Variability Of Neuronal Responses Research Articles

Spontaneous variations in arousal modulate subsequent visual processing and local field potential dynamics in the ferret during quiet wakefulness.

Behavioral states affect neuronal responses throughout the cortex and influence visual processing. Quiet wakefulness (QW) is a behavioral state during which subjects are quiescent but awake and connected to the environment. Here, we examined the effects of pre-stimulus arousal variability on post-stimulus neural activity in the primary visual cortex and posterior parietal cortex in awake ferrets, using pupil diameter as an indicator of arousal. We observed that the power of stimuli-induced alpha (8-12Hz) decreases when the arousal level increases. The peak of alpha power shifts depending on arousal. High arousal increases inter- and intra-areal coherence. Using a simplified model of laminar circuits, we show that this connectivity pattern is compatible with feedback signals targeting infragranular layers in area posterior parietal cortex and supragranular layers in V1. During high arousal, neurons in V1 displayed higher firing rates at their preferred orientations. Broad-spiking cells in V1 are entrained to high-frequency oscillations (>80Hz), whereas narrow-spiking neurons are phase-locked to low- (12-18Hz) and high-frequency (>80Hz) rhythms. These results indicate that the variability and sensitivity of post-stimulus cortical responses and coherence depend on the pre-stimulus behavioral state and account for the neuronal response variability observed during repeated stimulation.

Expectation violations enhance neuronal encoding of sensory information in mouse primary visual cortex

The response of cortical neurons to sensory stimuli is shaped both by past events (adaptation) and the expectation of future events (prediction). Here we employed a visual stimulus paradigm with different levels of predictability to characterise how expectation influences orientation selectivity in the primary visual cortex (V1) of male mice. We recorded neuronal activity using two-photon calcium imaging (GCaMP6f) while animals viewed sequences of grating stimuli which either varied randomly in their orientations or rotated predictably with occasional transitions to an unexpected orientation. For single neurons and the population, there was significant enhancement in the gain of orientation-selective responses to unexpected gratings. This gain-enhancement for unexpected stimuli was prominent in both awake and anaesthetised mice. We implemented a computational model to demonstrate how trial-to-trial variability in neuronal responses were best characterised when adaptation and expectation effects were combined.

Chaotic dynamics in spatially distributed neuronal networks generate population-wide shared variability.

Neural activity in the cortex is highly variable in response to repeated stimuli. Population recordings across the cortex demonstrate that the variability of neuronal responses is shared among large groups of neurons and concentrates in a low dimensional space. However, the source of the population-wide shared variability is unknown. In this work, we analyzed the dynamical regimes of spatially distributed networks of excitatory and inhibitory neurons. We found chaotic spatiotemporal dynamics in networks with similar excitatory and inhibitory projection widths, an anatomical feature of the cortex. The chaotic solutions contain broadband frequency power in rate variability and have distance-dependent and low-dimensional correlations, in agreement with experimental findings. In addition, rate chaos can be induced by globally correlated noisy inputs. These results suggest that spatiotemporal chaos in cortical networks can explain the shared variability observed in neuronal population responses.

Variability of neuronal responses in the posterior superior temporal sulcus predicts choice behavior during social interactions.

Recent studies have shown that neural activity in a well-defined patch in the posterior superior temporal sulcus (the "gaze-following patch," GFP) of the primate brain is strongly modulated when the other's gaze attracts the observer's attention to locations/objects, the other is looking at. Changes of the mean discharge rate of neurons in the monkey GFP indicate that they are involved in two distinct computations: the allocation of spatial attention guided by the other's gaze vector and the suppression of gaze following if inappropriate in a given situation. Here, we asked if and how the discharge variability of neurons in the GFP is related to the task and if it carries information on behavioral performance. To this end, we calculated the Fano factor as a measure of across-trial discharge variability as a function of time. Our results show that all neurons exhibiting a task-related discharge-rate modulation also exhibit a stimulus onset-dependent drop in the Fano factor. Furthermore, the amplitude of the Fano factor reduction is modulated by task condition and the neuron's selectivity in this regard. We found that these effects are directly related to the monkeys' behavioral performance in that the Fano factor is predictive about upcoming correct or wrong decisions. Our results indicate that neuronal discharge variability as gauged by the Fano factor, hitherto primarily studied in the context of visual perception or motor control, is an informative measure also in studies of the neural underpinnings of complex social behavior.NEW & NOTEWORTHY Quenching of neural variability following stimulus onset is a widely accepted phenomenon. However, the relevance of quenching for the shaping of complex social behaviors remains to be explored. Here, we show that task selective neurons in the GFP exhibit a higher degree of variability quenching than their neighboring unselective neurons. Furthermore, we demonstrate that behavioral errors are not only associated with lower firing rates but also less variability quenching, suggesting that both facilitate optimal performance.

Visual exposure enhances stimulus encoding and persistence in primary cortex

The brain adapts to the sensory environment. For example, simple sensory exposure can modify the response properties of early sensory neurons. How these changes affect the overall encoding and maintenance of stimulus information across neuronal populations remains unclear. We perform parallel recordings in the primary visual cortex of anesthetized cats and find that brief, repetitive exposure to structured visual stimuli enhances stimulus encoding by decreasing the selectivity and increasing the range of the neuronal responses that persist after stimulus presentation. Low-dimensional projection methods and simple classifiers demonstrate that visual exposure increases the segregation of persistent neuronal population responses into stimulus-specific clusters. These observed refinements preserve the representational details required for stimulus reconstruction and are detectable in postexposure spontaneous activity. Assuming response facilitation and recurrent network interactions as the core mechanisms underlying stimulus persistence, we show that the exposure-driven segregation of stimulus responses can arise through strictly local plasticity mechanisms, also in the absence of firing rate changes. Our findings provide evidence for the existence of an automatic, unguided optimization process that enhances the encoding power of neuronal populations in early visual cortex, thus potentially benefiting simple readouts at higher stages of visual processing.

Characterization of the dynamics and variability of neuronal subtype responses during growth, degrowth, and regeneration of Nematostella vectensis

BackgroundThe ability to regenerate body parts is a feature of metazoan organisms and the focus of intense research aiming to understand its basis. A number of mechanisms involved in regeneration, such as proliferation and tissue remodeling, affect whole tissues; however, little is known on how distinctively different constituent cell types respond to the dynamics of regenerating tissues. Preliminary studies suggest that a number of organisms alter neuronal numbers to scale with changes in body size. In some species with the ability of whole-body axis regeneration, it has additionally been observed that regenerates are smaller than their pre-amputated parent, but maintain the correct morphological proportionality, suggesting that scaling of tissue and neuronal numbers also occurs. However, the cell dynamics and responses of neuronal subtypes during nervous system regeneration, scaling, and whole-body axis regeneration are not well understood in any system. The cnidarian sea anemone Nematostella vectensis is capable of whole-body axis regeneration, with a number of observations suggesting the ability to alter its size in response to changes in feeding. We took advantage of Nematostella’s transparent and “simple” body plan and the NvLWamide-like mCherry fluorescent reporter transgenic line to probe the response of neuron populations to variations in body size in vivo in adult animals during body scaling and regeneration.ResultsWe utilized the previously characterized NvLWamide-like::mCherry transgenic reporter line to determine the in vivo response of neuronal subtypes during growth, degrowth, and regeneration. Nematostella alters its size in response to caloric intake, and the nervous system responds by altering neuronal number to scale as the animal changes in size. Neuronal numbers in both the endodermal and ectodermal nerve nets decreased as animals shrunk, increased as they grew, and these changes were reversible. Whole-body axis regeneration resulted in regenerates that were smaller than their pre-amputated size, and the regenerated nerve nets were reduced in neuronal number. Different neuronal subtypes had distinct responses during regeneration, including consistent, not consistent, and conditional increases in number. Conditional responses were regulated, in part, by the size of the remnant fragment and the position of the amputation site. Regenerates and adults with reduced nerve nets displayed normal behaviors, indicating that the nerve net retains functionality as it scales.ConclusionThese data suggest that the Nematostella nerve net is dynamic, capable of scaling with changes in body size, and that neuronal subtypes display differential regenerative responses, which we propose may be linked to the scale state of the regenerating animals.

Erratum: Coen-Cagli and Solomon, "Relating Divisive Normalization to Neuronal Response Variability".

In the article “Relating Divisive Normalization to Neuronal Response Variability” by Ruben Coen-Cagli and Selina S. Solomon, which appeared on pages [7344–7356][1] of the September 11, 2019 issue, the authors report an error in Materials and Methods in Equations 1.11–1.13, concerning the

Neuronal response variability as a product of divisive normalization; neurobiological implications at a macroscale level.

The occurrence of neuronal spikes recorded directly from sensory cortex is highly irregular within and between presentations of an invariant stimulus. The traditional solution has been to average responses across many trials. However, with this approach, response variability is downplayed as noise, so it is assumed that statistically controlling it will reveal the brain's true response to a stimulus. A mounting body of evidence suggests that this approach is inadequate. For example, experiments show that response variability itself varies as a function of stimulus dimensions like contrast and state dimensions like attention. In other words, response variability has structure, is therefore potentially informative and should be incorporated into models which try to explain neural encoding. In this article we provide commentary on a recently published study by Coen-Cagli and Solomon that incorporates spike variability in a quantitative model, by explaining it as a function of divisive normalization. We consider the potential role of neural oscillations in this process as a potential bridge between the current microscale findings and response variability at the mesoscale/macroscale level.

A Simulation Model of Neural Activity During Hand Reaching Movement.

Introduction:The neural response is a noisy random process. The neural response to a sensory stimulus is completely equivalent to a list of spike times in the spike train. In previous studies, decreased neuronal response variability was observed in the cortex’s various areas during motor preparatory in reaching tasks. The reasons for the reduction in Neural Variability (NV) are unclear. It could be influenced by an increased firing rate, or it could result from the intrinsic characteristic of cells during the Reaction Time (RT).Methods:A neural response function with an underlying deterministic instantaneous firing rate signal and a random Poisson process spike generator was simulated in this research. Neural stimulation could help us understand the relationships between the complex data structures of cortical activities and their stability in detail during motor intention in arm-reaching tasks.Results:Our measurements indicated a similar pattern of results to the cortex, a sharp reduction of the normalized variance of simulated spike trains across all trials. We also observed a reverse relationship between activity and normalized variance.Conclusion:The present study findings could be applied to neural engineering and brain-machine interfaces for controlling external devices, like the movement of a robot arm.

Distinct Waking States for Strong Evoked Responses in Primary Visual Cortex and Optimal Visual Detection Performance.

Variability in cortical neuronal responses to sensory stimuli and in perceptual decision making performance is substantial. Moment-to-moment fluctuations in waking state or arousal can account for much of this variability. Yet, this variability is rarely characterized across the full spectrum of waking states, leaving the characteristics of the optimal state for sensory processing unresolved. Using pupillometry in concert with extracellular multiunit and intracellular whole-cell recordings, we found that the magnitude and reliability of visually evoked responses in primary visual cortex (V1) of awake, passively behaving male mice increase as a function of arousal and are largest during sustained locomotion periods. During these high-arousal, sustained locomotion periods, cortical neuronal membrane potential was at its most depolarized and least variable. Contrastingly, behavioral performance of mice on two distinct visual detection tasks was generally best at a range of intermediate arousal levels, but worst during high arousal with locomotion. These results suggest that large, reliable responses to visual stimuli in V1 occur at a distinct arousal level from that associated with optimal visual detection performance. Our results clarify the relation between neuronal responsiveness and the continuum of waking states, and suggest new complexities in the relation between primary sensory cortical activity and behavior.SIGNIFICANCE STATEMENT Cortical sensory processing strongly depends on arousal. In the mouse visual system, locomotion (associated with high arousal) has previously been shown to enhance the sensory responses of neurons in primary visual cortex (V1). Yet, arousal fluctuates on a moment-to-moment basis, even during quiescent periods. The characteristics of V1 sensory processing across the continuum of arousal are unclear. Furthermore, the arousal level corresponding to optimal visual detection performance is unknown. We show that the magnitude and reliability of sensory-evoked V1 responses are monotonic increasing functions of arousal, and largest during locomotion. Visual detection behavior, however, is suboptimal during high arousal with locomotion, and usually best during intermediate arousal. Our study provides a more complete picture of the dependence of V1 sensory processing on arousal.

Effects of ketamine on orientation selectivity and variability of neuronal responses in primary visual cortex

The plasticity of the adult brain is one of the most highly evolving areas of recent neuroscience research. It has been acknowledged that the visual cortex in adulthood can adapt and restructure the neuronal connections in response to a sensory experience or to an imposed input such as in adaptation or ocular deprivation protocols. In order to understand the basic cellular mechanisms of plasticity in the primary visual cortex (V1), we examined the effects of ketamine, a non-competitive, glutamatergic NMDAR (N-methyl-D-aspartate receptor) antagonist, on the orientation of cortical cells by measuring their response variability and the Gaussian tuning curves in adult anesthetised mouse and cat. Neurons were recorded extracellularly using glass electrodes. The ketamine was applied locally by placing a custom-cut filter paper (1x1mm) soaked in ketamine solution (10 mg/ml) on the cortical surface next the site of the recording tip, in both species. Our results show that the local and acute exposure of ketamine on V1 changes the preferred orientation of the visual neurons established during the critical period of development. Furthermore, ketamine also leads to a decrease in the orientation selectivity (measured by orientation selectivity index, OSI) and the variability of neuronal evoked responses (measured by Fano factor), but does not affect spontaneous activity. These results suggest that ketamine induces plasticity in V1 neurons that might be operated by a different pathway than that of NMDARs.

Relating Divisive Normalization to Neuronal Response Variability.

Cortical responses to repeated presentations of a sensory stimulus are variable. This variability is sensitive to several stimulus dimensions, suggesting that it may carry useful information beyond the average firing rate. Many experimental manipulations that affect response variability are also known to engage divisive normalization, a widespread operation that describes neuronal activity as the ratio of a numerator (representing the excitatory stimulus drive) and denominator (the normalization signal). Although it has been suggested that normalization affects response variability, we lack a quantitative framework to determine the relation between the two. Here we extend the standard normalization model, by treating the numerator and the normalization signal as variable quantities. The resulting model predicts a general stabilizing effect of normalization on neuronal responses, and allows us to infer the single-trial normalization strength, a quantity that cannot be measured directly. We test the model on neuronal responses to stimuli of varying contrast, recorded in primary visual cortex of male macaques. We find that neurons that are more strongly normalized fire more reliably, and response variability and pairwise noise correlations are reduced during trials in which normalization is inferred to be strong. Our results thus suggest a novel functional role for normalization, namely, modulating response variability. Our framework could enable a direct quantification of the impact of single-trial normalization strength on the accuracy of perceptual judgments, and can be readily applied to other sensory and nonsensory factors.SIGNIFICANCE STATEMENT Divisive normalization is a widespread neural operation across sensory and nonsensory brain areas, which describes neuronal responses as the ratio between the excitatory drive to the neuron and a normalization signal. Normalization plays a key role in several important computations, including adjusting the neuron's dynamic range, reducing redundancy, and facilitating probabilistic inference. However, the relation between normalization and neuronal response variability (a fundamental aspect of neural coding) remains unclear. Here we develop a new model and test it on primary visual cortex responses. We show that normalization has a stabilizing effect on neuronal activity, beyond the known suppression of firing rate. This modulation of variability suggests a new functional role for normalization in neural coding and perception.

Neuron activity across the brain

Neuroscience How is it that groups of neurons dispersed through the brain interact to generate complex behaviors? Three papers in this issue present brain-scale studies of neuronal activity and dynamics (see the Perspective by Huk and Hart). Allen et al. found that in thirsty mice, there is widespread neural activity related to stimuli that elicit licking and drinking. Individual neurons encoded task-specific responses, but every brain area contained neurons with different types of response. Optogenetic stimulation of thirst-sensing neurons in one area of the brain reinstated drinking and neuronal activity across the brain that previously signaled thirst. Grundemann et al. investigated the activity of mouse basal amygdala neurons in relation to behavior during different tasks. Two ensembles of neurons showed orthogonal activity during exploratory and nonexploratory behaviors, possibly reflecting different levels of anxiety experienced in these areas. Stringer et al. analyzed spontaneous neuronal firing, finding that neurons in the primary visual cortex encoded both visual information and motor activity related to facial movements. The variability of neuronal responses to visual stimuli in the primary visual area is mainly related to arousal and reflects the encoding of latent behavioral states. Science , this issue p. [aav3932][1], p. [aav8736][2], p. [aav7893][3]; see also p. [236][4] [1]: /lookup/doi/10.1126/science.aav3932 [2]: /lookup/doi/10.1126/science.aav8736 [3]: /lookup/doi/10.1126/science.aav7893 [4]: /lookup/doi/10.1126/science.aax1512

Spontaneous behaviors drive multidimensional, brainwide activity.

Neuronal populations in sensory cortex produce variable responses to sensory stimuli and exhibit intricate spontaneous activity even without external sensory input. Cortical variability and spontaneous activity have been variously proposed to represent random noise, recall of prior experience, or encoding of ongoing behavioral and cognitive variables. Recording more than 10,000 neurons in mouse visual cortex, we observed that spontaneous activity reliably encoded a high-dimensional latent state, which was partially related to the mouse's ongoing behavior and was represented not just in visual cortex but also across the forebrain. Sensory inputs did not interrupt this ongoing signal but added onto it a representation of external stimuli in orthogonal dimensions. Thus, visual cortical population activity, despite its apparently noisy structure, reliably encodes an orthogonal fusion of sensory and multidimensional behavioral information.

Amygdala ensembles encode behavioral states.

Internal states, including affective or homeostatic states, are important behavioral motivators. The amygdala regulates motivated behaviors, yet how distinct states are represented in amygdala circuits is unknown. By longitudinally imaging neural calcium dynamics in freely moving mice across different environments, we identified opponent changes in activity levels of two major, nonoverlapping populations of basal amygdala principal neurons. This population signature does not report global anxiety but predicts switches between exploratory and nonexploratory, defensive states. Moreover, the amygdala separately processes external stimuli and internal states and broadcasts state information via several output pathways to larger brain networks. Our findings extend the concept of thalamocortical "brain-state" coding to include affective and exploratory states and provide an entry point into the state dependency of brain function and behavior in defined circuits.

Thirst regulates motivated behavior through modulation of brainwide neural population dynamics.

Physiological needs produce motivational drives, such as thirst and hunger, that regulate behaviors essential to survival. Hypothalamic neurons sense these needs and must coordinate relevant brainwide neuronal activity to produce the appropriate behavior. We studied dynamics from ~24,000 neurons in 34 brain regions during thirst-motivated choice behavior in 21 mice as they consumed water and became sated. Water-predicting sensory cues elicited activity that rapidly spread throughout the brain of thirsty animals. These dynamics were gated by a brainwide mode of population activity that encoded motivational state. After satiation, focal optogenetic activation of hypothalamic thirst-sensing neurons returned global activity to the pre-satiation state. Thus, motivational states specify initial conditions that determine how a brainwide dynamical system transforms sensory input into behavioral output.

Axon Collaterals and Brain States.

Multiple mechanisms have been identified as relevant to plasticity, functional stability, and reliable processing across brain states. In the context of stability under “ever-changing conditions” (this Topic), the role of axons has been relatively under-investigated. The highly branched topologies of many axons, however, seem well designed to differentially recruit and regulate distributed postsynaptic groups, possibly in a state-dependent fashion. In this Perspective, I briefly discuss several examples of axon collateralization, and then some of the branch-specific features that might subserve differential recruitment and whole brain activation. An emerging principle is that the number of collaterals and number of target structures are not stereotyped. Rather, axons originating from one defined source typically send branches to diversified subsets of target areas. This could achieve heterogeneous inputs, with different degrees of synchronicity. Variability of neuronal responses has been suggested as inversely proportional to the degree of temporally correlated input. Increased input homogeneity, driven by sensory stimulation or behavioral conditions, is reported to reduce neuronal variability, with axon collateralization potentially having an important role.

Attentional fluctuations induce shared variability in macaque primary visual cortex

Variability in neuronal responses to identical stimuli is frequently correlated across a population. Attention is thought to reduce these correlations by suppressing noisy inputs shared by the population. However, even with precise control of the visual stimulus, the subject’s attentional state varies across trials. While these state fluctuations are bound to induce some degree of correlated variability, it is currently unknown how strong their effect is, as previous studies generally do not dissociate changes in attentional strength from changes in attentional state variability. We designed a novel paradigm that does so and find both a pronounced effect of attentional fluctuations on correlated variability at long timescales and attention-dependent reductions in correlations at short timescales. These effects predominate in layers 2/3, as expected from a feedback signal such as attention. Thus, significant portions of correlated variability can be attributed to fluctuations in internally generated signals, like attention, rather than noise.

AB062. Cortical state contribution to neuronal response variability

Background: Visual cortex neurons often respond to stimuli very differently on repeated trials. This trial-by-trial variability is known to be correlated among nearby neurons. Our long-term goal is to quantitatively estimate neuronal response variability, using multi-channel local field potential (LFP) data from single trials.

Task-specific, dimension-based attentional shaping of motion processing in monkey area MT.

Nonspatially selective attention is based on the notion that specific features or objects in the visual environment are effectively prioritized in cortical visual processing. Feature-based attention (FBA), in particular, is a well-studied process that dynamically and selectively addresses neurons preferentially processing the attended feature attribute (e.g., leftward motion). In everyday life, however, behavior may require high sensitivity for an entire feature dimension (e.g., motion), but experimental evidence for a feature dimension-specific attentional modulation on a cellular level is lacking. Therefore, we investigated neuronal activity in macaque motion-selective mediotemporal area (MT) in an experimental setting requiring the monkeys to detect either a motion change or a color change. We hypothesized that neural activity in MT is enhanced when the task requires perceptual sensitivity to motion. In line with this, we found that mean firing rates were higher in the motion task and that response variability and latency were lower compared with values in the color task, despite identical visual stimulation. This task-specific, dimension-based modulation of motion processing emerged already in the absence of visual input, was independent of the relation between the attended and stimulating motion direction, and was accompanied by a spatially global reduction of neuronal variability. The results provide single-cell support for the hypothesis of a feature dimension-specific top-down signal emphasizing the processing of an entire feature class.NEW & NOTEWORTHY Cortical processing serving visual perception prioritizes information according to current task requirements. We provide evidence in favor of a dimension-based attentional mechanism addressing all neurons that process visual information in the task-relevant feature domain. Behavioral tasks required monkeys to attend either color or motion, causing modulations of response strength, variability, latency, and baseline activity of motion-selective monkey area MT neurons irrespective of the attended motion direction but specific to the attended feature dimension.