scholarly journals Low error discrimination using a correlated population code

2012 ◽  
Vol 108 (4) ◽  
pp. 1069-1088 ◽  
Author(s):  
Greg Schwartz ◽  
Jakob Macke ◽  
Dario Amodei ◽  
Hanlin Tang ◽  
Michael J. Berry
Keyword(s):  
Spatial Information ◽  
Ganglion Cells ◽  
Discrimination Performance ◽  
Spike Timing ◽  
Multiple Time ◽  
Entropy Model ◽  
Decoding Algorithms ◽  
Single Spike ◽  
Order Of Magnitude ◽  
Spike Latency

We explored the manner in which spatial information is encoded by retinal ganglion cell populations. We flashed a set of 36 shape stimuli onto the tiger salamander retina and used different decoding algorithms to read out information from a population of 162 ganglion cells. We compared the discrimination performance of linear decoders, which ignore correlation induced by common stimulation, with nonlinear decoders, which can accurately model these correlations. Similar to previous studies, decoders that ignored correlation suffered only a modest drop in discrimination performance for groups of up to ∼30 cells. However, for more realistic groups of 100+ cells, we found order-of-magnitude differences in the error rate. We also compared decoders that used only the presence of a single spike from each cell with more complex decoders that included information from multiple spike counts and multiple time bins. More complex decoders substantially outperformed simpler decoders, showing the importance of spike timing information. Particularly effective was the first spike latency representation, which allowed zero discrimination errors for the majority of shape stimuli. Furthermore, the performance of nonlinear decoders showed even greater enhancement compared with linear decoders for these complex representations. Finally, decoders that approximated the correlation structure in the population by matching all pairwise correlations with a maximum entropy model fit to all 162 neurons were quite successful, especially for the spike latency representation. Together, these results suggest a picture in which linear decoders allow a coarse categorization of shape stimuli, whereas nonlinear decoders, which take advantage of both correlation and spike timing, are needed to achieve high-fidelity discrimination.

scholarly journals Fine Spike Timing in Hippocampal–Prefrontal Ensembles Predicts Poor Encoding and Underlies Behavioral Performance in Healthy and Malformed Brains

2020 ◽  
Vol 31 (1) ◽  
pp. 147-158
Author(s):  
Amanda E Hernan ◽  
J Matthew Mahoney ◽  
Willie Curry ◽  
Seamus Mawe ◽  
Rod C Scott
Keyword(s):  
Working Memory ◽  
Spatial Information ◽  
Spatial Working Memory ◽  
Spike Timing ◽  
Functional Network ◽  
Long Term Memory ◽  
Encode Task ◽  
To Receive ◽  
Task Parameters

Abstract Spatial working memory (SWM) is a central cognitive process during which the hippocampus and prefrontal cortex (PFC) encode and maintain spatial information for subsequent decision-making. This occurs in the context of ongoing computations relating to spatial position, recall of long-term memory, attention, among many others. To establish how intermittently presented information is integrated with ongoing computations we recorded single units, simultaneously in hippocampus and PFC, in control rats and those with a brain malformation during performance of an SWM task. Neurons that encode intermittent task parameters are also well modulated in time and incorporated into a functional network across regions. Neurons from animals with cortical malformation are poorly modulated in time, less likely to encode task parameters, and less likely to be integrated into a functional network. Our results implicate a model in which ongoing oscillatory coordination among neurons in the hippocampal–PFC network describes a functional network that is poised to receive sensory inputs that are then integrated and multiplexed as working memory. The background temporal modulation is systematically altered in disease, but the relationship between these dynamics and behaviorally relevant firing is maintained, thereby providing potential targets for stimulation-based therapies.

scholarly journals STDP Forms Associations between Memory Traces in Networks of Spiking Neurons

2019 ◽  
Vol 30 (3) ◽  
pp. 952-968
Author(s):  
Christoph Pokorny ◽  
Matias J Ison ◽  
Arjun Rao ◽  
Robert Legenstein ◽  
Christos Papadimitriou ◽  
...  
Keyword(s):  
Brain Function ◽  
Spatial Information ◽  
Spike Timing ◽  
Spiking Neurons ◽  
Recurrent Networks ◽  
Neural Codes ◽  
Memory Traces ◽  
Conflicting Evidence ◽  
Excitability Of Neurons ◽  
The Brain

Abstract Memory traces and associations between them are fundamental for cognitive brain function. Neuron recordings suggest that distributed assemblies of neurons in the brain serve as memory traces for spatial information, real-world items, and concepts. However, there is conflicting evidence regarding neural codes for associated memory traces. Some studies suggest the emergence of overlaps between assemblies during an association, while others suggest that the assemblies themselves remain largely unchanged and new assemblies emerge as neural codes for associated memory items. Here we study the emergence of neural codes for associated memory items in a generic computational model of recurrent networks of spiking neurons with a data-constrained rule for spike-timing-dependent plasticity. The model depends critically on 2 parameters, which control the excitability of neurons and the scale of initial synaptic weights. By modifying these 2 parameters, the model can reproduce both experimental data from the human brain on the fast formation of associations through emergent overlaps between assemblies, and rodent data where new neurons are recruited to encode the associated memories. Hence, our findings suggest that the brain can use both of these 2 neural codes for associations, and dynamically switch between them during consolidation.

Time asymptotic perturbation theory in weak plasma turbulence I. Macroscopic description

1971 ◽  
Vol 5 (1) ◽  
pp. 31-37 ◽  
Author(s):  
Klaus Elsässer
Keyword(s):  
Multiple Time ◽  
Macroscopic Description ◽  
Wave Processes ◽  
Time Formalism ◽  
Hierarchy Equations ◽  
Order Of Magnitude ◽  
Unique Method ◽  
Non Linear Mechanics ◽  
Low Amplitude ◽  
Asymptotic Perturbation

The time asymptotic method of non-linear mechanics (Bogoljubov & Mitropoiski 1961) is used to solve the hierarchy equations of low-amplitude wave correlations. We start with a formal description of individual dispersive and undamped waves and derive the usual kinetic equation for the energy spectrum and the three-wave correlation in the lowest order (three-wave processes). We show that the equations are automatically closed (‘Quasi-Gaussian’) even in the case where the correlations have the same order of magnitude as the corresponding moments. This approach parallels the multiple-time formalism of Sandri and Frieman, but it represents an alternate systematic and unique method (without ‘extension’ in the sense of Sandri).

A Non-Markovian Random Walk Underlies a Stochastic Model of Spike-Timing-Dependent Plasticity

2010 ◽  
Vol 22 (5) ◽  
pp. 1180-1230 ◽  
Author(s):  
Terry Elliott
Keyword(s):  
Random Walk ◽  
Stochastic Model ◽  
Synaptic Strength ◽  
Spike Timing ◽  
Spatial Average ◽  
Spike Timing Dependent Plasticity ◽  
Dependent Plasticity ◽  
Strength Change ◽  
Single Spike ◽  
Switch Mechanism

A stochastic model of spike-timing-dependent plasticity (STDP) proposes that spike timing influences the probability but not the amplitude of synaptic strength change at single synapses. The classic, biphasic STDP profile emerges as a spatial average over many synapses presented with a single spike pair or as a temporal average over a single synapse presented with many spike pairs. We have previously shown that the model accounts for a variety of experimental data, including spike triplet results, and has a number of desirable theoretical properties, including being entirely self-stabilizing in all regions of parameter space. Our earlier analyses of the model have employed cumbersome spike-to-spike averaging arguments to derive results. Here, we show that the model can be reformulated as a non-Markovian random walk in synaptic strength, the step sizes being fixed as postulated. This change of perspective greatly simplifies earlier calculations by integrating out the proposed switch mechanism by which changes in strength are driven and instead concentrating on the changes in strength themselves. Moreover, this change of viewpoint is generative, facilitating further calculations that would be intractable, if not impossible, with earlier approaches. We prepare the machinery here for these later calculations but also briefly indicate how this machinery may be used by considering two particular applications.

scholarly journals Nerve fibers in culture and their interactions with non-neural cells visualized by immunofluorescence.

1979 ◽  
Vol 80 (3) ◽  
pp. 629-641 ◽  
Author(s):  
H Jockusch ◽  
B M Jockusch ◽  
M M Burger
Keyword(s):  
Spinal Cord ◽  
Ganglion Cells ◽  
Cell Types ◽  
Nerve Fibers ◽  
Affinity Column ◽  
Neural Cells ◽  
Embryonic Mouse ◽  
Antibody Staining ◽  
Order Of Magnitude ◽  
Nerve Muscle

Cultures of embryonic mouse spinal cord explants, alone or in combination with rat myotubes, were stained by indirect immunofluorescence using antibodies against three structural proteins to: (a) reveal the distribution of these proteins among different cell types, and (b) test the usefulness of antibody staining to reveal the gross morphology of the neurite network in complex cultures. Affinity column purified antibodies were used against chicken gizzard actin, porcine brain tubulin, and skeletal muscle alpha-actinin. Neurites were stained intensely by anti-actin as was the stress fiber pattern of underlying fibroblasts. With anti-tubulin, the staining of neurites was an order of magnitude more intense than the staining of the microtubule pattern of background fibroblasts. Neurite cell bodies and astrocyte-like glia cells were stained with anti-tubulin and their nuclei remained unstained. Anti-tubulin could thus be used to trace even the finest extensions of nerve processes in spinal cord and spinal cord-muscle cultures. Furthermore, it could be combined with the histochemical reaction for acetylcholinesterase (AChE, EC 3.1.1.7) to demonstrate AChE-positive neurons and specialized nerve-muscle contact sites. The staining of neural elements with anti-alpha-actinin was generally much weaker than with anti-actin and anti-tubulin. Neurites were stained only moderately in comparison to myotube Z lines in the same culture. However, a distinct staining of the periphery of dorsal root ganglion cells was observed. Thus, a protein immunologically related to muscle alpha-actinin is present in the nervous system. In myotubes, Z lines were stained intensely with anti-alpha-actinin while I bands were only faintly stained with anti-actin. In isolated myofibrils, both structures were stained intensely with the same antibody preparations.

scholarly journals Salamander retinal ganglion cell responses to rich stimuli

2020 ◽  
Author(s):  
Kolia Sadeghi ◽  
Michael J. Berry
Keyword(s):  
Ganglion Cell ◽  
Retinal Ganglion Cells ◽  
Spatial Information ◽  
Ganglion Cells ◽  
Light Stimulus ◽  
Linear Filter ◽  
Retinal Ganglion ◽  
Linear Filters ◽  
Cell Responses ◽  
Random Stimulus

AbstractThe retina’s phenomenological function is often considered to be well-understood: individual retinal ganglion cells are sensitive to a projection of the light stimulus movie onto a classical center-surround linear filter. Recent models elaborating on this basic framework by adding a second linear filter or spike histories, have been quite successful at predicting ganglion cell spikes for spatially uniform random stimuli, and for random stimuli varying spatially with low resolution. Fitting models for stimuli with more finely grained spatial variations becomes difficult because of the very high dimensionality of such stimuli. We present a method of reducing the dimensionality of a fine one dimensional random stimulus by using wavelets, allowing for several clean predictive linear filters to be found for each cell. For salamander retinal ganglion cells, we find in addition to the spike triggered average, 3 identifiable types of linear filters which modulate the firing of most cells. While some cells can be modeled fairly accurately, many cells are poorly captured, even with as many as 4 filters. The new linear filters we find shed some light on the nonlinearities in the retina’s integration of temporal and fine spatial information.

Regenerating axons from adult chick retinal ganglion cells recognize topographic cues from embryonic central targets

1991 ◽  
Vol 6 (6) ◽  
pp. 569-576 ◽  
Author(s):  
Jens Vanselow ◽  
Bernhard Müller ◽  
Solon Thanos
Keyword(s):  
Retinal Ganglion Cells ◽  
Axonal Regeneration ◽  
Ganglion Cells ◽  
Target Recognition ◽  
Growth Cones ◽  
Retinal Ganglion ◽  
Embryonic Growth ◽  
Retinal Axons ◽  
Order Of Magnitude ◽  
Mature Neurons

AbstractWe investigated whether regenerating mature axons recapitulate embryonic features essential to successful reconnectivity within the injured nervous system. Strips from embryonic and adult chick retinae were cultured, and outgrowing axons were examined morphometrically and immunohistochemically. In addition, the target-recognition properties of adult neurites were analyzed. Regenerating adult axons elongate on a poly-L-lysine/laminin substratum with a speed about one order of magnitude slower than that of embryonic axons. Morphologically, adult axonal tips differ dramatically from embryonic growth cones in that they possess only filopodial extensions whereas embryonic growth cones possess both lamellipodial and filopodial processes. Both embryonic and adult neurites express the growth-associated protein GAP-43. When cultured on alternating stripes of anterior and posterior embryonic tectal membranes, both adult and embryonic retinal axons distinguish between the two membrane preparations. Our results demonstrate that during axonal regeneration the mature neurons express embryonic properties that are involved in the recognition of tectal positional cues.

scholarly journals Intensity Coding in the Frog Retina

1973 ◽  
Vol 61 (3) ◽  
pp. 305-322 ◽  
Author(s):  
Dwight A. Burkhardt ◽  
Paul Whittle
Keyword(s):  
Dynamic Range ◽  
Ganglion Cells ◽  
Field Potential ◽  
Intensity Coding ◽  
Frog Retina ◽  
Independent Variable ◽  
Highly Correlated ◽  
Intensity Functions ◽  
Spike Latency ◽  
Stimulus Time

The impulse discharge of single on-off neurons and a graded field potential, the proximal negative response (PNR), were simultaneously recorded with an extracellular microelectrode in the inner frog retina. Normalized amplitude-intensity functions for the on-response of the PNR and the neuron's post-stimulus time histogram (PSTH) were nearly coincident and typically showed a dynamic range spanning approximately 2 log units of intensity. Thus a nearly linear relation is found between the amplitude of the PNR and the neuron's PSTH. A neuron's PSTH amplitude and maximum instantaneous frequency of discharge were usually highly correlated, but occasional marked disparities indicate that temporal jitter of the first spike latency is an additional, relatively independent variable influencing PSTH amplitude. It typically changes by a factor of 20–30 over the intensity range. These and other findings have implications for the functional significance of the PNR and the PSTH, for a possible linear link between amacrine and on-off ganglion cells, and for a mechanism of intensity coding in which temporal jitter of latency exerts a major role.

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