Total Spike Count Research Articles

Vortioxetine suppresses epileptiform activity and cognition deficits in a chronic PTZ-induced kindling rat model.

This study aimed to examine the effects of vortioxetine, a novel antidepressant, on epileptiform activity in pentylenetetrazole (PTZ)-induced kindling model in rats. For this purpose, 20 male Wistar Albino rats were used, and epileptiform activity was induced by injection of PTZ (35mg/kg, i.p., three times a week). In the vortioxetine groups, vortioxetine (5mg/kg and 10mg/kg) was administered before the kindling process. During the kindling process, the Fisher and Kittner seizure scales were used to score seizure severity. After kindling, novel object recognition (NOR) tests were performed to evaluate the cognitive performance of rats. Electrodes were implanted into the fully kindled animals for ECoG recordings. In the PTZ group, the number of total spikes was 1367±136 spikes/20minutes. First myoclonic jerks decreased while seizure severity and total spike count increased in the PTZ group. On the other hand, the total spike number and seizure severity significantly decreased and first myoclonic jerks increased in the vortioxetine groups compared to the PTZ group. Based on the NOR test, vortioxetine administration markedly raised the discrimination index compared to the PTZ group. Electrophysiological and behavioural data from the present study suggest that vortioxetine, a novel drug, plays a critical role in controlling PTZ-induced epileptiform activity in rats. Vortioxetine may therefore be a valuable candidate to prevent seizure activity and treat cognitive deficits associated with epilepsy.

Pinpointing the neural signatures of single-exposure visual recognition memory

Memories of the images that we have seen are thought to be reflected in the reduction of neural responses in high-level visual areas such as inferotemporal (IT) cortex, a phenomenon known as repetition suppression (RS). We challenged this hypothesis with a task that required rhesus monkeys to report whether images were novel or repeated while ignoring variations in contrast, a stimulus attribute that is also known to modulate the overall IT response. The monkeys' behavior was largely contrast invariant, contrary to the predictions of an RS-inspired decoder, which could not distinguish responses to images that are repeated from those that are of lower contrast. However, the monkeys' behavioral patterns were well predicted by a linearly decodable variant in which the total spike count was corrected for contrast modulation. These results suggest that the IT neural activity pattern that best aligns with single-exposure visual recognition memory behavior is not RS but rather sensory referenced suppression: reductions in IT population response magnitude, corrected for sensory modulation.

Odor Concentration Change Coding in the Olfactory Bulb.

Dynamical changes in the environment strongly impact our perception. Likewise, sensory systems preferentially represent stimulus changes, enhancing temporal contrast. In olfaction, odor concentration changes across consecutive inhalations (ΔCt) can guide odor source localization, yet the neural representation of ΔCt has not been studied in vertebrates. We have found that, in the mouse olfactory bulb, a subset of mitral/tufted (M/T) cells represents ΔCt, enhancing the contrast between different concentrations. These concentration change responses are direction selective: they respond either to increments or decrements of concentration, reminiscent of ON and OFF selectivity in the retina. This contrast enhancement scales with the magnitude, but not the duration of the concentration step. Further, ΔCt can be read out from the total spike count per sniff, unlike odor identity and intensity, which are represented by fast temporal spike patterns. Our results demonstrate that a subset of M/T cells represents ΔCt, providing a signal that may instruct navigational decisions in downstream olfactory circuits.

Single-exposure visual memory judgments are reflected in inferotemporal cortex

Our visual memory percepts of whether we have encountered specific objects or scenes before are hypothesized to manifest as decrements in neural responses in inferotemporal cortex (IT) with stimulus repetition. To evaluate this proposal, we recorded IT neural responses as two monkeys performed a single-exposure visual memory task designed to measure the rates of forgetting with time. We found that a weighted linear read-out of IT was a better predictor of the monkeys' forgetting rates and reaction time patterns than a strict instantiation of the repetition suppression hypothesis, expressed as a total spike count scheme. Behavioral predictions could be attributed to visual memory signals that were reflected as repetition suppression and were intermingled with visual selectivity, but only when combined across the most sensitive neurons.

How Much Does Movement and Location Encoding Impact Prefrontal Cortex Activity? An Algorithmic Decoding Approach in Freely Moving Rats.

Specialized brain structures encode spatial locations and movements, yet there is growing evidence that this information is also represented in the rodent medial prefrontal cortex (mPFC). Disambiguating such information from the encoding of other types of task-relevant information has proven challenging. To determine the extent to which movement and location information is relevant to mPFC neurons, tetrodes were used to record neuronal activity while limb positions, poses (i.e., recurring constellations of limb positions), velocity, and spatial locations were simultaneously recorded with two cameras every 200 ms as rats freely roamed in an experimental enclosure. Regression analyses using generalized linear models revealed that more than half of the individual mPFC neurons were significantly responsive to at least one of the factors, and many were responsive to more than one. On the other hand, each factor accounted for only a very small portion of the total spike count variance of any given neuron (<20% and typically <1%). Machine learning methods were used to analyze ensemble activity and revealed that ensembles were usually superior to the sum of the best neurons in encoding movements and spatial locations. Because movement and location encoding by individual neurons was so weak, it may not be such a concern for single-neuron analyses. Yet because these weak signals were so widely distributed across the population, this information was strongly represented at the ensemble level and should be considered in population analyses.

Prolonged stimulation with low-intensity ultrasound induces delayed increases in spontaneous hippocampal culture spiking activity.

Ultrasound is a promising neural stimulation modality, but an incomplete understanding of its range and mechanism of effect limits its therapeutic application. We investigated the modulation of spontaneous hippocampal spike activity by ultrasound at a lower acoustic intensity and longer time scale than has been previously attempted, hypothesizing that spiking would change conditionally upon the availability of glutamate receptors. Using a 60-channel multielectrode array (MEA), we measured spontaneous spiking across organotypic rat hippocampal slice cultures (N = 28) for 3 min each before, during, and after stimulation with low-intensity unfocused pulsed or sham ultrasound (spatial-peak pulse average intensity 780 μW/cm2 ) preperfused with artificial cerebrospinal fluid, 300 μM kynurenic acid (KA), or 0.5 μM tetrodotoxin (TTX) at 3 ml/min. Spike rates were normalized and compared across stimulation type and period, subregion, threshold level, and/or perfusion condition using repeated-measures ANOVA and generalized linear mixed models. Normalized 3-min spike counts for large but not midsized, small, or total spikes increased after but not during ultrasound relative to sham stimulation. This result was recapitulated in subregions CA1 and dentate gyrus and replicated in a separate experiment for all spike size groups in slices pretreated with aCSF but not KA or TTX. Increases in normalized 18-sec total, midsized, and large spike counts peaked predominantly 1.5 min following ultrasound stimulation. Our low-intensity ultrasound setup exerted delayed glutamate receptor-dependent, amplitude- and possibly region-specific influences on spontaneous spike rates across the hippocampus, expanding the range of known parameters at which ultrasound may be used for neural activity modulation. © 2016 Wiley Periodicals, Inc.

Commentary: Burst Firing in a Motion-Sensitive Neural Pathway Correlates with Expansion Properties of Looming Objects That Evoke Avoidance Behaviors.

Commentary: Burst Firing in a Motion-Sensitive Neural Pathway Correlates with Expansion Properties of Looming Objects That Evoke Avoidance Behaviors.

The Retinal Response to Sinusoidal Electrical Stimulation.

Rectangular electrical pulses are the primary stimulus waveform used in retinal prosthetics as well as many other neural stimulation applications. Unfortunately, the utility of pulsatile stimuli is limited by the inability to avoid the activation of passing axons, which can result in the distortion of the spatial patterns of elicited neural activity. Because avoiding axons would likely improve clinical outcomes, the examination of alternate stimulus waveforms is warranted. Here, we studied the response of rabbit retinal ganglion cells (RGCs) to sinusoidal electrical stimulation applied at frequencies of 5, 10, 25, and 100 Hz. Targeted RGCs were restricted to 4 common types: OFF-Brisk Transient, OFF-Sustained, ON-Brisk Transient, and ON-Sustained. Interestingly, response patterns varied between different types; the most notable difference was the relatively weak response of ON-Sustained cells to low frequencies. Calculation of total spike counts per trial revealed that lower frequencies are more charge efficient than high frequencies. Finally, experiments utilizing synaptic blockers revealed that 5 and 10 Hz activate photoreceptors while 25 and 100 Hz activate RGCs. Taken together, our results suggest that while sinusoidal electrical stimulation may provide a useful research tool, its clinical utility may be limited.

Spatiotemporal conditional inference and hypothesis tests for neural ensemble spiking precision.

The collective dynamics of neural ensembles create complex spike patterns with many spatial and temporal scales. Understanding the statistical structure of these patterns can help resolve fundamental questions about neural computation and neural dynamics. Spatiotemporal conditional inference (STCI) is introduced here as a semiparametric statistical framework for investigating the nature of precise spiking patterns from collections of neurons that is robust to arbitrarily complex and nonstationary coarse spiking dynamics. The main idea is to focus statistical modeling and inference not on the full distribution of the data, but rather on families of conditional distributions of precise spiking given different types of coarse spiking. The framework is then used to develop families of hypothesis tests for probing the spatiotemporal precision of spiking patterns. Relationships among different conditional distributions are used to improve multiple hypothesis-testing adjustments and design novel Monte Carlo spike resampling algorithms. Of special note are algorithms that can locally jitter spike times while still preserving the instantaneous peristimulus time histogram or the instantaneous total spike count from a group of recorded neurons. The framework can also be used to test whether first-order maximum entropy models with possibly random and time-varying parameters can account for observed patterns of spiking. STCI provides a detailed example of the generic principle of conditional inference, which may be applicable to other areas of neurostatistical analysis.

Encoding frequency contrast in primate auditory cortex

Changes in amplitude and frequency jointly determine much of the communicative significance of complex acoustic signals, including human speech. We have previously described responses of neurons in the core auditory cortex of awake rhesus macaques to sinusoidal amplitude modulation (SAM) signals. Here we report a complementary study of sinusoidal frequency modulation (SFM) in the same neurons. Responses to SFM were analogous to SAM responses in that changes in multiple parameters defining SFM stimuli (e.g., modulation frequency, modulation depth, carrier frequency) were robustly encoded in the temporal dynamics of the spike trains. For example, changes in the carrier frequency produced highly reproducible changes in shapes of the modulation period histogram, consistent with the notion that the instantaneous probability of discharge mirrors the moment-by-moment spectrum at low modulation rates. The upper limit for phase locking was similar across SAM and SFM within neurons, suggesting shared biophysical constraints on temporal processing. Using spike train classification methods, we found that neural thresholds for modulation depth discrimination are typically far lower than would be predicted from frequency tuning to static tones. This "dynamic hyperacuity" suggests a substantial central enhancement of the neural representation of frequency changes relative to the auditory periphery. Spike timing information was superior to average rate information when discriminating among SFM signals, and even when discriminating among static tones varying in frequency. This finding held even when differences in total spike count across stimuli were normalized, indicating both the primacy and generality of temporal response dynamics in cortical auditory processing.

Cortical neural populations can guide behavior by integrating inputs linearly, independent of synchrony

Neurons are sensitive to the relative timing of inputs, both because several inputs must coincide to reach spike threshold and because active dendritic mechanisms can amplify synchronous inputs. To determine if input synchrony can influence behavior, we trained mice to report activation of excitatory neurons in visual cortex using channelrhodopsin-2. We used light pulses that varied in duration from a few milliseconds to 100 ms and measured neuronal responses and animals' detection ability. We found detection performance was well predicted by the total amount of light delivered. Short pulses provided no behavioral advantage, even when they concentrated evoked spikes into an interval a few milliseconds long. Arranging pulses into trains of varying frequency from beta to gamma also produced no behavioral advantage. Light intensities required to drive behavior were low (at low intensities, channelrhodopsin-2 conductance varies linearly with intensity), and the accompanying changes in firing rate were small (over 100 ms, average change: 1.1 spikes per s). Firing rate changes varied linearly with pulse intensity and duration, and behavior was predicted by total spike count independent of temporal arrangement. Thus, animals' detection performance reflected the linear integration of total input over 100 ms. This behavioral linearity despite neurons' nonlinearities can be explained by a population code using noisy neurons. Ongoing background activity creates probabilistic spiking, allowing weak inputs to change spike probability linearly, with little amplification of coincident input. Summing across a population then yields a total spike count that weights inputs equally, regardless of their arrival time.

Energy-efficient encoding by shifting spikes in neocortical neurons

The speed of computations in neocortical networks critically depends on the ability of populations of spiking neurons to rapidly detect subtle changes in the input and translate them into firing rate changes. However, high sensitivity to perturbations may lead to explosion of noise and increased energy consumption. Can neuronal networks reconcile the requirements for high sensitivity, operation in a low-noise regime, and constrained energy consumption? Using intracellular recordings in slices from the rat visual cortex, we show that layer 2/3 pyramidal neurons are highly sensitive to minor input perturbations. They can change their population firing rate in response to small artificial excitatory postsynaptic currents (aEPSCs) immersed in fluctuating noise very quickly, within 2-2.5ms. These quick responses were mediated by the generation of new, additional action potentials (APs), but also by shifting spikes into the response peak. In that latter case, the spike count increase during the peak and the decrease after the peak cancelled each other, thus producing quick responses without increases in total spike count and associated energy costs. The contribution of spikes from one or the other source depended on the aEPSCs timing relative to the waves of depolarization produced by ongoing activity. Neurons responded by shifting spikes to aEPSCs arriving at the beginning of a depolarization wave, but generated additional spikes in response to aEPSCs arriving towards the end of a wave. We conclude that neuronal networks can combine high sensitivity to perturbations and operation in a low-noise regime. Moreover, certain patterns of ongoing activity favor this combination and energy-efficient computations.

Neural coding in the Non-Pacinian I tactile channel: A psychophysical and simulation study of magnitude estimation

Psychophysical experiments and model simulations were performed to identify plausible neural codes representing stimulus magnitude in the Non-Pacinian I (NP I) tactile channel associated with rapidly adapting fibers. Sinusoidal mechanical displacements were applied on the fingertips of eight human subjects. The NP I channel was isolated by elevating the thresholds of the Pacinian (P) channel during forward masking. Psychophysical magnitude estimates were obtained at 40 Hz for the NP I channel and at 250 Hz for the P channel by using a small contactor (radius: 2 mm). The P channel was additionally tested with a larger contactor (radius: 4.3 mm) to compensate for the lower innervation density of the Pacinian fibers. The magnitude estimates were fitted by power functions. The exponent (1.02) obtained with the large contactor for the P channel was higher than the exponent (0.68) obtained with the small contactor, but it was not statistically different from the exponent (1.21) obtained with the small contactor for the NP I channel. This suggests that the exponent increases when more fibers are recruited in the P channel. Six hypothetical neural codes were tested by using a computational population model for the rapidly adapting afferents. The validity of each code was evaluated by comparing psychophysical and simulation exponents, by finding the correlations between the magnitude estimates and the neural code results, and by a novel distance metric for measuring the proximity between the data sets. The codes based on the number of active fibers, the total spike count, the mean and the standard deviation of the spike count distribution yielded the best results, while the codes based on the interspike intervals were not related with the magnitude estimates.

A procedure for testing across-condition rhythmic spike-field association change

Many experiments in neuroscience have compared the strength of association between neural spike trains and rhythms present in local field potential (LFP) recordings. The measure employed in these comparisons, “spike-field coherence”, is a frequency dependent measure of linear association, and is shown to depend on overall neural activity (Lepage et al., 2011). Dependence upon overall neural activity, that is, dependence upon the total number of spikes, renders comparison of spike-field coherence across experimental context difficult. In this paper, an inferential procedure based upon a generalized linear model is shown to be capable of separating the effects of overall neural activity from spike train-LFP oscillatory coupling. This separation provides a means to compare the strength of oscillatory association between spike train-LFP pairs independent of differences in spike counts.Following a review of the generalized linear modelling framework of point process neural activity a specific class of generalized linear models are introduced. This model class, using either a piece-wise constant link function, or an exponential function to relate an LFP rhythm to neural response, is used to develop hypothesis tests capable of detecting changes in spike train-LFP oscillatory coupling. The performance of these tests is validated, both in simulation and on real data. The proposed method of inference provides a principled statistical procedure by which across-context change in spike train-LFP rhythmic association can be directly inferred that explicitly handles between-condition differences in total spike count.

Timescale-Invariant Representation of Acoustic Communication Signals by a Bursting Neuron

Acoustic communication often involves complex sound motifs in which the relative durations of individual elements, but not their absolute durations, convey meaning. Decoding such signals requires an explicit or implicit calculation of the ratios between time intervals. Using grasshopper communication as a model, we demonstrate how this seemingly difficult computation can be solved in real time by a small set of auditory neurons. One of these cells, an ascending interneuron, generates bursts of action potentials in response to the rhythmic syllable-pause structure of grasshopper calls. Our data show that these bursts are preferentially triggered at syllable onset; the number of spikes within the burst is linearly correlated with the duration of the preceding pause. Integrating the number of spikes over a fixed time window therefore leads to a total spike count that reflects the characteristic syllable-to-pause ratio of the species while being invariant to playing back the call faster or slower. Such a timescale-invariant recognition is essential under natural conditions, because grasshoppers do not thermoregulate; the call of a sender sitting in the shade will be slower than that of a grasshopper in the sun. Our results show that timescale-invariant stimulus recognition can be implemented at the single-cell level without directly calculating the ratio between pulse and interpulse durations.

Deviation from Weber's Law in the Non-Pacinian I Tactile Channel: A Psychophysical and Simulation Study of Intensity Discrimination

This study involves psychophysical experiments and computer simulations to investigate intensity discrimination in the non-Pacinian I (NP I) tactile channel. The simulations were based on an established population model for rapidly adapting mechanoreceptive fibers (Güuçlü & Bolanowski, 2004a). Several intensity codes were tested as decision criteria: number of active neurons, total spike count, maximal spike count, distribution of spike counts among the afferent population, and synchronization of spike times. Simulations that used the number of active fibers as the intensity code gave the most accurate results. However, the Weber fractions obtained from simulations are smaller than psychophysical Weber fractions, which suggests that only a subset of the afferent population is recruited for intensity discrimination during psychophysical experiments. Simulations could also capture the deviation from Weber's law, that is, the decrease of the Weber fraction as a function of the stimulus level, which was present in the psychophysical data. Since the psychophysical task selectively activated the NP I channel, the deviation effect is probably not due to the contribution of another tactile channel but rather is explicitly produced by the NP I channel. Moreover, because simulations with all tested intensity codes resulted in the same effect, the activity of the afferent population is sufficient to explain the deviation, without the need for a higher-order network. Depending on the intensity code used, the mechanical spread of the stimulus, rate-intensity functions of the tactile fibers, and the decreasing spike-phase jitter contribute to the deviation from Weber's law.

Correlated firing improves stimulus discrimination in a retinal model.

Synchronous firing limits the amount of information that can be extracted by averaging the firing rates of similarly tuned neurons. Here, we show that the loss of such rate-coded information due to synchronous oscillations between retinal ganglion cells can be overcome by exploiting the information encoded by the correlations themselves. Two very different models, one based on axon-mediated inhibitory feedback and the other on oscillatory common input, were used to generate artificial spike trains whose synchronous oscillations were similar to those measured experimentally. Pooled spike trains were summed into a threshold detector whose output was classified using Bayesian discrimination. For a threshold detector with short summation times, realistic oscillatory input yielded superior discrimination of stimulus intensity compared to rate-matched Poisson controls. Even for summation times too long to resolve synchronous inputs, gamma band oscillations still contributed to improved discrimination by reducing the total spike count variability, or Fano factor. In separate experiments in which neurons were synchronized in a stimulus-dependent manner without attendant oscillations, the Fano factor increased markedly with stimulus intensity, implying that stimulus-dependent oscillations can offset the increased variability due to synchrony alone.

Analysis of spatiotemporal patterns in a model of olfaction

We model spatiotemporal patterns in locust olfaction with the dynamic neural filter, a recurrent network that produces spatiotemporal patterns in reaction to sets of constant inputs. We specify, within the model, inputs corresponding to different odors and different concentrations of the same odor. Then we proceed to analyze the resulting spatiotemporal patterns of the neurons of our model. Using SVD we investigate three kinds of data: global spatiotemporal data consisting of neuronal firing patterns over the period of odor presentation, spatial data, i.e. total spike counts during this period, and local spatiotemporal data which are neuronal spikes in single temporal bins.

Weakly Modulated Spike Trains: Significance, Precision, and Correction for Sample Size

Many single-unit electrophysiological studies of visual cortex have investigated strong evoked responses to simple stimuli such as oriented gratings. Experiments involving other types of stimuli, such as natural scenes, higher-order features, and surface brightness, produce single-unit responses that are more difficult to interpret. Experiments with brightness, in particular, evoke single-unit responses that are typically weakly modulated. When the brightness is generated by a visual illusion such as the Cornsweet illusion, statistical tests are often necessary to distinguish true responses from baseline fluctuations. Here, using data collected from cat Areas 17 and 18 in response to real and illusory brightness stimuli, we provide a method for detecting and quantifying weak but significant periodic responses. By randomizing spike trains (via bootstrap methods), we provide confidence levels for response significance, permitting the evaluation of both weak and strong responses. We show that because of a strong dependence on total spike number, response significance can only be appropriately determined with randomized spike trains of similar spike number. Such randomizations can be performed for both stimulus-elicited and spontaneously occurring spike trains. By developing a method for generating randomized modulated spike trains (phase-restricted randomization) from actual recordings, we calculate upper and lower confidence limits of modulated spike trains and describe how measurement precision varies as a function of total spike count. Finally, using this randomization method, we describe how a correction function can be determined to correct for measurement bias introduced at low spike counts. These methods may also be useful in the study of small but potentially significant responses in other systems.

The responses of single units in the inferior colliculus of the guinea pig to damped and ramped sinusoids

Temporal asymmetry can have a pronounced effect on the perception of a sinusoid. For instance, if a sinusoid is amplitude modulated by a decaying exponential that restarts every 50 ms, (a damped sinusoid) listeners report a two-component percept: a tonal component corresponding to the carrier and a drumming component corresponding to the envelope modulation period. When the amplitude modulation is reversed in time (a ramped sinusoid) the perception changes markedly; the tonal component increases while the drumming component decreases. The long-term Fourier energy spectra are identical for damped and ramped sinusoids with the same exponential half-life. Modelling studies suggest that this perceptual asymmetry must occur central to the peripheral stages of auditory processing (Patterson and Irino, 1998). To test this hypothesis, we have recorded the responses of single units in the inferior colliculus of the anaesthetised guinea pig. We divided single units into three groups: onset, on-sustained and sustained, based on their temporal adaptation properties to suprathreshold tone bursts at the unit’s best frequency. The asymmetry observed in the neural responses of single units was quantified in two ways: a simple total spike count measure and a ratio of the tallest bin of the modulation period histogram to the total number of spikes. Responses were more diverse than those observed with similar stimuli in a previous study in the ventral cochlear nucleus (Pressnitzer et al., 2000). The main results were: (1) The shape of the responses of on-sustained units to ramped sinusoids resembled the shape of the responses to damped sinusoids. This is in contrast to the response shapes in the VCN, which were always similar to the stimulating sinusoid. (2) Units classified as onsets often responded only to the damped stimuli. (3) All units display significant asymmetry in discharge rate for at least one of the half-lives tested and 20% showed significant response asymmetry over all of the half-lives tested. (4) A summary population measure of temporal asymmetry based on total spike count reveals the same pattern of results as that obtained psychophysically using the same stimuli (Patterson, 1994a).