1
|
Johnsen KA, Cruzado NA, Menard ZC, Willats AA, Charles AS, Markowitz JE, Rozell CJ. Bridging model and experiment in systems neuroscience with Cleo: the Closed-Loop, Electrophysiology, and Optophysiology simulation testbed. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.01.27.525963. [PMID: 39026717 PMCID: PMC11257437 DOI: 10.1101/2023.01.27.525963] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/20/2024]
Abstract
Systems neuroscience has experienced an explosion of new tools for reading and writing neural activity, enabling exciting new experiments such as all-optical or closed-loop control that effect powerful causal interventions. At the same time, improved computational models are capable of reproducing behavior and neural activity with increasing fidelity. Unfortunately, these advances have drastically increased the complexity of integrating different lines of research, resulting in the missed opportunities and untapped potential of suboptimal experiments. Experiment simulation can help bridge this gap, allowing model and experiment to better inform each other by providing a low-cost testbed for experiment design, model validation, and methods engineering. Specifically, this can be achieved by incorporating the simulation of the experimental interface into our models, but no existing tool integrates optogenetics, two-photon calcium imaging, electrode recording, and flexible closed-loop processing with neural population simulations. To address this need, we have developed Cleo: the Closed-Loop, Electrophysiology, and Optophysiology experiment simulation testbed. Cleo is a Python package enabling injection of recording and stimulation devices as well as closed-loop control with realistic latency into a Brian spiking neural network model. It is the only publicly available tool currently supporting two-photon and multi-opsin/wavelength optogenetics. To facilitate adoption and extension by the community, Cleo is open-source, modular, tested, and documented, and can export results to various data formats. Here we describe the design and features of Cleo, validate output of individual components and integrated experiments, and demonstrate its utility for advancing optogenetic techniques in prospective experiments using previously published systems neuroscience models.
Collapse
Affiliation(s)
- Kyle A. Johnsen
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
| | | | - Zachary C. Menard
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
| | - Adam A. Willats
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
| | - Adam S. Charles
- Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD, USA
| | - Jeffrey E. Markowitz
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA
| | | |
Collapse
|
2
|
Hudetz AG. Microstimulation reveals anesthetic state-dependent effective connectivity of neurons in cerebral cortex. Front Neurosci 2024; 18:1387098. [PMID: 39035779 PMCID: PMC11258030 DOI: 10.3389/fnins.2024.1387098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Accepted: 06/07/2024] [Indexed: 07/23/2024] Open
Abstract
Introduction Complex neuronal interactions underlie cortical information processing that can be compromised in altered states of consciousness. Here intracortical microstimulation was applied to investigate anesthetic state-dependent effective connectivity of neurons in rat visual cortex in vivo. Methods Extracellular activity was recorded at 32 sites in layers 5/6 while stimulating with charge-balanced discrete pulses at each electrode in random order. The same stimulation pattern was applied at three levels of anesthesia with desflurane and in wakefulness. Spikes were sorted and classified by their waveform features as putative excitatory and inhibitory neurons. Network motifs were identified in graphs of effective connectivity constructed from monosynaptic cross-correlograms. Results Microstimulation caused early (<10 ms) increase followed by prolonged (11-100 ms) decrease in spiking of all neurons throughout the electrode array. The early response of excitatory but not inhibitory neurons decayed rapidly with distance from the stimulation site over 1 mm. Effective connectivity of neurons with significant stimulus response was dense in wakefulness and sparse under anesthesia. The number of network motifs, especially those of higher order, increased rapidly as the anesthesia was withdrawn indicating a substantial increase in network connectivity as the animals woke up. Conclusion The results illuminate the impact of anesthesia on functional integrity of local cortical circuits affecting the state of consciousness.
Collapse
Affiliation(s)
- Anthony G Hudetz
- Department of Anesthesiology, Center for Consciousness Science, University of Michigan, Ann Arbor, MI, United States
| |
Collapse
|
3
|
Hudetz AG. Microstimulation reveals anesthetic state-dependent effective connectivity of neurons in cerebral cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.29.591664. [PMID: 38746366 PMCID: PMC11092428 DOI: 10.1101/2024.04.29.591664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Complex neuronal interactions underlie cortical information processing that can be compromised in altered states of consciousness. Here intracortical microstimulation was applied to investigate the state-dependent effective connectivity of neurons in rat visual cortex in vivo. Extracellular activity was recorded at 32 sites in layers 5/6 while stimulating with charge-balanced discrete pulses at each electrode in random order. The same stimulation pattern was applied at three levels of anesthesia with desflurane and in wakefulness. Spikes were sorted and classified by their waveform features as putative excitatory and inhibitory neurons. Microstimulation caused early (<10ms) increase followed by prolonged (11-100ms) decrease in spiking of all neurons throughout the electrode array. The early response of excitatory but not inhibitory neurons decayed rapidly with distance from the stimulation site over 1mm. Effective connectivity of neurons with significant stimulus response was dense in wakefulness and sparse under anesthesia. Network motifs were identified in graphs of effective connectivity constructed from monosynaptic cross-correlograms. The number of motifs, especially those of higher order, increased rapidly as the anesthesia was withdrawn indicating a substantial increase in network connectivity as the animals woke up. The results illuminate the impact of anesthesia on functional integrity of local circuits affecting the state of consciousness.
Collapse
|
4
|
Zeng K, Jiao ZH, Jiang Q, He R, Zhang Y, Li WG, Xu TL, Chen Y. Genetically Encoded Photocatalysis Enables Spatially Restricted Optochemical Modulation of Neurons in Live Mice. ACS CENTRAL SCIENCE 2024; 10:163-175. [PMID: 38292609 PMCID: PMC10823520 DOI: 10.1021/acscentsci.3c01351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Revised: 12/01/2023] [Accepted: 12/04/2023] [Indexed: 02/01/2024]
Abstract
Light provides high temporal precision for neuronal modulations. Small molecules are advantageous for neuronal modulation due to their structural diversity, allowing them to suit versatile targets. However, current optochemical methods release uncaged small molecules with uniform concentrations in the irradiation area, which lack spatial specificity as counterpart optogenetic methods from genetic encoding for photosensitive proteins. Photocatalysis provides spatial specificity by generating reactive species in the proximity of photocatalysts. However, current photocatalytic methods use antibody-tagged heavy-metal photocatalysts for spatial specificity, which are unsuitable for neuronal applications. Here, we report a genetically encoded metal-free photocatalysis method for the optochemical modulation of neurons via deboronative hydroxylation. The genetically encoded photocatalysts generate doxorubicin, a mitochondrial uncoupler, and baclofen by uncaging stable organoboronate precursors. The mitochondria, nucleus, membrane, cytosol, and ER-targeted drug delivery are achieved by this method. The distinct signaling pathway dissection in a single projection is enabled by the dual optogenetic and optochemical control of synaptic transmission. The itching signaling pathway is investigated by photocatalytic uncaging under live-mice skin for the first time by visible light irradiation. The cell-type-specific release of baclofen reveals the GABABR activation on NaV1.8-expressing nociceptor terminals instead of pan peripheral sensory neurons for itch alleviation in live mice.
Collapse
Affiliation(s)
- Kaixing Zeng
- State
Key Laboratory of Chemical Biology, Shanghai Institute of Organic
Chemistry, University of Chinese Academy
of Sciences, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032 China
- School
of Physical Science and Technology, ShanghaiTech
University, 100 Haike Road, Shanghai 201210, China
| | - Zhi-Han Jiao
- Centre
for Brain Science and Department of Anatomy and Physiology, Shanghai Jiao Tong University School of Medicine, 280 South Chongqing Road, Shanghai 200025, China
| | - Qin Jiang
- Centre
for Brain Science and Department of Anatomy and Physiology, Shanghai Jiao Tong University School of Medicine, 280 South Chongqing Road, Shanghai 200025, China
| | - Ru He
- State
Key Laboratory of Chemical Biology, Shanghai Institute of Organic
Chemistry, University of Chinese Academy
of Sciences, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032 China
- School
of Physical Science and Technology, ShanghaiTech
University, 100 Haike Road, Shanghai 201210, China
| | - Yixin Zhang
- State
Key Laboratory of Chemical Biology, Shanghai Institute of Organic
Chemistry, University of Chinese Academy
of Sciences, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032 China
| | - Wei-Guang Li
- Centre
for Brain Science and Department of Anatomy and Physiology, Shanghai Jiao Tong University School of Medicine, 280 South Chongqing Road, Shanghai 200025, China
- Department
of Rehabilitation Medicine, Huashan Hospital, Institute for Translational
Brain Research, State Key Laboratory of Medical Neurobiology and Ministry
of Education Frontiers Centre for Brain Science, Fudan University, 131 Dongan Road, Shanghai 200032, China
| | - Tian-Le Xu
- Centre
for Brain Science and Department of Anatomy and Physiology, Shanghai Jiao Tong University School of Medicine, 280 South Chongqing Road, Shanghai 200025, China
| | - Yiyun Chen
- State
Key Laboratory of Chemical Biology, Shanghai Institute of Organic
Chemistry, University of Chinese Academy
of Sciences, Chinese Academy of Sciences, 345 Lingling Road, Shanghai 200032 China
- School
of Physical Science and Technology, ShanghaiTech
University, 100 Haike Road, Shanghai 201210, China
- School
of Chemistry and Material Sciences, Hangzhou Institute for Advanced
Study, University of Chinese Academy of
Sciences, Sub-lane Xiangshan, Hangzhou 310024, China
| |
Collapse
|
5
|
Grosu GF, Hopp AV, Moca VV, Bârzan H, Ciuparu A, Ercsey-Ravasz M, Winkel M, Linde H, Mureșan RC. The fractal brain: scale-invariance in structure and dynamics. Cereb Cortex 2023; 33:4574-4605. [PMID: 36156074 PMCID: PMC10110456 DOI: 10.1093/cercor/bhac363] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 08/09/2022] [Accepted: 08/10/2022] [Indexed: 11/12/2022] Open
Abstract
The past 40 years have witnessed extensive research on fractal structure and scale-free dynamics in the brain. Although considerable progress has been made, a comprehensive picture has yet to emerge, and needs further linking to a mechanistic account of brain function. Here, we review these concepts, connecting observations across different levels of organization, from both a structural and functional perspective. We argue that, paradoxically, the level of cortical circuits is the least understood from a structural point of view and perhaps the best studied from a dynamical one. We further link observations about scale-freeness and fractality with evidence that the environment provides constraints that may explain the usefulness of fractal structure and scale-free dynamics in the brain. Moreover, we discuss evidence that behavior exhibits scale-free properties, likely emerging from similarly organized brain dynamics, enabling an organism to thrive in an environment that shares the same organizational principles. Finally, we review the sparse evidence for and try to speculate on the functional consequences of fractality and scale-freeness for brain computation. These properties may endow the brain with computational capabilities that transcend current models of neural computation and could hold the key to unraveling how the brain constructs percepts and generates behavior.
Collapse
Affiliation(s)
- George F Grosu
- Department of Experimental and Theoretical Neuroscience, Transylvanian Institute of Neuroscience, Str. Ploiesti 33, 400157 Cluj-Napoca, Romania
- Faculty of Electronics, Telecommunications and Information Technology, Technical University of Cluj-Napoca, Str. Memorandumului 28, 400114 Cluj-Napoca, Romania
| | | | - Vasile V Moca
- Department of Experimental and Theoretical Neuroscience, Transylvanian Institute of Neuroscience, Str. Ploiesti 33, 400157 Cluj-Napoca, Romania
| | - Harald Bârzan
- Department of Experimental and Theoretical Neuroscience, Transylvanian Institute of Neuroscience, Str. Ploiesti 33, 400157 Cluj-Napoca, Romania
- Faculty of Electronics, Telecommunications and Information Technology, Technical University of Cluj-Napoca, Str. Memorandumului 28, 400114 Cluj-Napoca, Romania
| | - Andrei Ciuparu
- Department of Experimental and Theoretical Neuroscience, Transylvanian Institute of Neuroscience, Str. Ploiesti 33, 400157 Cluj-Napoca, Romania
- Faculty of Electronics, Telecommunications and Information Technology, Technical University of Cluj-Napoca, Str. Memorandumului 28, 400114 Cluj-Napoca, Romania
| | - Maria Ercsey-Ravasz
- Department of Experimental and Theoretical Neuroscience, Transylvanian Institute of Neuroscience, Str. Ploiesti 33, 400157 Cluj-Napoca, Romania
- Faculty of Physics, Babes-Bolyai University, Str. Mihail Kogalniceanu 1, 400084 Cluj-Napoca, Romania
| | - Mathias Winkel
- Merck KGaA, Frankfurter Straße 250, 64293 Darmstadt, Germany
| | - Helmut Linde
- Department of Experimental and Theoretical Neuroscience, Transylvanian Institute of Neuroscience, Str. Ploiesti 33, 400157 Cluj-Napoca, Romania
- Merck KGaA, Frankfurter Straße 250, 64293 Darmstadt, Germany
| | - Raul C Mureșan
- Department of Experimental and Theoretical Neuroscience, Transylvanian Institute of Neuroscience, Str. Ploiesti 33, 400157 Cluj-Napoca, Romania
| |
Collapse
|
6
|
Nikolić D. Where is the mind within the brain? Transient selection of subnetworks by metabotropic receptors and G protein-gated ion channels. Comput Biol Chem 2023; 103:107820. [PMID: 36724606 DOI: 10.1016/j.compbiolchem.2023.107820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 01/16/2023] [Accepted: 01/17/2023] [Indexed: 01/20/2023]
Abstract
Perhaps the most important question posed by brain research is: How the brain gives rise to the mind. To answer this question, we have primarily relied on the connectionist paradigm: The brain's entire knowledge and thinking skills are thought to be stored in the connections; and the mental operations are executed by network computations. I propose here an alternative paradigm: Our knowledge and skills are stored in metabotropic receptors (MRs) and the G protein-gated ion channels (GPGICs). Here, mental operations are assumed to be executed by the functions of MRs and GPGICs. As GPGICs have the capacity to close or open branches of dendritic trees and axon terminals, their states transiently re-route neural activity throughout the nervous system. First, MRs detect ligands that signal the need to activate GPGICs. Next, GPGICs transiently select a subnetwork within the brain. The process of selecting this new subnetwork is what constitutes a mental operation - be it in a form of directed attention, perception or making a decision. Synaptic connections and network computations play only a secondary role, supporting MRs and GPGICs. According to this new paradigm, the mind emerges within the brain as the function of MRs and GPGICs whose primary function is to continually select the pathways over which neural activity will be allowed to pass. It is argued that MRs and GPGICs solve the scaling problem of intelligence from which the connectionism paradigm suffers.
Collapse
Affiliation(s)
- Danko Nikolić
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Germany; evocenta GmbH, Germany; Robots Go Mental UG, Germany.
| |
Collapse
|
7
|
Thivierge JP, Giraud E, Lynn M, Théberge Charbonneau A. Key role of neuronal diversity in structured reservoir computing. CHAOS (WOODBURY, N.Y.) 2022; 32:113130. [PMID: 36456321 DOI: 10.1063/5.0111131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 10/24/2022] [Indexed: 06/17/2023]
Abstract
Chaotic time series have been captured by reservoir computing models composed of a recurrent neural network whose output weights are trained in a supervised manner. These models, however, are typically limited to randomly connected networks of homogeneous units. Here, we propose a new class of structured reservoir models that incorporates a diversity of cell types and their known connections. In a first version of the model, the reservoir was composed of mean-rate units separated into pyramidal, parvalbumin, and somatostatin cells. Stability analysis of this model revealed two distinct dynamical regimes, namely, (i) an inhibition-stabilized network (ISN) where strong recurrent excitation is balanced by strong inhibition and (ii) a non-ISN network with weak excitation. These results were extended to a leaky integrate-and-fire model that captured different cell types along with their network architecture. ISN and non-ISN reservoir networks were trained to relay and generate a chaotic Lorenz attractor. Despite their increased performance, ISN networks operate in a regime of activity near the limits of stability where external perturbations yield a rapid divergence in output. The proposed framework of structured reservoir computing opens avenues for exploring how neural microcircuits can balance performance and stability when representing time series through distinct dynamical regimes.
Collapse
Affiliation(s)
- Jean-Philippe Thivierge
- University of Ottawa Brain and Mind Research Institute, 451 Smyth Rd., Ottawa, Ontario K1H 8M5, Canada
| | - Eloïse Giraud
- School of Psychology, University of Ottawa, 156 Jean-Jacques Lussier, Ottawa, Ontario K1N 6N5, Canada
| | - Michael Lynn
- University of Ottawa Brain and Mind Research Institute, 451 Smyth Rd., Ottawa, Ontario K1H 8M5, Canada
| | | |
Collapse
|
8
|
Foroutannia A, Nazarimehr F, Ghasemi M, Jafari S. Chaos in memory function of sleep: A nonlinear dynamical analysis in thalamocortical study. J Theor Biol 2021; 528:110837. [PMID: 34273361 DOI: 10.1016/j.jtbi.2021.110837] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 07/07/2021] [Accepted: 07/11/2021] [Indexed: 11/30/2022]
Abstract
Studying the dynamical behaviors of neuronal models may help in better understanding of real nervous system. In addition, it can help researchers to understand some specific phenomena in neuronal system. The thalamocortical network is made of neurons in the thalamus and cortex. In it, the memory function is consolidated in sleep by creating up and down state oscillations (1 Hz) and fast (13-17 Hz) - slow (8-12 Hz) spindles. Recently, a nonlinear biological model for up-down oscillations and fast-slow spindles of the thalamocortical network has been proposed. In this research, the power spectral for the fast-slow spindle of the model is extracted. Dynamical properties of the model, such as the bifurcation diagrams, and attractors are investigated. The results show that the variation of the synaptic power between the excitatory neurons of the cortex and the reticular neurons in the thalamus changes the spindles' activity. According to previous experimental findings, it is an essential rule for consolidating the memory function during sleep. It is also pointed out that when the fast-slow spindles of the brain increase, the dynamics of the thalamocortical system tend to chaos.
Collapse
Affiliation(s)
- Ali Foroutannia
- Neural Engineering Laboratory, Department of Biomedical Engineering, University of Neyshabur, Neyshabur, Iran
| | - Fahimeh Nazarimehr
- Department of Biomedical Engineering, Amirkabir University of Technology, No. 350, Hafez Ave, Valiasr Square, Tehran 159163-4311, Iran
| | - Mahdieh Ghasemi
- Neural Engineering Laboratory, Department of Biomedical Engineering, University of Neyshabur, Neyshabur, Iran.
| | - Sajad Jafari
- Department of Biomedical Engineering, Amirkabir University of Technology, No. 350, Hafez Ave, Valiasr Square, Tehran 159163-4311, Iran; Health Technology Research Institute, Amirkabir University of Technology, No. 350, Hafez Ave, Valiasr Square, Tehran 159163-4311, Iran
| |
Collapse
|
9
|
O’Sullivan C, Weible AP, Wehr M. Disruption of Early or Late Epochs of Auditory Cortical Activity Impairs Speech Discrimination in Mice. Front Neurosci 2020; 13:1394. [PMID: 31998064 PMCID: PMC6965026 DOI: 10.3389/fnins.2019.01394] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Accepted: 12/10/2019] [Indexed: 11/22/2022] Open
Abstract
Speech evokes robust activity in auditory cortex, which contains information over a wide range of spatial and temporal scales. It remains unclear which components of these neural representations are causally involved in the perception and processing of speech sounds. Here we compared the relative importance of early and late speech-evoked activity for consonant discrimination. We trained mice to discriminate the initial consonants in spoken words, and then tested the effect of optogenetically suppressing different temporal windows of speech-evoked activity in auditory cortex. We found that both early and late suppression disrupted performance equivalently. These results suggest that mice are impaired at recognizing either type of disrupted representation because it differs from those learned in training.
Collapse
Affiliation(s)
- Conor O’Sullivan
- Institute of Neuroscience, University of Oregon, Eugene, OR, United States
- Department of Biology, University of Oregon, Eugene, OR, United States
| | - Aldis P. Weible
- Institute of Neuroscience, University of Oregon, Eugene, OR, United States
| | - Michael Wehr
- Institute of Neuroscience, University of Oregon, Eugene, OR, United States
- Department of Psychology, University of Oregon, Eugene, OR, United States
- *Correspondence: Michael Wehr,
| |
Collapse
|
10
|
Auditory Cortex Contributes to Discrimination of Pure Tones. eNeuro 2019; 6:ENEURO.0340-19.2019. [PMID: 31591138 PMCID: PMC6795560 DOI: 10.1523/eneuro.0340-19.2019] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Revised: 09/09/2019] [Accepted: 09/11/2019] [Indexed: 11/30/2022] Open
Abstract
The auditory cortex is topographically organized for sound frequency and contains highly selective frequency-tuned neurons, yet the role of auditory cortex in the perception of sound frequency remains unclear. Lesion studies have shown that auditory cortex is not essential for frequency discrimination of pure tones. However, transient pharmacological inactivation has been reported to impair frequency discrimination. This suggests the possibility that successful tone discrimination after recovery from lesion surgery could arise from long-term reorganization or plasticity of compensatory pathways. Here, we compared the effects of lesions and optogenetic suppression of auditory cortex on frequency discrimination in mice. We found that transient bilateral optogenetic suppression partially but significantly impaired discrimination performance. In contrast, bilateral electrolytic lesions of auditory cortex had no effect on performance of the identical task, even when tested only 4 h after lesion. This suggests that when auditory cortex is destroyed, an alternative pathway is almost immediately adequate for mediating frequency discrimination. Yet this alternative pathway is insufficient for task performance when auditory cortex is intact but has its activity suppressed. These results indicate a fundamental difference between the effects of brain lesions and optogenetic suppression, and suggest the existence of a rapid compensatory process possibly induced by injury.
Collapse
|
11
|
Adesnik H, Naka A. Cracking the Function of Layers in the Sensory Cortex. Neuron 2019; 100:1028-1043. [PMID: 30521778 DOI: 10.1016/j.neuron.2018.10.032] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2018] [Revised: 08/08/2018] [Accepted: 10/18/2018] [Indexed: 12/24/2022]
Abstract
Understanding how cortical activity generates sensory perceptions requires a detailed dissection of the function of cortical layers. Despite our relatively extensive knowledge of their anatomy and wiring, we have a limited grasp of what each layer contributes to cortical computation. We need to develop a theory of cortical function that is rooted solidly in each layer's component cell types and fine circuit architecture and produces predictions that can be validated by specific perturbations. Here we briefly review the progress toward such a theory and suggest an experimental road map toward this goal. We discuss new methods for the all-optical interrogation of cortical layers, for correlating in vivo function with precise identification of transcriptional cell type, and for mapping local and long-range activity in vivo with synaptic resolution. The new technologies that can crack the function of cortical layers are finally on the immediate horizon.
Collapse
Affiliation(s)
- Hillel Adesnik
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA; The Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA.
| | - Alexander Naka
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA; The Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| |
Collapse
|
12
|
Moore AK, Weible AP, Balmer TS, Trussell LO, Wehr M. Rapid Rebalancing of Excitation and Inhibition by Cortical Circuitry. Neuron 2018; 97:1341-1355.e6. [PMID: 29503186 PMCID: PMC5875716 DOI: 10.1016/j.neuron.2018.01.045] [Citation(s) in RCA: 73] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2016] [Revised: 07/29/2017] [Accepted: 01/24/2018] [Indexed: 12/23/2022]
Abstract
Excitation is balanced by inhibition to cortical neurons across a wide range of conditions. To understand how this relationship is maintained, we broadly suppressed the activity of parvalbumin-expressing (PV+) inhibitory neurons and asked how this affected the balance of excitation and inhibition throughout auditory cortex. Activating archaerhodopsin in PV+ neurons effectively suppressed them in layer 4. However, the resulting increase in excitation outweighed Arch suppression and produced a net increase in PV+ activity in downstream layers. Consequently, suppressing PV+ neurons did not reduce inhibition to principal neurons (PNs) but instead resulted in a tightly coordinated increase in both excitation and inhibition. The increase in inhibition constrained the magnitude of PN spiking responses to the increase in excitation and produced nonlinear changes in spike tuning. Excitatory-inhibitory rebalancing is mediated by strong PN-PV+ connectivity within and between layers and is likely engaged during normal cortical operation to ensure balance in downstream neurons.
Collapse
Affiliation(s)
- Alexandra K Moore
- Institute of Neuroscience, University of Oregon, Eugene, OR 97403, USA
| | - Aldis P Weible
- Institute of Neuroscience, University of Oregon, Eugene, OR 97403, USA
| | - Timothy S Balmer
- Vollum Institute, Oregon Health and Sciences University, Portland, OR 97239, USA
| | - Laurence O Trussell
- Vollum Institute, Oregon Health and Sciences University, Portland, OR 97239, USA
| | - Michael Wehr
- Institute of Neuroscience, University of Oregon, Eugene, OR 97403, USA.
| |
Collapse
|
13
|
Zippo AG, Della Rosa PA, Castiglioni I, Biella GEM. Alternating Dynamics of Segregation and Integration in Human EEG Functional Networks During Working-memory Task. Neuroscience 2017; 371:191-206. [PMID: 29246785 DOI: 10.1016/j.neuroscience.2017.12.004] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2017] [Revised: 12/02/2017] [Accepted: 12/04/2017] [Indexed: 01/28/2023]
Abstract
Brain functional networks show high variability in short time windows but mechanisms governing these transient dynamics remain unknown. In this work, we studied the temporal evolution of functional brain networks involved in a working memory (WM) task while recording high-density electroencephalography (EEG) in human normal subjects. We found that functional brain networks showed an initial phase characterized by an increase of the functional segregation index followed by a second phase where the functional segregation faded after the prevailing the functional integration. Notably, wrong trials were associated with different or disrupted sequences of the segregation-integration profiles and measures of network centrality and modularity were able to identify crucial aspects of the oscillatory network dynamics. Additionally, computational investigations further supported the experimental results. The brain functional organization may respond to the information processing demand of a WM task following a 2-step atomic scheme wherein segregation and integration alternately dominate the functional configurations.
Collapse
Affiliation(s)
- Antonio G Zippo
- Institute of Molecular Bioimaging and Physiology, Consiglio Nazionale delle Ricerche, Segrate, Milan, Italy.
| | | | - Isabella Castiglioni
- Institute of Molecular Bioimaging and Physiology, Consiglio Nazionale delle Ricerche, Segrate, Milan, Italy
| | - Gabriele E M Biella
- Institute of Molecular Bioimaging and Physiology, Consiglio Nazionale delle Ricerche, Segrate, Milan, Italy
| |
Collapse
|
14
|
Zhang X, Han J, Zhang W. An efficient algorithm for finding all possible input nodes for controlling complex networks. Sci Rep 2017; 7:10677. [PMID: 28878394 PMCID: PMC5587595 DOI: 10.1038/s41598-017-10744-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2017] [Accepted: 08/14/2017] [Indexed: 11/12/2022] Open
Abstract
Understanding structural controllability of a complex network requires to identify a Minimum Input nodes Set (MIS) of the network. Finding an MIS is known to be equivalent to computing a maximum matching of the network, where the unmatched nodes constitute an MIS. However, maximum matching is often not unique for a network, and finding all possible input nodes, the union of all MISs, may provide deep insights to the controllability of the network. Here we present an efficient enumerative algorithm for the problem. The main idea is to modify a maximum matching algorithm to make it efficient for finding all possible input nodes by computing only one MIS. The algorithm can also output a set of substituting nodes for each input node in the MIS, so that any node in the set can replace the latter. We rigorously proved the correctness of the new algorithm and evaluated its performance on synthetic and large real networks. The experimental results showed that the new algorithm ran several orders of magnitude faster than an existing method on large real networks.
Collapse
Affiliation(s)
- Xizhe Zhang
- Key Laboratory of Medical Image Computing of Northeastern University, Ministry of Education, Shenyang, China. .,School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China.
| | - Jianfei Han
- School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, China
| | - Weixiong Zhang
- College of Math and Computer Science, Institute for Systems Biology, Jianghan University, Wuhan, 430056, China.,Department of Computer Science and Engineering, Washington University, Saint Louis, Missouri, USA
| |
Collapse
|
15
|
Liu X, Gao J, Wang G, Chen ZW. Controllability Analysis of the Neural Mass Model with Dynamic Parameters. Neural Comput 2016; 29:485-501. [PMID: 28030778 DOI: 10.1162/neco_a_00925] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
The development of control technology for the brain is of potential significance to the prevention and treatment of neuropsychiatric disorders and the improvement of humans' mental health. A controllability analysis of the brain is necessary to ensure the feasibility of the brain control. In this letter, we investigate the influences of dynamical parameters on the controllability in the neural mass model by using controllability indices as quantitative indicators. The indices are obtained by computing Lie brackets and condition numbers of the system model. We show how controllability changes with important parameters of our dynamical (neuronal) model. Our results suggest that the underlying dynamical parameters have certain ranges with better controllability. We hope it can play potential roles in therapy for brain nervous disorder disease.
Collapse
Affiliation(s)
- Xian Liu
- Key Lab of Industrial Computer Control Engineering of Hebei Province, Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, P.R.C.
| | - Jing Gao
- Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, P.R.C.
| | - Guan Wang
- Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, P.R.C.
| | - Zhi-Wang Chen
- Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, P.R.C.
| |
Collapse
|
16
|
Zhang X, Lv T, Pu Y. Input graph: the hidden geometry in controlling complex networks. Sci Rep 2016; 6:38209. [PMID: 27901102 PMCID: PMC5128914 DOI: 10.1038/srep38209] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2016] [Accepted: 11/07/2016] [Indexed: 11/30/2022] Open
Abstract
The ability to control a complex network towards a desired behavior relies on our understanding of the complex nature of these social and technological networks. The existence of numerous control schemes in a network promotes us to wonder: what is the underlying relationship of all possible input nodes? Here we introduce input graph, a simple geometry that reveals the complex relationship between all control schemes and input nodes. We prove that the node adjacent to an input node in the input graph will appear in another control scheme, and the connected nodes in input graph have the same type in control, which they are either all possible input nodes or not. Furthermore, we find that the giant components emerge in the input graphs of many real networks, which provides a clear topological explanation of bifurcation phenomenon emerging in dense networks and promotes us to design an efficient method to alter the node type in control. The findings provide an insight into control principles of complex networks and offer a general mechanism to design a suitable control scheme for different purposes.
Collapse
Affiliation(s)
- Xizhe Zhang
- School of Computer Science and Engineering, Northeastern University, Shenyang 110819, China
| | - Tianyang Lv
- College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China.,IT Center, National Audit Office, Beijing 100830, China
| | - Yuanyuan Pu
- School of Computer Science and Engineering, Northeastern University, Shenyang 110819, China
| |
Collapse
|
17
|
Yavorska I, Wehr M. Somatostatin-Expressing Inhibitory Interneurons in Cortical Circuits. Front Neural Circuits 2016; 10:76. [PMID: 27746722 PMCID: PMC5040712 DOI: 10.3389/fncir.2016.00076] [Citation(s) in RCA: 111] [Impact Index Per Article: 13.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2016] [Accepted: 09/12/2016] [Indexed: 12/30/2022] Open
Abstract
Cortical inhibitory neurons exhibit remarkable diversity in their morphology, connectivity, and synaptic properties. Here, we review the function of somatostatin-expressing (SOM) inhibitory interneurons, focusing largely on sensory cortex. SOM neurons also comprise a number of subpopulations that can be distinguished by their morphology, input and output connectivity, laminar location, firing properties, and expression of molecular markers. Several of these classes of SOM neurons show unique dynamics and characteristics, such as facilitating synapses, specific axonal projections, intralaminar input, and top-down modulation, which suggest possible computational roles. SOM cells can be differentially modulated by behavioral state depending on their class, sensory system, and behavioral paradigm. The functional effects of such modulation have been studied with optogenetic manipulation of SOM cells, which produces effects on learning and memory, task performance, and the integration of cortical activity. Different classes of SOM cells participate in distinct disinhibitory circuits with different inhibitory partners and in different cortical layers. Through these disinhibitory circuits, SOM cells help encode the behavioral relevance of sensory stimuli by regulating the activity of cortical neurons based on subcortical and intracortical modulatory input. Associative learning leads to long-term changes in the strength of connectivity of SOM cells with other neurons, often influencing the strength of inhibitory input they receive. Thus despite their heterogeneity and variability across cortical areas, current evidence shows that SOM neurons perform unique neural computations, forming not only distinct molecular but also functional subclasses of cortical inhibitory interneurons.
Collapse
Affiliation(s)
| | - Michael Wehr
- Institute of Neuroscience and Department of Psychology, University of OregonEugene, OR, USA
| |
Collapse
|
18
|
Dynamical state of the network determines the efficacy of single neuron properties in shaping the network activity. Sci Rep 2016; 6:26029. [PMID: 27212008 PMCID: PMC4876512 DOI: 10.1038/srep26029] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2015] [Accepted: 04/08/2016] [Indexed: 11/26/2022] Open
Abstract
Spike patterns are among the most common electrophysiological descriptors of neuron types. Surprisingly, it is not clear how the diversity in firing patterns of the neurons in a network affects its activity dynamics. Here, we introduce the state-dependent stochastic bursting neuron model allowing for a change in its firing patterns independent of changes in its input-output firing rate relationship. Using this model, we show that the effect of single neuron spiking on the network dynamics is contingent on the network activity state. While spike bursting can both generate and disrupt oscillations, these patterns are ineffective in large regions of the network state space in changing the network activity qualitatively. Finally, we show that when single-neuron properties are made dependent on the population activity, a hysteresis like dynamics emerges. This novel phenomenon has important implications for determining the network response to time-varying inputs and for the network sensitivity at different operating points.
Collapse
|
19
|
Naka A, Adesnik H. Inhibitory Circuits in Cortical Layer 5. Front Neural Circuits 2016; 10:35. [PMID: 27199675 PMCID: PMC4859073 DOI: 10.3389/fncir.2016.00035] [Citation(s) in RCA: 71] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2016] [Accepted: 04/18/2016] [Indexed: 01/19/2023] Open
Abstract
Inhibitory neurons play a fundamental role in cortical computation and behavior. Recent technological advances, such as two photon imaging, targeted in vivo recording, and molecular profiling, have improved our understanding of the function and diversity of cortical interneurons, but for technical reasons most work has been directed towards inhibitory neurons in the superficial cortical layers. Here we review current knowledge specifically on layer 5 (L5) inhibitory microcircuits, which play a critical role in controlling cortical output. We focus on recent work from the well-studied rodent barrel cortex, but also draw on evidence from studies in primary visual cortex and other cortical areas. The diversity of both deep inhibitory neurons and their pyramidal cell targets make this a challenging but essential area of study in cortical computation and sensory processing.
Collapse
Affiliation(s)
- Alexander Naka
- The Helen Wills Neuroscience Institute, University of California Berkeley Berkeley, CA, USA
| | - Hillel Adesnik
- The Helen Wills Neuroscience Institute, University of California BerkeleyBerkeley, CA, USA; Department of Molecular and Cell Biology, University of California BerkeleyBerkeley, CA, USA
| |
Collapse
|
20
|
Braun E, Marom S. Universality, complexity and the praxis of biology: Two case studies. STUDIES IN HISTORY AND PHILOSOPHY OF BIOLOGICAL AND BIOMEDICAL SCIENCES 2015; 53:68-72. [PMID: 25903120 DOI: 10.1016/j.shpsc.2015.03.007] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2015] [Accepted: 03/30/2015] [Indexed: 06/04/2023]
Abstract
The phenomenon of biology provides a prime example for a naturally occurring complex system. The approach to this complexity reflects the tension between a reductionist, reverse-engineering stance, and more abstract, systemic ones. Both of us are reductionists, but our observations challenge reductionism, at least the naive version of it. Here we describe the challenge, focusing on two universal characteristics of biological complexity: two-way microscopic-macroscopic degeneracy, and lack of time scale separation within and between levels of organization. These two features and their consequences for the praxis of experimental biology, reflect inherent difficulties in separating the dynamics of any given level of organization from the coupled dynamics of all other levels, including the environment within which the system is embedded. Where these difficulties are not deeply acknowledged, the impacts of fallacies that are inherent to naive reductionism are significant. In an era where technology enables experimental high-resolution access to numerous observables, the challenge faced by the mature reductionist-identification of relevant microscopic variables-becomes more demanding than ever. The demonstrations provided here are taken from two very different biological realizations: populations of microorganisms and populations of neurons, thus making the lesson potentially general.
Collapse
Affiliation(s)
- Erez Braun
- Technion-Israel Institute of Technology, Israel
| | - Shimon Marom
- Technion-Israel Institute of Technology, Israel.
| |
Collapse
|
21
|
Feldman JL, Kam K. Facing the challenge of mammalian neural microcircuits: taking a few breaths may help. J Physiol 2015; 593:3-23. [PMID: 25556783 DOI: 10.1113/jphysiol.2014.277632] [Citation(s) in RCA: 67] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2014] [Accepted: 11/01/2014] [Indexed: 12/27/2022] Open
Abstract
Breathing in mammals is a seemingly straightforward behaviour controlled by the brain. A brainstem nucleus called the preBötzinger Complex sits at the core of the neural circuit generating respiratory rhythm. Despite the discovery of this microcircuit almost 25 years ago, the mechanisms controlling breathing remain elusive. Given the apparent simplicity and well-defined nature of regulatory breathing behaviour, the identification of much of the circuitry, and the ability to study breathing in vitro as well as in vivo, many neuroscientists and physiologists are surprised that respiratory rhythm generation is still not well understood. Our view is that conventional rhythmogenic mechanisms involving pacemakers, inhibition or bursting are problematic and that simplifying assumptions commonly made for many vertebrate neural circuits ignore consequential detail. We propose that novel emergent mechanisms govern the generation of respiratory rhythm. That a mammalian function as basic as rhythm generation arises from complex and dynamic molecular, synaptic and neuronal interactions within a diverse neural microcircuit highlights the challenges in understanding neural control of mammalian behaviours, many (considerably) more elaborate than breathing. We suggest that the neural circuit controlling breathing is inimitably tractable and may inspire general strategies for elucidating other neural microcircuits.
Collapse
Affiliation(s)
- Jack L Feldman
- Systems Neurobiology Laboratory, Department of Neurobiology, David Geffen School of Medicine at the University of California Los Angeles, Los Angeles, CA, USA
| | | |
Collapse
|
22
|
Modes and nodes explain the mechanism of action of vortioxetine, a multimodal agent (MMA): modifying serotonin's downstream effects on glutamate and GABA (gamma amino butyric acid) release. CNS Spectr 2015; 20:331-6. [PMID: 26062900 DOI: 10.1017/s1092852915000334] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Vortioxetine is an antidepressant with multiple pharmacologic modes of action at targets where serotonin neurons connect with other neurons. These actions modify the release of both glutamate and GABA (gamma amino butyric acid) within various brain circuits.
Collapse
|
23
|
Turkheimer FE, Leech R, Expert P, Lord LD, Vernon AC. The brain's code and its canonical computational motifs. From sensory cortex to the default mode network: A multi-scale model of brain function in health and disease. Neurosci Biobehav Rev 2015; 55:211-22. [PMID: 25956253 DOI: 10.1016/j.neubiorev.2015.04.014] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2014] [Revised: 04/01/2015] [Accepted: 04/25/2015] [Indexed: 12/21/2022]
Affiliation(s)
| | - Robert Leech
- Division of Brain Sciences, Imperial College London, London, UK
| | - Paul Expert
- Institute of Psychiatry, King's College London, London, UK
| | | | | |
Collapse
|
24
|
Agliari E, Barra A, Galluzzi A, Guerra F, Tantari D, Tavani F. Retrieval capabilities of hierarchical networks: from Dyson to Hopfield. PHYSICAL REVIEW LETTERS 2015; 114:028103. [PMID: 25635564 DOI: 10.1103/physrevlett.114.028103] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2014] [Indexed: 06/04/2023]
Abstract
We consider statistical-mechanics models for spin systems built on hierarchical structures, which provide a simple example of non-mean-field framework. We show that the coupling decay with spin distance can give rise to peculiar features and phase diagrams much richer than their mean-field counterpart. In particular, we consider the Dyson model, mimicking ferromagnetism in lattices, and we prove the existence of a number of metastabilities, beyond the ordered state, which become stable in the thermodynamic limit. Such a feature is retained when the hierarchical structure is coupled with the Hebb rule for learning, hence mimicking the modular architecture of neurons, and gives rise to an associative network able to perform single pattern retrieval as well as multiple-pattern retrieval, depending crucially on the external stimuli and on the rate of interaction decay with distance; however, those emergent multitasking features reduce the network capacity with respect to the mean-field counterpart. The analysis is accomplished through statistical mechanics, Markov chain theory, signal-to-noise ratio technique, and numerical simulations in full consistency. Our results shed light on the biological complexity shown by real networks, and suggest future directions for understanding more realistic models.
Collapse
Affiliation(s)
- Elena Agliari
- Dipartimento di Fisica, Sapienza Università di Roma, Piazzale Aldo Moro 2, 00185 Roma, Italy
| | - Adriano Barra
- Dipartimento di Fisica, Sapienza Università di Roma, Piazzale Aldo Moro 2, 00185 Roma, Italy
| | - Andrea Galluzzi
- Dipartimento di Matematica, Sapienza Università di Roma, Piazzale Aldo Moro 2, 00185 Roma, Italy
| | - Francesco Guerra
- Dipartimento di Fisica, Sapienza Università di Roma, Piazzale Aldo Moro 2, 00185 Roma, Italy
| | - Daniele Tantari
- Dipartimento di Matematica, Sapienza Università di Roma, Piazzale Aldo Moro 2, 00185 Roma, Italy
| | - Flavia Tavani
- Dipartimento SBAI (Ingegneria), Sapienza Università di Roma, Via Antonio Scarpa 14, 00185 Roma, Italy
| |
Collapse
|
25
|
Janušonis S. Serotonin dynamics in and around the central nervous system: is autism solvable without fundamental insights? Int J Dev Neurosci 2014; 39:9-15. [PMID: 24886833 DOI: 10.1016/j.ijdevneu.2014.05.009] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2014] [Accepted: 05/20/2014] [Indexed: 12/15/2022] Open
Abstract
Altered serotonin (5-hydroxytryptamine, 5-HT) signaling has been implicated in some developmental abnormalities of autism spectrum disorder (ASD). However, the presumed role of 5-HT in ASD raises new questions in fundamental neuroscience. Specifically, it is not clear if the current piecemeal approach to 5-HT signaling in the mammalian body is effective and whether new conceptual approaches may be required. This review briefly discusses 5-HT production and circulation in the central nervous system and outside of it, especially with regard to ASD, and proposes a more encompassing approach that questions the utility of the "neurotransmitter" concept. It then introduces the idea of a generalized 5-HT packet that may offer insights into possible links between serotonergic varicosities and blood platelets. These approaches have theoretical significance, but they are also well positioned to advance our understanding of some long-standing problems in autism research.
Collapse
Affiliation(s)
- Skirmantas Janušonis
- Department of Psychological and Brain Sciences, University of California, Santa Barbara, CA 93106-9660, USA.
| |
Collapse
|
26
|
Murphey DK, Herman AM, Arenkiel BR. Dissecting inhibitory brain circuits with genetically-targeted technologies. Front Neural Circuits 2014; 8:124. [PMID: 25368555 PMCID: PMC4201106 DOI: 10.3389/fncir.2014.00124] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2014] [Accepted: 09/22/2014] [Indexed: 12/14/2022] Open
Abstract
The evolution of genetically targeted tools has begun to allow us to dissect anatomically and functionally heterogeneous interneurons, and to probe circuit function from synapses to behavior. Over the last decade, these tools have been used widely to visualize neurons in a cell type-specific manner, and engage them to activate and inactivate with exquisite precision. In this process, we have expanded our understanding of interneuron diversity, their functional connectivity, and how selective inhibitory circuits contribute to behavior. Here we discuss the relative assets of genetically encoded fluorescent proteins (FPs), viral tracing methods, optogenetics, chemical genetics, and biosensors in the study of inhibitory interneurons and their respective circuits.
Collapse
Affiliation(s)
- Dona K Murphey
- Department of Neurology, Baylor College of Medicine Houston, TX, USA
| | - Alexander M Herman
- Program in Developmental Biology, Baylor College of Medicine Houston, TX, USA
| | - Benjamin R Arenkiel
- Program in Developmental Biology, Baylor College of Medicine Houston, TX, USA ; Department of Molecular and Human Genetics, Baylor College of Medicine Houston, TX, USA ; Department of Neuroscience, Baylor College of Medicine Houston, TX, USA ; Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital Houston, TX, USA
| |
Collapse
|
27
|
Dynamic circuit motifs underlying rhythmic gain control, gating and integration. Nat Neurosci 2014; 17:1031-9. [DOI: 10.1038/nn.3764] [Citation(s) in RCA: 251] [Impact Index Per Article: 25.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2014] [Accepted: 06/16/2014] [Indexed: 12/12/2022]
|
28
|
Behavioral consequences of GABAergic neuronal diversity. Curr Opin Neurobiol 2014; 26:27-33. [DOI: 10.1016/j.conb.2013.11.002] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2013] [Revised: 10/22/2013] [Accepted: 11/06/2013] [Indexed: 11/23/2022]
|
29
|
Vlachos I, Zaytsev YV, Spreizer S, Aertsen A, Kumar A. Neural system prediction and identification challenge. Front Neuroinform 2014; 7:43. [PMID: 24399966 PMCID: PMC3872335 DOI: 10.3389/fninf.2013.00043] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2013] [Accepted: 12/11/2013] [Indexed: 11/29/2022] Open
Abstract
Can we infer the function of a biological neural network (BNN) if we know the connectivity and activity of all its constituent neurons?This question is at the core of neuroscience and, accordingly, various methods have been developed to record the activity and connectivity of as many neurons as possible. Surprisingly, there is no theoretical or computational demonstration that neuronal activity and connectivity are indeed sufficient to infer the function of a BNN. Therefore, we pose the Neural Systems Identification and Prediction Challenge (nuSPIC). We provide the connectivity and activity of all neurons and invite participants (1) to infer the functions implemented (hard-wired) in spiking neural networks (SNNs) by stimulating and recording the activity of neurons and, (2) to implement predefined mathematical/biological functions using SNNs. The nuSPICs can be accessed via a web-interface to the NEST simulator and the user is not required to know any specific programming language. Furthermore, the nuSPICs can be used as a teaching tool. Finally, nuSPICs use the crowd-sourcing model to address scientific issues. With this computational approach we aim to identify which functions can be inferred by systematic recordings of neuronal activity and connectivity. In addition, nuSPICs will help the design and application of new experimental paradigms based on the structure of the SNN and the presumed function which is to be discovered.
Collapse
Affiliation(s)
- Ioannis Vlachos
- Faculty of Biology, Bernstein Center Freiburg, University of Freiburg Freiburg im Breisgau, Germany
| | - Yury V Zaytsev
- Faculty of Biology, Bernstein Center Freiburg, University of Freiburg Freiburg im Breisgau, Germany ; Simulation Laboratory Neuroscience - Bernstein Facility for Simulation and Database Technology, Institute for Advanced Simulation, Jülich Aachen Research Alliance, Jülich Research Center Jülich, Germany
| | - Sebastian Spreizer
- Faculty of Biology, Bernstein Center Freiburg, University of Freiburg Freiburg im Breisgau, Germany
| | - Ad Aertsen
- Faculty of Biology, Bernstein Center Freiburg, University of Freiburg Freiburg im Breisgau, Germany
| | - Arvind Kumar
- Faculty of Biology, Bernstein Center Freiburg, University of Freiburg Freiburg im Breisgau, Germany
| |
Collapse
|