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Larry N, Zur G, Joshua M. Organization of reward and movement signals in the basal ganglia and cerebellum. Nat Commun 2024; 15:2119. [PMID: 38459003 PMCID: PMC10923830 DOI: 10.1038/s41467-024-45921-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Accepted: 02/06/2024] [Indexed: 03/10/2024] Open
Abstract
The basal ganglia and the cerebellum are major subcortical structures in the motor system. The basal ganglia have been cast as the reward center of the motor system, whereas the cerebellum is thought to be involved in adjusting sensorimotor parameters. Recent findings of reward signals in the cerebellum have challenged this dichotomous view. To compare the basal ganglia and the cerebellum directly, we recorded from oculomotor regions in both structures from the same monkeys. We partitioned the trial-by-trial variability of the neurons into reward and eye-movement signals to compare the coding across structures. Reward expectation and movement signals were the most pronounced in the output structure of the basal ganglia, intermediate in the cerebellum, and the smallest in the input structure of the basal ganglia. These findings suggest that reward and movement information is sharpened through the basal ganglia, resulting in a higher signal-to-noise ratio than in the cerebellum.
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Affiliation(s)
- Noga Larry
- Edmond and Lily Safra Center for Brain Sciences, the Hebrew University, Jerusalem, Israel.
| | - Gil Zur
- Edmond and Lily Safra Center for Brain Sciences, the Hebrew University, Jerusalem, Israel
| | - Mati Joshua
- Edmond and Lily Safra Center for Brain Sciences, the Hebrew University, Jerusalem, Israel.
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2
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Stern M, Istrate N, Mazzucato L. A reservoir of timescales emerges in recurrent circuits with heterogeneous neural assemblies. eLife 2023; 12:e86552. [PMID: 38084779 PMCID: PMC10810607 DOI: 10.7554/elife.86552] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 12/07/2023] [Indexed: 01/26/2024] Open
Abstract
The temporal activity of many physical and biological systems, from complex networks to neural circuits, exhibits fluctuations simultaneously varying over a large range of timescales. Long-tailed distributions of intrinsic timescales have been observed across neurons simultaneously recorded within the same cortical circuit. The mechanisms leading to this striking temporal heterogeneity are yet unknown. Here, we show that neural circuits, endowed with heterogeneous neural assemblies of different sizes, naturally generate multiple timescales of activity spanning several orders of magnitude. We develop an analytical theory using rate networks, supported by simulations of spiking networks with cell-type specific connectivity, to explain how neural timescales depend on assembly size and show that our model can naturally explain the long-tailed timescale distribution observed in the awake primate cortex. When driving recurrent networks of heterogeneous neural assemblies by a time-dependent broadband input, we found that large and small assemblies preferentially entrain slow and fast spectral components of the input, respectively. Our results suggest that heterogeneous assemblies can provide a biologically plausible mechanism for neural circuits to demix complex temporal input signals by transforming temporal into spatial neural codes via frequency-selective neural assemblies.
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Affiliation(s)
- Merav Stern
- Institute of Neuroscience, University of OregonEugeneUnited States
- Faculty of Medicine, The Hebrew University of JerusalemJerusalemIsrael
| | - Nicolae Istrate
- Institute of Neuroscience, University of OregonEugeneUnited States
- Departments of Physics, University of OregonEugeneUnited States
| | - Luca Mazzucato
- Institute of Neuroscience, University of OregonEugeneUnited States
- Departments of Physics, University of OregonEugeneUnited States
- Mathematics and Biology, University of OregonEugeneUnited States
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3
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Herzfeld DJ, Joshua M, Lisberger SG. Rate versus synchrony codes for cerebellar control of motor behavior. Neuron 2023; 111:2448-2460.e6. [PMID: 37536289 PMCID: PMC10424531 DOI: 10.1016/j.neuron.2023.07.002] [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: 02/23/2023] [Revised: 05/24/2023] [Accepted: 07/05/2023] [Indexed: 08/05/2023]
Abstract
Information transmission between neural populations could occur through either coordinated changes in firing rates or the precise transmission of spike timing. We investigate the code for information transmission from a part of the cerebellar cortex that is crucial for the accurate execution of a quantifiable motor behavior. Simultaneous recordings from Purkinje cell pairs in the cerebellum of rhesus macaques reveal how these cells coordinate their activity to drive smooth pursuit eye movements. Purkinje cells show millisecond-scale coordination of spikes (synchrony), but the level of synchrony is small and insufficient to impact the firing of downstream vestibular nucleus neurons. Analysis of previous metrics that purported to reveal Purkinje cell synchrony demonstrates that these metrics conflate changes in firing rate and neuron-neuron covariance. We conclude that the output of the cerebellar cortex uses primarily a rate rather than a synchrony code to drive the activity of downstream neurons and thus control motor behavior.
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Affiliation(s)
- David J Herzfeld
- Department of Neurobiology, Duke University School of Medicine, Durham, NC 27710, USA.
| | - Mati Joshua
- Edmond & Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Stephen G Lisberger
- Department of Neurobiology, Duke University School of Medicine, Durham, NC 27710, USA
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4
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Cheron G, Ris L, Cebolla AM. Nucleus incertus provides eye velocity and position signals to the vestibulo-ocular cerebellum: a new perspective of the brainstem-cerebellum-hippocampus network. Front Syst Neurosci 2023; 17:1180627. [PMID: 37304152 PMCID: PMC10248067 DOI: 10.3389/fnsys.2023.1180627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 05/04/2023] [Indexed: 06/13/2023] Open
Abstract
The network formed by the brainstem, cerebellum, and hippocampus occupies a central position to achieve navigation. Multiple physiological functions are implicated in this complex behavior. Among these, control of the eye-head and body movements is crucial. The gaze-holding system realized by the brainstem oculomotor neural integrator (ONI) situated in the nucleus prepositus hypoglossi and fine-tuned by the contribution of different regions of the cerebellum assumes the stability of the image on the fovea. This function helps in the recognition of environmental targets and defining appropriate navigational pathways further elaborated by the entorhinal cortex and hippocampus. In this context, an enigmatic brainstem area situated in front of the ONI, the nucleus incertus (NIC), is implicated in the dynamics of brainstem-hippocampus theta oscillation and contains a group of neurons projecting to the cerebellum. These neurons are characterized by burst tonic behavior similar to the burst tonic neurons in the ONI that convey eye velocity-position signals to the cerebellar flocculus. Faced with these forgotten cerebellar projections of the NIC, the present perspective discusses the possibility that, in addition to the already described pathways linking the cerebellum and the hippocampus via the medial septum, these NIC signals related to the vestibulo-ocular reflex and gaze holding could participate in the hippocampal control of navigation.
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Affiliation(s)
- Guy Cheron
- Laboratory of Neurophysiology and Movement Biomechanics, Université Libre de Bruxelles, Brussels, Belgium
- ULB Neuroscience Institute, Université Libre de Bruxelles, Brussels, Belgium
- Laboratory of Neuroscience, Université de Mons, Mons, Belgium
- UMONS Research Institute for Health and Technology, Université de Mons, Mons, Belgium
| | - Laurence Ris
- Laboratory of Neuroscience, Université de Mons, Mons, Belgium
- UMONS Research Institute for Health and Technology, Université de Mons, Mons, Belgium
| | - Ana Maria Cebolla
- Laboratory of Neurophysiology and Movement Biomechanics, Université Libre de Bruxelles, Brussels, Belgium
- ULB Neuroscience Institute, Université Libre de Bruxelles, Brussels, Belgium
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5
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Herzfeld DJ, Joshua M, Lisberger SG. Rate versus synchrony codes for cerebellar control of motor behavior. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.17.529019. [PMID: 36824885 PMCID: PMC9949136 DOI: 10.1101/2023.02.17.529019] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2023]
Abstract
UNLABELLED Control of movement requires the coordination of multiple brain areas, each containing populations of neurons that receive inputs, process these inputs via recurrent dynamics, and then relay the processed information to downstream populations. Information transmission between neural populations could occur through either coordinated changes in firing rates or the precise transmission of spike timing. We investigate the nature of the code for transmission of signals to downstream areas from a part of the cerebellar cortex that is crucial for the accurate execution of a quantifiable motor behavior. Simultaneous recordings from Purkinje cell pairs in the cerebellar flocculus of rhesus macaques revealed how these cells coordinate their activity to drive smooth pursuit eye movements. Purkinje cells show millisecond-scale coordination of spikes (synchrony), but the level of synchrony is small and likely insufficient to impact the firing of downstream neurons in the vestibular nucleus. Further, analysis of previous metrics for assaying Purkinje cell synchrony demonstrates that these metrics conflate changes in firing rate and neuron-neuron covariance. We conclude that the output of the cerebellar cortex uses primarily a rate code rather than synchrony code to drive activity of downstream neurons and thus control motor behavior. IMPACT STATEMENT Information transmission in the brain can occur via changes in firing rate or via the precise timing of spikes. Simultaneous recordings from pairs of Purkinje cells in the floccular complex reveals that information transmission out of the cerebellar cortex relies almost exclusively on changes in firing rates rather than millisecond-scale coordination of spike timing across the Purkinje cell population.
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Affiliation(s)
- David J. Herzfeld
- Department of Neurobiology, Duke University School of Medicine, Durham, NC, USA
| | - Mati Joshua
- Edmond & Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
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6
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Jeong W, Kim S, Park J, Lee J. Multivariate EEG activity reflects the Bayesian integration and the integrated Galilean relative velocity of sensory motion during sensorimotor behavior. Commun Biol 2023; 6:113. [PMID: 36709242 PMCID: PMC9884247 DOI: 10.1038/s42003-023-04481-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 01/12/2023] [Indexed: 01/29/2023] Open
Abstract
Humans integrate multiple sources of information for action-taking, using the reliability of each source to allocate weight to the data. This reliability-weighted information integration is a crucial property of Bayesian inference. In this study, participants were asked to perform a smooth pursuit eye movement task in which we independently manipulated the reliability of pursuit target motion and the direction-of-motion cue. Through an analysis of pursuit initiation and multivariate electroencephalography activity, we found neural and behavioral evidence of Bayesian information integration: more attraction toward the cue direction was generated when the target motion was weak and unreliable. Furthermore, using mathematical modeling, we found that the neural signature of Bayesian information integration had extra-retinal origins, although most of the multivariate electroencephalography activity patterns during pursuit were best correlated with the retinal velocity errors accumulated over time. Our results demonstrated neural implementation of Bayesian inference in human oculomotor behavior.
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Affiliation(s)
- Woojae Jeong
- grid.410720.00000 0004 1784 4496Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, 16419 Republic of Korea ,grid.42505.360000 0001 2156 6853Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089 USA
| | - Seolmin Kim
- grid.410720.00000 0004 1784 4496Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, 16419 Republic of Korea ,grid.264381.a0000 0001 2181 989XDepartment of Biomedical Engineering, Sungkyunkwan University, Suwon, 16419 Republic of Korea
| | - JeongJun Park
- grid.410720.00000 0004 1784 4496Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, 16419 Republic of Korea ,grid.4367.60000 0001 2355 7002Division of Biology and Biomedical Sciences, Program in Neurosciences, Washington University in St. Louis, St. Louis, MO 63130 USA
| | - Joonyeol Lee
- grid.410720.00000 0004 1784 4496Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, 16419 Republic of Korea ,grid.264381.a0000 0001 2181 989XDepartment of Biomedical Engineering, Sungkyunkwan University, Suwon, 16419 Republic of Korea ,grid.264381.a0000 0001 2181 989XDepartment of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, 16419 Republic of Korea
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7
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Miri A, Bhasin BJ, Aksay ERF, Tank DW, Goldman MS. Oculomotor plant and neural dynamics suggest gaze control requires integration on distributed timescales. J Physiol 2022; 600:3837-3863. [PMID: 35789005 PMCID: PMC10010930 DOI: 10.1113/jp282496] [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: 01/20/2022] [Accepted: 06/30/2022] [Indexed: 11/08/2022] Open
Abstract
A fundamental principle of biological motor control is that the neural commands driving movement must conform to the response properties of the motor plants they control. In the oculomotor system, characterizations of oculomotor plant dynamics traditionally supported models in which the plant responds to neural drive to extraocular muscles on exclusively short, subsecond timescales. These models predict that the stabilization of gaze during fixations between saccades requires neural drive that approximates eye position on longer timescales and is generated through the temporal integration of brief eye velocity-encoding signals that cause saccades. However, recent measurements of oculomotor plant behaviour have revealed responses on longer timescales. Furthermore, measurements of firing patterns in the oculomotor integrator have revealed a more complex encoding of eye movement dynamics. Yet, the link between these observations has remained unclear. Here we use measurements from the larval zebrafish to link dynamics in the oculomotor plant to dynamics in the neural integrator. The oculomotor plant in both anaesthetized and awake larval zebrafish was characterized by a broad distribution of response timescales, including those much longer than 1 s. Analysis of the firing patterns of oculomotor integrator neurons, which exhibited a broadly distributed range of decay time constants, demonstrates the sufficiency of this activity for stabilizing gaze given an oculomotor plant with distributed response timescales. This work suggests that leaky integration on multiple, distributed timescales by the oculomotor integrator reflects an inverse model for generating oculomotor commands, and that multi-timescale dynamics may be a general feature of motor circuitry. KEY POINTS: Recent observations of oculomotor plant response properties and neural activity across the oculomotor system have called into question classical formulations of both the oculomotor plant and the oculomotor integrator. Here we use measurements from new and published experiments in the larval zebrafish together with modelling to reconcile recent oculomotor plant observations with oculomotor integrator function. We developed computational techniques to characterize oculomotor plant responses over several seconds in awake animals, demonstrating that long timescale responses seen in anaesthetized animals extend to the awake state. Analysis of firing patterns of oculomotor integrator neurons demonstrates the sufficiency of this activity for stabilizing gaze given an oculomotor plant with multiple, distributed response timescales. Our results support a formulation of gaze stabilization by the oculomotor system in which commands for stabilizing gaze are generated through integration on multiple, distributed timescales.
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Affiliation(s)
- Andrew Miri
- Princeton Neuroscience Institute, Bezos Center for Neural Circuit Dynamics, and the Department of Molecular Biology, Princeton University, Princeton, NJ, USA
| | - Brandon J Bhasin
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Emre R F Aksay
- Institute for Computational Biomedicine and the Department of Physiology and Biophysics, Weill Cornell Medical College, Cornell University, New York, NY, USA
| | - David W Tank
- Princeton Neuroscience Institute, Bezos Center for Neural Circuit Dynamics, and the Department of Molecular Biology, Princeton University, Princeton, NJ, USA
| | - Mark S Goldman
- Center for Neuroscience, Department of Neurobiology, Physiology, and Behavior, and Department of Ophthalmology and Vision Science, University of California, Davis, Davis, CA, USA
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8
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Wardak A, Gong P. Extended Anderson Criticality in Heavy-Tailed Neural Networks. PHYSICAL REVIEW LETTERS 2022; 129:048103. [PMID: 35939004 DOI: 10.1103/physrevlett.129.048103] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 05/08/2022] [Accepted: 07/05/2022] [Indexed: 06/15/2023]
Abstract
We investigate the emergence of complex dynamics in networks with heavy-tailed connectivity by developing a non-Hermitian random matrix theory. We uncover the existence of an extended critical regime of spatially multifractal fluctuations between the quiescent and active phases. This multifractal critical phase combines features of localization and delocalization and differs from the edge of chaos in classical networks by the appearance of universal hallmarks of Anderson criticality over an extended region in phase space. We show that the rich nonlinear response properties of the extended critical regime can account for a variety of neural dynamics such as the diversity of timescales, providing a computational advantage for persistent classification in a reservoir setting.
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Affiliation(s)
- Asem Wardak
- School of Physics, University of Sydney, New South Wales 2006, Australia
| | - Pulin Gong
- School of Physics, University of Sydney, New South Wales 2006, Australia
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9
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Mazzucato L. Neural mechanisms underlying the temporal organization of naturalistic animal behavior. eLife 2022; 11:76577. [PMID: 35792884 PMCID: PMC9259028 DOI: 10.7554/elife.76577] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Accepted: 06/07/2022] [Indexed: 12/17/2022] Open
Abstract
Naturalistic animal behavior exhibits a strikingly complex organization in the temporal domain, with variability arising from at least three sources: hierarchical, contextual, and stochastic. What neural mechanisms and computational principles underlie such intricate temporal features? In this review, we provide a critical assessment of the existing behavioral and neurophysiological evidence for these sources of temporal variability in naturalistic behavior. Recent research converges on an emergent mechanistic theory of temporal variability based on attractor neural networks and metastable dynamics, arising via coordinated interactions between mesoscopic neural circuits. We highlight the crucial role played by structural heterogeneities as well as noise from mesoscopic feedback loops in regulating flexible behavior. We assess the shortcomings and missing links in the current theoretical and experimental literature and propose new directions of investigation to fill these gaps.
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Affiliation(s)
- Luca Mazzucato
- Institute of Neuroscience, Departments of Biology, Mathematics and Physics, University of Oregon
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10
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Fixational drift is driven by diffusive dynamics in central neural circuitry. Nat Commun 2022; 13:1697. [PMID: 35361753 PMCID: PMC8971408 DOI: 10.1038/s41467-022-29201-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Accepted: 03/04/2022] [Indexed: 11/08/2022] Open
Abstract
During fixation and between saccades, our eyes undergo diffusive random motion called fixational drift. The role of fixational drift in visual coding and inference has been debated in the past few decades, but the mechanisms that underlie this motion remained unknown. In particular, it has been unclear whether fixational drift arises from peripheral sources, or from central sources within the brain. Here we show that fixational drift is correlated with neural activity, and identify its origin in central neural circuitry within the oculomotor system, upstream to the ocular motoneurons (OMNs). We analyzed a large data set of OMN recordings in the rhesus monkey, alongside precise measurements of eye position, and found that most of the variance of fixational eye drifts must arise upstream of the OMNs. The diffusive statistics of the motion points to the oculomotor integrator, a memory circuit responsible for holding the eyes still between saccades, as a likely source of the motion. Theoretical modeling, constrained by the parameters of the primate oculomotor system, supports this hypothesis by accounting for the amplitude as well as the statistics of the motion. Thus, we propose that fixational ocular drift provides a direct observation of diffusive dynamics in a neural circuit responsible for storage of continuous parameter memory in persistent neural activity. The identification of a mechanistic origin for fixational drift is likely to advance the understanding of its role in visual processing and inference.
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11
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Strupp ML, Straumann D, Helmchen C. Central Ocular Motor Disorders: Clinical and Topographic Anatomical Diagnosis, Syndromes and Underlying Diseases. Klin Monbl Augenheilkd 2021; 238:1197-1211. [PMID: 34784643 DOI: 10.1055/a-1654-0632] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
The key to the diagnosis of ocular motor disorders is a systematic clinical examination of the different types of eye movements, including eye position, spontaneous nystagmus, range of eye movements, smooth pursuit, saccades, gaze-holding function, vergence, optokinetic nystagmus, as well as testing of the function of the vestibulo-ocular reflex (VOR) and visual fixation suppression of the VOR. This is like a window which allows you to look into the brain stem and cerebellum even if imaging is normal. Relevant anatomical structures are the midbrain, pons, medulla, cerebellum and rarely the cortex. There is a simple clinical rule: vertical and torsional eye movements are generated in the midbrain, horizontal eye movements in the pons. For example, isolated dysfunction of vertical eye movements is due to a midbrain lesion affecting the rostral interstitial nucleus of the medial longitudinal fasciculus (riMLF), with impaired vertical saccades only or vertical gaze-evoked nystagmus due to dysfunction of the Interstitial nucleus of Cajal (INC). Lesions of the lateral medulla oblongata (Wallenberg syndrome) lead to typical findings: ocular tilt reaction, central fixation nystagmus and dysmetric saccades. The cerebellum is relevant for almost all types of eye movements; typical pathological findings are saccadic smooth pursuit, gaze-evoked nystagmus or dysmetric saccades. The time course of the development of symptoms and signs is important for the diagnosis of underlying diseases: acute: most likely stroke; subacute: inflammatory diseases, metabolic diseases like thiamine deficiencies; chronic progressive: inherited diseases like Niemann-Pick type C with typically initially vertical and then horizontal saccade palsy or degenerative diseases like progressive supranuclear palsy. Treatment depends on the underlying disease. In this article, we deal with central ocular motor disorders. In a second article, we focus on clinically relevant types of nystagmus such as downbeat, upbeat, fixation pendular, gaze-evoked, infantile or periodic alternating nystagmus. Therefore, these types of nystagmus will not be described here in detail.
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Affiliation(s)
- Michael Leo Strupp
- Neurologische Klinik der Ludwig-Maximilians-Universität München, Deutschland.,Deutsches Schwindel- und Gleichgewichtszentrum der Ludwig-Maximilians-Universität München, Deutschland
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12
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Herzfeld DJ, Hall NJ, Tringides M, Lisberger SG. Principles of operation of a cerebellar learning circuit. eLife 2020; 9:e55217. [PMID: 32352914 PMCID: PMC7255800 DOI: 10.7554/elife.55217] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Accepted: 04/29/2020] [Indexed: 12/17/2022] Open
Abstract
We provide behavioral evidence using monkey smooth pursuit eye movements for four principles of cerebellar learning. Using a circuit-level model of the cerebellum, we link behavioral data to learning's neural implementation. The four principles are: (1) early, fast, acquisition driven by climbing fiber inputs to the cerebellar cortex, with poor retention; (2) learned responses of Purkinje cells guide transfer of learning from the cerebellar cortex to the deep cerebellar nucleus, with excellent retention; (3) functionally different neural signals are subject to learning in the cerebellar cortex versus the deep cerebellar nuclei; and (4) negative feedback from the cerebellum to the inferior olive reduces the magnitude of the teaching signal in climbing fibers and limits learning. Our circuit-level model, based on these four principles, explains behavioral data obtained by strategically manipulating the signals responsible for acquisition and recall of direction learning in smooth pursuit eye movements across multiple timescales.
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Affiliation(s)
- David J Herzfeld
- Department of Neurobiology, Duke University School of MedicineDurhamUnited States
| | - Nathan J Hall
- Department of Neurobiology, Duke University School of MedicineDurhamUnited States
| | - Marios Tringides
- Department of Neurobiology, Duke University School of MedicineDurhamUnited States
| | - Stephen G Lisberger
- Department of Neurobiology, Duke University School of MedicineDurhamUnited States
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13
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Abstract
BACKGROUND The brainstem contains numerous structures including afferent and efferent fibers that are involved in generation and control of eye movements. EVIDENCE ACQUISITION These structures give rise to distinct patterns of abnormal eye movements when damaged. Defining these ocular motor abnormalities allows a topographic diagnosis of a lesion within the brainstem. RESULTS Although diverse patterns of impaired eye movements may be observed in lesions of the brainstem, medullary lesions primarily cause various patterns of nystagmus and impaired vestibular eye movements without obvious ophthalmoplegia. By contrast, pontine ophthalmoplegia is characterized by abnormal eye movements in the horizontal plane, while midbrain lesions typically show vertical ophthalmoplegia in addition to pupillary and eyelid abnormalities. CONCLUSIONS Recognition of the patterns and characteristics of abnormal eye movements observed in brainstem lesions is important in understanding the roles of each neural structure and circuit in ocular motor control as well as in localizing the offending lesion.
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Lixenberg A, Yarkoni M, Botschko Y, Joshua M. Encoding of eye movements explains reward-related activity in cerebellar simple spikes. J Neurophysiol 2020; 123:786-799. [PMID: 31940216 PMCID: PMC7052631 DOI: 10.1152/jn.00363.2019] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2019] [Revised: 01/09/2020] [Accepted: 01/09/2020] [Indexed: 11/22/2022] Open
Abstract
The cerebellum exhibits both motor and reward-related signals. However, it remains unclear whether reward is processed independently from the motor command or might reflect the motor consequences of the reward drive. To test how reward-related signals interact with sensorimotor processing in the cerebellum, we recorded Purkinje cell simple spike activity in the cerebellar floccular complex while monkeys were engaged in smooth pursuit eye movement tasks. The color of the target signaled the size of the reward the monkeys would receive at the end of the target motion. When the tracking task presented a single target, both pursuit and neural activity were only slightly modulated by the reward size. The reward modulations in single cells were rarely large enough to be detected. These modulations were only significant in the population analysis when we averaged across many neurons. In two-target tasks where the monkey learned to select based on the size of the reward outcome, both behavior and neural activity adapted rapidly. In both the single- and two-target tasks, the size of the reward-related modulation matched the size of the effect of reward on behavior. Thus, unlike cortical activity in eye movement structures, the reward-related signals could not be dissociated from the motor command. These results suggest that reward information is integrated with the eye movement command upstream of the Purkinje cells in the floccular complex. Thus reward-related modulations of the simple spikes are akin to modulations found in motor behavior and not to the central processing of the reward value.NEW & NOTEWORTHY Disentangling sensorimotor and reward signals is only possible if these signals do not completely overlap. We recorded activity in the floccular complex of the cerebellum while monkeys performed tasks designed to separate representations of reward from those of movement. Activity modulation by reward could be accounted for by the coding of eye movement parameters, suggesting that reward information is already integrated into motor commands upstream of the floccular complex.
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Affiliation(s)
- Adi Lixenberg
- Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Merav Yarkoni
- Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Yehudit Botschko
- Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Mati Joshua
- Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
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15
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Eye movement abnormalities in middle cerebellar peduncle strokes. Acta Neurol Belg 2019; 119:37-45. [PMID: 29129037 DOI: 10.1007/s13760-017-0860-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2017] [Accepted: 11/04/2017] [Indexed: 12/19/2022]
Abstract
The middle cerebellar peduncle (MCP) is a major conduit for cortico-ponto-cerebellar fibers that convey information related to eye movements. This study aims to elucidate eye movement abnormalities that arise from lesions confined to the MCP. In 23 patients with acute strokes restricted to unilateral MCPs, we investigated the clinical features and ocular motor findings including spontaneous nystagmus, saccades, smooth pursuit, ocular tilt reaction, and head impulse tests. Bithermal caloric tests and audiometry were also performed. Patients with strokes restricted to the MCP usually developed acute vertigo or imbalance, along with few sensorimotor signs or auditory symptoms. Patients frequently showed abnormal eye movements that included spontaneous horizontal/torsional nystagmus, ocular tilt reaction, gaze-evoked nystagmus, abnormal head impulse responses, and bilaterally impaired horizontal smooth pursuit. Unilateral MCP strokes produce acute vertigo and imbalance with distinct ocular motor abnormalities, which are primarily caused by damage to the central vestibular structures and by disruption of the neural pathways responsible for eye-position stabilization and smooth pursuit.
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Sadeghpour S, Zee DS, Leigh RJ. Clinical applications of control systems models: The neural integrators for eye movements. PROGRESS IN BRAIN RESEARCH 2019; 248:103-114. [DOI: 10.1016/bs.pbr.2018.12.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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17
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Encoding of Reward and Decoding Movement from the Frontal Eye Field during Smooth Pursuit Eye Movements. J Neurosci 2018; 38:10515-10524. [PMID: 30355635 DOI: 10.1523/jneurosci.1654-18.2018] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2018] [Revised: 10/02/2018] [Accepted: 10/05/2018] [Indexed: 11/21/2022] Open
Abstract
Expectation of reward potentiates sensorimotor transformations to drive vigorous movements. One of the main challenges in studying reward is to determine how representations of reward interact with the computations that drive behavior. We recorded activity in smooth pursuit neurons in the frontal eye field (FEF) of two male rhesus monkeys while controlling the eye speed by manipulating either reward size or target speed. The neurons encoded the different reward conditions more strongly than the different target speed conditions. This pattern could not be explained by differences in the eye speed, since the eye speed sensitivity of the neurons was also larger for the reward conditions. Pooling the responses by the preferred direction of the neurons attenuated the reward modulation and led to a tighter association between neural activity and behavior. Therefore, a plausible decoder such as the population vector could explain how the FEF both drives behavior and encodes reward beyond behavior.SIGNIFICANCE STATEMENT Motor areas combine sensory and reward information to drive movement. To disambiguate these sources, we manipulated the speed of smooth pursuit eye movements by controlling either the size of the reward or the speed of the visual motion signals. We found that the relationship between activity in frontal eye field and eye kinematics varied: the eye speed sensitivity was larger for the different reward conditions than for the different target speed conditions. Decoders that pooled signals by the preferred direction of the neurons attenuated the reward modulations. These decoders may indicate how reward can be both encoded beyond eye kinematics at the single neuron level and drive movement at the population level.
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18
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Vishwanathan A, Daie K, Ramirez AD, Lichtman JW, Aksay ERF, Seung HS. Electron Microscopic Reconstruction of Functionally Identified Cells in a Neural Integrator. Curr Biol 2017; 27:2137-2147.e3. [PMID: 28712570 DOI: 10.1016/j.cub.2017.06.028] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2016] [Revised: 03/02/2017] [Accepted: 06/09/2017] [Indexed: 11/27/2022]
Abstract
Neural integrators are involved in a variety of sensorimotor and cognitive behaviors. The oculomotor system contains a simple example, a hindbrain neural circuit that takes velocity signals as inputs and temporally integrates them to control eye position. Here we investigated the structural underpinnings of temporal integration in the larval zebrafish by first identifying integrator neurons using two-photon calcium imaging and then reconstructing the same neurons through serial electron microscopic analysis. Integrator neurons were identified as those neurons with activities highly correlated with eye position during spontaneous eye movements. Three morphological classes of neurons were observed: ipsilaterally projecting neurons located medially, contralaterally projecting neurons located more laterally, and a population at the extreme lateral edge of the hindbrain for which we were not able to identify axons. Based on their somatic locations, we inferred that neurons with only ipsilaterally projecting axons are glutamatergic, whereas neurons with only contralaterally projecting axons are largely GABAergic. Dendritic and synaptic organization of the ipsilaterally projecting neurons suggests a broad sampling from inputs on the ipsilateral side. We also observed the first conclusive evidence of synapses between integrator neurons, which have long been hypothesized by recurrent network models of integration via positive feedback.
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Affiliation(s)
| | - Kayvon Daie
- Institute for Computational Biomedicine and Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10021, USA
| | - Alexandro D Ramirez
- Institute for Computational Biomedicine and Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10021, USA
| | - Jeff W Lichtman
- Department of Molecular and Cellular Biology and Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Emre R F Aksay
- Institute for Computational Biomedicine and Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10021, USA
| | - H Sebastian Seung
- Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA; Computer Science Department, Princeton University, Princeton, NJ 08544, USA.
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19
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Neromyliotis E, Moschovakis AK. Response Properties of Motor Equivalence Neurons of the Primate Premotor Cortex. Front Behav Neurosci 2017; 11:61. [PMID: 28446867 PMCID: PMC5388740 DOI: 10.3389/fnbeh.2017.00061] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2017] [Accepted: 03/27/2017] [Indexed: 11/23/2022] Open
Abstract
To study the response properties of cells that could participate in eye-hand coordination we trained two macaque monkeys to perform center-out saccades and pointing movements with their right or left forelimb toward visual targets presented on a video display. We analyzed the phasic movement related discharges of neurons of the periarcuate cortex that fire before and during saccades and movements of the hand whether accompanied by movements of the other effector or not. Because such cells could encode an abstract form of the desired displacement vector without regard to the effector that would execute the movement we refer to such cells as motor equivalence neurons (Meq). Most of them (75%) were found in or near the smooth pursuit region and the grasp related region in the caudal bank of the arcuate sulcus. The onset of their phasic discharges preceded saccades by about 70 ms and hand movements by about 150 ms and was often correlated to both the onset of saccades and the onset of hand movements. The on-direction of Meq cells was uniformly distributed without preference for ipsiversive or contraversive movements. In about half of the Meq cells the preferred direction for saccades was the preferred direction for hand movements as well. In the remaining cells the difference was considerable (>90 deg), and the on-direction for eye-hand movements resembled that for isolated saccades in some cells and for isolated hand movements in others. A three layer neural network model that used Meq cells as its input layer showed that the combination of effector invariant discharges with non-invariant discharges could help reduce the number of decoding errors when the network attempts to compute the correct movement metrics of the right effector.
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Affiliation(s)
- Eleftherios Neromyliotis
- Institute of Applied and Computational Mathematics, Foundation for Research and TechnologyHeraklion, Greece.,Department of Basic Sciences, Faculty of Medicine, University of CreteHeraklion, Greece
| | - A K Moschovakis
- Institute of Applied and Computational Mathematics, Foundation for Research and TechnologyHeraklion, Greece.,Department of Basic Sciences, Faculty of Medicine, University of CreteHeraklion, Greece
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20
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Lee J, Joshua M, Medina JF, Lisberger SG. Signal, Noise, and Variation in Neural and Sensory-Motor Latency. Neuron 2016; 90:165-76. [PMID: 26971946 DOI: 10.1016/j.neuron.2016.02.012] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2015] [Revised: 01/16/2016] [Accepted: 02/04/2016] [Indexed: 01/22/2023]
Abstract
Analysis of the neural code for sensory-motor latency in smooth pursuit eye movements reveals general principles of neural variation and the specific origin of motor latency. The trial-by-trial variation in neural latency in MT comprises a shared component expressed as neuron-neuron latency correlations and an independent component that is local to each neuron. The independent component arises heavily from fluctuations in the underlying probability of spiking, with an unexpectedly small contribution from the stochastic nature of spiking itself. The shared component causes the latency of single-neuron responses in MT to be weakly predictive of the behavioral latency of pursuit. Neural latency deeper in the motor system is more strongly predictive of behavioral latency. A model reproduces both the variance of behavioral latency and the neuron-behavior latency correlations in MT if it includes realistic neural latency variation, neuron-neuron latency correlations in MT, and noisy gain control downstream of MT.
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Affiliation(s)
- Joonyeol Lee
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon 16419, Republic of Korea; Department of Biomedical Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea.
| | - Mati Joshua
- Edmond and Lily Safra Center for Brain Sciences, the Hebrew University, Jerusalem 91904, Israel
| | - Javier F Medina
- Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030, USA
| | - Stephen G Lisberger
- Department of Neurobiology, Duke University School of Medicine, Durham, NC 27710, USA
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21
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Abstract
The accumulation and storage of information over time, temporal integration, is key to numerous behaviors. Many oculomotor tasks depend on integration of eye-velocity signals to eye-position commands, a transformation achieved by a hindbrain cell group termed the velocity-to-position neural integrator (VPNI). Although the VPNI's coding properties have been well characterized, its mechanism of function remains poorly understood because few links exist between neuronal activity, structure, and genotypic identity. To fill this gap, we used calcium imaging and single-cell electroporation during oculomotor behaviors to map VPNI neural activity in zebrafish onto a hindbrain scaffold consisting of alternating excitatory and inhibitory parasagittal stripes. Three distinct classes of VPNI cells were identified. One glutamatergic class was medially located along a stripe associated with the alx transcription factor; these cells had ipsilateral projections terminating near abducens motoneurons and collateralized extensively within the ipsilateral VPNI in a manner consistent with integration through recurrent excitation. A second glutamatergic class was more laterally located along a stripe associated with transcription factor dbx1b; these glutamatergic cells had contralateral projections collateralizing near abducens motoneurons, consistent with a role in disconjugate eye movements. A third class, immunohistochemically suggested to be GABAergic, was located primarily in the dbx1b stripe and also had contralateral projections terminating near abducens motoneurons; these cells collateralized extensively in the dendritic field of contralateral VPNI neurons, consistent with a role in coordinating activity between functionally opposing populations. This mapping between VPNI activity, structure, and genotype may provide a blueprint for understanding the mechanisms governing temporal integration.
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22
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Rahimi-Balaei M, Afsharinezhad P, Bailey K, Buchok M, Yeganeh B, Marzban H. Embryonic stages in cerebellar afferent development. CEREBELLUM & ATAXIAS 2015; 2:7. [PMID: 26331050 PMCID: PMC4552263 DOI: 10.1186/s40673-015-0026-y] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/17/2015] [Accepted: 05/19/2015] [Indexed: 02/04/2023]
Abstract
The cerebellum is important for motor control, cognition, and language processing. Afferent and efferent fibers are major components of cerebellar circuitry and impairment of these circuits causes severe cerebellar malfunction, such as ataxia. The cerebellum receives information from two major afferent types – climbing fibers and mossy fibers. In addition, a third set of afferents project to the cerebellum as neuromodulatory fibers. The spatiotemporal pattern of early cerebellar afferents that enter the developing embryonic cerebellum is not fully understood. In this review, we will discuss the cerebellar architecture and connectivity specifically related to afferents during development in different species. We will also consider the order of afferent fiber arrival into the developing cerebellum to establish neural connectivity.
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Affiliation(s)
- Maryam Rahimi-Balaei
- Department of Human Anatomy and Cell Science, College of Medicine, Faculty of Health Sciences, University of Manitoba, Rm129, BMSB, 745 Bannatyne Avenue, Winnipeg, Manitoba R3E 0J9 Canada ; College of Medicine, Faculty of Health Sciences, Manitoba Institute of Child Health (MICH), University of Manitoba, Winnipeg, Manitoba Canada
| | - Pegah Afsharinezhad
- Department of Human Anatomy and Cell Science, College of Medicine, Faculty of Health Sciences, University of Manitoba, Rm129, BMSB, 745 Bannatyne Avenue, Winnipeg, Manitoba R3E 0J9 Canada
| | - Karen Bailey
- Department of Human Anatomy and Cell Science, College of Medicine, Faculty of Health Sciences, University of Manitoba, Rm129, BMSB, 745 Bannatyne Avenue, Winnipeg, Manitoba R3E 0J9 Canada
| | - Matthew Buchok
- Department of Human Anatomy and Cell Science, College of Medicine, Faculty of Health Sciences, University of Manitoba, Rm129, BMSB, 745 Bannatyne Avenue, Winnipeg, Manitoba R3E 0J9 Canada
| | - Behzad Yeganeh
- Program in Physiology and Experimental Medicine, Hospital for Sick Children and University of Toronto, Toronto, Ontario Canada
| | - Hassan Marzban
- Department of Human Anatomy and Cell Science, College of Medicine, Faculty of Health Sciences, University of Manitoba, Rm129, BMSB, 745 Bannatyne Avenue, Winnipeg, Manitoba R3E 0J9 Canada ; College of Medicine, Faculty of Health Sciences, Manitoba Institute of Child Health (MICH), University of Manitoba, Winnipeg, Manitoba Canada
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Daie K, Goldman MS, Aksay ERF. Spatial patterns of persistent neural activity vary with the behavioral context of short-term memory. Neuron 2015; 85:847-60. [PMID: 25661184 DOI: 10.1016/j.neuron.2015.01.006] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2014] [Revised: 08/25/2014] [Accepted: 01/06/2015] [Indexed: 10/24/2022]
Abstract
A short-term memory can be evoked by different inputs and control separate targets in different behavioral contexts. To address the circuit mechanisms underlying context-dependent memory function, we determined through optical imaging how memory is encoded at the whole-network level in two behavioral settings. Persistent neural activity maintaining a memory of desired eye position was imaged throughout the oculomotor integrator after saccadic or optokinetic stimulation. While eye position was encoded by the amplitude of network activity, the spatial patterns of firing were context dependent: cells located caudally generally were most persistent following saccadic input, whereas cells located rostrally were most persistent following optokinetic input. To explain these data, we computationally identified four independent modes of network activity and found these were differentially accessed by saccadic and optokinetic inputs. These results show how a circuit can simultaneously encode memory value and behavioral context, respectively, in its amplitude and spatial pattern of persistent firing.
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Affiliation(s)
- Kayvon Daie
- Institute for Computational Biomedicine and Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA; Department of Physics, Cornell University, Ithaca, NY 14853, USA
| | - Mark S Goldman
- Center for Neuroscience, Department of Neurobiology, Physiology, and Behavior, and Department of Ophthalmology and Vision Science, University of California, Davis, Davis, CA 95618, USA.
| | - Emre R F Aksay
- Institute for Computational Biomedicine and Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY 10065, USA.
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24
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The Neural Code for Motor Control in the Cerebellum and Oculomotor Brainstem. eNeuro 2014; 1:eN-NWRT-0004-14. [PMID: 26464956 PMCID: PMC4596133 DOI: 10.1523/eneuro.0004-14.2014] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2014] [Revised: 09/29/2014] [Accepted: 10/03/2014] [Indexed: 11/21/2022] Open
Abstract
Our paper evaluates the nature of the neural code under conditions where we can understand the details of trial-by-trial neural variation and its relationship to behavior. We demonstrate that a single extra spike in the activity of a neuron can predict impending motor behavior. Spike trains are rich in information that can be extracted to guide behaviors at millisecond time resolution or across longer time intervals. In sensory systems, the information usually is defined with respect to the stimulus. Especially in motor systems, however, it is equally critical to understand how spike trains predict behavior. Thus, our goal was to compare systematically spike trains in the oculomotor system with eye movement behavior on single movements. We analyzed the discharge of Purkinje cells in the floccular complex of the cerebellum, floccular target neurons in the brainstem, other vestibular neurons, and abducens neurons. We find that an extra spike in a brief analysis window predicts a substantial fraction of the trial-by-trial variation in the initiation of smooth pursuit eye movements. For Purkinje cells, a single extra spike in a 40 ms analysis window predicts, on average, 0.5 SDs of the variation in behavior. An optimal linear estimator predicts behavioral variation slightly better than do spike counts in brief windows. Simulations reveal that the ability of single spikes to predict a fraction of behavior also emerges from model spike trains that have the same statistics as the real spike trains, as long as they are driven by shared sensory inputs. We think that the shared sensory estimates in their inputs create correlations in neural spiking across time and across each population. As a result, one or a small number of spikes in a brief time interval can predict a substantial fraction of behavioral variation.
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25
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Joshua M, Lisberger SG. A tale of two species: Neural integration in zebrafish and monkeys. Neuroscience 2014; 296:80-91. [PMID: 24797331 DOI: 10.1016/j.neuroscience.2014.04.048] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2014] [Revised: 04/18/2014] [Accepted: 04/21/2014] [Indexed: 11/30/2022]
Abstract
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.
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Affiliation(s)
- M Joshua
- Department of Neurobiology and Howard Hughes Medical Institute, Duke University, Durham, NC, USA.
| | - S G Lisberger
- Department of Neurobiology and Howard Hughes Medical Institute, Duke University, Durham, NC, USA
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26
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Abstract
Neurons show diverse timescales, so that different parts of a network respond with disparate temporal dynamics. Such diversity is observed both when comparing timescales across brain areas and among cells within local populations; the underlying circuit mechanism remains unknown. We examine conditions under which spatially local connectivity can produce such diverse temporal behavior. In a linear network, timescales are segregated if the eigenvectors of the connectivity matrix are localized to different parts of the network. We develop a framework to predict the shapes of localized eigenvectors. Notably, local connectivity alone is insufficient for separate timescales. However, localization of timescales can be realized by heterogeneity in the connectivity profile, and we demonstrate two classes of network architecture that allow such localization. Our results suggest a framework to relate structural heterogeneity to functional diversity and, beyond neural dynamics, are generally applicable to the relationship between structure and dynamics in biological networks. DOI: http://dx.doi.org/10.7554/eLife.01239.001.
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Affiliation(s)
- Rishidev Chaudhuri
- Department of Applied Mathematics, Yale University, New Haven, United States
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27
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Joshua M, Lisberger SG. A framework for using signal, noise, and variation to determine whether the brain controls movement synergies or single muscles. J Neurophysiol 2013; 111:733-45. [PMID: 24259547 DOI: 10.1152/jn.00510.2013] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
We have used an analysis of signal and variation in motor behavior to elucidate the organization of the cerebellar and brain stem circuits that control smooth pursuit eye movements. We recorded from the abducens nucleus and identified floccular target neurons (FTNs) and other, non-FTN vestibular neurons. First, we assessed neuron-behavior correlations, defined as the trial-by-trial correlation between the variation in neural firing and eye movement, in brain stem neurons. In agreement with prior data from the cerebellum, neuron-behavior correlations during pursuit initiation were large in all neurons. Second, we asked whether movement variation arises upstream from, in parallel to, or downstream from a given site of recording. We developed a model that highlighted two measures: the ratio of the SDs of neural firing rate and eye movement ("SDratio") and the neuron-behavior correlation. The relationship between these measures defines possible sources of variation. During pursuit initiation, SDratio was approximately equal to neuron-behavior correlation, meaning that the source of signal and variation is upstream from the brain stem. During steady-state pursuit, neuron-behavior correlation became somewhat smaller than SDratio for FTNs, meaning that some variation may arise downstream in the brain stem. The data contradicted the model's predictions for sources of variation in pathways that run parallel to the site of recording. Because signal and noise are tightly linked in motor control, we take the source of variation as a proxy for the source of signal, leading us to conclude that the brain controls movement synergies rather than single muscles for eye movements.
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Affiliation(s)
- Mati Joshua
- Department of Neurobiology and Howard Hughes Medical Institute, Duke University, Durham, North Carolina
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28
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Cheron G, Dan B, Márquez-Ruiz J. Translational approach to behavioral learning: lessons from cerebellar plasticity. Neural Plast 2013; 2013:853654. [PMID: 24319600 PMCID: PMC3844268 DOI: 10.1155/2013/853654] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2013] [Accepted: 09/18/2013] [Indexed: 11/17/2022] Open
Abstract
The role of cerebellar plasticity has been increasingly recognized in learning. The privileged relationship between the cerebellum and the inferior olive offers an ideal circuit for attempting to integrate the numerous evidences of neuronal plasticity into a translational perspective. The high learning capacity of the Purkinje cells specifically controlled by the climbing fiber represents a major element within the feed-forward and feedback loops of the cerebellar cortex. Reciprocally connected with the basal ganglia and multimodal cerebral domains, this cerebellar network may realize fundamental functions in a wide range of behaviors. This review will outline the current understanding of three main experimental paradigms largely used for revealing cerebellar functions in behavioral learning: (1) the vestibuloocular reflex and smooth pursuit control, (2) the eyeblink conditioning, and (3) the sensory envelope plasticity. For each of these experimental conditions, we have critically revisited the chain of causalities linking together neural circuits, neural signals, and plasticity mechanisms, giving preference to behaving or alert animal physiology. Namely, recent experimental approaches mixing neural units and local field potentials recordings have demonstrated a spike timing dependent plasticity by which the cerebellum remains at a strategic crossroad for deciphering fundamental and translational mechanisms from cellular to network levels.
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Affiliation(s)
- Guy Cheron
- Laboratory of Electrophysiology, Université de Mons, 7000 Mons, Belgium
- Laboratory of Neurophysiology and Movement Biomechanics, CP640, ULB Neuroscience Institut, Université Libre de Bruxelles, 1070 Brussels, Belgium
| | - Bernard Dan
- Laboratory of Neurophysiology and Movement Biomechanics, CP640, ULB Neuroscience Institut, Université Libre de Bruxelles, 1070 Brussels, Belgium
- Department of Neurology, Hôpital Universitaire des Enfants Reine Fabiola, Université Libre de Bruxelles, 1020 Brussels, Belgium
| | - Javier Márquez-Ruiz
- División de Neurociencias, Universidad Pablo de Olavide, 41013 Sevilla, Spain
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