scholarly journals Comparison of latency and rate coding for the direction of whisker deflection in the subcortical somatosensory pathway

2012 ◽  
Vol 108 (7) ◽  
pp. 1810-1821 ◽  
Author(s):  
Riccardo Storchi ◽  
Michael R. Bale ◽  
Gabriele E. M. Biella ◽  
Rasmus S. Petersen
Keyword(s):  
Somatosensory System ◽  
Stimulus Onset ◽  
Spike Timing ◽  
Spike Count ◽  
Metabolic Efficiency ◽  
Neural Codes ◽  
Sensory Afferents ◽  
Population Activity ◽  
Additional Information ◽  
Spike Latency

The response of many neurons in the whisker somatosensory system depends on the direction in which a whisker is deflected. Although it is known that the spike count conveys information about this parameter, it is not known how important spike timing might be. The aim of this study was to compare neural codes based on spike count and first-spike latency, respectively. We extracellularly recorded single units from either the rat trigeminal ganglion (primary sensory afferents) or ventroposteromedial (VPM) thalamic nucleus in response to deflection in different directions and quantified alternative neural codes using mutual information. We found that neurons were diverse: some (58% in ganglion, 32% in VPM) conveyed information only by spike count; others conveyed additional information by latency. An issue with latency coding is that latency is measured with respect to the time of stimulus onset, a quantity known to the experimenter but not directly to the subject's brain. We found a potential solution using the integrated population activity as an internal timing signal: in this way, 91% of the first-spike latency information could be recovered. Finally, we asked how well direction could be decoded. For large populations, spike count and latency codes performed similarly; for small ones, decoding was more accurate using the latency code. Our findings indicate that whisker deflection direction is more efficiently encoded by spike timing than by spike count. Spike timing decreases the population size necessary for reliable information transmission and may thereby bring significant advantages in both wiring and metabolic efficiency.

Cortical Representation of Auditory Space: Information-Bearing Features of Spike Patterns

2002 ◽  
Vol 87 (4) ◽  
pp. 1749-1762 ◽  
Author(s):  
Shigeto Furukawa ◽  
John C. Middlebrooks
Keyword(s):  
Sound Source ◽  
Neuronal Response ◽  
Source Location ◽  
Spike Timing ◽  
Spike Count ◽  
Cortical Representation ◽  
Auditory Space ◽  
Transmitted Information ◽  
Related Information ◽  
Spike Patterns

Previous studies have demonstrated that the spike patterns of cortical neurons vary systematically as a function of sound-source location such that the response of a single neuron can signal the location of a sound source throughout 360° of azimuth. The present study examined specific features of spike patterns that might transmit information related to sound-source location. Analysis was based on responses of well-isolated single units recorded from cortical area A2 in α-chloralose-anesthetized cats. Stimuli were 80-ms noise bursts presented from loudspeakers in the horizontal plane; source azimuths ranged through 360° in 20° steps. Spike patterns were averaged across samples of eight trials. A competitive artificial neural network (ANN) identified sound-source locations by recognizing spike patterns; the ANN was trained using the learning vector quantization learning rule. The information about stimulus location that was transmitted by spike patterns was computed from joint stimulus-response probability matrices. Spike patterns were manipulated in various ways to isolate particular features. Full-spike patterns, which contained all spike-count information and spike timing with 100-μs precision, transmitted the most stimulus-related information. Transmitted information was sensitive to disruption of spike timing on a scale of more than ∼4 ms and was reduced by an average of ∼35% when spike-timing information was obliterated entirely. In a condition in which all but the first spike in each pattern were eliminated, transmitted information decreased by an average of only ∼11%. In many cases, that condition showed essentially no loss of transmitted information. Three unidimensional features were extracted from spike patterns. Of those features, spike latency transmitted ∼60% more information than that transmitted either by spike count or by a measure of latency dispersion. Information transmission by spike patterns recorded on single trials was substantially reduced compared with the information transmitted by averages of eight trials. In a comparison of averaged and nonaveraged responses, however, the information transmitted by latencies was reduced by only ∼29%, whereas information transmitted by spike counts was reduced by 79%. Spike counts clearly are sensitive to sound-source location and could transmit information about sound-source locations. Nevertheless, the present results demonstrate that the timing of the first poststimulus spike carries a substantial amount, probably the majority, of the location-related information present in spike patterns. The results indicate that any complete model of the cortical representation of auditory space must incorporate the temporal characteristics of neuronal response patterns.

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 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.

Band-Pass Response Properties of Rat SI Neurons

2003 ◽  
Vol 90 (3) ◽  
pp. 1379-1391 ◽  
Author(s):  
Catherine E. Garabedian ◽  
Stephanie R. Jones ◽  
Michael M. Merzenich ◽  
Anders Dale ◽  
Christopher I. Moore
Keyword(s):  
Inhibitory Neuron ◽  
Stimulus Onset ◽  
Spike Timing ◽  
Spike Rate ◽  
Frequency Range ◽  
Response Properties ◽  
Temporal Precision ◽  
Band Pass ◽  
Temporal Measures ◽  
Vector Strength

Rats typically employ 4- to 12-Hz “whisking” movements of their vibrissae during tactile exploration. The intentional sampling of signals in this frequency range suggests that neural processing of tactile information may be differentially engaged in this bandwidth. We examined action potential responses in rat primary somatosensory cortex (SI) to a range of frequencies of vibrissa motion. Single vibrissae were mechanically deflected with 5-s pulse trains at rates ≤40 Hz. As previously reported, vibrissa deflection evoked robust neural responses that consistently adapted to stimulus rates ≥3 Hz. In contrast with this low-pass feature of the response, several other characteristics of the response revealed bandpass response properties. While average evoked response amplitudes measured 0–35 ms after stimulus onset typically decreased with increasing frequency, the later components of the response (>15 ms post stimulus) were augmented at frequencies between 3 and 10 Hz. Further, during the steady state, both rate and temporal measures of neural activity, measured as total spike rate or vector strength (a measure of temporal fidelity of spike timing across cycles), showed peak signal values at 5–10 Hz. A minimal biophysical network model of SI layer IV, consisting of an excitatory and inhibitory neuron and thalamocortical input, captured the spike rate and vector strength band-pass characteristics. Further analyses in which specific elements were selectively removed from the model suggest that slow inhibitory influences give rise to the band-pass peak in temporal precision, while thalamocortical adaptation can account for the band-pass peak in spike rate. The presence of these band-pass characteristics may be a general property of thalamocortical circuits that lead rodents to target this frequency range with their whisking behavior.

scholarly journals Computational Role of Large Receptive Fields in the Primary Somatosensory Cortex

2008 ◽  
Vol 100 (1) ◽  
pp. 268-280 ◽  
Author(s):  
Guglielmo Foffani ◽  
John K. Chapin ◽  
Karen A. Moxon
Keyword(s):  
Somatosensory Cortex ◽  
Receptive Fields ◽  
Spike Timing ◽  
Spike Count ◽  
Primary Somatosensory Cortex ◽  
Single Neurons ◽  
Tuning Curves ◽  
Tactile Stimuli ◽  
Somatosensory Information

Computational studies are challenging the intuitive view that neurons with broad tuning curves are necessarily less discriminative than neurons with sharp tuning curves. In the context of somatosensory processing, broad tuning curves are equivalent to large receptive fields. To clarify the computational role of large receptive fields for cortical processing of somatosensory information, we recorded ensembles of single neurons from the infragranular forelimb/forepaw region of the rat primary somatosensory cortex while tactile stimuli were separately delivered to different locations on the forelimbs/forepaws under light anesthesia. We specifically adopted the perspective of individual columns/segregates receiving inputs from multiple body location. Using single-trial analyses of many single-neuron responses, we obtained two main results. 1) The responses of even small populations of neurons recorded from within the same estimated column/segregate can be used to discriminate between stimuli delivered to different surround locations in the excitatory receptive fields. 2) The temporal precision of surround responses is sufficiently high for spike timing to add information over spike count in the discrimination between surround locations. This surround spike-timing code (i) is particularly informative when spike count is ambiguous, e.g., in the discrimination between close locations or when receptive fields are large, (ii) becomes progressively more informative as the number of neurons increases, (iii) is a first-spike code, and (iv) is not limited by the assumption that the time of stimulus onset is known. These results suggest that even though large receptive fields result in a loss of spatial selectivity of single neurons, they can provide as a counterpart a sophisticated temporal code based on latency differences in large populations of neurons without necessarily sacrificing basic information about stimulus location.

Lack of Spike-Count and Spike-Time Correlations in the Substantia Nigra Reticulata Despite Overlap of Neural Responses

2007 ◽  
Vol 98 (4) ◽  
pp. 2232-2243 ◽  
Author(s):  
Alon Nevet ◽  
Genela Morris ◽  
Guy Saban ◽  
David Arkadir ◽  
Hagai Bergman
Keyword(s):  
Basal Ganglia ◽  
Substantia Nigra ◽  
Information Transfer ◽  
Spike Timing ◽  
Spike Count ◽  
Unique Event ◽  
Correlated Activity ◽  
Different Types ◽  
Substantia Nigra Reticulata ◽  
Response Task

Previous studies of single neurons in the substantia nigra reticulata (SNr) have shown that many of them respond to similar events. These results, as well as anatomical studies, suggest that SNr neurons share inputs and thus may have correlated activity. Different types of correlation can exist between pairs of neurons. These are traditionally classified as either spike-count (“signal” and “noise”) or spike-timing (spike-to-spike and joint peristimulus time histograms) correlations. These measures of neuronal correlation are partially independent and have different implications. Our purpose was to probe the computational characteristics of the basal ganglia output nuclei through an analysis of these different types of correlation in the SNr. We carried out simultaneous multiple-electrode single-unit recordings in the SNr of two monkeys performing a probabilistic delayed visuomotor response task. A total of 113 neurons (yielding 355 simultaneously recorded pairs) were studied. Most SNr neurons responded to one or more task-related events, with instruction cue (69%) and reward (63%) predominating. Response-match analysis, comparing peristimulus time histograms, revealed a significant overlap between response vectors. However, no measure of average correlation differed significantly from zero. The lack of significant SNr spike-count population correlations appears to be an exceptional phenomenon in the brain, perhaps indicating unique event-related processing by basal ganglia output neurons to achieve better information transfer. The lack of spike-timing correlations suggests that the basal high-frequency discharge of SNr neurons is not driven by the common inputs and is probably intrinsic.

scholarly journals Temporal coding of taste in the parabrachial nucleus of the pons of the rat

2011 ◽  
Vol 105 (4) ◽  
pp. 1889-1896 ◽  
Author(s):  
Andrew M. Rosen ◽  
Jonathan D. Victor ◽  
Patricia M. Di Lorenzo
Keyword(s):  
Time Course ◽  
Temporal Dynamics ◽  
Spike Timing ◽  
Temporal Coding ◽  
Taste Quality ◽  
Spike Count ◽  
Parabrachial Nucleus ◽  
Similar Proportion ◽  
Temporal Characteristics ◽  
Temporal Precision

Recent studies have provided evidence that temporal coding contributes significantly to encoding taste stimuli at the first central relay for taste, the nucleus of the solitary tract (NTS). However, it is not known whether this coding mechanism is also used at the next synapse in the central taste pathway, the parabrachial nucleus of the pons (PbN). In the present study, electrophysiological responses to taste stimuli (sucrose, NaCl, HCl, and quinine) were recorded from 44 cells in the PbN of anesthetized rats. In 29 cells, the contribution of the temporal characteristics of the response to the discrimination of various taste qualities was assessed. A family of metrics that quantifies the similarity of two spike trains in terms of spike count and spike timing was used. Results showed that spike timing in 14 PbN cells (48%) conveyed a significant amount of information about taste quality, beyond what could be conveyed by spike count alone. In another 14 cells (48%), the rate envelope (time course) of the response contributed significantly more information than spike count alone. Across cells there was a significant correlation ( r = 0.51; P < 0.01) between breadth of tuning and the proportion of information conveyed by temporal dynamics. Comparison with previous data from the NTS (Di Lorenzo PM and Victor JD. J Neurophysiol 90: 1418–31, 2003 and J Neurophysiol 97: 1857–1861, 2007) showed that temporal coding in the NTS occurred in a similar proportion of cells and contributed a similar fraction of the total information at the same average level of temporal precision, even though trial-to-trial variability was higher in the PbN than in the NTS. These data suggest that information about taste quality conveyed by the temporal characteristics of evoked responses is transmitted with high fidelity from the NTS to the PbN.

500–1000 Hz Responses in the Somatosensory System: Approaching Generators and Function

2005 ◽  
Vol 36 (4) ◽  
pp. 293-305 ◽  
Author(s):  
Fabian Klostermann
Keyword(s):  
Evoked Potentials ◽  
Somatosensory System ◽  
Clinical Applications ◽  
The Body ◽  
Wide Scope ◽  
Population Activity ◽  
Cellular Origin ◽  
Oscillatory Eeg ◽  
And Function ◽  
Somatosensory Coding

Spontaneous and stimulus-induced oscillatory EEG activities range over a wide scope of frequencies from 1 Hz to 1 kHz. In the ultrafast domain, trains of 5–10 micro-potentials are superimposed to primary thalamic and cortical components in somtosensory evoked potentials (SEP) as brief bursts of 1000 Hz and 600 Hz, respectively. Over the last years, hypotheses on generators and functions of this frequency-edge of population activity have been elaborated in numerous studies. Here, the relevant findings and ideas were surveyed from the body of literature. Special emphasis was paid to the anatomical and cellular origin of burst SEP, their assumed impact on somatosensory coding and perspectives for scientific as well as clinical applications.

scholarly journals Motor-induced Suppression of the Auditory Cortex

2009 ◽  
Vol 21 (4) ◽  
pp. 791-802 ◽  
Author(s):  
Sheye O. Aliu ◽  
John F. Houde ◽  
Srikantan S. Nagarajan
Keyword(s):  
Auditory Cortex ◽  
Auditory System ◽  
Somatosensory System ◽  
Motor Command ◽  
Stimulus Onset ◽  
Button Press ◽  
Motor Processing ◽  
Sensory Motor ◽  
Sensory Responses ◽  
And Control

Sensory responses to stimuli that are triggered by a self-initiated motor act are suppressed when compared with the response to the same stimuli triggered externally, a phenomenon referred to as motor-induced suppression (MIS) of sensory cortical feedback. Studies in the somatosensory system suggest that such suppression might be sensitive to delays between the motor act and the stimulus onset, and a recent study in the auditory system suggests that such MIS develops rapidly. In three MEG experiments, we characterize the properties of MIS by examining the M100 response from the auditory cortex to a simple tone triggered by a button press. In Experiment 1, we found that MIS develops for zero delays but does not generalize to nonzero delays. In Experiment 2, we found that MIS developed for 100-msec delays within 300 trials and occurs in excess of auditory habituation. In Experiment 3, we found that unlike MIS for zero delays, MIS for nonzero delays does not exhibit sensitivity to sensory, delay, or motor-command changes. These results are discussed in relation to suppression to self-produced speech and a general model of sensory motor processing and control.

scholarly journals Continuous multiplexed population representations of task context in the mouse primary visual cortex

2021 ◽  
Author(s):  
Marton Albert Hajnal ◽  
Duy Tran ◽  
Michael Einstein ◽  
Mauricio Vallejo Martelo ◽  
Karen Safaryan ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Activity Patterns ◽  
Visual Stimuli ◽  
Stimulus Onset ◽  
Decision Task ◽  
Cognitive Variables ◽  
Task Context ◽  
Population Activity ◽  
V1 Neurons

Primary visual cortex (V1) neurons integrate motor and multisensory information with visual inputs during sensory processing. However, whether V1 neurons also integrate and encode higher-order cognitive variables is less understood. We trained mice to perform a context-dependent cross-modal decision task where the interpretation of identical audio-visual stimuli depends on task context. We performed silicon probe population recordings of neuronal activity in V1 during task performance and showed that task context (whether the animal should base its decision on visual or auditory stimuli) can be decoded during both intertrial intervals and stimulus presentations. Context and visual stimuli were represented in overlapping populations but were orthogonal in the population activity space. Context representation was not static but displayed distinctive dynamics upon stimulus onset and offset. Thus, activity patterns in V1 independently represent visual stimuli and cognitive variables relevant to task execution.

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