101
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Abstract
In the primary visual cortex (V1), Simple and Complex receptive fields (RFs) are usually characterized on the basis of the linearity of the cell spiking response to stimuli of opposite contrast. Whether or not this classification reflects a functional dichotomy in the synaptic inputs to Simple and Complex cells is still an open issue. Here we combined intracellular membrane potential recordings in cat V1 with 2D dense noise stimulation to decompose the Simple-like and Complex-like components of the subthreshold RF into a parallel set of functionally distinct subunits. Results show that both Simple and Complex RFs exhibit a remarkable diversity of excitatory and inhibitory Complex-like contributions, which differ in orientation and spatial frequency selectivity from the linear RF, even in layer 4 and layer 6 Simple cells. We further show that the diversity of Complex-like contributions recovered at the subthreshold level is expressed in the cell spiking output. These results demonstrate that the Simple or Complex nature of V1 RFs does not rely on the diversity of Complex-like components received by the cell from its synaptic afferents but on the imbalance between the weights of the Simple-like and Complex-like synaptic contributions.
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102
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Van Hooser SD, Escobar GM, Maffei A, Miller P. Emerging feed-forward inhibition allows the robust formation of direction selectivity in the developing ferret visual cortex. J Neurophysiol 2014; 111:2355-73. [PMID: 24598528 PMCID: PMC4099478 DOI: 10.1152/jn.00891.2013] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2013] [Accepted: 03/03/2014] [Indexed: 11/22/2022] Open
Abstract
The computation of direction selectivity requires that a cell respond to joint spatial and temporal characteristics of the stimulus that cannot be separated into independent components. Direction selectivity in ferret visual cortex is not present at the time of eye opening but instead develops in the days and weeks following eye opening in a process that requires visual experience with moving stimuli. Classic Hebbian or spike timing-dependent modification of excitatory feed-forward synaptic inputs is unable to produce direction-selective cells from unselective or weakly directionally biased initial conditions because inputs eventually grow so strong that they can independently drive cortical neurons, violating the joint spatial-temporal activation requirement. Furthermore, without some form of synaptic competition, cells cannot develop direction selectivity in response to training with bidirectional stimulation, as cells in ferret visual cortex do. We show that imposing a maximum lateral geniculate nucleus (LGN)-to-cortex synaptic weight allows neurons to develop direction-selective responses that maintain the requirement for joint spatial and temporal activation. We demonstrate that a novel form of inhibitory plasticity, postsynaptic activity-dependent long-term potentiation of inhibition (POSD-LTPi), which operates in the developing cortex at the time of eye opening, can provide synaptic competition and enables robust development of direction-selective receptive fields with unidirectional or bidirectional stimulation. We propose a general model of the development of spatiotemporal receptive fields that consists of two phases: an experience-independent establishment of initial biases, followed by an experience-dependent amplification or modification of these biases via correlation-based plasticity of excitatory inputs that compete against gradually increasing feed-forward inhibition.
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Affiliation(s)
- Stephen D Van Hooser
- Department of Biology, Brandeis University, Waltham, Massachusetts; Sloan-Swartz Center for Theoretical Neurobiology, Brandeis University, Waltham, Massachusetts; Volen Center for Complex Systems, Brandeis University, Waltham, Massachusetts;
| | - Gina M Escobar
- Department of Biology, Brandeis University, Waltham, Massachusetts; Sloan-Swartz Center for Theoretical Neurobiology, Brandeis University, Waltham, Massachusetts; Volen Center for Complex Systems, Brandeis University, Waltham, Massachusetts
| | - Arianna Maffei
- Department of Neurobiology and Behavior, State University of New York-Stony Brook, Stony Brook, New York; and SUNY Eye Institute, State University of New York-Stony Brook, Stony Brook, New York
| | - Paul Miller
- Department of Biology, Brandeis University, Waltham, Massachusetts; Sloan-Swartz Center for Theoretical Neurobiology, Brandeis University, Waltham, Massachusetts; Volen Center for Complex Systems, Brandeis University, Waltham, Massachusetts
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103
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Nassi JJ, Gómez-Laberge C, Kreiman G, Born RT. Corticocortical feedback increases the spatial extent of normalization. Front Syst Neurosci 2014; 8:105. [PMID: 24910596 PMCID: PMC4039070 DOI: 10.3389/fnsys.2014.00105] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2014] [Accepted: 05/13/2014] [Indexed: 11/13/2022] Open
Abstract
Normalization has been proposed as a canonical computation operating across different brain regions, sensory modalities, and species. It provides a good phenomenological description of non-linear response properties in primary visual cortex (V1), including the contrast response function and surround suppression. Despite its widespread application throughout the visual system, the underlying neural mechanisms remain largely unknown. We recently observed that corticocortical feedback contributes to surround suppression in V1, raising the possibility that feedback acts through normalization. To test this idea, we characterized area summation and contrast response properties in V1 with and without feedback from V2 and V3 in alert macaques and applied a standard normalization model to the data. Area summation properties were well explained by a form of divisive normalization, which computes the ratio between a neuron's driving input and the spatially integrated activity of a "normalization pool." Feedback inactivation reduced surround suppression by shrinking the spatial extent of the normalization pool. This effect was independent of the gain modulation thought to mediate the influence of contrast on area summation, which remained intact during feedback inactivation. Contrast sensitivity within the receptive field center was also unaffected by feedback inactivation, providing further evidence that feedback participates in normalization independent of the circuit mechanisms involved in modulating contrast gain and saturation. These results suggest that corticocortical feedback contributes to surround suppression by increasing the visuotopic extent of normalization and, via this mechanism, feedback can play a critical role in contextual information processing.
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Affiliation(s)
- Jonathan J Nassi
- Department of Neurobiology, Harvard Medical School Boston, MA, USA
| | - Camille Gómez-Laberge
- Department of Neurobiology, Harvard Medical School Boston, MA, USA ; Department of Ophthalmology, Boston Children's Hospital Boston, MA, USA
| | - Gabriel Kreiman
- Department of Ophthalmology, Boston Children's Hospital Boston, MA, USA ; Swartz Center for Theoretical Neuroscience, Harvard University Cambridge, MA, USA
| | - Richard T Born
- Department of Neurobiology, Harvard Medical School Boston, MA, USA
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104
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Abstract
Training or exposure to a visual feature leads to a long-term improvement in performance on visual tasks that employ this feature. Such performance improvements and the processes that govern them are called visual perceptual learning (VPL). As an ever greater volume of research accumulates in the field, we have reached a point where a unifying model of VPL should be sought. A new wave of research findings has exposed diverging results along three major directions in VPL: specificity versus generalization of VPL, lower versus higher brain locus of VPL, and task-relevant versus task-irrelevant VPL. In this review, we propose a new theoretical model that suggests the involvement of two different stages in VPL: a low-level, stimulus-driven stage, and a higher-level stage dominated by task demands. If experimentally verified, this model would not only constructively unify the current divergent results in the VPL field, but would also lead to a significantly better understanding of visual plasticity, which may, in turn, lead to interventions to ameliorate diseases affecting vision and other pathological or age-related visual and nonvisual declines.
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Affiliation(s)
- Kazuhisa Shibata
- Department of Cognitive, Linguistic & Psychological Sciences, Brown University, Providence, Rhode Island
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105
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Grimes WN, Schwartz GW, Rieke F. The synaptic and circuit mechanisms underlying a change in spatial encoding in the retina. Neuron 2014; 82:460-73. [PMID: 24742466 PMCID: PMC4038266 DOI: 10.1016/j.neuron.2014.02.037] [Citation(s) in RCA: 83] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/14/2014] [Indexed: 10/25/2022]
Abstract
Components of neural circuits are often repurposed so that the same biological hardware can be used for distinct computations. This flexibility in circuit operation is required to account for the changes in sensory computations that accompany changes in input signals. Yet we know little about how such changes in circuit operation are implemented. Here we show that a single retinal ganglion cell performs a different computation in dim light--averaging contrast within its receptive field--than in brighter light, when the cell becomes sensitive to fine spatial detail. This computational change depends on interactions between two parallel circuits that control the ganglion cell's excitatory synaptic inputs. Specifically, steady-state interactions through dendro-axonal gap junctions control rectification of the synapses providing excitatory input to the ganglion cell. These findings provide a clear example of how a simple synaptic mechanism can repurpose a neural circuit to perform diverse computations.
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Affiliation(s)
- William N Grimes
- Department of Physiology and Biophysics and Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA
| | - Gregory W Schwartz
- Department of Physiology and Biophysics and Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA
| | - Fred Rieke
- Department of Physiology and Biophysics and Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA.
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106
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Abstract
How we attend to objects and their features that cannot be separated by location is not understood. We presented two temporally and spatially overlapping streams of objects, faces versus houses, and used magnetoencephalography and functional magnetic resonance imaging to separate neuronal responses to attended and unattended objects. Attention to faces versus houses enhanced the sensory responses in the fusiform face area (FFA) and parahippocampal place area (PPA), respectively. The increases in sensory responses were accompanied by induced gamma synchrony between the inferior frontal junction, IFJ, and either FFA or PPA, depending on which object was attended. The IFJ appeared to be the driver of the synchrony, as gamma phases were advanced by 20 ms in IFJ compared to FFA or PPA. Thus, the IFJ may direct the flow of visual processing during object-based attention, at least in part through coupled oscillations with specialized areas such as FFA and PPA.
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Affiliation(s)
- Daniel Baldauf
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, 02139 MA, USA
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107
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Griffen TC, Maffei A. GABAergic synapses: their plasticity and role in sensory cortex. Front Cell Neurosci 2014; 8:91. [PMID: 24723851 PMCID: PMC3972456 DOI: 10.3389/fncel.2014.00091] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2014] [Accepted: 03/12/2014] [Indexed: 12/17/2022] Open
Abstract
The mammalian neocortex is composed of a variety of cell types organized in a highly interconnected circuit. GABAergic neurons account for only about 20% of cortical neurons. However, they show widespread connectivity and a high degree of diversity in morphology, location, electrophysiological properties and gene expression. In addition, distinct populations of inhibitory neurons have different sensory response properties, capacities for plasticity and sensitivities to changes in sensory experience. In this review we summarize experimental evidence regarding the properties of GABAergic neurons in primary sensory cortex. We will discuss how distinct GABAergic neurons and different forms of GABAergic inhibitory plasticity may contribute to shaping sensory cortical circuit activity and function.
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Affiliation(s)
- Trevor C Griffen
- SUNY Eye Research Consortium Buffalo, NY, USA ; Program in Neuroscience, SUNY - Stony Brook Stony Brook, NY, USA ; Medical Scientist Training Program, SUNY - Stony Brook Stony Brook, NY, USA
| | - Arianna Maffei
- SUNY Eye Research Consortium Buffalo, NY, USA ; Department of Neurobiology and Behavior, SUNY - Stony Brook Stony Brook, NY, USA
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108
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Sadeh S, Cardanobile S, Rotter S. Mean-field analysis of orientation selectivity in inhibition-dominated networks of spiking neurons. SPRINGERPLUS 2014; 3:148. [PMID: 24790806 PMCID: PMC4003001 DOI: 10.1186/2193-1801-3-148] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/13/2014] [Accepted: 03/14/2014] [Indexed: 11/10/2022]
Abstract
Mechanisms underlying the emergence of orientation selectivity in the primary visual cortex are highly debated. Here we study the contribution of inhibition-dominated random recurrent networks to orientation selectivity, and more generally to sensory processing. By simulating and analyzing large-scale networks of spiking neurons, we investigate tuning amplification and contrast invariance of orientation selectivity in these networks. In particular, we show how selective attenuation of the common mode and amplification of the modulation component take place in these networks. Selective attenuation of the baseline, which is governed by the exceptional eigenvalue of the connectivity matrix, removes the unspecific, redundant signal component and ensures the invariance of selectivity across different contrasts. Selective amplification of modulation, which is governed by the operating regime of the network and depends on the strength of coupling, amplifies the informative signal component and thus increases the signal-to-noise ratio. Here, we perform a mean-field analysis which accounts for this process.
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Affiliation(s)
- Sadra Sadeh
- Bernstein Center Freiburg & Faculty of Biology, University of Freiburg, Hansastr. 9a, 79104 Freiburg, Germany
| | - Stefano Cardanobile
- Bernstein Center Freiburg & Faculty of Biology, University of Freiburg, Hansastr. 9a, 79104 Freiburg, Germany
| | - Stefan Rotter
- Bernstein Center Freiburg & Faculty of Biology, University of Freiburg, Hansastr. 9a, 79104 Freiburg, Germany
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109
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Lisman J. Gamma frequency feedback inhibition accounts for key aspects of orientation selectivity in V1. NETWORK (BRISTOL, ENGLAND) 2014; 25:63-71. [PMID: 24571098 PMCID: PMC4243463 DOI: 10.3109/0954898x.2013.877611] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
There is now strong evidence that gamma frequency oscillations occur during the engagement of cortical regions. These oscillations involve gamma frequency feedback inhibition. Thus, understanding the properties of this form of inhibition is critical to understanding how excitation and inhibition interact to determine which cells fire and, more generally, how cortex performs computations. In previous work, we argued that gamma frequency inhibition performs a type of winner-take-all computation that obeys simple rules: 1) cells fire if their excitation is within E% of the cell with maximum excitation; 2) E%max is determined by the delay of feedback inhibition and the membrane time constant. This framework was previously applied to the best-studied cortical computation, orientation selectivity of cells in V1. Measurements show that orientation tuning is insensitive to illumination contrast. We showed that this finding can be simply explained by the E%max model. Recently, a new property of orientation selectivity has been discovered: orientation tuning varies with the phase of the gamma oscillation. Here, we show that this too can be simply explained by the E%max model. These successes suggest that simple rules underlie the selection of which cells fire in cortical networks.
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Affiliation(s)
- John Lisman
- Brandeis University, Biology Department & Volen Center for Complex Systems, 415 South Street-MS 008, Waltham, MA 02454-9110, 781-736-3145
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110
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Hirabayashi T, Miyashita Y. Computational principles of microcircuits for visual object processing in the macaque temporal cortex. Trends Neurosci 2014; 37:178-87. [DOI: 10.1016/j.tins.2014.01.002] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2013] [Revised: 01/03/2014] [Accepted: 01/06/2014] [Indexed: 01/04/2023]
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111
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Chizhov AV, Smirnova EY, Kim KK, Zaitsev AV. A simple Markov model of sodium channels with a dynamic threshold. J Comput Neurosci 2014; 37:181-91. [PMID: 24469252 DOI: 10.1007/s10827-014-0496-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2013] [Revised: 12/15/2013] [Accepted: 01/16/2014] [Indexed: 11/27/2022]
Abstract
Characteristics of action potential generation are important to understanding brain functioning and, thus, must be understood and modeled. It is still an open question what model can describe concurrently the phenomena of sharp spike shape, the spike threshold variability, and the divisive effect of shunting on the gain of frequency-current dependence. We reproduced these three effects experimentally by patch-clamp recordings in cortical slices, but we failed to simulate them by any of 11 known neuron models, including one- and multi-compartment, with Hodgkin-Huxley and Markov equation-based sodium channel approximations, and those taking into account sodium channel subtype heterogeneity. Basing on our voltage-clamp data characterizing the dependence of sodium channel activation threshold on history of depolarization, we propose a 3-state Markov model with a closed-to-open state transition threshold dependent on slow inactivation. This model reproduces the all three phenomena. As a reduction of this model, a leaky integrate-and-fire model with a dynamic threshold also shows the effect of gain reduction by shunt. These results argue for the mechanism of gain reduction through threshold dynamics determined by the slow inactivation of sodium channels.
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Affiliation(s)
- A V Chizhov
- A.F. Ioffe Physical-Technical Institute of the Russian Academy of Sciences, Politekhnicheskaya str., 26, 194021, Saint-Petersburg, Russia,
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112
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Functional coupling from simple to complex cells in the visually driven cortical circuit. J Neurosci 2014; 33:18855-66. [PMID: 24285892 DOI: 10.1523/jneurosci.2665-13.2013] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
In the classic model of the primary visual cortex, upper-layer complex cells are driven by feedforward inputs from layer 4 simple cells. Based on spike cross-correlation, previous in vivo work has suggested that this connection is strong and dense, with a high probability of connection (50%) and significant strength in connected pairs. A much sparser projection has been found in brain slices, however, with the probability of layer 4 cells connecting to layer 2/3 cells being relatively low (10%). Here, we explore this connection in vivo in the cat primary visual cortex by recording simultaneously spikes of layer 4 simple cells and the membrane potential (V(m)) of layer 2/3 complex cells. By triggering the average of the complex cell's V(m) on the spikes of the simple cell (V(m)-STA), we found functional coupling to be very common during visual stimulation: the simple cell's spikes tended to occur near the troughs of the complex cell's V(m) fluctuations and were, on average, followed by a significant (~1 mV) fast-rising (10 ms) depolarization in the complex cell. In the absence of visual stimulation, however, when single simple cells were activated electrically through the recording electrode, no significant depolarization, or at most a very weak input (0.1-0.2 mV), was detected in the complex cell. We suggest that the functional coupling observed during visual stimulation arises from coordinated or nearly synchronous activity among a large population of simple cells, only a small fraction of which are presynaptic to the recorded complex cell.
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113
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Ramachandra CA, Mel BW. Computing local edge probability in natural scenes from a population of oriented simple cells. J Vis 2013; 13:13.14.19. [PMID: 24381295 DOI: 10.1167/13.14.19] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
A key computation in visual cortex is the extraction of object contours, where the first stage of processing is commonly attributed to V1 simple cells. The standard model of a simple cell-an oriented linear filter followed by a divisive normalization-fits a wide variety of physiological data, but is a poor performing local edge detector when applied to natural images. The brain's ability to finely discriminate edges from nonedges therefore likely depends on information encoded by local simple cell populations. To gain insight into the corresponding decoding problem, we used Bayes's rule to calculate edge probability at a given location/orientation in an image based on a surrounding filter population. Beginning with a set of ∼ 100 filters, we culled out a subset that were maximally informative about edges, and minimally correlated to allow factorization of the joint on- and off-edge likelihood functions. Key features of our approach include a new, efficient method for ground-truth edge labeling, an emphasis on achieving filter independence, including a focus on filters in the region orthogonal rather than tangential to an edge, and the use of a customized parametric model to represent the individual filter likelihood functions. The resulting population-based edge detector has zero parameters, calculates edge probability based on a sum of surrounding filter influences, is much more sharply tuned than the underlying linear filters, and effectively captures fine-scale edge structure in natural scenes. Our findings predict nonmonotonic interactions between cells in visual cortex, wherein a cell may for certain stimuli excite and for other stimuli inhibit the same neighboring cell, depending on the two cells' relative offsets in position and orientation, and their relative activation levels.
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114
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Sublinear binocular integration preserves orientation selectivity in mouse visual cortex. Nat Commun 2013; 4:2088. [PMID: 23800837 PMCID: PMC3703862 DOI: 10.1038/ncomms3088] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2013] [Accepted: 05/29/2013] [Indexed: 02/07/2023] Open
Abstract
Inputs from the two eyes are first combined in simple cells in the primary visual cortex. Consequently, visual cortical neurons need to have the flexibility to encode visual features under both monocular and binocular situations. Here we show that binocular orientation selectivity of mouse simple cells is nearly identical to monocular orientation selectivity in both anaesthetized and awake conditions. In vivo whole-cell recordings reveal that the binocular integration of membrane potential responses is sublinear. The sublinear integration keeps binocularly evoked depolarizations below threshold at non-preferred orientations, thus preserving orientation selectivity. Computational simulations based on measured synaptic conductances indicate that inhibition promotes sublinear binocular integration, which are further confirmed by experiments using genetic and pharmacological manipulations. Our findings therefore reveal a cellular mechanism for how visual system can switch effortlessly between monocular and binocular conditions. The same mechanism may apply to other sensory systems that also integrate multiple channels of inputs.
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115
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Seelig JD, Jayaraman V. Feature detection and orientation tuning in the Drosophila central complex. Nature 2013; 503:262-6. [PMID: 24107996 PMCID: PMC3830704 DOI: 10.1038/nature12601] [Citation(s) in RCA: 195] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2013] [Accepted: 08/22/2013] [Indexed: 12/11/2022]
Abstract
Many animals, including insects, are known to use visual landmarks to orient in their environment. In Drosophila melanogaster, behavioural genetics studies have identified a higher brain structure called the central complex as being required for the fly's innate responses to vertical visual features and its short- and long-term memory for visual patterns. But whether and how neurons of the fly central complex represent visual features are unknown. Here we use two-photon calcium imaging in head-fixed walking and flying flies to probe visuomotor responses of ring neurons--a class of central complex neurons that have been implicated in landmark-driven spatial memory in walking flies and memory for visual patterns in tethered flying flies. We show that dendrites of ring neurons are visually responsive and arranged retinotopically. Ring neuron receptive fields comprise both excitatory and inhibitory subfields, resembling those of simple cells in the mammalian primary visual cortex. Ring neurons show strong and, in some cases, direction-selective orientation tuning, with a notable preference for vertically oriented features similar to those that evoke innate responses in flies. Visual responses were diminished during flight, but, in contrast with the hypothesized role of the central complex in the control of locomotion, not modulated during walking. Taken together, these results indicate that ring neurons represent behaviourally relevant visual features in the fly's environment, enabling downstream central complex circuits to produce appropriate motor commands. More broadly, this study opens the door to mechanistic investigations of circuit computations underlying visually guided action selection in the Drosophila central complex.
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Affiliation(s)
- Johannes D Seelig
- Janelia Farm Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, Virginia 20147, USA
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116
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Kaschube M. Neural maps versus salt-and-pepper organization in visual cortex. Curr Opin Neurobiol 2013; 24:95-102. [PMID: 24492085 DOI: 10.1016/j.conb.2013.08.017] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2013] [Revised: 08/19/2013] [Accepted: 08/24/2013] [Indexed: 10/26/2022]
Abstract
Theoretical neuroscientists have long been intrigued by the spatial patterns of neuronal selectivities observed in the visual cortices of many mammals, including primates. While theoretical studies have contributed significantly to our understanding of how the brain learns to see, recent experimental discoveries of the spatial irregularity of visual response properties in the rodent visual cortex have prompted new questions about the origin and functional significance of cortical maps. Characterizing the marked differences of cortical design principles among species and comparing them may provide us with a deeper understanding of primate and non-primate vision.
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Affiliation(s)
- Matthias Kaschube
- Frankfurt Institute for Advanced Studies, Faculty of Computer Science and Mathematics, Goethe University, Frankfurt am Main, Germany.
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117
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Zhu M, Rozell CJ. Visual nonclassical receptive field effects emerge from sparse coding in a dynamical system. PLoS Comput Biol 2013; 9:e1003191. [PMID: 24009491 PMCID: PMC3757072 DOI: 10.1371/journal.pcbi.1003191] [Citation(s) in RCA: 55] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2012] [Accepted: 05/31/2013] [Indexed: 11/25/2022] Open
Abstract
Extensive electrophysiology studies have shown that many V1 simple cells have nonlinear response properties to stimuli within their classical receptive field (CRF) and receive contextual influence from stimuli outside the CRF modulating the cell's response. Models seeking to explain these non-classical receptive field (nCRF) effects in terms of circuit mechanisms, input-output descriptions, or individual visual tasks provide limited insight into the functional significance of these response properties, because they do not connect the full range of nCRF effects to optimal sensory coding strategies. The (population) sparse coding hypothesis conjectures an optimal sensory coding approach where a neural population uses as few active units as possible to represent a stimulus. We demonstrate that a wide variety of nCRF effects are emergent properties of a single sparse coding model implemented in a neurally plausible network structure (requiring no parameter tuning to produce different effects). Specifically, we replicate a wide variety of nCRF electrophysiology experiments (e.g., end-stopping, surround suppression, contrast invariance of orientation tuning, cross-orientation suppression, etc.) on a dynamical system implementing sparse coding, showing that this model produces individual units that reproduce the canonical nCRF effects. Furthermore, when the population diversity of an nCRF effect has also been reported in the literature, we show that this model produces many of the same population characteristics. These results show that the sparse coding hypothesis, when coupled with a biophysically plausible implementation, can provide a unified high-level functional interpretation to many response properties that have generally been viewed through distinct mechanistic or phenomenological models. Simple cells in the primary visual cortex (V1) demonstrate many response properties that are either nonlinear or involve response modulations (i.e., stimuli that do not cause a response in isolation alter the cell's response to other stimuli). These non-classical receptive field (nCRF) effects are generally modeled individually and their collective role in biological vision is not well understood. Previous work has shown that classical receptive field (CRF) properties of V1 cells (i.e., the spatial structure of the visual field responsive to stimuli) could be explained by the sparse coding hypothesis, which is an optimal coding model that conjectures a neural population should use the fewest number of cells simultaneously to represent each stimulus. In this paper, we have performed extensive simulated physiology experiments to show that many nCRF response properties are simply emergent effects of a dynamical system implementing this same sparse coding model. These results suggest that rather than representing disparate information processing operations themselves, these nCRF effects could be consequences of an optimal sensory coding strategy that attempts to represent each stimulus most efficiently. This interpretation provides a potentially unifying high-level functional interpretation to many response properties that have generally been viewed through distinct models.
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Affiliation(s)
- Mengchen Zhu
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America
| | - Christopher J. Rozell
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America
- * E-mail:
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118
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Hunter PR, Lowe AS, Thompson ID, Meyer MP. Emergent properties of the optic tectum revealed by population analysis of direction and orientation selectivity. J Neurosci 2013; 33:13940-5. [PMID: 23986231 PMCID: PMC3756745 DOI: 10.1523/jneurosci.1493-13.2013] [Citation(s) in RCA: 54] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2013] [Revised: 06/27/2013] [Accepted: 07/04/2013] [Indexed: 11/21/2022] Open
Abstract
How local circuits within the brain process visual information has classically been addressed at the single neuron level. Such reductionist approaches, however, struggle to capture the full scope of functional properties associated with even "simple" brain nuclei. Using population functional calcium imaging, we aim to describe how local circuits within the zebrafish optic tectum process visual information. Specifically, how are previously identified direction-selective (DS) and orientation-selective (OS) retinal ganglion cell (RGC) inputs (Nikolaou et al., 2012) represented in tectal cells? First, we identify an emergent population of DS tectal cell with a direction preference not explicitly present in any one of the RGC inputs. Second, this is associated with a striking shift from a tiled and triangular representation of directional space (RGC inputs) into an overlapping cardinal representation by tectal cell populations. Third, and in contrast, we find that orientation space is represented similarly in both the RGC input and tectal cell populations illustrating feature-dependent differences in how tectal circuits process their inputs. Finally, we identify OS and two populations of DS cells at the superficial border of the tectal neuropil, one of which is an emergent population. This study, together with our previous one (Nikolaou et al., 2012), demonstrate that direction-selectivity is established in both the retina and tectum.
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Affiliation(s)
- Paul R Hunter
- MRC Centre for Developmental Neurobiology, King's College London, Guy's Hospital Campus, London SE1 1UL, United Kingdom
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119
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Abstract
Many animals use visual motion cues for navigating within their surroundings. Both flies and vertebrates compute local motion by temporal correlation of neighboring photoreceptors, via so-called elementary motion detectors (EMDs). In the fly lobula plate and the vertebrate visual cortex the output from many EMDs is pooled in neurons sensitive to wide-field optic flow. Although the EMD has been the preferred model for more than 50 years, recent work has highlighted its limitations in describing some visual behaviors, such as responses to higher-order motion stimuli. Non-EMD motion processing may therefore serve an important function in vision. Here, we describe a novel neuron class in the fly lobula plate that clearly does not derive its input from classic EMDs. The centrifugal stationary inhibited flicker excited (cSIFE) neuron is strongly excited by flicker, up to very high temporal frequencies. The non-EMD driven flicker sensitivity leads to strong, nondirectional responses to high-speed, wide-field motion. Furthermore, cSIFE is strongly inhibited by stationary patterns, within a narrow wavelength band. cSIFE's outputs overlap with the inputs of well described optic flow-sensitive lobula plate tangential cells (LPTCs). Driving cSIFE affects the active dendrites of LPTCs, and cSIFE may therefore play a large role in motion vision.
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120
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Reitsma DC, Mathis J, Ulmer JL, Mueller W, Maciejewski MJ, DeYoe EA. Atypical retinotopic organization of visual cortex in patients with central brain damage: congenital and adult onset. J Neurosci 2013; 33:13010-24. [PMID: 23926256 PMCID: PMC3735882 DOI: 10.1523/jneurosci.0240-13.2013] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2013] [Revised: 06/07/2013] [Accepted: 06/20/2013] [Indexed: 11/21/2022] Open
Abstract
It remains unclear to what extent retinotopic maps can undergo large-scale plasticity following damage to human visual cortex. The literature has predominately focused on retinotopic changes in patients with retinal pathologies or congenital brain malformations. Yet, damage to the adult visual cortex itself is common in cases such as stroke, tumor, or trauma. To address this issue, we used a unique database of fMRI vision maps in patients with adult-onset (n=25) and congenital (n=2) pathology of the visual cortex. We identified atypical retinotopic organization in three patients (two with adult-onset, and one with congenital pathology) consisting of an expanded ipsilateral field representation that was on average 3.2 times greater than healthy controls. The expanded representations were located at the vertical meridian borders between visual areas such as V1/V2. Additionally, two of the three patients had apparently an ectopic (topographically inconsistent) representation of the ipsilateral field within lateral occipital cortex that is normally associated with visual areas V3/V3A (and possibly other areas). Both adult-onset cases had direct damage to early visual cortex itself (rather than to the afferent drive only), resulting in a mostly nonfunctional hemisphere. The congenital case had severe cortical malformation of the visual cortex and was acallosal. Our results are consistent with a competitive model in which unilateral damage to visual cortex or disruption of the transcallosal connections removes interhemispheric suppression from retino-geniculate afferents in intact visual cortex that represent the vertical meridian and ipsilateral visual field.
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121
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Hirabayashi T, Takeuchi D, Tamura K, Miyashita Y. Microcircuits for Hierarchical Elaboration of Object Coding Across Primate Temporal Areas. Science 2013; 341:191-5. [DOI: 10.1126/science.1236927] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
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122
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Cang J, Feldheim DA. Developmental mechanisms of topographic map formation and alignment. Annu Rev Neurosci 2013; 36:51-77. [PMID: 23642132 DOI: 10.1146/annurev-neuro-062012-170341] [Citation(s) in RCA: 163] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Brain connections are organized into topographic maps that are precisely aligned both within and across modalities. This alignment facilitates coherent integration of different categories of sensory inputs and allows for proper sensorimotor transformations. Topographic maps are established and aligned by multistep processes during development, including interactions of molecular guidance cues expressed in gradients; spontaneous activity-dependent axonal and dendritic remodeling; and sensory-evoked plasticity driven by experience. By focusing on the superior colliculus, a major site of topographic map alignment for different sensory modalities, this review summarizes current understanding of topographic map development in the mammalian visual system and highlights recent advances in map alignment studies. A major goal looking forward is to reveal the molecular and synaptic mechanisms underlying map alignment and to understand the physiological and behavioral consequences when these mechanisms are disrupted at various scales.
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Affiliation(s)
- Jianhua Cang
- Department of Neurobiology, Northwestern University, Evanston, IL 60208, USA.
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123
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Clemens J, Hennig RM. Computational principles underlying the recognition of acoustic signals in insects. J Comput Neurosci 2013; 35:75-85. [PMID: 23417450 DOI: 10.1007/s10827-013-0441-0] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2012] [Revised: 01/14/2013] [Accepted: 01/15/2013] [Indexed: 10/27/2022]
Abstract
Many animals produce pulse-like signals during acoustic communication. These signals exhibit structure on two time scales: they consist of trains of pulses that are often broadcast in packets-so called chirps. Temporal parameters of the pulse and of the chirp are decisive for female preference. Despite these signals being produced by animals from many different taxa (e.g. frogs, grasshoppers, crickets, bushcrickets, flies), a general framework for their evaluation is still lacking. We propose such a framework, based on a simple and physiologically plausible model. The model consists of feature detectors, whose time-varying output is averaged over the signal and then linearly combined to yield the behavioral preference. We fitted this model to large data sets collected in two species of crickets and found that Gabor filters--known from visual and auditory physiology--explain the preference functions in these two species very well. We further explored the properties of Gabor filters and found a systematic relationship between parameters of the filters and the shape of preference functions. Although these Gabor filters were relatively short, they were also able to explain aspects of the preference for signal parameters on the longer time scale due to the integration step in our model. Our framework explains a wide range of phenomena associated with female preference for a widespread class of signals in an intuitive and physiologically plausible fashion. This approach thus constitutes a valuable tool to understand the functioning and evolution of communication systems in many species.
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Affiliation(s)
- Jan Clemens
- Behavioral Physiology Group, Department of Biology, Humboldt-Universität zu Berlin, 10115 Berlin, Germany.
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124
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Phase sensitivity of complex cells in primary visual cortex. Neuroscience 2013; 237:19-28. [PMID: 23357120 DOI: 10.1016/j.neuroscience.2013.01.030] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2012] [Revised: 12/13/2012] [Accepted: 01/07/2013] [Indexed: 11/20/2022]
Abstract
Neurons in the primary visual cortex are often classified as either simple or complex based on the linearity (or otherwise) of their response to spatial luminance contrast. In practice, classification is typically based on Fourier analysis of a cell's response to an optimal drifting sine-wave grating. Simple cells are generally considered to be linear and produce responses modulated at the fundamental frequency of the stimulus grating. In contrast, complex cells exhibit significant nonlinearities that reduce the response at the fundamental frequency. Cells can therefore be easily and objectively classified based on the relative modulation of their responses - the ratio of the phase-sensitive response at the fundamental frequency of the stimulus (F₁) to the phase-invariant sustained response (F₀). Cells are classified as simple if F₁/F₀>1 and complex if F₁/F₀<1. This classification is broadly consistent with criteria based on the spatial organisation of cells' receptive fields and is accordingly presumed to reflect disparate functional roles of simple and complex cells in coding visual information. However, Fourier analysis of spiking responses is sensitive to the number of spikes available - F₁/F₀ increases as the number of spikes is reduced, even for phase-invariant complex cells. Moreover, many complex cells encountered in the laboratory exhibit some phase sensitivity, evident as modulation of their responses at the fundamental frequency. There currently exists no objective quantitative means of assessing the significance or otherwise of these modulations. Here we derive a statistical basis for objectively assessing whether the modulation of neuronal responses is reliable, thereby adding a level of statistical certainty to measures of phase sensitivity. We apply our statistical analysis to neuronal responses to moving sine-wave gratings recorded from 367 cells in cat primary visual cortex. We find that approximately 60% of complex cells exhibit statistically significant (α<0.01) modulation of their responses to optimal moving gratings. These complex cells are phase sensitive and reliably encode spatial phase.
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125
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Espinosa JS, Stryker MP. Development and plasticity of the primary visual cortex. Neuron 2012; 75:230-49. [PMID: 22841309 DOI: 10.1016/j.neuron.2012.06.009] [Citation(s) in RCA: 445] [Impact Index Per Article: 37.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/18/2012] [Indexed: 01/17/2023]
Abstract
Hubel and Wiesel began the modern study of development and plasticity of primary visual cortex (V1), discovering response properties of cortical neurons that distinguished them from their inputs and that were arranged in a functional architecture. Their findings revealed an early innate period of development and a later critical period of dramatic experience-dependent plasticity. Recent studies have used rodents to benefit from biochemistry and genetics. The roles of spontaneous neural activity and molecular signaling in innate, experience-independent development have been clarified, as have the later roles of visual experience. Plasticity produced by monocular visual deprivation (MD) has been dissected into stages governed by distinct signaling mechanisms, some of whose molecular players are known. Many crucial questions remain, but new tools for perturbing cortical cells and measuring plasticity at the level of changes in connections among identified neurons now exist. The future for the study of V1 to illuminate cortical development and plasticity is bright.
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Affiliation(s)
- J Sebastian Espinosa
- Center for Integrative Neuroscience, Department of Physiology, 675 Nelson Rising Lane, University of California, San Francisco, San Francisco, CA 94143-0444, USA
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126
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Abstract
The visual cortex has the capacity for experience-dependent change, or cortical plasticity, that is retained throughout life. Plasticity is invoked for encoding information during perceptual learning, by internally representing the regularities of the visual environment, which is useful for facilitating intermediate-level vision--contour integration and surface segmentation. The same mechanisms have adaptive value for functional recovery after CNS damage, such as that associated with stroke or neurodegenerative disease. A common feature to plasticity in primary visual cortex (V1) is an association field that links contour elements across the visual field. The circuitry underlying the association field includes a plexus of long-range horizontal connections formed by cortical pyramidal cells. These connections undergo rapid and exuberant sprouting and pruning in response to removal of sensory input, which can account for the topographic reorganization following retinal lesions. Similar alterations in cortical circuitry may be involved in perceptual learning, and the changes observed in V1 may be representative of how learned information is encoded throughout the cerebral cortex.
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127
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Abstract
"Receptive Fields, Binocular Interaction and Functional Architecture in the Cat's Visual Cortex" by Hubel and Wiesel (1962) reported several important discoveries: orientation columns, the distinct structures of simple and complex receptive fields, and binocular integration. But perhaps the paper's greatest influence came from the concept of functional architecture (the complex relationship between in vivo physiology and the spatial arrangement of neurons) and several models of functionally specific connectivity. They thus identified two distinct concepts, topographic specificity and functional specificity, which together with cell-type specificity constitute the major determinants of nonrandom cortical connectivity. Orientation columns are iconic examples of topographic specificity, whereby axons within a column connect with cells of a single orientation preference. Hubel and Wiesel also saw the need for functional specificity at a finer scale in their model of thalamic inputs to simple cells, verified in the 1990s. The difficult but potentially more important question of functional specificity between cortical neurons is only now becoming tractable with new experimental techniques.
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Affiliation(s)
- R Clay Reid
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02138, USA.
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