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1.  A mammalian retinal bipolar cell uses both graded changes in membrane voltage and all-or-nothing Na+ spikes to encode light 
Barlow studied summation in ganglion cell receptive fields and observed a fine discrimination of spatial information from which he inferred that retinal interneurons use analog signals to process images. Subsequent intracellular recordings confirmed that the interneurons of the outer retina, including photoreceptors, horizontal cells, and bipolar cells, respond to light with slow, graded changes in membrane potential. Analog processing may enable interneurons to discriminate fine gradations in light intensity and spatiotemporal pattern, but at the expense of the speed, temporal precision, and threshold discrimination that are characteristic of all-or-nothing Na+ spikes. We show that one type of mammalian On bipolar cell, the ground squirrel cb5b, has a large tetrodotoxin (TTX)-sensitive Na+ current. When recorded from in the perforated patch configuration, cb5b cells can signal the onset of a light step with 1–3 all-or-nothing action potentials that attain a peak amplitude of −10 to −20 mV (peak width at half-height equals 2 – 3 ms). When exposed to a continuous, temporally fluctuating stimulus, cb5b generate both graded and spiking responses. cb5b cells spike with millisecond precision, selecting for stimulus sequences in which transitions to light are preceded by a period of darkness. The axon terminals of cb5b bipolar cells co-stratify with the dendrites of amacrine and ganglion cells that encode light onset with a short latency burst of spikes. The results support the idea that a spiking On bipolar cell is part of a dedicated retinal pathway for rapidly and reliably signaling dark to light transitions.
doi:10.1523/JNEUROSCI.2739-08.2012
PMCID: PMC3503151  PMID: 22219291
Retina; Vision; Action Potential; Retinal bipolar cell; Sodium channel; Retinal ganglion cell
2.  Computing Complex Visual Features with Retinal Spike Times 
PLoS ONE  2013;8(1):e53063.
Neurons in sensory systems can represent information not only by their firing rate, but also by the precise timing of individual spikes. For example, certain retinal ganglion cells, first identified in the salamander, encode the spatial structure of a new image by their first-spike latencies. Here we explore how this temporal code can be used by downstream neural circuits for computing complex features of the image that are not available from the signals of individual ganglion cells. To this end, we feed the experimentally observed spike trains from a population of retinal ganglion cells to an integrate-and-fire model of post-synaptic integration. The synaptic weights of this integration are tuned according to the recently introduced tempotron learning rule. We find that this model neuron can perform complex visual detection tasks in a single synaptic stage that would require multiple stages for neurons operating instead on neural spike counts. Furthermore, the model computes rapidly, using only a single spike per afferent, and can signal its decision in turn by just a single spike. Extending these analyses to large ensembles of simulated retinal signals, we show that the model can detect the orientation of a visual pattern independent of its phase, an operation thought to be one of the primitives in early visual processing. We analyze how these computations work and compare the performance of this model to other schemes for reading out spike-timing information. These results demonstrate that the retina formats spatial information into temporal spike sequences in a way that favors computation in the time domain. Moreover, complex image analysis can be achieved already by a simple integrate-and-fire model neuron, emphasizing the power and plausibility of rapid neural computing with spike times.
doi:10.1371/journal.pone.0053063
PMCID: PMC3534662  PMID: 23301021
3.  Preserving information in neural transmission 
Along most neural pathways, the spike trains transmitted from one neuron to the next are altered. In the process, neurons can either achieve a more efficient stimulus representation, or extract some biologically important stimulus parameter, or succeed at both. We recorded the inputs from single retinal ganglion cells and the outputs from connected lateral geniculate neurons in the macaque to examine how visual signals are relayed from retina to cortex. We found that geniculate neurons re-encoded multiple temporal stimulus features to yield output spikes that carried more information about stimuli than was available in each input spike. The coding transformation of some relay neurons occurred with no decrement in information rate, despite output spike rates that averaged half the input spike rates. This preservation of transmitted information was achieved by the short-term summation of inputs that geniculate neurons require to spike. A reduced model of the retinal and geniculate visual responses, based on two stimulus features and their associated nonlinearities, could account for more than 85% of the total information available in the spike trains and the preserved information transmission. These results apply to neurons operating on a single time-varying input, suggesting that synaptic temporal integration can alter the temporal receptive field properties to create a more efficient representation of visual signals in the thalamus than the retina.
doi:10.1523/JNEUROSCI.3701-08.2009
PMCID: PMC2761742  PMID: 19439598
neural coding; synaptic transmission; retinal ganglion cell; information theory; receptive field center; macaque
4.  Retinal Ganglion Cells Can Rapidly Change Polarity from Off to On  
PLoS Biology  2007;5(3):e65.
Retinal ganglion cells are commonly classified as On-center or Off-center depending on whether they are excited predominantly by brightening or dimming within the receptive field. Here we report that many ganglion cells in the salamander retina can switch from one response type to the other, depending on stimulus events far from the receptive field. Specifically, a shift of the peripheral image—as produced by a rapid eye movement—causes a brief transition in visual sensitivity from Off-type to On-type for approximately 100 ms. We show that these ganglion cells receive inputs from both On and Off bipolar cells, and the Off inputs are normally dominant. The peripheral shift strongly modulates the strength of these two inputs in opposite directions, facilitating the On pathway and suppressing the Off pathway. Furthermore, we identify certain wide-field amacrine cells that contribute to this modulation. Depolarizing such an amacrine cell affects nearby ganglion cells in the same way as the peripheral image shift, facilitating the On inputs and suppressing the Off inputs. This study illustrates how inhibitory interneurons can rapidly gate the flow of information within a circuit, dramatically altering the behavior of the principal neurons in the course of a computation.
Author Summary
The eye communicates to the brain all the information needed for vision in the form of electrical pulses, or spikes, on optic nerve fibers. These spikes are produced by retinal ganglion cells, the output neurons of the retina. In a popular view of retinal function, each ganglion cell responds to a small region of interest in the visual image, known as its receptive field, and is specialized for certain image features within that window. When a cell encounters that image feature, the neuron responds by firing one or more spikes. Different neurons are tuned to different features. For example, some ganglion cells fire when light dims, others when it brightens. Here we show that a rapid shift in the image on the retina can cause a dramatic change in a neuron's preferred feature: For example, a dimming-detector can briefly turn into a brightening-detector. We explore the mechanisms that implement such a switch of feature tuning, and the consequences it might have for visual processing.
A peripheral image shift produces a transient switch in retinal ganglion cell responses from Off-dominated to On-dominated. This modulation is exerted at least in part presynaptically, presumably at the bipolar cell synaptic terminal.
doi:10.1371/journal.pbio.0050065
PMCID: PMC1808116  PMID: 17341132
5.  Network Variability Limits Stimulus-Evoked Spike Timing Precision in Retinal Ganglion Cells 
Neuron  2006;52(3):511-524.
Visual, auditory, somatosensory, and olfactory stimuli generate temporally precise patterns of action potentials (spikes). It is unclear, however, how the pattern and variability of synaptic input elicited by physiological stimuli governs the precision of spike generation. We determined how synaptic conductances evoked by light stimuli that activate the rod bipolar pathway control spike generation in three identified types of mouse retinal ganglion cells (RGCs). The relative amplitude, timing, and impact of excitatory and inhibitory input differed dramatically in On and Off RGCs. In each RGC type, however, the precision of light-evoked spikes was similar to that of spikes generated by somatic injection of measured light-evoked synaptic conductances that varied from trial to trial but less than that of spikes evoked by invariant synaptic conductances. Thus the rod bipolar pathway modulates different RGCs via unique combinations of synaptic input, and RGC temporal variability reflects variability in the input this circuit provides.
doi:10.1016/j.neuron.2006.09.014
PMCID: PMC2032021  PMID: 17088216
6.  Olfactory Stimulation Selectively Modulates the OFF Pathway in the Retina of Zebrafish 
Neuron  2013;79(1):97-110.
Summary
Cross-modal regulation of visual performance by olfactory stimuli begins in the retina, where dopaminergic interneurons receive projections from the olfactory bulb. However, we do not understand how olfactory stimuli alter the processing of visual signals within the retina. We investigated this question by in vivo imaging activity in transgenic zebrafish expressing SyGCaMP2 in bipolar cell terminals and GCaMP3.5 in ganglion cells. The food-related amino acid methionine reduced the gain and increased sensitivity of responses to luminance and contrast transmitted through OFF bipolar cells but not ON. The effects of olfactory stimulus were blocked by inhibiting dopamine uptake and release. Activation of dopamine receptors increased the gain of synaptic transmission in vivo and potentiated synaptic calcium currents in isolated bipolar cells. These results indicate that olfactory stimuli alter the sensitivity of the retina through the dopaminergic regulation of presynaptic calcium channels that control the gain of synaptic transmission through OFF bipolar cells.
Highlights
•Olfactory stimuli regulate transmission of signals through retinal bipolar cells•Modulation of synaptic gain and sensitivity occur in OFF bipolar cells but not ON•An inhibitor of dopamine uptake blocks odor-induced changes in synaptic gain•Dopamine potentiates presynaptic calcium channels in isolated bipolar cells
Esposti et al. show that olfactory stimulation selectively modulates synaptic transmission from retinal OFF bipolar cells in zebrafish. Dopamine plays a key role in this cross modal interaction by acting on the presynaptic calcium channels.
doi:10.1016/j.neuron.2013.05.001
PMCID: PMC3710973  PMID: 23849198
7.  Spectral Analysis of Input Spike Trains by Spike-Timing-Dependent Plasticity 
PLoS Computational Biology  2012;8(7):e1002584.
Spike-timing-dependent plasticity (STDP) has been observed in many brain areas such as sensory cortices, where it is hypothesized to structure synaptic connections between neurons. Previous studies have demonstrated how STDP can capture spiking information at short timescales using specific input configurations, such as coincident spiking, spike patterns and oscillatory spike trains. However, the corresponding computation in the case of arbitrary input signals is still unclear. This paper provides an overarching picture of the algorithm inherent to STDP, tying together many previous results for commonly used models of pairwise STDP. For a single neuron with plastic excitatory synapses, we show how STDP performs a spectral analysis on the temporal cross-correlograms between its afferent spike trains. The postsynaptic responses and STDP learning window determine kernel functions that specify how the neuron “sees” the input correlations. We thus denote this unsupervised learning scheme as ‘kernel spectral component analysis’ (kSCA). In particular, the whole input correlation structure must be considered since all plastic synapses compete with each other. We find that kSCA is enhanced when weight-dependent STDP induces gradual synaptic competition. For a spiking neuron with a “linear” response and pairwise STDP alone, we find that kSCA resembles principal component analysis (PCA). However, plain STDP does not isolate correlation sources in general, e.g., when they are mixed among the input spike trains. In other words, it does not perform independent component analysis (ICA). Tuning the neuron to a single correlation source can be achieved when STDP is paired with a homeostatic mechanism that reinforces the competition between synaptic inputs. Our results suggest that neuronal networks equipped with STDP can process signals encoded in the transient spiking activity at the timescales of tens of milliseconds for usual STDP.
Author Summary
Tuning feature extraction of sensory stimuli is an important function for synaptic plasticity models. A widely studied example is the development of orientation preference in the primary visual cortex, which can emerge using moving bars in the visual field. A crucial point is the decomposition of stimuli into basic information tokens, e.g., selecting individual bars even though they are presented in overlapping pairs (vertical and horizontal). Among classical unsupervised learning models, independent component analysis (ICA) is capable of isolating basic tokens, whereas principal component analysis (PCA) cannot. This paper focuses on spike-timing-dependent plasticity (STDP), whose functional implications for neural information processing have been intensively studied both theoretically and experimentally in the last decade. Following recent studies demonstrating that STDP can perform ICA for specific cases, we show how STDP relates to PCA or ICA, and in particular explains the conditions under which it switches between them. Here information at the neuronal level is assumed to be encoded in temporal cross-correlograms of spike trains. We find that a linear spiking neuron equipped with pairwise STDP requires additional mechanisms, such as a homeostatic regulation of its output firing, in order to separate mixed correlation sources and thus perform ICA.
doi:10.1371/journal.pcbi.1002584
PMCID: PMC3390410  PMID: 22792056
8.  Analysis of Slow (Theta) Oscillations as a Potential Temporal Reference Frame for Information Coding in Sensory Cortices 
PLoS Computational Biology  2012;8(10):e1002717.
While sensory neurons carry behaviorally relevant information in responses that often extend over hundreds of milliseconds, the key units of neural information likely consist of much shorter and temporally precise spike patterns. The mechanisms and temporal reference frames by which sensory networks partition responses into these shorter units of information remain unknown. One hypothesis holds that slow oscillations provide a network-intrinsic reference to temporally partitioned spike trains without exploiting the millisecond-precise alignment of spikes to sensory stimuli. We tested this hypothesis on neural responses recorded in visual and auditory cortices of macaque monkeys in response to natural stimuli. Comparing different schemes for response partitioning revealed that theta band oscillations provide a temporal reference that permits extracting significantly more information than can be obtained from spike counts, and sometimes almost as much information as obtained by partitioning spike trains using precisely stimulus-locked time bins. We further tested the robustness of these partitioning schemes to temporal uncertainty in the decoding process and to noise in the sensory input. This revealed that partitioning using an oscillatory reference provides greater robustness than partitioning using precisely stimulus-locked time bins. Overall, these results provide a computational proof of concept for the hypothesis that slow rhythmic network activity may serve as internal reference frame for information coding in sensory cortices and they foster the notion that slow oscillations serve as key elements for the computations underlying perception.
Author Summary
Neurons in sensory cortices encode objects in our sensory environment by varying the timing and number of action potentials that they emit. Brain networks that ‘decode’ this information need to partition those spike trains into their individual informative units. Experimenters achieve such partitioning by exploiting their knowledge about the millisecond precise timing of individual spikes relative to externally presented sensory stimuli. The brain, however, does not have access to this information and has to partition and decode spike trains using intrinsically available temporal reference frames. We show that slow (4–8 Hz) oscillatory network activity can provide such an intrinsic temporal reference. Specifically, we analyzed neural responses recorded in primary auditory and visual cortices. This revealed that the oscillatory reference frame performs nearly as well as the precise stimulus-locked reference frame and renders neural encoding robust to sensory noise and temporal uncertainty that naturally occurs during decoding. These findings provide a computational proof-of-concept that slow oscillatory network activity may serve the crucial function as temporal reference frame for sensory coding.
doi:10.1371/journal.pcbi.1002717
PMCID: PMC3469413  PMID: 23071429
9.  Interspike Interval Based Filtering of Directional Selective Retinal Ganglion Cells Spike Trains 
The information regarding visual stimulus is encoded in spike trains at the output of retina by retinal ganglion cells (RGCs). Among these, the directional selective cells (DSRGC) are signaling the direction of stimulus motion. DSRGCs' spike trains show accentuated periods of short interspike intervals (ISIs) framed by periods of isolated spikes. Here we use two types of visual stimulus, white noise and drifting bars, and show that short ISI spikes of DSRGCs spike trains are more often correlated to their preferred stimulus feature (that is, the direction of stimulus motion) and carry more information than longer ISI spikes. Firstly, our results show that correlation between stimulus and recorded neuronal response is best at short ISI spiking activity and decrease as ISI becomes larger. We then used grating bars stimulus and found that as ISI becomes shorter the directional selectivity is better and information rates are higher. Interestingly, for the less encountered type of DSRGC, known as ON-DSRGC, short ISI distribution and information rates revealed consistent differences when compared with the other directional selective cell type, the ON-OFF DSRGC. However, these findings suggest that ISI-based temporal filtering integrates a mechanism for visual information processing at the output of retina toward higher stages within early visual system.
doi:10.1155/2012/918030
PMCID: PMC3419397  PMID: 22919373
10.  Timing Precision in Population Coding of Natural Scenes in the Early Visual System 
PLoS Biology  2008;6(12):e324.
The timing of spiking activity across neurons is a fundamental aspect of the neural population code. Individual neurons in the retina, thalamus, and cortex can have very precise and repeatable responses but exhibit degraded temporal precision in response to suboptimal stimuli. To investigate the functional implications for neural populations in natural conditions, we recorded in vivo the simultaneous responses, to movies of natural scenes, of multiple thalamic neurons likely converging to a common neuronal target in primary visual cortex. We show that the response of individual neurons is less precise at lower contrast, but that spike timing precision across neurons is relatively insensitive to global changes in visual contrast. Overall, spike timing precision within and across cells is on the order of 10 ms. Since closely timed spikes are more efficient in inducing a spike in downstream cortical neurons, and since fine temporal precision is necessary to represent the more slowly varying natural environment, we argue that preserving relative spike timing at a ∼10-ms resolution is a crucial property of the neural code entering cortex.
Author Summary
Neurons convey information about the world in the form of trains of action potentials (spikes). These trains are highly repeatable when the same stimulus is presented multiple times, and this temporal precision across repetitions can be as fine as a few milliseconds. It is usually assumed that this time scale also corresponds to the timing precision of several neighboring neurons firing in concert. However, the relative timing of spikes emitted by different neurons in a local population is not necessarily as fine as the temporal precision across repetitions within a single neuron. In the visual system of the brain, the level of contrast in the image entering the retina can affect single-neuron temporal precision, but the effects of contrast on the neural population code are unknown. Here we show that the temporal scale of the population code entering visual cortex is on the order of 10 ms and is largely insensitive to changes in visual contrast. Since closely timed spikes are more efficient in inducing a spike in downstream cortical neurons, and since fine temporal precision is necessary in representing the more slowly varying natural environment, preserving relative spike timing at a ∼10-ms resolution may be a crucial property of the neural code entering cortex.
Early neural representation of visual scenes occurs with a temporal precision on the order of 10 ms, which is precise enough to strongly drive downstream neurons in the visual pathway. Unlike individual neurons, the neural population code is largely insensitive to pronounced changes in visual contrast.
doi:10.1371/journal.pbio.0060324
PMCID: PMC2602720  PMID: 19090624
11.  Nitric Oxide Mediates Activity-Dependent Plasticity of Retinal Bipolar Cell Output via S-Nitrosylation 
The Journal of Neuroscience  2013;33(49):19176-19193.
Coding a wide range of light intensities in natural scenes poses a challenge for the retina: adaptation to bright light should not compromise sensitivity to dim light. Here we report a novel form of activity-dependent synaptic plasticity, specifically, a “weighted potentiation” that selectively increases output of Mb-type bipolar cells in the goldfish retina in response to weak inputs but leaves the input–output ratio for strong stimuli unaffected. In retinal slice preparation, strong depolarization of bipolar terminals significantly lowered the threshold for calcium spike initiation, which originated from a shift in activation of voltage-gated calcium currents (ICa) to more negative potentials. The process depended upon glutamate-evoked retrograde nitric oxide (NO) signaling as it was eliminated by pretreatment with an NO synthase blocker, TRIM. The NO-dependent ICa modulation was cGMP independent but could be blocked by N-ethylmaleimide (NEM), indicating that NO acted via an S-nitrosylation mechanism. Importantly, the NO action resulted in a weighted potentiation of Mb output in response to small (≤−30 mV) depolarizations. Coincidentally, light flashes with intensity ≥2.4 × 108 photons/cm2/s lowered the latency of scotopic (≤2.4 × 108 photons/cm2/s) light-evoked calcium spikes in Mb axon terminals in an NEM-sensitive manner, but light responses above cone threshold (≥3.5 × 109 photons/cm2/s) were unaltered. Under bright scotopic/mesopic conditions, this novel form of Mb output potentiation selectively amplifies dim retinal inputs at Mb → ganglion cell synapses. We propose that this process might counteract decreases in retinal sensitivity during light adaptation by preventing the loss of visual information carried by dim scotopic signals.
doi:10.1523/JNEUROSCI.2792-13.2013
PMCID: PMC3850041  PMID: 24305814
12.  Rapid mapping of visual receptive fields by filtered back projection: application to multi-neuronal electrophysiology and imaging 
The Journal of Physiology  2014;592(22):4839-4854.
Key points
To understand vision, we must measure the spatio-temporal receptive field of neurons in the visual system. We describe how the filtered back projection can be used to map the receptive fields of many neurons simultaneously, within a few minutes. This method can also reveal complex features of visual receptive fields such as the tuning of orientation selective neurons and the contributions from separate ON and OFF components. We demonstrate that the filtered back projection is suited to mapping receptive fields from populations of neurons recorded with imaging or electrophysiology and should therefore prove useful for investigations of visual processing throughout the visual pathway.
Abstract
Neurons in the visual system vary widely in the spatiotemporal properties of their receptive fields (RFs), and understanding these variations is key to elucidating how visual information is processed. We present a new approach for mapping RFs based on the filtered back projection (FBP), an algorithm used for tomographic reconstructions. To estimate RFs, a series of bars were flashed across the retina at pseudo-random positions and at a minimum of five orientations. We apply this method to retinal neurons and show that it can accurately recover the spatial RF and impulse response of ganglion cells recorded on a multi-electrode array. We also demonstrate its utility for in vivo imaging by mapping the RFs of an array of bipolar cell synapses expressing a genetically encoded Ca2+ indicator. We find that FBP offers several advantages over the commonly used spike-triggered average (STA): (i) ON and OFF components of a RF can be separated; (ii) the impulse response can be reconstructed at sample rates of 125 Hz, rather than the refresh rate of a monitor; (iii) FBP reveals the response properties of neurons that are not evident using STA, including those that display orientation selectivity, or fire at low mean spike rates; and (iv) the FBP method is fast, allowing the RFs of all the bipolar cell synaptic terminals in a field of view to be reconstructed in under 4 min. Use of the FBP will benefit investigations of the visual system that employ electrophysiology or optical reporters to measure activity across populations of neurons.
doi:10.1113/jphysiol.2014.276642
PMCID: PMC4259530  PMID: 25172952
13.  Modeling the impact of common noise inputs on the network activity of retinal ganglion cells 
Synchronized spontaneous firing among retinal ganglion cells (RGCs), on timescales faster than visual responses, has been reported in many studies. Two candidate mechanisms of synchronized firing include direct coupling and shared noisy inputs. In neighboring parasol cells of primate retina, which exhibit rapid synchronized firing that has been studied extensively, recent experimental work indicates that direct electrical or synaptic coupling is weak, but shared synaptic input in the absence of modulated stimuli is strong. However, previous modeling efforts have not accounted for this aspect of firing in the parasol cell population. Here we develop a new model that incorporates the effects of common noise, and apply it to analyze the light responses and synchronized firing of a large, densely-sampled network of over 250 simultaneously recorded parasol cells. We use a generalized linear model in which the spike rate in each cell is determined by the linear combination of the spatio-temporally filtered visual input, the temporally filtered prior spikes of that cell, and unobserved sources representing common noise. The model accurately captures the statistical structure of the spike trains and the encoding of the visual stimulus, without the direct coupling assumption present in previous modeling work. Finally, we examined the problem of decoding the visual stimulus from the spike train given the estimated parameters. The common-noise model produces Bayesian decoding performance as accurate as that of a model with direct coupling, but with significantly more robustness to spike timing perturbations.
doi:10.1007/s10827-011-0376-2
PMCID: PMC3560841  PMID: 22203465
Retina; Generalized linear model; State-space model; Multielectrode; Recording; Random-effects model
14.  Inhibition of Adult Rat Retinal Ganglion Cells by D1-type Dopamine Receptor Activation 
The spike output of neural pathways can be regulated by modulating output neuron excitability and/or their synaptic inputs. Dopaminergic interneurons synapse onto cells that route signals to mammalian retinal ganglion cells, but it is unknown whether dopamine can activate receptors in these ganglion cells and, if it does, how this affects their excitability. Here, we show D1a-receptor-like immunoreactivity in ganglion cells identified in adult rats by retrogradely transported dextran, and that dopamine, D1-type receptor agonists, and cAMP analogs inhibit spiking in ganglion cells dissociated from adult rats. These ligands curtailed repetitive spiking during constant current injections, and reduced the number and rate of rise of spikes elicited by fluctuating current injections without significantly altering the timing of the remaining spikes. Consistent with mediation by D1-type receptors, SCH-23390 reversed the effects of dopamine on spikes. Contrary to a recent report, spike inhibition by dopamine was not precluded by blocking Ih. Consistent with the reduced rate of spike rise, dopamine reduced voltage-gated Na+ current (INa) amplitude and tetrodotoxin, at doses that reduced INa as moderately as dopamine, also inhibited spiking. These results provide the first direct evidence that D1-type dopamine receptor activation can alter mammalian retinal ganglion cell excitability, and demonstrate that dopamine can modulate spikes in these cells by a mechanism different from the pre- and postsynaptic means proposed by previous studies. To our knowledge, our results also provide the first evidence that dopamine receptor activation can reduce excitability without altering the temporal precision of spike firing.
doi:10.1523/JNEUROSCI.3827-09.2009
PMCID: PMC3236800  PMID: 19940196
retina; dopamine D1 receptor; feedforward inhibition; immunohistochemistry; spike timing
15.  Burst-Time-Dependent Plasticity Robustly Guides ON/OFF Segregation in the Lateral Geniculate Nucleus 
PLoS Computational Biology  2009;5(12):e1000618.
Spontaneous retinal activity (known as “waves”) remodels synaptic connectivity to the lateral geniculate nucleus (LGN) during development. Analysis of retinal waves recorded with multielectrode arrays in mouse suggested that a cue for the segregation of functionally distinct (ON and OFF) retinal ganglion cells (RGCs) in the LGN may be a desynchronization in their firing, where ON cells precede OFF cells by one second. Using the recorded retinal waves as input, with two different modeling approaches we explore timing-based plasticity rules for the evolution of synaptic weights to identify key features underlying ON/OFF segregation. First, we analytically derive a linear model for the evolution of ON and OFF weights, to understand how synaptic plasticity rules extract input firing properties to guide segregation. Second, we simulate postsynaptic activity with a nonlinear integrate-and-fire model to compare findings with the linear model. We find that spike-time-dependent plasticity, which modifies synaptic weights based on millisecond-long timing and order of pre- and postsynaptic spikes, fails to segregate ON and OFF retinal inputs in the absence of normalization. Implementing homeostatic mechanisms results in segregation, but only with carefully-tuned parameters. Furthermore, extending spike integration timescales to match the second-long input correlation timescales always leads to ON segregation because ON cells fire before OFF cells. We show that burst-time-dependent plasticity can robustly guide ON/OFF segregation in the LGN without normalization, by integrating pre- and postsynaptic bursts irrespective of their firing order and over second-long timescales. We predict that an LGN neuron will become ON- or OFF-responsive based on a local competition of the firing patterns of neighboring RGCs connecting to it. Finally, we demonstrate consistency with ON/OFF segregation in ferret, despite differences in the firing properties of retinal waves. Our model suggests that diverse input statistics of retinal waves can be robustly interpreted by a burst-based rule, which underlies retinogeniculate plasticity across different species.
Author Summary
Many central targets in the brain are involved in the processing of information from the outside world. Before information about the visual scene reaches the visual cortex, it is preprocessed in the retina and the lateral geniculate nucleus. Connections which relay this information between the different brain targets are not determined at birth, but undergo a developmental period during which they are guided by molecular cues to the correct locations, and refined by activity to the appropriate numbers and strengths. Before the onset of vision, spontaneous activity generated within the retina plays an important role in the remodeling of these connections. In a computational and theoretical model, we used recorded spontaneous retinal activity patterns with several plasticity rules at the retinogeniculate synapse to identify the key properties underlying the selective refinement of connections. Our model shows robust behavior when applied to both mouse and ferret data, demonstrating that a common plasticity rule across species may underlie synaptic refinements in the visual system driven by spontaneous retinal activity.
doi:10.1371/journal.pcbi.1000618
PMCID: PMC2790088  PMID: 20041207
16.  Exploring the retinal connectome 
Molecular Vision  2011;17:355-379.
Purpose
A connectome is a comprehensive description of synaptic connectivity for a neural domain. Our goal was to produce a connectome data set for the inner plexiform layer of the mammalian retina. This paper describes our first retinal connectome, validates the method, and provides key initial findings.
Methods
We acquired and assembled a 16.5 terabyte connectome data set RC1 for the rabbit retina at ≈2 nm resolution using automated transmission electron microscope imaging, automated mosaicking, and automated volume registration. RC1 represents a column of tissue 0.25 mm in diameter, spanning the inner nuclear, inner plexiform, and ganglion cell layers. To enhance ultrastructural tracing, we included molecular markers for 4-aminobutyrate (GABA), glutamate, glycine, taurine, glutamine, and the in vivo activity marker, 1-amino-4-guanidobutane. This enabled us to distinguish GABAergic and glycinergic amacrine cells; to identify ON bipolar cells coupled to glycinergic cells; and to discriminate different kinds of bipolar, amacrine, and ganglion cells based on their molecular signatures and activity. The data set was explored and annotated with Viking, our multiuser navigation tool. Annotations were exported to additional applications to render cells, visualize network graphs, and query the database.
Results
Exploration of RC1 showed that the 2 nm resolution readily recapitulated well known connections and revealed several new features of retinal organization: (1) The well known AII amacrine cell pathway displayed more complexity than previously reported, with no less than 17 distinct signaling modes, including ribbon synapse inputs from OFF bipolar cells, wide-field ON cone bipolar cells and rod bipolar cells, and extensive input from cone-pathway amacrine cells. (2) The axons of most cone bipolar cells formed a distinct signal integration compartment, with ON cone bipolar cell axonal synapses targeting diverse cell types. Both ON and OFF bipolar cells receive axonal veto synapses. (3) Chains of conventional synapses were very common, with intercalated glycinergic-GABAergic chains and very long chains associated with starburst amacrine cells. Glycinergic amacrine cells clearly play a major role in ON-OFF crossover inhibition. (4) Molecular and excitation mapping clearly segregates ultrastructurally defined bipolar cell groups into different response clusters. (5) Finally, low-resolution electron or optical imaging cannot reliably map synaptic connections by process geometry, as adjacency without synaptic contact is abundant in the retina. Only direct visualization of synapses and gap junctions suffices.
Conclusions
Connectome assembly and analysis using conventional transmission electron microscopy is now practical for network discovery. Our surveys of volume RC1 demonstrate that previously studied systems such as the AII amacrine cell network involve more network motifs than previously known. The AII network, primarily considered a scotopic pathway, clearly derives ribbon synapse input from photopic ON and OFF cone bipolar cell networks and extensive photopic GABAergic amacrine cell inputs. Further, bipolar cells show extensive inputs and outputs along their axons, similar to multistratified nonmammalian bipolar cells. Physiologic evidence of significant ON-OFF channel crossover is strongly supported by our anatomic data, showing alternating glycine-to-GABA paths. Long chains of amacrine cell networks likely arise from homocellular GABAergic synapses between starburst amacrine cells. Deeper analysis of RC1 offers the opportunity for more complete descriptions of specific networks.
PMCID: PMC3036568  PMID: 21311605
17.  A Synaptic Mechanism for Temporal Filtering of Visual Signals 
PLoS Biology  2014;12(10):e1001972.
Synaptic volume matters! The size of the presynaptic compartment of retinal bipolar cells controls the amplitude, speed, and adaptation of synaptic transmission.
The visual system transmits information about fast and slow changes in light intensity through separate neural pathways. We used in vivo imaging to investigate how bipolar cells transmit these signals to the inner retina. We found that the volume of the synaptic terminal is an intrinsic property that contributes to different temporal filters. Individual cells transmit through multiple terminals varying in size, but smaller terminals generate faster and larger calcium transients to trigger vesicle release with higher initial gain, followed by more profound adaptation. Smaller terminals transmitted higher stimulus frequencies more effectively. Modeling global calcium dynamics triggering vesicle release indicated that variations in the volume of presynaptic compartments contribute directly to all these differences in response dynamics. These results indicate how one neuron can transmit different temporal components in the visual signal through synaptic terminals of varying geometries with different adaptational properties.
Author Summary
The process of neurotransmission involves the conversion of electrical signals into the release of a chemical neurotransmitter from the neurons synaptic terminal, and the key trigger for this release is a rise in calcium concentration. Accordingly, the amplitude and speed of this calcium signal controls the amplitude and time-course of synaptic communication. Working on the synaptic terminals of fish retinal bipolar cells, we show that the presynaptic calcium signal and the subsequent neurotransmitter release are shaped by the basic property of synapse volume. Using a combination of experimental approaches and computational models, we found that large synapses are slow and adapt little during ongoing stimulation, while small synapses are fast and show more profound adaptation. This observation leads to a second key concept: since neurons usually have several presynaptic terminals that may vary in volume, a single neuron can, in principle, forward different synaptic signals to different postsynaptic partners. We provide direct evidence that this is the case for bipolar cells of the fish retina.
doi:10.1371/journal.pbio.1001972
PMCID: PMC4205119  PMID: 25333637
18.  Temporal Correlation Mechanisms and Their Role in Feature Selection: A Single-Unit Study in Primate Somatosensory Cortex 
PLoS Biology  2014;12(11):e1002004.
How neurons pay attention Top-down selective attention mediates feature selection by reducing the noise correlations in neural populations and enhancing the synchronized activity across subpopulations that encode the relevant features of sensory stimuli.
Studies in vision show that attention enhances the firing rates of cells when it is directed towards their preferred stimulus feature. However, it is unknown whether other sensory systems employ this mechanism to mediate feature selection within their modalities. Moreover, whether feature-based attention modulates the correlated activity of a population is unclear. Indeed, temporal correlation codes such as spike-synchrony and spike-count correlations (rsc) are believed to play a role in stimulus selection by increasing the signal and reducing the noise in a population, respectively. Here, we investigate (1) whether feature-based attention biases the correlated activity between neurons when attention is directed towards their common preferred feature, (2) the interplay between spike-synchrony and rsc during feature selection, and (3) whether feature attention effects are common across the visual and tactile systems. Single-unit recordings were made in secondary somatosensory cortex of three non-human primates while animals engaged in tactile feature (orientation and frequency) and visual discrimination tasks. We found that both firing rate and spike-synchrony between neurons with similar feature selectivity were enhanced when attention was directed towards their preferred feature. However, attention effects on spike-synchrony were twice as large as those on firing rate, and had a tighter relationship with behavioral performance. Further, we observed increased rsc when attention was directed towards the visual modality (i.e., away from touch). These data suggest that similar feature selection mechanisms are employed in vision and touch, and that temporal correlation codes such as spike-synchrony play a role in mediating feature selection. We posit that feature-based selection operates by implementing multiple mechanisms that reduce the overall noise levels in the neural population and synchronize activity across subpopulations that encode the relevant features of sensory stimuli.
Author Summary
Attention can select stimuli in space based on the stimulus features most relevant for a task. Attention effects have been linked to several important phenomena such as modulations in neuronal spiking rate (i.e., the average number of spikes per unit time) and spike-spike synchrony between neurons. Attention has also been associated with spike count correlations, a measure that is thought to reflect correlated noise in the population of neurons. Here, we studied whether feature-based attention biases the correlated activity between neurons when attention is directed towards their common preferred feature. Simultaneous single-unit recordings were obtained from multiple neurons in secondary somatosensory cortex in non-human primates performing feature-attention tasks. Both firing rate and spike-synchrony were enhanced when attention was directed towards the preferred feature of cells. However, attention effects on spike-synchrony had a tighter relationship with behavior. Further, attention decreased spike-count correlations when it was directed towards the receptive field of cells. Our data indicate that temporal correlation codes play a role in mediating feature selection, and are consistent with a feature-based selection model that operates by reducing the overall noise in a population and synchronizing activity across subpopulations that encode the relevant features of sensory stimuli.
doi:10.1371/journal.pbio.1002004
PMCID: PMC4244037  PMID: 25423284
19.  Axonal Transmission in the Retina Introduces a Small Dispersion of Relative Timing in the Ganglion Cell Population Response 
PLoS ONE  2011;6(6):e20810.
Background
Visual stimuli elicit action potentials in tens of different retinal ganglion cells. Each ganglion cell type responds with a different latency to a given stimulus, thus transforming the high-dimensional input into a temporal neural code. The timing of the first spikes between different retinal projection neurons cells may further change along axonal transmission. The purpose of this study is to investigate if intraretinal conduction velocity leads to a synchronization or dispersion of the population signal leaving the eye.
Methodology/Principal Findings
We ‘imaged’ the initiation and transmission of light-evoked action potentials along individual axons in the rabbit retina at micron-scale resolution using a high-density multi-transistor array. We measured unimodal conduction velocity distributions (1.3±0.3 m/sec, mean ± SD) for axonal populations at all retinal eccentricities with the exception of the central part that contains myelinated axons. The velocity variance within each piece of retina is caused by ganglion cell types that show narrower and slightly different average velocity tuning. Ganglion cells of the same type respond with similar latency to spatially homogenous stimuli and conduct with similar velocity. For ganglion cells of different type intraretinal conduction velocity and response latency to flashed stimuli are negatively correlated, indicating that differences in first spike timing increase (up to 10 msec). Similarly, the analysis of pair-wise correlated activity in response to white-noise stimuli reveals that conduction velocity and response latency are negatively correlated.
Conclusion/Significance
Intraretinal conduction does not change the relative spike timing between ganglion cells of the same type but increases spike timing differences among ganglion cells of different type. The fastest retinal ganglion cells therefore act as indicators of new stimuli for postsynaptic neurons. The intraretinal dispersion of the population activity will not be compensated by variability in extraretinal conduction times, estimated from data in the literature.
doi:10.1371/journal.pone.0020810
PMCID: PMC3107248  PMID: 21674067
20.  Spike timing in CA3 pyramidal cells during behavior: implications for synaptic transmission 
Journal of neurophysiology  2005;94(2):1528-1540.
Spike timing is thought to be an important mechanism for transmitting information in the CNS. Recent studies have emphasized millisecond precision in spike timing, to allow temporal summation of rapid synaptic signals. However, spike timing over slower timescales could also be important, through mechanisms including activity-dependent synaptic plasticity, or temporal summation of slow PSPs such as those mediated by kainate receptors. To determine the extent to which these slower mechanisms contribute to information processing, it is first necessary to understand the properties of behaviorally relevant spike timing over this slow timescale. In this study, we examine the activity of CA3 pyramidal cells during the performance of a complex behavioral task in rats. Sustained firing rates vary over a wide range, and the firing rate of a cell is poorly correlated with the behavioral cues to which the cell responds. Non-random interactions between successive spikes can last for several seconds, but the non-random distribution of interspike intervals (ISIs) can account for the majority of nonrandom multi-spike patterns. During a stimulus, cellular responses are temporally complex, causing a shift in spike timing that favors intermediate ISIs over short and long ISIs. Response discrimination between related stimuli occurs through changes in both response time-course and response intensity. Precise synchrony between cells is limited, but loosely correlated firing between cells is common. This study indicates that spike timing is regulated over long timescales, and suggests that slow synaptic mechanisms could play a substantial role in information processing in the CNS.
doi:10.1152/jn.00108.2005
PMCID: PMC1378104  PMID: 15872069
21.  Rapid mapping of visual receptive fields by filtered back projection: application to multi-neuronal electrophysiology and imaging 
The Journal of Physiology  2014;592(Pt 22):4839-4854.
Neurons in the visual system vary widely in the spatiotemporal properties of their receptive fields (RFs), and understanding these variations is key to elucidating how visual information is processed. We present a new approach for mapping RFs based on the filtered back projection (FBP), an algorithm used for tomographic reconstructions. To estimate RFs, a series of bars were flashed across the retina at pseudo-random positions and at a minimum of five orientations. We apply this method to retinal neurons and show that it can accurately recover the spatial RF and impulse response of ganglion cells recorded on a multi-electrode array. We also demonstrate its utility for in vivo imaging by mapping the RFs of an array of bipolar cell synapses expressing a genetically encoded Ca2+ indicator. We find that FBP offers several advantages over the commonly used spike-triggered average (STA): (i) ON and OFF components of a RF can be separated; (ii) the impulse response can be reconstructed at sample rates of 125 Hz, rather than the refresh rate of a monitor; (iii) FBP reveals the response properties of neurons that are not evident using STA, including those that display orientation selectivity, or fire at low mean spike rates; and (iv) the FBP method is fast, allowing the RFs of all the bipolar cell synaptic terminals in a field of view to be reconstructed in under 4 min. Use of the FBP will benefit investigations of the visual system that employ electrophysiology or optical reporters to measure activity across populations of neurons.
doi:10.1113/jphysiol.2014.276642
PMCID: PMC4259530  PMID: 25172952
22.  Neural Coding of Natural Stimuli: Information at Sub-Millisecond Resolution 
PLoS Computational Biology  2008;4(3):e1000025.
Sensory information about the outside world is encoded by neurons in sequences of discrete, identical pulses termed action potentials or spikes. There is persistent controversy about the extent to which the precise timing of these spikes is relevant to the function of the brain. We revisit this issue, using the motion-sensitive neurons of the fly visual system as a test case. Our experimental methods allow us to deliver more nearly natural visual stimuli, comparable to those which flies encounter in free, acrobatic flight. New mathematical methods allow us to draw more reliable conclusions about the information content of neural responses even when the set of possible responses is very large. We find that significant amounts of visual information are represented by details of the spike train at millisecond and sub-millisecond precision, even though the sensory input has a correlation time of ∼55 ms; different patterns of spike timing represent distinct motion trajectories, and the absolute timing of spikes points to particular features of these trajectories with high precision. Finally, the efficiency of our entropy estimator makes it possible to uncover features of neural coding relevant for natural visual stimuli: first, the system's information transmission rate varies with natural fluctuations in light intensity, resulting from varying cloud cover, such that marginal increases in information rate thus occur even when the individual photoreceptors are counting on the order of one million photons per second. Secondly, we see that the system exploits the relatively slow dynamics of the stimulus to remove coding redundancy and so generate a more efficient neural code.
Author Summary
Neurons communicate by means of stereotyped pulses, called action potentials or spikes, and a central issue in systems neuroscience is to understand this neural coding. Here we study how sensory information is encoded in sequences of spikes, using a combination of novel theoretical and experimental techniques. With motion detection in the blowfly as a model system, we perform experiments in an environment maximally similar to the natural one. We report a number of unexpected, striking observations about the structure of the neural code in this system: First, the timing of spikes is important with a precision roughly two orders of magnitude greater than the temporal dynamics of the stimulus. Second, the fly goes a long way to utilize the redundancy in the stimulus in order to optimize the neural code and encode more refined features than would be possible otherwise. This implies that the neural code, even in low-level vision, may be significantly context dependent.
doi:10.1371/journal.pcbi.1000025
PMCID: PMC2265477  PMID: 18369423
23.  Dendritic Spikes Amplify the Synaptic Signal to Enhance Detection of Motion in a Simulation of the Direction-Selective Ganglion Cell 
PLoS Computational Biology  2010;6(8):e1000899.
The On-Off direction-selective ganglion cell (DSGC) in mammalian retinas responds most strongly to a stimulus moving in a specific direction. The DSGC initiates spikes in its dendritic tree, which are thought to propagate to the soma with high probability. Both dendritic and somatic spikes in the DSGC display strong directional tuning, whereas somatic PSPs (postsynaptic potentials) are only weakly directional, indicating that spike generation includes marked enhancement of the directional signal. We used a realistic computational model based on anatomical and physiological measurements to determine the source of the enhancement. Our results indicate that the DSGC dendritic tree is partitioned into separate electrotonic regions, each summing its local excitatory and inhibitory synaptic inputs to initiate spikes. Within each local region the local spike threshold nonlinearly amplifies the preferred response over the null response on the basis of PSP amplitude. Using inhibitory conductances previously measured in DSGCs, the simulation results showed that inhibition is only sufficient to prevent spike initiation and cannot affect spike propagation. Therefore, inhibition will only act locally within the dendritic arbor. We identified the role of three mechanisms that generate directional selectivity (DS) in the local dendritic regions. First, a mechanism for DS intrinsic to the dendritic structure of the DSGC enhances DS on the null side of the cell's dendritic tree and weakens it on the preferred side. Second, spatially offset postsynaptic inhibition generates robust DS in the isolated dendritic tips but weak DS near the soma. Third, presynaptic DS is apparently necessary because it is more robust across the dendritic tree. The pre- and postsynaptic mechanisms together can overcome the local intrinsic DS. These local dendritic mechanisms can perform independent nonlinear computations to make a decision, and there could be analogous mechanisms within cortical circuitry.
Author Summary
The On-Off direction-selective ganglion cell (DSGC) found in mammalian retinas generates a directional signal, responding most strongly to a stimulus moving in a specific direction. The DSGC initiates spikes in its dendritic tree which are thought to propagate to the soma and brain with high probability. Both dendritic and somatic spikes in the DSGC display strong directional tuning, whereas postsynaptic potentials (PSPs) recorded in the soma are only weakly directional, indicating that postsynaptic spike generation markedly enhances the directional signal. We constructed a realistic computational model to determine the source of the enhancement. Our results indicate that the DSGC dendritic tree is partitioned into separate computational regions. Within each region, the local spike threshold produces nonlinear amplification of the preferred response over the null response on the basis of PSP amplitude. The simulation results showed that inhibition acts locally within the dendritic arbor and will not stop dendritic spikes from propagating. We identified the role of three mechanisms that generate direction selectivity in the local dendritic regions, which suggests the origin of the previously described “non-direction-selective region,” and also suggests that the known DS in the synaptic inputs is apparently necessary for robust DS across the dendritic tree.
doi:10.1371/journal.pcbi.1000899
PMCID: PMC2924322  PMID: 20808894
24.  Refractoriness Enhances Temporal Coding by Auditory Nerve Fibers 
The Journal of Neuroscience  2013;33(18):7681-7690.
A universal property of spiking neurons is refractoriness, a transient decrease in discharge probability immediately following an action potential (spike). The refractory period lasts only one to a few milliseconds, but has the potential to affect temporal coding of acoustic stimuli by auditory neurons, which are capable of submillisecond spike-time precision. Here this possibility was investigated systematically by recording spike times from chicken auditory nerve fibers in vivo while stimulating with repeated pure tones at characteristic frequency. Refractory periods were tightly distributed, with a mean of 1.58 ms. A statistical model was developed to recapitulate each fiber's responses and then used to predict the effect of removing the refractory period on a cell-by-cell basis for two largely independent facets of temporal coding: faithful entrainment of interspike intervals to the stimulus frequency and precise synchronization of spike times to the stimulus phase. The ratio of the refractory period to the stimulus period predicted the impact of refractoriness on entrainment and synchronization. For ratios less than ∼0.9, refractoriness enhanced entrainment and this enhancement was often accompanied by an increase in spike-time precision. At higher ratios, little or no change in entrainment or synchronization was observed. Given the tight distribution of refractory periods, the ability of refractoriness to improve temporal coding is restricted to neurons responding to low-frequency stimuli. Enhanced encoding of low frequencies likely affects sound localization and pitch perception in the auditory system, as well as perception in nonauditory sensory modalities, because all spiking neurons exhibit refractoriness.
doi:10.1523/JNEUROSCI.3405-12.2013
PMCID: PMC3865560  PMID: 23637161
25.  Dynamics of the ganglion cell response in the catfish and frog retinas 
The Journal of General Physiology  1987;90(2):229-259.
Responses were evoked from ganglion cells in catfish and frog retinas by a Gaussian modulation of the mean luminance. An algorithm was devised to decompose intracellularly recorded responses into the slow and spike components and to extract the time of occurrence of a spike discharge. The dynamics of both signals were analyzed in terms of a series of first-through third-order kernels obtained by cross- correlating the slow (analog) or spike (discrete or point process) signals against the white-noise input. We found that, in the catfish, (a) the slow signals were composed mostly of postsynaptic potentials, (b) their linear components reflected the dynamics found in bipolar cells or in the linear response component of type-N (sustained) amacrine cells, and (c) their nonlinear components were similar to those found in either type-N or type-C (transient) amacrine cells. A comparison of the dynamics of slow and spike signals showed that the characteristic linear and nonlinear dynamics of slow signals were encoded into a spike train, which could be recovered through the cross- correlation between the white-noise input and the spike (point process signals. In addition, well-defined spike correlates could predict the observed slow potentials. In the spike discharges from frog ganglion cells, the linear (or first-order) kernels were all inhibitory, whereas the second-order kernels had characteristics of on-off transient excitation. The transient and sustained amacrine cells similar to those found in catfish retina were the sources of the nonlinear excitation. We conclude that bipolar cells and possibly the linear part of the type- N cell response are the source of linear, either excitatory or inhibitory, components of the ganglion cell responses, whereas amacrine cells are the source of the cells' static nonlinearity.
PMCID: PMC2228836  PMID: 3498795

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