder. However, a clear dissociation of attentional and affective circuits and their behavioral correlates has yet to be shown in medication-naïve children with ADHD. Using resting-state functional connectivity MRI (rs-fcMRI) in a cohort of medication naïve children with (N=22) and without (N=20) ADHD, we demonstrate that children with ADHD have reduced connectivity in two neural circuits: one underlying executive attention (EA) and the other emotional regulation (ER). We also demonstrate a double dissociation between these two neural circuits and their behavioral correlates such that reduced connectivity in the EA circuit correlates with executive attention deficits but not with emotional lability, while on the other hand, reduced connectivity in the ER circuit correlates with emotional lability but not with executive attention deficits. These findings suggest potential avenues for future research such as examining treatment effects on these two neural circuits as well as the potential prognostic and developmental significance of disturbances in one circuit vs the other. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Thalamo-cortical communication, glutamatergic neurotransmission and neural oscillations: A unique window into the origins of ScZ?

PubMed

Pratt, Judith; Dawson, Neil; Morris, Brain J; Grent-'t-Jong, Tineke; Roux, Frederic; Uhlhaas, Peter J

2017-02-01

The thalamus has recently received renewed interest in systems-neuroscience and schizophrenia (ScZ) research because of emerging evidence highlighting its important role in coordinating functional interactions in cortical-subcortical circuits. Moreover, higher cognitive functions, such as working memory and attention, have been related to thalamo-cortical interactions, providing a novel perspective for the understanding of the neural substrate of cognition. The current review will support this perspective by summarizing evidence on the crucial role of neural oscillations in facilitating thalamo-cortical (TC) interactions during normal brain functioning and their potential impairment in ScZ. Specifically, we will focus on the relationship between NMDA-R mediated (glutamatergic) neurotransmission in TC-interactions. To this end, we will first review the functional anatomy and neurotransmitters in thalamic circuits, followed by a review of the oscillatory signatures and cognitive processes supported by TC-circuits. In the second part of the paper, data from preclinical research as well as human studies will be summarized that have implicated TC-interactions as a crucial target for NMDA-receptor hypofunctioning. Finally, we will compare these neural signatures with current evidence from ScZ-research, suggesting a potential overlap between alterations in TC-circuits as the result of NMDA-R deficits and stage-specific alterations in large-scale networks in ScZ. Copyright © 2016 Elsevier B.V. All rights reserved.

PCSIM: A Parallel Simulation Environment for Neural Circuits Fully Integrated with Python

PubMed Central

Pecevski, Dejan; Natschläger, Thomas; Schuch, Klaus

2008-01-01

The Parallel Circuit SIMulator (PCSIM) is a software package for simulation of neural circuits. It is primarily designed for distributed simulation of large scale networks of spiking point neurons. Although its computational core is written in C++, PCSIM's primary interface is implemented in the Python programming language, which is a powerful programming environment and allows the user to easily integrate the neural circuit simulator with data analysis and visualization tools to manage the full neural modeling life cycle. The main focus of this paper is to describe PCSIM's full integration into Python and the benefits thereof. In particular we will investigate how the automatically generated bidirectional interface and PCSIM's object-oriented modular framework enable the user to adopt a hybrid modeling approach: using and extending PCSIM's functionality either employing pure Python or C++ and thus combining the advantages of both worlds. Furthermore, we describe several supplementary PCSIM packages written in pure Python and tailored towards setting up and analyzing neural simulations. PMID:19543450

The neural circuits that generate tics in Tourette's syndrome.

PubMed

Wang, Zhishun; Maia, Tiago V; Marsh, Rachel; Colibazzi, Tiziano; Gerber, Andrew; Peterson, Bradley S

2011-12-01

The purpose of this study was to examine neural activity and connectivity within cortico-striato-thalamo-cortical circuits and to reveal circuit-based neural mechanisms that govern tic generation in Tourette's syndrome. Functional magnetic resonance imaging data were acquired from 13 individuals with Tourette's syndrome and 21 healthy comparison subjects during spontaneous or simulated tics. Independent component analysis with hierarchical partner matching was used to isolate neural activity within functionally distinct regions of cortico-striato-thalamo-cortical circuits. Granger causality was used to investigate causal interactions among these regions. The Tourette's syndrome group exhibited stronger neural activity and interregional causality than healthy comparison subjects throughout all portions of the motor pathway, including the sensorimotor cortex, putamen, pallidum, and substantia nigra. Activity in these areas correlated positively with the severity of tic symptoms. Activity within the Tourette's syndrome group was stronger during spontaneous tics than during voluntary tics in the somatosensory and posterior parietal cortices, putamen, and amygdala/hippocampus complex, suggesting that activity in these regions may represent features of the premonitory urges that generate spontaneous tic behaviors. In contrast, activity was weaker in the Tourette's syndrome group than in the healthy comparison group within portions of cortico-striato-thalamo-cortical circuits that exert top-down control over motor pathways (the caudate and anterior cingulate cortex), and progressively less activity in these regions accompanied more severe tic symptoms, suggesting that faulty activity in these circuits may result in their failure to control tic behaviors or the premonitory urges that generate them. Our findings, taken together, suggest that tics are caused by the combined effects of excessive activity in motor pathways and reduced activation in control portions of cortico-striato-thalamo-cortical circuits.

RRAM-based hardware implementations of artificial neural networks: progress update and challenges ahead

NASA Astrophysics Data System (ADS)

Prezioso, M.; Merrikh-Bayat, F.; Chakrabarti, B.; Strukov, D.

2016-02-01

Artificial neural networks have been receiving increasing attention due to their superior performance in many information processing tasks. Typically, scaling up the size of the network results in better performance and richer functionality. However, large neural networks are challenging to implement in software and customized hardware are generally required for their practical implementations. In this work, we will discuss our group's recent efforts on the development of such custom hardware circuits, based on hybrid CMOS/memristor circuits, in particular of CMOL variety. We will start by reviewing the basics of memristive devices and of CMOL circuits. We will then discuss our recent progress towards demonstration of hybrid circuits, focusing on the experimental and theoretical results for artificial neural networks based on crossbarintegrated metal oxide memristors. We will conclude presentation with the discussion of the remaining challenges and the most pressing research needs.

A neural circuit transforming temporal periodicity information into a rate-based representation in the mammalian auditory system.

PubMed

Dicke, Ulrike; Ewert, Stephan D; Dau, Torsten; Kollmeier, Birger

2007-01-01

Periodic amplitude modulations (AMs) of an acoustic stimulus are presumed to be encoded in temporal activity patterns of neurons in the cochlear nucleus. Physiological recordings indicate that this temporal AM code is transformed into a rate-based periodicity code along the ascending auditory pathway. The present study suggests a neural circuit for the transformation from the temporal to the rate-based code. Due to the neural connectivity of the circuit, bandpass shaped rate modulation transfer functions are obtained that correspond to recorded functions of inferior colliculus (IC) neurons. In contrast to previous modeling studies, the present circuit does not employ a continuously changing temporal parameter to obtain different best modulation frequencies (BMFs) of the IC bandpass units. Instead, different BMFs are yielded from varying the number of input units projecting onto different bandpass units. In order to investigate the compatibility of the neural circuit with a linear modulation filterbank analysis as proposed in psychophysical studies, complex stimuli such as tones modulated by the sum of two sinusoids, narrowband noise, and iterated rippled noise were processed by the model. The model accounts for the encoding of AM depth over a large dynamic range and for modulation frequency selective processing of complex sounds.

Engineering-Aligned 3D Neural Circuit in Microfluidic Device.

PubMed

Bang, Seokyoung; Na, Sangcheol; Jang, Jae Myung; Kim, Jinhyun; Jeon, Noo Li

2016-01-07

The brain is one of the most important and complex organs in the human body. Although various neural network models have been proposed for in vitro 3D neuronal networks, it has been difficult to mimic functional and structural complexity of the in vitro neural circuit. Here, a microfluidic model of a simplified 3D neural circuit is reported. First, the microfluidic device is filled with Matrigel and continuous flow is delivered across the device during gelation. The fluidic flow aligns the extracellular matrix (ECM) components along the flow direction. Following the alignment of ECM fibers, neurites of primary rat cortical neurons are grown into the Matrigel at the average speed of 250 μm d(-1) and form axon bundles approximately 1500 μm in length at 6 days in vitro (DIV). Additionally, neural networks are developed from presynaptic to postsynaptic neurons at 14 DIV. The establishment of aligned 3D neural circuits is confirmed with the immunostaining of PSD-95 and synaptophysin and the observation of calcium signal transmission. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Technologies for imaging neural activity in large volumes

PubMed Central

Ji, Na; Freeman, Jeremy; Smith, Spencer L.

2017-01-01

Neural circuitry has evolved to form distributed networks that act dynamically across large volumes. Collecting data from individual planes, conventional microscopy cannot sample circuitry across large volumes at the temporal resolution relevant to neural circuit function and behaviors. Here, we review emerging technologies for rapid volume imaging of neural circuitry. We focus on two critical challenges: the inertia of optical systems, which limits image speed, and aberrations, which restrict the image volume. Optical sampling time must be long enough to ensure high-fidelity measurements, but optimized sampling strategies and point spread function engineering can facilitate rapid volume imaging of neural activity within this constraint. We also discuss new computational strategies for the processing and analysis of volume imaging data of increasing size and complexity. Together, optical and computational advances are providing a broader view of neural circuit dynamics, and help elucidate how brain regions work in concert to support behavior. PMID:27571194

Massively parallel neural circuits for stereoscopic color vision: encoding, decoding and identification.

PubMed

Lazar, Aurel A; Slutskiy, Yevgeniy B; Zhou, Yiyin

2015-03-01

Past work demonstrated how monochromatic visual stimuli could be faithfully encoded and decoded under Nyquist-type rate conditions. Color visual stimuli were then traditionally encoded and decoded in multiple separate monochromatic channels. The brain, however, appears to mix information about color channels at the earliest stages of the visual system, including the retina itself. If information about color is mixed and encoded by a common pool of neurons, how can colors be demixed and perceived? We present Color Video Time Encoding Machines (Color Video TEMs) for encoding color visual stimuli that take into account a variety of color representations within a single neural circuit. We then derive a Color Video Time Decoding Machine (Color Video TDM) algorithm for color demixing and reconstruction of color visual scenes from spikes produced by a population of visual neurons. In addition, we formulate Color Video Channel Identification Machines (Color Video CIMs) for functionally identifying color visual processing performed by a spiking neural circuit. Furthermore, we derive a duality between TDMs and CIMs that unifies the two and leads to a general theory of neural information representation for stereoscopic color vision. We provide examples demonstrating that a massively parallel color visual neural circuit can be first identified with arbitrary precision and its spike trains can be subsequently used to reconstruct the encoded stimuli. We argue that evaluation of the functional identification methodology can be effectively and intuitively performed in the stimulus space. In this space, a signal reconstructed from spike trains generated by the identified neural circuit can be compared to the original stimulus. Copyright © 2014 Elsevier Ltd. All rights reserved.

SpikingLab: modelling agents controlled by Spiking Neural Networks in Netlogo.

PubMed

Jimenez-Romero, Cristian; Johnson, Jeffrey

2017-01-01

The scientific interest attracted by Spiking Neural Networks (SNN) has lead to the development of tools for the simulation and study of neuronal dynamics ranging from phenomenological models to the more sophisticated and biologically accurate Hodgkin-and-Huxley-based and multi-compartmental models. However, despite the multiple features offered by neural modelling tools, their integration with environments for the simulation of robots and agents can be challenging and time consuming. The implementation of artificial neural circuits to control robots generally involves the following tasks: (1) understanding the simulation tools, (2) creating the neural circuit in the neural simulator, (3) linking the simulated neural circuit with the environment of the agent and (4) programming the appropriate interface in the robot or agent to use the neural controller. The accomplishment of the above-mentioned tasks can be challenging, especially for undergraduate students or novice researchers. This paper presents an alternative tool which facilitates the simulation of simple SNN circuits using the multi-agent simulation and the programming environment Netlogo (educational software that simplifies the study and experimentation of complex systems). The engine proposed and implemented in Netlogo for the simulation of a functional model of SNN is a simplification of integrate and fire (I&F) models. The characteristics of the engine (including neuronal dynamics, STDP learning and synaptic delay) are demonstrated through the implementation of an agent representing an artificial insect controlled by a simple neural circuit. The setup of the experiment and its outcomes are described in this work.

Neuroimaging the interaction of mind and metabolism in humans

PubMed Central

D’Agostino, Alexandra E.; Small, Dana M.

2012-01-01

Hormonal and metabolic signals interact with neural circuits orchestrating behavior to guide food intake. Neuroimaging techniques such as functional magnetic resonance imaging (fMRI) enable the identification of where in the brain particular mental processes like desire, satiety and pleasure occur. Once these neural circuits are described it then becomes possible to determine how metabolic and hormonal signals can alter brain response to influence psychological states and decision-making processes to guide intake. Here, we provide an overview of the contributions of functional neuroimaging to the understanding of how subjective and neural responses to food and food cues interact with metabolic/hormonal factors. PMID:24024114

Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning.

PubMed

Xu, Tao; Xiao, Na; Zhai, Xiaolong; Kwan Chan, Pak; Tin, Chung

2018-02-01

Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

Sequencing the Connectome

PubMed Central

Zador, Anthony M.; Dubnau, Joshua; Oyibo, Hassana K.; Zhan, Huiqing; Cao, Gang; Peikon, Ian D.

2012-01-01

Connectivity determines the function of neural circuits. Historically, circuit mapping has usually been viewed as a problem of microscopy, but no current method can achieve high-throughput mapping of entire circuits with single neuron precision. Here we describe a novel approach to determining connectivity. We propose BOINC (“barcoding of individual neuronal connections”), a method for converting the problem of connectivity into a form that can be read out by high-throughput DNA sequencing. The appeal of using sequencing is that its scale—sequencing billions of nucleotides per day is now routine—is a natural match to the complexity of neural circuits. An inexpensive high-throughput technique for establishing circuit connectivity at single neuron resolution could transform neuroscience research. PMID:23109909

NT3-chitosan elicits robust endogenous neurogenesis to enable functional recovery after spinal cord injury

PubMed Central

Yang, Zhaoyang; Zhang, Aifeng; Duan, Hongmei; Zhang, Sa; Hao, Peng; Ye, Keqiang; Sun, Yi E.; Li, Xiaoguang

2015-01-01

Neural stem cells (NSCs) in the adult mammalian central nervous system (CNS) hold the key to neural regeneration through proper activation, differentiation, and maturation, to establish nascent neural networks, which can be integrated into damaged neural circuits to repair function. However, the CNS injury microenvironment is often inhibitory and inflammatory, limiting the ability of activated NSCs to differentiate into neurons and form nascent circuits. Here we report that neurotrophin-3 (NT3)-coupled chitosan biomaterial, when inserted into a 5-mm gap of completely transected and excised rat thoracic spinal cord, elicited robust activation of endogenous NSCs in the injured spinal cord. Through slow release of NT3, the biomaterial attracted NSCs to migrate into the lesion area, differentiate into neurons, and form functional neural networks, which interconnected severed ascending and descending axons, resulting in sensory and motor behavioral recovery. Our study suggests that enhancing endogenous neurogenesis could be a novel strategy for treatment of spinal cord injury. PMID:26460015

Insect Responses to Linearly Polarized Reflections: Orphan Behaviors Without Neural Circuits.

PubMed

Heinloth, Tanja; Uhlhorn, Juliane; Wernet, Mathias F

2018-01-01

The e-vector orientation of linearly polarized light represents an important visual stimulus for many insects. Especially the detection of polarized skylight by many navigating insect species is known to improve their orientation skills. While great progress has been made towards describing both the anatomy and function of neural circuit elements mediating behaviors related to navigation, relatively little is known about how insects perceive non-celestial polarized light stimuli, like reflections off water, leaves, or shiny body surfaces. Work on different species suggests that these behaviors are not mediated by the "Dorsal Rim Area" (DRA), a specialized region in the dorsal periphery of the adult compound eye, where ommatidia contain highly polarization-sensitive photoreceptor cells whose receptive fields point towards the sky. So far, only few cases of polarization-sensitive photoreceptors have been described in the ventral periphery of the insect retina. Furthermore, both the structure and function of those neural circuits connecting to these photoreceptor inputs remain largely uncharacterized. Here we review the known data on non-celestial polarization vision from different insect species (dragonflies, butterflies, beetles, bugs and flies) and present three well-characterized examples for functionally specialized non-DRA detectors from different insects that seem perfectly suited for mediating such behaviors. Finally, using recent advances from circuit dissection in Drosophila melanogaster , we discuss what types of potential candidate neurons could be involved in forming the underlying neural circuitry mediating non-celestial polarization vision.

A Point-process Response Model for Spike Trains from Single Neurons in Neural Circuits under Optogenetic Stimulation

PubMed Central

Luo, X.; Gee, S.; Sohal, V.; Small, D.

2015-01-01

Optogenetics is a new tool to study neuronal circuits that have been genetically modified to allow stimulation by flashes of light. We study recordings from single neurons within neural circuits under optogenetic stimulation. The data from these experiments present a statistical challenge of modeling a high frequency point process (neuronal spikes) while the input is another high frequency point process (light flashes). We further develop a generalized linear model approach to model the relationships between two point processes, employing additive point-process response functions. The resulting model, Point-process Responses for Optogenetics (PRO), provides explicit nonlinear transformations to link the input point process with the output one. Such response functions may provide important and interpretable scientific insights into the properties of the biophysical process that governs neural spiking in response to optogenetic stimulation. We validate and compare the PRO model using a real dataset and simulations, and our model yields a superior area-under-the- curve value as high as 93% for predicting every future spike. For our experiment on the recurrent layer V circuit in the prefrontal cortex, the PRO model provides evidence that neurons integrate their inputs in a sophisticated manner. Another use of the model is that it enables understanding how neural circuits are altered under various disease conditions and/or experimental conditions by comparing the PRO parameters. PMID:26411923

Functional identification of spike-processing neural circuits.

PubMed

Lazar, Aurel A; Slutskiy, Yevgeniy B

2014-02-01

We introduce a novel approach for a complete functional identification of biophysical spike-processing neural circuits. The circuits considered accept multidimensional spike trains as their input and comprise a multitude of temporal receptive fields and conductance-based models of action potential generation. Each temporal receptive field describes the spatiotemporal contribution of all synapses between any two neurons and incorporates the (passive) processing carried out by the dendritic tree. The aggregate dendritic current produced by a multitude of temporal receptive fields is encoded into a sequence of action potentials by a spike generator modeled as a nonlinear dynamical system. Our approach builds on the observation that during any experiment, an entire neural circuit, including its receptive fields and biophysical spike generators, is projected onto the space of stimuli used to identify the circuit. Employing the reproducing kernel Hilbert space (RKHS) of trigonometric polynomials to describe input stimuli, we quantitatively describe the relationship between underlying circuit parameters and their projections. We also derive experimental conditions under which these projections converge to the true parameters. In doing so, we achieve the mathematical tractability needed to characterize the biophysical spike generator and identify the multitude of receptive fields. The algorithms obviate the need to repeat experiments in order to compute the neurons' rate of response, rendering our methodology of interest to both experimental and theoretical neuroscientists.

Advances in two photon scanning and scanless microscopy technologies for functional neural circuit imaging.

PubMed

Schultz, Simon R; Copeland, Caroline S; Foust, Amanda J; Quicke, Peter; Schuck, Renaud

2017-01-01

Recent years have seen substantial developments in technology for imaging neural circuits, raising the prospect of large scale imaging studies of neural populations involved in information processing, with the potential to lead to step changes in our understanding of brain function and dysfunction. In this article we will review some key recent advances: improved fluorophores for single cell resolution functional neuroimaging using a two photon microscope; improved approaches to the problem of scanning active circuits; and the prospect of scanless microscopes which overcome some of the bandwidth limitations of current imaging techniques. These advances in technology for experimental neuroscience have in themselves led to technical challenges, such as the need for the development of novel signal processing and data analysis tools in order to make the most of the new experimental tools. We review recent work in some active topics, such as region of interest segmentation algorithms capable of demixing overlapping signals, and new highly accurate algorithms for calcium transient detection. These advances motivate the development of new data analysis tools capable of dealing with spatial or spatiotemporal patterns of neural activity, that scale well with pattern size.

Advances in two photon scanning and scanless microscopy technologies for functional neural circuit imaging

PubMed Central

Schultz, Simon R.; Copeland, Caroline S.; Foust, Amanda J.; Quicke, Peter; Schuck, Renaud

2017-01-01

Recent years have seen substantial developments in technology for imaging neural circuits, raising the prospect of large scale imaging studies of neural populations involved in information processing, with the potential to lead to step changes in our understanding of brain function and dysfunction. In this article we will review some key recent advances: improved fluorophores for single cell resolution functional neuroimaging using a two photon microscope; improved approaches to the problem of scanning active circuits; and the prospect of scanless microscopes which overcome some of the bandwidth limitations of current imaging techniques. These advances in technology for experimental neuroscience have in themselves led to technical challenges, such as the need for the development of novel signal processing and data analysis tools in order to make the most of the new experimental tools. We review recent work in some active topics, such as region of interest segmentation algorithms capable of demixing overlapping signals, and new highly accurate algorithms for calcium transient detection. These advances motivate the development of new data analysis tools capable of dealing with spatial or spatiotemporal patterns of neural activity, that scale well with pattern size. PMID:28757657

Spatiotemporal Imaging of Glutamate-Induced Biophotonic Activities and Transmission in Neural Circuits

PubMed Central

Tang, Rendong; Dai, Jiapei

2014-01-01

The processing of neural information in neural circuits plays key roles in neural functions. Biophotons, also called ultra-weak photon emissions (UPE), may play potential roles in neural signal transmission, contributing to the understanding of the high functions of nervous system such as vision, learning and memory, cognition and consciousness. However, the experimental analysis of biophotonic activities (emissions) in neural circuits has been hampered due to technical limitations. Here by developing and optimizing an in vitro biophoton imaging method, we characterize the spatiotemporal biophotonic activities and transmission in mouse brain slices. We show that the long-lasting application of glutamate to coronal brain slices produces a gradual and significant increase of biophotonic activities and achieves the maximal effect within approximately 90 min, which then lasts for a relatively long time (>200 min). The initiation and/or maintenance of biophotonic activities by glutamate can be significantly blocked by oxygen and glucose deprivation, together with the application of a cytochrome c oxidase inhibitor (sodium azide), but only partly by an action potential inhibitor (TTX), an anesthetic (procaine), or the removal of intracellular and extracellular Ca2+. We also show that the detected biophotonic activities in the corpus callosum and thalamus in sagittal brain slices mostly originate from axons or axonal terminals of cortical projection neurons, and that the hyperphosphorylation of microtubule-associated protein tau leads to a significant decrease of biophotonic activities in these two areas. Furthermore, the application of glutamate in the hippocampal dentate gyrus results in increased biophotonic activities in its intrahippocampal projection areas. These results suggest that the glutamate-induced biophotonic activities reflect biophotonic transmission along the axons and in neural circuits, which may be a new mechanism for the processing of neural information. PMID:24454909

Spatiotemporal imaging of glutamate-induced biophotonic activities and transmission in neural circuits.

PubMed

Tang, Rendong; Dai, Jiapei

2014-01-01

The processing of neural information in neural circuits plays key roles in neural functions. Biophotons, also called ultra-weak photon emissions (UPE), may play potential roles in neural signal transmission, contributing to the understanding of the high functions of nervous system such as vision, learning and memory, cognition and consciousness. However, the experimental analysis of biophotonic activities (emissions) in neural circuits has been hampered due to technical limitations. Here by developing and optimizing an in vitro biophoton imaging method, we characterize the spatiotemporal biophotonic activities and transmission in mouse brain slices. We show that the long-lasting application of glutamate to coronal brain slices produces a gradual and significant increase of biophotonic activities and achieves the maximal effect within approximately 90 min, which then lasts for a relatively long time (>200 min). The initiation and/or maintenance of biophotonic activities by glutamate can be significantly blocked by oxygen and glucose deprivation, together with the application of a cytochrome c oxidase inhibitor (sodium azide), but only partly by an action potential inhibitor (TTX), an anesthetic (procaine), or the removal of intracellular and extracellular Ca(2+). We also show that the detected biophotonic activities in the corpus callosum and thalamus in sagittal brain slices mostly originate from axons or axonal terminals of cortical projection neurons, and that the hyperphosphorylation of microtubule-associated protein tau leads to a significant decrease of biophotonic activities in these two areas. Furthermore, the application of glutamate in the hippocampal dentate gyrus results in increased biophotonic activities in its intrahippocampal projection areas. These results suggest that the glutamate-induced biophotonic activities reflect biophotonic transmission along the axons and in neural circuits, which may be a new mechanism for the processing of neural information.

The neurobiological basis of orientation in insects: insights from the silkmoth mating dance.

PubMed

Namiki, Shigehiro; Kanzaki, Ryohei

2016-06-01

Counterturning is a common movement pattern during orientation behavior in insects. Once male moths sense sex pheromones and then lose the input, they demonstrate zigzag movements, alternating between left and right turns, to increase the probability to contact with the pheromone plume. We summarize the anatomy and function of the neural circuit involved in pheromone orientation in the silkmoth. A neural circuit, the lateral accessory lobe (LAL), serves a role as the circuit module for zigzag movements and controls this operation using a flip-flop neural switch. Circuit design of the LAL is well conserved across species. We hypothesize that this zigzag module is utilized in a wide range of insect behavior. We introduce two examples of the potential use: orientation flight and the waggle dance in bees. Copyright © 2016 Elsevier Inc. All rights reserved.

Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning

NASA Astrophysics Data System (ADS)

Xu, Tao; Xiao, Na; Zhai, Xiaolong; Chan, Pak Kwan; Tin, Chung

2018-02-01

Objective. Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). Approach. The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. Main results. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. Significance. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

A simple structure wavelet transform circuit employing function link neural networks and SI filters

NASA Astrophysics Data System (ADS)

Mu, Li; Yigang, He

2016-12-01

Signal processing by means of analog circuits offers advantages from a power consumption viewpoint. Implementing wavelet transform (WT) using analog circuits is of great interest when low-power consumption becomes an important issue. In this article, a novel simple structure WT circuit in analog domain is presented by employing functional link neural network (FLNN) and switched-current (SI) filters. First, the wavelet base is approximated using FLNN algorithms for giving a filter transfer function that is suitable for simple structure WT circuit implementation. Next, the WT circuit is constructed with the wavelet filter bank, whose impulse response is the approximated wavelet and its dilations. The filter design that follows is based on a follow-the-leader feedback (FLF) structure with multiple output bilinear SI integrators and current mirrors as the main building blocks. SI filter is well suited for this application since the dilation constant across different scales of the transform can be precisely implemented and controlled by the clock frequency of the circuit with the same system architecture. Finally, to illustrate the design procedure, a seventh-order FLNN-approximated Gaussian wavelet is implemented as an example. Simulations have successfully verified that the designed simple structure WT circuit has low sensitivity, low-power consumption and litter effect to the imperfections.

Bidirectional Neural Interfaces

PubMed Central

Masters, Matthew R.; Thakor, Nitish V.

2016-01-01

A bidirectional neural interface is a device that transfers information into and out of the nervous system. This class of devices has potential to improve treatment and therapy in several patient populations. Progress in very-large-scale integration (VLSI) has advanced the design of complex integrated circuits. System-on-chip (SoC) devices are capable of recording neural electrical activity and altering natural activity with electrical stimulation. Often, these devices include wireless powering and telemetry functions. This review presents the state of the art of bidirectional circuits as applied to neuroprosthetic, neurorepair, and neurotherapeutic systems. PMID:26753776

The Roles of Sequencing and Verbal Working Memory in Sentence Comprehension Deficits in Parkinson's Disease

ERIC Educational Resources Information Center

Hochstadt, Jesse; Nakano, Hiroko; Lieberman, Philip; Friedman, Joseph

2006-01-01

Studies of sentence comprehension deficits in Parkinson's disease (PD) patients suggest that language processing involves circuits connecting subcortical and cortical regions. Anatomically segregated neural circuits appear to support different cognitive and motor functions. To investigate which functions are implicated in PD comprehension…

Implantable neurotechnologies: a review of integrated circuit neural amplifiers.

PubMed

Ng, Kian Ann; Greenwald, Elliot; Xu, Yong Ping; Thakor, Nitish V

2016-01-01

Neural signal recording is critical in modern day neuroscience research and emerging neural prosthesis programs. Neural recording requires the use of precise, low-noise amplifier systems to acquire and condition the weak neural signals that are transduced through electrode interfaces. Neural amplifiers and amplifier-based systems are available commercially or can be designed in-house and fabricated using integrated circuit (IC) technologies, resulting in very large-scale integration or application-specific integrated circuit solutions. IC-based neural amplifiers are now used to acquire untethered/portable neural recordings, as they meet the requirements of a miniaturized form factor, light weight and low power consumption. Furthermore, such miniaturized and low-power IC neural amplifiers are now being used in emerging implantable neural prosthesis technologies. This review focuses on neural amplifier-based devices and is presented in two interrelated parts. First, neural signal recording is reviewed, and practical challenges are highlighted. Current amplifier designs with increased functionality and performance and without penalties in chip size and power are featured. Second, applications of IC-based neural amplifiers in basic science experiments (e.g., cortical studies using animal models), neural prostheses (e.g., brain/nerve machine interfaces) and treatment of neuronal diseases (e.g., DBS for treatment of epilepsy) are highlighted. The review concludes with future outlooks of this technology and important challenges with regard to neural signal amplification.

Implantable neurotechnologies: a review of integrated circuit neural amplifiers

PubMed Central

Greenwald, Elliot; Xu, Yong Ping; Thakor, Nitish V.

2016-01-01

Neural signal recording is critical in modern day neuroscience research and emerging neural prosthesis programs. Neural recording requires the use of precise, low-noise amplifier systems to acquire and condition the weak neural signals that are transduced through electrode interfaces. Neural amplifiers and amplifier-based systems are available commercially or can be designed in-house and fabricated using integrated circuit (IC) technologies, resulting in very large-scale integration or application-specific integrated circuit solutions. IC-based neural amplifiers are now used to acquire untethered/portable neural recordings, as they meet the requirements of a miniaturized form factor, light weight and low power consumption. Furthermore, such miniaturized and low-power IC neural amplifiers are now being used in emerging implantable neural prosthesis technologies. This review focuses on neural amplifier-based devices and is presented in two interrelated parts. First, neural signal recording is reviewed, and practical challenges are highlighted. Current amplifier designs with increased functionality and performance and without penalties in chip size and power are featured. Second, applications of IC-based neural amplifiers in basic science experiments (e.g., cortical studies using animal models), neural prostheses (e.g., brain/nerve machine interfaces) and treatment of neuronal diseases (e.g., DBS for treatment of epilepsy) are highlighted. The review concludes with future outlooks of this technology and important challenges with regard to neural signal amplification. PMID:26798055

Reward from bugs to bipeds: a comparative approach to understanding how reward circuits function

PubMed Central

Scaplen, Kristin M.; Kaun, Karla R.

2016-01-01

Abstract In a complex environment, animals learn from their responses to stimuli and events. Appropriate response to reward and punishment can promote survival, reproduction and increase evolutionary fitness. Interestingly, the neural processes underlying these responses are remarkably similar across phyla. In all species, dopamine is central to encoding reward and directing motivated behaviors, however, a comprehensive understanding of how circuits encode reward and direct motivated behaviors is still lacking. In part, this is a result of the sheer diversity of neurons, the heterogeneity of their responses and the complexity of neural circuits within which they are found. We argue that general features of reward circuitry are common across model organisms, and thus principles learned from invertebrate model organisms can inform research across species. In particular, we discuss circuit motifs that appear to be functionally equivalent from flies to primates. We argue that a comparative approach to studying and understanding reward circuit function provides a more comprehensive understanding of reward circuitry, and informs disorders that affect the brain’s reward circuitry. PMID:27328845

Optogenetic interrogation of neural circuits: technology for probing mammalian brain structures

PubMed Central

Zhang, Feng; Gradinaru, Viviana; Adamantidis, Antoine R; Durand, Remy; Airan, Raag D; de Lecea, Luis; Deisseroth, Karl

2015-01-01

Elucidation of the neural substrates underlying complex animal behaviors depends on precise activity control tools, as well as compatible readout methods. Recent developments in optogenetics have addressed this need, opening up new possibilities for systems neuroscience. Interrogation of even deep neural circuits can be conducted by directly probing the necessity and sufficiency of defined circuit elements with millisecond-scale, cell type-specific optical perturbations, coupled with suitable readouts such as electrophysiology, optical circuit dynamics measures and freely moving behavior in mammals. Here we collect in detail our strategies for delivering microbial opsin genes to deep mammalian brain structures in vivo, along with protocols for integrating the resulting optical control with compatible readouts (electrophysiological, optical and behavioral). The procedures described here, from initial virus preparation to systems-level functional readout, can be completed within 4–5 weeks. Together, these methods may help in providing circuit-level insight into the dynamics underlying complex mammalian behaviors in health and disease. PMID:20203662

Synaptic plasticity functions in an organic electrochemical transistor

NASA Astrophysics Data System (ADS)

Gkoupidenis, Paschalis; Schaefer, Nathan; Strakosas, Xenofon; Fairfield, Jessamyn A.; Malliaras, George G.

2015-12-01

Synaptic plasticity functions play a crucial role in the transmission of neural signals in the brain. Short-term plasticity is required for the transmission, encoding, and filtering of the neural signal, whereas long-term plasticity establishes more permanent changes in neural microcircuitry and thus underlies memory and learning. The realization of bioinspired circuits that can actually mimic signal processing in the brain demands the reproduction of both short- and long-term aspects of synaptic plasticity in a single device. Here, we demonstrate the implementation of neuromorphic functions similar to biological memory, such as short- to long-term memory transition, in non-volatile organic electrochemical transistors (OECTs). Depending on the training of the OECT, the device displays either short- or long-term plasticity, therefore, exhibiting non von Neumann characteristics with merged processing and storing functionalities. These results are a first step towards the implementation of organic-based neuromorphic circuits.

Insect Responses to Linearly Polarized Reflections: Orphan Behaviors Without Neural Circuits

PubMed Central

Heinloth, Tanja; Uhlhorn, Juliane; Wernet, Mathias F.

2018-01-01

The e-vector orientation of linearly polarized light represents an important visual stimulus for many insects. Especially the detection of polarized skylight by many navigating insect species is known to improve their orientation skills. While great progress has been made towards describing both the anatomy and function of neural circuit elements mediating behaviors related to navigation, relatively little is known about how insects perceive non-celestial polarized light stimuli, like reflections off water, leaves, or shiny body surfaces. Work on different species suggests that these behaviors are not mediated by the “Dorsal Rim Area” (DRA), a specialized region in the dorsal periphery of the adult compound eye, where ommatidia contain highly polarization-sensitive photoreceptor cells whose receptive fields point towards the sky. So far, only few cases of polarization-sensitive photoreceptors have been described in the ventral periphery of the insect retina. Furthermore, both the structure and function of those neural circuits connecting to these photoreceptor inputs remain largely uncharacterized. Here we review the known data on non-celestial polarization vision from different insect species (dragonflies, butterflies, beetles, bugs and flies) and present three well-characterized examples for functionally specialized non-DRA detectors from different insects that seem perfectly suited for mediating such behaviors. Finally, using recent advances from circuit dissection in Drosophila melanogaster, we discuss what types of potential candidate neurons could be involved in forming the underlying neural circuitry mediating non-celestial polarization vision. PMID:29615868

[Not Available].

PubMed

Pecevski, Dejan; Natschläger, Thomas; Schuch, Klaus

2009-01-01

The Parallel Circuit SIMulator (PCSIM) is a software package for simulation of neural circuits. It is primarily designed for distributed simulation of large scale networks of spiking point neurons. Although its computational core is written in C++, PCSIM's primary interface is implemented in the Python programming language, which is a powerful programming environment and allows the user to easily integrate the neural circuit simulator with data analysis and visualization tools to manage the full neural modeling life cycle. The main focus of this paper is to describe PCSIM's full integration into Python and the benefits thereof. In particular we will investigate how the automatically generated bidirectional interface and PCSIM's object-oriented modular framework enable the user to adopt a hybrid modeling approach: using and extending PCSIM's functionality either employing pure Python or C++ and thus combining the advantages of both worlds. Furthermore, we describe several supplementary PCSIM packages written in pure Python and tailored towards setting up and analyzing neural simulations.

Neural circuits and motivational processes for hunger

PubMed Central

Sternson, Scott M; Betley, J Nicholas; Huang Cao, Zhen Fang

2014-01-01

How does an organism’s internal state direct its actions? At one moment an animal forages for food with acrobatic feats such as tree climbing and jumping between branches. At another time, it travels along the ground to find water or a mate, exposing itself to predators along the way. These behaviors are costly in terms of energy or physical risk, and the likelihood of performing one set of actions relative to another is strongly modulated by internal state. For example, an animal in energy deficit searches for food and a dehydrated animal looks for water. The crosstalk between physiological state and motivational processes influences behavioral intensity and intent, but the underlying neural circuits are poorly understood. Molecular genetics along with optogenetic and pharmacogenetic tools for perturbing neuron function have enabled cell type-selective dissection of circuits that mediate behavioral responses to physiological state changes. Here, we review recent progress into neural circuit analysis of hunger in the mouse by focusing on a starvation-sensitive neuron population in the hypothalamus that is sufficient to promote voracious eating. We also consider research into the motivational processes that are thought to underlie hunger in order to outline considerations for bridging the gap between homeostatic and motivational neural circuits. PMID:23648085

Neural correlates underlying micrographia in Parkinson’s disease

PubMed Central

Zhang, Jiarong; Hallett, Mark; Feng, Tao; Hou, Yanan; Chan, Piu

2016-01-01

Micrographia is a common symptom in Parkinson’s disease, which manifests as either a consistent or progressive reduction in the size of handwriting or both. Neural correlates underlying micrographia remain unclear. We used functional magnetic resonance imaging to investigate micrographia-related neural activity and connectivity modulations. In addition, the effect of attention and dopaminergic administration on micrographia was examined. We found that consistent micrographia was associated with decreased activity and connectivity in the basal ganglia motor circuit; while progressive micrographia was related to the dysfunction of basal ganglia motor circuit together with disconnections between the rostral supplementary motor area, rostral cingulate motor area and cerebellum. Attention significantly improved both consistent and progressive micrographia, accompanied by recruitment of anterior putamen and dorsolateral prefrontal cortex. Levodopa improved consistent micrographia accompanied by increased activity and connectivity in the basal ganglia motor circuit, but had no effect on progressive micrographia. Our findings suggest that consistent micrographia is related to dysfunction of the basal ganglia motor circuit; while dysfunction of the basal ganglia motor circuit and disconnection between the rostral supplementary motor area, rostral cingulate motor area and cerebellum likely contributes to progressive micrographia. Attention improves both types of micrographia by recruiting additional brain networks. Levodopa improves consistent micrographia by restoring the function of the basal ganglia motor circuit, but does not improve progressive micrographia, probably because of failure to repair the disconnected networks. PMID:26525918

A tale of two species: neural integration in zebrafish and monkeys

PubMed Central

Joshua, Mati; Lisberger, Stephen G.

2014-01-01

Selection of a model organism creates a tension between competing constraints. The recent explosion of modern molecular techniques has revolutionized the analysis of neural systems in organisms that are amenable to genetic techniques. Yet, the non-human primate remains the gold-standard for the analysis of the neural basis of behavior, and as a bridge to the operation of the human brain. The challenge is to generalize across species in a way that exposes the operation of circuits as well as the relationship of circuits to behavior. Eye movements provide an opportunity to cross the bridge from mechanism to behavior through research on diverse species. Here, we review experiments and computational studies on a circuit function called “neural integration” that occurs in the brainstems of larval zebrafish, non-human primates, and species “in between”. We show that analysis of circuit structure using modern molecular and imaging approaches in zebrafish has remarkable explanatory power for the details of the responses of integrator neurons in the monkey. The combination of research from the two species has led to a much stronger hypothesis for the implementation of the neural integrator than could have been achieved using either species alone. PMID:24797331

A tale of two species: Neural integration in zebrafish and monkeys.

PubMed

Joshua, M; Lisberger, S G

2015-06-18

Selection of a model organism creates tension between competing constraints. The recent explosion of modern molecular techniques has revolutionized the analysis of neural systems in organisms that are amenable to genetic techniques. Yet, the non-human primate remains the gold-standard for the analysis of the neural basis of behavior, and as a bridge to the operation of the human brain. The challenge is to generalize across species in a way that exposes the operation of circuits as well as the relationship of circuits to behavior. Eye movements provide an opportunity to cross the bridge from mechanism to behavior through research on diverse species. Here, we review experiments and computational studies on a circuit function called "neural integration" that occurs in the brainstems of larval zebrafish, primates, and species "in between". We show that analysis of circuit structure using modern molecular and imaging approaches in zebrafish has remarkable explanatory power for details of the responses of integrator neurons in the monkey. The combination of research from the two species has led to a much stronger hypothesis for the implementation of the neural integrator than could have been achieved using either species alone. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

Shared neural circuits for mentalizing about the self and others.

PubMed

Lombardo, Michael V; Chakrabarti, Bhismadev; Bullmore, Edward T; Wheelwright, Sally J; Sadek, Susan A; Suckling, John; Baron-Cohen, Simon

2010-07-01

Although many examples exist for shared neural representations of self and other, it is unknown how such shared representations interact with the rest of the brain. Furthermore, do high-level inference-based shared mentalizing representations interact with lower level embodied/simulation-based shared representations? We used functional neuroimaging (fMRI) and a functional connectivity approach to assess these questions during high-level inference-based mentalizing. Shared mentalizing representations in ventromedial prefrontal cortex, posterior cingulate/precuneus, and temporo-parietal junction (TPJ) all exhibited identical functional connectivity patterns during mentalizing of both self and other. Connectivity patterns were distributed across low-level embodied neural systems such as the frontal operculum/ventral premotor cortex, the anterior insula, the primary sensorimotor cortex, and the presupplementary motor area. These results demonstrate that identical neural circuits are implementing processes involved in mentalizing of both self and other and that the nature of such processes may be the integration of low-level embodied processes within higher level inference-based mentalizing.

The Neural Circuits that Generate Tics in Gilles de la Tourette Syndrome

PubMed Central

Wang, Zhishun; Maia, Tiago V.; Marsh, Rachel; Colibazzi, Tiziano; Gerber, Andrew; Peterson, Bradley S.

2014-01-01

Objective To study neural activity and connectivity within cortico-striato-thalamo-cortical circuits and to reveal circuit-based neural mechanisms that govern tic generation in Tourette syndrome. Method We acquired fMRI data from 13 participants with Tourette syndrome and 21 controls during spontaneous or simulated tics. We used independent component analysis with hierarchical partner matching to isolate neural activity within functionally distinct regions of cortico-striato-thalamo-cortical circuits. We used Granger causality to investigate causal interactions among these regions. Results We found that the Tourette group exhibited stronger neural activity and interregional causality than controls throughout all portions of the motor pathway including sensorimotor cortex, putamen, pallidum, and substania nigra. Activity in these areas correlated positively with the severity of tic symptoms. Activity within the Tourette group was stronger during spontaneous tics than during voluntary tics in somatosensory and posterior parietal cortices, putamen, and amygdala/hippocampus complex, suggesting that activity in these regions may represent features of the premonitory urges that generate spontaneous tic behaviors. In contrast, activity was weaker in the Tourette group than in controls within portions of cortico-striato-thalamo-cortical circuits that exert top-down control over motor pathways (caudate and anterior cingulate cortex), and progressively less activity in these regions accompanied more severe tic symptoms, suggesting that faulty activity in these circuits may fail to control tic behaviors or the premonitory urges that generate them. Conclusions Our findings taken together suggest that tics are caused by the combined effects of excessive activity in motor pathways and reduced activation in control portions of cortico-striato-thalamo-cortical circuits. PMID:21955933

An ultra low-power CMOS automatic action potential detector.

PubMed

Gosselin, Benoit; Sawan, Mohamad

2009-08-01

We present a low-power complementary metal-oxide semiconductor (CMOS) analog integrated biopotential detector intended for neural recording in wireless multichannel implants. The proposed detector can achieve accurate automatic discrimination of action potential (APs) from the background activity by means of an energy-based preprocessor and a linear delay element. This strategy improves detected waveforms integrity and prompts for better performance in neural prostheses. The delay element is implemented with a low-power continuous-time filter using a ninth-order equiripple allpass transfer function. All circuit building blocks use subthreshold OTAs employing dedicated circuit techniques for achieving ultra low-power and high dynamic range. The proposed circuit function in the submicrowatt range as the implemented CMOS 0.18- microm chip dissipates 780 nW, and it features a size of 0.07 mm(2). So it is suitable for massive integration in a multichannel device with modest overhead. The fabricated detector succeeds to automatically detect APs from underlying background activity. Testbench validation results obtained with synthetic neural waveforms are presented.

Resting-State Functional Connectivity in the Human Connectome Project: Current Status and Relevance to Understanding Psychopathology.

PubMed

Barch, Deanna M

A key tenet of modern psychiatry is that psychiatric disorders arise from abnormalities in brain circuits that support human behavior. Our ability to examine hypotheses around circuit-level abnormalities in psychiatric disorders has been made possible by advances in human neuroimaging technologies. These advances have provided the basis for recent efforts to develop a more complex understanding of the function of brain circuits in health and of their relationship to behavior-providing, in turn, a foundation for our understanding of how disruptions in such circuits contribute to the development of psychiatric disorders. This review focuses on the use of resting-state functional connectivity MRI to assess brain circuits, on the advances generated by the Human Connectome Project, and on how these advances potentially contribute to understanding neural circuit dysfunction in psychopathology. The review gives particular attention to the methods developed by the Human Connectome Project that may be especially relevant to studies of psychopathology; it outlines some of the key findings about what constitutes a brain region; and it highlights new information about the nature and stability of brain circuits. Some of the Human Connectome Project's new findings particularly relevant to psychopathology-about neural circuits and their relationships to behavior-are also presented. The review ends by discussing the extension of Human Connectome Project methods across the lifespan and into manifest illness. Potential treatment implications are also considered.

Grand Research Plan for Neural Circuits of Emotion and Memory--current status of neural circuit studies in China.

PubMed

Zhu, Yuan-Gui; Cao, He-Qi; Dong, Er-Dan

2013-02-01

During recent years, major advances have been made in neuroscience, i.e., asynchronous release, three-dimensional structural data sets, saliency maps, magnesium in brain research, and new functional roles of long non-coding RNAs. Especially, the development of optogenetic technology provides access to important information about relevant neural circuits by allowing the activation of specific neurons in awake mammals and directly observing the resulting behavior. The Grand Research Plan for Neural Circuits of Emotion and Memory was launched by the National Natural Science Foundation of China. It takes emotion and memory as its main objects, making the best use of cutting-edge technologies from medical science, life science and information science. In this paper, we outline the current status of neural circuit studies in China and the technologies and methodologies being applied, as well as studies related to the impairments of emotion and memory. In this phase, we are making efforts to repair the current deficiencies by making adjustments, mainly involving four aspects of core scientific issues to investigate these circuits at multiple levels. Five research directions have been taken to solve important scientific problems while the Grand Research Plan is implemented. Future research into this area will be multimodal, incorporating a range of methods and sciences into each project. Addressing these issues will ensure a bright future, major discoveries, and a higher level of treatment for all affected by debilitating brain illnesses.

Amigo adhesion protein regulates development of neural circuits in zebrafish brain.

PubMed

Zhao, Xiang; Kuja-Panula, Juha; Sundvik, Maria; Chen, Yu-Chia; Aho, Vilma; Peltola, Marjaana A; Porkka-Heiskanen, Tarja; Panula, Pertti; Rauvala, Heikki

2014-07-18

The Amigo protein family consists of three transmembrane proteins characterized by six leucine-rich repeat domains and one immunoglobulin-like domain in their extracellular moieties. Previous in vitro studies have suggested a role as homophilic adhesion molecules in brain neurons, but the in vivo functions remain unknown. Here we have cloned all three zebrafish amigos and show that amigo1 is the predominant family member expressed during nervous system development in zebrafish. Knockdown of amigo1 expression using morpholino oligonucleotides impairs the formation of fasciculated tracts in early fiber scaffolds of brain. A similar defect in fiber tract development is caused by mRNA-mediated expression of the Amigo1 ectodomain that inhibits adhesion mediated by the full-length protein. Analysis of differentiated neural circuits reveals defects in the catecholaminergic system. At the behavioral level, the disturbed formation of neural circuitry is reflected in enhanced locomotor activity and in the inability of the larvae to perform normal escape responses. We suggest that Amigo1 is essential for the development of neural circuits of zebrafish, where its mechanism involves homophilic interactions within the developing fiber tracts and regulation of the Kv2.1 potassium channel to form functional neural circuitry that controls locomotion. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

Emergence of binocular functional properties in a monocular neural circuit

PubMed Central

Ramdya, Pavan; Engert, Florian

2010-01-01

Sensory circuits frequently integrate converging inputs while maintaining precise functional relationships between them. For example, in mammals with stereopsis, neurons at the first stages of binocular visual processing show a close alignment of receptive-field properties for each eye. Still, basic questions about the global wiring mechanisms that enable this functional alignment remain unanswered, including whether the addition of a second retinal input to an otherwise monocular neural circuit is sufficient for the emergence of these binocular properties. We addressed this question by inducing a de novo binocular retinal projection to the larval zebrafish optic tectum and examining recipient neuronal populations using in vivo two-photon calcium imaging. Notably, neurons in rewired tecta were predominantly binocular and showed matching direction selectivity for each eye. We found that a model based on local inhibitory circuitry that computes direction selectivity using the topographic structure of both retinal inputs can account for the emergence of this binocular feature. PMID:19160507

Non-overlapping Neural Networks in Hydra vulgaris.

PubMed

Dupre, Christophe; Yuste, Rafael

2017-04-24

To understand the emergent properties of neural circuits, it would be ideal to record the activity of every neuron in a behaving animal and decode how it relates to behavior. We have achieved this with the cnidarian Hydra vulgaris, using calcium imaging of genetically engineered animals to measure the activity of essentially all of its neurons. Although the nervous system of Hydra is traditionally described as a simple nerve net, we surprisingly find instead a series of functional networks that are anatomically non-overlapping and are associated with specific behaviors. Three major functional networks extend through the entire animal and are activated selectively during longitudinal contractions, elongations in response to light, and radial contractions, whereas an additional network is located near the hypostome and is active during nodding. These results demonstrate the functional sophistication of apparently simple nerve nets, and the potential of Hydra and other basal metazoans as a model system for neural circuit studies. Published by Elsevier Ltd.

Neural Control of the Lower Urinary Tract

PubMed Central

de Groat, William C.; Griffiths, Derek; Yoshimura, Naoki

2015-01-01

This article summarizes anatomical, neurophysiological, pharmacological, and brain imaging studies in humans and animals that have provided insights into the neural circuitry and neurotransmitter mechanisms controlling the lower urinary tract. The functions of the lower urinary tract to store and periodically eliminate urine are regulated by a complex neural control system in the brain, spinal cord, and peripheral autonomic ganglia that coordinates the activity of smooth and striated muscles of the bladder and urethral outlet. The neural control of micturition is organized as a hierarchical system in which spinal storage mechanisms are in turn regulated by circuitry in the rostral brain stem that initiates reflex voiding. Input from the forebrain triggers voluntary voiding by modulating the brain stem circuitry. Many neural circuits controlling the lower urinary tract exhibit switch-like patterns of activity that turn on and off in an all-or-none manner. The major component of the micturition switching circuit is a spinobulbospinal parasympathetic reflex pathway that has essential connections in the periaqueductal gray and pontine micturition center. A computer model of this circuit that mimics the switching functions of the bladder and urethra at the onset of micturition is described. Micturition occurs involuntarily in infants and young children until the age of 3 to 5 years, after which it is regulated voluntarily. Diseases or injuries of the nervous system in adults can cause the re-emergence of involuntary micturition, leading to urinary incontinence. Neuroplasticity underlying these developmental and pathological changes in voiding function is discussed. PMID:25589273

Auto-programmable impulse neural circuits

NASA Technical Reports Server (NTRS)

Watula, D.; Meador, J.

1990-01-01

Impulse neural networks use pulse trains to communicate neuron activation levels. Impulse neural circuits emulate natural neurons at a more detailed level than that typically employed by contemporary neural network implementation methods. An impulse neural circuit which realizes short term memory dynamics is presented. The operation of that circuit is then characterized in terms of pulse frequency modulated signals. Both fixed and programmable synapse circuits for realizing long term memory are also described. The implementation of a simple and useful unsupervised learning law is then presented. The implementation of a differential Hebbian learning rule for a specific mean-frequency signal interpretation is shown to have a straightforward implementation using digital combinational logic with a variation of a previously developed programmable synapse circuit. This circuit is expected to be exploited for simple and straightforward implementation of future auto-adaptive neural circuits.

A structural and a functional aspect of stable information processing by the brain

PubMed Central

2007-01-01

Brain is an expert in producing the same output from a particular set of inputs, even from a very noisy environment. In this article a model of neural circuit in the brain has been proposed which is composed of cyclic sub-circuits. A big loop has been defined to be consisting of a feed forward path from the sensory neurons to the highest processing area of the brain and feed back paths from that region back up to close to the same sensory neurons. It has been mathematically shown how some smaller cycles can amplify signal. A big loop processes information by contrast and amplify principle. How a pair of presynaptic and postsynaptic neurons can be identified by an exact synchronization detection method has also been mentioned. It has been assumed that the spike train coming out of a firing neuron encodes all the information produced by it as output. It is possible to extract this information over a period of time by Fourier transforms. The Fourier coefficients arranged in a vector form will uniquely represent the neural spike train over a period of time. The information emanating out of all the neurons in a given neural circuit over a period of time can be represented by a collection of points in a multidimensional vector space. This cluster of points represents the functional or behavioral form of the neural circuit. It has been proposed that a particular cluster of vectors as the representation of a new behavior is chosen by the brain interactively with respect to the memory stored in that circuit and the amount of emotion involved. It has been proposed that in this situation a Coulomb force like expression governs the dynamics of functioning of the circuit and stability of the system is reached at the minimum of all the minima of a potential function derived from the force like expression. The calculations have been done with respect to a pseudometric defined in a multidimensional vector space. PMID:19003500

Brain-derived neurotrophic factor and addiction: Pathological versus therapeutic effects on drug seeking

PubMed Central

Barker, Jacqueline M.; Taylor, Jane R.; De Vries, Taco J.; Peters, Jamie

2015-01-01

Many abused drugs lead to changes in endogenous brain-derived neurotrophic factor (BDNF) expression in neural circuits responsible for addictive behaviors. BDNF is a known molecular mediator of memory consolidation processes, evident at both behavioral and neurophysiological levels. Specific neural circuits are responsible for storing and executing drug-procuring motor programs, whereas other neural circuits are responsible for the active suppression of these “seeking” systems. These seeking-circuits are established as associations are formed between drug-associated cues and the conditioned responses they elicit. Such conditioned responses (e.g. drug seeking) can be diminished either through a passive weakening of seeking-circuits or an active suppression of those circuits through extinction. Extinction learning occurs when the association between cues and drug are violated, for example, by cue exposure without the drug present. Cue exposure therapy has been proposed as a therapeutic avenue for the treatment of addictions. Here we explore the role of BDNF in extinction circuits, compared to seeking-circuits that “incubate” over prolonged withdrawal periods. We begin by discussing the role of BDNF in extinction memory for fear and cocaine-seeking behaviors, where extinction circuits overlap in infralimbic prefrontal cortex (PFC). We highlight the ability of estrogen to promote BDNF-like effects in hippocampal–prefrontal circuits and consider the role of sex differences in extinction and incubation of drug-seeking behaviors. Finally, we examine how opiates and alcohol “break the mold” in terms of BDNF function in extinction circuits. PMID:25451116

Optogenetic rewiring of thalamocortical circuits to restore function in the stroke injured brain

PubMed Central

Tennant, Kelly A.; Taylor, Stephanie L.; White, Emily R.; Brown, Craig E.

2017-01-01

To regain sensorimotor functions after stroke, surviving neural circuits must reorganize and form new connections. Although the thalamus is critical for processing and relaying sensory information to the cortex, little is known about how stroke affects the structure and function of these connections, or whether a therapeutic approach targeting these circuits can improve recovery. Here we reveal with in vivo calcium imaging that stroke in somatosensory cortex dampens the excitability of surviving thalamocortical circuits. Given this deficit, we hypothesized that chronic transcranial window optogenetic stimulation of thalamocortical axons could facilitate recovery. Using two-photon imaging, we show that optogenetic stimulation promotes the formation of new and stable thalamocortical synaptic boutons, without impacting axon branch dynamics. Stimulation also enhances the recovery of somatosensory cortical circuit function and forepaw sensorimotor abilities. These results demonstrate that an optogenetic approach can rewire thalamocortical circuits and restore function in the damaged brain. PMID:28643802

Neurotrophic actions of dopamine on the development of a serotonergic feeding circuit in Drosophila melanogaster

PubMed Central

2012-01-01

Background In the fruit fly, Drosophila melanogaster, serotonin functions both as a neurotransmitter to regulate larval feeding, and in the development of the stomatogastric feeding circuit. There is an inverse relationship between neuronal serotonin levels during late embryogenesis and the complexity of the serotonergic fibers projecting from the larval brain to the foregut, which correlate with perturbations in feeding, the functional output of the circuit. Dopamine does not modulate larval feeding, and dopaminergic fibers do not innervate the larval foregut. Since dopamine can function in central nervous system development, separate from its role as a neurotransmitter, the role of neuronal dopamine was assessed on the development, and mature function, of the 5-HT larval feeding circuit. Results Both decreased and increased neuronal dopamine levels in late embryogenesis during development of this circuit result in depressed levels of larval feeding. Perturbations in neuronal dopamine during this developmental period also result in greater branch complexity of the serotonergic fibers innervating the gut, as well as increased size and number of the serotonin-containing vesicles along the neurite length. This neurotrophic action for dopamine is modulated by the D2 dopamine receptor expressed during late embryogenesis in central 5-HT neurons. Animals carrying transgenic RNAi constructs to knock down both dopamine and serotonin synthesis in the central nervous system display normal feeding and fiber architecture. However, disparate levels of neuronal dopamine and serotonin during development of the circuit result in abnormal gut fiber architecture and feeding behavior. Conclusions These results suggest that dopamine can exert a direct trophic influence on the development of a specific neural circuit, and that dopamine and serotonin may interact with each other to generate the neural architecture necessary for normal function of the circuit. PMID:22413901

Neural circuit activity in freely behaving zebrafish (Danio rerio).

PubMed

Issa, Fadi A; O'Brien, Georgeann; Kettunen, Petronella; Sagasti, Alvaro; Glanzman, David L; Papazian, Diane M

2011-03-15

Examining neuronal network activity in freely behaving animals is advantageous for probing the function of the vertebrate central nervous system. Here, we describe a simple, robust technique for monitoring the activity of neural circuits in unfettered, freely behaving zebrafish (Danio rerio). Zebrafish respond to unexpected tactile stimuli with short- or long-latency escape behaviors, which are mediated by distinct neural circuits. Using dipole electrodes immersed in the aquarium, we measured electric field potentials generated in muscle during short- and long-latency escapes. We found that activation of the underlying neural circuits produced unique field potential signatures that are easily recognized and can be repeatedly monitored. In conjunction with behavioral analysis, we used this technique to track changes in the pattern of circuit activation during the first week of development in animals whose trigeminal sensory neurons were unilaterally ablated. One day post-ablation, the frequency of short- and long-latency responses was significantly lower on the ablated side than on the intact side. Three days post-ablation, a significant fraction of escapes evoked by stimuli on the ablated side was improperly executed, with the animal turning towards rather than away from the stimulus. However, the overall response rate remained low. Seven days post-ablation, the frequency of escapes increased dramatically and the percentage of improperly executed escapes declined. Our results demonstrate that trigeminal ablation results in rapid reconfiguration of the escape circuitry, with reinnervation by new sensory neurons and adaptive changes in behavior. This technique is valuable for probing the activity, development, plasticity and regeneration of neural circuits under natural conditions.

Neural circuit activity in freely behaving zebrafish (Danio rerio)

PubMed Central

Issa, Fadi A.; O'Brien, Georgeann; Kettunen, Petronella; Sagasti, Alvaro; Glanzman, David L.; Papazian, Diane M.

2011-01-01

Examining neuronal network activity in freely behaving animals is advantageous for probing the function of the vertebrate central nervous system. Here, we describe a simple, robust technique for monitoring the activity of neural circuits in unfettered, freely behaving zebrafish (Danio rerio). Zebrafish respond to unexpected tactile stimuli with short- or long-latency escape behaviors, which are mediated by distinct neural circuits. Using dipole electrodes immersed in the aquarium, we measured electric field potentials generated in muscle during short- and long-latency escapes. We found that activation of the underlying neural circuits produced unique field potential signatures that are easily recognized and can be repeatedly monitored. In conjunction with behavioral analysis, we used this technique to track changes in the pattern of circuit activation during the first week of development in animals whose trigeminal sensory neurons were unilaterally ablated. One day post-ablation, the frequency of short- and long-latency responses was significantly lower on the ablated side than on the intact side. Three days post-ablation, a significant fraction of escapes evoked by stimuli on the ablated side was improperly executed, with the animal turning towards rather than away from the stimulus. However, the overall response rate remained low. Seven days post-ablation, the frequency of escapes increased dramatically and the percentage of improperly executed escapes declined. Our results demonstrate that trigeminal ablation results in rapid reconfiguration of the escape circuitry, with reinnervation by new sensory neurons and adaptive changes in behavior. This technique is valuable for probing the activity, development, plasticity and regeneration of neural circuits under natural conditions. PMID:21346131

From circuits to behaviour in the amygdala

PubMed Central

Janak, Patricia H.; Tye, Kay M.

2015-01-01

The amygdala has long been associated with emotion and motivation, playing an essential part in processing both fearful and rewarding environmental stimuli. How can a single structure be crucial for such different functions? With recent technological advances that allow for causal investigations of specific neural circuit elements, we can now begin to map the complex anatomical connections of the amygdala onto behavioural function. Understanding how the amygdala contributes to a wide array of behaviours requires the study of distinct amygdala circuits. PMID:25592533

Top-Down Modulation on Perceptual Decision with Balanced Inhibition through Feedforward and Feedback Inhibitory Neurons

PubMed Central

Wang, Cheng-Te; Lee, Chung-Ting; Wang, Xiao-Jing; Lo, Chung-Chuan

2013-01-01

Recent physiological studies have shown that neurons in various regions of the central nervous systems continuously receive noisy excitatory and inhibitory synaptic inputs in a balanced and covaried fashion. While this balanced synaptic input (BSI) is typically described in terms of maintaining the stability of neural circuits, a number of experimental and theoretical studies have suggested that BSI plays a proactive role in brain functions such as top-down modulation for executive control. Two issues have remained unclear in this picture. First, given the noisy nature of neuronal activities in neural circuits, how do the modulatory effects change if the top-down control implements BSI with different ratios between inhibition and excitation? Second, how is a top-down BSI realized via only excitatory long-range projections in the neocortex? To address the first issue, we systematically tested how the inhibition/excitation ratio affects the accuracy and reaction times of a spiking neural circuit model of perceptual decision. We defined an energy function to characterize the network dynamics, and found that different ratios modulate the energy function of the circuit differently and form two distinct functional modes. To address the second issue, we tested BSI with long-distance projection to inhibitory neurons that are either feedforward or feedback, depending on whether these inhibitory neurons do or do not receive inputs from local excitatory cells, respectively. We found that BSI occurs in both cases. Furthermore, when relying on feedback inhibitory neurons, through the recurrent interactions inside the circuit, BSI dynamically and automatically speeds up the decision by gradually reducing its inhibitory component in the course of a trial when a decision process takes too long. PMID:23626812

Top-down modulation on perceptual decision with balanced inhibition through feedforward and feedback inhibitory neurons.

PubMed

Wang, Cheng-Te; Lee, Chung-Ting; Wang, Xiao-Jing; Lo, Chung-Chuan

2013-01-01

Recent physiological studies have shown that neurons in various regions of the central nervous systems continuously receive noisy excitatory and inhibitory synaptic inputs in a balanced and covaried fashion. While this balanced synaptic input (BSI) is typically described in terms of maintaining the stability of neural circuits, a number of experimental and theoretical studies have suggested that BSI plays a proactive role in brain functions such as top-down modulation for executive control. Two issues have remained unclear in this picture. First, given the noisy nature of neuronal activities in neural circuits, how do the modulatory effects change if the top-down control implements BSI with different ratios between inhibition and excitation? Second, how is a top-down BSI realized via only excitatory long-range projections in the neocortex? To address the first issue, we systematically tested how the inhibition/excitation ratio affects the accuracy and reaction times of a spiking neural circuit model of perceptual decision. We defined an energy function to characterize the network dynamics, and found that different ratios modulate the energy function of the circuit differently and form two distinct functional modes. To address the second issue, we tested BSI with long-distance projection to inhibitory neurons that are either feedforward or feedback, depending on whether these inhibitory neurons do or do not receive inputs from local excitatory cells, respectively. We found that BSI occurs in both cases. Furthermore, when relying on feedback inhibitory neurons, through the recurrent interactions inside the circuit, BSI dynamically and automatically speeds up the decision by gradually reducing its inhibitory component in the course of a trial when a decision process takes too long.

Cortical–Subcortical Interactions in Hypersomnia Disorders: Mechanisms Underlying Cognitive and Behavioral Aspects of the Sleep–Wake Cycle

PubMed Central

Larson-Prior, Linda J.; Ju, Yo-El; Galvin, James E.

2014-01-01

Subcortical circuits mediating sleep–wake functions have been well characterized in animal models, and corroborated by more recent human studies. Disruptions in these circuits have been identified in hypersomnia disorders (HDs) such as narcolepsy and Kleine–Levin Syndrome, as well as in neurodegenerative disorders expressing excessive daytime sleepiness. However, the behavioral expression of sleep–wake functions is not a simple on-or-off state determined by subcortical circuits, but encompasses a complex range of behaviors determined by the interaction between cortical networks and subcortical circuits. While conceived as disorders of sleep, HDs are equally disorders of wake, representing a fundamental instability in neural state characterized by lapses of alertness during wake. These episodic lapses in alertness and wakefulness are also frequently seen in neurodegenerative disorders where electroencephalogram demonstrates abnormal function in cortical regions associated with cognitive fluctuations (CFs). Moreover, functional connectivity MRI shows instability of cortical networks in individuals with CFs. We propose that the inability to stabilize neural state due to disruptions in the sleep–wake control networks is common to the sleep and cognitive dysfunctions seen in hypersomnia and neurodegenerative disorders. PMID:25309500

Neuromorphic Implementation of Attractor Dynamics in a Two-Variable Winner-Take-All Circuit with NMDARs: A Simulation Study

PubMed Central

You, Hongzhi; Wang, Da-Hui

2017-01-01

Neural networks configured with winner-take-all (WTA) competition and N-methyl-D-aspartate receptor (NMDAR)-mediated synaptic dynamics are endowed with various dynamic characteristics of attractors underlying many cognitive functions. This paper presents a novel method for neuromorphic implementation of a two-variable WTA circuit with NMDARs aimed at implementing decision-making, working memory and hysteresis in visual perceptions. The method proposed is a dynamical system approach of circuit synthesis based on a biophysically plausible WTA model. Notably, slow and non-linear temporal dynamics of NMDAR-mediated synapses was generated. Circuit simulations in Cadence reproduced ramping neural activities observed in electrophysiological recordings in experiments of decision-making, the sustained activities observed in the prefrontal cortex during working memory, and classical hysteresis behavior during visual discrimination tasks. Furthermore, theoretical analysis of the dynamical system approach illuminated the underlying mechanisms of decision-making, memory capacity and hysteresis loops. The consistence between the circuit simulations and theoretical analysis demonstrated that the WTA circuit with NMDARs was able to capture the attractor dynamics underlying these cognitive functions. Their physical implementations as elementary modules are promising for assembly into integrated neuromorphic cognitive systems. PMID:28223913

Neuromorphic Implementation of Attractor Dynamics in a Two-Variable Winner-Take-All Circuit with NMDARs: A Simulation Study.

PubMed

You, Hongzhi; Wang, Da-Hui

2017-01-01

Neural networks configured with winner-take-all (WTA) competition and N-methyl-D-aspartate receptor (NMDAR)-mediated synaptic dynamics are endowed with various dynamic characteristics of attractors underlying many cognitive functions. This paper presents a novel method for neuromorphic implementation of a two-variable WTA circuit with NMDARs aimed at implementing decision-making, working memory and hysteresis in visual perceptions. The method proposed is a dynamical system approach of circuit synthesis based on a biophysically plausible WTA model. Notably, slow and non-linear temporal dynamics of NMDAR-mediated synapses was generated. Circuit simulations in Cadence reproduced ramping neural activities observed in electrophysiological recordings in experiments of decision-making, the sustained activities observed in the prefrontal cortex during working memory, and classical hysteresis behavior during visual discrimination tasks. Furthermore, theoretical analysis of the dynamical system approach illuminated the underlying mechanisms of decision-making, memory capacity and hysteresis loops. The consistence between the circuit simulations and theoretical analysis demonstrated that the WTA circuit with NMDARs was able to capture the attractor dynamics underlying these cognitive functions. Their physical implementations as elementary modules are promising for assembly into integrated neuromorphic cognitive systems.

Social Status-Dependent Shift in Neural Circuit Activation Affects Decision Making.

PubMed

Miller, Thomas H; Clements, Katie; Ahn, Sungwoo; Park, Choongseok; Hye Ji, Eoon; Issa, Fadi A

2017-02-22

In a social group, animals make behavioral decisions that fit their social ranks. These behavioral choices are dependent on the various social cues experienced during social interactions. In vertebrates, little is known of how social status affects the underlying neural mechanisms regulating decision-making circuits that drive competing behaviors. Here, we demonstrate that social status in zebrafish ( Danio rerio ) influences behavioral decisions by shifting the balance in neural circuit activation between two competing networks (escape and swim). We show that socially dominant animals enhance activation of the swim circuit. Conversely, social subordinates display a decreased activation of the swim circuit, but an enhanced activation of the escape circuit. In an effort to understand how social status mediates these effects, we constructed a neurocomputational model of the escape and swim circuits. The model replicates our findings and suggests that social status-related shift in circuit dynamics could be mediated by changes in the relative excitability of the escape and swim networks. Together, our results reveal that changes in the excitabilities of the Mauthner command neuron for escape and the inhibitory interneurons that regulate swimming provide a cellular mechanism for the nervous system to adapt to changes in social conditions by permitting the animal to select a socially appropriate behavioral response. SIGNIFICANCE STATEMENT Understanding how social factors influence nervous system function is of great importance. Using zebrafish as a model system, we demonstrate how social experience affects decision making to enable animals to produce socially appropriate behavior. Based on experimental evidence and computational modeling, we show that behavioral decisions reflect the interplay between competing neural circuits whose activation thresholds shift in accordance with social status. We demonstrate this through analysis of the behavior and neural circuit responses that drive escape and swim behaviors in fish. We show that socially subordinate animals favor escape over swimming, while socially dominants favor swimming over escape. We propose that these differences are mediated by shifts in relative circuit excitability. Copyright © 2017 the authors 0270-6474/17/372137-12$15.00/0.

Modeling neural circuits in Parkinson's disease.

PubMed

Psiha, Maria; Vlamos, Panayiotis

2015-01-01

Parkinson's disease (PD) is caused by abnormal neural activity of the basal ganglia which are connected to the cerebral cortex in the brain surface through complex neural circuits. For a better understanding of the pathophysiological mechanisms of PD, it is important to identify the underlying PD neural circuits, and to pinpoint the precise nature of the crucial aberrations in these circuits. In this paper, the general architecture of a hybrid Multilayer Perceptron (MLP) network for modeling the neural circuits in PD is presented. The main idea of the proposed approach is to divide the parkinsonian neural circuitry system into three discrete subsystems: the external stimuli subsystem, the life-threatening events subsystem, and the basal ganglia subsystem. The proposed model, which includes the key roles of brain neural circuit in PD, is based on both feed-back and feed-forward neural networks. Specifically, a three-layer MLP neural network with feedback in the second layer was designed. The feedback in the second layer of this model simulates the dopamine modulatory effect of compacta on striatum.

Distinct neural circuits for control of movement vs. holding still

PubMed Central

2017-01-01

In generating a point-to-point movement, the brain does more than produce the transient commands needed to move the body part; it also produces the sustained commands that are needed to hold the body part at its destination. In the oculomotor system, these functions are mapped onto two distinct circuits: a premotor circuit that specializes in generating the transient activity that displaces the eyes and a “neural integrator” that transforms that transient input into sustained activity that holds the eyes. Different parts of the cerebellum adaptively control the motor commands during these two phases: the oculomotor vermis participates in fine tuning the transient neural signals that move the eyes, monitoring the activity of the premotor circuit via efference copy, whereas the flocculus participates in controlling the sustained neural signals that hold the eyes, monitoring the activity of the neural integrator. Here, I review the oculomotor literature and then ask whether this separation of control between moving and holding is a design principle that may be shared with other modalities of movement. To answer this question, I consider neurophysiological and psychophysical data in various species during control of head movements, arm movements, and locomotion, focusing on the brain stem, motor cortex, and hippocampus, respectively. The review of the data raises the possibility that across modalities of motor control, circuits that are responsible for producing commands that change the sensory state of a body part are distinct from those that produce commands that maintain that sensory state. PMID:28053244

Reward and Aversion.

PubMed

Hu, Hailan

2016-07-08

To benefit from opportunities and cope with challenges in the environment, animals must adapt their behavior to acquire rewards and to avoid punishments. Maladaptive changes in the neuromodulatory systems and neural circuits for reward and aversion can lead to manifestation of several prominent psychiatric disorders including addiction and depression. Recent progress is pushing the boundaries of knowledge on two major fronts in research on reward and aversion: First, new layers of complexity have been reported on the functions of dopamine (DA) and serotonin (5-HT) neuromodulatory systems in reward and aversion. Second, specific circuit components in the neural pathways that encode reward and aversion have begun to be identified. This review aims to outline historic perspectives and new insights into the functions of DA and 5-HT systems in coding the distinct components of rewards. It also highlights recent advances in neural circuit studies enabled by new technologies, such as cell-type-specific electrophysiology and tracing, and optogenetics-based behavioral manipulation. This knowledge may provide guidance for developing novel treatment strategies for neuropsychiatric diseases related to the malfunction of the reward system.

Disrupted reward circuits is associated with cognitive deficits and depression severity in major depressive disorder.

PubMed

Gong, Liang; Yin, Yingying; He, Cancan; Ye, Qing; Bai, Feng; Yuan, Yonggui; Zhang, Haisan; Lv, Luxian; Zhang, Hongxing; Xie, Chunming; Zhang, Zhijun

2017-01-01

Neuroimaging studies have demonstrated that major depressive disorder (MDD) patients show blunted activity responses to reward-related tasks. However, whether abnormal reward circuits affect cognition and depression in MDD patients remains unclear. Seventy-five drug-naive MDD patients and 42 cognitively normal (CN) subjects underwent a resting-state functional magnetic resonance imaging scan. The bilateral nucleus accumbens (NAc) were selected as seeds to construct reward circuits across all subjects. A multivariate linear regression analysis was employed to investigate the neural substrates of cognitive function and depression severity on the reward circuits in MDD patients. The common pathway underlying cognitive deficits and depression was identified with conjunction analysis. Compared with CN subjects, MDD patients showed decreased reward network connectivity that was primarily located in the prefrontal-striatal regions. Importantly, distinct and common neural pathways underlying cognition and depression were identified, implying the independent and synergistic effects of cognitive deficits and depression severity on reward circuits. This study demonstrated that disrupted topological organization within reward circuits was significantly associated with cognitive deficits and depression severity in MDD patients. These findings suggest that in addition to antidepressant treatment, normalized reward circuits should be a focus and a target for improving depression and cognitive deficits in MDD patients. Copyright © 2016 Elsevier Ltd. All rights reserved.

Lighting up the brain's reward circuitry.

PubMed

Lobo, Mary Kay

2012-07-01

The brain's reward circuit is critical for mediating natural reward behaviors including food, sex, and social interaction. Drugs of abuse take over this circuit and produce persistent molecular and cellular alterations in the brain regions and their neural circuitry that make up the reward pathway. Recent use of optogenetic technologies has provided novel insights into the functional and molecular role of the circuitry and cell subtypes within these circuits that constitute this pathway. This perspective will address the current and future use of light-activated proteins, including those involved in modulating neuronal activity, cellular signaling, and molecular properties in the neural circuitry mediating rewarding stimuli and maladaptive responses to drugs of abuse. © 2012 New York Academy of Sciences.

A neural circuit mechanism for regulating vocal variability during song learning in zebra finches.

PubMed

Garst-Orozco, Jonathan; Babadi, Baktash; Ölveczky, Bence P

2014-12-15

Motor skill learning is characterized by improved performance and reduced motor variability. The neural mechanisms that couple skill level and variability, however, are not known. The zebra finch, a songbird, presents a unique opportunity to address this question because production of learned song and induction of vocal variability are instantiated in distinct circuits that converge on a motor cortex analogue controlling vocal output. To probe the interplay between learning and variability, we made intracellular recordings from neurons in this area, characterizing how their inputs from the functionally distinct pathways change throughout song development. We found that inputs that drive stereotyped song-patterns are strengthened and pruned, while inputs that induce variability remain unchanged. A simple network model showed that strengthening and pruning of action-specific connections reduces the sensitivity of motor control circuits to variable input and neural 'noise'. This identifies a simple and general mechanism for learning-related regulation of motor variability.

Pubertally born neurons and glia are functionally integrated into limbic and hypothalamic circuits of the male Syrian hamster.

PubMed

Mohr, Margaret A; Sisk, Cheryl L

2013-03-19

During puberty, the brain goes through extensive remodeling, involving the addition of new neurons and glia to brain regions beyond the canonical neurogenic regions (i.e., dentate gyrus and olfactory bulb), including limbic and hypothalamic cell groups associated with sex-typical behavior. Whether these pubertally born cells become functionally integrated into neural circuits remains unknown. To address this question, we gave male Syrian hamsters daily injections of the cell birthdate marker bromodeoxyuridine throughout puberty (postnatal day 28-49). Half of the animals were housed in enriched environments with access to a running wheel to determine whether enrichment increased the survival of pubertally born cells compared with the control environment. At 4 wk after the last BrdU injection, animals were allowed to interact with a receptive female and were then killed 1 h later. Triple-label immunofluorescence for BrdU, the mature neuron marker neuronal nuclear antigen, and the astrocytic marker glial fibrillary acidic protein revealed that a proportion of pubertally born cells in the medial preoptic area, arcuate nucleus, and medial amygdala differentiate into either mature neurons or astrocytes. Double-label immunofluorescence for BrdU and the protein Fos revealed that a subset of pubertally born cells in these regions is activated during sociosexual behavior, indicative of their functional incorporation into neural circuits. Enrichment affected the survival and activation of pubertally born cells in a brain region-specific manner. These results demonstrate that pubertally born cells located outside of the traditional neurogenic regions differentiate into neurons and glia and become functionally incorporated into neural circuits that subserve sex-typical behaviors.

From Molecular Circuit Dysfunction to Disease: Case Studies in Epilepsy, Traumatic Brain Injury, and Alzheimer’s Disease

PubMed Central

Dulla, Chris G.; Coulter, Douglas A.; Ziburkus, Jokubas

2015-01-01

Complex circuitry with feed-forward and feed-back systems regulate neuronal activity throughout the brain. Cell biological, electrical, and neurotransmitter systems enable neural networks to process and drive the entire spectrum of cognitive, behavioral, and motor functions. Simultaneous orchestration of distinct cells and interconnected neural circuits relies on hundreds, if not thousands, of unique molecular interactions. Even single molecule dysfunctions can be disrupting to neural circuit activity, leading to neurological pathology. Here, we sample our current understanding of how molecular aberrations lead to disruptions in networks using three neurological pathologies as exemplars: epilepsy, traumatic brain injury (TBI), and Alzheimer’s disease (AD). Epilepsy provides a window into how total destabilization of network balance can occur. TBI is an abrupt physical disruption that manifests in both acute and chronic neurological deficits. Last, in AD progressive cell loss leads to devastating cognitive consequences. Interestingly, all three of these neurological diseases are interrelated. The goal of this review, therefore, is to identify molecular changes that may lead to network dysfunction, elaborate on how altered network activity and circuit structure can contribute to neurological disease, and suggest common threads that may lie at the heart of molecular circuit dysfunction. PMID:25948650

From Molecular Circuit Dysfunction to Disease: Case Studies in Epilepsy, Traumatic Brain Injury, and Alzheimer's Disease.

PubMed

Dulla, Chris G; Coulter, Douglas A; Ziburkus, Jokubas

2016-06-01

Complex circuitry with feed-forward and feed-back systems regulate neuronal activity throughout the brain. Cell biological, electrical, and neurotransmitter systems enable neural networks to process and drive the entire spectrum of cognitive, behavioral, and motor functions. Simultaneous orchestration of distinct cells and interconnected neural circuits relies on hundreds, if not thousands, of unique molecular interactions. Even single molecule dysfunctions can be disrupting to neural circuit activity, leading to neurological pathology. Here, we sample our current understanding of how molecular aberrations lead to disruptions in networks using three neurological pathologies as exemplars: epilepsy, traumatic brain injury (TBI), and Alzheimer's disease (AD). Epilepsy provides a window into how total destabilization of network balance can occur. TBI is an abrupt physical disruption that manifests in both acute and chronic neurological deficits. Last, in AD progressive cell loss leads to devastating cognitive consequences. Interestingly, all three of these neurological diseases are interrelated. The goal of this review, therefore, is to identify molecular changes that may lead to network dysfunction, elaborate on how altered network activity and circuit structure can contribute to neurological disease, and suggest common threads that may lie at the heart of molecular circuit dysfunction. © The Author(s) 2015.

From biological neural networks to thinking machines: Transitioning biological organizational principles to computer technology

NASA Technical Reports Server (NTRS)

Ross, Muriel D.

1991-01-01

The three-dimensional organization of the vestibular macula is under study by computer assisted reconstruction and simulation methods as a model for more complex neural systems. One goal of this research is to transition knowledge of biological neural network architecture and functioning to computer technology, to contribute to the development of thinking computers. Maculas are organized as weighted neural networks for parallel distributed processing of information. The network is characterized by non-linearity of its terminal/receptive fields. Wiring appears to develop through constrained randomness. A further property is the presence of two main circuits, highly channeled and distributed modifying, that are connected through feedforward-feedback collaterals and biasing subcircuit. Computer simulations demonstrate that differences in geometry of the feedback (afferent) collaterals affects the timing and the magnitude of voltage changes delivered to the spike initiation zone. Feedforward (efferent) collaterals act as voltage followers and likely inhibit neurons of the distributed modifying circuit. These results illustrate the importance of feedforward-feedback loops, of timing, and of inhibition in refining neural network output. They also suggest that it is the distributed modifying network that is most involved in adaptation, memory, and learning. Tests of macular adaptation, through hyper- and microgravitational studies, support this hypothesis since synapses in the distributed modifying circuit, but not the channeled circuit, are altered. Transitioning knowledge of biological systems to computer technology, however, remains problematical.

Contemporary approaches to neural circuit manipulation and mapping: focus on reward and addiction

PubMed Central

Saunders, Benjamin T.; Richard, Jocelyn M.; Janak, Patricia H.

2015-01-01

Tying complex psychological processes to precisely defined neural circuits is a major goal of systems and behavioural neuroscience. This is critical for understanding adaptive behaviour, and also how neural systems are altered in states of psychopathology, such as addiction. Efforts to relate psychological processes relevant to addiction to activity within defined neural circuits have been complicated by neural heterogeneity. Recent advances in technology allow for manipulation and mapping of genetically and anatomically defined neurons, which when used in concert with sophisticated behavioural models, have the potential to provide great insight into neural circuit bases of behaviour. Here we discuss contemporary approaches for understanding reward and addiction, with a focus on midbrain dopamine and cortico-striato-pallidal circuits. PMID:26240425

Affective neural response to restricted interests in Autism Spectrum Disorders

PubMed Central

Cascio, Carissa J.; Foss-Feig, Jennifer H.; Heacock, Jessica; Schauder, Kimberly B.; Loring, Whitney A.; Rogers, Baxter P.; Pryweller, Jennifer R.; Newsom, Cassandra R.; Cockhren, Jurnell; Cao, Aize; Bolton, Scott

2013-01-01

Background Restricted interests are a class of repetitive behavior in autism spectrum disorders (ASD) whose intensity and narrow focus often contribute to significant interference with daily functioning. While numerous neuroimaging studies have investigated executive circuits as putative neural substrates of repetitive behavior, recent work implicates affective neural circuits in restricted interests. We sought to explore the role of affective neural circuits and determine how restricted interests are distinguished from hobbies or interests in typical development. Methods We compared a group of children with ASD to a typically developing (TD) group of children with strong interests or hobbies, employing parent report, an operant behavioral task, and functional imaging with personalized stimuli based on individual interests. Results While performance on the operant task was similar between the two groups, parent report of intensity and interference of interests was significantly higher in the ASD group. Both the ASD and TD groups showed increased BOLD response in widespread affective neural regions to pictures of their own interest. When viewing pictures of other children's interests, the TD group showed a similar pattern, whereas BOLD response in the ASD group was much more limited. Increased BOLD response in the insula and anterior cingulate cortex distinguished the ASD from the TD group, and parent report of the intensity and interference with daily life of the child's restricted interest predicted insula response. Conclusions While affective neural network response and operant behavior are comparable in typical and restricted interests, the narrowness of focus that clinically distinguishes restricted interests in ASD is reflected in more interference in daily life and aberrantly enhanced insula and anterior cingulate response to individuals’ own interests in the ASD group. These results further support the involvement of affective neural networks in repetitive behaviors in ASD. PMID:24117668

A dynamical systems approach for estimating phase interactions between rhythms of different frequencies from experimental data.

PubMed

Onojima, Takayuki; Goto, Takahiro; Mizuhara, Hiroaki; Aoyagi, Toshio

2018-01-01

Synchronization of neural oscillations as a mechanism of brain function is attracting increasing attention. Neural oscillation is a rhythmic neural activity that can be easily observed by noninvasive electroencephalography (EEG). Neural oscillations show the same frequency and cross-frequency synchronization for various cognitive and perceptual functions. However, it is unclear how this neural synchronization is achieved by a dynamical system. If neural oscillations are weakly coupled oscillators, the dynamics of neural synchronization can be described theoretically using a phase oscillator model. We propose an estimation method to identify the phase oscillator model from real data of cross-frequency synchronized activities. The proposed method can estimate the coupling function governing the properties of synchronization. Furthermore, we examine the reliability of the proposed method using time-series data obtained from numerical simulation and an electronic circuit experiment, and show that our method can estimate the coupling function correctly. Finally, we estimate the coupling function between EEG oscillation and the speech sound envelope, and discuss the validity of these results.

Homology and homoplasy of swimming behaviors and neural circuits in the Nudipleura (Mollusca, Gastropoda, Opisthobranchia)

PubMed Central

Newcomb, James M.; Sakurai, Akira; Lillvis, Joshua L.; Gunaratne, Charuni A.; Katz, Paul S.

2012-01-01

How neural circuit evolution relates to behavioral evolution is not well understood. Here the relationship between neural circuits and behavior is explored with respect to the swimming behaviors of the Nudipleura (Mollusca, Gastropoda, Opithobranchia). Nudipleura is a diverse monophyletic clade of sea slugs among which only a small percentage of species can swim. Swimming falls into a limited number of categories, the most prevalent of which are rhythmic left–right body flexions (LR) and rhythmic dorsal–ventral body flexions (DV). The phylogenetic distribution of these behaviors suggests a high degree of homoplasy. The central pattern generator (CPG) underlying DV swimming has been well characterized in Tritonia diomedea and in Pleurobranchaea californica. The CPG for LR swimming has been elucidated in Melibe leonina and Dendronotus iris, which are more closely related. The CPGs for the categorically distinct DV and LR swimming behaviors consist of nonoverlapping sets of homologous identified neurons, whereas the categorically similar behaviors share some homologous identified neurons, although the exact composition of neurons and synapses in the neural circuits differ. The roles played by homologous identified neurons in categorically distinct behaviors differ. However, homologous identified neurons also play different roles even in the swim CPGs of the two LR swimming species. Individual neurons can be multifunctional within a species. Some of those functions are shared across species, whereas others are not. The pattern of use and reuse of homologous neurons in various forms of swimming and other behaviors further demonstrates that the composition of neural circuits influences the evolution of behaviors. PMID:22723353

CMOS-micromachined, two-dimenisional transistor arrays for neural recording and stimulation.

PubMed

Lin, J S; Chang, S R; Chang, C H; Lu, S C; Chen, H

2007-01-01

In-plane microelectrode arrays have proven to be useful tools for studying the connectivities and the functions of neural tissues. However, seldom microelectrode arrays are monolithically-integrated with signal-processing circuits, without which the maximum number of electrodes is limited by the compromise with routing complexity and interferences. This paper proposes a CMOS-compatible, two-dimensional array of oxide-semiconductor field-effect transistors(OSFETs), capable of both recording and stimulating neuronal activities. The fabrication of the OSFETs not only requires simply die-level, post-CMOS micromachining process, but also retains metal layers for monolithic integration with signal-processing circuits. A CMOS microsystem containing the OSFET arrays and gain-programmable recording circuits has been fabricated and tested. The preliminary testing results are presented and discussed.

Model-based evaluation of the short-circuited tripolar cuff configuration.

PubMed

Andreasen, Lotte N S; Struijk, Johannes J

2006-05-01

Recordings of neural information for use as feedback in functional electrical stimulation are often contaminated with interfering signals from muscles and from stimulus pulses. The cuff electrode used for the neural recording can be optimized to improve the S/I ratio. In this work, we evaluate a model of both the nerve signal and the interfering signals recorded by a cuff, and subsequently use this model to study the signal to interference ratio of different cuff designs and to evaluate a recently introduced short-circuited tripolar cuff configuration. The results of the model showed good agreement with results from measurements in rabbits and confirmed the superior performance of the short-circuited tripolar configuration as compared with the traditionally used tripolar configuration.

A scalable neural chip with synaptic electronics using CMOS integrated memristors.

PubMed

Cruz-Albrecht, Jose M; Derosier, Timothy; Srinivasa, Narayan

2013-09-27

The design and simulation of a scalable neural chip with synaptic electronics using nanoscale memristors fully integrated with complementary metal-oxide-semiconductor (CMOS) is presented. The circuit consists of integrate-and-fire neurons and synapses with spike-timing dependent plasticity (STDP). The synaptic conductance values can be stored in memristors with eight levels, and the topology of connections between neurons is reconfigurable. The circuit has been designed using a 90 nm CMOS process with via connections to on-chip post-processed memristor arrays. The design has about 16 million CMOS transistors and 73 728 integrated memristors. We provide circuit level simulations of the entire chip performing neuronal and synaptic computations that result in biologically realistic functional behavior.

Satisfiability of logic programming based on radial basis function neural networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hamadneh, Nawaf; Sathasivam, Saratha; Tilahun, Surafel Luleseged

2014-07-10

In this paper, we propose a new technique to test the Satisfiability of propositional logic programming and quantified Boolean formula problem in radial basis function neural networks. For this purpose, we built radial basis function neural networks to represent the proportional logic which has exactly three variables in each clause. We used the Prey-predator algorithm to calculate the output weights of the neural networks, while the K-means clustering algorithm is used to determine the hidden parameters (the centers and the widths). Mean of the sum squared error function is used to measure the activity of the two algorithms. We appliedmore » the developed technique with the recurrent radial basis function neural networks to represent the quantified Boolean formulas. The new technique can be applied to solve many applications such as electronic circuits and NP-complete problems.« less

In vivo imaging of neural activity

PubMed Central

Yang, Weijian; Yuste, Rafael

2017-01-01

Since the introduction of calcium imaging to monitor neuronal activity with single-cell resolution, optical imaging methods have revolutionized neuroscience by enabling systematic recordings of neuronal circuits in living animals. The plethora of methods for functional neural imaging can be daunting to the nonexpert to navigate. Here we review advanced microscopy techniques for in vivo functional imaging and offer guidelines for which technologies are best suited for particular applications. PMID:28362436

Corticotropin-Releasing Factor Critical for Zebrafish Camouflage Behavior Is Regulated by Light and Sensitive to Ethanol

PubMed Central

Wagle, Mahendra; Mathur, Priya; Guo, Su

2011-01-01

The zebrafish camouflage response is an innate “hard-wired” behavior that offers an excellent opportunity to explore neural circuit assembly and function. Moreover, the camouflage response is sensitive to ethanol, making it a tractable system for understanding how ethanol influences neural circuit development and function. Here we report the identification of corticotropin releasing factor (CRF) as a critical component of the camouflage response pathway. We further show that ethanol, having no direct effect on the visual sensory system or the melanocytes, acts downstream of retinal ganglion cells and requires the CRF-proopiomelanocortin (POMC) pathway to exert its effect on camouflage. Treatment with ethanol, as well as alteration of light exposure that changes sensory input into the camouflage circuit, robustly modifies CRF expression in subsets of neurons. Activity of both Adenylyl Cyclase 5 and Extracellular signal Regulated Kinase (ERK) is required for such ethanol- or light- induced plasticity of crf expression. These results reveal an essential role of a peptidergic pathway in camouflage that is regulated by light and influenced by ethanol at concentrations relevant to abuse and anxiolysis, in a cAMP- and ERK- dependent manner. We conclude that this ethanol-modulated camouflage response represents a novel and relevant system for molecular genetic dissection of a neural circuit that is regulated by light and sensitive to ethanol. PMID:21209207

Corticotropin-releasing factor critical for zebrafish camouflage behavior is regulated by light and sensitive to ethanol.

PubMed

Wagle, Mahendra; Mathur, Priya; Guo, Su

2011-01-05

The zebrafish camouflage response is an innate "hard-wired" behavior that offers an excellent opportunity to explore neural circuit assembly and function. Moreover, the camouflage response is sensitive to ethanol, making it a tractable system for understanding how ethanol influences neural circuit development and function. Here we report the identification of corticotropin-releasing factor (CRF) as a critical component of the camouflage response pathway. We further show that ethanol, having no direct effect on the visual sensory system or the melanocytes, acts downstream of retinal ganglion cells and requires the CRF-proopiomelanocortin pathway to exert its effect on camouflage. Treatment with ethanol, as well as alteration of light exposure that changes sensory input into the camouflage circuit, robustly modifies CRF expression in subsets of neurons. Activity of both adenylyl cyclase 5 and extracellular signal-regulated kinase (ERK) is required for such ethanol-induced or light-induced plasticity of crf expression. These results reveal an essential role of a peptidergic pathway in camouflage that is regulated by light and influenced by ethanol at concentrations relevant to abuse and anxiolysis, in a cAMP-dependent and ERK-dependent manner. We conclude that this ethanol-modulated camouflage response represents a novel and relevant system for molecular genetic dissection of a neural circuit that is regulated by light and sensitive to ethanol.

Dynamical systems, attractors, and neural circuits.

PubMed

Miller, Paul

2016-01-01

Biology is the study of dynamical systems. Yet most of us working in biology have limited pedagogical training in the theory of dynamical systems, an unfortunate historical fact that can be remedied for future generations of life scientists. In my particular field of systems neuroscience, neural circuits are rife with nonlinearities at all levels of description, rendering simple methodologies and our own intuition unreliable. Therefore, our ideas are likely to be wrong unless informed by good models. These models should be based on the mathematical theories of dynamical systems since functioning neurons are dynamic-they change their membrane potential and firing rates with time. Thus, selecting the appropriate type of dynamical system upon which to base a model is an important first step in the modeling process. This step all too easily goes awry, in part because there are many frameworks to choose from, in part because the sparsely sampled data can be consistent with a variety of dynamical processes, and in part because each modeler has a preferred modeling approach that is difficult to move away from. This brief review summarizes some of the main dynamical paradigms that can arise in neural circuits, with comments on what they can achieve computationally and what signatures might reveal their presence within empirical data. I provide examples of different dynamical systems using simple circuits of two or three cells, emphasizing that any one connectivity pattern is compatible with multiple, diverse functions.

Spikes alone do not behavior make: Why neuroscience needs biomechanics

PubMed Central

Tytell, E.D.; Holmes, P.; Cohen, A.H.

2011-01-01

Neural circuits do not function in isolation; they interact with the physical world, accepting sensory inputs and producing outputs via muscles. Since both these pathways are constrained by physics, the activity of neural circuits can only be understood by considering biomechanics of muscles, bodies, and the exterior world. We discuss how animal bodies have natural stable motions that require relatively little activation or control from the nervous system. The nervous system can substantially alter these motions, by subtly changing mechanical properties such as leg sti ness. Mechanics can also provide robustness to perturbations without sensory reflexes. By considering a complete neuromechanical system, neuroscientists and biomechanicians together can provide a more integrated view of neural circuitry and behavior. PMID:21683575

The dialectic of Hebb and homeostasis.

PubMed

Turrigiano, Gina G

2017-03-05

It has become widely accepted that homeostatic and Hebbian plasticity mechanisms work hand in glove to refine neural circuit function. Nonetheless, our understanding of how these fundamentally distinct forms of plasticity compliment (and under some circumstances interfere with) each other remains rudimentary. Here, I describe some of the recent progress of the field, as well as some of the deep puzzles that remain. These include unravelling the spatial and temporal scales of different homeostatic and Hebbian mechanisms, determining which aspects of network function are under homeostatic control, and understanding when and how homeostatic and Hebbian mechanisms must be segregated within neural circuits to prevent interference.This article is part of the themed issue 'Integrating Hebbian and homeostatic plasticity'. © 2017 The Author(s).

Neural, not gonadal, origin of brain sex differences in a gynandromorphic finch.

PubMed

Agate, Robert J; Grisham, William; Wade, Juli; Mann, Suzanne; Wingfield, John; Schanen, Carolyn; Palotie, Aarno; Arnold, Arthur P

2003-04-15

In mammals and birds, sex differences in brain function and disease are thought to derive exclusively from sex differences in gonadal hormone secretions. For example, testosterone in male mammals acts during fetal and neonatal life to cause masculine neural development. However, male and female brain cells also differ in genetic sex; thus, sex chromosome genes acting within cells could contribute to sex differences in cell function. We analyzed the sexual phenotype of the brain of a rare gynandromorphic finch in which the right half of the brain was genetically male and the left half genetically female. The neural song circuit on the right had a more masculine phenotype than that on the left. Because both halves of the brain were exposed to a common gonadal hormone environment, the lateral differences indicate that the genetic sex of brain cells contributes to the process of sexual differentiation. Because both sides of the song circuit were more masculine than that of females, diffusible factors such as hormones of gonadal or neural origin also likely played a role in sexual differentiation.

Delineating the Diversity of Spinal Interneurons in Locomotor Circuits.

PubMed

Gosgnach, Simon; Bikoff, Jay B; Dougherty, Kimberly J; El Manira, Abdeljabbar; Lanuza, Guillermo M; Zhang, Ying

2017-11-08

Locomotion is common to all animals and is essential for survival. Neural circuits located in the spinal cord have been shown to be necessary and sufficient for the generation and control of the basic locomotor rhythm by activating muscles on either side of the body in a specific sequence. Activity in these neural circuits determines the speed, gait pattern, and direction of movement, so the specific locomotor pattern generated relies on the diversity of the neurons within spinal locomotor circuits. Here, we review findings demonstrating that developmental genetics can be used to identify populations of neurons that comprise these circuits and focus on recent work indicating that many of these populations can be further subdivided into distinct subtypes, with each likely to play complementary functions during locomotion. Finally, we discuss data describing the manner in which these populations interact with each other to produce efficient, task-dependent locomotion. Copyright © 2017 the authors 0270-6474/17/3710835-07$15.00/0.

Synaptic up-scaling preserves motor circuit output after chronic, natural inactivity

PubMed Central

Vallejo, Mauricio; Hartzler, Lynn K

2017-01-01

Neural systems use homeostatic plasticity to maintain normal brain functions and to prevent abnormal activity. Surprisingly, homeostatic mechanisms that regulate circuit output have mainly been demonstrated during artificial and/or pathological perturbations. Natural, physiological scenarios that activate these stabilizing mechanisms in neural networks of mature animals remain elusive. To establish the extent to which a naturally inactive circuit engages mechanisms of homeostatic plasticity, we utilized the respiratory motor circuit in bullfrogs that normally remains inactive for several months during the winter. We found that inactive respiratory motoneurons exhibit a classic form of homeostatic plasticity, up-scaling of AMPA-glutamate receptors. Up-scaling increased the synaptic strength of respiratory motoneurons and acted to boost motor amplitude from the respiratory network following months of inactivity. Our results show that synaptic scaling sustains strength of the respiratory motor output following months of inactivity, thereby supporting a major neuroscience hypothesis in a normal context for an adult animal. PMID:28914603

Fractional Hopfield Neural Networks: Fractional Dynamic Associative Recurrent Neural Networks.

PubMed

Pu, Yi-Fei; Yi, Zhang; Zhou, Ji-Liu

2017-10-01

This paper mainly discusses a novel conceptual framework: fractional Hopfield neural networks (FHNN). As is commonly known, fractional calculus has been incorporated into artificial neural networks, mainly because of its long-term memory and nonlocality. Some researchers have made interesting attempts at fractional neural networks and gained competitive advantages over integer-order neural networks. Therefore, it is naturally makes one ponder how to generalize the first-order Hopfield neural networks to the fractional-order ones, and how to implement FHNN by means of fractional calculus. We propose to introduce a novel mathematical method: fractional calculus to implement FHNN. First, we implement fractor in the form of an analog circuit. Second, we implement FHNN by utilizing fractor and the fractional steepest descent approach, construct its Lyapunov function, and further analyze its attractors. Third, we perform experiments to analyze the stability and convergence of FHNN, and further discuss its applications to the defense against chip cloning attacks for anticounterfeiting. The main contribution of our work is to propose FHNN in the form of an analog circuit by utilizing a fractor and the fractional steepest descent approach, construct its Lyapunov function, prove its Lyapunov stability, analyze its attractors, and apply FHNN to the defense against chip cloning attacks for anticounterfeiting. A significant advantage of FHNN is that its attractors essentially relate to the neuron's fractional order. FHNN possesses the fractional-order-stability and fractional-order-sensitivity characteristics.

Understanding the dynamical control of animal movement

NASA Astrophysics Data System (ADS)

Edwards, Donald

2008-03-01

Over the last 50 years, neurophysiologists have described many neural circuits that transform sensory input into motor commands, while biomechanicians and behavioral biologists have described many patterns of animal movement that occur in response to sensory input. Attempts to link these two have been frustrated by our technical inability to record from the necessary neurons in a freely behaving animal. As a result, we don't know how these neural circuits function in the closed loop context of free behavior, where the sensory and motor context changes on a millisecond time-scale. To address this problem, we have developed a software package, AnimatLab (www.AnimatLab.com), that enables users to reconstruct an animal's body and its relevant neural circuits, to link them at the sensory and motor ends, and through simulation, to test their ability to reproduce appropriate patterns of the animal's movements in a simulated Newtonian world. A Windows-based program, AnimatLab consists of a neural editor, a body editor, a world editor, stimulus and recording facilities, neural and physics engines, and an interactive 3-D graphical display. We have used AnimatLab to study three patterns of behavior: the grasshopper jump, crayfish escape, and crayfish leg movements used in postural control, walking, reaching and grasping. In each instance, the simulation helped identify constraints on both nervous function and biomechanical performance that have provided the basis for new experiments. Colleagues elsewhere have begun to use AnimatLab to study control of paw movements in cats and postural control in humans. We have also used AnimatLab simulations to guide the development of an autonomous hexapod robot in which the neural control circuitry is downloaded to the robot from the test computer.

[The neural mechanisms of cigarette craving and self-control].

PubMed

Hayashi, Takuya

2014-01-01

A craving for cigarettes or drugs has been believed to be a fundamental psychopathological factor that drives drug-seeking behavior and relapse. Behavioral economics has revealed context-dependent changes in drug craving. Neuroimaging studies have also found craving-related signals that were altered depending on the context of the experiments. A rational decision-making theory modeled such context-dependency and uncovered a pivotal role of the prefrontal cortical circuit in both self-control and craving. Future studies should address how dopaminergic function and stress circuits can modify the function of decision-making circuits, and produce either craving or self-control.

Spatial gradients and multidimensional dynamics in a neural integrator circuit

PubMed Central

Miri, Andrew; Daie, Kayvon; Arrenberg, Aristides B.; Baier, Herwig; Aksay, Emre; Tank, David W.

2011-01-01

In a neural integrator, the variability and topographical organization of neuronal firing rate persistence can provide information about the circuit’s functional architecture. Here we use optical recording to measure the time constant of decay of persistent firing (“persistence time”) across a population of neurons comprising the larval zebrafish oculomotor velocity-to-position neural integrator. We find extensive persistence time variation (10-fold; coefficients of variation 0.58–1.20) across cells within individual larvae. We also find that the similarity in firing between two neurons decreased as the distance between them increased and that a gradient in persistence time was mapped along the rostrocaudal and dorsoventral axes. This topography is consistent with the emergence of persistence time heterogeneity from a circuit architecture in which nearby neurons are more strongly interconnected than distant ones. Collectively, our results can be accounted for by integrator circuit models characterized by multiple dimensions of slow firing rate dynamics. PMID:21857656

Engagement of neural circuits underlying 2D spatial navigation in a rodent virtual reality system.

PubMed

Aronov, Dmitriy; Tank, David W

2014-10-22

Virtual reality (VR) enables precise control of an animal's environment and otherwise impossible experimental manipulations. Neural activity in rodents has been studied on virtual 1D tracks. However, 2D navigation imposes additional requirements, such as the processing of head direction and environment boundaries, and it is unknown whether the neural circuits underlying 2D representations can be sufficiently engaged in VR. We implemented a VR setup for rats, including software and large-scale electrophysiology, that supports 2D navigation by allowing rotation and walking in any direction. The entorhinal-hippocampal circuit, including place, head direction, and grid cells, showed 2D activity patterns similar to those in the real world. Furthermore, border cells were observed, and hippocampal remapping was driven by environment shape, suggesting functional processing of virtual boundaries. These results illustrate that 2D spatial representations can be engaged by visual and rotational vestibular stimuli alone and suggest a novel VR tool for studying rat navigation.

Design strategies for dynamic closed-loop optogenetic neurocontrol in vivo

NASA Astrophysics Data System (ADS)

Bolus, M. F.; Willats, A. A.; Whitmire, C. J.; Rozell, C. J.; Stanley, G. B.

2018-04-01

Objective. Controlling neural activity enables the possibility of manipulating sensory perception, cognitive processes, and body movement, in addition to providing a powerful framework for functionally disentangling the neural circuits that underlie these complex phenomena. Over the last decade, optogenetic stimulation has become an increasingly important and powerful tool for understanding neural circuit function, owing to the ability to target specific cell types and bidirectionally modulate neural activity. To date, most stimulation has been provided in open-loop or in an on/off closed-loop fashion, where previously-determined stimulation is triggered by an event. Here, we describe and demonstrate a design approach for precise optogenetic control of neuronal firing rate modulation using feedback to guide stimulation continuously. Approach. Using the rodent somatosensory thalamus as an experimental testbed for realizing desired time-varying patterns of firing rate modulation, we utilized a moving average exponential filter to estimate firing rate online from single-unit spiking measured extracellularly. This estimate of instantaneous rate served as feedback for a proportional integral (PI) controller, which was designed during the experiment based on a linear-nonlinear Poisson (LNP) model of the neuronal response to light. Main results. The LNP model fit during the experiment enabled robust closed-loop control, resulting in good tracking of sinusoidal and non-sinusoidal targets, and rejection of unmeasured disturbances. Closed-loop control also enabled manipulation of trial-to-trial variability. Significance. Because neuroscientists are faced with the challenge of dissecting the functions of circuit components, the ability to maintain control of a region of interest in spite of changes in ongoing neural activity will be important for disambiguating function within networks. Closed-loop stimulation strategies are ideal for control that is robust to such changes, and the employment of continuous feedback to adjust stimulation in real-time can improve the quality of data collected using optogenetic manipulation.

Demultiplexer circuit for neural stimulation

DOEpatents

Wessendorf, Kurt O; Okandan, Murat; Pearson, Sean

2012-10-09

A demultiplexer circuit is disclosed which can be used with a conventional neural stimulator to extend the number of electrodes which can be activated. The demultiplexer circuit, which is formed on a semiconductor substrate containing a power supply that provides all the dc electrical power for operation of the circuit, includes digital latches that receive and store addressing information from the neural stimulator one bit at a time. This addressing information is used to program one or more 1:2.sup.N demultiplexers in the demultiplexer circuit which then route neural stimulation signals from the neural stimulator to an electrode array which is connected to the outputs of the 1:2.sup.N demultiplexer. The demultiplexer circuit allows the number of individual electrodes in the electrode array to be increased by a factor of 2.sup.N with N generally being in a range of 2-4.

A dynamical systems approach for estimating phase interactions between rhythms of different frequencies from experimental data

PubMed Central

Goto, Takahiro; Aoyagi, Toshio

2018-01-01

Synchronization of neural oscillations as a mechanism of brain function is attracting increasing attention. Neural oscillation is a rhythmic neural activity that can be easily observed by noninvasive electroencephalography (EEG). Neural oscillations show the same frequency and cross-frequency synchronization for various cognitive and perceptual functions. However, it is unclear how this neural synchronization is achieved by a dynamical system. If neural oscillations are weakly coupled oscillators, the dynamics of neural synchronization can be described theoretically using a phase oscillator model. We propose an estimation method to identify the phase oscillator model from real data of cross-frequency synchronized activities. The proposed method can estimate the coupling function governing the properties of synchronization. Furthermore, we examine the reliability of the proposed method using time-series data obtained from numerical simulation and an electronic circuit experiment, and show that our method can estimate the coupling function correctly. Finally, we estimate the coupling function between EEG oscillation and the speech sound envelope, and discuss the validity of these results. PMID:29337999

Thalamocortical and corticothalamic pathways differentially contribute to goal-directed behaviors in the rat

PubMed Central

Alcaraz, Fabien; Fresno, Virginie; Marchand, Alain R; Kremer, Eric J; Coutureau, Etienne

2018-01-01

Highly distributed neural circuits are thought to support adaptive decision-making in volatile and complex environments. Notably, the functional interactions between prefrontal and reciprocally connected thalamic nuclei areas may be important when choices are guided by current goal value or action-outcome contingency. We examined the functional involvement of selected thalamocortical and corticothalamic pathways connecting the dorsomedial prefrontal cortex (dmPFC) and the mediodorsal thalamus (MD) in the behaving rat. Using a chemogenetic approach to inhibit projection-defined dmPFC and MD neurons during an instrumental learning task, we show that thalamocortical and corticothalamic pathways differentially support goal attributes. Both pathways participate in adaptation to the current goal value, but only thalamocortical neurons are required to integrate current causal relationships. These data indicate that antiparallel flow of information within thalamocortical circuits may convey qualitatively distinct aspects of adaptive decision-making and highlight the importance of the direction of information flow within neural circuits. PMID:29405119

Integrated biocircuits: engineering functional multicellular circuits and devices.

PubMed

Prox, Jordan; Smith, Tory; Holl, Chad; Chehade, Nick; Guo, Liang

2018-04-01

Implantable neurotechnologies have revolutionized neuromodulatory medicine for treating the dysfunction of diseased neural circuitry. However, challenges with biocompatibility and lack of full control over neural network communication and function limits the potential to create more stable and robust neuromodulation devices. Thus, we propose a platform technology of implantable and programmable cellular systems, namely Integrated Biocircuits, which use only cells as the functional components of the device. We envision the foundational principles for this concept begins with novel in vitro platforms used for the study and reconstruction of cellular circuitry. Additionally, recent advancements in organoid and 3D culture systems account for microenvironment factors of cytoarchitecture to construct multicellular circuits as they are normally formed in the brain. We explore the current state of the art of these platforms to provide knowledge of their advancements in circuit fabrication and identify the current biological principles that could be applied in designing integrated biocircuit devices. We have highlighted the exemplary methodologies and techniques of in vitro circuit fabrication and propose the integration of selected controllable parameters, which would be required in creating suitable biodevices. We provide our perspective and propose new insights into the future of neuromodulaion devices within the scope of living cellular systems that can be applied in designing more reliable and biocompatible stimulation-based neuroprosthetics.

Integrated biocircuits: engineering functional multicellular circuits and devices

NASA Astrophysics Data System (ADS)

Prox, Jordan; Smith, Tory; Holl, Chad; Chehade, Nick; Guo, Liang

2018-04-01

Objective. Implantable neurotechnologies have revolutionized neuromodulatory medicine for treating the dysfunction of diseased neural circuitry. However, challenges with biocompatibility and lack of full control over neural network communication and function limits the potential to create more stable and robust neuromodulation devices. Thus, we propose a platform technology of implantable and programmable cellular systems, namely Integrated Biocircuits, which use only cells as the functional components of the device. Approach. We envision the foundational principles for this concept begins with novel in vitro platforms used for the study and reconstruction of cellular circuitry. Additionally, recent advancements in organoid and 3D culture systems account for microenvironment factors of cytoarchitecture to construct multicellular circuits as they are normally formed in the brain. We explore the current state of the art of these platforms to provide knowledge of their advancements in circuit fabrication and identify the current biological principles that could be applied in designing integrated biocircuit devices. Main results. We have highlighted the exemplary methodologies and techniques of in vitro circuit fabrication and propose the integration of selected controllable parameters, which would be required in creating suitable biodevices. Significance. We provide our perspective and propose new insights into the future of neuromodulaion devices within the scope of living cellular systems that can be applied in designing more reliable and biocompatible stimulation-based neuroprosthetics.

A plausible neural circuit for decision making and its formation based on reinforcement learning.

PubMed

Wei, Hui; Dai, Dawei; Bu, Yijie

2017-06-01

A human's, or lower insects', behavior is dominated by its nervous system. Each stable behavior has its own inner steps and control rules, and is regulated by a neural circuit. Understanding how the brain influences perception, thought, and behavior is a central mandate of neuroscience. The phototactic flight of insects is a widely observed deterministic behavior. Since its movement is not stochastic, the behavior should be dominated by a neural circuit. Based on the basic firing characteristics of biological neurons and the neural circuit's constitution, we designed a plausible neural circuit for this phototactic behavior from logic perspective. The circuit's output layer, which generates a stable spike firing rate to encode flight commands, controls the insect's angular velocity when flying. The firing pattern and connection type of excitatory and inhibitory neurons are considered in this computational model. We simulated the circuit's information processing using a distributed PC array, and used the real-time average firing rate of output neuron clusters to drive a flying behavior simulation. In this paper, we also explored how a correct neural decision circuit is generated from network flow view through a bee's behavior experiment based on the reward and punishment feedback mechanism. The significance of this study: firstly, we designed a neural circuit to achieve the behavioral logic rules by strictly following the electrophysiological characteristics of biological neurons and anatomical facts. Secondly, our circuit's generality permits the design and implementation of behavioral logic rules based on the most general information processing and activity mode of biological neurons. Thirdly, through computer simulation, we achieved new understanding about the cooperative condition upon which multi-neurons achieve some behavioral control. Fourthly, this study aims in understanding the information encoding mechanism and how neural circuits achieve behavior control. Finally, this study also helps establish a transitional bridge between the microscopic activity of the nervous system and macroscopic animal behavior.

Temporal Information of Directed Causal Connectivity in Multi-Trial ERP Data using Partial Granger Causality.

PubMed

Youssofzadeh, Vahab; Prasad, Girijesh; Naeem, Muhammad; Wong-Lin, KongFatt

2016-01-01

Partial Granger causality (PGC) has been applied to analyse causal functional neural connectivity after effectively mitigating confounding influences caused by endogenous latent variables and exogenous environmental inputs. However, it is not known how this connectivity obtained from PGC evolves over time. Furthermore, PGC has yet to be tested on realistic nonlinear neural circuit models and multi-trial event-related potentials (ERPs) data. In this work, we first applied a time-domain PGC technique to evaluate simulated neural circuit models, and demonstrated that the PGC measure is more accurate and robust in detecting connectivity patterns as compared to conditional Granger causality and partial directed coherence, especially when the circuit is intrinsically nonlinear. Moreover, the connectivity in PGC settles faster into a stable and correct configuration over time. After method verification, we applied PGC to reveal the causal connections of ERP trials of a mismatch negativity auditory oddball paradigm. The PGC analysis revealed a significant bilateral but asymmetrical localised activity in the temporal lobe close to the auditory cortex, and causal influences in the frontal, parietal and cingulate cortical areas, consistent with previous studies. Interestingly, the time to reach a stable connectivity configuration (~250–300 ms) coincides with the deviation of ensemble ERPs of oddball from standard tones. Finally, using a sliding time window, we showed higher resolution dynamics of causal connectivity within an ERP trial. In summary, time-domain PGC is promising in deciphering directed functional connectivity in nonlinear and ERP trials accurately, and at a sufficiently early stage. This data-driven approach can reduce computational time, and determine the key architecture for neural circuit modeling.

Electrical and Optical Activation of Mesoscale Neural Circuits with Implications for Coding.

PubMed

Millard, Daniel C; Whitmire, Clarissa J; Gollnick, Clare A; Rozell, Christopher J; Stanley, Garrett B

2015-11-25

Artificial activation of neural circuitry through electrical microstimulation and optogenetic techniques is important for both scientific discovery of circuit function and for engineered approaches to alleviate various disorders of the nervous system. However, evidence suggests that neural activity generated by artificial stimuli differs dramatically from normal circuit function, in terms of both the local neuronal population activity at the site of activation and the propagation to downstream brain structures. The precise nature of these differences and the implications for information processing remain unknown. Here, we used voltage-sensitive dye imaging of primary somatosensory cortex in the anesthetized rat in response to deflections of the facial vibrissae and electrical or optogenetic stimulation of thalamic neurons that project directly to the somatosensory cortex. Although the different inputs produced responses that were similar in terms of the average cortical activation, the variability of the cortical response was strikingly different for artificial versus sensory inputs. Furthermore, electrical microstimulation resulted in highly unnatural spatial activation of cortex, whereas optical input resulted in spatial cortical activation that was similar to that induced by sensory inputs. A thalamocortical network model suggested that observed differences could be explained by differences in the way in which artificial and natural inputs modulate the magnitude and synchrony of population activity. Finally, the variability structure in the response for each case strongly influenced the optimal inputs for driving the pathway from the perspective of an ideal observer of cortical activation when considered in the context of information transmission. Artificial activation of neural circuitry through electrical microstimulation and optogenetic techniques is important for both scientific discovery and clinical translation. However, neural activity generated by these artificial means differs dramatically from normal circuit function, both locally and in the propagation to downstream brain structures. The precise nature of these differences and the implications for information processing remain unknown. The significance of this work is in quantifying the differences, elucidating likely mechanisms underlying the differences, and determining the implications for information processing. Copyright © 2015 the authors 0270-6474/15/3515702-14$15.00/0.

Mechanisms of Hierarchical Reinforcement Learning in Corticostriatal Circuits 1: Computational Analysis

PubMed Central

Badre, David

2012-01-01

Growing evidence suggests that the prefrontal cortex (PFC) is organized hierarchically, with more anterior regions having increasingly abstract representations. How does this organization support hierarchical cognitive control and the rapid discovery of abstract action rules? We present computational models at different levels of description. A neural circuit model simulates interacting corticostriatal circuits organized hierarchically. In each circuit, the basal ganglia gate frontal actions, with some striatal units gating the inputs to PFC and others gating the outputs to influence response selection. Learning at all of these levels is accomplished via dopaminergic reward prediction error signals in each corticostriatal circuit. This functionality allows the system to exhibit conditional if–then hypothesis testing and to learn rapidly in environments with hierarchical structure. We also develop a hybrid Bayesian-reinforcement learning mixture of experts (MoE) model, which can estimate the most likely hypothesis state of individual participants based on their observed sequence of choices and rewards. This model yields accurate probabilistic estimates about which hypotheses are attended by manipulating attentional states in the generative neural model and recovering them with the MoE model. This 2-pronged modeling approach leads to multiple quantitative predictions that are tested with functional magnetic resonance imaging in the companion paper. PMID:21693490

Enhancement of electrical signaling in neural networks on graphene films.

PubMed

Tang, Mingliang; Song, Qin; Li, Ning; Jiang, Ziyun; Huang, Rong; Cheng, Guosheng

2013-09-01

One of the key challenges for neural tissue engineering is to exploit supporting materials with robust functionalities not only to govern cell-specific behaviors, but also to form functional neural network. The unique electrical and mechanical properties of graphene imply it as a promising candidate for neural interfaces, but little is known about the details of neural network formation on graphene as a scaffold material for tissue engineering. Therapeutic regenerative strategies aim to guide and enhance the intrinsic capacity of the neurons to reorganize by promoting plasticity mechanisms in a controllable manner. Here, we investigated the impact of graphene on the formation and performance in the assembly of neural networks in neural stem cell (NSC) culture. Using calcium imaging and electrophysiological recordings, we demonstrate the capabilities of graphene to support the growth of functional neural circuits, and improve neural performance and electrical signaling in the network. These results offer a better understanding of interactions between graphene and NSCs, also they clearly present the great potentials of graphene as neural interface in tissue engineering. Copyright © 2013 Elsevier Ltd. All rights reserved.

GaAs Optoelectronic Integrated-Circuit Neurons

NASA Technical Reports Server (NTRS)

Lin, Steven H.; Kim, Jae H.; Psaltis, Demetri

1992-01-01

Monolithic GaAs optoelectronic integrated circuits developed for use as artificial neurons. Neural-network computer contains planar arrays of optoelectronic neurons, and variable synaptic connections between neurons effected by diffraction of light from volume hologram in photorefractive material. Basic principles of neural-network computers explained more fully in "Optoelectronic Integrated Circuits For Neural Networks" (NPO-17652). In present circuits, devices replaced by metal/semiconductor field effect transistors (MESFET's), which consume less power.

Neural Correlates of Feigned Memory Impairment are Distinguishable from Answering Randomly and Answering Incorrectly: An fMRI and Behavioral Study

ERIC Educational Resources Information Center

Liang, Chun-Yu; Xu, Zhi-Yuan; Mei, Wei; Wang, Li-Li; Xue, Li; Lu, De Jian; Zhao, Hu

2012-01-01

Previous functional magnetic resonance imaging (fMRI) studies have identified activation in the prefrontal-parietal-sub-cortical circuit during feigned memory impairment when comparing with truthful telling. Here, we used fMRI to determine whether neural activity can differentiate between answering correctly, answering randomly, answering…

The role of efference copy in striatal learning.

PubMed

Fee, Michale S

2014-04-01

Reinforcement learning requires the convergence of signals representing context, action, and reward. While models of basal ganglia function have well-founded hypotheses about the neural origin of signals representing context and reward, the function and origin of signals representing action are less clear. Recent findings suggest that exploratory or variable behaviors are initiated by a wide array of 'action-generating' circuits in the midbrain, brainstem, and cortex. Thus, in order to learn, the striatum must incorporate an efference copy of action decisions made in these action-generating circuits. Here we review several recent neural models of reinforcement learning that emphasize the role of efference copy signals. Also described are ideas about how these signals might be integrated with inputs signaling context and reward. Copyright © 2014 Elsevier Ltd. All rights reserved.

Dynamic changes in neural circuit topology following mild mechanical injury in vitro.

PubMed

Patel, Tapan P; Ventre, Scott C; Meaney, David F

2012-01-01

Despite its enormous incidence, mild traumatic brain injury is not well understood. One aspect that needs more definition is how the mechanical energy during injury affects neural circuit function. Recent developments in cellular imaging probes provide an opportunity to assess the dynamic state of neural networks with single-cell resolution. In this article, we developed imaging methods to assess the state of dissociated cortical networks exposed to mild injury. We estimated the imaging conditions needed to achieve accurate measures of network properties, and applied these methodologies to evaluate if mild mechanical injury to cortical neurons produces graded changes to either spontaneous network activity or altered network topology. We found that modest injury produced a transient increase in calcium activity that dissipated within 1 h after injury. Alternatively, moderate mechanical injury produced immediate disruption in network synchrony, loss in excitatory tone, and increased modular topology. A calcium-activated neutral protease (calpain) was a key intermediary in these changes; blocking calpain activation restored the network nearly completely to its pre-injury state. Together, these findings show a more complex change in neural circuit behavior than previously reported for mild mechanical injury, and highlight at least one important early mechanism responsible for these changes.

No laughing matter: intranasal oxytocin administration changes functional brain connectivity during exposure to infant laughter.

PubMed

Riem, Madelon M E; van IJzendoorn, Marinus H; Tops, Mattie; Boksem, Maarten A S; Rombouts, Serge A R B; Bakermans-Kranenburg, Marian J

2012-04-01

Infant laughter is a rewarding experience. It activates neural reward circuits and promotes parental proximity and care, thus facilitating parent-infant attachment. The neuropeptide oxytocin might enhance the incentive salience of infant laughter by modulating neural circuits related to the perception of infant cues. In a randomized controlled trial with functional magnetic resonance imaging we investigated the influence of intranasally administered oxytocin on functional brain connectivity in response to infant laughter. Blood oxygenation level-dependent responses to infant laughter were measured in 22 nulliparous women who were administered oxytocin and 20 nulliparous women who were administered a placebo. Elevated oxytocin levels reduced activation in the amygdala during infant laughter and enhanced functional connectivity between the amygdala and the orbitofrontal cortex, the anterior cingulate, the hippocampus, the precuneus, the supramarginal gyri, and the middle temporal gyrus. Increased functional connectivity between the amygdala and regions involved in emotion regulation may reduce negative emotional arousal while enhancing the incentive salience of the infant laughter.

No Laughing Matter: Intranasal Oxytocin Administration Changes Functional Brain Connectivity during Exposure to Infant Laughter

PubMed Central

Riem, Madelon M E; van IJzendoorn, Marinus H; Tops, Mattie; Boksem, Maarten A S; Rombouts, Serge A R B; Bakermans-Kranenburg, Marian J

2012-01-01

Infant laughter is a rewarding experience. It activates neural reward circuits and promotes parental proximity and care, thus facilitating parent–infant attachment. The neuropeptide oxytocin might enhance the incentive salience of infant laughter by modulating neural circuits related to the perception of infant cues. In a randomized controlled trial with functional magnetic resonance imaging we investigated the influence of intranasally administered oxytocin on functional brain connectivity in response to infant laughter. Blood oxygenation level-dependent responses to infant laughter were measured in 22 nulliparous women who were administered oxytocin and 20 nulliparous women who were administered a placebo. Elevated oxytocin levels reduced activation in the amygdala during infant laughter and enhanced functional connectivity between the amygdala and the orbitofrontal cortex, the anterior cingulate, the hippocampus, the precuneus, the supramarginal gyri, and the middle temporal gyrus. Increased functional connectivity between the amygdala and regions involved in emotion regulation may reduce negative emotional arousal while enhancing the incentive salience of the infant laughter. PMID:22189289

Neurodevelopmental effects of chronic exposure to elevated levels of pro-inflammatory cytokines in a developing visual system

PubMed Central

2010-01-01

Background Imbalances in the regulation of pro-inflammatory cytokines have been increasingly correlated with a number of severe and prevalent neurodevelopmental disorders, including autism spectrum disorder, schizophrenia and Down syndrome. Although several studies have shown that cytokines have potent effects on neural function, their role in neural development is still poorly understood. In this study, we investigated the link between abnormal cytokine levels and neural development using the Xenopus laevis tadpole visual system, a model frequently used to examine the anatomical and functional development of neural circuits. Results Using a test for a visually guided behavior that requires normal visual system development, we examined the long-term effects of prolonged developmental exposure to three pro-inflammatory cytokines with known neural functions: interleukin (IL)-1β, IL-6 and tumor necrosis factor (TNF)-α. We found that all cytokines affected the development of normal visually guided behavior. Neuroanatomical imaging of the visual projection showed that none of the cytokines caused any gross abnormalities in the anatomical organization of this projection, suggesting that they may be acting at the level of neuronal microcircuits. We further tested the effects of TNF-α on the electrophysiological properties of the retinotectal circuit and found that long-term developmental exposure to TNF-α resulted in enhanced spontaneous excitatory synaptic transmission in tectal neurons, increased AMPA/NMDA ratios of retinotectal synapses, and a decrease in the number of immature synapses containing only NMDA receptors, consistent with premature maturation and stabilization of these synapses. Local interconnectivity within the tectum also appeared to remain widespread, as shown by increased recurrent polysynaptic activity, and was similar to what is seen in more immature, less refined tectal circuits. TNF-α treatment also enhanced the overall growth of tectal cell dendrites. Finally, we found that TNF-α-reared tadpoles had increased susceptibility to pentylenetetrazol-induced seizures. Conclusions Taken together our data are consistent with a model in which TNF-α causes premature stabilization of developing synapses within the tectum, therefore preventing normal refinement and synapse elimination that occurs during development, leading to increased local connectivity and epilepsy. This experimental model also provides an integrative approach to understanding the effects of cytokines on the development of neural circuits and may provide novel insights into the etiology underlying some neurodevelopmental disorders. PMID:20067608

Neurodevelopmental effects of chronic exposure to elevated levels of pro-inflammatory cytokines in a developing visual system.

PubMed

Lee, Ryan H; Mills, Elizabeth A; Schwartz, Neil; Bell, Mark R; Deeg, Katherine E; Ruthazer, Edward S; Marsh-Armstrong, Nicholas; Aizenman, Carlos D

2010-01-12

Imbalances in the regulation of pro-inflammatory cytokines have been increasingly correlated with a number of severe and prevalent neurodevelopmental disorders, including autism spectrum disorder, schizophrenia and Down syndrome. Although several studies have shown that cytokines have potent effects on neural function, their role in neural development is still poorly understood. In this study, we investigated the link between abnormal cytokine levels and neural development using the Xenopus laevis tadpole visual system, a model frequently used to examine the anatomical and functional development of neural circuits. Using a test for a visually guided behavior that requires normal visual system development, we examined the long-term effects of prolonged developmental exposure to three pro-inflammatory cytokines with known neural functions: interleukin (IL)-1beta, IL-6 and tumor necrosis factor (TNF)-alpha. We found that all cytokines affected the development of normal visually guided behavior. Neuroanatomical imaging of the visual projection showed that none of the cytokines caused any gross abnormalities in the anatomical organization of this projection, suggesting that they may be acting at the level of neuronal microcircuits. We further tested the effects of TNF-alpha on the electrophysiological properties of the retinotectal circuit and found that long-term developmental exposure to TNF-alpha resulted in enhanced spontaneous excitatory synaptic transmission in tectal neurons, increased AMPA/NMDA ratios of retinotectal synapses, and a decrease in the number of immature synapses containing only NMDA receptors, consistent with premature maturation and stabilization of these synapses. Local interconnectivity within the tectum also appeared to remain widespread, as shown by increased recurrent polysynaptic activity, and was similar to what is seen in more immature, less refined tectal circuits. TNF-alpha treatment also enhanced the overall growth of tectal cell dendrites. Finally, we found that TNF-alpha-reared tadpoles had increased susceptibility to pentylenetetrazol-induced seizures. Taken together our data are consistent with a model in which TNF-alpha causes premature stabilization of developing synapses within the tectum, therefore preventing normal refinement and synapse elimination that occurs during development, leading to increased local connectivity and epilepsy. This experimental model also provides an integrative approach to understanding the effects of cytokines on the development of neural circuits and may provide novel insights into the etiology underlying some neurodevelopmental disorders.

An Activity for Demonstrating the Concept of a Neural Circuit

ERIC Educational Resources Information Center

Kreiner, David S.

2012-01-01

College students in two sections of a general psychology course participated in a demonstration of a simple neural circuit. The activity was based on a neural circuit that Jeffress proposed for localizing sounds. Students in one section responded to a questionnaire prior to participating in the activity, while students in the other section…

Higher-Order Motion Inputs For Visual Figure Tracking: Control Algorithms and Neural Circuits

DTIC Science & Technology

2015-05-30

3 3 Accomplishments / New Findings .......................................................................................... 3 3.1...Posters: ........................................................................ 51 6.2 Consultative and advisory functions ...53 7 New Discoveries, Inventions, or Patent Disclosures

Exploring the Nature of Cortical Recurrent Interactions

NASA Astrophysics Data System (ADS)

Morita, Kenji; Kalra, Rita; Aihara, Kazuyuki; Robinson, Hugh P. C.

2011-09-01

Fast rhythmic activity of neural population has been frequently observed in cortical circuits, and suggested to be associated with various cognitive functions including working memory and selective attention. However, precisely how recurrent synaptic interactions, that are prominent in these circuits, shape and/or modulate such population rhythm has not been fully elucidated. We have addressed this issue by combining electrophysiological and computational approaches.

Synaptic E-I Balance Underlies Efficient Neural Coding.

PubMed

Zhou, Shanglin; Yu, Yuguo

2018-01-01

Both theoretical and experimental evidence indicate that synaptic excitation and inhibition in the cerebral cortex are well-balanced during the resting state and sensory processing. Here, we briefly summarize the evidence for how neural circuits are adjusted to achieve this balance. Then, we discuss how such excitatory and inhibitory balance shapes stimulus representation and information propagation, two basic functions of neural coding. We also point out the benefit of adopting such a balance during neural coding. We conclude that excitatory and inhibitory balance may be a fundamental mechanism underlying efficient coding.

Synaptic E-I Balance Underlies Efficient Neural Coding

PubMed Central

Zhou, Shanglin; Yu, Yuguo

2018-01-01

Both theoretical and experimental evidence indicate that synaptic excitation and inhibition in the cerebral cortex are well-balanced during the resting state and sensory processing. Here, we briefly summarize the evidence for how neural circuits are adjusted to achieve this balance. Then, we discuss how such excitatory and inhibitory balance shapes stimulus representation and information propagation, two basic functions of neural coding. We also point out the benefit of adopting such a balance during neural coding. We conclude that excitatory and inhibitory balance may be a fundamental mechanism underlying efficient coding. PMID:29456491

An Integrated Circuit for Simultaneous Extracellular Electrophysiology Recording and Optogenetic Neural Manipulation

PubMed Central

Chen, Chang Hao; McCullagh, Elizabeth A.; Pun, Sio Hang; Mak, Peng Un; Vai, Mang I; Mak, Pui In; Klug, Achim; Lei, Tim C.

2017-01-01

The ability to record and to control action potential firing in neuronal circuits of the brain is critical to understand how the brain functions on the cellular and network levels. Recent development of optogenetic proteins allows direct stimulation or inhibition of action potential firing of neurons upon optical illumination. In this paper, we combined a low-noise and high input impedance (or low input capacitance) neural recording amplifier, and a high current laser/LED driver in a monolithic integrated circuit (IC) for simultaneous neural recording and optogenetic neural control. The low input capacitance of the amplifier (9.7 pF) was achieved through adding a dedicated unity gain input stage optimized for high impedance metal electrodes. The input referred noise of the amplifier was measured to be 4.57 µVrms, which is lower than the estimated thermal noise of the metal electrode. Thus, action potentials originating from a single neuron can be recorded with a signal-to-noise ratio of ~6.6. The LED/laser current driver delivers a maximum current of 330 mA to generate adequate light for optogenetic control. We experimentally tested the functionality of the IC with an anesthetized Mongolian gerbil and recorded auditory stimulated action potentials from the inferior colliculus. Furthermore, we showed that spontaneous firing of 5th (trigeminal) nerve fibers was inhibited using the optogenetic protein Halorhodopsin. A noise model was also derived including the equivalent electronic components of the metal electrode and the high current driver to guide the design. PMID:28221990

Cracking the barcode of fullerene-like cortical microcolumns.

PubMed

Tozzi, Arturo; Peters, James F; Ori, Ottorino

2017-03-22

Artificial neural systems and nervous graph theoretical analysis rely upon the stance that the neural code is embodied in logic circuits, e.g., spatio-temporal sequences of ON/OFF spiking neurons. Nevertheless, this assumption does not fully explain complex brain functions. Here we show how nervous activity, other than logic circuits, could instead depend on topological transformations and symmetry constraints occurring at the micro-level of the cortical microcolumn, i.e., the embryological, anatomical and functional basic unit of the brain. Tubular microcolumns can be flattened in fullerene-like two-dimensional lattices, equipped with about 80 nodes standing for pyramidal neurons where neural computations take place. We show how the countless possible combinations of activated neurons embedded in the lattice resemble a barcode. Despite the fact that further experimental verification is required in order to validate our claim, different assemblies of firing neurons might have the appearance of diverse codes, each one responsible for a single mental activity. A two-dimensional fullerene-like lattice, grounded on simple topological changes standing for pyramidal neurons' activation, not just displays analogies with the real microcolumn's microcircuitry and the neural connectome, but also the potential for the manufacture of plastic, robust and fast artificial networks in robotic forms of full-fledged neural systems. Copyright © 2017 Elsevier B.V. All rights reserved.

Affective neural response to restricted interests in autism spectrum disorders.

PubMed

Cascio, Carissa J; Foss-Feig, Jennifer H; Heacock, Jessica; Schauder, Kimberly B; Loring, Whitney A; Rogers, Baxter P; Pryweller, Jennifer R; Newsom, Cassandra R; Cockhren, Jurnell; Cao, Aize; Bolton, Scott

2014-01-01

Restricted interests are a class of repetitive behavior in autism spectrum disorders (ASD) whose intensity and narrow focus often contribute to significant interference with daily functioning. While numerous neuroimaging studies have investigated executive circuits as putative neural substrates of repetitive behavior, recent work implicates affective neural circuits in restricted interests. We sought to explore the role of affective neural circuits and determine how restricted interests are distinguished from hobbies or interests in typical development. We compared a group of children with ASD to a typically developing (TD) group of children with strong interests or hobbies, employing parent report, an operant behavioral task, and functional imaging with personalized stimuli based on individual interests. While performance on the operant task was similar between the two groups, parent report of intensity and interference of interests was significantly higher in the ASD group. Both the ASD and TD groups showed increased BOLD response in widespread affective neural regions to the pictures of their own interest. When viewing pictures of other children's interests, the TD group showed a similar pattern, whereas BOLD response in the ASD group was much more limited. Increased BOLD response in the insula and anterior cingulate cortex distinguished the ASD from the TD group, and parent report of the intensity and interference with daily life of the child's restricted interest predicted insula response. While affective neural network response and operant behavior are comparable in typical and restricted interests, the narrowness of focus that clinically distinguishes restricted interests in ASD is reflected in more interference in daily life and aberrantly enhanced insula and anterior cingulate response to individuals' own interests in the ASD group. These results further support the involvement of affective neural networks in repetitive behaviors in ASD. © 2013 The Authors. Journal of Child Psychology and Psychiatry © 2013 Association for Child and Adolescent Mental Health.

Computer model of a reverberant and parallel circuit coupling

NASA Astrophysics Data System (ADS)

Kalil, Camila de Andrade; de Castro, Maria Clícia Stelling; Cortez, Célia Martins

2017-11-01

The objective of the present study was to deepen the knowledge about the functioning of the neural circuits by implementing a signal transmission model using the Graph Theory in a small network of neurons composed of an interconnected reverberant and parallel circuit, in order to investigate the processing of the signals in each of them and the effects on the output of the network. For this, a program was developed in C language and simulations were done using neurophysiological data obtained in the literature.

Document analysis with neural net circuits

NASA Technical Reports Server (NTRS)

Graf, Hans Peter

1994-01-01

Document analysis is one of the main applications of machine vision today and offers great opportunities for neural net circuits. Despite more and more data processing with computers, the number of paper documents is still increasing rapidly. A fast translation of data from paper into electronic format is needed almost everywhere, and when done manually, this is a time consuming process. Markets range from small scanners for personal use to high-volume document analysis systems, such as address readers for the postal service or check processing systems for banks. A major concern with present systems is the accuracy of the automatic interpretation. Today's algorithms fail miserably when noise is present, when print quality is poor, or when the layout is complex. A common approach to circumvent these problems is to restrict the variations of the documents handled by a system. In our laboratory, we had the best luck with circuits implementing basic functions, such as convolutions, that can be used in many different algorithms. To illustrate the flexibility of this approach, three applications of the NET32K circuit are described in this short viewgraph presentation: locating address blocks, cleaning document images by removing noise, and locating areas of interest in personal checks to improve image compression. Several of the ideas realized in this circuit that were inspired by neural nets, such as analog computation with a low resolution, resulted in a chip that is well suited for real-world document analysis applications and that compares favorably with alternative, 'conventional' circuits.

Evolution of central pattern generators and rhythmic behaviours

PubMed Central

Katz, Paul S.

2016-01-01

Comparisons of rhythmic movements and the central pattern generators (CPGs) that control them uncover principles about the evolution of behaviour and neural circuits. Over the course of evolutionary history, gradual evolution of behaviours and their neural circuitry within any lineage of animals has been a predominant occurrence. Small changes in gene regulation can lead to divergence of circuit organization and corresponding changes in behaviour. However, some behavioural divergence has resulted from large-scale rewiring of the neural network. Divergence of CPG circuits has also occurred without a corresponding change in behaviour. When analogous rhythmic behaviours have evolved independently, it has generally been with different neural mechanisms. Repeated evolution of particular rhythmic behaviours has occurred within some lineages due to parallel evolution or latent CPGs. Particular motor pattern generating mechanisms have also evolved independently in separate lineages. The evolution of CPGs and rhythmic behaviours shows that although most behaviours and neural circuits are highly conserved, the nature of the behaviour does not dictate the neural mechanism and that the presence of homologous neural components does not determine the behaviour. This suggests that although behaviour is generated by neural circuits, natural selection can act separately on these two levels of biological organization. PMID:26598733

Evolution of central pattern generators and rhythmic behaviours.

PubMed

Katz, Paul S

2016-01-05

Comparisons of rhythmic movements and the central pattern generators (CPGs) that control them uncover principles about the evolution of behaviour and neural circuits. Over the course of evolutionary history, gradual evolution of behaviours and their neural circuitry within any lineage of animals has been a predominant occurrence. Small changes in gene regulation can lead to divergence of circuit organization and corresponding changes in behaviour. However, some behavioural divergence has resulted from large-scale rewiring of the neural network. Divergence of CPG circuits has also occurred without a corresponding change in behaviour. When analogous rhythmic behaviours have evolved independently, it has generally been with different neural mechanisms. Repeated evolution of particular rhythmic behaviours has occurred within some lineages due to parallel evolution or latent CPGs. Particular motor pattern generating mechanisms have also evolved independently in separate lineages. The evolution of CPGs and rhythmic behaviours shows that although most behaviours and neural circuits are highly conserved, the nature of the behaviour does not dictate the neural mechanism and that the presence of homologous neural components does not determine the behaviour. This suggests that although behaviour is generated by neural circuits, natural selection can act separately on these two levels of biological organization. © 2015 The Author(s).

Insights into Rapid Modulation of Neuroplasticity by Brain Estrogens

PubMed Central

Woolfrey, Kevin M.; Penzes, Peter

2013-01-01

Converging evidence from cellular, electrophysiological, anatomic, and behavioral studies suggests that the remodeling of synapse structure and function is a critical component of cognition. This modulation of neuroplasticity can be achieved through the actions of numerous extracellular signals. Moreover, it is thought that it is the integration of different extracellular signals regulation of neuroplasticity that greatly influences cognitive function. One group of signals that exerts powerful effects on multiple neurologic processes is estrogens. Classically, estrogens have been described to exert their effects over a period of hours to days. However, there is now increasing evidence that estrogens can rapidly influence multiple behaviors, including those that require forebrain neural circuitry. Moreover, these effects are found in both sexes. Critically, it is now emerging that the modulation of cognition by rapid estrogenic signaling is achieved by activation of specific signaling cascades and regulation of synapse structure and function, cumulating in the rewiring of neural circuits. The importance of understanding the rapid effects of estrogens on forebrain function and circuitry is further emphasized as investigations continue to consider the potential of estrogenic-based therapies for neuropathologies. This review focuses on how estrogens can rapidly influence cognition and the emerging mechanisms that underlie these effects. We discuss the potential sources and the biosynthesis of estrogens within the brain and the consequences of rapid estrogenic-signaling on the remodeling of neural circuits. Furthermore, we argue that estrogens act via distinct signaling pathways to modulate synapse structure and function in a manner that may vary with cell type, developmental stage, and sex. Finally, we present a model in which the coordination of rapid estrogenic-signaling and activity-dependent stimuli can result in long-lasting changes in neural circuits, contributing to cognition, with potential relevance for the development of novel estrogenic-based therapies for neurodevelopmental or neurodegenerative disorders. PMID:24076546

Altered Neural Circuits Accompany Lower Performance during Narrative Comprehension in Children with Reading Difficulties: An fMRI Study

ERIC Educational Resources Information Center

Horowitz-Kraus, Tzipi; Buck, Catherine; Dorrmann, Dana

2016-01-01

Narrative comprehension is a linguistic ability that is foundational for future reading ability. The aim of the current study was to examine the neural circuitry of children with reading difficulties (RD) compared to typical readers during a narrative-comprehension task. We hypothesized that due to deficient executive functions, which support…

Central control of body temperature

PubMed Central

Morrison, Shaun F.

2016-01-01

Central neural circuits orchestrate the behavioral and autonomic repertoire that maintains body temperature during environmental temperature challenges and alters body temperature during the inflammatory response and behavioral states and in response to declining energy homeostasis. This review summarizes the central nervous system circuit mechanisms controlling the principal thermoeffectors for body temperature regulation: cutaneous vasoconstriction regulating heat loss and shivering and brown adipose tissue for thermogenesis. The activation of these thermoeffectors is regulated by parallel but distinct efferent pathways within the central nervous system that share a common peripheral thermal sensory input. The model for the neural circuit mechanism underlying central thermoregulatory control provides a useful platform for further understanding of the functional organization of central thermoregulation, for elucidating the hypothalamic circuitry and neurotransmitters involved in body temperature regulation, and for the discovery of novel therapeutic approaches to modulating body temperature and energy homeostasis. PMID:27239289

Central control of body temperature.

PubMed

Morrison, Shaun F

2016-01-01

Central neural circuits orchestrate the behavioral and autonomic repertoire that maintains body temperature during environmental temperature challenges and alters body temperature during the inflammatory response and behavioral states and in response to declining energy homeostasis. This review summarizes the central nervous system circuit mechanisms controlling the principal thermoeffectors for body temperature regulation: cutaneous vasoconstriction regulating heat loss and shivering and brown adipose tissue for thermogenesis. The activation of these thermoeffectors is regulated by parallel but distinct efferent pathways within the central nervous system that share a common peripheral thermal sensory input. The model for the neural circuit mechanism underlying central thermoregulatory control provides a useful platform for further understanding of the functional organization of central thermoregulation, for elucidating the hypothalamic circuitry and neurotransmitters involved in body temperature regulation, and for the discovery of novel therapeutic approaches to modulating body temperature and energy homeostasis.

Progress in understanding mood disorders: optogenetic dissection of neural circuits.

PubMed

Lammel, S; Tye, K M; Warden, M R

2014-01-01

Major depression is characterized by a cluster of symptoms that includes hopelessness, low mood, feelings of worthlessness and inability to experience pleasure. The lifetime prevalence of major depression approaches 20%, yet current treatments are often inadequate both because of associated side effects and because they are ineffective for many people. In basic research, animal models are often used to study depression. Typically, experimental animals are exposed to acute or chronic stress to generate a variety of depression-like symptoms. Despite its clinical importance, very little is known about the cellular and neural circuits that mediate these symptoms. Recent advances in circuit-targeted approaches have provided new opportunities to study the neuropathology of mood disorders such as depression and anxiety. We review recent progress and highlight some studies that have begun tracing a functional neuronal circuit diagram that may prove essential in establishing novel treatment strategies in mood disorders. First, we shed light on the complexity of mesocorticolimbic dopamine (DA) responses to stress by discussing two recent studies reporting that optogenetic activation of midbrain DA neurons can induce or reverse depression-related behaviors. Second, we describe the role of the lateral habenula circuitry in the pathophysiology of depression. Finally, we discuss how the prefrontal cortex controls limbic and neuromodulatory circuits in mood disorders. © 2013 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

The impact of neurotechnology on rehabilitation.

PubMed

Berger, Theodore W; Gerhardt, Greg; Liker, Mark A; Soussou, Walid

2008-01-01

This paper present results of a multi-disciplinary project that is developing a microchip-based neural prosthesis for the hippocampus, a region of the brain responsible for the formation of long-term memories. Damage to the hippocampus is frequently associated with epilepsy, stroke, and dementia (Alzheimer's disease) and is considered to underlie the memory deficits related to these neurological conditions. The essential goals of the multi-laboratory effort include: (1) experimental study of neuron and neural network function--how does the hippocampus encode information? (2) formulation of biologically realistic models of neural system dynamics--can that encoding process be described mathematically to realize a predictive model of how the hippocampus responds to any event? (3) microchip implementation of neural system models--can the mathematical model be realized as a set of electronic circuits to achieve parallel processing, rapid computational speed, and miniaturization? and (4) creation of hybrid neuron-silicon interfaces-can structural and functional connections between electronic devices and neural tissue be achieved for long-term, bi-directional communication with the brain? By integrating solutions to these component problems, we are realizing a microchip-based model of hippocampal nonlinear dynamics that can perform the same function as part of the hippocampus. Through bi-directional communication with other neural tissue that normally provides the inputs and outputs to/from a damaged hippocampal area, the biomimetic model could serve as a neural prosthesis. A proof-of-concept will be presented in which the CA3 region of the hippocampal slice is surgically removed and is replaced by a microchip model of CA3 nonlinear dynamics--the "hybrid" hippocampal circuit displays normal physiological properties. How the work in brain slices is being extended to behaving animals also will be described.

Expansion microscopy: development and neuroscience applications.

PubMed

Karagiannis, Emmanouil D; Boyden, Edward S

2018-06-01

Many neuroscience questions center around understanding how the molecules and wiring in neural circuits mechanistically yield behavioral functions, or go awry in disease states. However, mapping the molecules and wiring of neurons across the large scales of neural circuits has posed a great challenge. We recently developed expansion microscopy (ExM), a process in which we physically magnify biological specimens such as brain circuits. We synthesize throughout preserved brain specimens a dense, even mesh of a swellable polymer such as sodium polyacrylate, anchoring key biomolecules such as proteins and nucleic acids to the polymer. After mechanical homogenization of the specimen-polymer composite, we add water, and the polymer swells, pulling biomolecules apart. Due to the larger separation between molecules, ordinary microscopes can then perform nanoscale resolution imaging. We here review the ExM technology as well as applications to the mapping of synapses, cells, and circuits, including deployment in species such as Drosophila, mouse, non-human primate, and human. Copyright © 2017 Elsevier Ltd. All rights reserved.

Supervised Learning Using Spike-Timing-Dependent Plasticity of Memristive Synapses.

PubMed

Nishitani, Yu; Kaneko, Yukihiro; Ueda, Michihito

2015-12-01

We propose a supervised learning model that enables error backpropagation for spiking neural network hardware. The method is modeled by modifying an existing model to suit the hardware implementation. An example of a network circuit for the model is also presented. In this circuit, a three-terminal ferroelectric memristor (3T-FeMEM), which is a field-effect transistor with a gate insulator composed of ferroelectric materials, is used as an electric synapse device to store the analog synaptic weight. Our model can be implemented by reflecting the network error to the write voltage of the 3T-FeMEMs and introducing a spike-timing-dependent learning function to the device. An XOR problem was successfully demonstrated as a benchmark learning by numerical simulations using the circuit properties to estimate the learning performance. In principle, the learning time per step of this supervised learning model and the circuit is independent of the number of neurons in each layer, promising a high-speed and low-power calculation in large-scale neural networks.

Sleep Drive Is Encoded by Neural Plastic Changes in a Dedicated Circuit.

PubMed

Liu, Sha; Liu, Qili; Tabuchi, Masashi; Wu, Mark N

2016-06-02

Prolonged wakefulness leads to an increased pressure for sleep, but how this homeostatic drive is generated and subsequently persists is unclear. Here, from a neural circuit screen in Drosophila, we identify a subset of ellipsoid body (EB) neurons whose activation generates sleep drive. Patch-clamp analysis indicates these EB neurons are highly sensitive to sleep loss, switching from spiking to burst-firing modes. Functional imaging and translational profiling experiments reveal that elevated sleep need triggers reversible increases in cytosolic Ca(2+) levels, NMDA receptor expression, and structural markers of synaptic strength, suggesting these EB neurons undergo "sleep-need"-dependent plasticity. Strikingly, the synaptic plasticity of these EB neurons is both necessary and sufficient for generating sleep drive, indicating that sleep pressure is encoded by plastic changes within this circuit. These studies define an integrator circuit for sleep homeostasis and provide a mechanism explaining the generation and persistence of sleep drive. Copyright © 2016 Elsevier Inc. All rights reserved.

Simultaneous two-photon imaging and two-photon optogenetics of cortical circuits in three dimensions

PubMed Central

Carrillo-Reid, Luis; Bando, Yuki; Peterka, Darcy S

2018-01-01

The simultaneous imaging and manipulating of neural activity could enable the functional dissection of neural circuits. Here we have combined two-photon optogenetics with simultaneous volumetric two-photon calcium imaging to measure and manipulate neural activity in mouse neocortex in vivo in three-dimensions (3D) with cellular resolution. Using a hybrid holographic approach, we simultaneously photostimulate more than 80 neurons over 150 μm in depth in layer 2/3 of the mouse visual cortex, while simultaneously imaging the activity of the surrounding neurons. We validate the usefulness of the method by photoactivating in 3D selected groups of interneurons, suppressing the response of nearby pyramidal neurons to visual stimuli in awake animals. Our all-optical approach could be used as a general platform to read and write neuronal activity. PMID:29412138

Overlapping neurobehavioral circuits in ADHD, obesity, and binge eating: Evidence from Neuroimaging Research

PubMed Central

Seymour, Karen E.; Reinblatt, Shauna P.; Benson, Leora; Carnell, Susan

2015-01-01

Attention-deficit/hyperactivity disorder (ADHD) and conditions involving excessive eating (e.g. obesity, binge / loss of control eating) are increasingly prevalent within pediatric populations, and correlational and some longitudinal studies have suggested inter-relationships between these disorders. In addition, a number of common neural correlates are emerging across conditions, e.g. functional abnormalities within circuits subserving reward processing and executive functioning. To explore this potential cross-condition overlap in neurobehavioral underpinnings, we selectively review relevant functional neuroimaging literature, specifically focusing on studies probing i) reward processing, ii) response inhibition, and iii) emotional processing and regulation, and outline three specific shared neurobehavioral circuits. Based on our review, we also identify gaps within the literature that would benefit from further research. PMID:26098969

A theory of neural dimensionality, dynamics, and measurement

NASA Astrophysics Data System (ADS)

Ganguli, Surya

In many experiments, neuroscientists tightly control behavior, record many trials, and obtain trial-averaged firing rates from hundreds of neurons in circuits containing millions of behaviorally relevant neurons. Dimensionality reduction has often shown that such datasets are strikingly simple; they can be described using a much smaller number of dimensions than the number of recorded neurons, and the resulting projections onto these dimensions yield a remarkably insightful dynamical portrait of circuit computation. This ubiquitous simplicity raises several profound and timely conceptual questions. What is the origin of this simplicity and its implications for the complexity of brain dynamics? Would neuronal datasets become more complex if we recorded more neurons? How and when can we trust dynamical portraits obtained from only hundreds of neurons in circuits containing millions of neurons? We present a theory that answers these questions, and test it using neural data recorded from reaching monkeys. Overall, this theory yields a picture of the neural measurement process as a random projection of neural dynamics, conceptual insights into how we can reliably recover dynamical portraits in such under-sampled measurement regimes, and quantitative guidelines for the design of future experiments. Moreover, it reveals the existence of phase transition boundaries in our ability to successfully decode cognition and behavior as a function of the number of recorded neurons, the complexity of the task, and the smoothness of neural dynamics. membership pending.

Modulation of neural circuits: how stimulus context shapes innate behavior in Drosophila.

PubMed

Su, Chih-Ying; Wang, Jing W

2014-12-01

Remarkable advances have been made in recent years in our understanding of innate behavior and the underlying neural circuits. In particular, a wealth of neuromodulatory mechanisms have been uncovered that can alter the input-output relationship of a hereditary neural circuit. It is now clear that this inbuilt flexibility allows animals to modify their behavioral responses according to environmental cues, metabolic demands and physiological states. Here, we discuss recent insights into how modulation of neural circuits impacts innate behavior, with a special focus on how environmental cues and internal physiological states shape different aspects of feeding behavior in Drosophila. Copyright © 2014 Elsevier Ltd. All rights reserved.

Childhood physical abuse predicts stressor-evoked activity within central visceral control regions

PubMed Central

Sheu, Lei K.; Midei, Aimee J.; Gianaros, Peter J.

2015-01-01

Early life experience differentially shapes later stress reactivity, as evidenced by both animal and human studies. However, early experience-related changes in the function of central visceral neural circuits that control stress responses have not been well characterized, particularly in humans. The paraventricular nucleus of the hypothalamus (PVN), bed nucleus of the stria terminalis (BNST), amygdala (Amyg) and subgenual anterior cingulate cortex (sgACC) form a core visceral stress-responsive circuit. The goal of this study is to examine how childhood emotional and physical abuse relates to adulthood stressor-evoked activity within these visceral brain regions. To evoke acute states of mental stress, participants (n = 155) performed functional magnetic resonance imaging (fMRI)-adapted versions of the multi-source interference task (MSIT) and the Stroop task with simultaneous monitoring of mean arterial pressure (MAP) and heart rate. Regression analyses revealed that childhood physical abuse correlated positively with stressor-evoked changes in MAP, and negatively with unbiased, a priori extractions of fMRI blood-oxygen level-dependent signal change values within the sgACC, BNST, PVN and Amyg (n = 138). Abuse-related changes in the function of visceral neural circuits may reflect neurobiological vulnerability to adverse health outcomes conferred by early adversity. PMID:24847113

Precise Spatiotemporal Control of Optogenetic Activation Using an Acousto-Optic Device

PubMed Central

Guo, Yanmeng; Song, Peipei; Zhang, Xiaohui; Zeng, Shaoqun; Wang, Zuoren

2011-01-01

Light activation and inactivation of neurons by optogenetic techniques has emerged as an important tool for studying neural circuit function. To achieve a high resolution, new methods are being developed to selectively manipulate the activity of individual neurons. Here, we report that the combination of an acousto-optic device (AOD) and single-photon laser was used to achieve rapid and precise spatiotemporal control of light stimulation at multiple points in a neural circuit with millisecond time resolution. The performance of this system in activating ChIEF expressed on HEK 293 cells as well as cultured neurons was first evaluated, and the laser stimulation patterns were optimized. Next, the spatiotemporally selective manipulation of multiple neurons was achieved in a precise manner. Finally, we demonstrated the versatility of this high-resolution method in dissecting neural circuits both in the mouse cortical slice and the Drosophila brain in vivo. Taken together, our results show that the combination of AOD-assisted laser stimulation and optogenetic tools provides a flexible solution for manipulating neuronal activity at high efficiency and with high temporal precision. PMID:22174813

Converging on a core cognitive deficit: the impact of various neurodevelopmental insults on cognitive control

PubMed Central

O'Reilly, Kally C.; Kao, Hsin-Yi; Lee, Heekyung; Fenton, André A.

2014-01-01

Despite substantial effort and immense need, the treatment options for major neuropsychiatric illnesses like schizophrenia are limited and largely ineffective at improving the most debilitating cognitive symptoms that are central to mental illness. These symptoms include cognitive control deficits, the inability to selectively use information that is currently relevant and ignore what is currently irrelevant. Contemporary attempts to accelerate progress are in part founded on an effort to reconceptualize neuropsychiatric illness as a disorder of neural development. This neuro-developmental framework emphasizes abnormal neural circuits on the one hand, and on the other, it suggests there are therapeutic opportunities to exploit the developmental processes of excitatory neuron pruning, inhibitory neuron proliferation, elaboration of myelination, and other circuit refinements that extend through adolescence and into early adulthood. We have crafted a preclinical research program aimed at cognition failures that may be relevant to mental illness. By working with a variety of neurodevelopmental rodent models, we strive to identify a common pathophysiology that underlies cognitive control failure as well as a common strategy for improving cognition in the face of neural circuit abnormalities. Here we review our work to characterize cognitive control deficits in rats with a neonatal ventral hippocampus lesion and rats that were exposed to Methylazoxymethanol acetate (MAM) in utero. We review our findings as they pertain to early developmental processes, including neurogenesis, as well as the power of cognitive experience to refine neural circuit function within the mature and maturing brain's cognitive circuitry. PMID:24966811

Large-scale neural circuit mapping data analysis accelerated with the graphical processing unit (GPU).

PubMed

Shi, Yulin; Veidenbaum, Alexander V; Nicolau, Alex; Xu, Xiangmin

2015-01-15

Modern neuroscience research demands computing power. Neural circuit mapping studies such as those using laser scanning photostimulation (LSPS) produce large amounts of data and require intensive computation for post hoc processing and analysis. Here we report on the design and implementation of a cost-effective desktop computer system for accelerated experimental data processing with recent GPU computing technology. A new version of Matlab software with GPU enabled functions is used to develop programs that run on Nvidia GPUs to harness their parallel computing power. We evaluated both the central processing unit (CPU) and GPU-enabled computational performance of our system in benchmark testing and practical applications. The experimental results show that the GPU-CPU co-processing of simulated data and actual LSPS experimental data clearly outperformed the multi-core CPU with up to a 22× speedup, depending on computational tasks. Further, we present a comparison of numerical accuracy between GPU and CPU computation to verify the precision of GPU computation. In addition, we show how GPUs can be effectively adapted to improve the performance of commercial image processing software such as Adobe Photoshop. To our best knowledge, this is the first demonstration of GPU application in neural circuit mapping and electrophysiology-based data processing. Together, GPU enabled computation enhances our ability to process large-scale data sets derived from neural circuit mapping studies, allowing for increased processing speeds while retaining data precision. Copyright © 2014 Elsevier B.V. All rights reserved.

Predicting better performance on a college preparedness test from narrative comprehension at the age of 6 years: An fMRI study.

PubMed

Horowitz-Kraus, Tzipi; Eaton, Kenneth; Farah, Rola; Hajinazarian, Ardag; Vannest, Jennifer; Holland, Scott K

2015-12-10

To investigate whether high performance on college preparedness tests at 18 years of age can be predicted from brain activation patterns during narrative comprehension at 5-7 years of age. In this longitudinal study, functional MRI data during an auditory narrative-comprehension task were acquired from 15 children (5-7 years of age) who also provided their American College Testing (ACT) scores at the age of 18 years. Active voxels during the narrative-comprehension task were correlated with both composite ACT scores and the reading-comprehension component of the exam. Higher composite ACT scores and behavioral scores for reading comprehension were positively correlated with greater activation in frontal and anterior brain regions during the narrative-comprehension task. Our results suggest that neural circuits supporting higher ACT performance are predictable from a narrative-comprehension task at the age of 5-7 years. This supports a critical role for the anterior cingulate cortex, which is a part of the cingulo-opercular cognitive-control network early in development, as a facilitator for better ACT scores. This study highlights that shared neural circuits that support overall ACT performance and neural circuits that support reading comprehension both rely on neural circuits related to narrative comprehension in childhood, suggesting that interventions involving narrative comprehension should be considered for individuals with reading and other academic difficulties. Copyright © 2015 Elsevier B.V. All rights reserved.

Large scale neural circuit mapping data analysis accelerated with the graphical processing unit (GPU)

PubMed Central

Shi, Yulin; Veidenbaum, Alexander V.; Nicolau, Alex; Xu, Xiangmin

2014-01-01

Background Modern neuroscience research demands computing power. Neural circuit mapping studies such as those using laser scanning photostimulation (LSPS) produce large amounts of data and require intensive computation for post-hoc processing and analysis. New Method Here we report on the design and implementation of a cost-effective desktop computer system for accelerated experimental data processing with recent GPU computing technology. A new version of Matlab software with GPU enabled functions is used to develop programs that run on Nvidia GPUs to harness their parallel computing power. Results We evaluated both the central processing unit (CPU) and GPU-enabled computational performance of our system in benchmark testing and practical applications. The experimental results show that the GPU-CPU co-processing of simulated data and actual LSPS experimental data clearly outperformed the multi-core CPU with up to a 22x speedup, depending on computational tasks. Further, we present a comparison of numerical accuracy between GPU and CPU computation to verify the precision of GPU computation. In addition, we show how GPUs can be effectively adapted to improve the performance of commercial image processing software such as Adobe Photoshop. Comparison with Existing Method(s) To our best knowledge, this is the first demonstration of GPU application in neural circuit mapping and electrophysiology-based data processing. Conclusions Together, GPU enabled computation enhances our ability to process large-scale data sets derived from neural circuit mapping studies, allowing for increased processing speeds while retaining data precision. PMID:25277633

Central neural pathways for thermoregulation.

PubMed

Morrison, Shaun F; Nakamura, Kazuhiro

2011-01-01

Central neural circuits orchestrate a homeostatic repertoire to maintain body temperature during environmental temperature challenges and to alter body temperature during the inflammatory response. This review summarizes the functional organization of the neural pathways through which cutaneous thermal receptors alter thermoregulatory effectors: the cutaneous circulation for heat loss, the brown adipose tissue, skeletal muscle and heart for thermogenesis and species-dependent mechanisms (sweating, panting and saliva spreading) for evaporative heat loss. These effectors are regulated by parallel but distinct, effector-specific neural pathways that share a common peripheral thermal sensory input. The thermal afferent circuits include cutaneous thermal receptors, spinal dorsal horn neurons and lateral parabrachial nucleus neurons projecting to the preoptic area to influence warm-sensitive, inhibitory output neurons which control thermogenesis-promoting neurons in the dorsomedial hypothalamus that project to premotor neurons in the rostral ventromedial medulla, including the raphe pallidus, that descend to provide the excitation necessary to drive thermogenic thermal effectors. A distinct population of warm-sensitive preoptic neurons controls heat loss through an inhibitory input to raphe pallidus neurons controlling cutaneous vasoconstriction.

Oscillation-Induced Signal Transmission and Gating in Neural Circuits

PubMed Central

Jahnke, Sven; Memmesheimer, Raoul-Martin; Timme, Marc

2014-01-01

Reliable signal transmission constitutes a key requirement for neural circuit function. The propagation of synchronous pulse packets through recurrent circuits is hypothesized to be one robust form of signal transmission and has been extensively studied in computational and theoretical works. Yet, although external or internally generated oscillations are ubiquitous across neural systems, their influence on such signal propagation is unclear. Here we systematically investigate the impact of oscillations on propagating synchrony. We find that for standard, additive couplings and a net excitatory effect of oscillations, robust propagation of synchrony is enabled in less prominent feed-forward structures than in systems without oscillations. In the presence of non-additive coupling (as mediated by fast dendritic spikes), even balanced oscillatory inputs may enable robust propagation. Here, emerging resonances create complex locking patterns between oscillations and spike synchrony. Interestingly, these resonances make the circuits capable of selecting specific pathways for signal transmission. Oscillations may thus promote reliable transmission and, in co-action with dendritic nonlinearities, provide a mechanism for information processing by selectively gating and routing of signals. Our results are of particular interest for the interpretation of sharp wave/ripple complexes in the hippocampus, where previously learned spike patterns are replayed in conjunction with global high-frequency oscillations. We suggest that the oscillations may serve to stabilize the replay. PMID:25503492

The relative phases of basal ganglia activities dynamically shape effective connectivity in Parkinson's disease.

PubMed

Cagnan, Hayriye; Duff, Eugene Paul; Brown, Peter

2015-06-01

Optimal phase alignment between oscillatory neural circuits is hypothesized to optimize information flow and enhance system performance. This theory is known as communication-through-coherence. The basal ganglia motor circuit exhibits exaggerated oscillatory and coherent activity patterns in Parkinson's disease. Such activity patterns are linked to compromised motor system performance as evinced by bradykinesia, rigidity and tremor, suggesting that network function might actually deteriorate once a certain level of net synchrony is exceeded in the motor circuit. Here, we characterize the processes underscoring excessive synchronization and its termination. To this end, we analysed local field potential recordings from the subthalamic nucleus and globus pallidus of five patients with Parkinson's disease (four male and one female, aged 37-64 years). We observed that certain phase alignments between subthalamic nucleus and globus pallidus amplified local neural synchrony in the beta frequency band while others either suppressed it or did not induce any significant change with respect to surrogates. The increase in local beta synchrony directly correlated with how long the two nuclei locked to beta-amplifying phase alignments. Crucially, administration of the dopamine prodrug, levodopa, reduced the frequency and duration of periods during which subthalamic and pallidal populations were phase-locked to beta-amplifying alignments. Conversely ON dopamine, the total duration over which subthalamic and pallidal populations were aligned to phases that left beta-amplitude unchanged with respect to surrogates increased. Thus dopaminergic input shifted circuit dynamics from persistent periods of locking to amplifying phase alignments, associated with compromised motoric function, to more dynamic phase alignment and improved motoric function. This effect of dopamine on local circuit resonance suggests means by which novel electrical interventions might prevent resonance-related pathological circuit interactions. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain.

Characterization of GdFFD, a d-Amino Acid-containing Neuropeptide That Functions as an Extrinsic Modulator of the Aplysia Feeding Circuit*

PubMed Central

Bai, Lu; Livnat, Itamar; Romanova, Elena V.; Alexeeva, Vera; Yau, Peter M.; Vilim, Ferdinand S.; Weiss, Klaudiusz R.; Jing, Jian; Sweedler, Jonathan V.

2013-01-01

During eukaryotic translation, peptides/proteins are created using l-amino acids. However, a d-amino acid-containing peptide (DAACP) can be produced through post-translational modification via an isomerase enzyme. General approaches to identify novel DAACPs and investigate their function, particularly in specific neural circuits, are lacking. This is primarily due to the difficulty in characterizing this modification and due to the limited information on neural circuits in most species. We describe a multipronged approach to overcome these limitations using the sea slug Aplysia californica. Based on bioinformatics and homology to known DAACPs in the land snail Achatina fulica, we targeted two predicted peptides in Aplysia, GFFD, similar to achatin-I (GdFAD versus GFAD, where dF stands for d-phenylalanine), and YAEFLa, identical to fulyal (YdAEFLa versus YAEFLa), using stereoselective analytical methods, i.e. MALDI MS fragmentation analysis and LC-MS/MS. Although YAEFLa in Aplysia was detected only in an all l-form, we found that both GFFD and GdFFD were present in the Aplysia CNS. In situ hybridization and immunolabeling of GFFD/GdFFD-positive neurons and fibers suggested that GFFD/GdFFD might act as an extrinsic modulator of the feeding circuit. Consistent with this hypothesis, we found that GdFFD induced robust activity in the feeding circuit and elicited egestive motor patterns. In contrast, the peptide consisting of all l-amino acids, GFFD, was not bioactive. Our data indicate that the modification of an l-amino acid-containing neuropeptide to a DAACP is essential for peptide bioactivity in a motor circuit, and thus it provides a functional significance to this modification. PMID:24078634

Principles of motivation revealed by the diverse functions of neuropharmacological and neuroanatomical substrates underlying feeding behavior

PubMed Central

Baldo, Brian A.; Pratt, Wayne E.; Will, Matthew J.; Hanlon, Erin C.; Bakshi, Vaishali P.; Cador, Martine

2013-01-01

Circuits that participate in specific subcomponents of feeding (e.g., gustatory perception, peripheral feedback relevant to satiety and energy balance, reward coding, etc.) are found at all levels of the neural axis. Further complexity is conferred by the wide variety of feeding-modulatory neurotransmitters and neuropeptides that act within these circuits. An ongoing challenge has been to refine the understanding of the functional specificity of these neurotransmitters and circuits, and there have been exciting advances in recent years. We focus here on foundational work of Dr. Ann Kelley that identified distinguishable actions of striatal opioid peptide modulation and dopamine transmission in subcomponents of reward processing. We also discuss her work in overlaying these neuropharmacological effects upon anatomical pathways that link the telencephalon (cortex and basal ganglia) with feeding-control circuits in the hypothalamus. Using these seminal contributions as a starting point, we will discuss new findings that expand our understanding of (1) the specific, differentiable motivational processes that are governed by central dopamine and opioid transmission, (2) the manner in which other striatal neuromodulators, specifically acetylcholine, endocannabinoids and adenosine, modulate these motivational processes (including via interactions with opioid systems), and (3) the organization of the cortical-subcortical network that subserves opioid-driven feeding. The findings discussed here strengthen the view that incentive-motivational properties of food are coded by substrates and neural circuits that are distinguishable from those that mediate the acute hedonic experience of food reward. Striatal opioid transmission modulates reward processing by engaging frontotemporal circuits, possibly via a hypothalamic-thalamic axis, that ultimately impinges upon hypothalamic modules dedicated to autonomic function and motor pattern control. We will conclude by discussing implications for understanding disorders of “non-homeostatic” feeding. PMID:23466532

Principles of motivation revealed by the diverse functions of neuropharmacological and neuroanatomical substrates underlying feeding behavior.

PubMed

Baldo, Brian A; Pratt, Wayne E; Will, Matthew J; Hanlon, Erin C; Bakshi, Vaishali P; Cador, Martine

2013-11-01

Circuits that participate in specific subcomponents of feeding (e.g., gustatory perception, peripheral feedback relevant to satiety and energy balance, reward coding, etc.) are found at all levels of the neural axis. Further complexity is conferred by the wide variety of feeding-modulatory neurotransmitters and neuropeptides that act within these circuits. An ongoing challenge has been to refine the understanding of the functional specificity of these neurotransmitters and circuits, and there have been exciting advances in recent years. We focus here on foundational work of Dr. Ann Kelley that identified distinguishable actions of striatal opioid peptide modulation and dopamine transmission in subcomponents of reward processing. We also discuss her work in overlaying these neuropharmacological effects upon anatomical pathways that link the telencephalon (cortex and basal ganglia) with feeding-control circuits in the hypothalamus. Using these seminal contributions as a starting point, we will discuss new findings that expand our understanding of (1) the specific, differentiable motivational processes that are governed by central dopamine and opioid transmission, (2) the manner in which other striatal neuromodulators, specifically acetylcholine, endocannabinoids and adenosine, modulate these motivational processes (including via interactions with opioid systems), and (3) the organization of the cortical-subcortical network that subserves opioid-driven feeding. The findings discussed here strengthen the view that incentive-motivational properties of food are coded by substrates and neural circuits that are distinguishable from those that mediate the acute hedonic experience of food reward. Striatal opioid transmission modulates reward processing by engaging frontotemporal circuits, possibly via a hypothalamic-thalamic axis, that ultimately impinges upon hypothalamic modules dedicated to autonomic function and motor pattern control. We will conclude by discussing implications for understanding disorders of "non-homeostatic" feeding. Copyright © 2013 Elsevier Ltd. All rights reserved.

A conserved juxtacrine signal regulates synaptic partner recognition in Caenorhabditis elegans

PubMed Central

2011-01-01

Background An essential stage of neural development involves the assembly of neural circuits via formation of inter-neuronal connections. Early steps in neural circuit formation, including cell migration, axon guidance, and the localization of synaptic components, are well described. However, upon reaching their target region, most neurites still contact many potential partners. In order to assemble functional circuits, it is critical that within this group of cells, neurons identify and form connections only with their appropriate partners, a process we call synaptic partner recognition (SPR). To understand how SPR is mediated, we previously developed a genetically encoded fluorescent trans-synaptic marker called NLG-1 GRASP, which labels synaptic contacts between individual neurons of interest in dense cellular environments in the genetic model organism Caenorhabditis elegans. Results Here, we describe the first use of NLG-1 GRASP technology, to identify SPR genes that function in this critical process. The NLG-1 GRASP system allows us to assess synaptogenesis between PHB sensory neurons and AVA interneurons instantly in live animals, making genetic analysis feasible. Additionally, we employ a behavioral assay to specifically test PHB sensory circuit function. Utilizing this approach, we reveal a new role for the secreted UNC-6/Netrin ligand and its transmembrane receptor UNC-40/Deleted in colorectal cancer (DCC) in SPR. Synapses between PHB and AVA are severely reduced in unc-6 and unc-40 animals despite normal axon guidance and subcellular localization of synaptic components. Additionally, behavioral defects indicate a complete disruption of PHB circuit function in unc-40 mutants. Our data indicate that UNC-40 and UNC-6 function in PHB and AVA, respectively, to specify SPR. Strikingly, overexpression of UNC-6 in postsynaptic neurons is sufficient to promote increased PHB-AVA synaptogenesis and to potentiate the behavioral response beyond wild-type levels. Furthermore, an artificially membrane-tethered UNC-6 expressed in the postsynaptic neurons promotes SPR, consistent with a short-range signal between adjacent synaptic partners. Conclusions These results indicate that the conserved UNC-6/Netrin-UNC-40/DCC ligand-receptor pair has a previously unknown function, acting in a juxtacrine manner to specify recognition of individual postsynaptic neurons. Furthermore, they illustrate the potential of this new approach, combining NLG-1 GRASP and behavioral analysis, in gene discovery and characterization. PMID:21663630

Motor Cortical Visuomotor Feedback Activity Is Initially Isolated from Downstream Targets in Output-Null Neural State Space Dimensions.

PubMed

Stavisky, Sergey D; Kao, Jonathan C; Ryu, Stephen I; Shenoy, Krishna V

2017-07-05

Neural circuits must transform new inputs into outputs without prematurely affecting downstream circuits while still maintaining other ongoing communication with these targets. We investigated how this isolation is achieved in the motor cortex when macaques received visual feedback signaling a movement perturbation. To overcome limitations in estimating the mapping from cortex to arm movements, we also conducted brain-machine interface (BMI) experiments where we could definitively identify neural firing patterns as output-null or output-potent. This revealed that perturbation-evoked responses were initially restricted to output-null patterns that cancelled out at the neural population code readout and only later entered output-potent neural dimensions. This mechanism was facilitated by the circuit's large null space and its ability to strongly modulate output-potent dimensions when generating corrective movements. These results show that the nervous system can temporarily isolate portions of a circuit's activity from its downstream targets by restricting this activity to the circuit's output-null neural dimensions. Copyright © 2017 Elsevier Inc. All rights reserved.

Network architectures and circuit function: testing alternative hypotheses in multifunctional networks.

PubMed

Leonard, J L

2000-05-01

Understanding how species-typical movement patterns are organized in the nervous system is a central question in neurobiology. The current explanations involve 'alphabet' models in which an individual neuron may participate in the circuit for several behaviors but each behavior is specified by a specific neural circuit. However, not all of the well-studied model systems fit the 'alphabet' model. The 'equation' model provides an alternative possibility, whereby a system of parallel motor neurons, each with a unique (but overlapping) field of innervation, can account for the production of stereotyped behavior patterns by variable circuits. That is, it is possible for such patterns to arise as emergent properties of a generalized neural network in the absence of feedback, a simple version of a 'self-organizing' behavioral system. Comparison of systems of identified neurons suggest that the 'alphabet' model may account for most observations where CPGs act to organize motor patterns. Other well-known model systems, involving architectures corresponding to feed-forward neural networks with a hidden layer, may organize patterned behavior in a manner consistent with the 'equation' model. Such architectures are found in the Mauthner and reticulospinal circuits, 'escape' locomotion in cockroaches, CNS control of Aplysia gill, and may also be important in the coordination of sensory information and motor systems in insect mushroom bodies and the vertebrate hippocampus. The hidden layer of such networks may serve as an 'internal representation' of the behavioral state and/or body position of the animal, allowing the animal to fine-tune oriented, or particularly context-sensitive, movements to the prevalent conditions. Experiments designed to distinguish between the two models in cases where they make mutually exclusive predictions provide an opportunity to elucidate the neural mechanisms by which behavior is organized in vivo and in vitro. Copyright 2000 S. Karger AG, Basel

Impaired activity-dependent neural circuit assembly and refinement in autism spectrum disorder genetic models

PubMed Central

Doll, Caleb A.; Broadie, Kendal

2014-01-01

Early-use activity during circuit-specific critical periods refines brain circuitry by the coupled processes of eliminating inappropriate synapses and strengthening maintained synapses. We theorize these activity-dependent (A-D) developmental processes are specifically impaired in autism spectrum disorders (ASDs). ASD genetic models in both mouse and Drosophila have pioneered our insights into normal A-D neural circuit assembly and consolidation, and how these developmental mechanisms go awry in specific genetic conditions. The monogenic fragile X syndrome (FXS), a common cause of heritable ASD and intellectual disability, has been particularly well linked to defects in A-D critical period processes. The fragile X mental retardation protein (FMRP) is positively activity-regulated in expression and function, in turn regulates excitability and activity in a negative feedback loop, and appears to be required for the A-D remodeling of synaptic connectivity during early-use critical periods. The Drosophila FXS model has been shown to functionally conserve the roles of human FMRP in synaptogenesis, and has been centrally important in generating our current mechanistic understanding of the FXS disease state. Recent advances in Drosophila optogenetics, transgenic calcium reporters, highly-targeted transgenic drivers for individually-identified neurons, and a vastly improved connectome of the brain are now being combined to provide unparalleled opportunities to both manipulate and monitor A-D processes during critical period brain development in defined neural circuits. The field is now poised to exploit this new Drosophila transgenic toolbox for the systematic dissection of A-D mechanisms in normal versus ASD brain development, particularly utilizing the well-established Drosophila FXS disease model. PMID:24570656

Comparative mapping of GABA-immunoreactive neurons in the central nervous systems of nudibranch molluscs.

PubMed

Gunaratne, Charuni A; Sakurai, Akira; Katz, Paul S

2014-03-01

The relative simplicity of certain invertebrate nervous systems, such as those of gastropod molluscs, allows behaviors to be dissected at the level of small neural circuits composed of individually identifiable neurons. Elucidating the neurotransmitter phenotype of neurons in neural circuits is important for understanding how those neural circuits function. In this study, we examined the distribution of γ-aminobutyric-acid;-immunoreactive (GABA-ir) neurons in four species of sea slugs (Mollusca, Gastropoda, Opisthobranchia, Nudibranchia): Tritonia diomedea, Melibe leonina, Dendronotus iris, and Hermissenda crassicornis. We found consistent patterns of GABA immunoreactivity in the pedal and cerebral-pleural ganglia across species. In particular, there were bilateral clusters in the lateral and medial regions of the dorsal surface of the cerebral ganglia as well as a cluster on the ventral surface of the pedal ganglia. There were also individual GABA-ir neurons that were recognizable across species. The invariant presence of these individual neurons and clusters suggests that they are homologous, although there were interspecies differences in the numbers of neurons in the clusters. The GABAergic system was largely restricted to the central nervous system, with the majority of axons confined to ganglionic connectives and commissures, suggesting a central, integrative role for GABA. GABA was a candidate inhibitory neurotransmitter for neurons in central pattern generator (CPG) circuits underlying swimming behaviors in these species, however none of the known swim CPG neurons were GABA-ir. Although the functions of these GABA-ir neurons are not known, it is clear that their presence has been strongly conserved across nudibranchs. Copyright © 2013 Wiley Periodicals, Inc.

Cholinergic modulation of cognitive processing: insights drawn from computational models

PubMed Central

Newman, Ehren L.; Gupta, Kishan; Climer, Jason R.; Monaghan, Caitlin K.; Hasselmo, Michael E.

2012-01-01

Acetylcholine plays an important role in cognitive function, as shown by pharmacological manipulations that impact working memory, attention, episodic memory, and spatial memory function. Acetylcholine also shows striking modulatory influences on the cellular physiology of hippocampal and cortical neurons. Modeling of neural circuits provides a framework for understanding how the cognitive functions may arise from the influence of acetylcholine on neural and network dynamics. We review the influences of cholinergic manipulations on behavioral performance in working memory, attention, episodic memory, and spatial memory tasks, the physiological effects of acetylcholine on neural and circuit dynamics, and the computational models that provide insight into the functional relationships between the physiology and behavior. Specifically, we discuss the important role of acetylcholine in governing mechanisms of active maintenance in working memory tasks and in regulating network dynamics important for effective processing of stimuli in attention and episodic memory tasks. We also propose that theta rhythm plays a crucial role as an intermediary between the physiological influences of acetylcholine and behavior in episodic and spatial memory tasks. We conclude with a synthesis of the existing modeling work and highlight future directions that are likely to be rewarding given the existing state of the literature for both empiricists and modelers. PMID:22707936

SMN is required for sensory-motor circuit function in Drosophila

PubMed Central

Imlach, Wendy L.; Beck, Erin S.; Choi, Ben Jiwon; Lotti, Francesco; Pellizzoni, Livio; McCabe, Brian D.

2012-01-01

Summary Spinal muscular atrophy (SMA) is a lethal human disease characterized by motor neuron dysfunction and muscle deterioration due to depletion of the ubiquitous Survival Motor Neuron (SMN) protein. Drosophila SMN mutants have reduced muscle size and defective locomotion, motor rhythm and motor neuron neurotransmission. Unexpectedly, restoration of SMN in either muscles or motor neurons did not alter these phenotypes. Instead, SMN must be expressed in proprioceptive neurons and interneurons in the motor circuit to non-autonomously correct defects in motor neurons and muscles. SMN depletion disrupts the motor system subsequent to circuit development and can be mimicked by the inhibition of motor network function. Furthermore, increasing motor circuit excitability by genetic or pharmacological inhibition of K+ channels can correct SMN-dependent phenotypes. These results establish sensory-motor circuit dysfunction as the origin of motor system deficits in this SMA model and suggest that enhancement of motor neural network activity could ameliorate the disease. PMID:23063130

A modeling framework for deriving the structural and functional architecture of a short-term memory microcircuit.

PubMed

Fisher, Dimitry; Olasagasti, Itsaso; Tank, David W; Aksay, Emre R F; Goldman, Mark S

2013-09-04

Although many studies have identified neural correlates of memory, relatively little is known about the circuit properties connecting single-neuron physiology to behavior. Here we developed a modeling framework to bridge this gap and identify circuit interactions capable of maintaining short-term memory. Unlike typical studies that construct a phenomenological model and test whether it reproduces select aspects of neuronal data, we directly fit the synaptic connectivity of an oculomotor memory circuit to a broad range of anatomical, electrophysiological, and behavioral data. Simultaneous fits to all data, combined with sensitivity analyses, revealed complementary roles of synaptic and neuronal recruitment thresholds in providing the nonlinear interactions required to generate the observed circuit behavior. This work provides a methodology for identifying the cellular and synaptic mechanisms underlying short-term memory and demonstrates how the anatomical structure of a circuit may belie its functional organization. Copyright © 2013 Elsevier Inc. All rights reserved.

Linking ADHD to the Neural Circuitry of Attention

PubMed Central

Mueller, Adrienne; Hong, David S.; Shepard, Steven; Moore, Tirin

2017-01-01

ADHD is a complex condition with a heterogeneous presentation. Current diagnosis is primarily based on subjective experience and observer reports of behavioral symptoms – an approach that has significant limitations. Many studies show that individuals with ADHD exhibit poorer performance on cognitive tasks than neurotypical controls, and at least seven main functional domains appear implicated in ADHD. We discuss the underlying neural mechanisms of cognitive functions associated with ADHD with emphasis on the neural basis of selective attention, demonstrating the feasibility of basic research approaches for further understanding cognitive behavioral processes as they relate to human psychopathology. The study of circuit-level mechanisms underlying executive functions in nonhuman primates holds promise for advancing our understanding, and ultimately the treatment, of ADHD. PMID:28483638

Hardware implementation of an adaptive resonance theory (ART) neural network using compensated operational amplifiers

NASA Astrophysics Data System (ADS)

Ho, Ching S.; Liou, Juin J.; Georgiopoulos, Michael; Christodoulou, Christos G.

1994-03-01

This paper presents an analog circuit design and implementation for an adaptive resonance theory neural network architecture called the augmented ART1 neural network (AART1-NN). Practical monolithic operational amplifiers (Op-Amps) LM741 and LM318 are selected to implement the circuit, and a simple compensation scheme is developed to adjust the Op-Amp electrical characteristics to meet the design requirement. A 7-node prototype circuit has been designed and verified using the Pspice circuit simulator run on a Sun workstation. Results simulated from the AART1-NN circuit using the LM741, LM318, and ideal Op-Amps are presented and compared.

Active C4 Electrodes for Local Field Potential Recording Applications

PubMed Central

Wang, Lu; Freedman, David; Sahin, Mesut; Ünlü, M. Selim; Knepper, Ronald

2016-01-01

Extracellular neural recording, with multi-electrode arrays (MEAs), is a powerful method used to study neural function at the network level. However, in a high density array, it can be costly and time consuming to integrate the active circuit with the expensive electrodes. In this paper, we present a 4 mm × 4 mm neural recording integrated circuit (IC) chip, utilizing IBM C4 bumps as recording electrodes, which enable a seamless active chip and electrode integration. The IC chip was designed and fabricated in a 0.13 μm BiCMOS process for both in vitro and in vivo applications. It has an input-referred noise of 4.6 μVrms for the bandwidth of 10 Hz to 10 kHz and a power dissipation of 11.25 mW at 2.5 V, or 43.9 μW per input channel. This prototype is scalable for implementing larger number and higher density electrode arrays. To validate the functionality of the chip, electrical testing results and acute in vivo recordings from a rat barrel cortex are presented. PMID:26861324

The neurobiology of focus and distraction: The case for incorporating mindfulness into leadership.

PubMed

Mohapel, Paul

2018-05-01

Increasingly health leaders are experiencing greater demands and pressures, which require the need for better focus while limiting unwarranted distractions. This article offers a neurobiological explanation of how the brain focuses and becomes distracted, in order to help health leaders gain insight into their own effectiveness. Two main neural circuits are contrasted: the mind-wandering default mode circuit and the attentional central executive system. These two systems act in an antagonistic pairing, where the degree of toggling between systems is associated with the degree a person can sustain focus and filter out unwarranted distractions. Excessive multitasking appears to compromise the neural switch of these two systems, thereby diminishing our focus and concentration. In contrast, mindfulness practice is shown to have the opposite effect by enhancing the neural switch, thereby enhancing leadership focus that can lead to greater flexibility, foresight, regulation, and creativity. To conclude, leaders who are excessively distracted, such as with multitasking, may be compromising cognitive brain functioning, while engaging in mindfulness may replenish the brain and thereby enhance leaders' ability to sustain focus and tap into higher cognitive functioning.

Computational Models and Emergent Properties of Respiratory Neural Networks

PubMed Central

Lindsey, Bruce G.; Rybak, Ilya A.; Smith, Jeffrey C.

2012-01-01

Computational models of the neural control system for breathing in mammals provide a theoretical and computational framework bringing together experimental data obtained from different animal preparations under various experimental conditions. Many of these models were developed in parallel and iteratively with experimental studies and provided predictions guiding new experiments. This data-driven modeling approach has advanced our understanding of respiratory network architecture and neural mechanisms underlying generation of the respiratory rhythm and pattern, including their functional reorganization under different physiological conditions. Models reviewed here vary in neurobiological details and computational complexity and span multiple spatiotemporal scales of respiratory control mechanisms. Recent models describe interacting populations of respiratory neurons spatially distributed within the Bötzinger and pre-Bötzinger complexes and rostral ventrolateral medulla that contain core circuits of the respiratory central pattern generator (CPG). Network interactions within these circuits along with intrinsic rhythmogenic properties of neurons form a hierarchy of multiple rhythm generation mechanisms. The functional expression of these mechanisms is controlled by input drives from other brainstem components, including the retrotrapezoid nucleus and pons, which regulate the dynamic behavior of the core circuitry. The emerging view is that the brainstem respiratory network has rhythmogenic capabilities at multiple levels of circuit organization. This allows flexible, state-dependent expression of different neural pattern-generation mechanisms under various physiological conditions, enabling a wide repertoire of respiratory behaviors. Some models consider control of the respiratory CPG by pulmonary feedback and network reconfiguration during defensive behaviors such as cough. Future directions in modeling of the respiratory CPG are considered. PMID:23687564

Integrating Functional Brain Neuroimaging and Developmental Cognitive Neuroscience in Child Psychiatry Research

ERIC Educational Resources Information Center

Pavuluri, Mani N.; Sweeney, John A.

2008-01-01

The use of cognitive neuroscience and functional brain neuroimaging to understand brain dysfunction in pediatric psychiatric disorders is discussed. Results show that bipolar youths demonstrate impairment in affective and cognitive neural systems and in these two circuits' interface. Implications for the diagnosis and treatment of psychiatric…

A Common Function of Basal Ganglia-Cortical Circuits Subserving Speed in Both Motor and Cognitive Domains.

PubMed

Hanakawa, Takashi; Goldfine, Andrew M; Hallett, Mark

2017-01-01

Distinct regions of the frontal cortex connect with their basal ganglia and thalamic counterparts, constituting largely segregated basal ganglia-thalamo-cortical (BTC) circuits. However, any common role of the BTC circuits in different behavioral domains remains unclear. Indeed, whether dysfunctional motor and cognitive BTC circuits are responsible for motor slowing and cognitive slowing, respectively, in Parkinson's disease (PD) is a matter of debate. Here, we used an effortful behavioral paradigm in which the effects of task rate on accuracy were tested in movement, imagery, and calculation tasks in humans. Using nonlinear fitting, we separated baseline accuracy ( A base ) and "agility" (ability to function quickly) components of performance in healthy participants and then confirmed reduced agility and preserved A base for the three tasks in PD. Using functional magnetic resonance imaging (fMRI) and diffusion tractography, we explored the neural substrates underlying speeded performance of the three tasks in healthy participants, suggesting the involvement of distinct BTC circuits in cognitive and motor agility. Language and motor BTC circuits were specifically active during speeded performance of the calculation and movement tasks, respectively, whereas premotor BTC circuits revealed activity for speeded performance of all tasks. Finally, PD showed reduced task rate-correlated activity in the language BTC circuits for speeded calculation, in the premotor BTC circuit for speeded imagery, and in the motor BTC circuits for speeded movement, as compared with controls. The present study casts light on the anatomo-functional organization of the BTC circuits and their parallel roles in invigorating movement and cognition through a function of dopamine.

A Common Function of Basal Ganglia-Cortical Circuits Subserving Speed in Both Motor and Cognitive Domains

PubMed Central

2017-01-01

Abstract Distinct regions of the frontal cortex connect with their basal ganglia and thalamic counterparts, constituting largely segregated basal ganglia-thalamo-cortical (BTC) circuits. However, any common role of the BTC circuits in different behavioral domains remains unclear. Indeed, whether dysfunctional motor and cognitive BTC circuits are responsible for motor slowing and cognitive slowing, respectively, in Parkinson’s disease (PD) is a matter of debate. Here, we used an effortful behavioral paradigm in which the effects of task rate on accuracy were tested in movement, imagery, and calculation tasks in humans. Using nonlinear fitting, we separated baseline accuracy (Abase) and “agility” (ability to function quickly) components of performance in healthy participants and then confirmed reduced agility and preserved Abase for the three tasks in PD. Using functional magnetic resonance imaging (fMRI) and diffusion tractography, we explored the neural substrates underlying speeded performance of the three tasks in healthy participants, suggesting the involvement of distinct BTC circuits in cognitive and motor agility. Language and motor BTC circuits were specifically active during speeded performance of the calculation and movement tasks, respectively, whereas premotor BTC circuits revealed activity for speeded performance of all tasks. Finally, PD showed reduced task rate-correlated activity in the language BTC circuits for speeded calculation, in the premotor BTC circuit for speeded imagery, and in the motor BTC circuits for speeded movement, as compared with controls. The present study casts light on the anatomo-functional organization of the BTC circuits and their parallel roles in invigorating movement and cognition through a function of dopamine. PMID:29379873

Altered topology of neural circuits in congenital prosopagnosia.

PubMed

Rosenthal, Gideon; Tanzer, Michal; Simony, Erez; Hasson, Uri; Behrmann, Marlene; Avidan, Galia

2017-08-21

Using a novel, fMRI-based inter-subject functional correlation (ISFC) approach, which isolates stimulus-locked inter-regional correlation patterns, we compared the cortical topology of the neural circuit for face processing in participants with an impairment in face recognition, congenital prosopagnosia (CP), and matched controls. Whereas the anterior temporal lobe served as the major network hub for face processing in controls, this was not the case for the CPs. Instead, this group evinced hyper-connectivity in posterior regions of the visual cortex, mostly associated with the lateral occipital and the inferior temporal cortices. Moreover, the extent of this hyper-connectivity was correlated with the face recognition deficit. These results offer new insights into the perturbed cortical topology in CP, which may serve as the underlying neural basis of the behavioral deficits typical of this disorder. The approach adopted here has the potential to uncover altered topologies in other neurodevelopmental disorders, as well.

Neural Circuits Underlying Crying and Cry Responding in Mammals

PubMed Central

Newman, John D.

2007-01-01

Crying is a universal vocalization in human infants, as well as in the infants of other mammals. Little is known about the neural structures underlying cry production, or the circuitry that mediates a caregiver’s response to cry sounds. In this review, the specific structures known or suspected to be involved in this circuit are identified, along with neurochemical systems and hormones for which evidence suggests a role in responding to infants and infant cries. In addition, evidence that crying elicits parental responses in different mammals is presented. An argument is made for including ‘crying’ as a functional category in the vocal repertoire of all mammalian infants (and the adults of some species). The prevailing neural model for crying production considers forebrain structures to be dispensable. However, evidence for the anterior cingulate gyrus in cry production, and this structure along with the amygdala and some other forebrain areas in responding to cries is presented. PMID:17363076

Functional connectivity decreases in autism in emotion, self, and face circuits identified by Knowledge-based Enrichment Analysis.

PubMed

Cheng, Wei; Rolls, Edmund T; Zhang, Jie; Sheng, Wenbo; Ma, Liang; Wan, Lin; Luo, Qiang; Feng, Jianfeng

2017-03-01

A powerful new method is described called Knowledge based functional connectivity Enrichment Analysis (KEA) for interpreting resting state functional connectivity, using circuits that are functionally identified using search terms with the Neurosynth database. The method derives its power by focusing on neural circuits, sets of brain regions that share a common biological function, instead of trying to interpret single functional connectivity links. This provides a novel way of investigating how task- or function-related networks have resting state functional connectivity differences in different psychiatric states, provides a new way to bridge the gap between task and resting-state functional networks, and potentially helps to identify brain networks that might be treated. The method was applied to interpreting functional connectivity differences in autism. Functional connectivity decreases at the network circuit level in 394 patients with autism compared with 473 controls were found in networks involving the orbitofrontal cortex, anterior cingulate cortex, middle temporal gyrus cortex, and the precuneus, in networks that are implicated in the sense of self, face processing, and theory of mind. The decreases were correlated with symptom severity. Copyright © 2017. Published by Elsevier Inc.

Changes in brain activation during working memory and facial recognition tasks in patients with bipolar disorder with Lamotrigine monotherapy.

PubMed

Haldane, Morgan; Jogia, Jigar; Cobb, Annabel; Kozuch, Eliza; Kumari, Veena; Frangou, Sophia

2008-01-01

Verbal working memory and emotional self-regulation are impaired in Bipolar Disorder (BD). Our aim was to investigate the effect of Lamotrigine (LTG), which is effective in the clinical management of BD, on the neural circuits subserving working memory and emotional processing. Functional Magnetic Resonance Imaging data from 12 stable BD patients was used to detect LTG-induced changes as the differences in brain activity between drug-free and post-LTG monotherapy conditions during a verbal working memory (N-back sequential letter task) and an angry facial affect recognition task. For both tasks, LGT monotherapy compared to baseline was associated with increased activation mostly within the prefrontal cortex and cingulate gyrus, in regions normally engaged in verbal working memory and emotional processing. Therefore, LTG monotherapy in BD patients may enhance cortical function within neural circuits involved in memory and emotional self-regulation.

Dynamic labelling of neural connections in multiple colours by trans-synaptic fluorescence complementation

PubMed Central

Macpherson, Lindsey J.; Zaharieva, Emanuela E.; Kearney, Patrick J.; Alpert, Michael H.; Lin, Tzu-Yang; Turan, Zeynep; Lee, Chi-Hon; Gallio, Marco

2015-01-01

Determining the pattern of activity of individual connections within a neural circuit could provide insights into the computational processes that underlie brain function. Here, we develop new strategies to label active synapses by trans-synaptic fluorescence complementation in Drosophila. First, we demonstrate that a synaptobrevin-GRASP chimera functions as a powerful activity-dependent marker for synapses in vivo. Next, we create cyan and yellow variants, achieving activity-dependent, multi-colour fluorescence reconstitution across synapses (X-RASP). Our system allows for the first time retrospective labelling of synapses (rather than whole neurons) based on their activity, in multiple colours, in the same animal. As individual synapses often act as computational units in the brain, our method will promote the design of experiments that are not possible using existing techniques. Moreover, our strategies are easily adaptable to circuit mapping in any genetic system. PMID:26635273

Dopamine prediction errors in reward learning and addiction: from theory to neural circuitry

PubMed Central

Keiflin, Ronald; Janak, Patricia H.

2015-01-01

Summary Midbrain dopamine (DA) neurons are proposed to signal reward prediction error (RPE), a fundamental parameter in associative learning models. This RPE hypothesis provides a compelling theoretical framework for understanding DA function in reward learning and addiction. New studies support a causal role for DA-mediated RPE activity in promoting learning about natural reward; however, this question has not been explicitly tested in the context of drug addiction. In this review, we integrate theoretical models with experimental findings on the activity of DA systems, and on the causal role of specific neuronal projections and cell types, to provide a circuit-based framework for probing DA-RPE function in addiction. By examining error-encoding DA neurons in the neural network in which they are embedded, hypotheses regarding circuit-level adaptations that possibly contribute to pathological error-signaling and addiction can be formulated and tested. PMID:26494275

A Fly's Eye View of Natural and Drug Reward.

PubMed

Lowenstein, Eve G; Velazquez-Ulloa, Norma A

2018-01-01

Animals encounter multiple stimuli each day. Some of these stimuli are innately appetitive or aversive, while others are assigned valence based on experience. Drugs like ethanol can elicit aversion in the short term and attraction in the long term. The reward system encodes the predictive value for different stimuli, mediating anticipation for attractive or punishing stimuli and driving animal behavior to approach or avoid conditioned stimuli. The neurochemistry and neurocircuitry of the reward system is partly evolutionarily conserved. In both vertebrates and invertebrates, including Drosophila melanogaster , dopamine is at the center of a network of neurotransmitters and neuromodulators acting in concert to encode rewards. Behavioral assays in D. melanogaster have become increasingly sophisticated, allowing more direct comparison with mammalian research. Moreover, recent evidence has established the functional modularity of the reward neural circuits in Drosophila . This functional modularity resembles the organization of reward circuits in mammals. The powerful genetic and molecular tools for D. melanogaster allow characterization and manipulation at the single-cell level. These tools are being used to construct a detailed map of the neural circuits mediating specific rewarding stimuli and have allowed for the identification of multiple genes and molecular pathways that mediate the effects of reinforcing stimuli, including their rewarding effects. This report provides an overview of the research on natural and drug reward in D. melanogaster , including natural rewards such as sugar and other food nutrients, and drug rewards including ethanol, cocaine, amphetamine, methamphetamine, and nicotine. We focused mainly on the known genetic and neural mechanisms underlying appetitive reward for sugar and reward for ethanol. We also include genes, molecular pathways, and neural circuits that have been identified using assays that test the palatability of the rewarding stimulus, the preference for the rewarding stimulus, or other effects of the stimulus that indicate how it can modify behavior. Commonalities between mechanisms of natural and drug reward are highlighted and future directions are presented, putting forward questions best suited for research using D. melanogaster as a model organism.

A Fly’s Eye View of Natural and Drug Reward

PubMed Central

Lowenstein, Eve G.; Velazquez-Ulloa, Norma A.

2018-01-01

Animals encounter multiple stimuli each day. Some of these stimuli are innately appetitive or aversive, while others are assigned valence based on experience. Drugs like ethanol can elicit aversion in the short term and attraction in the long term. The reward system encodes the predictive value for different stimuli, mediating anticipation for attractive or punishing stimuli and driving animal behavior to approach or avoid conditioned stimuli. The neurochemistry and neurocircuitry of the reward system is partly evolutionarily conserved. In both vertebrates and invertebrates, including Drosophila melanogaster, dopamine is at the center of a network of neurotransmitters and neuromodulators acting in concert to encode rewards. Behavioral assays in D. melanogaster have become increasingly sophisticated, allowing more direct comparison with mammalian research. Moreover, recent evidence has established the functional modularity of the reward neural circuits in Drosophila. This functional modularity resembles the organization of reward circuits in mammals. The powerful genetic and molecular tools for D. melanogaster allow characterization and manipulation at the single-cell level. These tools are being used to construct a detailed map of the neural circuits mediating specific rewarding stimuli and have allowed for the identification of multiple genes and molecular pathways that mediate the effects of reinforcing stimuli, including their rewarding effects. This report provides an overview of the research on natural and drug reward in D. melanogaster, including natural rewards such as sugar and other food nutrients, and drug rewards including ethanol, cocaine, amphetamine, methamphetamine, and nicotine. We focused mainly on the known genetic and neural mechanisms underlying appetitive reward for sugar and reward for ethanol. We also include genes, molecular pathways, and neural circuits that have been identified using assays that test the palatability of the rewarding stimulus, the preference for the rewarding stimulus, or other effects of the stimulus that indicate how it can modify behavior. Commonalities between mechanisms of natural and drug reward are highlighted and future directions are presented, putting forward questions best suited for research using D. melanogaster as a model organism. PMID:29720947

Cognitive Neural Prosthetics

PubMed Central

Andersen, Richard A.; Hwang, Eun Jung; Mulliken, Grant H.

2010-01-01

The cognitive neural prosthetic (CNP) is a very versatile method for assisting paralyzed patients and patients with amputations. The CNP records the cognitive state of the subject, rather than signals strictly related to motor execution or sensation. We review a number of high-level cortical signals and their application for CNPs, including intention, motor imagery, decision making, forward estimation, executive function, attention, learning, and multi-effector movement planning. CNPs are defined by the cognitive function they extract, not the cortical region from which the signals are recorded. However, some cortical areas may be better than others for particular applications. Signals can also be extracted in parallel from multiple cortical areas using multiple implants, which in many circumstances can increase the range of applications of CNPs. The CNP approach relies on scientific understanding of the neural processes involved in cognition, and many of the decoding algorithms it uses also have parallels to underlying neural circuit functions. PMID:19575625

Low Temperature Performance of High-Speed Neural Network Circuits

NASA Technical Reports Server (NTRS)

Duong, T.; Tran, M.; Daud, T.; Thakoor, A.

1995-01-01

Artificial neural networks, derived from their biological counterparts, offer a new and enabling computing paradigm specially suitable for such tasks as image and signal processing with feature classification/object recognition, global optimization, and adaptive control. When implemented in fully parallel electronic hardware, it offers orders of magnitude speed advantage. Basic building blocks of the new architecture are the processing elements called neurons implemented as nonlinear operational amplifiers with sigmoidal transfer function, interconnected through weighted connections called synapses implemented using circuitry for weight storage and multiply functions either in an analog, digital, or hybrid scheme.

Chaos in a neural network circuit

NASA Astrophysics Data System (ADS)

Kepler, Thomas B.; Datt, Sumeet; Meyer, Robert B.; Abott, L. F.

1990-12-01

We have constructed a neural network circuit of four clipped, high-grain, integrating operational amplifiers coupled to each other through an array of digitally programmable resistor ladders (MDACs). In addition to fixed-point and cyclic behavior, the circuit exhibits chaotic behavior with complex strange attractors which are approached through period doubling, intermittent attractor expansion and/or quasiperiodic pathways. Couplings between the nonlinear circuit elements are controlled by a computer which can automatically search through the space of couplings for interesting phenomena. We report some initial statistical results relating the behavior of the network to properties of its coupling matrix. Through these results and further research the circuit should help resolve fundamental issues concerning chaos in neural networks.

Adaptive Neurotechnology for Making Neural Circuits Functional .

NASA Astrophysics Data System (ADS)

Jung, Ranu

2008-03-01

Two of the most important trends in recent technological developments are that technology is increasingly integrated with biological systems and that it is increasingly adaptive in its capabilities. Neuroprosthetic systems that provide lost sensorimotor function after a neural disability offer a platform to investigate this interplay between biological and engineered systems. Adaptive neurotechnology (hardware and software) could be designed to be biomimetic, guided by the physical and programmatic constraints observed in biological systems, and allow for real-time learning, stability, and error correction. An example will present biomimetic neural-network hardware that can be interfaced with the isolated spinal cord of a lower vertebrate to allow phase-locked real-time neural control. Another will present adaptive neural network control algorithms for functional electrical stimulation of the peripheral nervous system to provide desired movements of paralyzed limbs in rodents or people. Ultimately, the frontier lies in being able to utilize the adaptive neurotechnology to promote neuroplasticity in the living system on a long-time scale under co-adaptive conditions.

Striatal Circuits as a Common Node for Autism Pathophysiology

PubMed Central

Fuccillo, Marc V.

2016-01-01

Autism spectrum disorders (ASD) are characterized by two seemingly unrelated symptom domains—deficits in social interactions and restrictive, repetitive patterns of behavioral output. Whether the diverse nature of ASD symptomatology represents distributed dysfunction of brain networks or abnormalities within specific neural circuits is unclear. Striatal dysfunction is postulated to underlie the repetitive motor behaviors seen in ASD, and neurological and brain-imaging studies have supported this assumption. However, as our appreciation of striatal function expands to include regulation of behavioral flexibility, motivational state, goal-directed learning, and attention, we consider whether alterations in striatal physiology are a central node mediating a range of autism-associated behaviors, including social and cognitive deficits that are hallmarks of the disease. This review investigates multiple genetic mouse models of ASD to explore whether abnormalities in striatal circuits constitute a common pathophysiological mechanism in the development of autism-related behaviors. Despite the heterogeneity of genetic insult investigated, numerous genetic ASD models display alterations in the structure and function of striatal circuits, as well as abnormal behaviors including repetitive grooming, stereotypic motor routines, deficits in social interaction and decision-making. Comparative analysis in rodents provides a unique opportunity to leverage growing genetic association data to reveal canonical neural circuits whose dysfunction directly contributes to discrete aspects of ASD symptomatology. The description of such circuits could provide both organizing principles for understanding the complex genetic etiology of ASD as well as novel treatment routes. Furthermore, this focus on striatal mechanisms of behavioral regulation may also prove useful for exploring the pathogenesis of other neuropsychiatric diseases, which display overlapping behavioral deficits with ASD. PMID:26903795

Temporal relation between neural activity and neurite pruning on a numerical model and a microchannel device with micro electrode array.

PubMed

Kondo, Yohei; Yada, Yuichiro; Haga, Tatsuya; Takayama, Yuzo; Isomura, Takuya; Jimbo, Yasuhiko; Fukayama, Osamu; Hoshino, Takayuki; Mabuchi, Kunihiko

2017-04-29

Synapse elimination and neurite pruning are essential processes for the formation of neuronal circuits. These regressive events depend on neural activity and occur in the early postnatal days known as the critical period, but what makes this temporal specificity is not well understood. One possibility is that the neural activities during the developmentally regulated shift of action of GABA inhibitory transmission lead to the critical period. Moreover, it has been reported that the shifting action of the inhibitory transmission on immature neurons overlaps with synapse elimination and neurite pruning and that increased inhibitory transmission by drug treatment could induce temporal shift of the critical period. However, the relationship among these phenomena remains unclear because it is difficult to experimentally show how the developmental shift of inhibitory transmission influences neural activities and whether the activities promote synapse elimination and neurite pruning. In this study, we modeled synapse elimination in neuronal circuits using the modified Izhikevich's model with functional shifting of GABAergic transmission. The simulation results show that synaptic pruning within a specified period like the critical period is spontaneously generated as a function of the developmentally shifting inhibitory transmission and that the specific firing rate and increasing synchronization of neural circuits are seen at the initial stage of the critical period. This temporal relationship was experimentally supported by an in vitro primary culture of rat cortical neurons in a microchannel on a multi-electrode array (MEA). The firing rate decreased remarkably between the 18-25 days in vitro (DIV), and following these changes in the firing rate, the neurite density was slightly reduced. Our simulation and experimental results suggest that decreasing neural activity due to developing inhibitory synaptic transmission could induce synapse elimination and neurite pruning at particular time such as the critical period. Additionally, these findings indicate that we can estimate the maturity level of inhibitory transmission and the critical period by measuring the firing rate and the degree of synchronization in engineered neural networks. Copyright © 2017 Elsevier Inc. All rights reserved.

Systemic lipopolysaccharide administration impairs retrieval of context-object discrimination, but not spatial, memory: Evidence for selective disruption of specific hippocampus-dependent memory functions during acute neuroinflammation

PubMed Central

Czerniawski, Jennifer; Miyashita, Teiko; Lewandowski, Gail; Guzowski, John F.

2014-01-01

Neuroinflammation is implicated in impairments in neuronal function and cognition that arise with aging, trauma, and/or disease. Therefore, understanding the underlying basis of the effect of immune system activation on neural function could lead to therapies for treating cognitive decline. Although neuroinflammation is widely thought to preferentially impair hippocampus-dependent memory, data on the effects of cytokines on cognition are mixed. One possible explanation for these inconsistent results is that cytokines may disrupt specific neural processes underlying some forms of memory but not others. In an earlier study, we tested the effect of systemic administration of bacterial lipopolysaccharide (LPS) on retrieval of hippocampus-dependent context memory and neural circuit function in CA3 and CA1 (Czerniawski and Guzowski, 2014). Paralleling impairment in context discrimination memory, we observed changes in neural circuit function consistent with disrupted pattern separation function. In the current study we tested the hypothesis that acute neuroinflammation selectively disrupts memory retrieval in tasks requiring hippocampal pattern separation processes. Male Sprague-Dawley rats given LPS systemically prior to testing exhibited intact performance in tasks that do not require hippocampal pattern separation processes: novel object recognition and spatial memory in the water maze. By contrast, memory retrieval in a task thought to require hippocampal pattern separation, context-object discrimination, was strongly impaired in LPS-treated rats in the absence of any gross effects on exploratory activity or motivation. These data show that LPS administration does not impair memory retrieval in all hippocampus-dependent tasks, and support the hypothesis that acute neuroinflammation impairs context discrimination memory via disruption of pattern separation processes in hippocampus. PMID:25451612

Systemic lipopolysaccharide administration impairs retrieval of context-object discrimination, but not spatial, memory: Evidence for selective disruption of specific hippocampus-dependent memory functions during acute neuroinflammation.

PubMed

Czerniawski, Jennifer; Miyashita, Teiko; Lewandowski, Gail; Guzowski, John F

2015-02-01

Neuroinflammation is implicated in impairments in neuronal function and cognition that arise with aging, trauma, and/or disease. Therefore, understanding the underlying basis of the effect of immune system activation on neural function could lead to therapies for treating cognitive decline. Although neuroinflammation is widely thought to preferentially impair hippocampus-dependent memory, data on the effects of cytokines on cognition are mixed. One possible explanation for these inconsistent results is that cytokines may disrupt specific neural processes underlying some forms of memory but not others. In an earlier study, we tested the effect of systemic administration of bacterial lipopolysaccharide (LPS) on retrieval of hippocampus-dependent context memory and neural circuit function in CA3 and CA1 (Czerniawski and Guzowski, 2014). Paralleling impairment in context discrimination memory, we observed changes in neural circuit function consistent with disrupted pattern separation function. In the current study we tested the hypothesis that acute neuroinflammation selectively disrupts memory retrieval in tasks requiring hippocampal pattern separation processes. Male Sprague-Dawley rats given LPS systemically prior to testing exhibited intact performance in tasks that do not require hippocampal pattern separation processes: novel object recognition and spatial memory in the water maze. By contrast, memory retrieval in a task thought to require hippocampal pattern separation, context-object discrimination, was strongly impaired in LPS-treated rats in the absence of any gross effects on exploratory activity or motivation. These data show that LPS administration does not impair memory retrieval in all hippocampus-dependent tasks, and support the hypothesis that acute neuroinflammation impairs context discrimination memory via disruption of pattern separation processes in hippocampus. Copyright © 2014 Elsevier Inc. All rights reserved.

Seeing the whole picture: A comprehensive imaging approach to functional mapping of circuits in behaving zebrafish.

PubMed

Feierstein, C E; Portugues, R; Orger, M B

2015-06-18

In recent years, the zebrafish has emerged as an appealing model system to tackle questions relating to the neural circuit basis of behavior. This can be attributed not just to the growing use of genetically tractable model organisms, but also in large part to the rapid advances in optical techniques for neuroscience, which are ideally suited for application to the small, transparent brain of the larval fish. Many characteristic features of vertebrate brains, from gross anatomy down to particular circuit motifs and cell-types, as well as conserved behaviors, can be found in zebrafish even just a few days post fertilization, and, at this early stage, the physical size of the brain makes it possible to analyze neural activity in a comprehensive fashion. In a recent study, we used a systematic and unbiased imaging method to record the pattern of activity dynamics throughout the whole brain of larval zebrafish during a simple visual behavior, the optokinetic response (OKR). This approach revealed the broadly distributed network of neurons that were active during the behavior and provided insights into the fine-scale functional architecture in the brain, inter-individual variability, and the spatial distribution of behaviorally relevant signals. Combined with mapping anatomical and functional connectivity, targeted electrophysiological recordings, and genetic labeling of specific populations, this comprehensive approach in zebrafish provides an unparalleled opportunity to study complete circuits in a behaving vertebrate animal. Copyright © 2014. Published by Elsevier Ltd.

The neural circuits of innate fear: detection, integration, action, and memorization

PubMed Central

Silva, Bianca A.; Gross, Cornelius T.

2016-01-01

How fear is represented in the brain has generated a lot of research attention, not only because fear increases the chances for survival when appropriately expressed but also because it can lead to anxiety and stress-related disorders when inadequately processed. In this review, we summarize recent progress in the understanding of the neural circuits processing innate fear in rodents. We propose that these circuits are contained within three main functional units in the brain: a detection unit, responsible for gathering sensory information signaling the presence of a threat; an integration unit, responsible for incorporating the various sensory information and recruiting downstream effectors; and an output unit, in charge of initiating appropriate bodily and behavioral responses to the threatful stimulus. In parallel, the experience of innate fear also instructs a learning process leading to the memorization of the fearful event. Interestingly, while the detection, integration, and output units processing acute fear responses to different threats tend to be harbored in distinct brain circuits, memory encoding of these threats seems to rely on a shared learning system. PMID:27634145

Cell-type Specific Optogenetic Mice for Dissecting Neural Circuitry Function

PubMed Central

Zhao, Shengli; Ting, Jonathan T.; Atallah, Hisham E.; Qiu, Li; Tan, Jie; Gloss, Bernd; Augustine, George J.; Deisseroth, Karl; Luo, Minmin; Graybiel, Ann M.; Feng, Guoping

2011-01-01

Optogenetic methods have emerged as powerful tools for dissecting neural circuit connectivity, function, and dysfunction. We used a Bacterial Artificial Chromosome (BAC) transgenic strategy to express Channelrhodopsin2 (ChR2) under the control of cell-type specific promoter elements. We provide a detailed functional characterization of the newly established VGAT-ChR2-EYFP, ChAT-ChR2-EYFP, TPH2-ChR2-EYFP and Pvalb-ChR2-EYFP BAC transgenic mouse lines and demonstrate the utility of these lines for precisely controlling action potential firing of GABAergic, cholinergic, serotonergic, and parvalbumin+ neuron subsets using blue light. This resource of cell type-specific ChR2 mouse lines will facilitate the precise mapping of neuronal connectivity and the dissection of the neural basis of behavior. PMID:21985008

Deconstruction of a neural circuit for hunger.

PubMed

Atasoy, Deniz; Betley, J Nicholas; Su, Helen H; Sternson, Scott M

2012-08-09

Hunger is a complex behavioural state that elicits intense food seeking and consumption. These behaviours are rapidly recapitulated by activation of starvation-sensitive AGRP neurons, which present an entry point for reverse-engineering neural circuits for hunger. Here we mapped synaptic interactions of AGRP neurons with multiple cell populations in mice and probed the contribution of these distinct circuits to feeding behaviour using optogenetic and pharmacogenetic techniques. An inhibitory circuit with paraventricular hypothalamus (PVH) neurons substantially accounted for acute AGRP neuron-evoked eating, whereas two other prominent circuits were insufficient. Within the PVH, we found that AGRP neurons target and inhibit oxytocin neurons, a small population that is selectively lost in Prader-Willi syndrome, a condition involving insatiable hunger. By developing strategies for evaluating molecularly defined circuits, we show that AGRP neuron suppression of oxytocin neurons is critical for evoked feeding. These experiments reveal a new neural circuit that regulates hunger state and pathways associated with overeating disorders.

Deconstruction of a neural circuit for hunger

PubMed Central

Atasoy, Deniz; Betley, J. Nicholas; Su, Helen H.; Sternson, Scott M.

2012-01-01

Hunger is a complex behavioural state that elicits intense food seeking and consumption. These behaviours are rapidly recapitulated by activation of starvation-sensitive AGRP neurons, which present an entry point for reverse-engineering neural circuits for hunger. We mapped synaptic interactions of AGRP neurons with multiple cell populations and probed the contribution of these distinct circuits to feeding behaviour using optogenetic and pharmacogenetic techniques. An inhibitory circuit with paraventricular hypothalamus (PVH) neurons substantially accounted for acute AGRP neuron-evoked eating, whereas two other prominent circuits were insufficient. Within the PVH, we found that AGRP neurons target and inhibit oxytocin neurons, a small population that is selectively lost in Prader-Willi syndrome, a condition involving insatiable hunger. By developing strategies for evaluating molecularly-defined circuits, we show that AGRP neuron suppression of oxytocin neurons is critical for evoked feeding. These experiments reveal a new neural circuit that regulates hunger state and pathways associated with overeating disorders. PMID:22801496

VLSI circuits implementing computational models of neocortical circuits.

PubMed

Wijekoon, Jayawan H B; Dudek, Piotr

2012-09-15

This paper overviews the design and implementation of three neuromorphic integrated circuits developed for the COLAMN ("Novel Computing Architecture for Cognitive Systems based on the Laminar Microcircuitry of the Neocortex") project. The circuits are implemented in a standard 0.35 μm CMOS technology and include spiking and bursting neuron models, and synapses with short-term (facilitating/depressing) and long-term (STDP and dopamine-modulated STDP) dynamics. They enable execution of complex nonlinear models in accelerated-time, as compared with biology, and with low power consumption. The neural dynamics are implemented using analogue circuit techniques, with digital asynchronous event-based input and output. The circuits provide configurable hardware blocks that can be used to simulate a variety of neural networks. The paper presents experimental results obtained from the fabricated devices, and discusses the advantages and disadvantages of the analogue circuit approach to computational neural modelling. Copyright © 2012 Elsevier B.V. All rights reserved.

Dynamical foundations of the neural circuit for bayesian decision making.

PubMed

Morita, Kenji

2009-07-01

On the basis of accumulating behavioral and neural evidences, it has recently been proposed that the brain neural circuits of humans and animals are equipped with several specific properties, which ensure that perceptual decision making implemented by the circuits can be nearly optimal in terms of Bayesian inference. Here, I introduce the basic ideas of such a proposal and discuss its implications from the standpoint of biophysical modeling developed in the framework of dynamical systems.

Dopamine modulation of emotional processing in cortical and subcortical neural circuits: evidence for a final common pathway in schizophrenia?

PubMed

Laviolette, Steven R

2007-07-01

The neural regulation of emotional perception, learning, and memory is essential for normal behavioral and cognitive functioning. Many of the symptoms displayed by individuals with schizophrenia may arise from fundamental disturbances in the ability to accurately process emotionally salient sensory information. The neurotransmitter dopamine (DA) and its ability to modulate neural regions involved in emotional learning, perception, and memory formation has received considerable research attention as a potential final common pathway to account for the aberrant emotional regulation and psychosis present in the schizophrenic syndrome. Evidence from both human neuroimaging studies and animal-based research using neurodevelopmental, behavioral, and electrophysiological techniques have implicated the mesocorticolimbic DA circuit as a crucial system for the encoding and expression of emotionally salient learning and memory formation. While many theories have examined the cortical-subcortical interactions between prefrontal cortical regions and subcortical DA substrates, many questions remain as to how DA may control emotional perception and learning and how disturbances linked to DA abnormalities may underlie the disturbed emotional processing in schizophrenia. Beyond the mesolimbic DA system, increasing evidence points to the amygdala-prefrontal cortical circuit as an important processor of emotionally salient information and how neurodevelopmental perturbances within this circuitry may lead to dysregulation of DAergic modulation of emotional processing and learning along this cortical-subcortical emotional processing circuit.

Neural integrators for decision making: a favorable tradeoff between robustness and sensitivity

PubMed Central

Cain, Nicholas; Barreiro, Andrea K.; Shadlen, Michael

2013-01-01

A key step in many perceptual decision tasks is the integration of sensory inputs over time, but a fundamental questions remain about how this is accomplished in neural circuits. One possibility is to balance decay modes of membranes and synapses with recurrent excitation. To allow integration over long timescales, however, this balance must be exceedingly precise. The need for fine tuning can be overcome via a “robust integrator” mechanism in which momentary inputs must be above a preset limit to be registered by the circuit. The degree of this limiting embodies a tradeoff between sensitivity to the input stream and robustness against parameter mistuning. Here, we analyze the consequences of this tradeoff for decision-making performance. For concreteness, we focus on the well-studied random dot motion discrimination task and constrain stimulus parameters by experimental data. We show that mistuning feedback in an integrator circuit decreases decision performance but that the robust integrator mechanism can limit this loss. Intriguingly, even for perfectly tuned circuits with no immediate need for a robustness mechanism, including one often does not impose a substantial penalty for decision-making performance. The implication is that robust integrators may be well suited to subserve the basic function of evidence integration in many cognitive tasks. We develop these ideas using simulations of coupled neural units and the mathematics of sequential analysis. PMID:23446688

Fragile X Mental Retardation Protein Restricts Small Dye Iontophoresis Entry into Central Neurons

PubMed Central

2017-01-01

Fragile X mental retardation protein (FMRP) loss causes Fragile X syndrome (FXS), a major disorder characterized by autism, intellectual disability, hyperactivity, and seizures. FMRP is both an RNA- and channel-binding regulator, with critical roles in neural circuit formation and function. However, it remains unclear how these FMRP activities relate to each other and how dysfunction in their absence underlies FXS neurological symptoms. In testing circuit level defects in the Drosophila FXS model, we discovered a completely unexpected and highly robust neuronal dye iontophoresis phenotype in the well mapped giant fiber (GF) circuit. Controlled dye injection into the GF interneuron results in a dramatic increase in dye uptake in neurons lacking FMRP. Transgenic wild-type FMRP reintroduction rescues the mutant defect, demonstrating a specific FMRP requirement. This phenotype affects only small dyes, but is independent of dye charge polarity. Surprisingly, the elevated dye iontophoresis persists in shaking B mutants that eliminate gap junctions and dye coupling among GF circuit neurons. We therefore used a wide range of manipulations to investigate the dye uptake defect, including timed injection series, pharmacology and ion replacement, and optogenetic activity studies. The results show that FMRP strongly limits the rate of dye entry via a cytosolic mechanism. This study reveals an unexpected new phenotype in a physical property of central neurons lacking FMRP that could underlie aspects of FXS disruption of neural function. SIGNIFICANCE STATEMENT FXS is a leading heritable cause of intellectual disability and autism spectrum disorders. Although researchers established the causal link with FMRP loss >;25 years ago, studies continue to reveal diverse FMRP functions. The Drosophila FXS model is key to discovering new FMRP roles, because of its genetic malleability and individually identified neuron maps. Taking advantage of a well characterized Drosophila neural circuit, we discovered that neurons lacking FMRP take up dramatically more current-injected small dye. After examining many neuronal properties, we determined that this dye defect is cytoplasmic and occurs due to a highly elevated dye iontophoresis rate. We also report several new factors affecting neuron dye uptake. Understanding how FMRP regulates iontophoresis should reveal new molecular factors underpinning FXS dysfunction. PMID:28887386

Emerging Structure–Function Relations in the Developing Face Processing System

PubMed Central

Suzanne Scherf, K.; Thomas, Cibu; Doyle, Jaime; Behrmann, Marlene

2014-01-01

To evaluate emerging structure–function relations in a neural circuit that mediates complex behavior, we investigated age-related differences among cortical regions that support face recognition behavior and the fiber tracts through which they transmit and receive signals using functional neuroimaging and diffusion tensor imaging. In a large sample of human participants (aged 6–23 years), we derived the microstructural and volumetric properties of the inferior longitudinal fasciculus (ILF), the inferior fronto-occipital fasciculus, and control tracts, using independently defined anatomical markers. We also determined the functional characteristics of core face- and place-selective regions that are distributed along the trajectory of the pathways of interest. We observed disproportionately large age-related differences in the volume, fractional anisotropy, and mean and radial, but not axial, diffusivities of the ILF. Critically, these differences in the structural properties of the ILF were tightly and specifically linked with an age-related increase in the size of a key face-selective functional region, the fusiform face area. This dynamic association between emerging structural and functional architecture in the developing brain may provide important clues about the mechanisms by which neural circuits become organized and optimized in the human cortex. PMID:23765156

Stabilization of memory States by stochastic facilitating synapses.

PubMed

Miller, Paul

2013-12-06

Bistability within a small neural circuit can arise through an appropriate strength of excitatory recurrent feedback. The stability of a state of neural activity, measured by the mean dwelling time before a noise-induced transition to another state, depends on the neural firing-rate curves, the net strength of excitatory feedback, the statistics of spike times, and increases exponentially with the number of equivalent neurons in the circuit. Here, we show that such stability is greatly enhanced by synaptic facilitation and reduced by synaptic depression. We take into account the alteration in times of synaptic vesicle release, by calculating distributions of inter-release intervals of a synapse, which differ from the distribution of its incoming interspike intervals when the synapse is dynamic. In particular, release intervals produced by a Poisson spike train have a coefficient of variation greater than one when synapses are probabilistic and facilitating, whereas the coefficient of variation is less than one when synapses are depressing. However, in spite of the increased variability in postsynaptic input produced by facilitating synapses, their dominant effect is reduced synaptic efficacy at low input rates compared to high rates, which increases the curvature of neural input-output functions, leading to wider regions of bistability in parameter space and enhanced lifetimes of memory states. Our results are based on analytic methods with approximate formulae and bolstered by simulations of both Poisson processes and of circuits of noisy spiking model neurons.

Updating Procedures Can Reorganize the Neural Circuit Supporting a Fear Memory.

PubMed

Kwapis, Janine L; Jarome, Timothy J; Ferrara, Nicole C; Helmstetter, Fred J

2017-07-01

Established memories undergo a period of vulnerability following retrieval, a process termed 'reconsolidation.' Recent work has shown that the hypothetical process of reconsolidation is only triggered when new information is presented during retrieval, suggesting that this process may allow existing memories to be modified. Reconsolidation has received increasing attention as a possible therapeutic target for treating disorders that stem from traumatic memories, yet little is known about how this process changes the original memory. In particular, it is unknown whether reconsolidation can reorganize the neural circuit supporting an existing memory after that memory is modified with new information. Here, we show that trace fear memory undergoes a protein synthesis-dependent reconsolidation process following exposure to a single updating trial of delay conditioning. Further, this reconsolidation-dependent updating process appears to reorganize the neural circuit supporting the trace-trained memory, so that it better reflects the circuit supporting delay fear. Specifically, after a trace-to-delay update session, the amygdala is now required for extinction of the updated memory but the retrosplenial cortex is no longer required for retrieval. These results suggest that updating procedures could be used to force a complex, poorly defined memory circuit to rely on a better-defined neural circuit that may be more amenable to behavioral or pharmacological manipulation. This is the first evidence that exposure to new information can fundamentally reorganize the neural circuit supporting an existing memory.

[Review of the regeneration mechanism of complete spinal cord injury].

PubMed

Li, Jiayin; Li, Xing; Xiao, Zhifeng; Dai, Jianwu

2018-06-01

Spinal cord injury (SCI), especially the complete SCI, usually results in complete paralysis below the level of the injury and seriously affects the patient's quality of life. SCI repair is still a worldwide medical problem. In the last twenty years, Professor DAI Jianwu and his team pioneered complete SCI model by removing spinal tissue with varied lengths in rodents, canine, and non-human primates to verify therapeutic effect of different repair strategies. Moreover, they also started the first clinical study of functional collagen scaffold on patients with acute complete SCI on January 16th, 2015. This review mainly focusses on the possible mechanisms responsible for complete SCI. In common, recovery of some sensory and motor functions post complete SCI include the following three contributing reasons. ① Regeneration of long ascending and descending axons throughout the lesion site to re-connect the original targets; ② New neural circuits formed in the lesion site by newly generated neurons post injury, which effectively re-connect the transected stumps; ③ The combined effect of ① and ②. The numerous studies have confirmed that neural circuits rebuilt across the injury site by newborn neurons might be the main mechanisms for functional recovery of animals from rodents to dogs. In many SCI model, especially the complete spinal cord transection model, many studies have convincingly demonstrated that the quantity and length of regenerated long descending axons, particularly like CST fibers, are too few to across the lesion site that is millimeters in length to realize motor functional recovery. Hence, it is more feasible in guiding neuronal relays formation by bio-scaffolds implantation than directing long motor axons regeneration in improving motor function of animals with complete spinal cord transection. However, some other issues such as promoting more neuronal relays formation, debugging wrong connections, and maintaining adequate neural circuits for functional recovery are urgent problems to be addressed.

Imbalanced functional link between reward circuits and the cognitive control system in patients with obsessive-compulsive disorder.

PubMed

Xie, Chunming; Ma, Lisha; Jiang, Nan; Huang, Ruyan; Li, Li; Gong, Liang; He, Cancan; Xiao, Chaoyong; Liu, Wen; Xu, Shu; Zhang, Zhijun

2017-08-01

Altered reward processing and cognitive deficits are often observed in patients with obsessive-compulsive disorder (OCD); however, whether the imbalance in activity between reward circuits and the cognitive control (CC) system is associated with compulsive behavior remains unknown. Sixty-eight OCD patients and 33 cognitively normal (CN) healthy subjects participated in this resting-state functional magnetic resonance imaging study. Alterations in the functional connectivity between reward circuits and the CC system were quantitatively assessed and compared between the groups. A Granger causality analysis was used to determine the causal informational influence between and within reward circuits and the CC system across all subjects. OCD patients showed a dichotomous pattern of enhanced functional coupling in their reward circuits and a weakened functional coupling in their CC system when compared to CN subjects. Neural correlates of compulsive behavior were primarily located in the reward circuits and CC system in OCD patients. Importantly, the CC system exerted a reduced interregional causal influence over the reward system in OCD patients relative to its effect in CN subjects. The limitations of this study are that it was a cross-sectional study and the potential effects of environmental and genetic factors were not explored. OCD patients showed an imbalance in the functional link between reward circuits and the CC system at rest. This bias toward a loss of control may define a pathological state in which subjects are more vulnerable to engaging in compulsive behaviors.

Identifying the integrated neural networks involved in capsaicin-induced pain using fMRI in awake TRPV1 knockout and wild-type rats

PubMed Central

Yee, Jason R.; Kenkel, William; Caccaviello, John C.; Gamber, Kevin; Simmons, Phil; Nedelman, Mark; Kulkarni, Praveen; Ferris, Craig F.

2015-01-01

In the present study, we used functional MRI in awake rats to investigate the pain response that accompanies intradermal injection of capsaicin into the hindpaw. To this end, we used BOLD imaging together with a 3D segmented, annotated rat atlas and computational analysis to identify the integrated neural circuits involved in capsaicin-induced pain. The specificity of the pain response to capsaicin was tested in a transgenic model that contains a biallelic deletion of the gene encoding for the transient receptor potential cation channel subfamily V member 1 (TRPV1). Capsaicin is an exogenous ligand for the TRPV1 receptor, and in wild-type rats, activated the putative pain neural circuit. In addition, capsaicin-treated wild-type rats exhibited activation in brain regions comprising the Papez circuit and habenular system, systems that play important roles in the integration of emotional information, and learning and memory of aversive information, respectively. As expected, capsaicin administration to TRPV1-KO rats failed to elicit the robust BOLD activation pattern observed in wild-type controls. However, the intradermal injection of formalin elicited a significant activation of the putative pain pathway as represented by such areas as the anterior cingulate, somatosensory cortex, parabrachial nucleus, and periaqueductal gray. Notably, comparison of neural responses to capsaicin in wild-type vs. knock-out rats uncovered evidence that capsaicin may function in an antinociceptive capacity independent of TRPV1 signaling. Our data suggest that neuroimaging of pain in awake, conscious animals has the potential to inform the neurobiological basis of full and integrated perceptions of pain. PMID:25745388

Central neural pathways for thermoregulation

PubMed Central

Morrison, Shaun F.; Nakamura, Kazuhiro

2010-01-01

Central neural circuits orchestrate a homeostatic repertoire to maintain body temperature during environmental temperature challenges and to alter body temperature during the inflammatory response. This review summarizes the functional organization of the neural pathways through which cutaneous thermal receptors alter thermoregulatory effectors: the cutaneous circulation for heat loss, the brown adipose tissue, skeletal muscle and heart for thermogenesis and species-dependent mechanisms (sweating, panting and saliva spreading) for evaporative heat loss. These effectors are regulated by parallel but distinct, effector-specific neural pathways that share a common peripheral thermal sensory input. The thermal afferent circuits include cutaneous thermal receptors, spinal dorsal horn neurons and lateral parabrachial nucleus neurons projecting to the preoptic area to influence warm-sensitive, inhibitory output neurons which control thermogenesis-promoting neurons in the dorsomedial hypothalamus that project to premotor neurons in the rostral ventromedial medulla, including the raphe pallidus, that descend to provide the excitation necessary to drive thermogenic thermal effectors. A distinct population of warm-sensitive preoptic neurons controls heat loss through an inhibitory input to raphe pallidus neurons controlling cutaneous vasoconstriction. PMID:21196160

High-Gain AlxGa1-xAs/GaAs Transistors For Neural Networks

NASA Technical Reports Server (NTRS)

Kim, Jae-Hoon; Lin, Steven H.

1991-01-01

High-gain AlxGa1-xAs/GaAs npn double heterojunction bipolar transistors developed for use as phototransistors in optoelectronic integrated circuits, especially in artificial neural networks. Transistors perform both photodetection and saturating-amplification functions of neurons. Good candidates for such application because structurally compatible with laser diodes and light-emitting diodes, detect light, and provide high current gain needed to compensate for losses in holographic optical elements.

A Dynamic Connectome Supports the Emergence of Stable Computational Function of Neural Circuits through Reward-Based Learning.

PubMed

Kappel, David; Legenstein, Robert; Habenschuss, Stefan; Hsieh, Michael; Maass, Wolfgang

2018-01-01

Synaptic connections between neurons in the brain are dynamic because of continuously ongoing spine dynamics, axonal sprouting, and other processes. In fact, it was recently shown that the spontaneous synapse-autonomous component of spine dynamics is at least as large as the component that depends on the history of pre- and postsynaptic neural activity. These data are inconsistent with common models for network plasticity and raise the following questions: how can neural circuits maintain a stable computational function in spite of these continuously ongoing processes, and what could be functional uses of these ongoing processes? Here, we present a rigorous theoretical framework for these seemingly stochastic spine dynamics and rewiring processes in the context of reward-based learning tasks. We show that spontaneous synapse-autonomous processes, in combination with reward signals such as dopamine, can explain the capability of networks of neurons in the brain to configure themselves for specific computational tasks, and to compensate automatically for later changes in the network or task. Furthermore, we show theoretically and through computer simulations that stable computational performance is compatible with continuously ongoing synapse-autonomous changes. After reaching good computational performance it causes primarily a slow drift of network architecture and dynamics in task-irrelevant dimensions, as observed for neural activity in motor cortex and other areas. On the more abstract level of reinforcement learning the resulting model gives rise to an understanding of reward-driven network plasticity as continuous sampling of network configurations.

A Dynamic Connectome Supports the Emergence of Stable Computational Function of Neural Circuits through Reward-Based Learning

PubMed Central

Habenschuss, Stefan; Hsieh, Michael

2018-01-01

Synaptic connections between neurons in the brain are dynamic because of continuously ongoing spine dynamics, axonal sprouting, and other processes. In fact, it was recently shown that the spontaneous synapse-autonomous component of spine dynamics is at least as large as the component that depends on the history of pre- and postsynaptic neural activity. These data are inconsistent with common models for network plasticity and raise the following questions: how can neural circuits maintain a stable computational function in spite of these continuously ongoing processes, and what could be functional uses of these ongoing processes? Here, we present a rigorous theoretical framework for these seemingly stochastic spine dynamics and rewiring processes in the context of reward-based learning tasks. We show that spontaneous synapse-autonomous processes, in combination with reward signals such as dopamine, can explain the capability of networks of neurons in the brain to configure themselves for specific computational tasks, and to compensate automatically for later changes in the network or task. Furthermore, we show theoretically and through computer simulations that stable computational performance is compatible with continuously ongoing synapse-autonomous changes. After reaching good computational performance it causes primarily a slow drift of network architecture and dynamics in task-irrelevant dimensions, as observed for neural activity in motor cortex and other areas. On the more abstract level of reinforcement learning the resulting model gives rise to an understanding of reward-driven network plasticity as continuous sampling of network configurations. PMID:29696150

Establishment of Tools for Neurogenetic Analysis of Sexual Behavior in the Silkmoth, Bombyx mori

PubMed Central

Kiya, Taketoshi; Morishita, Koudai; Uchino, Keiro; Iwami, Masafumi; Sezutsu, Hideki

2014-01-01

Background Silkmoth, Bombyx mori, is an ideal model insect for investigating the neural mechanisms underlying sex pheromone-induced innate behavior. Although transgenic techniques and the GAL4/UAS system are well established in the silkmoth, genetic tools useful for investigating brain function at the neural circuit level have been lacking. Results In the present study, we established silkmoth strains in which we could visualize neural projections (UAS-mCD8GFP) and cell nucleus positions (UAS-GFP.nls), and manipulate neural excitability by thermal stimulation (UAS-dTrpA1). In these strains, neural projections and nucleus position were reliably labeled with green fluorescent protein in a GAL4-dependent manner. Further, the behavior of silkworm larvae and adults could be controlled by GAL4-dependent misexpression of dTrpA1. Ubiquitous dTrpA1 misexpression led both silkmoth larvae and adults to exhibit seizure-like phenotypes in a heat stimulation-dependent manner. Furthermore, dTrpA1 misexpression in the sex pheromone receptor neurons of male silkmoths allowed us to control male sexual behavior by changing the temperature. Thermally stimulated male silkmoths exhibited full sexual behavior, including wing-flapping, orientation, and attempted copulation, and precisely approached a thermal source in a manner similar to male silkmoths stimulated with the sex pheromone. Conclusion These findings indicate that a thermogenetic approach using dTrpA1 is feasible in Lepidopteran insects and thermogenetic analysis of innate behavior is applicable in the silkmoth. These tools are essential for elucidating the relationships between neural circuits and function using neurogenetic methods. PMID:25396742

Establishment of tools for neurogenetic analysis of sexual behavior in the silkmoth, Bombyx mori.

PubMed

Kiya, Taketoshi; Morishita, Koudai; Uchino, Keiro; Iwami, Masafumi; Sezutsu, Hideki

2014-01-01

Silkmoth, Bombyx mori, is an ideal model insect for investigating the neural mechanisms underlying sex pheromone-induced innate behavior. Although transgenic techniques and the GAL4/UAS system are well established in the silkmoth, genetic tools useful for investigating brain function at the neural circuit level have been lacking. In the present study, we established silkmoth strains in which we could visualize neural projections (UAS-mCD8GFP) and cell nucleus positions (UAS-GFP.nls), and manipulate neural excitability by thermal stimulation (UAS-dTrpA1). In these strains, neural projections and nucleus position were reliably labeled with green fluorescent protein in a GAL4-dependent manner. Further, the behavior of silkworm larvae and adults could be controlled by GAL4-dependent misexpression of dTrpA1. Ubiquitous dTrpA1 misexpression led both silkmoth larvae and adults to exhibit seizure-like phenotypes in a heat stimulation-dependent manner. Furthermore, dTrpA1 misexpression in the sex pheromone receptor neurons of male silkmoths allowed us to control male sexual behavior by changing the temperature. Thermally stimulated male silkmoths exhibited full sexual behavior, including wing-flapping, orientation, and attempted copulation, and precisely approached a thermal source in a manner similar to male silkmoths stimulated with the sex pheromone. These findings indicate that a thermogenetic approach using dTrpA1 is feasible in Lepidopteran insects and thermogenetic analysis of innate behavior is applicable in the silkmoth. These tools are essential for elucidating the relationships between neural circuits and function using neurogenetic methods.

Habenula Circuit Development: Past, Present, and Future

PubMed Central

Beretta, Carlo A.; Dross, Nicolas; Guiterrez-Triana, Jose A.; Ryu, Soojin; Carl, Matthias

2012-01-01

The habenular neural circuit is attracting increasing attention from researchers in fields as diverse as neuroscience, medicine, behavior, development, and evolution. Recent studies have revealed that this part of the limbic system in the dorsal diencephalon is involved in reward, addiction, and other behaviors and its impairment is associated with various neurological conditions and diseases. Since the initial description of the dorsal diencephalic conduction system (DDC) with the habenulae in its center at the end of the nineteenth century, increasingly sophisticated techniques have resolved much of its anatomy and have shown that these pathways relay information from different parts of the forebrain to the tegmentum, midbrain, and hindbrain. The first part of this review gives a brief historical overview on how the improving experimental approaches have allowed the stepwise uncovering much of the architecture of the habenula circuit as we know it today. Our brain distributes tasks differentially between left and right and it has become a paradigm that this functional lateralization is a universal feature of vertebrates. Moreover, task dependent differential brain activities have been linked to anatomical differences across the left–right axis in humans. A good way to further explore this fundamental issue will be to study the functional consequences of subtle changes in neural network formation, which requires that we fully understand DDC system development. As the habenular circuit is evolutionarily highly conserved, researchers have the option to perform such difficult experiments in more experimentally amenable vertebrate systems. Indeed, research in the last decade has shown that the zebrafish is well suited for the study of DDC system development and the phenomenon of functional lateralization. We will critically discuss the advantages of the zebrafish model, available techniques, and others that are needed to fully understand habenular circuit development. PMID:22536170

Habenula circuit development: past, present, and future.

PubMed

Beretta, Carlo A; Dross, Nicolas; Guiterrez-Triana, Jose A; Ryu, Soojin; Carl, Matthias

2012-01-01

The habenular neural circuit is attracting increasing attention from researchers in fields as diverse as neuroscience, medicine, behavior, development, and evolution. Recent studies have revealed that this part of the limbic system in the dorsal diencephalon is involved in reward, addiction, and other behaviors and its impairment is associated with various neurological conditions and diseases. Since the initial description of the dorsal diencephalic conduction system (DDC) with the habenulae in its center at the end of the nineteenth century, increasingly sophisticated techniques have resolved much of its anatomy and have shown that these pathways relay information from different parts of the forebrain to the tegmentum, midbrain, and hindbrain. The first part of this review gives a brief historical overview on how the improving experimental approaches have allowed the stepwise uncovering much of the architecture of the habenula circuit as we know it today. Our brain distributes tasks differentially between left and right and it has become a paradigm that this functional lateralization is a universal feature of vertebrates. Moreover, task dependent differential brain activities have been linked to anatomical differences across the left-right axis in humans. A good way to further explore this fundamental issue will be to study the functional consequences of subtle changes in neural network formation, which requires that we fully understand DDC system development. As the habenular circuit is evolutionarily highly conserved, researchers have the option to perform such difficult experiments in more experimentally amenable vertebrate systems. Indeed, research in the last decade has shown that the zebrafish is well suited for the study of DDC system development and the phenomenon of functional lateralization. We will critically discuss the advantages of the zebrafish model, available techniques, and others that are needed to fully understand habenular circuit development.

Natural Variation in the Thermotolerance of Neural Function and Behavior due to a cGMP-Dependent Protein Kinase

PubMed Central

Dawson-Scully, Ken; Armstrong, Gary A.B.; Kent, Clement; Robertson, R. Meldrum; Sokolowski, Marla B.

2007-01-01

Although it is acknowledged that genetic variation contributes to individual differences in thermotolerance, the specific genes and pathways involved and how they are modulated by the environment remain poorly understood. We link natural variation in the thermotolerance of neural function and behavior in Drosophila melanogaster to the foraging gene (for, which encodes a cGMP-dependent protein kinase (PKG)) as well as to its downstream target, protein phosphatase 2A (PP2A). Genetic and pharmacological manipulations revealed that reduced PKG (or PP2A) activity caused increased thermotolerance of synaptic transmission at the larval neuromuscular junction. Like synaptic transmission, feeding movements were preserved at higher temperatures in larvae with lower PKG levels. In a comparative assay, pharmacological manipulations altering thermotolerance in a central circuit of Locusta migratoria demonstrated conservation of this neuroprotective pathway. In this circuit, either the inhibition of PKG or PP2A induced robust thermotolerance of neural function. We suggest that PKG and therefore the polymorphism associated with the allelic variation in for may provide populations with natural variation in heat stress tolerance. for's function in behavior is conserved across most organisms, including ants, bees, nematodes, and mammals. PKG's role in thermotolerance may also apply to these and other species. Natural variation in thermotolerance arising from genes involved in the PKG pathway could impact the evolution of thermotolerance in natural populations. PMID:17712421

Muscle spindle feedback directs locomotor recovery and circuit reorganization after spinal cord injury.

PubMed

Takeoka, Aya; Vollenweider, Isabel; Courtine, Grégoire; Arber, Silvia

2014-12-18

Spinal cord injuries alter motor function by disconnecting neural circuits above and below the lesion, rendering sensory inputs a primary source of direct external drive to neuronal networks caudal to the injury. Here, we studied mice lacking functional muscle spindle feedback to determine the role of this sensory channel in gait control and locomotor recovery after spinal cord injury. High-resolution kinematic analysis of intact mutant mice revealed proficient execution in basic locomotor tasks but poor performance in a precision task. After injury, wild-type mice spontaneously recovered basic locomotor function, whereas mice with deficient muscle spindle feedback failed to regain control over the hindlimb on the lesioned side. Virus-mediated tracing demonstrated that mutant mice exhibit defective rearrangements of descending circuits projecting to deprived spinal segments during recovery. Our findings reveal an essential role for muscle spindle feedback in directing basic locomotor recovery and facilitating circuit reorganization after spinal cord injury. Copyright © 2014 Elsevier Inc. All rights reserved.

Scalable, Lightweight, Integrated and Quick-to-Assemble (SLIQ) Hyperdrives for Functional Circuit Dissection.

PubMed

Liang, Li; Oline, Stefan N; Kirk, Justin C; Schmitt, Lukas Ian; Komorowski, Robert W; Remondes, Miguel; Halassa, Michael M

2017-01-01

Independently adjustable multielectrode arrays are routinely used to interrogate neuronal circuit function, enabling chronic in vivo monitoring of neuronal ensembles in freely behaving animals at a single-cell, single spike resolution. Despite the importance of this approach, its widespread use is limited by highly specialized design and fabrication methods. To address this, we have developed a Scalable, Lightweight, Integrated and Quick-to-assemble multielectrode array platform. This platform additionally integrates optical fibers with independently adjustable electrodes to allow simultaneous single unit recordings and circuit-specific optogenetic targeting and/or manipulation. In current designs, the fully assembled platforms are scalable from 2 to 32 microdrives, and yet range 1-3 g, light enough for small animals. Here, we describe the design process starting from intent in computer-aided design, parameter testing through finite element analysis and experimental means, and implementation of various applications across mice and rats. Combined, our methods may expand the utility of multielectrode recordings and their continued integration with other tools enabling functional dissection of intact neural circuits.

Deficient Activity in the Neural Systems That Mediate Self-regulatory Control in Bulimia Nervosa

PubMed Central

Marsh, Rachel; Steinglass, Joanna E.; Gerber, Andrew J.; O’Leary, Kara Graziano; Wang, Zhishun; Murphy, David; Walsh, B. Timothy; Peterson, Bradley S.

2009-01-01

Context Disturbances in neural systems that mediate voluntary self-regulatory processes may contribute to bulimia nervosa (BN) by releasing feeding behaviors from regulatory control. Objective To study the functional activity in neural circuits that subserve self-regulatory control in women with BN. Design We compared functional magnetic resonance imaging blood oxygenation level–dependent responses in patients with BN with healthy controls during performance of the Simon Spatial Incompatibility task. Setting University research institute. Participants Forty women: 20 patients with BN and 20 healthy control participants. Main Outcome Measure We used general linear modeling of Simon Spatial Incompatibility task–related activations to compare groups on their patterns of brain activation associated with the successful or unsuccessful engagement of self-regulatory control. Results Patients with BN responded more impulsively and made more errors on the task than did healthy controls; patients with the most severe symptoms made the most errors. During correct responding on incongruent trials, patients failed to activate frontostriatal circuits to the same degree as healthy controls in the left inferolateral prefrontal cortex (Brodmann area [BA] 45), bilateral inferior frontal gyrus (BA 44), lenticular and caudate nuclei, and anterior cingulate cortex (BA 24/32). Patients activated the dorsal anterior cingulate cortex (BA 32) more when making errors than when responding correctly. In contrast, healthy participants activated the anterior cingulate cortex more during correct than incorrect responses, and they activated the striatum more when responding incorrectly, likely reflecting an automatic response tendency that, in the absence of concomitant anterior cingulate cortex activity, produced incorrect responses. Conclusions Self-regulatory processes are impaired in women with BN, likely because of their failure to engage frontostriatal circuits appropriately. These findings enhance our understanding of the pathogenesis of BN by pointing to functional abnormalities within a neural system that subserves self-regulatory control, which may contribute to binge eating and other impulsive behaviors in women with BN. PMID:19124688

Prefrontal contributions to visual selective attention.

PubMed

Squire, Ryan F; Noudoost, Behrad; Schafer, Robert J; Moore, Tirin

2013-07-08

The faculty of attention endows us with the capacity to process important sensory information selectively while disregarding information that is potentially distracting. Much of our understanding of the neural circuitry underlying this fundamental cognitive function comes from neurophysiological studies within the visual modality. Past evidence suggests that a principal function of the prefrontal cortex (PFC) is selective attention and that this function involves the modulation of sensory signals within posterior cortices. In this review, we discuss recent progress in identifying the specific prefrontal circuits controlling visual attention and its neural correlates within the primate visual system. In addition, we examine the persisting challenge of precisely defining how behavior should be affected when attentional function is lost.

An Integrated Circuit for Simultaneous Extracellular Electrophysiology Recording and Optogenetic Neural Manipulation.

PubMed

Chen, Chang Hao; McCullagh, Elizabeth A; Pun, Sio Hang; Mak, Peng Un; Vai, Mang I; Mak, Pui In; Klug, Achim; Lei, Tim C

2017-03-01

The ability to record and to control action potential firing in neuronal circuits is critical to understand how the brain functions. The objective of this study is to develop a monolithic integrated circuit (IC) to record action potentials and simultaneously control action potential firing using optogenetics. A low-noise and high input impedance (or low input capacitance) neural recording amplifier is combined with a high current laser/light-emitting diode (LED) driver in a single IC. The low input capacitance of the amplifier (9.7 pF) was achieved by adding a dedicated unity gain stage optimized for high impedance metal electrodes. The input referred noise of the amplifier is [Formula: see text], which is lower than the estimated thermal noise of the metal electrode. Thus, the action potentials originating from a single neuron can be recorded with a signal-to-noise ratio of at least 6.6. The LED/laser current driver delivers a maximum current of 330 mA, which is adequate for optogenetic control. The functionality of the IC was tested with an anesthetized Mongolian gerbil and auditory stimulated action potentials were recorded from the inferior colliculus. Spontaneous firings of fifth (trigeminal) nerve fibers were also inhibited using the optogenetic protein Halorhodopsin. Moreover, a noise model of the system was derived to guide the design. A single IC to measure and control action potentials using optogenetic proteins is realized so that more complicated behavioral neuroscience research and the translational neural disorder treatments become possible in the future.

Conserved neural circuit structure across Drosophila larval development revealed by comparative connectomics.

PubMed

Gerhard, Stephan; Andrade, Ingrid; Fetter, Richard D; Cardona, Albert; Schneider-Mizell, Casey M

2017-10-23

During postembryonic development, the nervous system must adapt to a growing body. How changes in neuronal structure and connectivity contribute to the maintenance of appropriate circuit function remains unclear. Previously , we measured the cellular neuroanatomy underlying synaptic connectivity in Drosophila (Schneider-Mizell et al., 2016). Here, we examined how neuronal morphology and connectivity change between first instar and third instar larval stages using serial section electron microscopy. We reconstructed nociceptive circuits in a larva of each stage and found consistent topographically arranged connectivity between identified neurons. Five-fold increases in each size, number of terminal dendritic branches, and total number of synaptic inputs were accompanied by cell type-specific connectivity changes that preserved the fraction of total synaptic input associated with each pre-synaptic partner. We propose that precise patterns of structural growth act to conserve the computational function of a circuit, for example determining the location of a dangerous stimulus.

Parallel circuits control temperature preference in Drosophila during ageing.

PubMed

Shih, Hsiang-Wen; Wu, Chia-Lin; Chang, Sue-Wei; Liu, Tsung-Ho; Lai, Jason Sih-Yu; Fu, Tsai-Feng; Fu, Chien-Chung; Chiang, Ann-Shyn

2015-07-16

The detection of environmental temperature and regulation of body temperature are integral determinants of behaviour for all animals. These functions become less efficient in aged animals, particularly during exposure to cold environments, yet the cellular and molecular mechanisms are not well understood. Here, we identify an age-related change in the temperature preference of adult fruit flies that results from a shift in the relative contributions of two parallel mushroom body (MB) circuits—the β'- and β-systems. The β'-circuit primarily controls cold avoidance through dopamine signalling in young flies, whereas the β-circuit increasingly contributes to cold avoidance as adult flies age. Elevating dopamine levels in β'-afferent neurons of aged flies restores cold sensitivity, suggesting that the alteration of cold avoidance behaviour with ageing is functionally reversible. These results provide a framework for investigating how molecules and individual neural circuits modulate homeostatic alterations during the course of senescence.

Large-scale, high-density (up to 512 channels) recording of local circuits in behaving animals

PubMed Central

Berényi, Antal; Somogyvári, Zoltán; Nagy, Anett J.; Roux, Lisa; Long, John D.; Fujisawa, Shigeyoshi; Stark, Eran; Leonardo, Anthony; Harris, Timothy D.

2013-01-01

Monitoring representative fractions of neurons from multiple brain circuits in behaving animals is necessary for understanding neuronal computation. Here, we describe a system that allows high-channel-count recordings from a small volume of neuronal tissue using a lightweight signal multiplexing headstage that permits free behavior of small rodents. The system integrates multishank, high-density recording silicon probes, ultraflexible interconnects, and a miniaturized microdrive. These improvements allowed for simultaneous recordings of local field potentials and unit activity from hundreds of sites without confining free movements of the animal. The advantages of large-scale recordings are illustrated by determining the electroanatomic boundaries of layers and regions in the hippocampus and neocortex and constructing a circuit diagram of functional connections among neurons in real anatomic space. These methods will allow the investigation of circuit operations and behavior-dependent interregional interactions for testing hypotheses of neural networks and brain function. PMID:24353300

Parallel circuits control temperature preference in Drosophila during ageing

PubMed Central

Shih, Hsiang-Wen; Wu, Chia-Lin; Chang, Sue-Wei; Liu, Tsung-Ho; Sih-Yu Lai, Jason; Fu, Tsai-Feng; Fu, Chien-Chung; Chiang, Ann-Shyn

2015-01-01

The detection of environmental temperature and regulation of body temperature are integral determinants of behaviour for all animals. These functions become less efficient in aged animals, particularly during exposure to cold environments, yet the cellular and molecular mechanisms are not well understood. Here, we identify an age-related change in the temperature preference of adult fruit flies that results from a shift in the relative contributions of two parallel mushroom body (MB) circuits—the β′- and β-systems. The β′-circuit primarily controls cold avoidance through dopamine signalling in young flies, whereas the β-circuit increasingly contributes to cold avoidance as adult flies age. Elevating dopamine levels in β′-afferent neurons of aged flies restores cold sensitivity, suggesting that the alteration of cold avoidance behaviour with ageing is functionally reversible. These results provide a framework for investigating how molecules and individual neural circuits modulate homeostatic alterations during the course of senescence. PMID:26178754

The Principle of the Micro-Electronic Neural Bridge and a Prototype System Design.

PubMed

Huang, Zong-Hao; Wang, Zhi-Gong; Lu, Xiao-Ying; Li, Wen-Yuan; Zhou, Yu-Xuan; Shen, Xiao-Yan; Zhao, Xin-Tai

2016-01-01

The micro-electronic neural bridge (MENB) aims to rebuild lost motor function of paralyzed humans by routing movement-related signals from the brain, around the damage part in the spinal cord, to the external effectors. This study focused on the prototype system design of the MENB, including the principle of the MENB, the neural signal detecting circuit and the functional electrical stimulation (FES) circuit design, and the spike detecting and sorting algorithm. In this study, we developed a novel improved amplitude threshold spike detecting method based on variable forward difference threshold for both training and bridging phase. The discrete wavelet transform (DWT), a new level feature coefficient selection method based on Lilliefors test, and the k-means clustering method based on Mahalanobis distance were used for spike sorting. A real-time online spike detecting and sorting algorithm based on DWT and Euclidean distance was also implemented for the bridging phase. Tested by the data sets available at Caltech, in the training phase, the average sensitivity, specificity, and clustering accuracies are 99.43%, 97.83%, and 95.45%, respectively. Validated by the three-fold cross-validation method, the average sensitivity, specificity, and classification accuracy are 99.43%, 97.70%, and 96.46%, respectively.

Distributed affective space represents multiple emotion categories across the human brain

PubMed Central

Saarimäki, Heini; Ejtehadian, Lara Farzaneh; Jääskeläinen, Iiro P; Vuilleumier, Patrik; Sams, Mikko; Nummenmaa, Lauri

2018-01-01

Abstract The functional organization of human emotion systems as well as their neuroanatomical basis and segregation in the brain remains unresolved. Here, we used pattern classification and hierarchical clustering to characterize the organization of a wide array of emotion categories in the human brain. We induced 14 emotions (6 ‘basic’, e.g. fear and anger; and 8 ‘non-basic’, e.g. shame and gratitude) and a neutral state using guided mental imagery while participants' brain activity was measured with functional magnetic resonance imaging (fMRI). Twelve out of 14 emotions could be reliably classified from the haemodynamic signals. All emotions engaged a multitude of brain areas, primarily in midline cortices including anterior and posterior cingulate gyri and precuneus, in subcortical regions, and in motor regions including cerebellum and premotor cortex. Similarity of subjective emotional experiences was associated with similarity of the corresponding neural activation patterns. We conclude that different basic and non-basic emotions have distinguishable neural bases characterized by specific, distributed activation patterns in widespread cortical and subcortical circuits. Regionally differentiated engagement of these circuits defines the unique neural activity pattern and the corresponding subjective feeling associated with each emotion. PMID:29618125

GABA neuron alterations, cortical circuit dysfunction and cognitive deficits in schizophrenia.

PubMed

Gonzalez-Burgos, Guillermo; Fish, Kenneth N; Lewis, David A

2011-01-01

Schizophrenia is a brain disorder associated with cognitive deficits that severely affect the patients' capacity for daily functioning. Whereas our understanding of its pathophysiology is limited, postmortem studies suggest that schizophrenia is associated with deficits of GABA-mediated synaptic transmission. A major role of GABA-mediated transmission may be producing synchronized network oscillations which are currently hypothesized to be essential for normal cognitive function. Therefore, cognitive deficits in schizophrenia may result from a GABA synapse dysfunction that disturbs neural synchrony. Here, we highlight recent studies further suggesting alterations of GABA transmission and network oscillations in schizophrenia. We also review current models for the mechanisms of GABA-mediated synchronization of neural activity, focusing on parvalbumin-positive GABA neurons, which are altered in schizophrenia and whose function has been strongly linked to the production of neural synchrony. Alterations of GABA signaling that impair gamma oscillations and, as a result, cognitive function suggest paths for novel therapeutic interventions.

Image Segmentation for Connectomics Using Machine Learning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tasdizen, Tolga; Seyedhosseini, Mojtaba; Liu, TIng

Reconstruction of neural circuits at the microscopic scale of individual neurons and synapses, also known as connectomics, is an important challenge for neuroscience. While an important motivation of connectomics is providing anatomical ground truth for neural circuit models, the ability to decipher neural wiring maps at the individual cell level is also important in studies of many neurodegenerative diseases. Reconstruction of a neural circuit at the individual neuron level requires the use of electron microscopy images due to their extremely high resolution. Computational challenges include pixel-by-pixel annotation of these images into classes such as cell membrane, mitochondria and synaptic vesiclesmore » and the segmentation of individual neurons. State-of-the-art image analysis solutions are still far from the accuracy and robustness of human vision and biologists are still limited to studying small neural circuits using mostly manual analysis. In this chapter, we describe our image analysis pipeline that makes use of novel supervised machine learning techniques to tackle this problem.« less

Strategies for targeting primate neural circuits with viral vectors

PubMed Central

El-Shamayleh, Yasmine; Ni, Amy M.

2016-01-01

Understanding how the brain works requires understanding how different types of neurons contribute to circuit function and organism behavior. Progress on this front has been accelerated by optogenetics and chemogenetics, which provide an unprecedented level of control over distinct neuronal types in small animals. In primates, however, targeting specific types of neurons with these tools remains challenging. In this review, we discuss existing and emerging strategies for directing genetic manipulations to targeted neurons in the adult primate central nervous system. We review the literature on viral vectors for gene delivery to neurons, focusing on adeno-associated viral vectors and lentiviral vectors, their tropism for different cell types, and prospects for new variants with improved efficacy and selectivity. We discuss two projection targeting approaches for probing neural circuits: anterograde projection targeting and retrograde transport of viral vectors. We conclude with an analysis of cell type-specific promoters and other nucleotide sequences that can be used in viral vectors to target neuronal types at the transcriptional level. PMID:27052579

Two-photon holographic optogenetics of neural circuits (Conference Presentation)

NASA Astrophysics Data System (ADS)

Yang, Weijian; Carrillo-Reid, Luis; Peterka, Darcy S.; Yuste, Rafael

2016-03-01

Optical manipulation of in vivo neural circuits with cellular resolution could be important for understanding cortical function. Despite recent progress, simultaneous optogenetic activation with cellular precision has either been limited to 2D planes, or a very small numbers of neurons over a limited volume. Here we demonstrate a novel paradigm for simultaneous 3D activation using a low repetition rate pulse-amplified fiber laser system and a spatial light modulator (SLM) to project 3D holographic excitation patterns on the cortex of mice in vivo for targeted volumetric 3D photoactivation. This method is compatible with two-photon imaging, and enables the simultaneous activation of multiple cells in 3D, using red-shifted opsins, such as C1V1 or ReaChR, while simultaneously imaging GFP-based sensors such as GCaMP6. This all-optical imaging and 3D manipulation approach achieves simultaneous reading and writing of cortical activity, and should be a powerful tool for the study of neuronal circuits.

Orientation-Selective Retinal Circuits in Vertebrates

PubMed Central

Antinucci, Paride; Hindges, Robert

2018-01-01

Visual information is already processed in the retina before it is transmitted to higher visual centers in the brain. This includes the extraction of salient features from visual scenes, such as motion directionality or contrast, through neurons belonging to distinct neural circuits. Some retinal neurons are tuned to the orientation of elongated visual stimuli. Such ‘orientation-selective’ neurons are present in the retinae of most, if not all, vertebrate species analyzed to date, with species-specific differences in frequency and degree of tuning. In some cases, orientation-selective neurons have very stereotyped functional and morphological properties suggesting that they represent distinct cell types. In this review, we describe the retinal cell types underlying orientation selectivity found in various vertebrate species, and highlight their commonalities and differences. In addition, we discuss recent studies that revealed the cellular, synaptic and circuit mechanisms at the basis of retinal orientation selectivity. Finally, we outline the significance of these findings in shaping our current understanding of how this fundamental neural computation is implemented in the visual systems of vertebrates. PMID:29467629

Orientation-Selective Retinal Circuits in Vertebrates.

PubMed

Antinucci, Paride; Hindges, Robert

2018-01-01

Visual information is already processed in the retina before it is transmitted to higher visual centers in the brain. This includes the extraction of salient features from visual scenes, such as motion directionality or contrast, through neurons belonging to distinct neural circuits. Some retinal neurons are tuned to the orientation of elongated visual stimuli. Such 'orientation-selective' neurons are present in the retinae of most, if not all, vertebrate species analyzed to date, with species-specific differences in frequency and degree of tuning. In some cases, orientation-selective neurons have very stereotyped functional and morphological properties suggesting that they represent distinct cell types. In this review, we describe the retinal cell types underlying orientation selectivity found in various vertebrate species, and highlight their commonalities and differences. In addition, we discuss recent studies that revealed the cellular, synaptic and circuit mechanisms at the basis of retinal orientation selectivity. Finally, we outline the significance of these findings in shaping our current understanding of how this fundamental neural computation is implemented in the visual systems of vertebrates.

Toward an Integration of Deep Learning and Neuroscience

PubMed Central

Marblestone, Adam H.; Wayne, Greg; Kording, Konrad P.

2016-01-01

Neuroscience has focused on the detailed implementation of computation, studying neural codes, dynamics and circuits. In machine learning, however, artificial neural networks tend to eschew precisely designed codes, dynamics or circuits in favor of brute force optimization of a cost function, often using simple and relatively uniform initial architectures. Two recent developments have emerged within machine learning that create an opportunity to connect these seemingly divergent perspectives. First, structured architectures are used, including dedicated systems for attention, recursion and various forms of short- and long-term memory storage. Second, cost functions and training procedures have become more complex and are varied across layers and over time. Here we think about the brain in terms of these ideas. We hypothesize that (1) the brain optimizes cost functions, (2) the cost functions are diverse and differ across brain locations and over development, and (3) optimization operates within a pre-structured architecture matched to the computational problems posed by behavior. In support of these hypotheses, we argue that a range of implementations of credit assignment through multiple layers of neurons are compatible with our current knowledge of neural circuitry, and that the brain's specialized systems can be interpreted as enabling efficient optimization for specific problem classes. Such a heterogeneously optimized system, enabled by a series of interacting cost functions, serves to make learning data-efficient and precisely targeted to the needs of the organism. We suggest directions by which neuroscience could seek to refine and test these hypotheses. PMID:27683554

Visual Circuit Development Requires Patterned Activity Mediated by Retinal Acetylcholine Receptors

PubMed Central

Burbridge, Timothy J.; Xu, Hong-Ping; Ackman, James B.; Ge, Xinxin; Zhang, Yueyi; Ye, Mei-Jun; Zhou, Z. Jimmy; Xu, Jian; Contractor, Anis; Crair, Michael C.

2014-01-01

SUMMARY The elaboration of nascent synaptic connections into highly ordered neural circuits is an integral feature of the developing vertebrate nervous system. In sensory systems, patterned spontaneous activity before the onset of sensation is thought to influence this process, but this conclusion remains controversial largely due to the inherent difficulty recording neural activity in early development. Here, we describe novel genetic and pharmacological manipulations of spontaneous retinal activity, assayed in vivo, that demonstrate a causal link between retinal waves and visual circuit refinement. We also report a de-coupling of downstream activity in retinorecipient regions of the developing brain after retinal wave disruption. Significantly, we show that the spatiotemporal characteristics of retinal waves affect the development of specific visual circuits. These results conclusively establish retinal waves as necessary and instructive for circuit refinement in the developing nervous system and reveal how neural circuits adjust to altered patterns of activity prior to experience. PMID:25466916

Determining Changes in Neural Circuits in Tuberous Sclerosis

DTIC Science & Technology

2013-05-01

features of human Tuberous Sclerosis including mosaicism, autism and epilepsy. This research progress deepened our understanding of Tuberous Sclerosis by... autism and epilepsy. This research progress deepened our understanding of Tuberous Sclerosis by linking temporal gene function, mTOR function, physiology...of function of Tsc1 in the brain causes intellectual disability, seizures, sleep disorders, and autism . We took advantage of our CreER/loxP based

Genetic determinants of aggression and impulsivity in humans.

PubMed

Pavlov, Konstantin A; Chistiakov, Dimitry A; Chekhonin, Vladimir P

2012-02-01

Human aggression/impulsivity-related traits have a complex background that is greatly influenced by genetic and non-genetic factors. The relationship between aggression and anxiety is regulated by highly conserved brain regions including amygdala, which controls neural circuits triggering defensive, aggressive, or avoidant behavioral models. The dysfunction of neural circuits responsible for emotional control was shown to represent an etiological factor of violent behavior. In addition to the amygdala, these circuits also involve the anterior cingulated cortex and regions of the prefrontal cortex. Excessive reactivity in the amygdala coupled with inadequate prefrontal regulation serves to increase the likelihood of aggressive behavior. Developmental alterations in prefrontal-subcortical circuitry as well as neuromodulatory and hormonal abnormality appear to play a role. Imbalance in testosterone/serotonin and testosterone/cortisol ratios (e.g., increased testosterone levels and reduced cortisol levels) increases the propensity toward aggression because of reduced activation of the neural circuitry of impulse control and self-regulation. Serotonin facilitates prefrontal inhibition, and thus insufficient serotonergic activity can enhance aggression. Genetic predisposition to aggression appears to be deeply affected by the polymorphic genetic variants of the serotoninergic system that influences serotonin levels in the central and peripheral nervous system, biological effects of this hormone, and rate of serotonin production, synaptic release and degradation. Among these variants, functional polymorphisms in the monoamine oxidase A (MAOA) and serotonin transporter (5-HTT) may be of particular importance due to the relationship between these polymorphic variants and anatomical changes in the limbic system of aggressive people. Furthermore, functional variants of MAOA and 5-HTT are capable of mediating the influence of environmental factors on aggression-related traits. In this review, we consider genetic determinants of human aggression, with special emphasis on genes involved in serotonin and dopamine metabolism and function.

An integrated modelling framework for neural circuits with multiple neuromodulators.

PubMed

Joshi, Alok; Youssofzadeh, Vahab; Vemana, Vinith; McGinnity, T M; Prasad, Girijesh; Wong-Lin, KongFatt

2017-01-01

Neuromodulators are endogenous neurochemicals that regulate biophysical and biochemical processes, which control brain function and behaviour, and are often the targets of neuropharmacological drugs. Neuromodulator effects are generally complex partly owing to the involvement of broad innervation, co-release of neuromodulators, complex intra- and extrasynaptic mechanism, existence of multiple receptor subtypes and high interconnectivity within the brain. In this work, we propose an efficient yet sufficiently realistic computational neural modelling framework to study some of these complex behaviours. Specifically, we propose a novel dynamical neural circuit model that integrates the effective neuromodulator-induced currents based on various experimental data (e.g. electrophysiology, neuropharmacology and voltammetry). The model can incorporate multiple interacting brain regions, including neuromodulator sources, simulate efficiently and easily extendable to large-scale brain models, e.g. for neuroimaging purposes. As an example, we model a network of mutually interacting neural populations in the lateral hypothalamus, dorsal raphe nucleus and locus coeruleus, which are major sources of neuromodulator orexin/hypocretin, serotonin and norepinephrine/noradrenaline, respectively, and which play significant roles in regulating many physiological functions. We demonstrate that such a model can provide predictions of systemic drug effects of the popular antidepressants (e.g. reuptake inhibitors), neuromodulator antagonists or their combinations. Finally, we developed user-friendly graphical user interface software for model simulation and visualization for both fundamental sciences and pharmacological studies. © 2017 The Authors.

An integrated modelling framework for neural circuits with multiple neuromodulators

PubMed Central

Vemana, Vinith

2017-01-01

Neuromodulators are endogenous neurochemicals that regulate biophysical and biochemical processes, which control brain function and behaviour, and are often the targets of neuropharmacological drugs. Neuromodulator effects are generally complex partly owing to the involvement of broad innervation, co-release of neuromodulators, complex intra- and extrasynaptic mechanism, existence of multiple receptor subtypes and high interconnectivity within the brain. In this work, we propose an efficient yet sufficiently realistic computational neural modelling framework to study some of these complex behaviours. Specifically, we propose a novel dynamical neural circuit model that integrates the effective neuromodulator-induced currents based on various experimental data (e.g. electrophysiology, neuropharmacology and voltammetry). The model can incorporate multiple interacting brain regions, including neuromodulator sources, simulate efficiently and easily extendable to large-scale brain models, e.g. for neuroimaging purposes. As an example, we model a network of mutually interacting neural populations in the lateral hypothalamus, dorsal raphe nucleus and locus coeruleus, which are major sources of neuromodulator orexin/hypocretin, serotonin and norepinephrine/noradrenaline, respectively, and which play significant roles in regulating many physiological functions. We demonstrate that such a model can provide predictions of systemic drug effects of the popular antidepressants (e.g. reuptake inhibitors), neuromodulator antagonists or their combinations. Finally, we developed user-friendly graphical user interface software for model simulation and visualization for both fundamental sciences and pharmacological studies. PMID:28100828

Regulation of Body Temperature by the Nervous System.

PubMed

Tan, Chan Lek; Knight, Zachary A

2018-04-04

The regulation of body temperature is one of the most critical functions of the nervous system. Here we review our current understanding of thermoregulation in mammals. We outline the molecules and cells that measure body temperature in the periphery, the neural pathways that communicate this information to the brain, and the central circuits that coordinate the homeostatic response. We also discuss some of the key unresolved issues in this field, including the following: the role of temperature sensing in the brain, the molecular identity of the warm sensor, the central representation of the labeled line for cold, and the neural substrates of thermoregulatory behavior. We suggest that approaches for molecularly defined circuit analysis will provide new insight into these topics in the near future. Copyright © 2018 Elsevier Inc. All rights reserved.

Neural Circuits via Which Single Prolonged Stress Exposure Leads to Fear Extinction Retention Deficits

ERIC Educational Resources Information Center

Knox, Dayan; Stanfield, Briana R.; Staib, Jennifer M.; David, Nina P.; Keller, Samantha M.; DePietro, Thomas

2016-01-01

Single prolonged stress (SPS) has been used to examine mechanisms via which stress exposure leads to post-traumatic stress disorder symptoms. SPS induces fear extinction retention deficits, but neural circuits critical for mediating these deficits are unknown. To address this gap, we examined the effect of SPS on neural activity in brain regions…

Training Excitatory-Inhibitory Recurrent Neural Networks for Cognitive Tasks: A Simple and Flexible Framework

PubMed Central

Wang, Xiao-Jing

2016-01-01

The ability to simultaneously record from large numbers of neurons in behaving animals has ushered in a new era for the study of the neural circuit mechanisms underlying cognitive functions. One promising approach to uncovering the dynamical and computational principles governing population responses is to analyze model recurrent neural networks (RNNs) that have been optimized to perform the same tasks as behaving animals. Because the optimization of network parameters specifies the desired output but not the manner in which to achieve this output, “trained” networks serve as a source of mechanistic hypotheses and a testing ground for data analyses that link neural computation to behavior. Complete access to the activity and connectivity of the circuit, and the ability to manipulate them arbitrarily, make trained networks a convenient proxy for biological circuits and a valuable platform for theoretical investigation. However, existing RNNs lack basic biological features such as the distinction between excitatory and inhibitory units (Dale’s principle), which are essential if RNNs are to provide insights into the operation of biological circuits. Moreover, trained networks can achieve the same behavioral performance but differ substantially in their structure and dynamics, highlighting the need for a simple and flexible framework for the exploratory training of RNNs. Here, we describe a framework for gradient descent-based training of excitatory-inhibitory RNNs that can incorporate a variety of biological knowledge. We provide an implementation based on the machine learning library Theano, whose automatic differentiation capabilities facilitate modifications and extensions. We validate this framework by applying it to well-known experimental paradigms such as perceptual decision-making, context-dependent integration, multisensory integration, parametric working memory, and motor sequence generation. Our results demonstrate the wide range of neural activity patterns and behavior that can be modeled, and suggest a unified setting in which diverse cognitive computations and mechanisms can be studied. PMID:26928718

IP3R-mediated Ca2+ release regulates protein metabolism in Drosophila neuroendocrine cells: implications for development under nutrient stress.

PubMed

Megha; Hasan, Gaiti

2017-04-15

Successful completion of animal development is fundamentally reliant on nutritional cues. Surviving periods of nutritional insufficiency requires adaptations that are coordinated, in part, by neural circuits. As neuropeptides secreted by neuroendocrine (NE) cells modulate neural circuits, we investigated NE cell function during development under nutrient stress. Starved Drosophila larvae exhibited reduced pupariation if either insulin signaling or IP 3 /Ca 2+ signaling were downregulated in NE cells. Moreover, an IP 3 R (inositol 1,4,5-trisphosphate receptor) loss-of-function mutant displayed reduced protein synthesis, which was rescued by overexpression of either InR (insulin receptor) or IP 3 R in NE cells of the mutant, suggesting that the two signaling pathways might be functionally compensatory. Furthermore, cultured IP 3 R mutant NE cells, but not neurons, exhibited reduced protein translation. Thus cell-specific regulation of protein synthesis by IP 3 R in NE cells influences protein metabolism. We propose that this regulation helps developing animals survive in poor nutritional conditions. © 2017. Published by The Company of Biologists Ltd.

Encoding neural and synaptic functionalities in electron spin: A pathway to efficient neuromorphic computing

NASA Astrophysics Data System (ADS)

Sengupta, Abhronil; Roy, Kaushik

2017-12-01

Present day computers expend orders of magnitude more computational resources to perform various cognitive and perception related tasks that humans routinely perform every day. This has recently resulted in a seismic shift in the field of computation where research efforts are being directed to develop a neurocomputer that attempts to mimic the human brain by nanoelectronic components and thereby harness its efficiency in recognition problems. Bridging the gap between neuroscience and nanoelectronics, this paper attempts to provide a review of the recent developments in the field of spintronic device based neuromorphic computing. Description of various spin-transfer torque mechanisms that can be potentially utilized for realizing device structures mimicking neural and synaptic functionalities is provided. A cross-layer perspective extending from the device to the circuit and system level is presented to envision the design of an All-Spin neuromorphic processor enabled with on-chip learning functionalities. Device-circuit-algorithm co-simulation framework calibrated to experimental results suggest that such All-Spin neuromorphic systems can potentially achieve almost two orders of magnitude energy improvement in comparison to state-of-the-art CMOS implementations.

Cognitive deficits caused by prefrontal cortical and hippocampal neural disinhibition.

PubMed

Bast, Tobias; Pezze, Marie; McGarrity, Stephanie

2017-10-01

We review recent evidence concerning the significance of inhibitory GABA transmission and of neural disinhibition, that is, deficient GABA transmission, within the prefrontal cortex and the hippocampus, for clinically relevant cognitive functions. Both regions support important cognitive functions, including attention and memory, and their dysfunction has been implicated in cognitive deficits characterizing neuropsychiatric disorders. GABAergic inhibition shapes cortico-hippocampal neural activity, and, recently, prefrontal and hippocampal neural disinhibition has emerged as a pathophysiological feature of major neuropsychiatric disorders, especially schizophrenia and age-related cognitive decline. Regional neural disinhibition, disrupting spatio-temporal control of neural activity and causing aberrant drive of projections, may disrupt processing within the disinhibited region and efferent regions. Recent studies in rats showed that prefrontal and hippocampal neural disinhibition (by local GABA antagonist microinfusion) dysregulates burst firing, which has been associated with important aspects of neural information processing. Using translational tests of clinically relevant cognitive functions, these studies showed that prefrontal and hippocampal neural disinhibition disrupts regional cognitive functions (including prefrontal attention and hippocampal memory function). Moreover, hippocampal neural disinhibition disrupted attentional performance, which does not require the hippocampus but requires prefrontal-striatal circuits modulated by the hippocampus. However, some prefrontal and hippocampal functions (including inhibitory response control) are spared by regional disinhibition. We consider conceptual implications of these findings, regarding the distinct relationships of distinct cognitive functions to prefrontal and hippocampal GABA tone and neural activity. Moreover, the findings support the proposition that prefrontal and hippocampal neural disinhibition contributes to clinically relevant cognitive deficits, and we consider pharmacological strategies for ameliorating cognitive deficits by rebalancing disinhibition-induced aberrant neural activity. Linked Articles This article is part of a themed section on Pharmacology of Cognition: a Panacea for Neuropsychiatric Disease? To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v174.19/issuetoc. © 2017 The British Pharmacological Society.

The Pleiotropic MET Receptor Network: Circuit Development and the Neural-Medical Interface of Autism

PubMed Central

Eagleson, Kathie L.; Xie, Zhihui; Levitt, Pat

2016-01-01

People with autism spectrum disorder (ASD) and other neurodevelopmental disorders (NDDs) are behaviorally and medically heterogeneous. The combination of polygenicity and gene pleiotropy - the influence of one gene on distinct phenotypes - raises questions of how specific genes and their protein products interact to contribute to NDDs. A preponderance of evidence supports developmental and pathophysiological roles for the MET receptor tyrosine kinase, a multi-functional receptor that mediates distinct biological responses depending upon cell context. MET influences neuron architecture and synapse maturation in the forebrain, and regulates homeostasis in gastrointestinal and immune systems, both commonly disrupted in NDDs. Peak expression of synapse-enriched MET is conserved across rodent and primate forebrain, yet regional differences in primate neocortex are pronounced, with enrichment in circuits that participate in social information processing. A functional risk allele in the MET promoter, enriched in subgroups of children with ASD, reduces transcription and disrupts socially-relevant neural circuits structurally and functionally. In mice, circuit-specific deletion of Met causes distinct atypical behaviors. MET activation increases dendritic complexity and nascent synapse number, but synapse maturation requires reductions in MET. MET mediates its specific biological effects through different intracellular signaling pathways, and has a complex protein interactome that is enriched in ASD and other NDD candidates. The interactome is co-regulated in developing human neocortex. We suggest that a gene as pleiotropic and highly regulated as MET, together with its interactome, is biologically relevant in normal and pathophysiological contexts, impacting central and peripheral phenotypes that contribute to NDD risk and clinical symptoms. PMID:27837921

Neural activation in the "reward circuit" shows a nonlinear response to facial attractiveness.

PubMed

Liang, Xiaoyun; Zebrowitz, Leslie A; Zhang, Yi

2010-01-01

Positive behavioral responses to attractive faces have led neuroscientists to investigate underlying neural mechanisms in a "reward circuit" that includes brain regions innervated by dopamine pathways. Using male faces ranging from attractive to extremely unattractive, disfigured ones, this study is the first to demonstrate heightened responses to both rewarding and aversive faces in numerous areas of this putative reward circuit. Parametric analyses employing orthogonal linear and nonlinear regressors revealed positive nonlinear effects in anterior cingulate cortex, lateral orbital frontal cortex (LOFC), striatum (nucleus accumbens, caudate, putamen), and ventral tegmental area, in addition to replicating previously documented linear effects in medial orbital frontal cortex (MOFC) and LOFC and nonlinear effects in amygdala and MOFC. The widespread nonlinear responses are consistent with single cell recordings in animals showing responses to both rewarding and aversive stimuli, and with some human fMRI investigations of non-face stimuli. They indicate that the reward circuit does not process face valence with any simple dissociation of function across structures. Perceiver gender modulated some responses to our male faces: Women showed stronger linear effects, and men showed stronger nonlinear effects, which may have functional implications. Our discovery of nonlinear responses to attractiveness throughout the reward circuit echoes the history of amygdala research: Early work indicated a linear response to threatening stimuli, including faces; later work also revealed a nonlinear response with heightened activation to affectively salient stimuli regardless of valence. The challenge remains to determine how such dual coding influences feelings, such as pleasure and pain, and guides goal-related behavioral responses, such as approach and avoidance.

Multichannel brain recordings in behaving Drosophila reveal oscillatory activity and local coherence in response to sensory stimulation and circuit activation

PubMed Central

Paulk, Angelique C.; Zhou, Yanqiong; Stratton, Peter; Liu, Li

2013-01-01

Neural networks in vertebrates exhibit endogenous oscillations that have been associated with functions ranging from sensory processing to locomotion. It remains unclear whether oscillations may play a similar role in the insect brain. We describe a novel “whole brain” readout for Drosophila melanogaster using a simple multichannel recording preparation to study electrical activity across the brain of flies exposed to different sensory stimuli. We recorded local field potential (LFP) activity from >2,000 registered recording sites across the fly brain in >200 wild-type and transgenic animals to uncover specific LFP frequency bands that correlate with: 1) brain region; 2) sensory modality (olfactory, visual, or mechanosensory); and 3) activity in specific neural circuits. We found endogenous and stimulus-specific oscillations throughout the fly brain. Central (higher-order) brain regions exhibited sensory modality-specific increases in power within narrow frequency bands. Conversely, in sensory brain regions such as the optic or antennal lobes, LFP coherence, rather than power, best defined sensory responses across modalities. By transiently activating specific circuits via expression of TrpA1, we found that several circuits in the fly brain modulate LFP power and coherence across brain regions and frequency domains. However, activation of a neuromodulatory octopaminergic circuit specifically increased neuronal coherence in the optic lobes during visual stimulation while decreasing coherence in central brain regions. Our multichannel recording and brain registration approach provides an effective way to track activity simultaneously across the fly brain in vivo, allowing investigation of functional roles for oscillations in processing sensory stimuli and modulating behavior. PMID:23864378

The roles of cannabinoid and dopamine receptor systems in neural emotional learning circuits: implications for schizophrenia and addiction.

PubMed

Laviolette, S R; Grace, A A

2006-07-01

Cannabinoids represent one of the most widely used hallucinogenic drugs and induce profound alterations in sensory perception and emotional processing. Similarly, the dopamine (DA) neurotransmitter system is critical for the central processing of emotion and motivation. Functional disturbances in either of these neurotransmitter systems are well-established correlates of the psychopathological symptoms and behavioral manifestations observed in addiction and schizophrenia. Increasing evidence from the anatomical, pharmacological and behavioral neuroscience fields points to complex functional interactions between these receptor systems at the anatomical, pharmacological and neural systems levels. An important question relates to whether these systems act in an orchestrated manner to produce the emotional processing and sensory perception deficits underlying addiction and schizophrenia. This review describes evidence for functional neural interactions between cannabinoid and DA receptor systems and how disturbances in this neural circuitry may underlie the aberrant emotional learning and processing observed in disorders such as addiction and schizophrenia.

Cortical control of intraspinal microstimulation: Toward a new approach for restoration of function after spinal cord injury.

PubMed

Shahdoost, Shahab; Frost, Shawn; Dunham, Caleb; DeJong, Stacey; Barbay, Scott; Nudo, Randolph; Mohseni, Pedram

2015-08-01

Approximately 6 million people in the United States are currently living with paralysis in which 23% of the cases are related to spinal cord injury (SCI). Miniaturized closed-loop neural interfaces have the potential for restoring function and mobility lost to debilitating neural injuries such as SCI by leveraging recent advancements in bioelectronics and a better understanding of the processes that underlie functional and anatomical reorganization in an injured nervous system. This paper describes our current progress toward developing a miniaturized brain-machine-spinal cord interface (BMSI) that converts in real time the neural command signals recorded from the cortical motor regions to electrical stimuli delivered to the spinal cord below the injury level. Using a combination of custom integrated circuit (IC) technology for corticospinal interfacing and field-programmable gate array (FPGA)-based technology for embedded signal processing, we demonstrate proof-of-concept of distinct muscle pattern activation via intraspinal microstimulation (ISMS) controlled in real time by intracortical neural spikes in an anesthetized laboratory rat.

Optogenetic control of Drosophila using a red-shifted channelrhodopsin reveals experience-dependent influences on courtship.

PubMed

Inagaki, Hidehiko K; Jung, Yonil; Hoopfer, Eric D; Wong, Allan M; Mishra, Neeli; Lin, John Y; Tsien, Roger Y; Anderson, David J

2014-03-01

Optogenetics allows the manipulation of neural activity in freely moving animals with millisecond precision, but its application in Drosophila melanogaster has been limited. Here we show that a recently described red activatable channelrhodopsin (ReaChR) permits control of complex behavior in freely moving adult flies, at wavelengths that are not thought to interfere with normal visual function. This tool affords the opportunity to control neural activity over a broad dynamic range of stimulation intensities. Using time-resolved activation, we show that the neural control of male courtship song can be separated into (i) probabilistic, persistent and (ii) deterministic, command-like components. The former, but not the latter, neurons are subject to functional modulation by social experience, which supports the idea that they constitute a locus of state-dependent influence. This separation is not evident using thermogenetic tools, a result underscoring the importance of temporally precise control of neuronal activation in the functional dissection of neural circuits in Drosophila.

Functional architecture of an optic flow-responsive area that drives horizontal eye movements in zebrafish.

PubMed

Kubo, Fumi; Hablitzel, Bastian; Dal Maschio, Marco; Driever, Wolfgang; Baier, Herwig; Arrenberg, Aristides B

2014-03-19

Animals respond to whole-field visual motion with compensatory eye and body movements in order to stabilize both their gaze and position with respect to their surroundings. In zebrafish, rotational stimuli need to be distinguished from translational stimuli to drive the optokinetic and the optomotor responses, respectively. Here, we systematically characterize the neural circuits responsible for these operations using a combination of optogenetic manipulation and in vivo calcium imaging during optic flow stimulation. By recording the activity of thousands of neurons within the area pretectalis (APT), we find four bilateral pairs of clusters that process horizontal whole-field motion and functionally classify eleven prominent neuron types with highly selective response profiles. APT neurons are prevalently direction selective, either monocularly or binocularly driven, and hierarchically organized to distinguish between rotational and translational optic flow. Our data predict a wiring diagram of a neural circuit tailored to drive behavior that compensates for self-motion. Copyright © 2014 Elsevier Inc. All rights reserved.

Numerical Analysis of Modeling Based on Improved Elman Neural Network

PubMed Central

Jie, Shao

2014-01-01

A modeling based on the improved Elman neural network (IENN) is proposed to analyze the nonlinear circuits with the memory effect. The hidden layer neurons are activated by a group of Chebyshev orthogonal basis functions instead of sigmoid functions in this model. The error curves of the sum of squared error (SSE) varying with the number of hidden neurons and the iteration step are studied to determine the number of the hidden layer neurons. Simulation results of the half-bridge class-D power amplifier (CDPA) with two-tone signal and broadband signals as input have shown that the proposed behavioral modeling can reconstruct the system of CDPAs accurately and depict the memory effect of CDPAs well. Compared with Volterra-Laguerre (VL) model, Chebyshev neural network (CNN) model, and basic Elman neural network (BENN) model, the proposed model has better performance. PMID:25054172

Neural-genetic synthesis for state-space controllers based on linear quadratic regulator design for eigenstructure assignment.

PubMed

da Fonseca Neto, João Viana; Abreu, Ivanildo Silva; da Silva, Fábio Nogueira

2010-04-01

Toward the synthesis of state-space controllers, a neural-genetic model based on the linear quadratic regulator design for the eigenstructure assignment of multivariable dynamic systems is presented. The neural-genetic model represents a fusion of a genetic algorithm and a recurrent neural network (RNN) to perform the selection of the weighting matrices and the algebraic Riccati equation solution, respectively. A fourth-order electric circuit model is used to evaluate the convergence of the computational intelligence paradigms and the control design method performance. The genetic search convergence evaluation is performed in terms of the fitness function statistics and the RNN convergence, which is evaluated by landscapes of the energy and norm, as a function of the parameter deviations. The control problem solution is evaluated in the time and frequency domains by the impulse response, singular values, and modal analysis.

Ethical issues in neuroprosthetics

NASA Astrophysics Data System (ADS)

Glannon, Walter

2016-04-01

Objective. Neuroprosthetics are artificial devices or systems designed to generate, restore or modulate a range of neurally mediated functions. These include sensorimotor, visual, auditory, cognitive affective and volitional functions that have been impaired or lost from congenital anomalies, traumatic brain injury, infection, amputation or neurodevelopmental and neurodegenerative disorders. Cochlear implants, visual prosthetics, deep brain stimulation, brain-computer interfaces, brain-to-brain interfaces and hippocampal prosthetics can bypass, replace or compensate for dysfunctional neural circuits, brain injury and limb loss. They can enable people with these conditions to gain or regain varying degrees of control of thought and behavior. These direct and indirect interventions in the brain raise general ethical questions about weighing the potential benefit of altering neural circuits against the potential harm from neurophysiological and psychological sequelae. Other ethical questions are more specific to the therapeutic goals of particular neuroprosthetics and the conditions for which they are indicated. These include informed consent, agency, autonomy (free will) and identity. Approach. This review is an analysis and discussion of these questions. It also includes consideration of social justice issues such as how to establish and implement fair selection criteria in providing access to neuroprosthetic research and balancing technological innovation with patients’ best interests. Main results. Neuroprosthetics can restore or improve motor and mental functions in bypassing areas of injury or modulating dysregulation in neural circuits. As enabling devices that integrate with these circuits, neuroprosthetics can restore varying degrees of autonomous agency for people affected by neurological and psychiatric disorders. They can also re-establish the connectedness and continuity of the psychological properties they had before injury or disease onset and thereby re-establish their identity. Neuroprosthetics can maximize benefit and minimize harm for people affected by damaged or dysfunctional brains and improve the quality of their lives. Significance. Provided that adequate protections are in place for research subjects and patients, the probable benefit of research into and therapeutic applications of neuroprosthetics outweighs the risk and therefore can be ethically justified. Depending on their neurogenerative potential, there may be an ethical obligation to conduct this research. Advances in neuroscience will generate new ethical and philosophical questions about people and their brains. These questions should shape the evolution and application of novel techniques to better understand and treat brain disorders.

Ethical issues in neuroprosthetics.

PubMed

Glannon, Walter

2016-04-01

Neuroprosthetics are artificial devices or systems designed to generate, restore or modulate a range of neurally mediated functions. These include sensorimotor, visual, auditory, cognitive affective and volitional functions that have been impaired or lost from congenital anomalies, traumatic brain injury, infection, amputation or neurodevelopmental and neurodegenerative disorders. Cochlear implants, visual prosthetics, deep brain stimulation, brain-computer interfaces, brain-to-brain interfaces and hippocampal prosthetics can bypass, replace or compensate for dysfunctional neural circuits, brain injury and limb loss. They can enable people with these conditions to gain or regain varying degrees of control of thought and behavior. These direct and indirect interventions in the brain raise general ethical questions about weighing the potential benefit of altering neural circuits against the potential harm from neurophysiological and psychological sequelae. Other ethical questions are more specific to the therapeutic goals of particular neuroprosthetics and the conditions for which they are indicated. These include informed consent, agency, autonomy (free will) and identity. This review is an analysis and discussion of these questions. It also includes consideration of social justice issues such as how to establish and implement fair selection criteria in providing access to neuroprosthetic research and balancing technological innovation with patients' best interests. Neuroprosthetics can restore or improve motor and mental functions in bypassing areas of injury or modulating dysregulation in neural circuits. As enabling devices that integrate with these circuits, neuroprosthetics can restore varying degrees of autonomous agency for people affected by neurological and psychiatric disorders. They can also re-establish the connectedness and continuity of the psychological properties they had before injury or disease onset and thereby re-establish their identity. Neuroprosthetics can maximize benefit and minimize harm for people affected by damaged or dysfunctional brains and improve the quality of their lives. Provided that adequate protections are in place for research subjects and patients, the probable benefit of research into and therapeutic applications of neuroprosthetics outweighs the risk and therefore can be ethically justified. Depending on their neurogenerative potential, there may be an ethical obligation to conduct this research. Advances in neuroscience will generate new ethical and philosophical questions about people and their brains. These questions should shape the evolution and application of novel techniques to better understand and treat brain disorders.

Altered mGluR5-Homer scaffolds and corticostriatal connectivity in a Shank3 complete knockout model of autism.

PubMed

Wang, Xiaoming; Bey, Alexandra L; Katz, Brittany M; Badea, Alexandra; Kim, Namsoo; David, Lisa K; Duffney, Lara J; Kumar, Sunil; Mague, Stephen D; Hulbert, Samuel W; Dutta, Nisha; Hayrapetyan, Volodya; Yu, Chunxiu; Gaidis, Erin; Zhao, Shengli; Ding, Jin-Dong; Xu, Qiong; Chung, Leeyup; Rodriguiz, Ramona M; Wang, Fan; Weinberg, Richard J; Wetsel, William C; Dzirasa, Kafui; Yin, Henry; Jiang, Yong-Hui

2016-05-10

Human neuroimaging studies suggest that aberrant neural connectivity underlies behavioural deficits in autism spectrum disorders (ASDs), but the molecular and neural circuit mechanisms underlying ASDs remain elusive. Here, we describe a complete knockout mouse model of the autism-associated Shank3 gene, with a deletion of exons 4-22 (Δe4-22). Both mGluR5-Homer scaffolds and mGluR5-mediated signalling are selectively altered in striatal neurons. These changes are associated with perturbed function at striatal synapses, abnormal brain morphology, aberrant structural connectivity and ASD-like behaviour. In vivo recording reveals that the cortico-striatal-thalamic circuit is tonically hyperactive in mutants, but becomes hypoactive during social behaviour. Manipulation of mGluR5 activity attenuates excessive grooming and instrumental learning differentially, and rescues impaired striatal synaptic plasticity in Δe4-22(-/-) mice. These findings show that deficiency of Shank3 can impair mGluR5-Homer scaffolding, resulting in cortico-striatal circuit abnormalities that underlie deficits in learning and ASD-like behaviours. These data suggest causal links between genetic, molecular, and circuit mechanisms underlying the pathophysiology of ASDs.

Altered mGluR5-Homer scaffolds and corticostriatal connectivity in a Shank3 complete knockout model of autism

PubMed Central

Wang, Xiaoming; Bey, Alexandra L.; Katz, Brittany M.; Badea, Alexandra; Kim, Namsoo; David, Lisa K.; Duffney, Lara J.; Kumar, Sunil; Mague, Stephen D.; Hulbert, Samuel W.; Dutta, Nisha; Hayrapetyan, Volodya; Yu, Chunxiu; Gaidis, Erin; Zhao, Shengli; Ding, Jin-Dong; Xu, Qiong; Chung, Leeyup; Rodriguiz, Ramona M.; Wang, Fan; Weinberg, Richard J.; Wetsel, William C.; Dzirasa, Kafui; Yin, Henry; Jiang, Yong-hui

2016-01-01

Human neuroimaging studies suggest that aberrant neural connectivity underlies behavioural deficits in autism spectrum disorders (ASDs), but the molecular and neural circuit mechanisms underlying ASDs remain elusive. Here, we describe a complete knockout mouse model of the autism-associated Shank3 gene, with a deletion of exons 4–22 (Δe4–22). Both mGluR5-Homer scaffolds and mGluR5-mediated signalling are selectively altered in striatal neurons. These changes are associated with perturbed function at striatal synapses, abnormal brain morphology, aberrant structural connectivity and ASD-like behaviour. In vivo recording reveals that the cortico-striatal-thalamic circuit is tonically hyperactive in mutants, but becomes hypoactive during social behaviour. Manipulation of mGluR5 activity attenuates excessive grooming and instrumental learning differentially, and rescues impaired striatal synaptic plasticity in Δe4–22−/− mice. These findings show that deficiency of Shank3 can impair mGluR5-Homer scaffolding, resulting in cortico-striatal circuit abnormalities that underlie deficits in learning and ASD-like behaviours. These data suggest causal links between genetic, molecular, and circuit mechanisms underlying the pathophysiology of ASDs. PMID:27161151

Neuromorphic neural interfaces: from neurophysiological inspiration to biohybrid coupling with nervous systems

NASA Astrophysics Data System (ADS)

Broccard, Frédéric D.; Joshi, Siddharth; Wang, Jun; Cauwenberghs, Gert

2017-08-01

Objective. Computation in nervous systems operates with different computational primitives, and on different hardware, than traditional digital computation and is thus subjected to different constraints from its digital counterpart regarding the use of physical resources such as time, space and energy. In an effort to better understand neural computation on a physical medium with similar spatiotemporal and energetic constraints, the field of neuromorphic engineering aims to design and implement electronic systems that emulate in very large-scale integration (VLSI) hardware the organization and functions of neural systems at multiple levels of biological organization, from individual neurons up to large circuits and networks. Mixed analog/digital neuromorphic VLSI systems are compact, consume little power and operate in real time independently of the size and complexity of the model. Approach. This article highlights the current efforts to interface neuromorphic systems with neural systems at multiple levels of biological organization, from the synaptic to the system level, and discusses the prospects for future biohybrid systems with neuromorphic circuits of greater complexity. Main results. Single silicon neurons have been interfaced successfully with invertebrate and vertebrate neural networks. This approach allowed the investigation of neural properties that are inaccessible with traditional techniques while providing a realistic biological context not achievable with traditional numerical modeling methods. At the network level, populations of neurons are envisioned to communicate bidirectionally with neuromorphic processors of hundreds or thousands of silicon neurons. Recent work on brain-machine interfaces suggests that this is feasible with current neuromorphic technology. Significance. Biohybrid interfaces between biological neurons and VLSI neuromorphic systems of varying complexity have started to emerge in the literature. Primarily intended as a computational tool for investigating fundamental questions related to neural dynamics, the sophistication of current neuromorphic systems now allows direct interfaces with large neuronal networks and circuits, resulting in potentially interesting clinical applications for neuroengineering systems, neuroprosthetics and neurorehabilitation.

Cortical networks dynamically emerge with the interplay of slow and fast oscillations for memory of a natural scene.

PubMed

Mizuhara, Hiroaki; Sato, Naoyuki; Yamaguchi, Yoko

2015-05-01

Neural oscillations are crucial for revealing dynamic cortical networks and for serving as a possible mechanism of inter-cortical communication, especially in association with mnemonic function. The interplay of the slow and fast oscillations might dynamically coordinate the mnemonic cortical circuits to rehearse stored items during working memory retention. We recorded simultaneous EEG-fMRI during a working memory task involving a natural scene to verify whether the cortical networks emerge with the neural oscillations for memory of the natural scene. The slow EEG power was enhanced in association with the better accuracy of working memory retention, and accompanied cortical activities in the mnemonic circuits for the natural scene. Fast oscillation showed a phase-amplitude coupling to the slow oscillation, and its power was tightly coupled with the cortical activities for representing the visual images of natural scenes. The mnemonic cortical circuit with the slow neural oscillations would rehearse the distributed natural scene representations with the fast oscillation for working memory retention. The coincidence of the natural scene representations could be obtained by the slow oscillation phase to create a coherent whole of the natural scene in the working memory. Copyright © 2015 Elsevier Inc. All rights reserved.

Prefrontal-limbic connectivity during worry in older adults with generalized anxiety disorder.

PubMed

Mohlman, Jan; Eldreth, Dana A; Price, Rebecca B; Staples, Alison M; Hanson, Catherine

2017-04-01

Although generalized anxiety disorder (GAD) is one of the most prevalent anxiety disorders in older adults, very little is known about the neurobiology of worry, the hallmark symptom of GAD in adults over the age of 60. This study investigated the neurobiology and neural circuitry of worry in older GAD patients and controls. Twenty older GAD patients and 16 age-matched controls (mean age = 67.88) were compared on clinical measures and neural activity during worry using functional magnetic resonance imaging. As expected, worry elicited activation in frontal regions, amygdala, and insula within the GAD group, with a similar but less prominent frontal pattern was observed in controls. Effective connectivity analyses revealed a positive directional circuit in the GAD group extending from ventromedial through dorsolateral prefrontal cortices, converging on the amygdala. A less complex circuit was observed in controls with only dorsolateral prefrontal regions converging on the amygdala; however, a separate circuit passing through the orbitofrontal cortex converged on the insula. Results elucidate a different neurobiology of pathological versus normal worry in later life. A limited resource model is implicated wherein worry in GAD competes for the same neural resources (e.g. prefrontal cortical areas) that are involved in the adaptive regulation of emotion through cognitive and behavioral strategies.

Neural Markers and Rehabilitation of Executive Functioning in Veterans with TBI and PTSD

DTIC Science & Technology

2015-10-01

functioning. Functional magnetic resonance imaging ( fMRI ) will be used to evaluate changes in cortical function in frontostriate and frontoparietal circuits...EEG and fMRI will be conducted and then transport Veterans back to our laboratory. We will assure transportation is running efficiently and without...delays before study commencement.  Transportation to the EEG and fMRI was arranged through the UNC-Chapel Hill School of Medicine at month 9

Modification of tenascin-R expression following unilateral labyrinthectomy in rats indicates its possible role in neural plasticity of the vestibular neural circuit.

PubMed

Gaal, Botond; Jóhannesson, Einar Örn; Dattani, Amit; Magyar, Agnes; Wéber, Ildikó; Matesz, Clara

2015-09-01

We have previously found that unilateral labyrinthectomy is accompanied by modification of hyaluronan and chondroitin sulfate proteoglycan staining in the lateral vestibular nucleus of rats and the time course of subsequent reorganization of extracellular matrix assembly correlates to the restoration of impaired vestibular function. The tenascin-R has repelling effect on pathfinding during axonal growth/regrowth, and thus inhibits neural circuit repair. By using immunohistochemical method, we studied the modification of tenascin-R expression in the superior, medial, lateral, and descending vestibular nuclei of the rat following unilateral labyrinthectomy. On postoperative day 1, tenascin-R reaction in the perineuronal nets disappeared on the side of labyrinthectomy in the superior, lateral, medial, and rostral part of the descending vestibular nuclei. On survival day 3, the staining intensity of tenascin-R reaction in perineuronal nets recovered on the operated side of the medial vestibular nucleus, whereas it was restored by the time of postoperative day 7 in the superior, lateral and rostral part of the descending vestibular nuclei. The staining intensity of tenascin-R reaction remained unchanged in the caudal part of the descending vestibular nucleus bilaterally. Regional differences in the modification of tenascin-R expression presented here may be associated with different roles of individual vestibular nuclei in the compensatory processes. The decreased expression of the tenascin-R may suggest the extracellular facilitation of plastic modifications in the vestibular neural circuit after lesion of the labyrinthine receptors.

2010 Carl Ludwig Distinguished Lectureship of the APS Neural Control and Autonomic Regulation Section: Central neural pathways for thermoregulatory cold defense

PubMed Central

2011-01-01

Central neural circuits orchestrate the homeostatic repertoire to maintain body temperature during environmental temperature challenges and to alter body temperature during the inflammatory response. This review summarizes the research leading to a model representing our current understanding of the neural pathways through which cutaneous thermal receptors alter thermoregulatory effectors: the cutaneous circulation for control of heat loss, and brown adipose tissue, skeletal muscle, and the heart for thermogenesis. The activation of these effectors is regulated by parallel but distinct, effector-specific core efferent pathways within the central nervous system (CNS) that share a common peripheral thermal sensory input. The thermal afferent circuit from cutaneous thermal receptors includes neurons in the spinal dorsal horn projecting to lateral parabrachial nucleus neurons that project to the medial aspect of the preoptic area. Within the preoptic area, warm-sensitive, inhibitory output neurons control heat production by reducing the discharge of thermogenesis-promoting neurons in the dorsomedial hypothalamus. The rostral ventromedial medulla, including the raphe pallidus, receives projections form the dorsomedial hypothalamus and contains spinally projecting premotor neurons that provide the excitatory drive to spinal circuits controlling the activity of thermogenic effectors. A distinct population of warm-sensitive preoptic neurons controls heat loss through an inhibitory input to raphe pallidus sympathetic premotor neurons controlling cutaneous vasoconstriction. The model proposed for central thermoregulatory control provides a platform for further understanding of the functional organization of central thermoregulation. PMID:21270352

The therapeutic potential of cell identity reprogramming for the treatment of aging-related neurodegenerative disorders

PubMed Central

Smith, Derek K.; He, Miao; Zhang, Chun-Li; Zheng, Jialin C.

2018-01-01

Neural cell identity reprogramming strategies aim to treat age-related neurodegenerative disorders with newly induced neurons that regenerate neural architecture and functional circuits in vivo. The isolation and neural differentiation of pluripotent embryonic stem cells provided the first in vitro models of human neurodegenerative disease. Investigation into the molecular mechanisms underlying stem cell pluripotency revealed that somatic cells could be reprogrammed to induced pluripotent stem cells (iPSCs) and these cells could be used to model Alzheimer disease, amyotrophic lateral sclerosis, Huntington disease, and Parkinson disease. Additional neural precursor and direct transdifferentiation strategies further enabled the induction of diverse neural linages and neuron subtypes both in vitro and in vivo. In this review, we highlight neural induction strategies that utilize stem cells, iPSCs, and lineage reprogramming to model or treat age-related neurodegenerative diseases, as well as, the clinical challenges related to neural transplantation and in vivo reprogramming strategies. PMID:26844759

Neuroendocrine circuits governing energy balance and stress regulation: functional overlap and therapeutic implications

PubMed Central

Ulrich-Lai, Yvonne M.; Ryan, Karen K.

2014-01-01

Significant co-morbidities between obesity-related metabolic disease and stress-related psychological disorders suggest important functional interactions between energy balance and brain stress integration. Largely overlapping neural circuits control these systems, and this anatomical arrangement optimizes opportunities for mutual influence. Here we first review the current literature identifying effects of metabolic neuroendocrine signals on stress regulation, and vice versa. Next, the contributions of reward driven food intake to these metabolic and stress interactions are discussed. Lastly, we consider the inter-relationships among metabolism, stress and reward in light of their important implications in the development of therapies for metabolism- or stress-related disease. PMID:24630812

Assimilation of Biophysical Neuronal Dynamics in Neuromorphic VLSI.

PubMed

Wang, Jun; Breen, Daniel; Akinin, Abraham; Broccard, Frederic; Abarbanel, Henry D I; Cauwenberghs, Gert

2017-12-01

Representing the biophysics of neuronal dynamics and behavior offers a principled analysis-by-synthesis approach toward understanding mechanisms of nervous system functions. We report on a set of procedures assimilating and emulating neurobiological data on a neuromorphic very large scale integrated (VLSI) circuit. The analog VLSI chip, NeuroDyn, features 384 digitally programmable parameters specifying for 4 generalized Hodgkin-Huxley neurons coupled through 12 conductance-based chemical synapses. The parameters also describe reversal potentials, maximal conductances, and spline regressed kinetic functions for ion channel gating variables. In one set of experiments, we assimilated membrane potential recorded from one of the neurons on the chip to the model structure upon which NeuroDyn was designed using the known current input sequence. We arrived at the programmed parameters except for model errors due to analog imperfections in the chip fabrication. In a related set of experiments, we replicated songbird individual neuron dynamics on NeuroDyn by estimating and configuring parameters extracted using data assimilation from intracellular neural recordings. Faithful emulation of detailed biophysical neural dynamics will enable the use of NeuroDyn as a tool to probe electrical and molecular properties of functional neural circuits. Neuroscience applications include studying the relationship between molecular properties of neurons and the emergence of different spike patterns or different brain behaviors. Clinical applications include studying and predicting effects of neuromodulators or neurodegenerative diseases on ion channel kinetics.

Implementing neural nets with programmable logic

NASA Technical Reports Server (NTRS)

Vidal, Jacques J.

1988-01-01

Networks of Boolean programmable logic modules are presented as one purely digital class of artificial neural nets. The approach contrasts with the continuous analog framework usually suggested. Programmable logic networks are capable of handling many neural-net applications. They avoid some of the limitations of threshold logic networks and present distinct opportunities. The network nodes are called dynamically programmable logic modules. They can be implemented with digitally controlled demultiplexers. Each node performs a Boolean function of its inputs which can be dynamically assigned. The overall network is therefore a combinational circuit and its outputs are Boolean global functions of the network's input variables. The approach offers definite advantages for VLSI implementation, namely, a regular architecture with limited connectivity, simplicity of the control machinery, natural modularity, and the support of a mature technology.

Implementation of an integrated op-amp based chaotic neuron model and observation of its chaotic dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jung, Jinwoo; Lee, Jewon; Song, Hanjung

2011-03-15

This paper presents a fully integrated circuit implementation of an operational amplifier (op-amp) based chaotic neuron model with a bipolar output function, experimental measurements, and analyses of its chaotic behavior. The proposed chaotic neuron model integrated circuit consists of several op-amps, sample and hold circuits, a nonlinear function block for chaotic signal generation, a clock generator, a nonlinear output function, etc. Based on the HSPICE (circuit program) simulation results, approximated empirical equations for analyses were formulated. Then, the chaotic dynamical responses such as bifurcation diagrams, time series, and Lyapunov exponent were calculated using these empirical equations. In addition, we performedmore » simulations about two chaotic neuron systems with four synapses to confirm neural network connections and got normal behavior of the chaotic neuron such as internal state bifurcation diagram according to the synaptic weight variation. The proposed circuit was fabricated using a 0.8-{mu}m single poly complementary metal-oxide semiconductor technology. Measurements of the fabricated single chaotic neuron with {+-}2.5 V power supplies and a 10 kHz sampling clock frequency were carried out and compared with the simulated results.« less

Dynamic neural activity during stress signals resilient coping

PubMed Central

Sinha, Rajita; Lacadie, Cheryl M.; Constable, R. Todd; Seo, Dongju

2016-01-01

Active coping underlies a healthy stress response, but neural processes supporting such resilient coping are not well-known. Using a brief, sustained exposure paradigm contrasting highly stressful, threatening, and violent stimuli versus nonaversive neutral visual stimuli in a functional magnetic resonance imaging (fMRI) study, we show significant subjective, physiologic, and endocrine increases and temporally related dynamically distinct patterns of neural activation in brain circuits underlying the stress response. First, stress-specific sustained increases in the amygdala, striatum, hypothalamus, midbrain, right insula, and right dorsolateral prefrontal cortex (DLPFC) regions supported the stress processing and reactivity circuit. Second, dynamic neural activation during stress versus neutral runs, showing early increases followed by later reduced activation in the ventrolateral prefrontal cortex (VLPFC), dorsal anterior cingulate cortex (dACC), left DLPFC, hippocampus, and left insula, suggested a stress adaptation response network. Finally, dynamic stress-specific mobilization of the ventromedial prefrontal cortex (VmPFC), marked by initial hypoactivity followed by increased VmPFC activation, pointed to the VmPFC as a key locus of the emotional and behavioral control network. Consistent with this finding, greater neural flexibility signals in the VmPFC during stress correlated with active coping ratings whereas lower dynamic activity in the VmPFC also predicted a higher level of maladaptive coping behaviors in real life, including binge alcohol intake, emotional eating, and frequency of arguments and fights. These findings demonstrate acute functional neuroplasticity during stress, with distinct and separable brain networks that underlie critical components of the stress response, and a specific role for VmPFC neuroflexibility in stress-resilient coping. PMID:27432990

Probing Compulsive and Impulsive Behaviors, from Animal Models to Endophenotypes: A Narrative Review

PubMed Central

Fineberg, Naomi A; Potenza, Marc N; Chamberlain, Samuel R; Berlin, Heather A; Menzies, Lara; Bechara, Antoine; Sahakian, Barbara J; Robbins, Trevor W; Bullmore, Edward T; Hollander, Eric

2010-01-01

Failures in cortical control of fronto-striatal neural circuits may underpin impulsive and compulsive acts. In this narrative review, we explore these behaviors from the perspective of neural processes and consider how these behaviors and neural processes contribute to mental disorders such as obsessive–compulsive disorder (OCD), obsessive–compulsive personality disorder, and impulse-control disorders such as trichotillomania and pathological gambling. We present findings from a broad range of data, comprising translational and human endophenotypes research and clinical treatment trials, focussing on the parallel, functionally segregated, cortico-striatal neural projections, from orbitofrontal cortex (OFC) to medial striatum (caudate nucleus), proposed to drive compulsive activity, and from the anterior cingulate/ventromedial prefrontal cortex to the ventral striatum (nucleus accumbens shell), proposed to drive impulsive activity, and the interaction between them. We suggest that impulsivity and compulsivity each seem to be multidimensional. Impulsive or compulsive behaviors are mediated by overlapping as well as distinct neural substrates. Trichotillomania may stand apart as a disorder of motor-impulse control, whereas pathological gambling involves abnormal ventral reward circuitry that identifies it more closely with substance addiction. OCD shows motor impulsivity and compulsivity, probably mediated through disruption of OFC-caudate circuitry, as well as other frontal, cingulate, and parietal connections. Serotonin and dopamine interact across these circuits to modulate aspects of both impulsive and compulsive responding and as yet unidentified brain-based systems may also have important functions. Targeted application of neurocognitive tasks, receptor-specific neurochemical probes, and brain systems neuroimaging techniques have potential for future research in this field. PMID:19940844

Neuron Stimulation Device Integrated with Silicon Nanowire-Based Photodetection Circuit on a Flexible Substrate.

PubMed

Jung, Suk Won; Shin, Jong Yoon; Pi, Kilwha; Goo, Yong Sook; Cho, Dong-Il Dan

2016-12-01

This paper proposes a neural stimulation device integrated with a silicon nanowire (SiNW)-based photodetection circuit for the activation of neurons with light. The proposed device is comprised of a voltage divider and a current driver in which SiNWs are used as photodetector and field-effect transistors; it has the functions of detecting light, generating a stimulation signal in proportion to the light intensity, and transmitting the signal to a micro electrode. To show the applicability of the proposed neural stimulation device as a high-resolution retinal prosthesis system, a high-density neural stimulation device with a unit cell size of 110 × 110 μ m and a resolution of 32 × 32 was fabricated on a flexible film with a thickness of approximately 50 μm. Its effectiveness as a retinal stimulation device was then evaluated using a unit cell in an in vitro animal experiment involving the retinal tissue of retinal Degeneration 1 ( rd1 ) mice. Experiments wherein stimulation pulses were applied to the retinal tissues successfully demonstrate that the number of spikes in neural response signals increases in proportion to light intensity.

CRHR1 genotypes, neural circuits and the diathesis for anxiety and depression.

PubMed

Rogers, J; Raveendran, M; Fawcett, G L; Fox, A S; Shelton, S E; Oler, J A; Cheverud, J; Muzny, D M; Gibbs, R A; Davidson, R J; Kalin, N H

2013-06-01

The corticotrophin-releasing hormone (CRH) system integrates the stress response and is associated with stress-related psychopathology. Previous reports have identified interactions between childhood trauma and sequence variation in the CRH receptor 1 gene (CRHR1) that increase risk for affective disorders. However, the underlying mechanisms that connect variation in CRHR1 to psychopathology are unknown. To explore potential mechanisms, we used a validated rhesus macaque model to investigate association between genetic variation in CRHR1, anxious temperament (AT) and brain metabolic activity. In young rhesus monkeys, AT is analogous to the childhood risk phenotype that predicts the development of human anxiety and depressive disorders. Regional brain metabolism was assessed with (18)F-labeled fluoro-2-deoxyglucose (FDG) positron emission tomography in 236 young, normally reared macaques that were also characterized for AT. We show that single nucleotide polymorphisms (SNPs) affecting exon 6 of CRHR1 influence both AT and metabolic activity in the anterior hippocampus and amygdala, components of the neural circuit underlying AT. We also find evidence for association between SNPs in CRHR1 and metabolism in the intraparietal sulcus and precuneus. These translational data suggest that genetic variation in CRHR1 affects the risk for affective disorders by influencing the function of the neural circuit underlying AT and that differences in gene expression or the protein sequence involving exon 6 may be important. These results suggest that variation in CRHR1 may influence brain function before any childhood adversity and may be a diathesis for the interaction between CRHR1 genotypes and childhood trauma reported to affect human psychopathology.

Navigating the Neural Space in Search of the Neural Code.

PubMed

Jazayeri, Mehrdad; Afraz, Arash

2017-03-08

The advent of powerful perturbation tools, such as optogenetics, has created new frontiers for probing causal dependencies in neural and behavioral states. These approaches have significantly enhanced the ability to characterize the contribution of different cells and circuits to neural function in health and disease. They have shifted the emphasis of research toward causal interrogations and increased the demand for more precise and powerful tools to control and manipulate neural activity. Here, we clarify the conditions under which measurements and perturbations support causal inferences. We note that the brain functions at multiple scales and that causal dependencies may be best inferred with perturbation tools that interface with the system at the appropriate scale. Finally, we develop a geometric framework to facilitate the interpretation of causal experiments when brain perturbations do or do not respect the intrinsic patterns of brain activity. We describe the challenges and opportunities of applying perturbations in the presence of dynamics, and we close with a general perspective on navigating the activity space of neurons in the search for neural codes. Copyright © 2017 Elsevier Inc. All rights reserved.

The Cerebellum and Neurodevelopmental Disorders.

PubMed

Stoodley, Catherine J

2016-02-01

Cerebellar dysfunction is evident in several developmental disorders, including autism, attention deficit-hyperactivity disorder (ADHD), and developmental dyslexia, and damage to the cerebellum early in development can have long-term effects on movement, cognition, and affective regulation. Early cerebellar damage is often associated with poorer outcomes than cerebellar damage in adulthood, suggesting that the cerebellum is particularly important during development. Differences in cerebellar development and/or early cerebellar damage could impact a wide range of behaviors via the closed-loop circuits connecting the cerebellum with multiple cerebral cortical regions. Based on these anatomical circuits, behavioral outcomes should depend on which cerebro-cerebellar circuits are affected. Here, we briefly review cerebellar structural and functional differences in autism, ADHD, and developmental dyslexia, and discuss clinical outcomes following pediatric cerebellar damage. These data confirm the prediction that abnormalities in different cerebellar subregions produce behavioral symptoms related to the functional disruption of specific cerebro-cerebellar circuits. These circuits might also be crucial to structural brain development, as peri-natal cerebellar lesions have been associated with impaired growth of the contralateral cerebral cortex. The specific contribution of the cerebellum to typical development may therefore involve the optimization of both the structure and function of cerebro-cerebellar circuits underlying skill acquisition in multiple domains; when this process is disrupted, particularly in early development, there could be long-term alterations of these neural circuits, with significant impacts on behavior.

The cerebellum and neurodevelopmental disorders

PubMed Central

Stoodley, Catherine J.

2015-01-01

Cerebellar dysfunction is evident in several developmental disorders, including autism, attention deficit hyperactivity disorder (ADHD), and developmental dyslexia, and damage to the cerebellum early in development can have long-term effects on movement, cognition, and affective regulation. Early cerebellar damage is often associated with poorer outcomes than cerebellar damage in adulthood, suggesting that the cerebellum is particularly important during development. Differences in cerebellar development and/or early cerebellar damage could impact a wide range of behaviors via the closed-loop circuits connecting the cerebellum with multiple cerebral cortical regions. Based on these anatomical circuits, behavioral outcomes should depend on which cerebro-cerebellar circuits are affected. Here, we briefly review cerebellar structural and functional differences in autism, ADHD, and developmental dyslexia, and discuss clinical outcomes following pediatric cerebellar damage. These data confirm the prediction that abnormalities in different cerebellar subregions produce behavioral symptoms related to the functional disruption of specific cerebro-cerebellar circuits. These circuits might also be crucial to structural brain development, as peri-natal cerebellar lesions have been associated with impaired growth of the contralateral cerebral cortex. The specific contribution of the cerebellum to typical development may therefore involve the optimization of both the structure and function of cerebro-cerebellar circuits underlying skill acquisition in multiple domains; when this process is disrupted, particularly in early development, there could be long-term alterations of these neural circuits, with significant impacts on behavior. PMID:26298473

Maternal Neural Responses to Infant Cries and Faces: Relationships with Substance Use

PubMed Central

Landi, Nicole; Montoya, Jessica; Kober, Hedy; Rutherford, Helena J. V.; Mencl, W. Einar; Worhunsky, Patrick D.; Potenza, Marc N.; Mayes, Linda C.

2011-01-01

Substance abuse in pregnant and recently post-partum women is a major public health concern because of effects on the infant and on the ability of the adult to care for the infant. In addition to the negative health effects of teratogenic substances on fetal development, substance use can contribute to difficulties associated with the social and behavioral aspects of parenting. Neural circuits associated with parenting behavior overlap with circuits involved in addiction (e.g., frontal, striatal, and limbic systems) and thus may be co-opted for the craving/reward cycle associated with substance use and abuse and be less available for parenting. The current study investigates the degree to which neural circuits associated with parenting are disrupted in mothers who are substance-using. Specifically, we used functional magnetic resonance imaging to examine the neural response to emotional infant cues (faces and cries) in substance-using compared to non-using mothers. In response to both faces (of varying emotional valence) and cries (of varying distress levels), substance-using mothers evidenced reduced neural activation in regions that have been previously implicated in reward and motivation as well as regions involved in cognitive control. Specifically, in response to faces, substance users showed reduced activation in prefrontal regions, including the dorsolateral and ventromedial prefrontal cortices, as well as visual processing (occipital lobes) and limbic regions (parahippocampus and amygdala). Similarly, in response to infant cries, substance-using mothers showed reduced activation relative to non-using mothers in prefrontal regions, auditory sensory processing regions, insula and limbic regions (parahippocampus and amygdala). These findings suggest that infant stimuli may be less salient for substance-using mothers, and such reduced saliency may impair developing infant-caregiver attachment and the ability of mothers to respond appropriately to their infants. PMID:21720537

Emerging roles of gut microbiota and the immune system in the development of the enteric nervous system

PubMed Central

Kabouridis, Panagiotis S.; Pachnis, Vassilis

2015-01-01

The enteric nervous system (ENS) consists of neurons and glial cells that differentiate from neural crest progenitors. During embryogenesis, development of the ENS is controlled by the interplay of neural crest cell–intrinsic factors and instructive cues from the surrounding gut mesenchyme. However, postnatal ENS development occurs in a different context, which is characterized by the presence of microbiota and an extensive immune system, suggesting an important role of these factors on enteric neural circuit formation and function. Initial reports confirm this idea while further studies in this area promise new insights into ENS physiology and pathophysiology. PMID:25729852

The relationship between stress and Alzheimer's disease.

PubMed

Justice, Nicholas J

2018-02-01

Stress is critically involved in the development and progression of disease. From the stress of undergoing treatments to facing your own mortality, the physiological processes that stress drives have a serious detrimental effect on the ability to heal, cope and maintain a positive quality of life. This is becoming increasingly clear in the case of neurodegenerative diseases. Neurodegenerative diseases involve the devastating loss of cognitive and motor function which is stressful in itself, but can also disrupt neural circuits that mediate stress responses. Disrupting these circuits produces aberrant emotional and aggressive behavior that causes long-term care to be especially difficult. In addition, added stress drives progression of the disease and can exacerbate symptoms. In this review, I describe how neural and endocrine pathways activated by stress interact with ongoing neurodegenerative disease from both a clinical and experimental perspective.

Fragile X Mental Retardation Protein Restricts Small Dye Iontophoresis Entry into Central Neurons.

PubMed

Kennedy, Tyler; Broadie, Kendal

2017-10-11

Fragile X mental retardation protein (FMRP) loss causes Fragile X syndrome (FXS), a major disorder characterized by autism, intellectual disability, hyperactivity, and seizures. FMRP is both an RNA- and channel-binding regulator, with critical roles in neural circuit formation and function. However, it remains unclear how these FMRP activities relate to each other and how dysfunction in their absence underlies FXS neurological symptoms. In testing circuit level defects in the Drosophila FXS model, we discovered a completely unexpected and highly robust neuronal dye iontophoresis phenotype in the well mapped giant fiber (GF) circuit. Controlled dye injection into the GF interneuron results in a dramatic increase in dye uptake in neurons lacking FMRP. Transgenic wild-type FMRP reintroduction rescues the mutant defect, demonstrating a specific FMRP requirement. This phenotype affects only small dyes, but is independent of dye charge polarity. Surprisingly, the elevated dye iontophoresis persists in shaking B mutants that eliminate gap junctions and dye coupling among GF circuit neurons. We therefore used a wide range of manipulations to investigate the dye uptake defect, including timed injection series, pharmacology and ion replacement, and optogenetic activity studies. The results show that FMRP strongly limits the rate of dye entry via a cytosolic mechanism. This study reveals an unexpected new phenotype in a physical property of central neurons lacking FMRP that could underlie aspects of FXS disruption of neural function. SIGNIFICANCE STATEMENT FXS is a leading heritable cause of intellectual disability and autism spectrum disorders. Although researchers established the causal link with FMRP loss >;25 years ago, studies continue to reveal diverse FMRP functions. The Drosophila FXS model is key to discovering new FMRP roles, because of its genetic malleability and individually identified neuron maps. Taking advantage of a well characterized Drosophila neural circuit, we discovered that neurons lacking FMRP take up dramatically more current-injected small dye. After examining many neuronal properties, we determined that this dye defect is cytoplasmic and occurs due to a highly elevated dye iontophoresis rate. We also report several new factors affecting neuron dye uptake. Understanding how FMRP regulates iontophoresis should reveal new molecular factors underpinning FXS dysfunction. Copyright © 2017 the authors 0270-6474/17/379844-15$15.00/0.

Optoelectronic Integrated Circuits For Neural Networks

NASA Technical Reports Server (NTRS)

Psaltis, D.; Katz, J.; Kim, Jae-Hoon; Lin, S. H.; Nouhi, A.

1990-01-01

Many threshold devices placed on single substrate. Integrated circuits containing optoelectronic threshold elements developed for use as planar arrays of artificial neurons in research on neural-network computers. Mounted with volume holograms recorded in photorefractive crystals serving as dense arrays of variable interconnections between neurons.

Role of neurotrophins in the development and function of neural circuits that regulate energy homeostasis.

PubMed

Fargali, Samira; Sadahiro, Masato; Jiang, Cheng; Frick, Amy L; Indall, Tricia; Cogliani, Valeria; Welagen, Jelle; Lin, Wei-Jye; Salton, Stephen R

2012-11-01

Members of the neurotrophin family, including nerve growth factor, brain-derived neurotrophic factor, neurotrophin-3, and neurotrophin-4/5, and other neurotrophic growth factors such as ciliary neurotrophic factor and artemin, regulate peripheral and central nervous system development and function. A subset of the neurotrophin-dependent pathways in the hypothalamus, brainstem, and spinal cord, and those that project via the sympathetic nervous system to peripheral metabolic tissues including brown and white adipose tissue, muscle and liver, regulate feeding, energy storage, and energy expenditure. We briefly review the role that neurotrophic growth factors play in energy balance, as regulators of neuronal survival and differentiation, neurogenesis, and circuit formation and function, and as inducers of critical gene products that control energy homeostasis.

REFLEX MODIFICATION: AN APPROACH TO INCORPORATE INTO A DEVELOPMENTAL NEUROTOXICITY (DNT) STUDY DESIGN WITH COMMERCIAL EQUIPMENT.

EPA Science Inventory

Reflex modification (RM) of the startle response is a very useful tool for testing sensory function and the integrity of a well-defined complement of neural circuits. Advantages of this procedure include the ability to rapidly acquire objective measurements and differentiate sen...

Temperature-Robust Neural Function from Activity-Dependent Ion Channel Regulation.

PubMed

O'Leary, Timothy; Marder, Eve

2016-11-07

Many species of cold-blooded animals experience substantial and rapid fluctuations in body temperature. Because biological processes are differentially temperature dependent, it is difficult to understand how physiological processes in such animals can be temperature robust [1-8]. Experiments have shown that core neural circuits, such as the pyloric circuit of the crab stomatogastric ganglion (STG), exhibit robust neural activity in spite of large (20°C) temperature fluctuations [3, 5, 7, 8]. This robustness is surprising because (1) each neuron has many different kinds of ion channels with different temperature dependencies (Q 10 s) that interact in a highly nonlinear way to produce firing patterns and (2) across animals there is substantial variability in conductance densities that nonetheless produce almost identical firing properties. The high variability in conductance densities in these neurons [9, 10] appears to contradict the possibility that robustness is achieved through precise tuning of key temperature-dependent processes. In this paper, we develop a theoretical explanation for how temperature robustness can emerge from a simple regulatory control mechanism that is compatible with highly variable conductance densities [11-13]. The resulting model suggests a general mechanism for how nervous systems and excitable tissues can exploit degenerate relationships among temperature-sensitive processes to achieve robust function. Copyright © 2016 Elsevier Ltd. All rights reserved.

Ephrin-B3 coordinates timed axon targeting and amygdala spinogenesis for innate fear behaviour

PubMed Central

Zhu, Xiao-Na; Liu, Xian-Dong; Sun, Suya; Zhuang, Hanyi; Yang, Jing-Yu; Henkemeyer, Mark; Xu, Nan-Jie

2016-01-01

Innate emotion response to environmental stimuli is a fundamental brain function that is controlled by specific neural circuits. Dysfunction of early emotional circuits may lead to neurodevelopmental disorders such as autism and schizophrenia. However, how the functional circuits are formed to prime initial emotional behaviours remain elusive. We reveal here using gene-targeted mutations an essential role for ephrin-B3 ligand-like activity in the development of innate fear in the neonatal brain. We further demonstrate that ephrin-B3 controls axon targeting and coordinates spinogenesis and neuronal activity within the amygdala. The morphological and behavioural abnormalities in ephrin-B3 mutant mice are rescued by conditional knock-in of wild-type ephrin-B3 during the critical period when axon targeting and fear responses are initiated. Our results thus define a key axonal molecule that participates in the wiring of amygdala circuits and helps bring about fear emotion during the important adolescence period. PMID:27008987

Ephrin-B3 coordinates timed axon targeting and amygdala spinogenesis for innate fear behaviour.

PubMed

Zhu, Xiao-Na; Liu, Xian-Dong; Sun, Suya; Zhuang, Hanyi; Yang, Jing-Yu; Henkemeyer, Mark; Xu, Nan-Jie

2016-03-24

Innate emotion response to environmental stimuli is a fundamental brain function that is controlled by specific neural circuits. Dysfunction of early emotional circuits may lead to neurodevelopmental disorders such as autism and schizophrenia. However, how the functional circuits are formed to prime initial emotional behaviours remain elusive. We reveal here using gene-targeted mutations an essential role for ephrin-B3 ligand-like activity in the development of innate fear in the neonatal brain. We further demonstrate that ephrin-B3 controls axon targeting and coordinates spinogenesis and neuronal activity within the amygdala. The morphological and behavioural abnormalities in ephrin-B3 mutant mice are rescued by conditional knock-in of wild-type ephrin-B3 during the critical period when axon targeting and fear responses are initiated. Our results thus define a key axonal molecule that participates in the wiring of amygdala circuits and helps bring about fear emotion during the important adolescence period.

Emotion and the motivational brain

PubMed Central

Lang, Peter J.; Bradley, Margaret M.

2013-01-01

Psychophysiological and neuroscience studies of emotional processing undertaken by investigators at the University of Florida Laboratory of the Center for the Study of Emotion and Attention (CSEA) are reviewed, with a focus on reflex reactions, neural structures and functional circuits that mediate emotional expression. The theoretical view shared among the investigators is that expressed emotions are founded on motivational circuits in the brain that developed early in evolutionary history to ensure the survival of individuals and their progeny. These circuits react to appetitive and aversive environmental and memorial cues, mediating appetitive and defensive reflexes that tune sensory systems and mobilize the organism for action and underly negative and positive affects. The research reviewed here assesses the reflex physiology of emotion, both autonomic and somatic, studying affects evoked in picture perception, memory imagery, and in the context of tangible reward and punishment, and using the electroencephalograph (EEG) and functional magnetic resonance imaging (fMRI), explores the brain’s motivational circuits that determine human emotion. PMID:19879918

High level cognitive information processing in neural networks

NASA Technical Reports Server (NTRS)

Barnden, John A.; Fields, Christopher A.

1992-01-01

Two related research efforts were addressed: (1) high-level connectionist cognitive modeling; and (2) local neural circuit modeling. The goals of the first effort were to develop connectionist models of high-level cognitive processes such as problem solving or natural language understanding, and to understand the computational requirements of such models. The goals of the second effort were to develop biologically-realistic model of local neural circuits, and to understand the computational behavior of such models. In keeping with the nature of NASA's Innovative Research Program, all the work conducted under the grant was highly innovative. For instance, the following ideas, all summarized, are contributions to the study of connectionist/neural networks: (1) the temporal-winner-take-all, relative-position encoding, and pattern-similarity association techniques; (2) the importation of logical combinators into connection; (3) the use of analogy-based reasoning as a bridge across the gap between the traditional symbolic paradigm and the connectionist paradigm; and (4) the application of connectionism to the domain of belief representation/reasoning. The work on local neural circuit modeling also departs significantly from the work of related researchers. In particular, its concentration on low-level neural phenomena that could support high-level cognitive processing is unusual within the area of biological local circuit modeling, and also serves to expand the horizons of the artificial neural net field.

Aberrant functional connectivity in Papez circuit correlates with memory performance in cognitively intact middle-aged APOE4 carriers.

PubMed

Li, Wenjun; Antuono, Piero G; Xie, Chunming; Chen, Gang; Jones, Jennifer L; Ward, B Douglas; Singh, Suraj P; Franczak, Malgorzata B; Goveas, Joseph S; Li, Shi-Jiang

2014-08-01

The main objective of this study is to detect the early changes in resting-state Papez circuit functional connectivity using the hippocampus as the seed, and to determine the associations between altered functional connectivity (FC) and the episodic memory performance in cognitively intact middle-aged apolipoprotein E4 (APOE4) carriers who are at risk of Alzheimer's disease (AD). Forty-six cognitively intact, middle-aged participants, including 20 APOE4 carriers and 26 age-, sex-, and education-matched noncarriers were studied. The resting-state FC of the hippocampus (HFC) was compared between APOE4 carriers and noncarriers. APOE4 carriers showed significantly decreased FC in brain areas that involve learning and memory functions, including the frontal, cingulate, thalamus and basal ganglia regions. Multiple linear regression analysis showed significant correlations between HFC and the episodic memory performance. Conjunction analysis between neural correlates of memory and altered HFC showed the overlapping regions, especially the subcortical regions such as thalamus, caudate nucleus, and cingulate cortices involved in the Papez circuit. Thus, changes in connectivity in the Papez circuit may be used as an early risk detection for AD. Copyright © 2014. Published by Elsevier Ltd.

Postnatal Developmental Trajectories of Neural Circuits in the Primate Prefrontal Cortex: Identifying Sensitive Periods for Vulnerability to Schizophrenia

PubMed Central

Hoftman, Gil D.; Lewis, David A.

2011-01-01

Schizophrenia is a disorder of cognitive neurodevelopment with characteristic abnormalities in working memory attributed, at least in part, to alterations in the circuitry of the dorsolateral prefrontal cortex. Various environmental exposures from conception through adolescence increase risk for the illness, possibly by altering the developmental trajectories of prefrontal cortical circuits. Macaque monkeys provide an excellent model system for studying the maturation of prefrontal cortical circuits. Here, we review the development of glutamatergic and γ-aminobutyric acid (GABA)-ergic circuits in macaque monkey prefrontal cortex and discuss how these trajectories may help to identify sensitive periods during which environmental exposures, such as those associated with increased risk for schizophrenia, might lead to the types of abnormalities in prefrontal cortical function present in schizophrenia. PMID:21505116

The computational worm: spatial orientation and its neuronal basis in C. elegans.

PubMed

Lockery, Shawn R

2011-10-01

Spatial orientation behaviors in animals are fundamental for survival but poorly understood at the neuronal level. The nematode Caenorhabditis elegans orients to a wide range of stimuli and has a numerically small and well-described nervous system making it advantageous for investigating the mechanisms of spatial orientation. Recent work by the C. elegans research community has identified essential computational elements of the neural circuits underlying two orientation strategies that operate in five different sensory modalities. Analysis of these circuits reveals novel motifs including simple circuits for computing temporal derivatives of sensory input and for integrating sensory input with behavioral state to generate adaptive behavior. These motifs constitute hypotheses concerning the identity and functionality of circuits controlling spatial orientation in higher organisms. Copyright © 2011 Elsevier Ltd. All rights reserved.

Frequency-specific alterations in functional connectivity in treatment-resistant and -sensitive major depressive disorder.

PubMed

He, Zongling; Cui, Qian; Zheng, Junjie; Duan, Xujun; Pang, Yajing; Gao, Qing; Han, Shaoqiang; Long, Zhiliang; Wang, Yifeng; Li, Jiao; Wang, Xiao; Zhao, Jingping; Chen, Huafu

2016-11-01

Major depressive disorder (MDD) may involve alterations in brain functional connectivity in multiple neural circuits and present large-scale network dysfunction. Patients with treatment-resistant depression (TRD) and treatment-sensitive depression (TSD) show different responses to antidepressants and aberrant brain functions. This study aims to investigate functional connectivity patterns of TRD and TSD at the whole brain resting state. Seventeen patients with TRD, 17 patients with TSD, and 17 healthy controls matched with age, gender, and years of education were recruited in this study. The brain was divided using an automated anatomical labeling atlas into 90 regions of interest, which were used to construct the entire brain functional networks. An analysis method called network-based statistic was used to explore the dysconnected subnetworks of TRD and TSD at different frequency bands. At resting state, TSD and TRD present characteristic patterns of network dysfunction at special frequency bands. The dysconnected subnetwork of TSD mainly lies in the fronto-parietal top-down control network. Moreover, the abnormal neural circuits of TRD are extensive and complex. These circuits not only depend on the abnormal affective network but also involve other networks, including salience network, auditory network, visual network, and language processing cortex. Our findings reflect that the pathological mechanism of TSD may refer to impairment in cognitive control, whereas TRD mainly triggers the dysfunction of emotion processing and affective cognition. This study reveals that differences in brain functional connectivity at resting state reflect distinct pathophysiological mechanisms in TSD and TRD. These findings may be helpful in differentiating two types of MDD and predicting treatment responses. Copyright © 2016 Elsevier Ltd. All rights reserved.

Alcohol Dose Effects on Brain Circuits During Simulated Driving: An fMRI Study

PubMed Central

Meda, Shashwath A.; Calhoun, Vince D.; Astur, Robert S.; Turner, Beth M.; Ruopp, Kathryn; Pearlson, Godfrey D.

2009-01-01

Driving while intoxicated remains a major public health hazard. Driving is a complex task involving simultaneous recruitment of multiple cognitive functions. The investigators studied the neural substrates of driving and their response to different blood alcohol concentrations (BACs), using functional magnetic resonance imaging (fMRI) and a virtual reality driving simulator. We used independent component analysis (ICA) to isolate spatially independent and temporally correlated driving-related brain circuits in 40 healthy, adult moderate social drinkers. Each subject received three individualized, separate single-blind doses of beverage alcohol to produce BACs of 0.05% (moderate), 0.10% (high), or 0% (placebo). 3 T fMRI scanning and continuous behavioral measurement occurred during simulated driving. Brain function was assessed and compared using both ICA and a conventional general linear model (GLM) analysis. ICA results replicated and significantly extended our previous 1.5T study (Calhoun et al. [2004a]: Neuropsychopharmacology 29:2097–2017). GLM analysis revealed significant dose-related functional differences, complementing ICA data. Driving behaviors including opposite white line crossings and mean speed independently demonstrated significant dose-dependent changes. Behavior-based factors also predicted a frontal-basal-temporal circuit to be functionally impaired with alcohol dosage across baseline scaled, good versus poorly performing drivers. We report neural correlates of driving behavior and found dose-related spatio-temporal disruptions in critical driving-associated regions including the superior, middle and orbito frontal gyri, anterior cingulate, primary/supplementary motor areas, basal ganglia, and cerebellum. Overall, results suggest that alcohol (especially at high doses) causes significant impairment of both driving behavior and brain functionality related to motor planning and control, goal directedness, error monitoring, and memory. PMID:18571794

Sex differences in olfactory-induced neural activation of the amygdala.

PubMed

Kikusui, Takefumi; Kajita, Mayu; Otsuka, Natsumi; Hattori, Tatsuya; Kumazawa, Kanako; Watarai, Akiyuki; Nagasawa, Miho; Inutsuka, Ayumu; Yamanaka, Akihiro; Matsuo, Naoki; Covington, Herbert E; Mogi, Kazutaka

2018-07-02

Olfactory signals, including the scent of urine, are thought to be processed by specific brain regions, such as the medial amygdala (Me), and regulate sexual behavior in a sex-dependent manner. We aimed to reveal the sex-specific neural circuit from the accessory olfactory bulb (AOB) to Me by using a transgenic mouse. We quantified the long-lasting green fluorescent protein (GFP) expression profile, which was controlled by the c-fos promotor in a sex-dependent manner by the scent of urine. Female urine predominantly activated neurons of the posterodorsal medial amygdala (MePD) in male mice and the posteroventral medial amygdala (MePV) in female mice. Male urine, in contrast, generated the opposite pattern of activation in the Me. Secondary, the selective artificial activation of these circuits was used to examine their specific behavioral function, by using a dual Cre-loxP viral infection. AAV-hSyn-FLEX-hM3Dq-EGFP-the designer receptor exclusively activated by a designer drug-was infused into the AOB after infection with trans-synaptic AAV(DJ)-CMV-mCherry-2A-Cre-TTC into either the MePD or the MePV. Double virus-transfected mice were injected with hM 3 Dq activator and their sexual behavior was monitored. However, selective activation of sex-dependent circuits, i.e., the AOB-MePD or AOB-MePV, did not significantly alter mounting or attack behavior in male mice. There were clear sex differences in the pheromone conveying circuits in the AOB-Me of mice. The sex-dependent functional activation of the Me, however, no effect on behavior. This suggests that a diverse number of nuclei and brain areas are likely to function in concert to successfully facilitate sexual and aggressive behaviors. Copyright © 2017 Elsevier B.V. All rights reserved.

Mechanisms to medicines: elucidating neural and molecular substrates of fear extinction to identify novel treatments for anxiety disorders.

PubMed

Bukalo, Olena; Pinard, Courtney R; Holmes, Andrew

2014-10-01

The burden of anxiety disorders is growing, but the efficacy of available anxiolytic treatments remains inadequate. Cognitive behavioural therapy for anxiety disorders focuses on identifying and modifying maladaptive patterns of thinking and behaving, and has a testable analogue in rodents in the form of fear extinction. A large preclinical literature has amassed in recent years describing the neural and molecular basis of fear extinction in rodents. In this review, we discuss how this work is being harnessed to foster translational research on anxiety disorders and facilitate the search for new anxiolytic treatments. We begin by summarizing the anatomical and functional connectivity of a medial prefrontal cortex (mPFC)-amygdala circuit that subserves fear extinction, including new insights from optogenetics. We then cover some of the approaches that have been taken to model impaired fear extinction and associated impairments with mPFC-amygdala dysfunction. The principal goal of the review is to evaluate evidence that various neurotransmitter and neuromodulator systems mediate fear extinction by modulating the mPFC-amygdala circuitry. To that end, we describe studies that have tested how fear extinction is impaired or facilitated by pharmacological manipulations of dopamine, noradrenaline, 5-HT, GABA, glutamate, neuropeptides, endocannabinoids and various other systems, which either directly target the mPFC-amygdala circuit, or produce behavioural effects that are coincident with functional changes in the circuit. We conclude that there are good grounds to be optimistic that the progress in defining the molecular substrates of mPFC-amygdala circuit function can be effectively leveraged to identify plausible candidates for extinction-promoting therapies for anxiety disorders. © 2014 The British Pharmacological Society.

Neuroestrogen signaling in the songbird auditory cortex propagates into a sensorimotor network via an `interface' nucleus

PubMed Central

Pawlisch, Benjamin A.; Remage-Healey, Luke

2014-01-01

Neuromodulators rapidly alter activity of neural circuits and can therefore shape higher-order functions, such as sensorimotor integration. Increasing evidence suggests that brain-derived estrogens, such as 17-β-estradiol, can act rapidly to modulate sensory processing. However, less is known about how rapid estrogen signaling can impact downstream circuits. Past studies have demonstrated that estradiol levels increase within the songbird auditory cortex (the caudomedial nidopallium, NCM) during social interactions. Local estradiol signaling enhances the auditory-evoked firing rate of neurons in NCM to a variety of stimuli, while also enhancing the selectivity of auditory-evoked responses of neurons in a downstream sensorimotor brain region, HVC (proper name). Since these two brain regions are not directly connected, we employed dual extracellular recordings in HVC and the upstream nucleus interfacialis of the nidopallium (NIf) during manipulations of estradiol within NCM to better understand the pathway by which estradiol signaling propagates to downstream circuits. NIf has direct input into HVC, passing auditory information into the vocal motor output pathway, and is a possible source of the neural selectivity within HVC. Here, during acute estradiol administration in NCM, NIf neurons showed increases in baseline firing rates and auditory-evoked firing rates to all stimuli. Furthermore, when estradiol synthesis was blocked in NCM, we observed simultaneous decreases in the selectivity of NIf and HVC neurons. These effects were not due to direct estradiol actions because NIf has little to no capability for local estrogen synthesis or estrogen receptors, and these effects were specific to NIf because other neurons immediately surrounding NIf did not show these changes. Our results demonstrate that transsynaptic, rapid fluctuations in neuroestrogens are transmitted into NIf and subsequently HVC, both regions important for sensorimotor integration. Overall, these findings support the hypothesis that acute neurosteroid actions can propagate within and between neural circuits to modulate their functional connectivity. PMID:25453773

Neuroestrogen signaling in the songbird auditory cortex propagates into a sensorimotor network via an 'interface' nucleus.

PubMed

Pawlisch, B A; Remage-Healey, L

2015-01-22

Neuromodulators rapidly alter activity of neural circuits and can therefore shape higher order functions, such as sensorimotor integration. Increasing evidence suggests that brain-derived estrogens, such as 17-β-estradiol, can act rapidly to modulate sensory processing. However, less is known about how rapid estrogen signaling can impact downstream circuits. Past studies have demonstrated that estradiol levels increase within the songbird auditory cortex (the caudomedial nidopallium, NCM) during social interactions. Local estradiol signaling enhances the auditory-evoked firing rate of neurons in NCM to a variety of stimuli, while also enhancing the selectivity of auditory-evoked responses of neurons in a downstream sensorimotor brain region, HVC (proper name). Since these two brain regions are not directly connected, we employed dual extracellular recordings in HVC and the upstream nucleus interfacialis of the nidopallium (NIf) during manipulations of estradiol within NCM to better understand the pathway by which estradiol signaling propagates to downstream circuits. NIf has direct input into HVC, passing auditory information into the vocal motor output pathway, and is a possible source of the neural selectivity within HVC. Here, during acute estradiol administration in NCM, NIf neurons showed increases in baseline firing rates and auditory-evoked firing rates to all stimuli. Furthermore, when estradiol synthesis was blocked in NCM, we observed simultaneous decreases in the selectivity of NIf and HVC neurons. These effects were not due to direct estradiol actions because NIf has little to no capability for local estrogen synthesis or estrogen receptors, and these effects were specific to NIf because other neurons immediately surrounding NIf did not show these changes. Our results demonstrate that transsynaptic, rapid fluctuations in neuroestrogens are transmitted into NIf and subsequently HVC, both regions important for sensorimotor integration. Overall, these findings support the hypothesis that acute neurosteroid actions can propagate within and between neural circuits to modulate their functional connectivity. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

Goal-Directed Decision Making with Spiking Neurons.

PubMed

Friedrich, Johannes; Lengyel, Máté

2016-02-03

Behavioral and neuroscientific data on reward-based decision making point to a fundamental distinction between habitual and goal-directed action selection. The formation of habits, which requires simple updating of cached values, has been studied in great detail, and the reward prediction error theory of dopamine function has enjoyed prominent success in accounting for its neural bases. In contrast, the neural circuit mechanisms of goal-directed decision making, requiring extended iterative computations to estimate values online, are still unknown. Here we present a spiking neural network that provably solves the difficult online value estimation problem underlying goal-directed decision making in a near-optimal way and reproduces behavioral as well as neurophysiological experimental data on tasks ranging from simple binary choice to sequential decision making. Our model uses local plasticity rules to learn the synaptic weights of a simple neural network to achieve optimal performance and solves one-step decision-making tasks, commonly considered in neuroeconomics, as well as more challenging sequential decision-making tasks within 1 s. These decision times, and their parametric dependence on task parameters, as well as the final choice probabilities match behavioral data, whereas the evolution of neural activities in the network closely mimics neural responses recorded in frontal cortices during the execution of such tasks. Our theory provides a principled framework to understand the neural underpinning of goal-directed decision making and makes novel predictions for sequential decision-making tasks with multiple rewards. Goal-directed actions requiring prospective planning pervade decision making, but their circuit-level mechanisms remain elusive. We show how a model circuit of biologically realistic spiking neurons can solve this computationally challenging problem in a novel way. The synaptic weights of our network can be learned using local plasticity rules such that its dynamics devise a near-optimal plan of action. By systematically comparing our model results to experimental data, we show that it reproduces behavioral decision times and choice probabilities as well as neural responses in a rich set of tasks. Our results thus offer the first biologically realistic account for complex goal-directed decision making at a computational, algorithmic, and implementational level. Copyright © 2016 the authors 0270-6474/16/361529-18$15.00/0.

Goal-Directed Decision Making with Spiking Neurons

PubMed Central

Lengyel, Máté

2016-01-01

Behavioral and neuroscientific data on reward-based decision making point to a fundamental distinction between habitual and goal-directed action selection. The formation of habits, which requires simple updating of cached values, has been studied in great detail, and the reward prediction error theory of dopamine function has enjoyed prominent success in accounting for its neural bases. In contrast, the neural circuit mechanisms of goal-directed decision making, requiring extended iterative computations to estimate values online, are still unknown. Here we present a spiking neural network that provably solves the difficult online value estimation problem underlying goal-directed decision making in a near-optimal way and reproduces behavioral as well as neurophysiological experimental data on tasks ranging from simple binary choice to sequential decision making. Our model uses local plasticity rules to learn the synaptic weights of a simple neural network to achieve optimal performance and solves one-step decision-making tasks, commonly considered in neuroeconomics, as well as more challenging sequential decision-making tasks within 1 s. These decision times, and their parametric dependence on task parameters, as well as the final choice probabilities match behavioral data, whereas the evolution of neural activities in the network closely mimics neural responses recorded in frontal cortices during the execution of such tasks. Our theory provides a principled framework to understand the neural underpinning of goal-directed decision making and makes novel predictions for sequential decision-making tasks with multiple rewards. SIGNIFICANCE STATEMENT Goal-directed actions requiring prospective planning pervade decision making, but their circuit-level mechanisms remain elusive. We show how a model circuit of biologically realistic spiking neurons can solve this computationally challenging problem in a novel way. The synaptic weights of our network can be learned using local plasticity rules such that its dynamics devise a near-optimal plan of action. By systematically comparing our model results to experimental data, we show that it reproduces behavioral decision times and choice probabilities as well as neural responses in a rich set of tasks. Our results thus offer the first biologically realistic account for complex goal-directed decision making at a computational, algorithmic, and implementational level. PMID:26843636

Characterization of the central neural projections to brown, white, and beige adipose tissue.

PubMed

Wiedmann, Nicole M; Stefanidis, Aneta; Oldfield, Brian J

2017-11-01

The functional recruitment of classic brown adipose tissue (BAT) and inducible brown-like or beige fat is, to a large extent, dependent on intact sympathetic neural input. Whereas the central neural circuits directed specifically to BAT or white adipose tissue (WAT) are well established, there is only a developing insight into the nature of neural inputs common to both fat types. Moreover, there is no clear view of the specific central and peripheral innervation of the browned component of WAT: beige fat. The objective of the present study is to examine the neural input to both BAT and WAT in the same animal and, by exposing different cohorts of rats to either thermoneutral or cold conditions, define changes in central neural organization that will ensure that beige fat is appropriately recruited and modulated after browning of inguinal WAT (iWAT). At thermoneutrality, injection of the neurotropic (pseudorabies) viruses into BAT and WAT demonstrates that there are dedicated axonal projections, as well as collateral axonal branches of command neurons projecting to both types of fat. After cold exposure, central neural circuits directed to iWAT showed evidence of reorganization with a greater representation of command neurons projecting to both brown and beiged WAT in hypothalamic (paraventricular nucleus and lateral hypothalamus) and brainstem (raphe pallidus and locus coeruleus) sites. This shift was driven by a greater number of supraspinal neurons projecting to iWAT under cold conditions. These data provide evidence for a reorganization of the nervous system at the level of neural connectivity following browning of WAT.-Wiedmann, N. M., Stefanidis, A., Oldfield, B. J. Characterization of the central neural projections to brown, white, and beige adipose tissue. © FASEB.

The C. elegans Connectome Consists of Homogenous Circuits with Defined Functional Roles

PubMed Central

Azulay, Aharon; Zaslaver, Alon

2016-01-01

A major goal of systems neuroscience is to decipher the structure-function relationship in neural networks. Here we study network functionality in light of the common-neighbor-rule (CNR) in which a pair of neurons is more likely to be connected the more common neighbors it shares. Focusing on the fully-mapped neural network of C. elegans worms, we establish that the CNR is an emerging property in this connectome. Moreover, sets of common neighbors form homogenous structures that appear in defined layers of the network. Simulations of signal propagation reveal their potential functional roles: signal amplification and short-term memory at the sensory/inter-neuron layer, and synchronized activity at the motoneuron layer supporting coordinated movement. A coarse-grained view of the neural network based on homogenous connected sets alone reveals a simple modular network architecture that is intuitive to understand. These findings provide a novel framework for analyzing larger, more complex, connectomes once these become available. PMID:27606684

GABA Neuron Alterations, Cortical Circuit Dysfunction and Cognitive Deficits in Schizophrenia

PubMed Central

Gonzalez-Burgos, Guillermo; Fish, Kenneth N.; Lewis, David A.

2011-01-01

Schizophrenia is a brain disorder associated with cognitive deficits that severely affect the patients' capacity for daily functioning. Whereas our understanding of its pathophysiology is limited, postmortem studies suggest that schizophrenia is associated with deficits of GABA-mediated synaptic transmission. A major role of GABA-mediated transmission may be producing synchronized network oscillations which are currently hypothesized to be essential for normal cognitive function. Therefore, cognitive deficits in schizophrenia may result from a GABA synapse dysfunction that disturbs neural synchrony. Here, we highlight recent studies further suggesting alterations of GABA transmission and network oscillations in schizophrenia. We also review current models for the mechanisms of GABA-mediated synchronization of neural activity, focusing on parvalbumin-positive GABA neurons, which are altered in schizophrenia and whose function has been strongly linked to the production of neural synchrony. Alterations of GABA signaling that impair gamma oscillations and, as a result, cognitive function suggest paths for novel therapeutic interventions. PMID:21904685

Synaptic behaviors of a single metal-oxide-metal resistive device

NASA Astrophysics Data System (ADS)

Choi, Sang-Jun; Kim, Guk-Bae; Lee, Kyoobin; Kim, Ki-Hong; Yang, Woo-Young; Cho, Soohaeng; Bae, Hyung-Jin; Seo, Dong-Seok; Kim, Sang-Il; Lee, Kyung-Jin

2011-03-01

The mammalian brain is far superior to today's electronic circuits in intelligence and efficiency. Its functions are realized by the network of neurons connected via synapses. Much effort has been extended in finding satisfactory electronic neural networks that act like brains, i.e., especially the electronic version of synapse that is capable of the weight control and is independent of the external data storage. We demonstrate experimentally that a single metal-oxide-metal structure successfully stores the biological synaptic weight variations (synaptic plasticity) without any external storage node or circuit. Our device also demonstrates the reliability of plasticity experimentally with the model considering the time dependence of spikes. All these properties are embodied by the change of resistance level corresponding to the history of injected voltage-pulse signals. Moreover, we prove the capability of second-order learning of the multi-resistive device by applying it to the circuit composed of transistors. We anticipate our demonstration will invigorate the study of electronic neural networks using non-volatile multi-resistive device, which is simpler and superior compared to other storage devices.

Neuromimetic Circuits with Synaptic Devices Based on Strongly Correlated Electron Systems

NASA Astrophysics Data System (ADS)

Ha, Sieu D.; Shi, Jian; Meroz, Yasmine; Mahadevan, L.; Ramanathan, Shriram

2014-12-01

Strongly correlated electron systems such as the rare-earth nickelates (R NiO3 , R denotes a rare-earth element) can exhibit synapselike continuous long-term potentiation and depression when gated with ionic liquids; exploiting the extreme sensitivity of coupled charge, spin, orbital, and lattice degrees of freedom to stoichiometry. We present experimental real-time, device-level classical conditioning and unlearning using nickelate-based synaptic devices in an electronic circuit compatible with both excitatory and inhibitory neurons. We establish a physical model for the device behavior based on electric-field-driven coupled ionic-electronic diffusion that can be utilized for design of more complex systems. We use the model to simulate a variety of associate and nonassociative learning mechanisms, as well as a feedforward recurrent network for storing memory. Our circuit intuitively parallels biological neural architectures, and it can be readily generalized to other forms of cellular learning and extinction. The simulation of neural function with electronic device analogs may provide insight into biological processes such as decision making, learning, and adaptation, while facilitating advanced parallel information processing in hardware.

GRAPES-Grounding representations in action, perception, and emotion systems: How object properties and categories are represented in the human brain.

PubMed

Martin, Alex

2016-08-01

In this article, I discuss some of the latest functional neuroimaging findings on the organization of object concepts in the human brain. I argue that these data provide strong support for viewing concepts as the products of highly interactive neural circuits grounded in the action, perception, and emotion systems. The nodes of these circuits are defined by regions representing specific object properties (e.g., form, color, and motion) and thus are property-specific, rather than strictly modality-specific. How these circuits are modified by external and internal environmental demands, the distinction between representational content and format, and the grounding of abstract social concepts are also discussed.

Neural circuitry coordinating male copulation

PubMed Central

Pavlou, Hania J; Lin, Andrew C; Neville, Megan C; Nojima, Tetsuya; Diao, Fengqiu; Chen, Brian E; White, Benjamin H; Goodwin, Stephen F

2016-01-01

Copulation is the goal of the courtship process, crucial to reproductive success and evolutionary fitness. Identifying the circuitry underlying copulation is a necessary step towards understanding universal principles of circuit operation, and how circuit elements are recruited into the production of ordered action sequences. Here, we identify key sex-specific neurons that mediate copulation in Drosophila, and define a sexually dimorphic motor circuit in the male abdominal ganglion that mediates the action sequence of initiating and terminating copulation. This sexually dimorphic circuit composed of three neuronal classes – motor neurons, interneurons and mechanosensory neurons – controls the mechanics of copulation. By correlating the connectivity, function and activity of these neurons we have determined the logic for how this circuitry is coordinated to generate this male-specific behavior, and sets the stage for a circuit-level dissection of active sensing and modulation of copulatory behavior. DOI: http://dx.doi.org/10.7554/eLife.20713.001 PMID:27855059

A neural command circuit for grooming movement control.

PubMed

Hampel, Stefanie; Franconville, Romain; Simpson, Julie H; Seeds, Andrew M

2015-09-07

Animals perform many stereotyped movements, but how nervous systems are organized for controlling specific movements remains unclear. Here we use anatomical, optogenetic, behavioral, and physiological techniques to identify a circuit in Drosophila melanogaster that can elicit stereotyped leg movements that groom the antennae. Mechanosensory chordotonal neurons detect displacements of the antennae and excite three different classes of functionally connected interneurons, which include two classes of brain interneurons and different parallel descending neurons. This multilayered circuit is organized such that neurons within each layer are sufficient to specifically elicit antennal grooming. However, we find differences in the durations of antennal grooming elicited by neurons in the different layers, suggesting that the circuit is organized to both command antennal grooming and control its duration. As similar features underlie stimulus-induced movements in other animals, we infer the possibility of a common circuit organization for movement control that can be dissected in Drosophila.

Developmental metaplasticity in neural circuit codes of firing and structure.

PubMed

Baram, Yoram

2017-01-01

Firing-rate dynamics have been hypothesized to mediate inter-neural information transfer in the brain. While the Hebbian paradigm, relating learning and memory to firing activity, has put synaptic efficacy variation at the center of cortical plasticity, we suggest that the external expression of plasticity by changes in the firing-rate dynamics represents a more general notion of plasticity. Hypothesizing that time constants of plasticity and firing dynamics increase with age, and employing the filtering property of the neuron, we obtain the elementary code of global attractors associated with the firing-rate dynamics in each developmental stage. We define a neural circuit connectivity code as an indivisible set of circuit structures generated by membrane and synapse activation and silencing. Synchronous firing patterns under parameter uniformity, and asynchronous circuit firing are shown to be driven, respectively, by membrane and synapse silencing and reactivation, and maintained by the neuronal filtering property. Analytic, graphical and simulation representation of the discrete iteration maps and of the global attractor codes of neural firing rate are found to be consistent with previous empirical neurobiological findings, which have lacked, however, a specific correspondence between firing modes, time constants, circuit connectivity and cortical developmental stages. Copyright © 2016 Elsevier Ltd. All rights reserved.

Analog Delta-Back-Propagation Neural-Network Circuitry

NASA Technical Reports Server (NTRS)

Eberhart, Silvio

1990-01-01

Changes in synapse weights due to circuit drifts suppressed. Proposed fully parallel analog version of electronic neural-network processor based on delta-back-propagation algorithm. Processor able to "learn" when provided with suitable combinations of inputs and enforced outputs. Includes programmable resistive memory elements (corresponding to synapses), conductances (synapse weights) adjusted during learning. Buffer amplifiers, summing circuits, and sample-and-hold circuits arranged in layers of electronic neurons in accordance with delta-back-propagation algorithm.

Central genes, pathways and modules that regulate bone mass.

PubMed

Quiros-Gonzalez, Isabel; Yadav, Vijay K

2014-11-01

Bones are structures that give the shape and defined features to vertebrates, protect several soft organs and perform multiple endocrine influences on other organs. To achieve these functions bones are first modeled early during life and then constantly remodeled throughout life. The process of bone (re)modeling happens simultaneously at multitude of locations in the skeleton and ensures that vertebrates have a mechanically strong yet a flexible skeleton to the most part of their life. Given the extent of its occurrence in the body, bone remodeling is a highly energy demanding process and is co-ordinated with other physiological processes as diverse as energy metabolism, sleep-wake cycle and reproduction. Neuronal circuits in the brain play a very important role in the coordination of bone remodeling with other organ system functions, and perform this function in sync with environmental and peripheral hormonal cues. In this review, we will focus on the roles of hormonal signals and neural circuits that originate in, or impinge on, the brain in the regulation of bone mass. We will provide herein an updated view of how advances in molecular genetics have refined the neural circuits involved in the regulation of bone mass, from the whole brain level to the specific neuronal populations and their neurotransmitters. This will help to understand the mechanisms whereby vertebrate brain regulates bone mass by fine-tuning metabolic signals that originate in the brain or elsewhere in the body. Copyright © 2014 Elsevier Inc. All rights reserved.

Neural circuits underlying mother’s voice perception predict social communication abilities in children

PubMed Central

Abrams, Daniel A.; Chen, Tianwen; Odriozola, Paola; Cheng, Katherine M.; Baker, Amanda E.; Padmanabhan, Aarthi; Ryali, Srikanth; Kochalka, John; Feinstein, Carl; Menon, Vinod

2016-01-01

The human voice is a critical social cue, and listeners are extremely sensitive to the voices in their environment. One of the most salient voices in a child’s life is mother's voice: Infants discriminate their mother’s voice from the first days of life, and this stimulus is associated with guiding emotional and social function during development. Little is known regarding the functional circuits that are selectively engaged in children by biologically salient voices such as mother’s voice or whether this brain activity is related to children’s social communication abilities. We used functional MRI to measure brain activity in 24 healthy children (mean age, 10.2 y) while they attended to brief (<1 s) nonsense words produced by their biological mother and two female control voices and explored relationships between speech-evoked neural activity and social function. Compared to female control voices, mother’s voice elicited greater activity in primary auditory regions in the midbrain and cortex; voice-selective superior temporal sulcus (STS); the amygdala, which is crucial for processing of affect; nucleus accumbens and orbitofrontal cortex of the reward circuit; anterior insula and cingulate of the salience network; and a subregion of fusiform gyrus associated with face perception. The strength of brain connectivity between voice-selective STS and reward, affective, salience, memory, and face-processing regions during mother’s voice perception predicted social communication skills. Our findings provide a novel neurobiological template for investigation of typical social development as well as clinical disorders, such as autism, in which perception of biologically and socially salient voices may be impaired. PMID:27185915

Neural circuits underlying mother's voice perception predict social communication abilities in children.

PubMed

Abrams, Daniel A; Chen, Tianwen; Odriozola, Paola; Cheng, Katherine M; Baker, Amanda E; Padmanabhan, Aarthi; Ryali, Srikanth; Kochalka, John; Feinstein, Carl; Menon, Vinod

2016-05-31

The human voice is a critical social cue, and listeners are extremely sensitive to the voices in their environment. One of the most salient voices in a child's life is mother's voice: Infants discriminate their mother's voice from the first days of life, and this stimulus is associated with guiding emotional and social function during development. Little is known regarding the functional circuits that are selectively engaged in children by biologically salient voices such as mother's voice or whether this brain activity is related to children's social communication abilities. We used functional MRI to measure brain activity in 24 healthy children (mean age, 10.2 y) while they attended to brief (<1 s) nonsense words produced by their biological mother and two female control voices and explored relationships between speech-evoked neural activity and social function. Compared to female control voices, mother's voice elicited greater activity in primary auditory regions in the midbrain and cortex; voice-selective superior temporal sulcus (STS); the amygdala, which is crucial for processing of affect; nucleus accumbens and orbitofrontal cortex of the reward circuit; anterior insula and cingulate of the salience network; and a subregion of fusiform gyrus associated with face perception. The strength of brain connectivity between voice-selective STS and reward, affective, salience, memory, and face-processing regions during mother's voice perception predicted social communication skills. Our findings provide a novel neurobiological template for investigation of typical social development as well as clinical disorders, such as autism, in which perception of biologically and socially salient voices may be impaired.

Circuit Motifs for Contrast-Adaptive Differentiation in Early Sensory Systems: The Role of Presynaptic Inhibition and Short-Term Plasticity

PubMed Central

Zhang, Danke; Wu, Si; Rasch, Malte J.

2015-01-01

In natural signals, such as the luminance value across of a visual scene, abrupt changes in intensity value are often more relevant to an organism than intensity values at other positions and times. Thus to reduce redundancy, sensory systems are specialized to detect the times and amplitudes of informative abrupt changes in the input stream rather than coding the intensity values at all times. In theory, a system that responds transiently to fast changes is called a differentiator. In principle, several different neural circuit mechanisms exist that are capable of responding transiently to abrupt input changes. However, it is unclear which circuit would be best suited for early sensory systems, where the dynamic range of the natural input signals can be very wide. We here compare the properties of different simple neural circuit motifs for implementing signal differentiation. We found that a circuit motif based on presynaptic inhibition (PI) is unique in a sense that the vesicle resources in the presynaptic site can be stably maintained over a wide range of stimulus intensities, making PI a biophysically plausible mechanism to implement a differentiator with a very wide dynamical range. Moreover, by additionally considering short-term plasticity (STP), differentiation becomes contrast adaptive in the PI-circuit but not in other potential neural circuit motifs. Numerical simulations show that the behavior of the adaptive PI-circuit is consistent with experimental observations suggesting that adaptive presynaptic inhibition might be a good candidate neural mechanism to achieve differentiation in early sensory systems. PMID:25723493

Circuit motifs for contrast-adaptive differentiation in early sensory systems: the role of presynaptic inhibition and short-term plasticity.

PubMed

Zhang, Danke; Wu, Si; Rasch, Malte J

2015-01-01

In natural signals, such as the luminance value across of a visual scene, abrupt changes in intensity value are often more relevant to an organism than intensity values at other positions and times. Thus to reduce redundancy, sensory systems are specialized to detect the times and amplitudes of informative abrupt changes in the input stream rather than coding the intensity values at all times. In theory, a system that responds transiently to fast changes is called a differentiator. In principle, several different neural circuit mechanisms exist that are capable of responding transiently to abrupt input changes. However, it is unclear which circuit would be best suited for early sensory systems, where the dynamic range of the natural input signals can be very wide. We here compare the properties of different simple neural circuit motifs for implementing signal differentiation. We found that a circuit motif based on presynaptic inhibition (PI) is unique in a sense that the vesicle resources in the presynaptic site can be stably maintained over a wide range of stimulus intensities, making PI a biophysically plausible mechanism to implement a differentiator with a very wide dynamical range. Moreover, by additionally considering short-term plasticity (STP), differentiation becomes contrast adaptive in the PI-circuit but not in other potential neural circuit motifs. Numerical simulations show that the behavior of the adaptive PI-circuit is consistent with experimental observations suggesting that adaptive presynaptic inhibition might be a good candidate neural mechanism to achieve differentiation in early sensory systems.

Structural and functional maturation of the developing primate brain.

PubMed

Levitt, Pat

2003-10-01

Descriptive studies have established that the developmental events responsible for the assembly of neural systems and circuitry are conserved across mammalian species. However, primates are unique regarding the time during which histogenesis occurs and the extended postnatal period during which myelination of pathways and circuitry formation occur and are then subsequently modified, particularly in the cerebral cortex. As in lower mammals, the framework for subcortical-cortical connectivity in primates is established before midgestation and already begins to remodel before birth. Association systems, responsible for modulating intracortical circuits that integrate information across functional domains, also form before birth, but their growth and reorganization extend into puberty. There are substantial differences across species in the patterns of development of specific neurochemical systems. The complexity is even greater when considering that the development of any particular cellular component may differ among cortical areas in the same primate species. Developmental and behavioral neurobiologists, psychologists, and pediatricians are challenged with understanding how functional maturation relates to the evolving anatomical organization of the human brain during childhood, and moreover, how genetic and environmental perturbations affect the adaptive changes exhibited by neural circuits in response to developmental disruption.

Optogenetic Functional MRI

PubMed Central

Lin, Peter; Fang, Zhongnan; Liu, Jia; Lee, Jin Hyung

2016-01-01

The investigation of the functional connectivity of precise neural circuits across the entire intact brain can be achieved through optogenetic functional magnetic resonance imaging (ofMRI), which is a novel technique that combines the relatively high spatial resolution of high-field fMRI with the precision of optogenetic stimulation. Fiber optics that enable delivery of specific wavelengths of light deep into the brain in vivo are implanted into regions of interest in order to specifically stimulate targeted cell types that have been genetically induced to express light-sensitive trans-membrane conductance channels, called opsins. fMRI is used to provide a non-invasive method of determining the brain's global dynamic response to optogenetic stimulation of specific neural circuits through measurement of the blood-oxygen-level-dependent (BOLD) signal, which provides an indirect measurement of neuronal activity. This protocol describes the construction of fiber optic implants, the implantation surgeries, the imaging with photostimulation and the data analysis required to successfully perform ofMRI. In summary, the precise stimulation and whole-brain monitoring ability of ofMRI are crucial factors in making ofMRI a powerful tool for the study of the connectomics of the brain in both healthy and diseased states. PMID:27167840

The Complexity of Dynamics in Small Neural Circuits

PubMed Central

Panzeri, Stefano

2016-01-01

Mean-field approximations are a powerful tool for studying large neural networks. However, they do not describe well the behavior of networks composed of a small number of neurons. In this case, major differences between the mean-field approximation and the real behavior of the network can arise. Yet, many interesting problems in neuroscience involve the study of mesoscopic networks composed of a few tens of neurons. Nonetheless, mathematical methods that correctly describe networks of small size are still rare, and this prevents us to make progress in understanding neural dynamics at these intermediate scales. Here we develop a novel systematic analysis of the dynamics of arbitrarily small networks composed of homogeneous populations of excitatory and inhibitory firing-rate neurons. We study the local bifurcations of their neural activity with an approach that is largely analytically tractable, and we numerically determine the global bifurcations. We find that for strong inhibition these networks give rise to very complex dynamics, caused by the formation of multiple branching solutions of the neural dynamics equations that emerge through spontaneous symmetry-breaking. This qualitative change of the neural dynamics is a finite-size effect of the network, that reveals qualitative and previously unexplored differences between mesoscopic cortical circuits and their mean-field approximation. The most important consequence of spontaneous symmetry-breaking is the ability of mesoscopic networks to regulate their degree of functional heterogeneity, which is thought to help reducing the detrimental effect of noise correlations on cortical information processing. PMID:27494737

Neural sex modifies the function of a C. elegans sensory circuit.

PubMed

Lee, Kyunghwa; Portman, Douglas S

2007-11-06

Though sex differences in animal behavior are ubiquitous, their neural and genetic underpinnings remain poorly understood. In particular, the role of functional differences in the neural circuitry that is shared by both sexes has not been extensively investigated. We have addressed these issues with C. elegans olfaction, a simple innate behavior mediated by sexually isomorphic neurons. Though males respond to the same olfactory attractants as do hermaphrodites, we find that each sex has a characteristic repertoire of olfactory preferences. These are not secondary to other sex-specific behaviors and do not require signaling from the gonad. Sex-specific olfactory preferences are controlled by tra-1, the master regulator of C. elegans sexual differentiation. Moreover, the genetic masculinization of neurons in an otherwise wild-type hermaphrodite is sufficient to switch the sexual phenotype of olfactory preference behavior. These studies reveal novel and unexpected sex differences in a C. elegans sensory behavior that is exhibited by both sexes. Our results indicate that these differences are a function of the chromosomally determined sexual identity of shared neural circuitry.

Sensori-motor experience leads to changes in visual processing in the developing brain.

PubMed

James, Karin Harman

2010-03-01

Since Broca's studies on language processing, cortical functional specialization has been considered to be integral to efficient neural processing. A fundamental question in cognitive neuroscience concerns the type of learning that is required for functional specialization to develop. To address this issue with respect to the development of neural specialization for letters, we used functional magnetic resonance imaging (fMRI) to compare brain activation patterns in pre-school children before and after different letter-learning conditions: a sensori-motor group practised printing letters during the learning phase, while the control group practised visual recognition. Results demonstrated an overall left-hemisphere bias for processing letters in these pre-literate participants, but, more interestingly, showed enhanced blood oxygen-level-dependent activation in the visual association cortex during letter perception only after sensori-motor (printing) learning. It is concluded that sensori-motor experience augments processing in the visual system of pre-school children. The change of activation in these neural circuits provides important evidence that 'learning-by-doing' can lay the foundation for, and potentially strengthen, the neural systems used for visual letter recognition.

Changes in the interaction of resting-state neural networks from adolescence to adulthood.

PubMed

Stevens, Michael C; Pearlson, Godfrey D; Calhoun, Vince D

2009-08-01

This study examined how the mutual interactions of functionally integrated neural networks during resting-state fMRI differed between adolescence and adulthood. Independent component analysis (ICA) was used to identify functionally connected neural networks in 100 healthy participants aged 12-30 years. Hemodynamic timecourses that represented integrated neural network activity were analyzed with tools that quantified system "causal density" estimates, which indexed the proportion of significant Granger causality relationships among system nodes. Mutual influences among networks decreased with age, likely reflecting stronger within-network connectivity and more efficient between-network influences with greater development. Supplemental tests showed that this normative age-related reduction in causal density was accompanied by fewer significant connections to and from each network, regional increases in the strength of functional integration within networks, and age-related reductions in the strength of numerous specific system interactions. The latter included paths between lateral prefrontal-parietal circuits and "default mode" networks. These results contribute to an emerging understanding that activity in widely distributed networks thought to underlie complex cognition influences activity in other networks. (c) 2009 Wiley-Liss, Inc.

Multi-Connection Pattern Analysis: Decoding the representational content of neural communication.

PubMed

Li, Yuanning; Richardson, Robert Mark; Ghuman, Avniel Singh

2017-11-15

The lack of multivariate methods for decoding the representational content of interregional neural communication has left it difficult to know what information is represented in distributed brain circuit interactions. Here we present Multi-Connection Pattern Analysis (MCPA), which works by learning mappings between the activity patterns of the populations as a factor of the information being processed. These maps are used to predict the activity from one neural population based on the activity from the other population. Successful MCPA-based decoding indicates the involvement of distributed computational processing and provides a framework for probing the representational structure of the interaction. Simulations demonstrate the efficacy of MCPA in realistic circumstances. In addition, we demonstrate that MCPA can be applied to different signal modalities to evaluate a variety of hypothesis associated with information coding in neural communications. We apply MCPA to fMRI and human intracranial electrophysiological data to provide a proof-of-concept of the utility of this method for decoding individual natural images and faces in functional connectivity data. We further use a MCPA-based representational similarity analysis to illustrate how MCPA may be used to test computational models of information transfer among regions of the visual processing stream. Thus, MCPA can be used to assess the information represented in the coupled activity of interacting neural circuits and probe the underlying principles of information transformation between regions. Copyright © 2017 Elsevier Inc. All rights reserved.

Alternative forms of axial startle behaviors in fishes.

PubMed

Liu, Yen-Chyi; Hale, Melina E

2014-02-01

For most aquatic vertebrates, axial movements play key roles in the performance of startle responses. In fishes, these axis-based startle behaviors fall into three distinct categories - the C-start, withdrawal, and S-start - defined by patterns of body bending and underlying motor control. Startle behaviors have been widely studied due to their importance for predator evasion. In addition, the neural circuits that control startles are relatively accessible, compared to other vertebrate circuits, and have provided opportunities to understand basic nervous system function. The C-start neural circuit has long been a model in systems neuroscience and considerable work on neural control of withdrawal response has been conducted in the larval lamprey. The S-start response has only recently been explored from a physiological perspective and we focus here on reviewing S-start motor control and movement in the context of the other two responses. Axial elongation has previously been associated with startle behavior in comparisons of C-starts and withdrawal, with extremely elongate animals performing withdrawals. We suggest that the S-start tends to occur with moderate body elongation, complementing the C-start in animals with this body form. As many larval fishes are moderately elongate, we suggest that the S-start may be common in larvae but may be secondarily lost with body shape change through development. Copyright © 2013 Elsevier GmbH. All rights reserved.

Differential regulation of polarized synaptic vesicle trafficking and synapse stability in neural circuit rewiring in Caenorhabditis elegans

PubMed Central

Kurup, Naina; Kono, Karina

2017-01-01

Neural circuits are dynamic, with activity-dependent changes in synapse density and connectivity peaking during different phases of animal development. In C. elegans, young larvae form mature motor circuits through a dramatic switch in GABAergic neuron connectivity, by concomitant elimination of existing synapses and formation of new synapses that are maintained throughout adulthood. We have previously shown that an increase in microtubule dynamics during motor circuit rewiring facilitates new synapse formation. Here, we further investigate cellular control of circuit rewiring through the analysis of mutants obtained in a forward genetic screen. Using live imaging, we characterize novel mutations that alter cargo binding in the dynein motor complex and enhance anterograde synaptic vesicle movement during remodeling, providing in vivo evidence for the tug-of-war between kinesin and dynein in fast axonal transport. We also find that a casein kinase homolog, TTBK-3, inhibits stabilization of nascent synapses in their new locations, a previously unexplored facet of structural plasticity of synapses. Our study delineates temporally distinct signaling pathways that are required for effective neural circuit refinement. PMID:28636662

Statistical modeling implicates neuroanatomical circuit mediating stress relief by ‘comfort’ food

PubMed Central

Ulrich-Lai, Yvonne M.; Christiansen, Anne M.; Wang, Xia; Song, Seongho; Herman, James P.

2015-01-01

A history of eating highly-palatable foods reduces physiological and emotional responses to stress. For instance, we have previously shown that limited sucrose intake (4 ml of 30% sucrose twice daily for 14 days) reduces hypothalamic-pituitary-adrenocortical (HPA) axis responses to stress. However, the neural mechanisms underlying stress relief by such ‘comfort’ foods are unclear, and could reveal an endogenous brain pathway for stress mitigation. As such, the present work assessed the expression of several proteins related to neuronal activation and/or plasticity in multiple stress- and reward-regulatory brain regions of rats after limited sucrose (vs. water control) intake. These data were then subjected to a series of statistical analyses, including Bayesian modeling, to identify the most likely neurocircuit mediating stress relief by sucrose. The analyses suggest that sucrose reduces HPA activation by dampening an excitatory basolateral amygdala - medial amygdala circuit, while also potentiating an inhibitory bed nucleus of the stria terminalis principle subdivision-mediated circuit, resulting in reduced HPA activation after stress. Collectively, the results support the hypothesis that sucrose limits stress responses via plastic changes to the structure and function of stress-regulatory neural circuits. The work also illustrates that advanced statistical methods are useful approaches to identify potentially novel and important underlying relationships in biological data sets. PMID:26246177

Statistical modeling implicates neuroanatomical circuit mediating stress relief by 'comfort' food.

PubMed

Ulrich-Lai, Yvonne M; Christiansen, Anne M; Wang, Xia; Song, Seongho; Herman, James P

2016-07-01

A history of eating highly palatable foods reduces physiological and emotional responses to stress. For instance, we have previously shown that limited sucrose intake (4 ml of 30 % sucrose twice daily for 14 days) reduces hypothalamic-pituitary-adrenocortical (HPA) axis responses to stress. However, the neural mechanisms underlying stress relief by such 'comfort' foods are unclear, and could reveal an endogenous brain pathway for stress mitigation. As such, the present work assessed the expression of several proteins related to neuronal activation and/or plasticity in multiple stress- and reward-regulatory brain regions of rats after limited sucrose (vs. water control) intake. These data were then subjected to a series of statistical analyses, including Bayesian modeling, to identify the most likely neurocircuit mediating stress relief by sucrose. The analyses suggest that sucrose reduces HPA activation by dampening an excitatory basolateral amygdala-medial amygdala circuit, while also potentiating an inhibitory bed nucleus of the stria terminalis principle subdivision-mediated circuit, resulting in reduced HPA activation after stress. Collectively, the results support the hypothesis that sucrose limits stress responses via plastic changes to the structure and function of stress-regulatory neural circuits. The work also illustrates that advanced statistical methods are useful approaches to identify potentially novel and important underlying relationships in biological datasets.

Commentary: Elucidating the Neural Correlates of Early Childhood Memory

ERIC Educational Resources Information Center

Mullally, Sinead L.

2015-01-01

Both episodic memory and the key neural structure believed to support it, namely the hippocampus, are believed to undergo protracted periods of postnatal developmental. Critically however, the hippocampus is comprised of distinct subfields and circuits, and these circuits appear to mature at different rates (Lavenex and Banta Lavenex, 2013).…

From a meso- to micro-scale connectome: array tomography and mGRASP

PubMed Central

Rah, Jong-Cheol; Feng, Linqing; Druckmann, Shaul; Lee, Hojin; Kim, Jinhyun

2015-01-01

Mapping mammalian synaptic connectivity has long been an important goal of neuroscience because knowing how neurons and brain areas are connected underpins an understanding of brain function. Meeting this goal requires advanced techniques with single synapse resolution and large-scale capacity, especially at multiple scales tethering the meso- and micro-scale connectome. Among several advanced LM-based connectome technologies, Array Tomography (AT) and mammalian GFP-Reconstitution Across Synaptic Partners (mGRASP) can provide relatively high-throughput mapping synaptic connectivity at multiple scales. AT- and mGRASP-assisted circuit mapping (ATing and mGRASPing), combined with techniques such as retrograde virus, brain clearing techniques, and activity indicators will help unlock the secrets of complex neural circuits. Here, we discuss these useful new tools to enable mapping of brain circuits at multiple scales, some functional implications of spatial synaptic distribution, and future challenges and directions of these endeavors. PMID:26089781

Clonazepam responsive opsoclonus myoclonus syndrome: additional evidence in favour of fastigial nucleus disinhibition hypothesis?

PubMed

Paliwal, Vimal Kumar; Chandra, Satish; Verma, Ritu; Kalita, Jayantee; Misra, Usha K

2010-05-01

Opsoclonus myoclonus syndrome is a rare paraneoplastic syndrome seen in 50% of children with neuroblastoma. Neural generator of opsoclonus and myoclonus is not known but evidences suggest the role of fastigial nucleus disinhibition from the loss of function of inhibitory (GABAergic) Purkinje cells in the cerebellum. We present a child with paraneoplastic opsoclonus myoclonus syndrome who responded well to clonazepam. Response to clonazepam is an evidence for the involvement of GABAergic neural circuits in the genesis of opsoclonus myoclonus syndrome and is in agreement with fastigial nucleus disinhibition hypothesis.

Proposal for an All-Spin Artificial Neural Network: Emulating Neural and Synaptic Functionalities Through Domain Wall Motion in Ferromagnets.

PubMed

Sengupta, Abhronil; Shim, Yong; Roy, Kaushik

2016-12-01

Non-Boolean computing based on emerging post-CMOS technologies can potentially pave the way for low-power neural computing platforms. However, existing work on such emerging neuromorphic architectures have either focused on solely mimicking the neuron, or the synapse functionality. While memristive devices have been proposed to emulate biological synapses, spintronic devices have proved to be efficient at performing the thresholding operation of the neuron at ultra-low currents. In this work, we propose an All-Spin Artificial Neural Network where a single spintronic device acts as the basic building block of the system. The device offers a direct mapping to synapse and neuron functionalities in the brain while inter-layer network communication is accomplished via CMOS transistors. To the best of our knowledge, this is the first demonstration of a neural architecture where a single nanoelectronic device is able to mimic both neurons and synapses. The ultra-low voltage operation of low resistance magneto-metallic neurons enables the low-voltage operation of the array of spintronic synapses, thereby leading to ultra-low power neural architectures. Device-level simulations, calibrated to experimental results, was used to drive the circuit and system level simulations of the neural network for a standard pattern recognition problem. Simulation studies indicate energy savings by  ∼  100× in comparison to a corresponding digital/analog CMOS neuron implementation.

Identifying Predictors, Moderators, and Mediators of Antidepressant Response in Major Depressive Disorder: Neuroimaging Approaches

PubMed Central

Phillips, Mary L.; Chase, Henry W.; Sheline, Yvette I.; Etkin, Amit; Almeida, Jorge R.C.; Deckersbach, Thilo; Trivedi, Madhukar H.

2015-01-01

Objective Despite significant advances in neuroscience and treatment development, no widely accepted biomarkers are available to inform diagnostics or identify preferred treatments for individuals with major depressive disorder. Method In this critical review, the authors examine the extent to which multimodal neuroimaging techniques can identify biomarkers reflecting key pathophysiologic processes in depression and whether such biomarkers may act as predictors, moderators, and mediators of treatment response that might facilitate development of personalized treatments based on a better understanding of these processes. Results The authors first highlight the most consistent findings from neuroimaging studies using different techniques in depression, including structural and functional abnormalities in two parallel neural circuits: serotonergically modulated implicit emotion regulation circuitry, centered on the amygdala and different regions in the medial prefrontal cortex; and dopaminergically modulated reward neural circuitry, centered on the ventral striatum and medial prefrontal cortex. They then describe key findings from the relatively small number of studies indicating that specific measures of regional function and, to a lesser extent, structure in these neural circuits predict treatment response in depression. Conclusions Limitations of existing studies include small sample sizes, use of only one neuroimaging modality, and a focus on identifying predictors rather than moderators and mediators of differential treatment response. By addressing these limitations and, most importantly, capitalizing on the benefits of multimodal neuroimaging, future studies can yield moderators and mediators of treatment response in depression to facilitate significant improvements in shorter- and longer-term clinical and functional outcomes. PMID:25640931

Functional Imaging and Optogenetics in Drosophila

PubMed Central

Simpson, Julie H.; Looger, Loren L.

2018-01-01

Understanding how activity patterns in specific neural circuits coordinate an animal’s behavior remains a key area of neuroscience research. Genetic tools and a brain of tractable complexity make Drosophila a premier model organism for these studies. Here, we review the wealth of reagents available to map and manipulate neuronal activity with light. PMID:29618589

Aberrant Neural Function during Emotion Attribution in Female Subjects with Fragile X Syndrome

ERIC Educational Resources Information Center

Hagan, Cindy C.; Hoeft, Fumiko; Mackey, Allyson; Mobbs, Dean; Reiss, Allan L.

2008-01-01

The neurobiological systems which underlie emotion attribution among female patients with Fragile X (FraX) syndrome are examined. Results show that the emotion circuit which regulates responses to facial stimuli is potentially disrupted among female subjects with FraX syndrome. Anterior cingulate cortex activity in female subjects with FraX…

Mechanisms of input and output synaptic specificity: finding partners, building synapses, and fine-tuning communication.

PubMed

Rawson, Randi L; Martin, E Anne; Williams, Megan E

2017-08-01

For most neurons to function properly, they need to develop synaptic specificity. This requires finding specific partner neurons, building the correct types of synapses, and fine-tuning these synapses in response to neural activity. Synaptic specificity is common at both a neuron's input and output synapses, whereby unique synapses are built depending on the partnering neuron. Neuroscientists have long appreciated the remarkable specificity of neural circuits but identifying molecular mechanisms mediating synaptic specificity has only recently accelerated. Here, we focus on recent progress in understanding input and output synaptic specificity in the mammalian brain. We review newly identified circuit examples for both and the latest research identifying molecular mediators including Kirrel3, FGFs, and DGLα. Lastly, we expect the pace of research on input and output specificity to continue to accelerate with the advent of new technologies in genomics, microscopy, and proteomics. Copyright © 2017 Elsevier Ltd. All rights reserved.

Functional identification of an aggression locus in the mouse hypothalamus

PubMed Central

Lin, Dayu; Boyle, Maureen P.; Dollar, Piotr; Lee, Hyosang; Perona, Pietro; Lein, Ed S.; Anderson, David J.

2010-01-01

Electrical stimulation of certain hypothalamic regions in cats and rodents can elicit attack behavior, but the exact location of relevant cells within these regions, their requirement for naturally occurring aggression and their relationship to mating circuits have not been clear. Genetic methods for neural circuit manipulation in mice provide a potentially powerful approach to this problem, but brain stimulation-evoked aggression has never been demonstrated in this species. Here we show that optogenetic, but not electrical, stimulation of neurons in the ventromedial hypothalamus, ventrolateral subdivision (VMHvl) causes male mice to attack both females and inanimate objects, as well as males. Pharmacogenetic silencing of VMHvl reversibly inhibits inter-male aggression. Immediate early gene analysis and single unit recordings from VMHvl during social interactions reveal overlapping but distinct neuronal subpopulations involved in fighting and mating. Neurons activated during attack are inhibited during mating, suggesting a potential neural substrate for competition between these behaviors. PMID:21307935

Functional identification of an aggression locus in the mouse hypothalamus.

PubMed

Lin, Dayu; Boyle, Maureen P; Dollar, Piotr; Lee, Hyosang; Lein, E S; Perona, Pietro; Anderson, David J

2011-02-10

Electrical stimulation of certain hypothalamic regions in cats and rodents can elicit attack behaviour, but the exact location of relevant cells within these regions, their requirement for naturally occurring aggression and their relationship to mating circuits have not been clear. Genetic methods for neural circuit manipulation in mice provide a potentially powerful approach to this problem, but brain-stimulation-evoked aggression has never been demonstrated in this species. Here we show that optogenetic, but not electrical, stimulation of neurons in the ventromedial hypothalamus, ventrolateral subdivision (VMHvl) causes male mice to attack both females and inanimate objects, as well as males. Pharmacogenetic silencing of VMHvl reversibly inhibits inter-male aggression. Immediate early gene analysis and single unit recordings from VMHvl during social interactions reveal overlapping but distinct neuronal subpopulations involved in fighting and mating. Neurons activated during attack are inhibited during mating, suggesting a potential neural substrate for competition between these opponent social behaviours.

Oscillatory integration windows in neurons

PubMed Central

Gupta, Nitin; Singh, Swikriti Saran; Stopfer, Mark

2016-01-01

Oscillatory synchrony among neurons occurs in many species and brain areas, and has been proposed to help neural circuits process information. One hypothesis states that oscillatory input creates cyclic integration windows: specific times in each oscillatory cycle when postsynaptic neurons become especially responsive to inputs. With paired local field potential (LFP) and intracellular recordings and controlled stimulus manipulations we directly test this idea in the locust olfactory system. We find that inputs arriving in Kenyon cells (KCs) sum most effectively in a preferred window of the oscillation cycle. With a computational model, we show that the non-uniform structure of noise in the membrane potential helps mediate this process. Further experiments performed in vivo demonstrate that integration windows can form in the absence of inhibition and at a broad range of oscillation frequencies. Our results reveal how a fundamental coincidence-detection mechanism in a neural circuit functions to decode temporally organized spiking. PMID:27976720

Neurocircuitry of limbic dysfunction in anorexia nervosa.

PubMed

Lipsman, Nir; Woodside, D Blake; Lozano, Andres M

2015-01-01

Anorexia Nervosa (AN) is a serious psychiatric condition marked by firmly entrenched and maladaptive behaviors and beliefs about body, weight and food, as well as high rates of psychiatric comorbidity. The neural roots of AN are now beginning to emerge, and appear to be related to dysfunctional, primarily limbic, circuits driving pathological thoughts and behaviors. As a result, the significant physical symptoms of AN are increasingly being understood at least partially as a result of abnormal or dysregulated emotional processing. This paper reviews the nature of limbic dysfunction in AN, and how structural and functional imaging has implicated distinct emotional and perceptual neural circuits driving AN symptoms. We propose that top-down and bottom-up influences converge on key limbic modulatory structures, such as the subcallosal cingulate and insula, whose normal functioning is critical to affective regulation and emotional homeostasis. Dysfunctional activity in these structures, as is seen in AN, may lead to emotional processing deficits and psychiatric symptoms, which then drive maladaptive behaviors. Modulating limbic dysregulation may therefore be a potential treatment strategy in some AN patients. Copyright © 2014 Elsevier Ltd. All rights reserved.

Activity of the C. elegans egg-laying behavior circuit is controlled by competing activation and feedback inhibition

PubMed Central

Collins, Kevin M; Bode, Addys; Fernandez, Robert W; Tanis, Jessica E; Brewer, Jacob C; Creamer, Matthew S; Koelle, Michael R

2016-01-01

Like many behaviors, Caenorhabditis elegans egg laying alternates between inactive and active states. To understand how the underlying neural circuit turns the behavior on and off, we optically recorded circuit activity in behaving animals while manipulating circuit function using mutations, optogenetics, and drugs. In the active state, the circuit shows rhythmic activity phased with the body bends of locomotion. The serotonergic HSN command neurons initiate the active state, but accumulation of unlaid eggs also promotes the active state independent of the HSNs. The cholinergic VC motor neurons slow locomotion during egg-laying muscle contraction and egg release. The uv1 neuroendocrine cells mechanically sense passage of eggs through the vulva and release tyramine to inhibit egg laying, in part via the LGC-55 tyramine-gated Cl- channel on the HSNs. Our results identify discrete signals that entrain or detach the circuit from the locomotion central pattern generator to produce active and inactive states. DOI: http://dx.doi.org/10.7554/eLife.21126.001 PMID:27849154

Neural learning circuits utilizing nano-crystalline silicon transistors and memristors.

PubMed

Cantley, Kurtis D; Subramaniam, Anand; Stiegler, Harvey J; Chapman, Richard A; Vogel, Eric M

2012-04-01

Properties of neural circuits are demonstrated via SPICE simulations and their applications are discussed. The neuron and synapse subcircuits include ambipolar nano-crystalline silicon transistor and memristor device models based on measured data. Neuron circuit characteristics and the Hebbian synaptic learning rule are shown to be similar to biology. Changes in the average firing rate learning rule depending on various circuit parameters are also presented. The subcircuits are then connected into larger neural networks that demonstrate fundamental properties including associative learning and pulse coincidence detection. Learned extraction of a fundamental frequency component from noisy inputs is demonstrated. It is then shown that if the fundamental sinusoid of one neuron input is out of phase with the rest, its synaptic connection changes differently than the others. Such behavior indicates that the system can learn to detect which signals are important in the general population, and that there is a spike-timing-dependent component of the learning mechanism. Finally, future circuit design and considerations are discussed, including requirements for the memristive device.

Maintenance of Mouse Gustatory Terminal Field Organization Is Disrupted following Selective Removal of Peripheral Sodium Salt Taste Activity at Adulthood

PubMed Central

Sun, Chengsan

2017-01-01

Neural activity plays a critical role in the development of central circuits in sensory systems. However, the maintenance of these circuits at adulthood is usually not dependent on sensory-elicited neural activity. Recent work in the mouse gustatory system showed that selectively deleting the primary transduction channel for sodium taste, the epithelial sodium channel (ENaC), throughout development dramatically impacted the organization of the central terminal fields of three nerves that carry taste information to the nucleus of the solitary tract. More specifically, deleting ENaCs during development prevented the normal maturation of the fields. The present study was designed to extend these findings by testing the hypothesis that the loss of sodium taste activity impacts the maintenance of the normal adult terminal field organization in male and female mice. To do this, we used an inducible Cre-dependent genetic recombination strategy to delete ENaC function after terminal field maturation occurred. We found that removal of sodium taste neural activity at adulthood resulted in significant reorganization of mature gustatory afferent terminal fields in the nucleus of the solitary tract. Specifically, the chorda tympani and greater superficial petrosal nerve terminal fields were 1.4× and 1.6× larger than age-matched controls, respectively. By contrast, the glossopharyngeal nerve, which is not highly sensitive to sodium taste stimulation, did not undergo terminal field reorganization. These surprising results suggest that gustatory nerve terminal fields remain plastic well into adulthood, which likely impacts central coding of taste information and taste-related behaviors with altered taste experience. SIGNIFICANCE STATEMENT Neural activity plays a major role in the development of sensory circuits in the mammalian brain. However, the importance of sensory-driven activity in maintaining these circuits at adulthood, especially in subcortical structures, appears to be much less. Here, we tested whether the loss of sodium taste activity in adult mice impacts the maintenance of how taste nerves project to the first central relay. We found that specific loss of sodium-elicited taste activity at adulthood produced dramatic and selective reorganization of terminal fields in the brainstem. This demonstrates, for the first time, that taste-elicited activity is necessary for the normal maintenance of central gustatory circuits at adulthood and highlights a level of plasticity not seen in other sensory system subcortical circuits. PMID:28676575

Cortico-Amygdala Coupling as a Marker of Early Relapse Risk in Cocaine-Addicted Individuals

PubMed Central

McHugh, Meredith J.; Demers, Catherine H.; Salmeron, Betty Jo; Devous, Michael D.; Stein, Elliot A.; Adinoff, Bryon

2014-01-01

Addiction to cocaine is a chronic condition characterized by high rates of early relapse. This study builds on efforts to identify neural markers of relapse risk by studying resting-state functional connectivity (rsFC) in neural circuits arising from the amygdala, a brain region implicated in relapse-related processes including craving and reactivity to stress following acute and protracted withdrawal from cocaine. Whole-brain resting-state functional magnetic resonance imaging connectivity (6 min) was assessed in 45 cocaine-addicted individuals and 22 healthy controls. Cocaine-addicted individuals completed scans in the final week of a residential treatment episode. To approximate preclinical models of relapse-related circuitry, separate seeds were derived for the left and right basolateral (BLA) and corticomedial (CMA) amygdala. Participants also completed the Iowa Gambling Task, Wisconsin Card Sorting Test, Cocaine Craving Questionnaire, Obsessive-Compulsive Cocaine Use Scale and Personality Inventory. Relapse within the first 30 days post-treatment (n = 24) was associated with reduced rsFC between the left CMA and ventromedial prefrontal cortex/rostral anterior cingulate cortex (vmPFC/rACC) relative to cocaine-addicted individuals who remained abstinent (non-relapse, n = 21). Non-relapse participants evidenced reduced rsFC between the bilateral BLA and visual processing regions (lingual gyrus/cuneus) compared to controls and relapsed participants. Early relapse was associated with fewer years of education but unrelated to trait reactivity to stress, neurocognitive and clinical characteristics or cocaine use history. Findings suggest that rsFC within neural circuits implicated in preclinical models of relapse may provide a promising marker of relapse risk in cocaine-addicted individuals. Future efforts to replicate the current findings and alter connectivity within these circuits may yield novel interventions and improve treatment outcomes. PMID:24578695

Pathological anxiety and function/dysfunction in the brain's fear/defense circuitry.

PubMed

Lang, Peter J; McTeague, Lisa M; Bradley, Margaret M

2014-01-01

Research from the University of Florida Center for the Study of Emotion and Attention aims to develop neurobiological measures that objectively discriminate among symptom patterns in patients with anxiety disorders. From this perspective, anxiety and mood pathologies are considered to be brain disorders, resulting from dysfunction and maladaptive plasticity in the neural circuits that determine fearful/defensive and appetitive/reward behavior (Insel et al., 2010). We review recent studies indicating that an enhanced probe startle reflex during the processing of fear memory cues (mediated by cortico-limbic circuitry and thus indicative of plastic brain changes), varies systematically in strength over a spectrum-wide dimension of anxiety pathology-across and within diagnoses-extending from strong focal fear reactions to a consistently blunted reaction in patients with more generalized anxiety and comorbid mood disorders. Preliminary studies with functional magnetic resonance imaging (fMRI) encourage the hypothesis that fear/defense circuit dysfunction covaries with this same dimension of psychopathology. Plans are described for an extended study of the brain's motivation circuitry in anxiety spectrum patients, with the aim of defining the specifics of circuit dysfunction in severe disorders. A sub-project explores the use of real-time fMRI feedback in circuit analysis and as a modality to up-regulate circuit function in the context of blunted affect.

Individual differences in regulatory focus predict neural response to reward.

PubMed

Scult, Matthew A; Knodt, Annchen R; Hanson, Jamie L; Ryoo, Minyoung; Adcock, R Alison; Hariri, Ahmad R; Strauman, Timothy J

2017-08-01

Although goal pursuit is related to both functioning of the brain's reward circuits and psychological factors, the literatures surrounding these concepts have often been separate. Here, we use the psychological construct of regulatory focus to investigate individual differences in neural response to reward. Regulatory focus theory proposes two motivational orientations for personal goal pursuit: (1) promotion, associated with sensitivity to potential gain, and (2) prevention, associated with sensitivity to potential loss. The monetary incentive delay task was used to manipulate reward circuit function, along with instructional framing corresponding to promotion and prevention in a within-subject design. We observed that the more promotion oriented an individual was, the lower their ventral striatum response to gain cues. Follow-up analyses revealed that greater promotion orientation was associated with decreased ventral striatum response even to no-value cues, suggesting that promotion orientation may be associated with relatively hypoactive reward system function. The findings are also likely to represent an interaction between the cognitive and motivational characteristics of the promotion system with the task demands. Prevention orientation did not correlate with ventral striatum response to gain cues, supporting the discriminant validity of regulatory focus theory. The results highlight a dynamic association between individual differences in self-regulation and reward system function.

The therapeutic potential of cell identity reprogramming for the treatment of aging-related neurodegenerative disorders.

PubMed

Smith, Derek K; He, Miao; Zhang, Chun-Li; Zheng, Jialin C

2017-10-01

Neural cell identity reprogramming strategies aim to treat age-related neurodegenerative disorders with newly induced neurons that regenerate neural architecture and functional circuits in vivo. The isolation and neural differentiation of pluripotent embryonic stem cells provided the first in vitro models of human neurodegenerative disease. Investigation into the molecular mechanisms underlying stem cell pluripotency revealed that somatic cells could be reprogrammed to induced pluripotent stem cells (iPSCs) and these cells could be used to model Alzheimer disease, amyotrophic lateral sclerosis, Huntington disease, and Parkinson disease. Additional neural precursor and direct transdifferentiation strategies further enabled the induction of diverse neural linages and neuron subtypes both in vitro and in vivo. In this review, we highlight neural induction strategies that utilize stem cells, iPSCs, and lineage reprogramming to model or treat age-related neurodegenerative diseases, as well as, the clinical challenges related to neural transplantation and in vivo reprogramming strategies. Copyright © 2016. Published by Elsevier Ltd.

Alzheimer's disease Braak Stage progressions: reexamined and redefined as Borrelia infection transmission through neural circuits.

PubMed

MacDonald, Alan B

2007-01-01

Brain structure in health is a dynamic energized equation incorporating chemistry, neuronal structure, and circuitry components. The chemistry "piece" is represented by multiple neurotransmitters such as Acetylcholine, Serotonin, and Dopamine. The neuronal structure "piece" incorporates synapses and their connections. And finally circuits of neurons establish "architectural blueprints" of anatomic wiring diagrams of the higher order of brain neuron organizations. In Alzheimer's disease, there are progressive losses in all of these components. Brain structure crumbles. The deterioration in Alzheimer's is ordered, reproducible, and stepwise. Drs. Braak and Braak have described stages in the Alzheimer disease continuum. "Progressions" through Braak Stages benchmark "Regressions" in Cognitive function. Under the microscope, the Stages of Braak commence in brain regions near to the hippocampus, and over time, like a tsunami wave of destruction, overturn healthy brain regions, with neurofibrillary tangle damaged neurons "marching" through the temporal lobe, neocortex and occipital cortex. In effect the destruction ascends from the limbic regions to progressively destroy the higher brain centers. Rabies infection also "begins low and finishes high" in its wave of destruction of brain tissue. Herpes Zoster infections offer the paradigm of clinical latency of infection inside of nerves before the "marching commences". Varicella Zoster virus enters neurons in the pediatric years. Dormant virus remains inside the neurons for 50-80 years, tissue damage late in life (shingles) demonstrates the "march of the infection" down neural pathways (dermatomes) as linear areas of painful blisters loaded with virus from a childhood infection. Amalgamation of Zoster with Rabies models produces a hybrid model to explain all of the Braak Stages of Alzheimer's disease under a new paradigm, namely "Alzheimer's neuroborreliosis" in which latent Borrelia infections ascend neural circuits through the hippocampus to the higher brain centers, creating a trail of neurofibrillary tangle injured neurons in neural circuits of cholinergic neurons by transsynaptic transmission of infection from nerve to nerve.

Polarity-specific high-level information propagation in neural networks.

PubMed

Lin, Yen-Nan; Chang, Po-Yen; Hsiao, Pao-Yueh; Lo, Chung-Chuan

2014-01-01

Analyzing the connectome of a nervous system provides valuable information about the functions of its subsystems. Although much has been learned about the architectures of neural networks in various organisms by applying analytical tools developed for general networks, two distinct and functionally important properties of neural networks are often overlooked. First, neural networks are endowed with polarity at the circuit level: Information enters a neural network at input neurons, propagates through interneurons, and leaves via output neurons. Second, many functions of nervous systems are implemented by signal propagation through high-level pathways involving multiple and often recurrent connections rather than by the shortest paths between nodes. In the present study, we analyzed two neural networks: the somatic nervous system of Caenorhabditis elegans (C. elegans) and the partial central complex network of Drosophila, in light of these properties. Specifically, we quantified high-level propagation in the vertical and horizontal directions: the former characterizes how signals propagate from specific input nodes to specific output nodes and the latter characterizes how a signal from a specific input node is shared by all output nodes. We found that the two neural networks are characterized by very efficient vertical and horizontal propagation. In comparison, classic small-world networks show a trade-off between vertical and horizontal propagation; increasing the rewiring probability improves the efficiency of horizontal propagation but worsens the efficiency of vertical propagation. Our result provides insights into how the complex functions of natural neural networks may arise from a design that allows them to efficiently transform and combine input signals.

Polarity-specific high-level information propagation in neural networks

PubMed Central

Lin, Yen-Nan; Chang, Po-Yen; Hsiao, Pao-Yueh; Lo, Chung-Chuan

2014-01-01

Analyzing the connectome of a nervous system provides valuable information about the functions of its subsystems. Although much has been learned about the architectures of neural networks in various organisms by applying analytical tools developed for general networks, two distinct and functionally important properties of neural networks are often overlooked. First, neural networks are endowed with polarity at the circuit level: Information enters a neural network at input neurons, propagates through interneurons, and leaves via output neurons. Second, many functions of nervous systems are implemented by signal propagation through high-level pathways involving multiple and often recurrent connections rather than by the shortest paths between nodes. In the present study, we analyzed two neural networks: the somatic nervous system of Caenorhabditis elegans (C. elegans) and the partial central complex network of Drosophila, in light of these properties. Specifically, we quantified high-level propagation in the vertical and horizontal directions: the former characterizes how signals propagate from specific input nodes to specific output nodes and the latter characterizes how a signal from a specific input node is shared by all output nodes. We found that the two neural networks are characterized by very efficient vertical and horizontal propagation. In comparison, classic small-world networks show a trade-off between vertical and horizontal propagation; increasing the rewiring probability improves the efficiency of horizontal propagation but worsens the efficiency of vertical propagation. Our result provides insights into how the complex functions of natural neural networks may arise from a design that allows them to efficiently transform and combine input signals. PMID:24672472

High-frequency stimulation of the subthalamic nucleus restores neural and behavioral functions during reaction time task in a rat model of Parkinson's disease.

PubMed

Li, Xiang-Hong; Wang, Jin-Yan; Gao, Ge; Chang, Jing-Yu; Woodward, Donald J; Luo, Fei

2010-05-15

Deep brain stimulation (DBS) has been used in the clinic to treat Parkinson's disease (PD) and other neuropsychiatric disorders. Our previous work has shown that DBS in the subthalamic nucleus (STN) can improve major motor deficits, and induce a variety of neural responses in rats with unilateral dopamine (DA) lesions. In the present study, we examined the effect of STN DBS on reaction time (RT) performance and parallel changes in neural activity in the cortico-basal ganglia regions of partially bilateral DA- lesioned rats. We recorded neural activity with a multiple-channel single-unit electrode system in the primary motor cortex (MI), the STN, and the substantia nigra pars reticulata (SNr) during RT test. RT performance was severely impaired following bilateral injection of 6-OHDA into the dorsolateral part of the striatum. In parallel with such behavioral impairments, the number of responsive neurons to different behavioral events was remarkably decreased after DA lesion. Bilateral STN DBS improved RT performance in 6-OHDA lesioned rats, and restored operational behavior-related neural responses in cortico-basal ganglia regions. These behavioral and electrophysiological effects of DBS lasted nearly an hour after DBS termination. These results demonstrate that a partial DA lesion-induced impairment of RT performance is associated with changes in neural activity in the cortico-basal ganglia circuit. Furthermore, STN DBS can reverse changes in behavior and neural activity caused by partial DA depletion. The observed long-lasting beneficial effect of STN DBS suggests the involvement of the mechanism of neural plasticity in modulating cortico-basal ganglia circuits. (c) 2009 Wiley-Liss, Inc.

Pivotal response treatment prompts a functional rewiring of the brain among individuals with autism spectrum disorder.

PubMed

Venkataraman, Archana; Yang, Daniel Y-J; Dvornek, Nicha; Staib, Lawrence H; Duncan, James S; Pelphrey, Kevin A; Ventola, Pamela

2016-09-28

Behavioral interventions for autism have gained prominence in recent years; however, the neural-systems-level targets of these interventions remain poorly understood. We use a novel Bayesian framework to extract network-based differences before and after a 16-week pivotal response treatment (PRT) regimen. Our results suggest that the functional changes induced by PRT localize to the posterior cingulate and are marked by a shift in connectivity from the orbitofrontal cortex to the occipital-temporal cortex. Our results illuminate a potential PRT-induced learning mechanism, whereby the neural circuits involved during social perception shift from sensory and attentional systems to higher-level object and face processing areas.

Pivotal Response Treatment Prompts a Functional Rewiring of the Brain amongst Individuals with Autism Spectrum Disorder

PubMed Central

Venkataraman, Archana; Yang, Daniel Y.-J.; Dvornek, Nicha; Staib, Lawrence H.; Duncan, James S.; Pelphrey, Kevin A.; Ventola, Pamela

2016-01-01

Behavioral interventions for autism have gained prominence in recent years; however, the neural-systems-level targets of these interventions remain poorly understood. We use a novel Bayesian framework to extract network-based differences before and after a 16-week Pivotal Response Treatment (PRT) regimen. Our results suggest that functional changes induced by PRT localize to the posterior cingulate and are marked by a shift in connectivity from the orbitofrontal cortex to the occipital temporal cortex. Our results illuminate a potential PRT-induced learning mechanism, whereby the neural circuits involved during social perception shift from sensory and attentional systems to higher-level object and face processing areas. PMID:27532879

Three Pillars for the Neural Control of Appetite.

PubMed

Sternson, Scott M; Eiselt, Anne-Kathrin

2017-02-10

The neural control of appetite is important for understanding motivated behavior as well as the present rising prevalence of obesity. Over the past several years, new tools for cell type-specific neuron activity monitoring and perturbation have enabled increasingly detailed analyses of the mechanisms underlying appetite-control systems. Three major neural circuits strongly and acutely influence appetite but with notably different characteristics. Although these circuits interact, they have distinct properties and thus appear to contribute to separate but interlinked processes influencing appetite, thereby forming three pillars of appetite control. Here, we summarize some of the key characteristics of appetite circuits that are emerging from recent work and synthesize the findings into a provisional framework that can guide future studies.

Possible Explanation for Cancer in Rats due to Cell Phone Radio Frequency Radiation

NASA Astrophysics Data System (ADS)

Feldman, Bernard J.

Very recently, the National Toxicology Program reported a correlation between exposure to whole body 900 MHz radio frequency radiation and cancer in the brains and hearts of Sprague Dawley male rats. Assuming that the National Toxicology Program is statistically significant, I propose the following explanation for these results. The neurons around the brain and heart form closed electrical circuits and, following Faraday's Law, 900 MHz radio frequency radiation induces 900 MHz electrical currents in these neural circuits. In turn, these 900 MHz currents in the neural circuits generate sufficient localized heat in the neural cells to shift the equilibrium concentration of carcinogenic radicals to higher levels and thus, to higher incidences of cancer.

A power-efficient analog integrated circuit for amplification and detection of neural signals.

PubMed

Borghi, T; Bonfanti, A; Gusmeroli, R; Zambra, G; Spinelli, A S

2008-01-01

We present a neural amplifier that optimizes the trade-off between power consumption and noise performance down to the best so far reported. In the perspective of realizing a fully autonomous implantable system we also address the problem of spike detection by using a new simple algorithm and we discuss the implementation with analog integrated circuits. Implemented in 0.35-microm CMOS technology and with total current consumption of about 20 microA, the whole circuit occupies an area of 0.18 mm(2). Reduced power consumption and small area make it suited to be used in chronic multichannel recording systems for neural prosthetics and neuroscience experiments.

Real-time emulation of neural images in the outer retinal circuit.

PubMed

Hasegawa, Jun; Yagi, Tetsuya

2008-12-01

We describe a novel real-time system that emulates the architecture and functionality of the vertebrate retina. This system reconstructs the neural images formed by the retinal neurons in real time by using a combination of analog and digital systems consisting of a neuromorphic silicon retina chip, a field-programmable gate array, and a digital computer. While the silicon retina carries out the spatial filtering of input images instantaneously, using the embedded resistive networks that emulate the receptive field structure of the outer retinal neurons, the digital computer carries out the temporal filtering of the spatially filtered images to emulate the dynamical properties of the outer retinal circuits. The emulations of the neural image, including 128 x 128 bipolar cells, are carried out at a frame rate of 62.5 Hz. The emulation of the response to the Hermann grid and a spot of light and an annulus of lights has demonstrated that the system responds as expected by previous physiological and psychophysical observations. Furthermore, the emulated dynamics of neural images in response to natural scenes revealed the complex nature of retinal neuron activity. We have concluded that the system reflects the spatiotemporal responses of bipolar cells in the vertebrate retina. The proposed emulation system is expected to aid in understanding the visual computation in the retina and the brain.

Simplified Design Equations for Class-E Neural Prosthesis Transmitters

PubMed Central

Troyk, Philip; Hu, Zhe

2013-01-01

Extreme miniaturization of implantable electronic devices is recognized as essential for the next generation of neural prostheses, owing to the need for minimizing the damage and disruption of the surrounding neural tissue. Transcutaneous power and data transmission via a magnetic link remains the most effective means of powering and controlling implanted neural prostheses. Reduction in the size of the coil, within the neural prosthesis, demands the generation of a high-intensity radio frequency magnetic field from the extracoporeal transmitter. The Class-E power amplifier circuit topology has been recognized as a highly effective means of producing large radio frequency currents within the transmitter coil. Unfortunately, design of a Class-E circuit is most often fraught by the need to solve a complex set of equations so as to implement both the zero-voltage-switching and zero-voltage-derivative-switching conditions that are required for efficient operation. This paper presents simple explicit design equations for designing the Class-E circuit topology. Numerical design examples are presented to illustrate the design procedure. PMID:23292784

Mediodorsal thalamus and cognition in non-human primates

PubMed Central

Baxter, Mark G.

2013-01-01

Several recent studies in non-human primates have provided new insights into the role of the medial thalamus in different aspects of cognitive function. The mediodorsal nucleus of the thalamus (MD), by virtue of its connectivity with the frontal cortex, has been implicated in an array of cognitive functions. Rather than serving as an engine or relay for the prefrontal cortex, this area seems to be more specifically involved in regulating plasticity and flexibility of prefrontal-dependent cognitive functions. Focal damage to MD may also exacerbate the effects of damage to other subcortical relays. Thus, a wide range of distributed circuits and cognitive functions may be disrupted from focal damage within the medial thalamus (for example as a consequence of stroke or brain injury). Conversely, this region may make an interesting target for neuromodulation of cognitive function via deep brain stimulation or related methods, in conditions associated with dysfunction of these neural circuits. PMID:23964206

Mediodorsal thalamus and cognition in non-human primates.

PubMed

Baxter, Mark G

2013-01-01

Several recent studies in non-human primates have provided new insights into the role of the medial thalamus in different aspects of cognitive function. The mediodorsal nucleus of the thalamus (MD), by virtue of its connectivity with the frontal cortex, has been implicated in an array of cognitive functions. Rather than serving as an engine or relay for the prefrontal cortex, this area seems to be more specifically involved in regulating plasticity and flexibility of prefrontal-dependent cognitive functions. Focal damage to MD may also exacerbate the effects of damage to other subcortical relays. Thus, a wide range of distributed circuits and cognitive functions may be disrupted from focal damage within the medial thalamus (for example as a consequence of stroke or brain injury). Conversely, this region may make an interesting target for neuromodulation of cognitive function via deep brain stimulation or related methods, in conditions associated with dysfunction of these neural circuits.

Bidirectional global spontaneous network activity precedes the canonical unidirectional circuit organization in the developing hippocampus.

PubMed

Shi, Yulin; Ikrar, Taruna; Olivas, Nicholas D; Xu, Xiangmin

2014-06-15

Spontaneous network activity is believed to sculpt developing neural circuits. Spontaneous giant depolarizing potentials (GDPs) were first identified with single-cell recordings from rat CA3 pyramidal neurons, but here we identify and characterize a large-scale spontaneous network activity we term global network activation (GNA) in the developing mouse hippocampal slices, which is measured macroscopically by fast voltage-sensitive dye imaging. The initiation and propagation of GNA in the mouse is largely GABA-independent and dominated by glutamatergic transmission via AMPA receptors. Despite the fact that signal propagation in the adult hippocampus is strongly unidirectional through the canonical trisynaptic circuit (dentate gyrus [DG] to CA3 to CA1), spontaneous GNA in the developing hippocampus originates in distal CA3 and propagates both forward to CA1 and backward to DG. Photostimulation-evoked GNA also shows prominent backward propagation in the developing hippocampus from CA3 to DG. Mouse GNA is strongly correlated to electrophysiological recordings of highly localized single-cell and local field potential events. Photostimulation mapping of neural circuitry demonstrates that the enhancement of local circuit connections to excitatory pyramidal neurons occurs over the same time course as GNA and reveals the underlying pathways accounting for GNA backward propagation from CA3 to DG. The disappearance of GNA coincides with a transition to the adult-like unidirectional circuit organization at about 2 weeks of age. Taken together, our findings strongly suggest a critical link between GNA activity and maturation of functional circuit connections in the developing hippocampus. Copyright © 2013 Wiley Periodicals, Inc.

Optogenetics in preclinical neuroscience and psychiatry research: recent insights and potential applications.

PubMed

McDevitt, Ross A; Reed, Sean J; Britt, Jonathan P

2014-01-01

There have been significant advances in the treatment of psychiatric disease in the last half century, but it is still unclear which neural circuits are ultimately responsible for specific disease states. Fortunately, technical limitations that have constrained this research have recently been mitigated by advances in research tools that facilitate circuit-based analyses. The most prominent of these tools is optogenetics, which refers to the use of genetically encoded, light-sensitive proteins that can be used to manipulate discrete neural circuits with temporal precision. Optogenetics has recently been used to examine the neural underpinnings of both psychiatric disease and symptom relief, and this research has rapidly identified novel therapeutic targets for what could be a new generation of rational drug development. As these and related methodologies for controlling neurons ultimately make their way into the clinic, circuit-based strategies for alleviating psychiatric symptoms could become a remarkably refined approach to disease treatment.

History of winning remodels thalamo-PFC circuit to reinforce social dominance.

PubMed

Zhou, Tingting; Zhu, Hong; Fan, Zhengxiao; Wang, Fei; Chen, Yang; Liang, Hexing; Yang, Zhongfei; Zhang, Lu; Lin, Longnian; Zhan, Yang; Wang, Zheng; Hu, Hailan

2017-07-14

Mental strength and history of winning play an important role in the determination of social dominance. However, the neural circuits mediating these intrinsic and extrinsic factors have remained unclear. Working in mice, we identified a dorsomedial prefrontal cortex (dmPFC) neural population showing "effort"-related firing during moment-to-moment competition in the dominance tube test. Activation or inhibition of the dmPFC induces instant winning or losing, respectively. In vivo optogenetic-based long-term potentiation and depression experiments establish that the mediodorsal thalamic input to the dmPFC mediates long-lasting changes in the social dominance status that are affected by history of winning. The same neural circuit also underlies transfer of dominance between different social contests. These results provide a framework for understanding the circuit basis of adaptive and pathological social behaviors. Copyright © 2017, American Association for the Advancement of Science.

Neural electrical activity and neural network growth.

PubMed

Gafarov, F M

2018-05-01

The development of central and peripheral neural system depends in part on the emergence of the correct functional connectivity in its input and output pathways. Now it is generally accepted that molecular factors guide neurons to establish a primary scaffold that undergoes activity-dependent refinement for building a fully functional circuit. However, a number of experimental results obtained recently shows that the neuronal electrical activity plays an important role in the establishing of initial interneuronal connections. Nevertheless, these processes are rather difficult to study experimentally, due to the absence of theoretical description and quantitative parameters for estimation of the neuronal activity influence on growth in neural networks. In this work we propose a general framework for a theoretical description of the activity-dependent neural network growth. The theoretical description incorporates a closed-loop growth model in which the neural activity can affect neurite outgrowth, which in turn can affect neural activity. We carried out the detailed quantitative analysis of spatiotemporal activity patterns and studied the relationship between individual cells and the network as a whole to explore the relationship between developing connectivity and activity patterns. The model, developed in this work will allow us to develop new experimental techniques for studying and quantifying the influence of the neuronal activity on growth processes in neural networks and may lead to a novel techniques for constructing large-scale neural networks by self-organization. Copyright © 2018 Elsevier Ltd. All rights reserved.

Large scale in vivo recordings to study neuronal biophysics.

PubMed

Giocomo, Lisa M

2015-06-01

Over the last several years, technological advances have enabled researchers to more readily observe single-cell membrane biophysics in awake, behaving animals. Studies utilizing these technologies have provided important insights into the mechanisms generating functional neural codes in both sensory and non-sensory cortical circuits. Crucial for a deeper understanding of how membrane biophysics control circuit dynamics however, is a continued effort to move toward large scale studies of membrane biophysics, in terms of the numbers of neurons and ion channels examined. Future work faces a number of theoretical and technical challenges on this front but recent technological developments hold great promise for a larger scale understanding of how membrane biophysics contribute to circuit coding and computation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Novel Stroke Therapeutics: Unraveling Stroke Pathophysiology and Its Impact on Clinical Treatments

PubMed Central

George, Paul M.; Steinberg, Gary K.

2016-01-01

Stroke remains a leading cause of death and disability in the world. Over the past few decades our understanding of the pathophysiology of stroke has increased, but greater insight is required to advance the field of stroke recovery. Clinical treatments have improved in the acute time window, but long-term therapeutics remain limited. Complex neural circuits damaged by ischemia make restoration of function after stroke difficult. New therapeutic approaches, including cell transplantation or stimulation, focus on reestablishing these circuits through multiple mechanisms to improve circuit plasticity and remodeling. Other research targets intact networks to compensate for damaged regions. This review highlights several important mechanisms of stroke injury and describes emerging therapies aimed at improving clinical outcomes. PMID:26182415

GRAPES—Grounding representations in action, perception, and emotion systems: How object properties and categories are represented in the human brain

PubMed Central

Martin, Alex

2016-01-01

In this article, I discuss some of the latest functional neuroimaging findings on the organization of object concepts in the human brain. I argue that these data provide strong support for viewing concepts as the products of highly interactive neural circuits grounded in the action, perception, and emotion systems. The nodes of these circuits are defined by regions representing specific object properties (e.g., form, color, and motion) and thus are property-specific, rather than strictly modality-specific. How these circuits are modified by external and internal environmental demands, the distinction between representational content and format, and the grounding of abstract social concepts are also discussed. PMID:25968087

Relationships between music training, speech processing, and word learning: a network perspective.

PubMed

Elmer, Stefan; Jäncke, Lutz

2018-03-15

Numerous studies have documented the behavioral advantages conferred on professional musicians and children undergoing music training in processing speech sounds varying in the spectral and temporal dimensions. These beneficial effects have previously often been associated with local functional and structural changes in the auditory cortex (AC). However, this perspective is oversimplified, in that it does not take into account the intrinsic organization of the human brain, namely, neural networks and oscillatory dynamics. Therefore, we propose a new framework for extending these previous findings to a network perspective by integrating multimodal imaging, electrophysiology, and neural oscillations. In particular, we provide concrete examples of how functional and structural connectivity can be used to model simple neural circuits exerting a modulatory influence on AC activity. In addition, we describe how such a network approach can be used for better comprehending the beneficial effects of music training on more complex speech functions, such as word learning. © 2018 New York Academy of Sciences.

Intra- and interregional coregulation of opioid genes: broken symmetry in spinal circuits

PubMed Central

Kononenko, Olga; Galatenko, Vladimir; Andersson, Malin; Bazov, Igor; Watanabe, Hiroyuki; Zhou, Xing Wu; Iatsyshyna, Anna; Mityakina, Irina; Yakovleva, Tatiana; Sarkisyan, Daniil; Ponomarev, Igor; Krishtal, Oleg; Marklund, Niklas; Tonevitsky, Alex; Adkins, DeAnna L.; Bakalkin, Georgy

2017-01-01

Regulation of the formation and rewiring of neural circuits by neuropeptides may require coordinated production of these signaling molecules and their receptors that may be established at the transcriptional level. Here, we address this hypothesis by comparing absolute expression levels of opioid peptides with their receptors, the largest neuropeptide family, and by characterizing coexpression (transcriptionally coordinated) patterns of these genes. We demonstrated that expression patterns of opioid genes highly correlate within and across functionally and anatomically different areas. Opioid peptide genes, compared with their receptor genes, are transcribed at much greater absolute levels, which suggests formation of a neuropeptide cloud that covers the receptor-expressed circuits. Surprisingly, we found that both expression levels and the proportion of opioid receptors are strongly lateralized in the spinal cord, interregional coexpression patterns are side specific, and intraregional coexpression profiles are affected differently by left- and right-side unilateral body injury. We propose that opioid genes are regulated as interconnected components of the same molecular system distributed between distinct anatomic regions. The striking feature of this system is its asymmetric coexpression patterns, which suggest side-specific regulation of selective neural circuits by opioid neurohormones.—Kononenko, O., Galatenko, V., Andersson, M., Bazov, I., Watanabe, H., Zhou, X. W., Iatsyshyna, A., Mityakina, I., Yakovleva, T., Sarkisyan, D., Ponomarev, I., Krishtal, O., Marklund, N., Tonevitsky, A., Adkins, D. L., Bakalkin, G. Intra- and interregional coregulation of opioid genes: broken symmetry in spinal circuits. PMID:28122917

Nanotools for Neuroscience and Brain Activity Mapping

PubMed Central

Alivisatos, A. Paul; Andrews, Anne M.; Boyden, Edward S.; Chun, Miyoung; Church, George M.; Deisseroth, Karl; Donoghue, John P.; Fraser, Scott E.; Lippincott-Schwartz, Jennifer; Looger, Loren L.; Masmanidis, Sotiris; McEuen, Paul L.; Nurmikko, Arto V.; Park, Hongkun; Peterka, Darcy S.; Reid, Clay; Roukes, Michael L.; Scherer, Axel; Schnitzer, Mark; Sejnowski, Terrence J.; Shepard, Kenneth L.; Tsao, Doris; Turrigiano, Gina; Weiss, Paul S.; Xu, Chris; Yuste, Rafael; Zhuang, Xiaowei

2013-01-01

Neuroscience is at a crossroads. Great effort is being invested into deciphering specific neural interactions and circuits. At the same time, there exist few general theories or principles that explain brain function. We attribute this disparity, in part, to limitations in current methodologies. Traditional neurophysiological approaches record the activities of one neuron or a few neurons at a time. Neurochemical approaches focus on single neurotransmitters. Yet, there is an increasing realization that neural circuits operate at emergent levels, where the interactions between hundreds or thousands of neurons, utilizing multiple chemical transmitters, generate functional states. Brains function at the nanoscale, so tools to study brains must ultimately operate at this scale, as well. Nanoscience and nanotechnology are poised to provide a rich toolkit of novel methods to explore brain function by enabling simultaneous measurement and manipulation of activity of thousands or even millions of neurons. We and others refer to this goal as the Brain Activity Mapping Project. In this Nano Focus, we discuss how recent developments in nanoscale analysis tools and in the design and synthesis of nanomaterials have generated optical, electrical, and chemical methods that can readily be adapted for use in neuroscience. These approaches represent exciting areas of technical development and research. Moreover, unique opportunities exist for nanoscientists, nanotechnologists, and other physical scientists and engineers to contribute to tackling the challenging problems involved in understanding the fundamentals of brain function. PMID:23514423

The Vite Model: A Neural Command Circuit for Generating Arm and Articulator Trajectories,

DTIC Science & Technology

1988-03-01

Principles of Learning, Perception, Development , Cognition , and Motor Control. Boston: Reidel Press, (1982). Grossberg, S . and Kuperstein, M., Neural...AD-RI92 705 THE YITE MODEL: A NEURAL COMMAND CIRCUIT FO R .# GENERATING ARM AND ARTUCULA..(U) BOSTON UNJY MA CENTER FOR ADAPTIVE SYSTEMS S GROSSUERO...and Articulator Trajectories 6 EFRIGOG EOTNME 7. AUTHOR( s ) 5. CONTRACT OR GRANT NUMBER( s ) Stephen Grossberg XM- F49620-86-C-0O37 Daniel Bullock 9. S

Acute neuroinflammation impairs context discrimination memory and disrupts pattern separation processes in hippocampus.

PubMed

Czerniawski, Jennifer; Guzowski, John F

2014-09-10

Although it is known that immune system activation can impair cognition, no study to date has linked cognitive deficits during acute neuroinflammation to dysregulation of task-relevant neuronal ensemble activity. Here, we assessed both neural circuit activity and context discrimination memory retrieval, in a within-subjects design, of male rats given systemic administration of saline or lipopolysaccharide (LPS). Rats were exposed over several days to two similar contexts: one of which was paired with weak foot shock and the other was not. After reaching criteria for discriminative freezing, rats were given systemic LPS or saline injection and tested for retrieval of context discrimination 6 h later. Importantly, LPS administration produced an acute neuroinflammatory response in dorsal hippocampus at this time (as assessed by elevation of proinflammatory cytokine mRNA levels) and abolished retrieval of the previously acquired discrimination. The impact of neuroinflammation on hippocampal CA3 and CA1 neural circuit activity was assessed using the Arc/Homer1a cellular analysis of temporal activity by fluorescence in situ hybridization imaging method. Whereas the saline-treated subjects discriminated and had low overlap of hippocampal ensembles activated in the two contexts, LPS-treated subjects did not discriminate and had greater ensemble overlap (i.e., reduced orthogonalization). Additionally, retrieval of standard contextual fear conditioning, which does not require context discrimination, was not affected by pretesting LPS administration. Together, the behavioral and circuit analyses data provide compelling evidence that LPS administration impairs context discrimination memory by disrupting cellular pattern separation processes within the hippocampus, thus linking acute neuroinflammation to disruption of specific neural circuit functions and cognitive impairment. Copyright © 2014 the authors 0270-6474/14/3412470-11$15.00/0.

Acute Neuroinflammation Impairs Context Discrimination Memory and Disrupts Pattern Separation Processes in Hippocampus

PubMed Central

Czerniawski, Jennifer

2014-01-01

Although it is known that immune system activation can impair cognition, no study to date has linked cognitive deficits during acute neuroinflammation to dysregulation of task-relevant neuronal ensemble activity. Here, we assessed both neural circuit activity and context discrimination memory retrieval, in a within-subjects design, of male rats given systemic administration of saline or lipopolysaccharide (LPS). Rats were exposed over several days to two similar contexts: one of which was paired with weak foot shock and the other was not. After reaching criteria for discriminative freezing, rats were given systemic LPS or saline injection and tested for retrieval of context discrimination 6 h later. Importantly, LPS administration produced an acute neuroinflammatory response in dorsal hippocampus at this time (as assessed by elevation of proinflammatory cytokine mRNA levels) and abolished retrieval of the previously acquired discrimination. The impact of neuroinflammation on hippocampal CA3 and CA1 neural circuit activity was assessed using the Arc/Homer1a cellular analysis of temporal activity by fluorescence in situ hybridization imaging method. Whereas the saline-treated subjects discriminated and had low overlap of hippocampal ensembles activated in the two contexts, LPS-treated subjects did not discriminate and had greater ensemble overlap (i.e., reduced orthogonalization). Additionally, retrieval of standard contextual fear conditioning, which does not require context discrimination, was not affected by pretesting LPS administration. Together, the behavioral and circuit analyses data provide compelling evidence that LPS administration impairs context discrimination memory by disrupting cellular pattern separation processes within the hippocampus, thus linking acute neuroinflammation to disruption of specific neural circuit functions and cognitive impairment. PMID:25209285

CMOS-based Stochastically Spiking Neural Network for Optimization under Uncertainties

DTIC Science & Technology

2017-03-01

inverse tangent characteristics at varying input voltage (VIN) [Fig. 3], thereby it is suitable for Kernel function implementation. By varying bias...cost function/constraint variables are generated based on inverse transform on CDF. In Fig. 5, F-1(u) for uniformly distributed random number u [0, 1...extracts random samples of x varying with CDF of F(x). In Fig. 6, we present a successive approximation (SA) circuit to evaluate inverse

Long-Term Memory Shapes the Primary Olfactory Center of an Insect Brain

ERIC Educational Resources Information Center

Hourcade, Benoit; Perisse, Emmanuel; Devaud, Jean-Marc; Sandoz, Jean-Christophe

2009-01-01

The storage of stable memories is generally considered to rely on changes in the functional properties and/or the synaptic connectivity of neural networks. However, these changes are not easily tractable given the complexity of the learning procedures and brain circuits studied. Such a search can be narrowed down by studying memories of specific…

Micropower circuits for bidirectional wireless telemetry in neural recording applications.

PubMed

Neihart, Nathan M; Harrison, Reid R

2005-11-01

State-of-the art neural recording systems require electronics allowing for transcutaneous, bidirectional data transfer. As these circuits will be implanted near the brain, they must be small and low power. We have developed micropower integrated circuits for recovering clock and data signals over a transcutaneous power link. The data recovery circuit produces a digital data signal from an ac power waveform that has been amplitude modulated. We have also developed an FM transmitter with the lowest power dissipation reported for biosignal telemetry. The FM transmitter consists of a low-noise biopotential amplifier and a voltage controlled oscillator used to transmit amplified neural signals at a frequency near 433 MHz. All circuits were fabricated in a standard 0.5-microm CMOS VLSI process. The resulting chip is powered through a wireless inductive link. The power consumption of the clock and data recovery circuits is measured to be 129 microW; the power consumption of the transmitter is measured to be 465 microW when using an external surface mount inductor. Using a parasitic antenna less than 2 mm long, a received power level was measured to be -59.73 dBm at a distance of one meter.

Evolution of behavior and neural control of the fast-start escape response.

PubMed

Hale, Melina E; Long, John H; McHenry, Matthew J; Westneat, Mark W

2002-05-01

The fast-start startle behavior is the primary mechanism of rapid escape in fishes and is a model system for examining neural circuit design and musculoskeletal function. To develop a dataset for evolutionary analysis of the startle response, the kinematics and muscle activity patterns of the fast-start were analyzed for four fish species at key branches in the phylogeny of vertebrates. Three of these species (Polypterus palmas, Lepisosteus osseus, and Amia calva) represent the base of the actinopterygian radiation. A fourth species (Oncorhynchus mykiss) provided data for a species in the central region of the teleost phylogeny. Using these data, we explored the evolution of this behavior within the phylogeny of vertebrates. To test the hypothesis that startle features are evolutionarily conservative, the variability of motor patterns and kinematics in fast-starts was described. Results show that the evolution of the startle behavior in fishes, and more broadly among vertebrates, is not conservative. The fast-start has undergone substantial change in suites of kinematics and electromyogram features, including the presence of either a one- or a two-stage kinematic response and change in the extent of bilateral muscle activity. Comparative methods were used to test the evolutionary hypothesis that changes in motor control are correlated with key differences in the kinematics and behavior of the fast-start. Significant evolutionary correlations were found between several motor pattern and behavioral characters. These results suggest that the startle neural circuit itself is not conservative. By tracing the evolution of motor pattern and kinematics on a phylogeny, it is shown that major changes in the neural circuit of the startle behavior occur at several levels in the phylogeny of vertebrates.

Development Switch in Neural Circuitry Underlying Odor-Malaise Learning

ERIC Educational Resources Information Center

Lunday, Lauren; Miner, Cathrine; Roth, Tania L.; Sullivan, Regina M.; Shionoya, Kiseko; Moriceau, Stephanie

2006-01-01

Fetal and infant rats can learn to avoid odors paired with illness before development of brain areas supporting this learning in adults, suggesting an alternate learning circuit. Here we begin to document the transition from the infant to adult neural circuit underlying odor-malaise avoidance learning using LiCl (0.3 M; 1% of body weight, ip) and…

Energy-efficient neural information processing in individual neurons and neuronal networks.

PubMed

Yu, Lianchun; Yu, Yuguo

2017-11-01

Brains are composed of networks of an enormous number of neurons interconnected with synapses. Neural information is carried by the electrical signals within neurons and the chemical signals among neurons. Generating these electrical and chemical signals is metabolically expensive. The fundamental issue raised here is whether brains have evolved efficient ways of developing an energy-efficient neural code from the molecular level to the circuit level. Here, we summarize the factors and biophysical mechanisms that could contribute to the energy-efficient neural code for processing input signals. The factors range from ion channel kinetics, body temperature, axonal propagation of action potentials, low-probability release of synaptic neurotransmitters, optimal input and noise, the size of neurons and neuronal clusters, excitation/inhibition balance, coding strategy, cortical wiring, and the organization of functional connectivity. Both experimental and computational evidence suggests that neural systems may use these factors to maximize the efficiency of energy consumption in processing neural signals. Studies indicate that efficient energy utilization may be universal in neuronal systems as an evolutionary consequence of the pressure of limited energy. As a result, neuronal connections may be wired in a highly economical manner to lower energy costs and space. Individual neurons within a network may encode independent stimulus components to allow a minimal number of neurons to represent whole stimulus characteristics efficiently. This basic principle may fundamentally change our view of how billions of neurons organize themselves into complex circuits to operate and generate the most powerful intelligent cognition in nature. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

A systematic review of the neural bases of psychotherapy for anxiety and related disorders

PubMed Central

Brooks, Samantha J.; Stein, Dan J.

2015-01-01

Brain imaging studies over two decades have delineated the neural circuitry of anxiety and related disorders, particularly regions involved in fear processing and in obsessive-compulsive symptoms. The neural circuitry of fear processing involves the amygdala, anterior cingulate, and insular cortex, while cortico-striatal-thalamic circuitry plays a key role in obsessive-compulsive disorder. More recently, neuroimaging studies have examined how psychotherapy for anxiety and related disorders impacts on these neural circuits. Here we conduct a systematic review of the findings of such work, which yielded 19 functional magnetic resonance imaging studies examining the neural bases of cognitive-behavioral therapy (CBT) in 509 patients with anxiety and related disorders. We conclude that, although each of these related disorders is mediated by somewhat different neural circuitry, CBT may act in a similar way to increase prefrontal control of subcortical structures. These findings are consistent with an emphasis in cognitive-affective neuroscience on the potential therapeutic value of enhancing emotional regulation in various psychiatric conditions. PMID:26487807

A systematic review of the neural bases of psychotherapy for anxiety and related disorders.

PubMed

Brooks, Samantha J; Stein, Dan J

2015-09-01

Brain imaging studies over two decades have delineated the neural circuitry of anxiety and related disorders, particularly regions involved in fear processing and in obsessive-compulsive symptoms. The neural circuitry of fear processing involves the amygdala, anterior cingulate, and insular cortex, while cortico-striatal-thalamic circuitry plays a key role in obsessive-compulsive disorder. More recently, neuroimaging studies have examined how psychotherapy for anxiety and related disorders impacts on these neural circuits. Here we conduct a systematic review of the findings of such work, which yielded 19 functional magnetic resonance imaging studies examining the neural bases of cognitive-behavioral therapy (CBT) in 509 patients with anxiety and related disorders. We conclude that, although each of these related disorders is mediated by somewhat different neural circuitry, CBT may act in a similar way to increase prefrontal control of subcortical structures. These findings are consistent with an emphasis in cognitive-affective neuroscience on the potential therapeutic value of enhancing emotional regulation in various psychiatric conditions.

Integrative approaches for modeling regulation and function of the respiratory system.

PubMed

Ben-Tal, Alona; Tawhai, Merryn H

2013-01-01

Mathematical models have been central to understanding the interaction between neural control and breathing. Models of the entire respiratory system-which comprises the lungs and the neural circuitry that controls their ventilation-have been derived using simplifying assumptions to compartmentalize each component of the system and to define the interactions between components. These full system models often rely-through necessity-on empirically derived relationships or parameters, in addition to physiological values. In parallel with the development of whole respiratory system models are mathematical models that focus on furthering a detailed understanding of the neural control network, or of the several functions that contribute to gas exchange within the lung. These models are biophysically based, and rely on physiological parameters. They include single-unit models for a breathing lung or neural circuit, through to spatially distributed models of ventilation and perfusion, or multicircuit models for neural control. The challenge is to bring together these more recent advances in models of neural control with models of lung function, into a full simulation for the respiratory system that builds upon the more detailed models but remains computationally tractable. This requires first understanding the mathematical models that have been developed for the respiratory system at different levels, and which could be used to study how physiological levels of O2 and CO2 in the blood are maintained. Copyright © 2013 Wiley Periodicals, Inc.

Optogenetic Activation of Zebrafish Somatosensory Neurons using ChEF-tdTomato

PubMed Central

Palanca, Ana Marie S.; Sagasti, Alvaro

2013-01-01

Larval zebrafish are emerging as a model for describing the development and function of simple neural circuits. Due to their external fertilization, rapid development, and translucency, zebrafish are particularly well suited for optogenetic approaches to investigate neural circuit function. In this approach, light-sensitive ion channels are expressed in specific neurons, enabling the experimenter to activate or inhibit them at will and thus assess their contribution to specific behaviors. Applying these methods in larval zebrafish is conceptually simple but requires the optimization of technical details. Here we demonstrate a procedure for expressing a channelrhodopsin variant in larval zebrafish somatosensory neurons, photo-activating single cells, and recording the resulting behaviors. By introducing a few modifications to previously established methods, this approach could be used to elicit behavioral responses from single neurons activated up to at least 4 days post-fertilization (dpf). Specifically, we created a transgene using a somatosensory neuron enhancer, CREST3, to drive the expression of the tagged channelrhodopsin variant, ChEF-tdTomato. Injecting this transgene into 1-cell stage embryos results in mosaic expression in somatosensory neurons, which can be imaged with confocal microscopy. Illuminating identified cells in these animals with light from a 473 nm DPSS laser, guided through a fiber optic cable, elicits behaviors that can be recorded with a high-speed video camera and analyzed quantitatively. This technique could be adapted to study behaviors elicited by activating any zebrafish neuron. Combining this approach with genetic or pharmacological perturbations will be a powerful way to investigate circuit formation and function. PMID:23407374

Searching for memories, Sudoku, implicit check bits, and the iterative use of not-always-correct rapid neural computation.

PubMed

Hopfield, J J

2008-05-01

The algorithms that simple feedback neural circuits representing a brain area can rapidly carry out are often adequate to solve easy problems but for more difficult problems can return incorrect answers. A new excitatory-inhibitory circuit model of associative memory displays the common human problem of failing to rapidly find a memory when only a small clue is present. The memory model and a related computational network for solving Sudoku puzzles produce answers that contain implicit check bits in the representation of information across neurons, allowing a rapid evaluation of whether the putative answer is correct or incorrect through a computation related to visual pop-out. This fact may account for our strong psychological feeling of right or wrong when we retrieve a nominal memory from a minimal clue. This information allows more difficult computations or memory retrievals to be done in a serial fashion by using the fast but limited capabilities of a computational module multiple times. The mathematics of the excitatory-inhibitory circuits for associative memory and for Sudoku, both of which are understood in terms of energy or Lyapunov functions, is described in detail.

Pathological circuit function underlying addiction and anxiety disorders.

PubMed

Lüthi, Andreas; Lüscher, Christian

2014-12-01

Current models of addiction and anxiety stem from the idea that aberrant function and remodeling of neural circuits cause the pathological behaviors. According to this hypothesis, a disease-defining experience (for example, drug reward or stress) would trigger specific forms of synaptic plasticity, which in susceptible subjects would become persistent and lead to the disease. While the notion of synaptic diseases has received much attention, no candidate disorder has been sufficiently investigated to yield new, rational therapies that could be tested in the clinic. Here we review the arguments in favor of abnormal neuronal plasticity underlying addiction and anxiety disorders, with a focus on the functional diversity of neurons that make up the circuits involved. We argue that future research must strive to obtain a comprehensive description of the relevant functional anatomy. This will allow identification of molecular mechanisms that govern the induction and expression of disease-relevant plasticity in identified neurons. To establish causality, one will have to test whether normalization of function can reverse pathological behavior. With these elements in hand, it will be possible to propose blueprints for manipulations to be tested in translational studies. The challenge is daunting, but new techniques, above all optogenetics, may enable decisive advances.

Improved Estimation and Interpretation of Correlations in Neural Circuits

PubMed Central

Yatsenko, Dimitri; Josić, Krešimir; Ecker, Alexander S.; Froudarakis, Emmanouil; Cotton, R. James; Tolias, Andreas S.

2015-01-01

Ambitious projects aim to record the activity of ever larger and denser neuronal populations in vivo. Correlations in neural activity measured in such recordings can reveal important aspects of neural circuit organization. However, estimating and interpreting large correlation matrices is statistically challenging. Estimation can be improved by regularization, i.e. by imposing a structure on the estimate. The amount of improvement depends on how closely the assumed structure represents dependencies in the data. Therefore, the selection of the most efficient correlation matrix estimator for a given neural circuit must be determined empirically. Importantly, the identity and structure of the most efficient estimator informs about the types of dominant dependencies governing the system. We sought statistically efficient estimators of neural correlation matrices in recordings from large, dense groups of cortical neurons. Using fast 3D random-access laser scanning microscopy of calcium signals, we recorded the activity of nearly every neuron in volumes 200 μm wide and 100 μm deep (150–350 cells) in mouse visual cortex. We hypothesized that in these densely sampled recordings, the correlation matrix should be best modeled as the combination of a sparse graph of pairwise partial correlations representing local interactions and a low-rank component representing common fluctuations and external inputs. Indeed, in cross-validation tests, the covariance matrix estimator with this structure consistently outperformed other regularized estimators. The sparse component of the estimate defined a graph of interactions. These interactions reflected the physical distances and orientation tuning properties of cells: The density of positive ‘excitatory’ interactions decreased rapidly with geometric distances and with differences in orientation preference whereas negative ‘inhibitory’ interactions were less selective. Because of its superior performance, this ‘sparse+latent’ estimator likely provides a more physiologically relevant representation of the functional connectivity in densely sampled recordings than the sample correlation matrix. PMID:25826696

Family of new operations equivalency of neuro-fuzzy logic: optoelectronic realization and applications

NASA Astrophysics Data System (ADS)

Krasilenko, Vladimir G.; Nikolsky, Alexander I.; Yatskovsky, Victor I.; Ogorodnik, K. V.; Lischenko, Sergey

2002-07-01

The perspective of neural networks equivalental models (EM) base on vector-matrix procedure with basic operations of continuous and neuro-fuzzy logic (equivalence, absolute difference) are shown. Capacity on base EMs exceeded the amount of neurons in 2.5 times. This is larger than others neural networks paradigms. Amount neurons of this neural networks on base EMs may be 10 - 20 thousands. The base operations in EMs are normalized equivalency operations. The family of new operations equivalency and non-equivalency of neuro-fuzzy logic's, which we have elaborated on the based of such generalized operations of fuzzy-logic's as fuzzy negation, t-norm and s-norm are shown. Generalized rules of construction of new functions (operations) equivalency which uses relations of t-norm and s-norm to fuzzy negation are proposed. Among these elements the following should be underlined: (1) the element which fulfills the operation of limited difference; (2) the element which algebraic product (intensifier with controlled coefficient of transmission or multiplier of analog signals); (3) the element which fulfills a sample summarizing (uniting) of signals (including the one during normalizing). Synthesized structures which realize on the basic of these elements the whole spectrum of required operations: t-norm, s-norm and new operations equivalency are shown. These realization on the basic of new multifunctional optoelectronical BISPIN- devices (MOEBD) represent the circuit with constant and pulse optical input signals. They are modeling the operation of limited difference. These circuits realize frequency- dynamic neuron models and neural networks. Experimental results of these MOEBD and equivalency circuits, which fulfill the limited difference operation are discussed. For effective realization of neural networks on the basic of EMs as it is shown in report, picture elements are required as main nodes to implement element operations equivalence ('non-equivalence') of neuro-fuzzy logic's.

Dendritic nonlinearities are tuned for efficient spike-based computations in cortical circuits.

PubMed

Ujfalussy, Balázs B; Makara, Judit K; Branco, Tiago; Lengyel, Máté

2015-12-24

Cortical neurons integrate thousands of synaptic inputs in their dendrites in highly nonlinear ways. It is unknown how these dendritic nonlinearities in individual cells contribute to computations at the level of neural circuits. Here, we show that dendritic nonlinearities are critical for the efficient integration of synaptic inputs in circuits performing analog computations with spiking neurons. We developed a theory that formalizes how a neuron's dendritic nonlinearity that is optimal for integrating synaptic inputs depends on the statistics of its presynaptic activity patterns. Based on their in vivo preynaptic population statistics (firing rates, membrane potential fluctuations, and correlations due to ensemble dynamics), our theory accurately predicted the responses of two different types of cortical pyramidal cells to patterned stimulation by two-photon glutamate uncaging. These results reveal a new computational principle underlying dendritic integration in cortical neurons by suggesting a functional link between cellular and systems--level properties of cortical circuits.

BK channels are required for multisensory plasticity in the oculomotor system

PubMed Central

Nelson, Alexandra; Faulstich, Michael; Moghadam, Setareh; Onori, Kimberly; Meredith, Andrea; du Lac, Sascha

2017-01-01

SUMMARY Neural circuits are endowed with several forms of intrinsic and synaptic plasticity that could contribute to adaptive changes in behavior, but circuit complexities have hindered linking specific cellular mechanisms with their behavioral consequences. Eye movements generated by simple brainstem circuits provide a means for relating cellular plasticity to behavioral gain control. Here we show that firing rate potentiation, a form of intrinsic plasticity mediated by reductions in BK-type calcium activated potassium currents in spontaneously firing neurons, is engaged during optokinetic reflex compensation for inner ear dysfunction. Vestibular loss triggers transient increases in postsynaptic excitability, occlusion of firing rate potentiation, and reductions in BK currents in vestibular nucleus neurons. Concurrently, adaptive increases in visually-evoked eye movements rapidly restore oculomotor function in wildtype mice but are profoundly impaired in BK channel null mice. Activity-dependent regulation of intrinsic excitability may be a general mechanism for adaptive control of behavioral output in multisensory circuits. PMID:27989457

Role of Neurotrophins in the Development and Function of Neural Circuits that Regulate Energy Homeostasis

PubMed Central

Fargali, Samira; Sadahiro, Masato; Jiang, Cheng; Frick, Amy L.; Indall, Tricia; Cogliani, Valeria; Welagen, Jelle; Lin, Wei-jye; Salton, Stephen R.

2012-01-01

Members of the neurotrophin family, including nerve growth factor (NGF), brain-derived neurotrophic factor (BDNF), neurotrophin-3 (NT-3), and neurotrophin-4/5 (NT-4/5), and other neurotrophic growth factors such as ciliary neurotrophic factor (CNTF) and artemin, regulate peripheral and central nervous system development and function. A subset of the neurotrophin-dependent pathways in the hypothalamus, brainstem, and spinal cord, and those that project via the sympathetic nervous system to peripheral metabolic tissues including brown and white adipose tissue (BAT and WAT), muscle and liver, regulate feeding, energy storage, and energy expenditure. We briefly review the role that neurotrophic growth factors play in energy balance, as regulators of neuronal survival and differentiation, neurogenesis, and circuit formation and function, and as inducers of critical gene products that control energy homeostasis. PMID:22581449

On the origin of reproducible sequential activity in neural circuits

NASA Astrophysics Data System (ADS)

Afraimovich, V. S.; Zhigulin, V. P.; Rabinovich, M. I.

2004-12-01

Robustness and reproducibility of sequential spatio-temporal responses is an essential feature of many neural circuits in sensory and motor systems of animals. The most common mathematical images of dynamical regimes in neural systems are fixed points, limit cycles, chaotic attractors, and continuous attractors (attractive manifolds of neutrally stable fixed points). These are not suitable for the description of reproducible transient sequential neural dynamics. In this paper we present the concept of a stable heteroclinic sequence (SHS), which is not an attractor. SHS opens the way for understanding and modeling of transient sequential activity in neural circuits. We show that this new mathematical object can be used to describe robust and reproducible sequential neural dynamics. Using the framework of a generalized high-dimensional Lotka-Volterra model, that describes the dynamics of firing rates in an inhibitory network, we present analytical results on the existence of the SHS in the phase space of the network. With the help of numerical simulations we confirm its robustness in presence of noise in spite of the transient nature of the corresponding trajectories. Finally, by referring to several recent neurobiological experiments, we discuss possible applications of this new concept to several problems in neuroscience.

On the origin of reproducible sequential activity in neural circuits.

PubMed

Afraimovich, V S; Zhigulin, V P; Rabinovich, M I

2004-12-01

Robustness and reproducibility of sequential spatio-temporal responses is an essential feature of many neural circuits in sensory and motor systems of animals. The most common mathematical images of dynamical regimes in neural systems are fixed points, limit cycles, chaotic attractors, and continuous attractors (attractive manifolds of neutrally stable fixed points). These are not suitable for the description of reproducible transient sequential neural dynamics. In this paper we present the concept of a stable heteroclinic sequence (SHS), which is not an attractor. SHS opens the way for understanding and modeling of transient sequential activity in neural circuits. We show that this new mathematical object can be used to describe robust and reproducible sequential neural dynamics. Using the framework of a generalized high-dimensional Lotka-Volterra model, that describes the dynamics of firing rates in an inhibitory network, we present analytical results on the existence of the SHS in the phase space of the network. With the help of numerical simulations we confirm its robustness in presence of noise in spite of the transient nature of the corresponding trajectories. Finally, by referring to several recent neurobiological experiments, we discuss possible applications of this new concept to several problems in neuroscience.

Light, heat, action: neural control of fruit fly behaviour.

PubMed

Owald, David; Lin, Suewei; Waddell, Scott

2015-09-19

The fruit fly Drosophila melanogaster has emerged as a popular model to investigate fundamental principles of neural circuit operation. The sophisticated genetics and small brain permit a cellular resolution understanding of innate and learned behavioural processes. Relatively recent genetic and technical advances provide the means to specifically and reproducibly manipulate the function of many fly neurons with temporal resolution. The same cellular precision can also be exploited to express genetically encoded reporters of neural activity and cell-signalling pathways. Combining these approaches in living behaving animals has great potential to generate a holistic view of behavioural control that transcends the usual molecular, cellular and systems boundaries. In this review, we discuss these approaches with particular emphasis on the pioneering studies and those involving learning and memory.

Bio-Inspired Neural Model for Learning Dynamic Models

NASA Technical Reports Server (NTRS)

Duong, Tuan; Duong, Vu; Suri, Ronald

2009-01-01

A neural-network mathematical model that, relative to prior such models, places greater emphasis on some of the temporal aspects of real neural physical processes, has been proposed as a basis for massively parallel, distributed algorithms that learn dynamic models of possibly complex external processes by means of learning rules that are local in space and time. The algorithms could be made to perform such functions as recognition and prediction of words in speech and of objects depicted in video images. The approach embodied in this model is said to be "hardware-friendly" in the following sense: The algorithms would be amenable to execution by special-purpose computers implemented as very-large-scale integrated (VLSI) circuits that would operate at relatively high speeds and low power demands.

Connecting a Connectome to Behavior: An Ensemble of Neuroanatomical Models of C. elegans Klinotaxis

PubMed Central

Izquierdo, Eduardo J.; Beer, Randall D.

2013-01-01

Increased efforts in the assembly and analysis of connectome data are providing new insights into the principles underlying the connectivity of neural circuits. However, despite these considerable advances in connectomics, neuroanatomical data must be integrated with neurophysiological and behavioral data in order to obtain a complete picture of neural function. Due to its nearly complete wiring diagram and large behavioral repertoire, the nematode worm Caenorhaditis elegans is an ideal organism in which to explore in detail this link between neural connectivity and behavior. In this paper, we develop a neuroanatomically-grounded model of salt klinotaxis, a form of chemotaxis in which changes in orientation are directed towards the source through gradual continual adjustments. We identify a minimal klinotaxis circuit by systematically searching the C. elegans connectome for pathways linking chemosensory neurons to neck motor neurons, and prune the resulting network based on both experimental considerations and several simplifying assumptions. We then use an evolutionary algorithm to find possible values for the unknown electrophsyiological parameters in the network such that the behavioral performance of the entire model is optimized to match that of the animal. Multiple runs of the evolutionary algorithm produce an ensemble of such models. We analyze in some detail the mechanisms by which one of the best evolved circuits operates and characterize the similarities and differences between this mechanism and other solutions in the ensemble. Finally, we propose a series of experiments to determine which of these alternatives the worm may be using. PMID:23408877

Existence and global exponential stability of periodic solution to BAM neural networks with periodic coefficients and continuously distributed delays

NASA Astrophysics Data System (ADS)

Zhou, distributed delays [rapid communication] T.; Chen, A.; Zhou, Y.

2005-08-01

By using the continuation theorem of coincidence degree theory and Liapunov function, we obtain some sufficient criteria to ensure the existence and global exponential stability of periodic solution to the bidirectional associative memory (BAM) neural networks with periodic coefficients and continuously distributed delays. These results improve and generalize the works of papers [J. Cao, L. Wang, Phys. Rev. E 61 (2000) 1825] and [Z. Liu, A. Chen, J. Cao, L. Huang, IEEE Trans. Circuits Systems I 50 (2003) 1162]. An example is given to illustrate that the criteria are feasible.

Why the Brain Knows More than We Do: Non-Conscious Representations and Their Role in the Construction of Conscious Experience

PubMed Central

Dresp-Langley, Birgitta

2011-01-01

Scientific studies have shown that non-conscious stimuli and representations influence information processing during conscious experience. In the light of such evidence, questions about potential functional links between non-conscious brain representations and conscious experience arise. This article discusses neural model capable of explaining how statistical learning mechanisms in dedicated resonant circuits could generate specific temporal activity traces of non-conscious representations in the brain. How reentrant signaling, top-down matching, and statistical coincidence of such activity traces may lead to the progressive consolidation of temporal patterns that constitute the neural signatures of conscious experience in networks extending across large distances beyond functionally specialized brain regions is then explained. PMID:24962683

Signal transfer within a cultured asymmetric cortical neuron circuit

NASA Astrophysics Data System (ADS)

Isomura, Takuya; Shimba, Kenta; Takayama, Yuzo; Takeuchi, Akimasa; Kotani, Kiyoshi; Jimbo, Yasuhiko

2015-12-01

Objective. Simplified neuronal circuits are required for investigating information representation in nervous systems and for validating theoretical neural network models. Here, we developed patterned neuronal circuits using micro fabricated devices, comprising a micro-well array bonded to a microelectrode-array substrate. Approach. The micro-well array consisted of micrometre-scale wells connected by tunnels, all contained within a silicone slab called a micro-chamber. The design of the micro-chamber confined somata to the wells and allowed axons to grow through the tunnels bidirectionally but with a designed, unidirectional bias. We guided axons into the point of the arrow structure where one of the two tunnel entrances is located, making that the preferred direction. Main results. When rat cortical neurons were cultured in the wells, their axons grew through the tunnels and connected to neurons in adjoining wells. Unidirectional burst transfers and other asymmetric signal-propagation phenomena were observed via the substrate-embedded electrodes. Seventy-nine percent of burst transfers were in the forward direction. We also observed rapid propagation of activity from sites of local electrical stimulation, and significant effects of inhibitory synapse blockade on bursting activity. Significance. These results suggest that this simple, substrate-controlled neuronal circuit can be applied to develop in vitro models of the function of cortical microcircuits or deep neural networks, better to elucidate the laws governing the dynamics of neuronal networks.

The Lateral Habenula Circuitry: Reward Processing and Cognitive Control

PubMed Central

Baker, Phillip M.; Jhou, Thomas; Matsumoto, Masayuki; Mizumori, Sheri J.Y.; Stephenson-Jones, Marcus

2016-01-01

There has been a growing interest in understanding the role of the lateral habenula (LHb) in reward processing, affect regulation, and goal-directed behaviors. The LHb gets major inputs from the habenula-projecting globus pallidus and the mPFC, sending its efferents to the dopaminergic VTA and SNc, serotonergic dorsal raphe nuclei, and the GABAergic rostromedial tegmental nucleus. Recent studies have made advances in our understanding of the LHb circuit organization, yet the precise mechanisms of its involvement in complex behaviors are largely unknown. To begin to address this unresolved question, we present here emerging cross-species perspectives with a goal to provide a more refined understanding of the role of the LHb circuits in reward and cognition. We begin by highlighting recent findings from rodent experiments using optogenetics, electrophysiology, molecular, pharmacology, and tracing techniques that reveal diverse neural phenotypes in the LHb circuits that may underlie previously undescribed behavioral functions. We then discuss results from electrophysiological studies in macaques that suggest that the LHb cooperates with the anterior cingulate cortex to monitor action outcomes and signal behavioral adjustment. Finally, we provide an integrated summary of cross-species findings and discuss how further research on the connectivity, neural signaling, and physiology of the LHb circuits can deepen our understanding of the role of the LHb in normal and maladaptive behaviors associated with mental illnesses and drug abuse. PMID:27911751

Signal transfer within a cultured asymmetric cortical neuron circuit.

PubMed

Isomura, Takuya; Shimba, Kenta; Takayama, Yuzo; Takeuchi, Akimasa; Kotani, Kiyoshi; Jimbo, Yasuhiko

2015-12-01

Simplified neuronal circuits are required for investigating information representation in nervous systems and for validating theoretical neural network models. Here, we developed patterned neuronal circuits using micro fabricated devices, comprising a micro-well array bonded to a microelectrode-array substrate. The micro-well array consisted of micrometre-scale wells connected by tunnels, all contained within a silicone slab called a micro-chamber. The design of the micro-chamber confined somata to the wells and allowed axons to grow through the tunnels bidirectionally but with a designed, unidirectional bias. We guided axons into the point of the arrow structure where one of the two tunnel entrances is located, making that the preferred direction. When rat cortical neurons were cultured in the wells, their axons grew through the tunnels and connected to neurons in adjoining wells. Unidirectional burst transfers and other asymmetric signal-propagation phenomena were observed via the substrate-embedded electrodes. Seventy-nine percent of burst transfers were in the forward direction. We also observed rapid propagation of activity from sites of local electrical stimulation, and significant effects of inhibitory synapse blockade on bursting activity. These results suggest that this simple, substrate-controlled neuronal circuit can be applied to develop in vitro models of the function of cortical microcircuits or deep neural networks, better to elucidate the laws governing the dynamics of neuronal networks.

A comparative examination of neural circuit and brain patterning between the lamprey and amphioxus reveals the evolutionary origin of the vertebrate visual center.

PubMed

Suzuki, Daichi G; Murakami, Yasunori; Escriva, Hector; Wada, Hiroshi

2015-02-01

Vertebrates are equipped with so-called camera eyes, which provide them with image-forming vision. Vertebrate image-forming vision evolved independently from that of other animals and is regarded as a key innovation for enhancing predatory ability and ecological success. Evolutionary changes in the neural circuits, particularly the visual center, were central for the acquisition of image-forming vision. However, the evolutionary steps, from protochordates to jaw-less primitive vertebrates and then to jawed vertebrates, remain largely unknown. To bridge this gap, we present the detailed development of retinofugal projections in the lamprey, the neuroarchitecture in amphioxus, and the brain patterning in both animals. Both the lateral eye in larval lamprey and the frontal eye in amphioxus project to a light-detecting visual center in the caudal prosencephalic region marked by Pax6, which possibly represents the ancestral state of the chordate visual system. Our results indicate that the visual system of the larval lamprey represents an evolutionarily primitive state, forming a link from protochordates to vertebrates and providing a new perspective of brain evolution based on developmental mechanisms and neural functions. © 2014 Wiley Periodicals, Inc.

The Brain as an Efficient and Robust Adaptive Learner.

PubMed

Denève, Sophie; Alemi, Alireza; Bourdoukan, Ralph

2017-06-07

Understanding how the brain learns to compute functions reliably, efficiently, and robustly with noisy spiking activity is a fundamental challenge in neuroscience. Most sensory and motor tasks can be described as dynamical systems and could presumably be learned by adjusting connection weights in a recurrent biological neural network. However, this is greatly complicated by the credit assignment problem for learning in recurrent networks, e.g., the contribution of each connection to the global output error cannot be determined based only on locally accessible quantities to the synapse. Combining tools from adaptive control theory and efficient coding theories, we propose that neural circuits can indeed learn complex dynamic tasks with local synaptic plasticity rules as long as they associate two experimentally established neural mechanisms. First, they should receive top-down feedbacks driving both their activity and their synaptic plasticity. Second, inhibitory interneurons should maintain a tight balance between excitation and inhibition in the circuit. The resulting networks could learn arbitrary dynamical systems and produce irregular spike trains as variable as those observed experimentally. Yet, this variability in single neurons may hide an extremely efficient and robust computation at the population level. Copyright © 2017 Elsevier Inc. All rights reserved.

Moving towards causality in attention-deficit hyperactivity disorder: overview of neural and genetic mechanisms

PubMed Central

Gallo, Eduardo F; Posner, Jonathan

2016-01-01

Attention-deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterised by developmentally inappropriate levels of inattention and hyperactivity or impulsivity. The heterogeneity of its clinical manifestations and the differential responses to treatment and varied prognoses have long suggested myriad underlying causes. Over the past decade, clinical and basic research efforts have uncovered many behavioural and neurobiological alterations associated with ADHD, from genes to higher order neural networks. Here, we review the neurobiology of ADHD by focusing on neural circuits implicated in the disorder and discuss how abnormalities in circuitry relate to symptom presentation and treatment. We summarise the literature on genetic variants that are potentially related to the development of ADHD, and how these, in turn, might affect circuit function and relevant behaviours. Whether these underlying neurobiological factors are causally related to symptom presentation remains unresolved. Therefore, we assess efforts aimed at disentangling issues of causality, and showcase the shifting research landscape towards endophenotype refinement in clinical and preclinical settings. Furthermore, we review approaches being developed to understand the neurobiological underpinnings of this complex disorder including the use of animal models, neuromodulation, and pharmaco-imaging studies. PMID:27183902

Disruptions in Functional Network Connectivity during Alcohol Intoxicated Driving

PubMed Central

Rzepecki-Smith, Catherine I.; Meda, Shashwath A.; Calhoun, Vince D.; Stevens, Michael C.; Jafri, Madiha J.; Astur, Robert S.; Pearlson, Godfrey D.

2009-01-01

Background: Driving while under the influence of alcohol is a major public health problem whose neural basis is not well understood. In a recently published fMRI study (Meda et al, 2009), our group identified five, independent critical driving-associated brain circuits whose inter-regional connectivity was disrupted by alcohol intoxication. However, the functional connectivity between these circuits has not yet been explored in order to determine how these networks communicate with each other during sober and alcohol-intoxicated states. Methods: In the current study, we explored such differences in connections between the above brain circuits and driving behavior, under the influence of alcohol versus placebo. Forty social drinkers who drove regularly underwent fMRI scans during virtual reality driving simulations following two alcohol doses, placebo and an individualized dose producing blood alcohol concentrations (BACs) of 0.10%. Results: At the active dose, we found specific disruptions of functional network connectivity between the frontal-temporal-basal ganglia and the cerebellar circuits. The temporal connectivity between these two circuits was found to be less correlated (p <0.05) when driving under the influence of alcohol. This disconnection was also associated with an abnormal driving behavior (unstable motor vehicle steering). Conclusions: Connections between frontal-temporal-basal ganglia and cerebellum have recently been explored; these may be responsible in part for maintaining normal motor behavior by integrating their overlapping motor control functions. These connections appear to be disrupted by alcohol intoxication, in turn associated with an explicit type of impaired driving behavior. PMID:20028354

Neural mechanism of optimal limb coordination in crustacean swimming

PubMed Central

Zhang, Calvin; Guy, Robert D.; Mulloney, Brian; Zhang, Qinghai; Lewis, Timothy J.

2014-01-01

A fundamental challenge in neuroscience is to understand how biologically salient motor behaviors emerge from properties of the underlying neural circuits. Crayfish, krill, prawns, lobsters, and other long-tailed crustaceans swim by rhythmically moving limbs called swimmerets. Over the entire biological range of animal size and paddling frequency, movements of adjacent swimmerets maintain an approximate quarter-period phase difference with the more posterior limbs leading the cycle. We use a computational fluid dynamics model to show that this frequency-invariant stroke pattern is the most effective and mechanically efficient paddling rhythm across the full range of biologically relevant Reynolds numbers in crustacean swimming. We then show that the organization of the neural circuit underlying swimmeret coordination provides a robust mechanism for generating this stroke pattern. Specifically, the wave-like limb coordination emerges robustly from a combination of the half-center structure of the local central pattern generating circuits (CPGs) that drive the movements of each limb, the asymmetric network topology of the connections between local CPGs, and the phase response properties of the local CPGs, which we measure experimentally. Thus, the crustacean swimmeret system serves as a concrete example in which the architecture of a neural circuit leads to optimal behavior in a robust manner. Furthermore, we consider all possible connection topologies between local CPGs and show that the natural connectivity pattern generates the biomechanically optimal stroke pattern most robustly. Given the high metabolic cost of crustacean swimming, our results suggest that natural selection has pushed the swimmeret neural circuit toward a connection topology that produces optimal behavior. PMID:25201976

Neural Networks For Demodulation Of Phase-Modulated Signals

NASA Technical Reports Server (NTRS)

Altes, Richard A.

1995-01-01

Hopfield neural networks proposed for demodulating quadrature phase-shift-keyed (QPSK) signals carrying digital information. Networks solve nonlinear integral equations prior demodulation circuits cannot solve. Consists of set of N operational amplifiers connected in parallel, with weighted feedback from output terminal of each amplifier to input terminals of other amplifiers. Used to solve signal processing problems. Implemented as analog very-large-scale integrated circuit that achieves rapid convergence. Alternatively, implemented as digital simulation of such circuit. Also used to improve phase estimation performance over that of phase-locked loop.

Motor Neurons Tune Premotor Activity in a Vertebrate Central Pattern Generator

PubMed Central

2017-01-01

Central patterns generators (CPGs) are neural circuits that drive rhythmic motor output without sensory feedback. Vertebrate CPGs are generally believed to operate in a top-down manner in which premotor interneurons activate motor neurons that in turn drive muscles. In contrast, the frog (Xenopus laevis) vocal CPG contains a functionally unexplored neuronal projection from the motor nucleus to the premotor nucleus, indicating a recurrent pathway that may contribute to rhythm generation. In this study, we characterized the function of this bottom-up connection. The X. laevis vocal CPG produces a 50–60 Hz “fast trill” song used by males during courtship. We recorded “fictive vocalizations” in the in vitro CPG from the laryngeal nerve while simultaneously recording premotor activity at the population and single-cell level. We show that transecting the motor-to-premotor projection eliminated the characteristic firing rate of premotor neurons. Silencing motor neurons with the intracellular sodium channel blocker QX-314 also disrupted premotor rhythms, as did blockade of nicotinic synapses in the motor nucleus (the putative location of motor neuron-to-interneuron connections). Electrically stimulating the laryngeal nerve elicited primarily IPSPs in premotor neurons that could be blocked by a nicotinic receptor antagonist. Our results indicate that an inhibitory signal, activated by motor neurons, is required for proper CPG function. To our knowledge, these findings represent the first example of a CPG in which precise premotor rhythms are tuned by motor neuron activity. SIGNIFICANCE STATEMENT Central pattern generators (CPGs) are neural circuits that produce rhythmic behaviors. In vertebrates, motor neurons are not commonly known to contribute to CPG function, with the exception of a few spinal circuits where the functional significance of motor neuron feedback is still poorly understood. The frog hindbrain vocal circuit contains a previously unexplored connection from the motor to premotor region. Our results indicate that motor neurons activate this bottom-up connection, and blocking this signal eliminates normal premotor activity. These findings may promote increased awareness of potential involvement of motor neurons in a wider range of CPGs, perhaps clarifying our understanding of network principles underlying motor behaviors in numerous organisms, including humans. PMID:28219984

The Pleiotropic MET Receptor Network: Circuit Development and the Neural-Medical Interface of Autism.

PubMed

Eagleson, Kathie L; Xie, Zhihui; Levitt, Pat

2017-03-01

People with autism spectrum disorder and other neurodevelopmental disorders (NDDs) are behaviorally and medically heterogeneous. The combination of polygenicity and gene pleiotropy-the influence of one gene on distinct phenotypes-raises questions of how specific genes and their protein products interact to contribute to NDDs. A preponderance of evidence supports developmental and pathophysiological roles for the MET receptor tyrosine kinase, a multifunctional receptor that mediates distinct biological responses depending upon cell context. MET influences neuron architecture and synapse maturation in the forebrain and regulates homeostasis in gastrointestinal and immune systems, both commonly disrupted in NDDs. Peak expression of synapse-enriched MET is conserved across rodent and primate forebrain, yet regional differences in primate neocortex are pronounced, with enrichment in circuits that participate in social information processing. A functional risk allele in the MET promoter, enriched in subgroups of children with autism spectrum disorder, reduces transcription and disrupts socially relevant neural circuits structurally and functionally. In mice, circuit-specific deletion of Met causes distinct atypical behaviors. MET activation increases dendritic complexity and nascent synapse number, but synapse maturation requires reductions in MET. MET mediates its specific biological effects through different intracellular signaling pathways and has a complex protein interactome that is enriched in autism spectrum disorder and other NDD candidates. The interactome is coregulated in developing human neocortex. We suggest that a gene as pleiotropic and highly regulated as MET, together with its interactome, is biologically relevant in normal and pathophysiological contexts, affecting central and peripheral phenotypes that contribute to NDD risk and clinical symptoms. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Neural Networks Based Approach to Enhance Space Hardware Reliability

NASA Technical Reports Server (NTRS)

Zebulum, Ricardo S.; Thakoor, Anilkumar; Lu, Thomas; Franco, Lauro; Lin, Tsung Han; McClure, S. S.

2011-01-01

This paper demonstrates the use of Neural Networks as a device modeling tool to increase the reliability analysis accuracy of circuits targeted for space applications. The paper tackles a number of case studies of relevance to the design of Flight hardware. The results show that the proposed technique generates more accurate models than the ones regularly used to model circuits.

Biologically based neural circuit modelling for the study of fear learning and extinction

NASA Astrophysics Data System (ADS)

Nair, Satish S.; Paré, Denis; Vicentic, Aleksandra

2016-11-01

The neuronal systems that promote protective defensive behaviours have been studied extensively using Pavlovian conditioning. In this paradigm, an initially neutral-conditioned stimulus is paired with an aversive unconditioned stimulus leading the subjects to display behavioural signs of fear. Decades of research into the neural bases of this simple behavioural paradigm uncovered that the amygdala, a complex structure comprised of several interconnected nuclei, is an essential part of the neural circuits required for the acquisition, consolidation and expression of fear memory. However, emerging evidence from the confluence of electrophysiological, tract tracing, imaging, molecular, optogenetic and chemogenetic methodologies, reveals that fear learning is mediated by multiple connections between several amygdala nuclei and their distributed targets, dynamical changes in plasticity in local circuit elements as well as neuromodulatory mechanisms that promote synaptic plasticity. To uncover these complex relations and analyse multi-modal data sets acquired from these studies, we argue that biologically realistic computational modelling, in conjunction with experiments, offers an opportunity to advance our understanding of the neural circuit mechanisms of fear learning and to address how their dysfunction may lead to maladaptive fear responses in mental disorders.

Development switch in neural circuitry underlying odor-malaise learning.

PubMed

Shionoya, Kiseko; Moriceau, Stephanie; Lunday, Lauren; Miner, Cathrine; Roth, Tania L; Sullivan, Regina M

2006-01-01

Fetal and infant rats can learn to avoid odors paired with illness before development of brain areas supporting this learning in adults, suggesting an alternate learning circuit. Here we begin to document the transition from the infant to adult neural circuit underlying odor-malaise avoidance learning using LiCl (0.3 M; 1% of body weight, ip) and a 30-min peppermint-odor exposure. Conditioning groups included: Paired odor-LiCl, Paired odor-LiCl-Nursing, LiCl, and odor-saline. Results showed that Paired LiCl-odor conditioning induced a learned odor aversion in postnatal day (PN) 7, 12, and 23 pups. Odor-LiCl Paired Nursing induced a learned odor preference in PN7 and PN12 pups but blocked learning in PN23 pups. 14C 2-deoxyglucose (2-DG) autoradiography indicated enhanced olfactory bulb activity in PN7 and PN12 pups with odor preference and avoidance learning. The odor aversion in weanling aged (PN23) pups resulted in enhanced amygdala activity in Paired odor-LiCl pups, but not if they were nursing. Thus, the neural circuit supporting malaise-induced aversions changes over development, indicating that similar infant and adult-learned behaviors may have distinct neural circuits.

Detection of inter-turn short-circuit at start-up of induction machine based on torque analysis

NASA Astrophysics Data System (ADS)

Pietrowski, Wojciech; Górny, Konrad

2017-12-01

Recently, interest in new diagnostics methods in a field of induction machines was observed. Research presented in the paper shows the diagnostics of induction machine based on torque pulsation, under inter-turn short-circuit, during start-up of a machine. In the paper three numerical techniques were used: finite element analysis, signal analysis and artificial neural networks (ANN). The elaborated numerical model of faulty machine consists of field, circuit and motion equations. Voltage excited supply allowed to determine the torque waveform during start-up. The inter-turn short-circuit was treated as a galvanic connection between two points of the stator winding. The waveforms were calculated for different amounts of shorted-turns from 0 to 55. Due to the non-stationary waveforms a wavelet packet decomposition was used to perform an analysis of the torque. The obtained results of analysis were used as input vector for ANN. The response of the neural network was the number of shorted-turns in the stator winding. Special attention was paid to compare response of general regression neural network (GRNN) and multi-layer perceptron neural network (MLP). Based on the results of the research, the efficiency of the developed algorithm can be inferred.

Neural-like computing with populations of superparamagnetic basis functions.

PubMed

Mizrahi, Alice; Hirtzlin, Tifenn; Fukushima, Akio; Kubota, Hitoshi; Yuasa, Shinji; Grollier, Julie; Querlioz, Damien

2018-04-18

In neuroscience, population coding theory demonstrates that neural assemblies can achieve fault-tolerant information processing. Mapped to nanoelectronics, this strategy could allow for reliable computing with scaled-down, noisy, imperfect devices. Doing so requires that the population components form a set of basis functions in terms of their response functions to inputs, offering a physical substrate for computing. Such a population can be implemented with CMOS technology, but the corresponding circuits have high area or energy requirements. Here, we show that nanoscale magnetic tunnel junctions can instead be assembled to meet these requirements. We demonstrate experimentally that a population of nine junctions can implement a basis set of functions, providing the data to achieve, for example, the generation of cursive letters. We design hybrid magnetic-CMOS systems based on interlinked populations of junctions and show that they can learn to realize non-linear variability-resilient transformations with a low imprint area and low power.

Multifarious Functions of the Fragile X Mental Retardation Protein.

PubMed

Davis, Jenna K; Broadie, Kendal

2017-10-01

Fragile X syndrome (FXS), a heritable intellectual and autism spectrum disorder (ASD), results from the loss of Fragile X mental retardation protein (FMRP). This neurodevelopmental disease state exhibits neural circuit hyperconnectivity and hyperexcitability. Canonically, FMRP functions as an mRNA-binding translation suppressor, but recent findings have enormously expanded its proposed roles. Although connections between burgeoning FMRP functions remain unknown, recent advances have extended understanding of its involvement in RNA, channel, and protein binding that modulate calcium signaling, activity-dependent critical period development, and the excitation-inhibition (E/I) neural circuitry balance. In this review, we contextualize 3 years of FXS model research. Future directions extrapolated from recent advances focus on discovering links between FMRP roles to determine whether FMRP has a multitude of unrelated functions or whether combinatorial mechanisms can explain its multifaceted existence. Copyright © 2017 Elsevier Ltd. All rights reserved.

Connectivity constraints on cortical reorganization of neural circuits involved in object naming.

PubMed

Papagno, Costanza; Gallucci, Marcello; Casarotti, Alessandra; Castellano, Antonella; Falini, Andrea; Fava, Enrica; Giussani, Carlo; Carrabba, Giorgio; Bello, Lorenzo; Caramazza, Alfonso

2011-04-01

The brain's plasticity in response to sensory deprivation and other perturbations is well established. While the functional properties of the reorganized areas are under vigorous investigation, the factors that constrain cortical reorganization remain poorly understood. One factor constraining such reorganization may be long-distance subcortical connectivity between relevant cortical regions-reorganization attempts to preserve the functionality of subcortical connections. Here we provide human neurophysiological evidence for the role of the subcortical connections in shaping cortical reorganization of the networks involved in object naming following perturbation of normal function. We used direct electrical stimulation (DES) during surgical removal of gliomas to identify the sites that are involved in naming different categories of objects. The sites that were selectively inhibited in naming either living or non-living objects were displaced relative to those observed with other subject populations, possibly reflecting cortical reorganization due to slowly evolving brain damage. Subcortical DES applied to the white matter underlying these regions also led to category-specific naming deficits. The existence of these subcortical fiber pathways was confirmed using diffusion tensor tractography. These results constitute the first neurophysiological evidence for the critical role of subcortical pathways as part of the neural circuits that are involved in object naming; they also highlight the importance of subcortical connectivity in shaping cortical reorganization following perturbations of normal function. Copyright © 2011 Elsevier Inc. All rights reserved.

Hedonic Eating and the “Delicious Circle”: From Lipid-Derived Mediators to Brain Dopamine and Back

PubMed Central

Coccurello, Roberto; Maccarrone, Mauro

2018-01-01

Palatable food can be seductive and hedonic eating can become irresistible beyond hunger and negative consequences. This is witnessed by the subtle equilibrium between eating to provide energy intake for homeostatic functions, and reward-induced overeating. In recent years, considerable efforts have been devoted to study neural circuits, and to identify potential factors responsible for the derangement of homeostatic eating toward hedonic eating and addiction-like feeding behavior. Here, we examined recent literature on “old” and “new” players accountable for reward-induced overeating and possible liability to eating addiction. Thus, the role of midbrain dopamine is positioned at the intersection between selected hormonal signals involved in food reward information processing (namely, leptin, ghrelin, and insulin), and lipid-derived neural mediators such as endocannabinoids. The impact of high fat palatable food and dietary lipids on endocannabinoid formation is reviewed in its pathogenetic potential for the derangement of feeding homeostasis. Next, endocannabinoid signaling that regulates synaptic plasticity is discussed as a key mechanism acting both at hypothalamic and mesolimbic circuits, and affecting both dopamine function and interplay between leptin and ghrelin signaling. Outside the canonical hypothalamic feeding circuits involved in energy homeostasis and the notion of “feeding center,” we focused on lateral hypothalamus as neural substrate able to confront food-associated homeostatic information with food salience, motivation to eat, reward-seeking, and development of compulsive eating. Thus, the lateral hypothalamus-ventral tegmental area-nucleus accumbens neural circuitry is reexamined in order to interrogate the functional interplay between ghrelin, dopamine, orexin, and endocannabinoid signaling. We suggested a pivotal role for endocannabinoids in food reward processing within the lateral hypothalamus, and for orexin neurons to integrate endocrine signals with food reinforcement and hedonic eating. In addition, the role played by different stressors in the reinstatement of preference for palatable food and food-seeking behavior is also considered in the light of endocannabinoid production, activation of orexin receptors and disinhibition of dopamine neurons. Finally, type-1 cannabinoid receptor-dependent inhibition of GABA-ergic release and relapse to reward-associated stimuli is linked to ghrelin and orexin signaling in the lateral hypothalamus-ventral tegmental area-nucleus accumbens network to highlight its pathological potential for food addiction-like behavior. PMID:29740277

Long-Term Plasticity of Neurotransmitter Release: Emerging Mechanisms and Contributions to Brain Function and Disease.

PubMed

Monday, Hannah R; Younts, Thomas J; Castillo, Pablo E

2018-04-25

Long-lasting changes of brain function in response to experience rely on diverse forms of activity-dependent synaptic plasticity. Chief among them are long-term potentiation and long-term depression of neurotransmitter release, which are widely expressed by excitatory and inhibitory synapses throughout the central nervous system and can dynamically regulate information flow in neural circuits. This review article explores recent advances in presynaptic long-term plasticity mechanisms and contributions to circuit function. Growing evidence indicates that presynaptic plasticity may involve structural changes, presynaptic protein synthesis, and transsynaptic signaling. Presynaptic long-term plasticity can alter the short-term dynamics of neurotransmitter release, thereby contributing to circuit computations such as novelty detection, modifications of the excitatory/inhibitory balance, and sensory adaptation. In addition, presynaptic long-term plasticity underlies forms of learning and its dysregulation participates in several neuropsychiatric conditions, including schizophrenia, autism, intellectual disabilities, neurodegenerative diseases, and drug abuse. Expected final online publication date for the Annual Review of Neuroscience Volume 41 is July 8, 2018. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Oxytocin modulation of neural circuits for social behavior.

PubMed

Marlin, Bianca J; Froemke, Robert C

2017-02-01

Oxytocin is a hypothalamic neuropeptide that has gained attention for the effects on social behavior. Recent findings shed new light on the mechanisms of oxytocin in synaptic plasticity and adaptively modifying neural circuits for social interactions such as conspecific recognition, pair bonding, and maternal care. Here, we review several of these newer studies on oxytocin in the context of previous findings, with an emphasis on social behavior and circuit plasticity in various brain regions shown to be enriched for oxytocin receptors. We provide a framework that highlights current circuit-level mechanisms underlying the widespread action of oxytocin. © 2016 Wiley Periodicals, Inc. Develop Neurobiol 77: 169-189, 2017. © 2016 Wiley Periodicals, Inc.

Exponential H(infinity) synchronization of general discrete-time chaotic neural networks with or without time delays.

PubMed

Qi, Donglian; Liu, Meiqin; Qiu, Meikang; Zhang, Senlin

2010-08-01

This brief studies exponential H(infinity) synchronization of a class of general discrete-time chaotic neural networks with external disturbance. On the basis of the drive-response concept and H(infinity) control theory, and using Lyapunov-Krasovskii (or Lyapunov) functional, state feedback controllers are established to not only guarantee exponential stable synchronization between two general chaotic neural networks with or without time delays, but also reduce the effect of external disturbance on the synchronization error to a minimal H(infinity) norm constraint. The proposed controllers can be obtained by solving the convex optimization problems represented by linear matrix inequalities. Most discrete-time chaotic systems with or without time delays, such as Hopfield neural networks, cellular neural networks, bidirectional associative memory networks, recurrent multilayer perceptrons, Cohen-Grossberg neural networks, Chua's circuits, etc., can be transformed into this general chaotic neural network to be H(infinity) synchronization controller designed in a unified way. Finally, some illustrated examples with their simulations have been utilized to demonstrate the effectiveness of the proposed methods.

Synaptic plasticity, neural circuits, and the emerging role of altered short-term information processing in schizophrenia

PubMed Central

Crabtree, Gregg W.; Gogos, Joseph A.

2014-01-01

Synaptic plasticity alters the strength of information flow between presynaptic and postsynaptic neurons and thus modifies the likelihood that action potentials in a presynaptic neuron will lead to an action potential in a postsynaptic neuron. As such, synaptic plasticity and pathological changes in synaptic plasticity impact the synaptic computation which controls the information flow through the neural microcircuits responsible for the complex information processing necessary to drive adaptive behaviors. As current theories of neuropsychiatric disease suggest that distinct dysfunctions in neural circuit performance may critically underlie the unique symptoms of these diseases, pathological alterations in synaptic plasticity mechanisms may be fundamental to the disease process. Here we consider mechanisms of both short-term and long-term plasticity of synaptic transmission and their possible roles in information processing by neural microcircuits in both health and disease. As paradigms of neuropsychiatric diseases with strongly implicated risk genes, we discuss the findings in schizophrenia and autism and consider the alterations in synaptic plasticity and network function observed in both human studies and genetic mouse models of these diseases. Together these studies have begun to point toward a likely dominant role of short-term synaptic plasticity alterations in schizophrenia while dysfunction in autism spectrum disorders (ASDs) may be due to a combination of both short-term and long-term synaptic plasticity alterations. PMID:25505409

Mechanisms to medicines: elucidating neural and molecular substrates of fear extinction to identify novel treatments for anxiety disorders

PubMed Central

Bukalo, Olena; Pinard, Courtney R; Holmes, Andrew

2014-01-01

The burden of anxiety disorders is growing, but the efficacy of available anxiolytic treatments remains inadequate. Cognitive behavioural therapy for anxiety disorders focuses on identifying and modifying maladaptive patterns of thinking and behaving, and has a testable analogue in rodents in the form of fear extinction. A large preclinical literature has amassed in recent years describing the neural and molecular basis of fear extinction in rodents. In this review, we discuss how this work is being harnessed to foster translational research on anxiety disorders and facilitate the search for new anxiolytic treatments. We begin by summarizing the anatomical and functional connectivity of a medial prefrontal cortex (mPFC)–amygdala circuit that subserves fear extinction, including new insights from optogenetics. We then cover some of the approaches that have been taken to model impaired fear extinction and associated impairments with mPFC–amygdala dysfunction. The principal goal of the review is to evaluate evidence that various neurotransmitter and neuromodulator systems mediate fear extinction by modulating the mPFC–amygdala circuitry. To that end, we describe studies that have tested how fear extinction is impaired or facilitated by pharmacological manipulations of dopamine, noradrenaline, 5-HT, GABA, glutamate, neuropeptides, endocannabinoids and various other systems, which either directly target the mPFC–amygdala circuit, or produce behavioural effects that are coincident with functional changes in the circuit. We conclude that there are good grounds to be optimistic that the progress in defining the molecular substrates of mPFC–amygdala circuit function can be effectively leveraged to identify plausible candidates for extinction-promoting therapies for anxiety disorders. Linked Articles This article is part of a themed section on Animal Models in Psychiatry Research. To view the other articles in this section visit http://dx.doi.org/10.1111/bph.2014.171.issue-20 PMID:24835117

Commentary: The Development of Hippocampal-Dependent Memory Functions: Theoretical Comments on Jabès and Nelson Review (2015)

ERIC Educational Resources Information Center

Bachevalier, Jocelyne

2015-01-01

Studies investigating the development of memory processes and their neural substrates have flourished over the past two decades. The review by Jabès and Nelson (2015) adds an important piece to our understanding of the maturation of different elements and circuits within the hippocampal system and their association with the progressive development…

Signaling in large-scale neural networks.

PubMed

Berg, Rune W; Hounsgaard, Jørn

2009-02-01

We examine the recent finding that neurons in spinal motor circuits enter a high conductance state during functional network activity. The underlying concomitant increase in random inhibitory and excitatory synaptic activity leads to stochastic signal processing. The possible advantages of this metabolically costly organization are analyzed by comparing with synaptically less intense networks driven by the intrinsic response properties of the network neurons.

Imaging Voltage in Genetically Defined Neuronal Subpopulations with a Cre Recombinase-Targeted Hybrid Voltage Sensor.

PubMed

Bayguinov, Peter O; Ma, Yihe; Gao, Yu; Zhao, Xinyu; Jackson, Meyer B

2017-09-20

Genetically encoded voltage indicators create an opportunity to monitor electrical activity in defined sets of neurons as they participate in the complex patterns of coordinated electrical activity that underlie nervous system function. Taking full advantage of genetically encoded voltage indicators requires a generalized strategy for targeting the probe to genetically defined populations of cells. To this end, we have generated a mouse line with an optimized hybrid voltage sensor (hVOS) probe within a locus designed for efficient Cre recombinase-dependent expression. Crossing this mouse with Cre drivers generated double transgenics expressing hVOS probe in GABAergic, parvalbumin, and calretinin interneurons, as well as hilar mossy cells, new adult-born neurons, and recently active neurons. In each case, imaging in brain slices from male or female animals revealed electrically evoked optical signals from multiple individual neurons in single trials. These imaging experiments revealed action potentials, dynamic aspects of dendritic integration, and trial-to-trial fluctuations in response latency. The rapid time response of hVOS imaging revealed action potentials with high temporal fidelity, and enabled accurate measurements of spike half-widths characteristic of each cell type. Simultaneous recording of rapid voltage changes in multiple neurons with a common genetic signature offers a powerful approach to the study of neural circuit function and the investigation of how neural networks encode, process, and store information. SIGNIFICANCE STATEMENT Genetically encoded voltage indicators hold great promise in the study of neural circuitry, but realizing their full potential depends on targeting the sensor to distinct cell types. Here we present a new mouse line that expresses a hybrid optical voltage sensor under the control of Cre recombinase. Crossing this line with Cre drivers generated double-transgenic mice, which express this sensor in targeted cell types. In brain slices from these animals, single-trial hybrid optical voltage sensor recordings revealed voltage changes with submillisecond resolution in multiple neurons simultaneously. This imaging tool will allow for the study of the emergent properties of neural circuits and permit experimental tests of the roles of specific types of neurons in complex circuit activity. Copyright © 2017 the authors 0270-6474/17/379305-15$15.00/0.

Schaffer Collateral Inputs to CA1 Excitatory and Inhibitory Neurons Follow Different Connectivity Rules.

PubMed

Kwon, Osung; Feng, Linqing; Druckmann, Shaul; Kim, Jinhyun

2018-05-30

Neural circuits, governed by a complex interplay between excitatory and inhibitory neurons, are the substrate for information processing, and the organization of synaptic connectivity in neural network is an important determinant of circuit function. Here, we analyzed the fine structure of connectivity in hippocampal CA1 excitatory and inhibitory neurons innervated by Schaffer collaterals (SCs) using mGRASP in male mice. Our previous study revealed spatially structured synaptic connectivity between CA3 and CA1 pyramidal cells (PCs). Surprisingly, parvalbumin-positive interneurons (PVs) showed a significantly more random pattern spatial structure. Notably, application of Peters' rule for synapse prediction by random overlap between axons and dendrites enhanced structured connectivity in PCs, but, by contrast, made the connectivity pattern in PVs more random. In addition, PCs in a deep sublayer of striatum pyramidale appeared more highly structured than PCs in superficial layers, and little or no sublayer specificity was found in PVs. Our results show that CA1 excitatory PCs and inhibitory PVs innervated by the same SC inputs follow different connectivity rules. The different organizations of fine scale structured connectivity in hippocampal excitatory and inhibitory neurons provide important insights into the development and functions of neural networks. SIGNIFICANCE STATEMENT Understanding how neural circuits generate behavior is one of the central goals of neuroscience. An important component of this endeavor is the mapping of fine-scale connection patterns that underlie, and help us infer, signal processing in the brain. Here, using our recently developed synapse detection technology (mGRASP and neuTube), we provide detailed profiles of synaptic connectivity in excitatory (CA1 pyramidal) and inhibitory (CA1 parvalbumin-positive) neurons innervated by the same presynaptic inputs (CA3 Schaffer collaterals). Our results reveal that these two types of CA1 neurons follow different connectivity patterns. Our new evidence for differently structured connectivity at a fine scale in hippocampal excitatory and inhibitory neurons provides a better understanding of hippocampal networks and will guide theoretical and experimental studies. Copyright © 2018 the authors 0270-6474/18/385140-13$15.00/0.

Oxytocin administration suppresses hypothalamic activation in response to visual food cues.

PubMed

van der Klaauw, Agatha A; Ziauddeen, Hisham; Keogh, Julia M; Henning, Elana; Dachi, Sekesai; Fletcher, Paul C; Farooqi, I Sadaf

2017-06-27

The aim of this study was to use functional neuroimaging to investigate whether oxytocin modulates the neural response to visual food cues in brain regions involved in the control of food intake. Twenty-four normal weight volunteers received intranasal oxytocin (24 IU) or placebo in a double-blind, randomized crossover study. Measurements were made forty-five minutes after dosing. On two occasions, functional MRI (fMRI) scans were performed in the fasted state; the blood oxygen level-dependent (BOLD) response to images of high-calorie foods versus low-calorie foods was measured. Given its critical role in eating behaviour, the primary region of interest was the hypothalamus. Secondary analyses examined the parabrachial nuclei and other brain regions involved in food intake and food reward. Intranasal oxytocin administration suppressed hypothalamic activation to images of high-calorie compared to low-calorie food (P = 0.0125). There was also a trend towards suppression of activation in the parabrachial nucleus (P = 0.0683). No effects of intranasal oxytocin were seen in reward circuits or on ad libitum food intake. Further characterization of the effects of oxytocin on neural circuits in the hypothalamus is needed to establish the utility of targeting oxytocin signalling in obesity.

The neuropsychiatry of hyperkinetic movement disorders: insights from neuroimaging into the neural circuit bases of dysfunction.

PubMed

Hayhow, Bradleigh D; Hassan, Islam; Looi, Jeffrey C L; Gaillard, Francesco; Velakoulis, Dennis; Walterfang, Mark

2013-01-01

Movement disorders, particularly those associated with basal ganglia disease, have a high rate of comorbid neuropsychiatric illness. We consider the pathophysiological basis of the comorbidity between movement disorders and neuropsychiatric illness by 1) reviewing the epidemiology of neuropsychiatric illness in a range of hyperkinetic movement disorders, and 2) correlating findings to evidence from studies that have utilized modern neuroimaging techniques to investigate these disorders. In addition to diseases classically associated with basal ganglia pathology, such as Huntington disease, Wilson disease, the neuroacanthocytoses, and diseases of brain iron accumulation, we include diseases associated with pathology of subcortical white matter tracts, brain stem nuclei, and the cerebellum, such as metachromatic leukodystrophy, dentatorubropallidoluysian atrophy, and the spinocerebellar ataxias. Neuropsychiatric symptoms are integral to a thorough phenomenological account of hyperkinetic movement disorders. Drawing on modern theories of cortico-subcortical circuits, we argue that these disorders can be conceptualized as disorders of complex subcortical networks with distinct functional architectures. Damage to any component of these complex information-processing networks can have variable and often profound consequences for the function of more remote neural structures, creating a diverse but nonetheless rational pattern of clinical symptomatology.

Optogenetic approaches to evaluate striatal function in animal models of Parkinson disease.

PubMed

Parker, Krystal L; Kim, Youngcho; Alberico, Stephanie L; Emmons, Eric B; Narayanan, Nandakumar S

2016-03-01

Optogenetics refers to the ability to control cells that have been genetically modified to express light-sensitive ion channels. The introduction of optogenetic approaches has facilitated the dissection of neural circuits. Optogenetics allows for the precise stimulation and inhibition of specific sets of neurons and their projections with fine temporal specificity. These techniques are ideally suited to investigating neural circuitry underlying motor and cognitive dysfunction in animal models of human disease. Here, we focus on how optogenetics has been used over the last decade to probe striatal circuits that are involved in Parkinson disease, a neurodegenerative condition involving motor and cognitive abnormalities resulting from degeneration of midbrain dopaminergic neurons. The precise mechanisms underlying the striatal contribution to both cognitive and motor dysfunction in Parkinson disease are unknown. Although optogenetic approaches are somewhat removed from clinical use, insight from these studies can help identify novel therapeutic targets and may inspire new treatments for Parkinson disease. Elucidating how neuronal and behavioral functions are influenced and potentially rescued by optogenetic manipulation in animal models could prove to be translatable to humans. These insights can be used to guide future brain-stimulation approaches for motor and cognitive abnormalities in Parkinson disease and other neuropsychiatric diseases.

Excitatory and inhibitory STDP jointly tune feedforward neural circuits to selectively propagate correlated spiking activity

PubMed Central

Kleberg, Florence I.; Fukai, Tomoki; Gilson, Matthieu

2014-01-01

Spike-timing-dependent plasticity (STDP) has been well established between excitatory neurons and several computational functions have been proposed in various neural systems. Despite some recent efforts, however, there is a significant lack of functional understanding of inhibitory STDP (iSTDP) and its interplay with excitatory STDP (eSTDP). Here, we demonstrate by analytical and numerical methods that iSTDP contributes crucially to the balance of excitatory and inhibitory weights for the selection of a specific signaling pathway among other pathways in a feedforward circuit. This pathway selection is based on the high sensitivity of STDP to correlations in spike times, which complements a recent proposal for the role of iSTDP in firing-rate based selection. Our model predicts that asymmetric anti-Hebbian iSTDP exceeds asymmetric Hebbian iSTDP for supporting pathway-specific balance, which we show is useful for propagating transient neuronal responses. Furthermore, we demonstrate how STDPs at excitatory–excitatory, excitatory–inhibitory, and inhibitory–excitatory synapses cooperate to improve the pathway selection. We propose that iSTDP is crucial for shaping the network structure that achieves efficient processing of synchronous spikes. PMID:24847242

Cost-benefit decision circuitry: proposed modulatory role for acetylcholine.

PubMed

Fobbs, Wambura C; Mizumori, Sheri J Y

2014-01-01

In order to select which action should be taken, an animal must weigh the costs and benefits of possible outcomes associate with each action. Such decisions, called cost-benefit decisions, likely involve several cognitive processes (including memory) and a vast neural circuitry. Rodent models have allowed research to begin to probe the neural basis of three forms of cost-benefit decision making: effort-, delay-, and risk-based decision making. In this review, we detail the current understanding of the functional circuits that subserve each form of decision making. We highlight the extensive literature by detailing the ability of dopamine to influence decisions by modulating structures within these circuits. Since acetylcholine projects to all of the same important structures, we propose several ways in which the cholinergic system may play a local modulatory role that will allow it to shape these behaviors. A greater understanding of the contribution of the cholinergic system to cost-benefit decisions will permit us to better link the decision and memory processes, and this will help us to better understand and/or treat individuals with deficits in a number of higher cognitive functions including decision making, learning, memory, and language. © 2014 Elsevier Inc. All rights reserved.

Human high intelligence is involved in spectral redshift of biophotonic activities in the brain

PubMed Central

Wang, Niting; Li, Zehua; Xiao, Fangyan; Dai, Jiapei

2016-01-01

Human beings hold higher intelligence than other animals on Earth; however, it is still unclear which brain properties might explain the underlying mechanisms. The brain is a major energy-consuming organ compared with other organs. Neural signal communications and information processing in neural circuits play an important role in the realization of various neural functions, whereas improvement in cognitive function is driven by the need for more effective communication that requires less energy. Combining the ultraweak biophoton imaging system (UBIS) with the biophoton spectral analysis device (BSAD), we found that glutamate-induced biophotonic activities and transmission in the brain, which has recently been demonstrated as a novel neural signal communication mechanism, present a spectral redshift from animals (in order of bullfrog, mouse, chicken, pig, and monkey) to humans, even up to a near-infrared wavelength (∼865 nm) in the human brain. This brain property may be a key biophysical basis for explaining high intelligence in humans because biophoton spectral redshift could be a more economical and effective measure of biophotonic signal communications and information processing in the human brain. PMID:27432962

Maintenance of Mouse Gustatory Terminal Field Organization Is Disrupted following Selective Removal of Peripheral Sodium Salt Taste Activity at Adulthood.

PubMed

Skyberg, Rolf; Sun, Chengsan; Hill, David L

2017-08-09

Neural activity plays a critical role in the development of central circuits in sensory systems. However, the maintenance of these circuits at adulthood is usually not dependent on sensory-elicited neural activity. Recent work in the mouse gustatory system showed that selectively deleting the primary transduction channel for sodium taste, the epithelial sodium channel (ENaC), throughout development dramatically impacted the organization of the central terminal fields of three nerves that carry taste information to the nucleus of the solitary tract. More specifically, deleting ENaCs during development prevented the normal maturation of the fields. The present study was designed to extend these findings by testing the hypothesis that the loss of sodium taste activity impacts the maintenance of the normal adult terminal field organization in male and female mice. To do this, we used an inducible Cre-dependent genetic recombination strategy to delete ENaC function after terminal field maturation occurred. We found that removal of sodium taste neural activity at adulthood resulted in significant reorganization of mature gustatory afferent terminal fields in the nucleus of the solitary tract. Specifically, the chorda tympani and greater superficial petrosal nerve terminal fields were 1.4× and 1.6× larger than age-matched controls, respectively. By contrast, the glossopharyngeal nerve, which is not highly sensitive to sodium taste stimulation, did not undergo terminal field reorganization. These surprising results suggest that gustatory nerve terminal fields remain plastic well into adulthood, which likely impacts central coding of taste information and taste-related behaviors with altered taste experience. SIGNIFICANCE STATEMENT Neural activity plays a major role in the development of sensory circuits in the mammalian brain. However, the importance of sensory-driven activity in maintaining these circuits at adulthood, especially in subcortical structures, appears to be much less. Here, we tested whether the loss of sodium taste activity in adult mice impacts the maintenance of how taste nerves project to the first central relay. We found that specific loss of sodium-elicited taste activity at adulthood produced dramatic and selective reorganization of terminal fields in the brainstem. This demonstrates, for the first time, that taste-elicited activity is necessary for the normal maintenance of central gustatory circuits at adulthood and highlights a level of plasticity not seen in other sensory system subcortical circuits. Copyright © 2017 the authors 0270-6474/17/377619-12$15.00/0.

Tracing Activity Across the Whole Brain Neural Network with Optogenetic Functional Magnetic Resonance Imaging

PubMed Central

Lee, Jin Hyung

2011-01-01

Despite the overwhelming need, there has been a relatively large gap in our ability to trace network level activity across the brain. The complex dense wiring of the brain makes it extremely challenging to understand cell-type specific activity and their communication beyond a few synapses. Recent development of the optogenetic functional magnetic resonance imaging (ofMRI) provides a new impetus for the study of brain circuits by enabling causal tracing of activities arising from defined cell types and firing patterns across the whole brain. Brain circuit elements can be selectively triggered based on their genetic identity, cell body location, and/or their axonal projection target with temporal precision while the resulting network response is monitored non-invasively with unprecedented spatial and temporal accuracy. With further studies including technological innovations to bring ofMRI to its full potential, ofMRI is expected to play an important role in our system-level understanding of the brain circuit mechanism. PMID:22046160

Implementation of olfactory bulb glomerular-layer computations in a digital neurosynaptic core.

PubMed

Imam, Nabil; Cleland, Thomas A; Manohar, Rajit; Merolla, Paul A; Arthur, John V; Akopyan, Filipp; Modha, Dharmendra S

2012-01-01

We present a biomimetic system that captures essential functional properties of the glomerular layer of the mammalian olfactory bulb, specifically including its capacity to decorrelate similar odor representations without foreknowledge of the statistical distributions of analyte features. Our system is based on a digital neuromorphic chip consisting of 256 leaky-integrate-and-fire neurons, 1024 × 256 crossbar synapses, and address-event representation communication circuits. The neural circuits configured in the chip reflect established connections among mitral cells, periglomerular cells, external tufted cells, and superficial short-axon cells within the olfactory bulb, and accept input from convergent sets of sensors configured as olfactory sensory neurons. This configuration generates functional transformations comparable to those observed in the glomerular layer of the mammalian olfactory bulb. Our circuits, consuming only 45 pJ of active power per spike with a power supply of 0.85 V, can be used as the first stage of processing in low-power artificial chemical sensing devices inspired by natural olfactory systems.

Neuroscience Literacy: "Brain Tells" as Signals of Brain Dysfunction Affecting Daily Life.

PubMed

Royeen, Charlotte B; Brašić, James R; Dvorak, Leah; Provoziak-O'Brien, Casey; Sethi, Chetna; Ahmad, S Omar

2016-01-01

The structures and circuits of the central and the peripheral nervous systems provide the basis for thinking, speaking, experiencing sensations, and performing perceptual and motor activities in daily life. Healthy people experience normal functioning without giving brain functions a second thought, while dysfunction of the neural circuits may lead to marked impairments in cognition, communication, sensory awareness, and performing perceptual and motor tasks. Neuroscience literacy provides the knowledge to associate the deficits observed in patients with the underlying deficits in the structures and circuits of the nervous system. The purpose of this paper is to begin the conversation in this area via a neuroscience literacy model of "Brain Tells," defined as stereotypical or observable behaviors often associated with brain dysfunction. Occupational therapists and other allied health professionals should be alert for the signs of "Brain Tells" that may be early warning signs of brain pathology. We also suggest that neuroscience literacy be emphasized in training provided to public safety workers, teachers, caregivers, and health care professionals at all levels.

Activation in mesolimbic and visuospatial neural circuits elicited by smoking cues: evidence from functional magnetic resonance imaging.

PubMed

Due, Deborah L; Huettel, Scott A; Hall, Warren G; Rubin, David C

2002-06-01

The authors sought to increase understanding of the brain mechanisms involved in cigarette addiction by identifying neural substrates modulated by visual smoking cues in nicotine-deprived smokers. Event-related functional magnetic resonance imaging (fMRI) was used to detect brain activation after exposure to smoking-related images in a group of nicotine-deprived smokers and a nonsmoking comparison group. Subjects viewed a pseudo-random sequence of smoking images, neutral nonsmoking images, and rare targets (photographs of animals). Subjects pressed a button whenever a rare target appeared. In smokers, the fMRI signal was greater after exposure to smoking-related images than after exposure to neutral images in mesolimbic dopamine reward circuits known to be activated by addictive drugs (right posterior amygdala, posterior hippocampus, ventral tegmental area, and medial thalamus) as well as in areas related to visuospatial attention (bilateral prefrontal and parietal cortex and right fusiform gyrus). In nonsmokers, no significant differences in fMRI signal following exposure to smoking-related and neutral images were detected. In most regions studied, both subject groups showed greater activation following presentation of rare target images than after exposure to neutral images. In nicotine-deprived smokers, both reward and attention circuits were activated by exposure to smoking-related images. Smoking cues are processed like rare targets in that they activate attentional regions. These cues are also processed like addictive drugs in that they activate mesolimbic reward regions.

Neural circuits. Labeling of active neural circuits in vivo with designed calcium integrators.

PubMed

Fosque, Benjamin F; Sun, Yi; Dana, Hod; Yang, Chao-Tsung; Ohyama, Tomoko; Tadross, Michael R; Patel, Ronak; Zlatic, Marta; Kim, Douglas S; Ahrens, Misha B; Jayaraman, Vivek; Looger, Loren L; Schreiter, Eric R

2015-02-13

The identification of active neurons and circuits in vivo is a fundamental challenge in understanding the neural basis of behavior. Genetically encoded calcium (Ca(2+)) indicators (GECIs) enable quantitative monitoring of cellular-resolution activity during behavior. However, such indicators require online monitoring within a limited field of view. Alternatively, post hoc staining of immediate early genes (IEGs) indicates highly active cells within the entire brain, albeit with poor temporal resolution. We designed a fluorescent sensor, CaMPARI, that combines the genetic targetability and quantitative link to neural activity of GECIs with the permanent, large-scale labeling of IEGs, allowing a temporally precise "activity snapshot" of a large tissue volume. CaMPARI undergoes efficient and irreversible green-to-red conversion only when elevated intracellular Ca(2+) and experimenter-controlled illumination coincide. We demonstrate the utility of CaMPARI in freely moving larvae of zebrafish and flies, and in head-fixed mice and adult flies. Copyright © 2015, American Association for the Advancement of Science.

The anatomy and physiology of the ocular motor system.

PubMed

Horn, Anja K E; Leigh, R John

2011-01-01

Accurate diagnosis of abnormal eye movements depends upon knowledge of the purpose, properties, and neural substrate of distinct functional classes of eye movement. Here, we summarize current concepts of the anatomy of eye movement control. Our approach is bottom-up, starting with the extraocular muscles and their innervation by the cranial nerves. Second, we summarize the neural circuits in the pons underlying horizontal gaze control, and the midbrain connections that coordinate vertical and torsional movements. Third, the role of the cerebellum in governing and optimizing eye movements is presented. Fourth, each area of cerebral cortex contributing to eye movements is discussed. Last, descending projections from cerebral cortex, including basal ganglionic circuits that govern different components of gaze, and the superior colliculus, are summarized. At each stage of this review, the anatomical scheme is used to predict the effects of lesions on the control of eye movements, providing clinical-anatomical correlation. Copyright © 2011 Elsevier B.V. All rights reserved.

Multi-sensory integration in a small brain

NASA Astrophysics Data System (ADS)

Gepner, Ruben; Wolk, Jason; Gershow, Marc

Understanding how fluctuating multi-sensory stimuli are integrated and transformed in neural circuits has proved a difficult task. To address this question, we study the sensori-motor transformations happening in the brain of the Drosophila larva, a tractable model system with about 10,000 neurons. Using genetic tools that allow us to manipulate the activity of individual brain cells through their transparent body, we observe the stochastic decisions made by freely-behaving animals as their visual and olfactory environments fluctuate independently. We then use simple linear-nonlinear models to correlate outputs with relevant features in the inputs, and adaptive filtering processes to track changes in these relevant parameters used by the larva's brain to make decisions. We show how these techniques allow us to probe how statistics of stimuli from different sensory modalities combine to affect behavior, and can potentially guide our understanding of how neural circuits are anatomically and functionally integrated. Supported by NIH Grant 1DP2EB022359 and NSF Grant PHY-1455015.

Neural mechanisms underlying sensitivity to reverse-phi motion in the fly

PubMed Central

Meier, Matthias; Serbe, Etienne; Eichner, Hubert; Borst, Alexander

2017-01-01

Optical illusions provide powerful tools for mapping the algorithms and circuits that underlie visual processing, revealing structure through atypical function. Of particular note in the study of motion detection has been the reverse-phi illusion. When contrast reversals accompany discrete movement, detected direction tends to invert. This occurs across a wide range of organisms, spanning humans and invertebrates. Here, we map an algorithmic account of the phenomenon onto neural circuitry in the fruit fly Drosophila melanogaster. Through targeted silencing experiments in tethered walking flies as well as electrophysiology and calcium imaging, we demonstrate that ON- or OFF-selective local motion detector cells T4 and T5 are sensitive to certain interactions between ON and OFF. A biologically plausible detector model accounts for subtle features of this particular form of illusory motion reversal, like the re-inversion of turning responses occurring at extreme stimulus velocities. In light of comparable circuit architecture in the mammalian retina, we suggest that similar mechanisms may apply even to human psychophysics. PMID:29261684

Neural mechanisms underlying sensitivity to reverse-phi motion in the fly.

PubMed

Leonhardt, Aljoscha; Meier, Matthias; Serbe, Etienne; Eichner, Hubert; Borst, Alexander

2017-01-01

Optical illusions provide powerful tools for mapping the algorithms and circuits that underlie visual processing, revealing structure through atypical function. Of particular note in the study of motion detection has been the reverse-phi illusion. When contrast reversals accompany discrete movement, detected direction tends to invert. This occurs across a wide range of organisms, spanning humans and invertebrates. Here, we map an algorithmic account of the phenomenon onto neural circuitry in the fruit fly Drosophila melanogaster. Through targeted silencing experiments in tethered walking flies as well as electrophysiology and calcium imaging, we demonstrate that ON- or OFF-selective local motion detector cells T4 and T5 are sensitive to certain interactions between ON and OFF. A biologically plausible detector model accounts for subtle features of this particular form of illusory motion reversal, like the re-inversion of turning responses occurring at extreme stimulus velocities. In light of comparable circuit architecture in the mammalian retina, we suggest that similar mechanisms may apply even to human psychophysics.

Distinct Sources of Deterministic and Stochastic Components of Action Timing Decisions in Rodent Frontal Cortex.

PubMed

Murakami, Masayoshi; Shteingart, Hanan; Loewenstein, Yonatan; Mainen, Zachary F

2017-05-17

The selection and timing of actions are subject to determinate influences such as sensory cues and internal state as well as to effectively stochastic variability. Although stochastic choice mechanisms are assumed by many theoretical models, their origin and mechanisms remain poorly understood. Here we investigated this issue by studying how neural circuits in the frontal cortex determine action timing in rats performing a waiting task. Electrophysiological recordings from two regions necessary for this behavior, medial prefrontal cortex (mPFC) and secondary motor cortex (M2), revealed an unexpected functional dissociation. Both areas encoded deterministic biases in action timing, but only M2 neurons reflected stochastic trial-by-trial fluctuations. This differential coding was reflected in distinct timescales of neural dynamics in the two frontal cortical areas. These results suggest a two-stage model in which stochastic components of action timing decisions are injected by circuits downstream of those carrying deterministic bias signals. Copyright © 2017 Elsevier Inc. All rights reserved.

Multiple conserved cell adhesion protein interactions mediate neural wiring of a sensory circuit in C. elegans.

PubMed

Kim, Byunghyuk; Emmons, Scott W

2017-09-13

Nervous system function relies on precise synaptic connections. A number of widely-conserved cell adhesion proteins are implicated in cell recognition between synaptic partners, but how these proteins act as a group to specify a complex neural network is poorly understood. Taking advantage of known connectivity in C. elegans , we identified and studied cell adhesion genes expressed in three interacting neurons in the mating circuits of the adult male. Two interacting pairs of cell surface proteins independently promote fasciculation between sensory neuron HOA and its postsynaptic target interneuron AVG: BAM-2/neurexin-related in HOA binds to CASY-1/calsyntenin in AVG; SAX-7/L1CAM in sensory neuron PHC binds to RIG-6/contactin in AVG. A third, basal pathway results in considerable HOA-AVG fasciculation and synapse formation in the absence of the other two. The features of this multiplexed mechanism help to explain how complex connectivity is encoded and robustly established during nervous system development.

Fife organizes synaptic vesicles and calcium channels for high-probability neurotransmitter release

PubMed Central

Rao, Monica; Ukken, Fiona

2017-01-01

The strength of synaptic connections varies significantly and is a key determinant of communication within neural circuits. Mechanistic insight into presynaptic factors that establish and modulate neurotransmitter release properties is crucial to understanding synapse strength, circuit function, and neural plasticity. We previously identified Drosophila Piccolo-RIM-related Fife, which regulates neurotransmission and motor behavior through an unknown mechanism. Here, we demonstrate that Fife localizes and interacts with RIM at the active zone cytomatrix to promote neurotransmitter release. Loss of Fife results in the severe disruption of active zone cytomatrix architecture and molecular organization. Through electron tomographic and electrophysiological studies, we find a decrease in the accumulation of release-ready synaptic vesicles and their release probability caused by impaired coupling to Ca2+ channels. Finally, we find that Fife is essential for the homeostatic modulation of neurotransmission. We propose that Fife organizes active zones to create synaptic vesicle release sites within nanometer distance of Ca2+ channel clusters for reliable and modifiable neurotransmitter release. PMID:27998991

Video time encoding machines.

PubMed

Lazar, Aurel A; Pnevmatikakis, Eftychios A

2011-03-01

We investigate architectures for time encoding and time decoding of visual stimuli such as natural and synthetic video streams (movies, animation). The architecture for time encoding is akin to models of the early visual system. It consists of a bank of filters in cascade with single-input multi-output neural circuits. Neuron firing is based on either a threshold-and-fire or an integrate-and-fire spiking mechanism with feedback. We show that analog information is represented by the neural circuits as projections on a set of band-limited functions determined by the spike sequence. Under Nyquist-type and frame conditions, the encoded signal can be recovered from these projections with arbitrary precision. For the video time encoding machine architecture, we demonstrate that band-limited video streams of finite energy can be faithfully recovered from the spike trains and provide a stable algorithm for perfect recovery. The key condition for recovery calls for the number of neurons in the population to be above a threshold value.

Video Time Encoding Machines

PubMed Central

Lazar, Aurel A.; Pnevmatikakis, Eftychios A.

2013-01-01

We investigate architectures for time encoding and time decoding of visual stimuli such as natural and synthetic video streams (movies, animation). The architecture for time encoding is akin to models of the early visual system. It consists of a bank of filters in cascade with single-input multi-output neural circuits. Neuron firing is based on either a threshold-and-fire or an integrate-and-fire spiking mechanism with feedback. We show that analog information is represented by the neural circuits as projections on a set of band-limited functions determined by the spike sequence. Under Nyquist-type and frame conditions, the encoded signal can be recovered from these projections with arbitrary precision. For the video time encoding machine architecture, we demonstrate that band-limited video streams of finite energy can be faithfully recovered from the spike trains and provide a stable algorithm for perfect recovery. The key condition for recovery calls for the number of neurons in the population to be above a threshold value. PMID:21296708

Using high-throughput barcode sequencing to efficiently map connectomes

PubMed Central

Peikon, Ian D.; Kebschull, Justus M.; Vagin, Vasily V.; Ravens, Diana I.; Sun, Yu-Chi; Brouzes, Eric; Corrêa, Ivan R.; Bressan, Dario

2017-01-01

Abstract The function of a neural circuit is determined by the details of its synaptic connections. At present, the only available method for determining a neural wiring diagram with single synapse precision—a ‘connectome’—is based on imaging methods that are slow, labor-intensive and expensive. Here, we present SYNseq, a method for converting the connectome into a form that can exploit the speed and low cost of modern high-throughput DNA sequencing. In SYNseq, each neuron is labeled with a unique random nucleotide sequence—an RNA ‘barcode’—which is targeted to the synapse using engineered proteins. Barcodes in pre- and postsynaptic neurons are then associated through protein-protein crosslinking across the synapse, extracted from the tissue, and joined into a form suitable for sequencing. Although our failure to develop an efficient barcode joining scheme precludes the widespread application of this approach, we expect that with further development SYNseq will enable tracing of complex circuits at high speed and low cost. PMID:28449067

Neuromorphic photonic networks using silicon photonic weight banks.

PubMed

Tait, Alexander N; de Lima, Thomas Ferreira; Zhou, Ellen; Wu, Allie X; Nahmias, Mitchell A; Shastri, Bhavin J; Prucnal, Paul R

2017-08-07

Photonic systems for high-performance information processing have attracted renewed interest. Neuromorphic silicon photonics has the potential to integrate processing functions that vastly exceed the capabilities of electronics. We report first observations of a recurrent silicon photonic neural network, in which connections are configured by microring weight banks. A mathematical isomorphism between the silicon photonic circuit and a continuous neural network model is demonstrated through dynamical bifurcation analysis. Exploiting this isomorphism, a simulated 24-node silicon photonic neural network is programmed using "neural compiler" to solve a differential system emulation task. A 294-fold acceleration against a conventional benchmark is predicted. We also propose and derive power consumption analysis for modulator-class neurons that, as opposed to laser-class neurons, are compatible with silicon photonic platforms. At increased scale, Neuromorphic silicon photonics could access new regimes of ultrafast information processing for radio, control, and scientific computing.

Changes in the Spinal Neural Circuits are Dependent on the Movement Speed of the Visuomotor Task

PubMed Central

Kubota, Shinji; Hirano, Masato; Koizume, Yoshiki; Tanabe, Shigeo; Funase, Kozo

2015-01-01

Previous studies have shown that spinal neural circuits are modulated by motor skill training. However, the effects of task movement speed on changes in spinal neural circuits have not been clarified. The aim of this research was to investigate whether spinal neural circuits were affected by task movement speed. Thirty-eight healthy subjects participated in this study. In experiment 1, the effects of task movement speed on the spinal neural circuits were examined. Eighteen subjects performed a visuomotor task involving ankle muscle slow (nine subjects) or fast (nine subjects) movement speed. Another nine subjects performed a non-visuomotor task (controls) in fast movement speed. The motor task training lasted for 20 min. The amounts of D1 inhibition and reciprocal Ia inhibition were measured using H-relfex condition-test paradigm and recorded before, and at 5, 15, and 30 min after the training session. In experiment 2, using transcranial magnetic stimulation (TMS), the effects of corticospinal descending inputs on the presynaptic inhibitory pathway were examined before and after performing either a visuomotor (eight subjects) or a control task (eight subjects). All measurements were taken under resting conditions. The amount of D1 inhibition increased after the visuomotor task irrespective of movement speed (P < 0.01). The amount of reciprocal Ia inhibition increased with fast movement speed conditioning (P < 0.01), but was unchanged by slow movement speed conditioning. These changes lasted up to 15 min in D1 inhibition and 5 min in reciprocal Ia inhibition after the training session. The control task did not induce changes in D1 inhibition and reciprocal Ia inhibition. The TMS conditioned inhibitory effects of presynaptic inhibitory pathways decreased following visuomotor tasks (P < 0.01). The size of test H-reflex was almost the same size throughout experiments. The results suggest that supraspinal descending inputs for controlling joint movement are responsible for changes in the spinal neural circuits, and that task movement speed is one of the critical factors for inducing plastic changes in reciprocal Ia inhibition. PMID:26696873

Complex computation in the retina

NASA Astrophysics Data System (ADS)

Deshmukh, Nikhil Rajiv

Elucidating the general principles of computation in neural circuits is a difficult problem requiring both a tractable model circuit as well as sophisticated measurement tools. This thesis advances our understanding of complex computation in the salamander retina and its underlying circuitry and furthers the development of advanced tools to enable detailed study of neural circuits. The retina provides an ideal model system for neural circuits in general because it is capable of producing complex representations of the visual scene, and both its inputs and outputs are accessible to the experimenter. Chapter 2 describes the biophysical mechanisms that give rise to the omitted stimulus response in retinal ganglion cells described in Schwartz et al., (2007) and Schwartz and Berry, (2008). The extra response to omitted flashes is generated at the input to bipolar cells, and is separable from the characteristic latency shift of the OSR apparent in ganglion cells, which must occur downstream in the circuit. Chapter 3 characterizes the nonlinearities at the first synapse of the ON pathway in response to high contrast flashes and develops a phenomenological model that captures the effect of synaptic activation and intracellular signaling dynamics on flash responses. This work is the first attempt to model the dynamics of the poorly characterized mGluR6 transduction cascade unique to ON bipolar cells, and explains the second lobe of the biphasic flash response. Complementary to the study of neural circuits, recent advances in wafer-scale photolithography have made possible new devices to measure the electrical and mechanical properties of neurons. Chapter 4 reports a novel piezoelectric sensor that facilitates the simultaneous measurement of electrical and mechanical signals in neural tissue. This technology could reveal the relationship between the electrical activity of neurons and their local mechanical environment, which is critical to the study of mechanoreceptors, neural development, and traumatic brain injury. Chapter 5 describes advances in the development, fabrication, and testing of a prototype silicon micropipette for patch clamp physiology. Nanoscale photolithography addresses some of the limitations of traditional glass patch electrodes, such as the rapid dialysis of the cell with internal solution, and provides a platform for integration of microfluidics and electronics into the device, which can enable novel experimental methodology.

Thalamo-Sensorimotor Functional Connectivity Correlates with World Ranking of Olympic, Elite, and High Performance Athletes.

PubMed

Huang, Zirui; Davis, Henry Hap; Wolff, Annemarie; Northoff, Georg

2017-01-01

Brain plasticity studies have shown functional reorganization in participants with outstanding motor expertise. Little is known about neural plasticity associated with exceptionally long motor training or of its predictive value for motor performance excellence. The present study utilised resting-state functional magnetic resonance imaging (rs-fMRI) in a unique sample of world-class athletes: Olympic, elite, and internationally ranked swimmers ( n = 30). Their world ranking ranged from 1st to 250th: each had prepared for participation in the Olympic Games. Combining rs-fMRI graph-theoretical and seed-based functional connectivity analyses, it was discovered that the thalamus has its strongest connections with the sensorimotor network in elite swimmers with the highest world rankings (career best rank: 1-35). Strikingly, thalamo-sensorimotor functional connections were highly correlated with the swimmers' motor performance excellence, that is, accounting for 41% of the individual variance in best world ranking. Our findings shed light on neural correlates of long-term athletic performance involving thalamo-sensorimotor functional circuits.

Repetitive behaviors in autism are linked to imbalance of corticostriatal connectivity: a functional connectivity MRI study.

PubMed

Abbott, Angela E; Linke, Annika C; Nair, Aarti; Jahedi, Afrooz; Alba, Laura A; Keown, Christopher L; Fishman, Inna; Müller, Ralph-Axel

2018-01-01

The neural underpinnings of repetitive behaviors (RBs) in autism spectrum disorders (ASDs), ranging from cognitive to motor characteristics, remain unknown. We assessed RB symptomatology in 50 ASD and 52 typically developing (TD) children and adolescents (ages 8-17 years), examining intrinsic functional connectivity (iFC) of corticostriatal circuitry, which is important for reward-based learning and integration of emotional, cognitive and motor processing, and considered impaired in ASDs. Connectivity analyses were performed for three functionally distinct striatal seeds (limbic, frontoparietal and motor). Functional connectivity with cortical regions of interest was assessed for corticostriatal circuit connectivity indices and ratios, testing the balance of connectivity between circuits. Results showed corticostriatal overconnectivity of limbic and frontoparietal seeds, but underconnectivity of motor seeds. Correlations with RBs were found for connectivity between the striatal motor seeds and cortical motor clusters from the whole-brain analysis, and for frontoparietal/limbic and motor/limbic connectivity ratios. Division of ASD participants into high (n = 17) and low RB subgroups (n = 19) showed reduced frontoparietal/limbic and motor/limbic circuit ratios for high RB compared to low RB and TD groups in the right hemisphere. Results suggest an association between RBs and an imbalance of corticostriatal iFC in ASD, being increased for limbic, but reduced for frontoparietal and motor circuits. © The Author (2017). Published by Oxford University Press.

Repetitive behaviors in autism are linked to imbalance of corticostriatal connectivity: a functional connectivity MRI study

PubMed Central

Abbott, Angela E; Linke, Annika C; Nair, Aarti; Jahedi, Afrooz; Alba, Laura A; Keown, Christopher L; Fishman, Inna

2018-01-01

Abstract The neural underpinnings of repetitive behaviors (RBs) in autism spectrum disorders (ASDs), ranging from cognitive to motor characteristics, remain unknown. We assessed RB symptomatology in 50 ASD and 52 typically developing (TD) children and adolescents (ages 8–17 years), examining intrinsic functional connectivity (iFC) of corticostriatal circuitry, which is important for reward-based learning and integration of emotional, cognitive and motor processing, and considered impaired in ASDs. Connectivity analyses were performed for three functionally distinct striatal seeds (limbic, frontoparietal and motor). Functional connectivity with cortical regions of interest was assessed for corticostriatal circuit connectivity indices and ratios, testing the balance of connectivity between circuits. Results showed corticostriatal overconnectivity of limbic and frontoparietal seeds, but underconnectivity of motor seeds. Correlations with RBs were found for connectivity between the striatal motor seeds and cortical motor clusters from the whole-brain analysis, and for frontoparietal/limbic and motor/limbic connectivity ratios. Division of ASD participants into high (n = 17) and low RB subgroups (n = 19) showed reduced frontoparietal/limbic and motor/limbic circuit ratios for high RB compared to low RB and TD groups in the right hemisphere. Results suggest an association between RBs and an imbalance of corticostriatal iFC in ASD, being increased for limbic, but reduced for frontoparietal and motor circuits. PMID:29177509

Nonlinear dynamics based digital logic and circuits.

PubMed

Kia, Behnam; Lindner, John F; Ditto, William L

2015-01-01

We discuss the role and importance of dynamics in the brain and biological neural networks and argue that dynamics is one of the main missing elements in conventional Boolean logic and circuits. We summarize a simple dynamics based computing method, and categorize different techniques that we have introduced to realize logic, functionality, and programmability. We discuss the role and importance of coupled dynamics in networks of biological excitable cells, and then review our simple coupled dynamics based method for computing. In this paper, for the first time, we show how dynamics can be used and programmed to implement computation in any given base, including but not limited to base two.

Ionic current devices-Recent progress in the merging of electronic, microfluidic, and biomimetic structures.

PubMed

Koo, Hyung-Jun; Velev, Orlin D

2013-05-09

We review the recent progress in the emerging area of devices and circuits operating on the basis of ionic currents. These devices operate at the intersection of electrochemistry, electronics, and microfluidics, and their potential applications are inspired by essential biological processes such as neural transmission. Ionic current rectification has been demonstrated in diode-like devices containing electrolyte solutions, hydrogel, or hydrated nanofilms. More complex functions have been realized in ionic current based transistors, solar cells, and switching memory devices. Microfluidic channels and networks-an intrinsic component of the ionic devices-could play the role of wires and circuits in conventional electronics.

A wave shaping approach of ferrite inductors exhibiting hysteresis using orthogonal field bias

NASA Astrophysics Data System (ADS)

Adly, A. A.; Abd-El-Hafiz, S. K.; Mahgoub, A. O.

2018-05-01

Advances in power electronic systems have considerably contributed to a wide spectrum of applications. In most power electronic circuits, inductors play crucial functions. Utilization of ferrite cores becomes a must when large inductances are required. Nevertheless, this results in an additional complexity due to their hysteresis nature. Recently, an efficient approach for modeling vector hysteresis using tri-node Hopfield neural networks (HNNs) has been introduced. This paper presents a wave shaping approach using hollow cylindrical ferrite core inductors having axial and toroidal windings. The approach investigates the possibility of tuning the inductor permeability to minimize circuit harmonics. Details of the approach are given in the paper.

Supraspinal Control Predicts Locomotor Function and Forecasts Responsiveness to Training after Spinal Cord Injury

PubMed Central

Field-Fote, Edelle C.; Yang, Jaynie F.; Basso, D. Michele; Gorassini, Monica A.

2017-01-01

Abstract Restoration of walking ability is an area of great interest in the rehabilitation of persons with spinal cord injury. Because many cortical, subcortical, and spinal neural centers contribute to locomotor function, it is important that intervention strategies be designed to target neural elements at all levels of the neuraxis that are important for walking ability. While to date most strategies have focused on activation of spinal circuits, more recent studies are investigating the value of engaging supraspinal circuits. Despite the apparent potential of pharmacological, biological, and genetic approaches, as yet none has proved more effective than physical therapeutic rehabilitation strategies. By making optimal use of the potential of the nervous system to respond to training, strategies can be developed that meet the unique needs of each person. To complement the development of optimal training interventions, it is valuable to have the ability to predict future walking function based on early clinical presentation, and to forecast responsiveness to training. A number of clinical prediction rules and association models based on common clinical measures have been developed with the intent, respectively, to predict future walking function based on early clinical presentation, and to delineate characteristics associated with responsiveness to training. Further, a number of variables that are correlated with walking function have been identified. Not surprisingly, most of these prediction rules, association models, and correlated variables incorporate measures of volitional lower extremity strength, illustrating the important influence of supraspinal centers in the production of walking behavior in humans. PMID:27673569

Towards a mechanistic understanding of pathological anxiety: the dorsal medial prefrontal-amygdala 'aversive amplification' circuit in unmedicated generalized and social anxiety disorders.

PubMed

Robinson, Oliver J; Krimsky, Marissa; Lieberman, Lynne; Allen, Phillip; Vytal, Katherine; Grillon, Christian

2014-09-01

We have delineated, across four prior studies, the role of positive dorsal medial prefrontal/anterior cingulate cortex (dmPFC/ACC)-amygdala circuit coupling during aversive processing in healthy individuals under stress. This translational circuit, termed the 'aversive amplification circuit', is thought to drive adaptive, harm-avoidant behavior in threatening environments. Here, in a natural progression of this prior work, we confirm that this circuit also plays a role in the pathological manifestation of anxiety disorders. Forty-five unmedicated participants (N=22 generalized and social anxiety disorder/N=23 controls) recruited from Washington DC metropolitan area completed a simple emotion identification task during functional magnetic resonance imaging at the National Institutes of Health, Bethesda, MD, USA. As predicted, a diagnosis by valence interaction was seen in whole-brain amygdala connectivity within the dmPFC/ACC clusters identified in our prior study; driven by significantly greater circuit coupling during fearful versus happy face processing in anxious, but not healthy, participants. Critically, and in accordance with contemporary theoretical approaches to psychiatry, circuit coupling correlated positively with self-reported anxious symptoms, providing evidence of a continuous circuit-subjective symptomatology relationship. We track the functional role of a single neural circuit from its involvement in adaptive threat-biases under stress, to its chronic engagement in anxiety disorders in the absence of experimentally induced stress. Thus, we uniquely map a mood and anxiety related circuit across its adaptive and maladaptive stages. Clinically, this may provide a step towards a more mechanistic spectrum-based approach to anxiety disorder diagnosis and may ultimately lead to more targeted treatments.

Neural mechanisms of movement planning: motor cortex and beyond.

PubMed

Svoboda, Karel; Li, Nuo

2018-04-01

Neurons in motor cortex and connected brain regions fire in anticipation of specific movements, long before movement occurs. This neural activity reflects internal processes by which the brain plans and executes volitional movements. The study of motor planning offers an opportunity to understand how the structure and dynamics of neural circuits support persistent internal states and how these states influence behavior. Recent advances in large-scale neural recordings are beginning to decipher the relationship of the dynamics of populations of neurons during motor planning and movements. New behavioral tasks in rodents, together with quantified perturbations, link dynamics in specific nodes of neural circuits to behavior. These studies reveal a neural network distributed across multiple brain regions that collectively supports motor planning. We review recent advances and highlight areas where further work is needed to achieve a deeper understanding of the mechanisms underlying motor planning and related cognitive processes. Copyright © 2017. Published by Elsevier Ltd.

Intergenerational neural mediators of early-life anxious temperament.

PubMed

Fox, Andrew S; Oler, Jonathan A; Shackman, Alexander J; Shelton, Steven E; Raveendran, Muthuswamy; McKay, D Reese; Converse, Alexander K; Alexander, Andrew; Davidson, Richard J; Blangero, John; Rogers, Jeffrey; Kalin, Ned H

2015-07-21

Understanding the heritability of neural systems linked to psychopathology is not sufficient to implicate them as intergenerational neural mediators. By closely examining how individual differences in neural phenotypes and psychopathology cosegregate as they fall through the family tree, we can identify the brain systems that underlie the parent-to-child transmission of psychopathology. Although research has identified genes and neural circuits that contribute to the risk of developing anxiety and depression, the specific neural systems that mediate the inborn risk for these debilitating disorders remain unknown. In a sample of 592 young rhesus monkeys that are part of an extended multigenerational pedigree, we demonstrate that metabolism within a tripartite prefrontal-limbic-midbrain circuit mediates some of the inborn risk for developing anxiety and depression. Importantly, although brain volume is highly heritable early in life, it is brain metabolism-not brain structure-that is the critical intermediary between genetics and the childhood risk to develop stress-related psychopathology.

Executive Dysfunctions: The Role in Attention Deficit Hyperactivity and Post-traumatic Stress Neuropsychiatric Disorders

PubMed Central

Martínez, Lía; Prada, Edward; Satler, Corina; Tavares, Maria C. H.; Tomaz, Carlos

2016-01-01

Executive functions (EFs) is an umbrella term for various cognitive processes controlled by a complex neural activity, which allow the production of different types of behaviors seeking to achieve specific objectives, one of them being inhibitory control. There is a wide consensus that clinical and behavioral alterations associated with EF, such as inhibitory control, are present in various neuropsychiatric disorders. This paper reviews the research literature on the relationship between executive dysfunction, frontal-subcortical neural circuit changes, and the psychopathological processes associated with attention deficit hyperactivity disorder (ADHD) and post-traumatic stress disorder (PTSD). A revision on the role of frontal-subcortical neural circuits and their presumable abnormal functioning and the high frequency of neuropsychiatric symptoms could explain the difficulties with putting effector mechanisms into action, giving individuals the necessary tools to act efficiently in their environment. Although, neuronal substrate data about ADHD and PTSD has been reported in the literature, it is isolated. Therefore, this review highlights the overlapping of neural substrates in the symptomatology of ADHD and PTSD disorders concerning EFs, especially in the inhibitory component. Thus, the changes related to impaired EF that accompany disorders like ADHD and PTSD could be explained by disturbances that have a direct or indirect impact on the functioning of these loops. Initially, the theoretical model of EF according to current neuropsychology will be presented, focusing on the inhibitory component. In a second stage, this component will be analyzed for each of the disorders of interest, considering the clinical aspects, the etiology and the neurobiological basis. Additionally, commonalities between the two neuropsychiatric conditions will be taken into consideration from the perspectives of cognitive and emotional inhibition. Finally, the implications and future prospects for research and interventions in the area will be outlined, with the intention of contributing scientific reference information that encompasses the knowledge and understanding of executive dysfunction and its relationship with these treated disorders. PMID:27602003

The neural architecture of expert calendar calculation: a matter of strategy?

PubMed

Fehr, Thorsten; Wallace, Gregory L; Erhard, Peter; Herrmann, Manfred

2011-08-01

Savants and prodigies are individuals with exceptional skills in particular mental domains. In the present study we used functional magnetic resonance imaging to examine neural correlates of calendar calculation in two individuals, a savant with Asperger's disorder and a self-taught mathematical prodigy. If there is a modular neural organization of exceptional performance in a specific mental domain, calendar calculation should be reflected in a considerable overlap in the recruitment of brain circuits across expert individuals. However, considerable individual differences in activation patterns during calendar calculation were noted. The present results indicate that activation patterns produced by complex mental processing, such as calendar calculation, seem to be influenced strongly by learning history and idiosyncratic strategy usage rather than a modular neural organization. Thus, well-known individual differences in complex cognition play a major role even in experts with exceptional abilities in a particular mental domain and should in particular be considered when examining the neural architecture of complex mental processes and skills.

Reward and aversion in a heterogeneous midbrain dopamine system.

PubMed

Lammel, Stephan; Lim, Byung Kook; Malenka, Robert C

2014-01-01

The ventral tegmental area (VTA) is a heterogeneous brain structure that serves a central role in motivation and reward processing. Abnormalities in the function of VTA dopamine (DA) neurons and the targets they influence are implicated in several prominent neuropsychiatric disorders including addiction and depression. Recent studies suggest that the midbrain DA system is composed of anatomically and functionally heterogeneous DA subpopulations with different axonal projections. These findings may explain a number of previously confusing observations that suggested a role for DA in processing both rewarding as well as aversive events. Here we will focus on recent advances in understanding the neural circuits mediating reward and aversion in the VTA and how stress as well as drugs of abuse, in particular cocaine, alter circuit function within a heterogeneous midbrain DA system. This article is part of a Special Issue entitled 'NIDA 40th Anniversary Issue'. Copyright © 2013 Elsevier Ltd. All rights reserved.

Whole-brain activity maps reveal stereotyped, distributed networks for visuomotor behavior.

PubMed

Portugues, Ruben; Feierstein, Claudia E; Engert, Florian; Orger, Michael B

2014-03-19

Most behaviors, even simple innate reflexes, are mediated by circuits of neurons spanning areas throughout the brain. However, in most cases, the distribution and dynamics of firing patterns of these neurons during behavior are not known. We imaged activity, with cellular resolution, throughout the whole brains of zebrafish performing the optokinetic response. We found a sparse, broadly distributed network that has an elaborate but ordered pattern, with a bilaterally symmetrical organization. Activity patterns fell into distinct clusters reflecting sensory and motor processing. By correlating neuronal responses with an array of sensory and motor variables, we find that the network can be clearly divided into distinct functional modules. Comparing aligned data from multiple fish, we find that the spatiotemporal activity dynamics and functional organization are highly stereotyped across individuals. These experiments systematically reveal the functional architecture of neural circuits underlying a sensorimotor behavior in a vertebrate brain. Copyright © 2014 Elsevier Inc. All rights reserved.

Whole-brain activity maps reveal stereotyped, distributed networks for visuomotor behavior

PubMed Central

Portugues, Ruben; Feierstein, Claudia E.; Engert, Florian; Orger, Michael B.

2014-01-01

Summary Most behaviors, even simple innate reflexes, are mediated by circuits of neurons spanning areas throughout the brain. However, in most cases, the distribution and dynamics of firing patterns of these neurons during behavior are not known. We imaged activity, with cellular resolution, throughout the whole brains of zebrafish performing the optokinetic response. We found a sparse, broadly distributed network that has an elaborate, but ordered, pattern, with a bilaterally symmetrical organization. Activity patterns fell into distinct clusters reflecting sensory and motor processing. By correlating neuronal responses with an array of sensory and motor variables, we find that the network can be clearly divided into distinct functional modules. Comparing aligned data from multiple fish, we find that the spatiotemporal activity dynamics and functional organization are highly stereotyped across individuals. These experiments reveal, for the first time in a vertebrate, the comprehensive functional architecture of the neural circuits underlying a sensorimotor behavior. PMID:24656252

THE ROLE OF SEROTONIN IN RESPIRATORY FUNCTION AND DYSFUNCTION

PubMed Central

Hilaire, Gérard; Voituron, Nicolas; Menuet, Clément; Ichiyama, Ronaldo M.; Subramanian, Hari H.; Dutschmann, Mathias

2010-01-01

Serotonin (5-HT) is a neuro-modulator–transmitter influencing global brain function. Past and present findings illustrate a prominent role for 5-HT in the modulation of ponto-medullary autonomic circuits. 5-HT is also involved in the control of neurotrophic processes during pre- and postnatal development of neural circuits. The functional implications of 5-HT is particularly illustrated in the alterations to the serotonergic system, as seen in a wide range of neurological disorders. This article reviews the role of 5-HT in the development and control of respiratory networks in the ponto-medullary brainstem. The review further examines the role of 5-HT in breathing disorders occurring at different stages of life, in particular, the neonatal neurodevelopmental diseases such as Rett, sudden infant death and Prader-Willi syndromes, adult diseases such as sleep apnoea and mental illness linked to neurodegeneration. PMID:20801236

A closed-loop compressive-sensing-based neural recording system.

PubMed

Zhang, Jie; Mitra, Srinjoy; Suo, Yuanming; Cheng, Andrew; Xiong, Tao; Michon, Frederic; Welkenhuysen, Marleen; Kloosterman, Fabian; Chin, Peter S; Hsiao, Steven; Tran, Trac D; Yazicioglu, Firat; Etienne-Cummings, Ralph

2015-06-01

This paper describes a low power closed-loop compressive sensing (CS) based neural recording system. This system provides an efficient method to reduce data transmission bandwidth for implantable neural recording devices. By doing so, this technique reduces a majority of system power consumption which is dissipated at data readout interface. The design of the system is scalable and is a viable option for large scale integration of electrodes or recording sites onto a single device. The entire system consists of an application-specific integrated circuit (ASIC) with 4 recording readout channels with CS circuits, a real time off-chip CS recovery block and a recovery quality evaluation block that provides a closed feedback to adaptively adjust compression rate. Since CS performance is strongly signal dependent, the ASIC has been tested in vivo and with standard public neural databases. Implemented using efficient digital circuit, this system is able to achieve >10 times data compression on the entire neural spike band (500-6KHz) while consuming only 0.83uW (0.53 V voltage supply) additional digital power per electrode. When only the spikes are desired, the system is able to further compress the detected spikes by around 16 times. Unlike other similar systems, the characteristic spikes and inter-spike data can both be recovered which guarantes a >95% spike classification success rate. The compression circuit occupied 0.11mm(2)/electrode in a 180nm CMOS process. The complete signal processing circuit consumes <16uW/electrode. Power and area efficiency demonstrated by the system make it an ideal candidate for integration into large recording arrays containing thousands of electrode. Closed-loop recording and reconstruction performance evaluation further improves the robustness of the compression method, thus making the system more practical for long term recording.

Beyond Molecular Codes: Simple Rules to Wire Complex Brains

PubMed Central

Hassan, Bassem A.; Hiesinger, P. Robin

2015-01-01

Summary Molecular codes, like postal zip codes, are generally considered a robust way to ensure the specificity of neuronal target selection. However, a code capable of unambiguously generating complex neural circuits is difficult to conceive. Here, we re-examine the notion of molecular codes in the light of developmental algorithms. We explore how molecules and mechanisms that have been considered part of a code may alternatively implement simple pattern formation rules sufficient to ensure wiring specificity in neural circuits. This analysis delineates a pattern-based framework for circuit construction that may contribute to our understanding of brain wiring. PMID:26451480

Light, heat, action: neural control of fruit fly behaviour

PubMed Central

Owald, David; Lin, Suewei; Waddell, Scott

2015-01-01

The fruit fly Drosophila melanogaster has emerged as a popular model to investigate fundamental principles of neural circuit operation. The sophisticated genetics and small brain permit a cellular resolution understanding of innate and learned behavioural processes. Relatively recent genetic and technical advances provide the means to specifically and reproducibly manipulate the function of many fly neurons with temporal resolution. The same cellular precision can also be exploited to express genetically encoded reporters of neural activity and cell-signalling pathways. Combining these approaches in living behaving animals has great potential to generate a holistic view of behavioural control that transcends the usual molecular, cellular and systems boundaries. In this review, we discuss these approaches with particular emphasis on the pioneering studies and those involving learning and memory. PMID:26240426

Microfluidic neurite guidance to study structure-function relationships in topologically-complex population-based neural networks.

PubMed

Honegger, Thibault; Thielen, Moritz I; Feizi, Soheil; Sanjana, Neville E; Voldman, Joel

2016-06-22

The central nervous system is a dense, layered, 3D interconnected network of populations of neurons, and thus recapitulating that complexity for in vitro CNS models requires methods that can create defined topologically-complex neuronal networks. Several three-dimensional patterning approaches have been developed but none have demonstrated the ability to control the connections between populations of neurons. Here we report a method using AC electrokinetic forces that can guide, accelerate, slow down and push up neurites in un-modified collagen scaffolds. We present a means to create in vitro neural networks of arbitrary complexity by using such forces to create 3D intersections of primary neuronal populations that are plated in a 2D plane. We report for the first time in vitro basic brain motifs that have been previously observed in vivo and show that their functional network is highly decorrelated to their structure. This platform can provide building blocks to reproduce in vitro the complexity of neural circuits and provide a minimalistic environment to study the structure-function relationship of the brain circuitry.

Therapeutic intraspinal stimulation to generate activity and promote long-term recovery.

PubMed

Mondello, Sarah E; Kasten, Michael R; Horner, Philip J; Moritz, Chet T

2014-01-01

Neuroprosthetic approaches have tremendous potential for the treatment of injuries to the brain and spinal cord by inducing appropriate neural activity in otherwise disordered circuits. Substantial work has demonstrated that stimulation applied to both the central and peripheral nervous system leads to immediate and in some cases sustained benefits after injury. Here we focus on cervical intraspinal microstimulation (ISMS) as a promising method of activating the spinal cord distal to an injury site, either to directly produce movements or more intriguingly to improve subsequent volitional control of the paretic extremities. Incomplete injuries to the spinal cord are the most commonly observed in human patients, and these injuries spare neural tissue bypassing the lesion that could be influenced by neural devices to promote recovery of function. In fact, recent results have demonstrated that therapeutic ISMS leads to modest but sustained improvements in forelimb function after an incomplete spinal cord injury (SCI). This therapeutic spinal stimulation may promote long-term recovery of function by providing the necessary electrical activity needed for neuron survival, axon growth, and synaptic stability.

Novel Roles for Immune Molecules in Neural Development: Implications for Neurodevelopmental Disorders

PubMed Central

Garay, Paula A.; McAllister, A. Kimberley

2010-01-01

Although the brain has classically been considered “immune-privileged”, current research suggests an extensive communication between the immune and nervous systems in both health and disease. Recent studies demonstrate that immune molecules are present at the right place and time to modulate the development and function of the healthy and diseased central nervous system (CNS). Indeed, immune molecules play integral roles in the CNS throughout neural development, including affecting neurogenesis, neuronal migration, axon guidance, synapse formation, activity-dependent refinement of circuits, and synaptic plasticity. Moreover, the roles of individual immune molecules in the nervous system may change over development. This review focuses on the effects of immune molecules on neuronal connections in the mammalian central nervous system – specifically the roles for MHCI and its receptors, complement, and cytokines on the function, refinement, and plasticity of geniculate, cortical and hippocampal synapses, and their relationship to neurodevelopmental disorders. These functions for immune molecules during neural development suggest that they could also mediate pathological responses to chronic elevations of cytokines in neurodevelopmental disorders, including autism spectrum disorders (ASD) and schizophrenia. PMID:21423522

Microfluidic neurite guidance to study structure-function relationships in topologically-complex population-based neural networks

NASA Astrophysics Data System (ADS)

Honegger, Thibault; Thielen, Moritz I.; Feizi, Soheil; Sanjana, Neville E.; Voldman, Joel

2016-06-01

The central nervous system is a dense, layered, 3D interconnected network of populations of neurons, and thus recapitulating that complexity for in vitro CNS models requires methods that can create defined topologically-complex neuronal networks. Several three-dimensional patterning approaches have been developed but none have demonstrated the ability to control the connections between populations of neurons. Here we report a method using AC electrokinetic forces that can guide, accelerate, slow down and push up neurites in un-modified collagen scaffolds. We present a means to create in vitro neural networks of arbitrary complexity by using such forces to create 3D intersections of primary neuronal populations that are plated in a 2D plane. We report for the first time in vitro basic brain motifs that have been previously observed in vivo and show that their functional network is highly decorrelated to their structure. This platform can provide building blocks to reproduce in vitro the complexity of neural circuits and provide a minimalistic environment to study the structure-function relationship of the brain circuitry.

Risky Decision Making in Neurofibromatosis Type 1: An Exploratory Study.

PubMed

Jonas, Rachel K; Roh, EunJi; Montojo, Caroline A; Pacheco, Laura A; Rosser, Tena; Silva, Alcino J; Bearden, Carrie E

2017-03-01

Neurofibromatosis type 1 (NF1) is a monogenic disorder affecting cognitive function. About one third of children with NF1 have attentional disorders, and the cognitive phenotype is characterized by impairment in prefrontally-mediated functions. Mouse models of NF1 show irregularities in GABA release and striatal dopamine metabolism. We hypothesized that youth with NF1 would show abnormal behavior and neural activity on a task of risk-taking reliant on prefrontal-striatal circuits. Youth with NF1 (N=29) and demographically comparable healthy controls (N=22), ages 8-19, were administered a developmentally sensitive gambling task, in which they chose between low-risk gambles with a high probability of obtaining a small reward, and high-risk gambles with a low probability of obtaining a large reward. We used functional magnetic resonance imaging (fMRI) to investigate neural activity associated with risky decision making, as well as age-associated changes in these behavioral and neural processes. Behaviorally, youth with NF1 tended to make fewer risky decisions than controls. Neuroimaging analyses revealed significantly reduced neural activity across multiple brain regions involved in higher-order semantic processing and motivation (i.e., anterior cingulate, paracingulate, supramarginal, and angular gyri) in patients with NF1 relative to controls during the task. We also observed atypical age-associated changes in neural activity in patients with NF1, such that during risk taking, neural activity tended to decrease with age in controls, whereas it tended to increase with age in patients with NF1. Findings suggest that developmental trajectories of neural activity during risky decision-making may be disrupted in youth with NF1.

The Neuro-endocrinological Role of Microbial Glutamate and GABA Signaling

PubMed Central

Mazzoli, Roberto; Pessione, Enrica

2016-01-01

Gut microbiota provides the host with multiple functions (e.g., by contributing to food digestion, vitamin supplementation, and defense against pathogenic strains) and interacts with the host organism through both direct contact (e.g., through surface antigens) and soluble molecules, which are produced by the microbial metabolism. The existence of the so-called gut–brain axis of bi-directional communication between the gastrointestinal tract and the central nervous system (CNS) also supports a communication pathway between the gut microbiota and neural circuits of the host, including the CNS. An increasing body of evidence has shown that gut microbiota is able to modulate gut and brain functions, including the mood, cognitive functions, and behavior of humans. Nonetheless, given the extreme complexity of this communication network, its comprehension is still at its early stage. The present contribution will attempt to provide a state-of-the art description of the mechanisms by which gut microbiota can affect the gut–brain axis and the multiple cellular and molecular communication circuits (i.e., neural, immune, and humoral). In this context, special attention will be paid to the microbial strains that produce bioactive compounds and display ascertained or potential probiotic activity. Several neuroactive molecules (e.g., catecholamines, histamine, serotonin, and trace amines) will be considered, with special focus on Glu and GABA circuits, receptors, and signaling. From the basic science viewpoint, “microbial endocrinology” deals with those theories in which neurochemicals, produced by both multicellular organisms and prokaryotes (e.g., serotonin, GABA, glutamate), are considered as a common shared language that enables interkingdom communication. With regards to its application, research in this area opens the way toward the possibility of the future use of neuroactive molecule-producing probiotics as therapeutic agents for the treatment of neurogastroenteric and/or psychiatric disorders. PMID:27965654

The Neuro-endocrinological Role of Microbial Glutamate and GABA Signaling.

PubMed

Mazzoli, Roberto; Pessione, Enrica

2016-01-01

Gut microbiota provides the host with multiple functions (e.g., by contributing to food digestion, vitamin supplementation, and defense against pathogenic strains) and interacts with the host organism through both direct contact (e.g., through surface antigens) and soluble molecules, which are produced by the microbial metabolism. The existence of the so-called gut-brain axis of bi-directional communication between the gastrointestinal tract and the central nervous system (CNS) also supports a communication pathway between the gut microbiota and neural circuits of the host, including the CNS. An increasing body of evidence has shown that gut microbiota is able to modulate gut and brain functions, including the mood, cognitive functions, and behavior of humans. Nonetheless, given the extreme complexity of this communication network, its comprehension is still at its early stage. The present contribution will attempt to provide a state-of-the art description of the mechanisms by which gut microbiota can affect the gut-brain axis and the multiple cellular and molecular communication circuits (i.e., neural, immune, and humoral). In this context, special attention will be paid to the microbial strains that produce bioactive compounds and display ascertained or potential probiotic activity. Several neuroactive molecules (e.g., catecholamines, histamine, serotonin, and trace amines) will be considered, with special focus on Glu and GABA circuits, receptors, and signaling. From the basic science viewpoint, "microbial endocrinology" deals with those theories in which neurochemicals, produced by both multicellular organisms and prokaryotes (e.g., serotonin, GABA, glutamate), are considered as a common shared language that enables interkingdom communication. With regards to its application, research in this area opens the way toward the possibility of the future use of neuroactive molecule-producing probiotics as therapeutic agents for the treatment of neurogastroenteric and/or psychiatric disorders.

Hippocampal Plasticity During the Progression of Alzheimer’s disease

PubMed Central

Mufson, Elliott J.; Mahady, Laura; Waters, Diana; Counts, Scott E.; Perez, Sylvia E.; DeKosky, Steven; Ginsberg, Stephen D.; Ikonomovic, Milos D.; Scheff, Stephen; Binder, Lester

2015-01-01

Neuroplasticity involves molecular changes in central nervous system (CNS) synaptic structure and function throughout life. The concept of neural organization allows for synaptic remodeling as a compensatory mechanism to the early pathobiology of Alzheimer’s disease (AD) in an attempt to maintain brain function and cognition during the onset of dementia. The hippocampus, a crucial component of the medial temporal lobe memory circuit, is affected early in AD and displays synaptic and intraneuronal molecular remodeling against a pathological background of extracellular amyloid-beta (Aβ) deposition and intracellular neurofibrillary tangle (NFT) formation in the early stages of AD. Here we discuss human clinical pathological findings supporting the concept that the hippocampus is capable of neural plasticity during mild cognitive impairment (MCI), a prodromal stage of AD and early stage AD. PMID:25772787

Temporal pattern processing in songbirds.

PubMed

Comins, Jordan A; Gentner, Timothy Q

2014-10-01

Understanding how the brain perceives, organizes and uses patterned information is directly related to the neurobiology of language. Given the present limitations, such knowledge at the scale of neurons, neural circuits and neural populations can only come from non-human models, focusing on shared capacities that are relevant to language processing. Here we review recent advances in the behavioral and neural basis of temporal pattern processing of natural auditory communication signals in songbirds, focusing on European starlings. We suggest a general inhibitory circuit for contextual modulation that can act to control sensory representations based on patterning rules. Copyright © 2014. Published by Elsevier Ltd.