Spiking Irregularity and Frequency Modulate the Behavioral Report of Single-Neuron Stimulation

Neocortical inhibitory imbalance predicts successful sensory detection

Perceptual success depends on fast-spiking, parvalbumin-positive interneurons (FS/PVs). However, competing theories of optimal rate and correlation in pyramidal (PYR) firing make opposing predictions regarding the underlying FS/PV dynamics. We addressed this with population calcium imaging of FS/PVs and putative PYR neurons during threshold detection. In primary somatosensory and visual neocortex, a distinct PYR subset shows increased rate and spike-count correlations on detected trials ("hits"), while most show no rate change and decreased correlations. A larger fraction of FS/PVs predicts hits with either rate increases or decreases. Using computational modeling, we found that inhibitory imbalance, created by excitatory "feedback" and interactions between FS/PV pools, can account for the data. Rate-decreasing FS/PVs increase rate and correlation in a PYR subset, while rate-increasing FS/PVs reduce correlations and offset enhanced excitation in PYR neurons. These findings indicate that selection of informative PYR ensembles, through transient inhibitory imbalance, is a common motif of optimal neocortical processing.

A latent pool of neurons silenced by sensory-evoked inhibition can be recruited to enhance perception

To investigate which activity patterns in sensory cortex are relevant for perceptual decision-making, we combined two-photon calcium imaging and targeted two-photon optogenetics to interrogate barrel cortex activity during perceptual discrimination. We trained mice to discriminate bilateral whisker deflections and report decisions by licking left or right. Two-photon calcium imaging revealed sparse coding of contralateral and ipsilateral whisker input in layer 2/3, with most neurons remaining silent during the task. Activating pyramidal neurons using two-photon holographic photostimulation evoked a perceptual bias that scaled with the number of neurons photostimulated. This effect was dominated by optogenetic activation of non-coding neurons, which did not show sensory or motor-related activity during task performance. Photostimulation also revealed potent recruitment of cortical inhibition during sensory processing, which strongly and preferentially suppressed non-coding neurons. Our results suggest that a pool of non-coding neurons, selectively suppressed by network inhibition during sensory processing, can be recruited to enhance perception.

Value-Based Search Efficiency Is Encoded in the Substantia Nigra Reticulata Firing Rate, Spiking Irregularity and Local Field Potential

Recent results show that valuable objects can pop out in visual search, yet its neural mechanisms remain unexplored. Given the role of substantia nigra reticulata (SNr) in object value memory and control of gaze, we recorded its single-unit activity while male macaque monkeys engaged in efficient or inefficient search for a valuable target object among low-value objects. The results showed that efficient search was concurrent with stronger inhibition and higher spiking irregularity in the target-present (TP) compared with the target-absent (TA) trials in SNr. Importantly, the firing rate differentiation of TP and TA trials happened within ∼100 ms of display onset, and its magnitude was significantly correlated with the search times and slopes (search efficiency). Time-frequency analyses of local field potential (LFP) after display onset revealed significant modulations of the gamma band power with search efficiency. The greater reduction of SNr firing in TP trials in efficient search can create a stronger disinhibition of downstream superior colliculus, which in turn can facilitate saccade to obtain valuable targets in competitive environments.

Silences, spikes and bursts: Three-part knot of the neural code

When a neuron breaks silence, it can emit action potentials in a number of patterns. Some responses are so sudden and intense that electrophysiologists felt the need to single them out, labelling action potentials emitted at a particularly high frequency with a metonym - bursts. Is there more to bursts than a figure of speech? After all, sudden bouts of high-frequency firing are expected to occur whenever inputs surge. The burst coding hypothesis advances that the neural code has three syllables: silences, spikes and bursts. We review evidence supporting this ternary code in terms of devoted mechanisms for burst generation, synaptic transmission and synaptic plasticity. We also review the learning and attention theories for which such a triad is beneficial.

Single spikes drive sequential propagation and routing of activity in a cortical network

Single spikes can trigger repeatable firing sequences in cortical networks. The mechanisms that support reliable propagation of activity from such small events and their functional consequences remain unclear. By constraining a recurrent network model with experimental statistics from turtle cortex, we generate reliable and temporally precise sequences from single spike triggers. We find that rare strong connections support sequence propagation, while dense weak connections modulate propagation reliability. We identify sections of sequences corresponding to divergent branches of strongly connected neurons which can be selectively gated. Applying external inputs to specific neurons in the sparse backbone of strong connections can effectively control propagation and route activity within the network. Finally, we demonstrate that concurrent sequences interact reliably, generating a highly combinatorial space of sequence activations. Our results reveal the impact of individual spikes in cortical circuits, detailing how repeatable sequences of activity can be triggered, sustained, and controlled during cortical computations.

Layer- and cell-type-specific differences in neural activity in mouse barrel cortex during a whisker detection task

To address the question which neocortical layers and cell types are important for the perception of a sensory stimulus, we performed multielectrode recordings in the barrel cortex of head-fixed mice performing a single-whisker go/no-go detection task with vibrotactile stimuli of differing intensities. We found that behavioral detection probability decreased gradually over the course of each session, which was well explained by a signal detection theory-based model that posits stable psychometric sensitivity and a variable decision criterion updated after each reinforcement, reflecting decreasing motivation. Analysis of multiunit activity demonstrated highest neurometric sensitivity in layer 4, which was achieved within only 30 ms after stimulus onset. At the level of single neurons, we observed substantial heterogeneity of neurometric sensitivity within and across layers, ranging from nonresponsiveness to approaching or even exceeding psychometric sensitivity. In all cortical layers, putative inhibitory interneurons on average proffered higher neurometric sensitivity than putative excitatory neurons. In infragranular layers, neurons increasing firing rate in response to stimulation featured higher sensitivities than neurons decreasing firing rate. Offline machine-learning-based analysis of videos of behavioral sessions showed that mice performed better when not moving, which at the neuronal level, was reflected by increased stimulus-evoked firing rates.

Modality specific roles for metabotropic GABAergic signaling and calcium induced calcium release mechanisms in regulating cold nociception

Calcium (Ca2+) plays a pivotal role in modulating neuronal-mediated responses to modality-specific sensory stimuli. Recent studies in Drosophila reveal class III (CIII) multidendritic (md) sensory neurons function as multimodal sensors regulating distinct behavioral responses to innocuous mechanical and nociceptive thermal stimuli. Functional analyses revealed CIII-mediated multimodal behavioral output is dependent upon activation levels with stimulus-evoked Ca2+ displaying relatively low vs. high intracellular levels in response to gentle touch vs. noxious cold, respectively. However, the mechanistic bases underlying modality-specific differential Ca2+ responses in CIII neurons remain incompletely understood. We hypothesized that noxious cold-evoked high intracellular Ca2+ responses in CIII neurons may rely upon Ca2+ induced Ca2+ release (CICR) mechanisms involving transient receptor potential (TRP) channels and/or metabotropic G protein coupled receptor (GPCR) activation to promote cold nociceptive behaviors. Mutant and/or CIII-specific knockdown of GPCR and CICR signaling molecules [GABA B -R2, Gαq, phospholipase C, ryanodine receptor (RyR) and Inositol trisphosphate receptor (IP3R)] led to impaired cold-evoked nociceptive behavior. GPCR mediated signaling, through GABA B -R2 and IP3R, is not required in CIII neurons for innocuous touch evoked behaviors. However, CICR via RyR is required for innocuous touch-evoked behaviors. Disruptions in GABA B -R2, IP3R, and RyR in CIII neurons leads to significantly lower levels of cold-evoked Ca2+ responses indicating GPCR and CICR signaling mechanisms function in regulating Ca2+ release. CIII neurons exhibit bipartite cold-evoked firing patterns, where CIII neurons burst during rapid temperature change and tonically fire during steady state cold temperatures. GABA B -R2 knockdown in CIII neurons resulted in disorganized firing patterns during cold exposure. We further demonstrate that application of GABA or the GABA B specific agonist baclofen potentiates cold-evoked CIII neuron activity. Upon ryanodine application, CIII neurons exhibit increased bursting activity and with CIII-specific RyR knockdown, there is an increase in cold-evoked tonic firing and decrease in bursting. Lastly, our previous studies implicated the TRPP channel Pkd2 in cold nociception, and here, we show that Pkd2 and IP3R genetically interact to specifically regulate cold-evoked behavior, but not innocuous mechanosensation. Collectively, these analyses support novel, modality-specific roles for metabotropic GABAergic signaling and CICR mechanisms in regulating intracellular Ca2+ levels and cold-evoked behavioral output from multimodal CIII neurons.

All-optical interrogation of neural circuits in behaving mice

Recent advances combining two-photon calcium imaging and two-photon optogenetics with computer-generated holography now allow us to read and write the activity of large populations of neurons in vivo at cellular resolution and with high temporal resolution. Such 'all-optical' techniques enable experimenters to probe the effects of functionally defined neurons on neural circuit function and behavioral output with new levels of precision. This greatly increases flexibility, resolution, targeting specificity and throughput compared with alternative approaches based on electrophysiology and/or one-photon optogenetics and can interrogate larger and more densely labeled populations of neurons than current voltage imaging-based implementations. This protocol describes the experimental workflow for all-optical interrogation experiments in awake, behaving head-fixed mice. We describe modular procedures for the setup and calibration of an all-optical system (~3 h), the preparation of an indicator and opsin-expressing and task-performing animal (~3-6 weeks), the characterization of functional and photostimulation responses (~2 h per field of view) and the design and implementation of an all-optical experiment (achievable within the timescale of a normal behavioral experiment; ~3-5 h per field of view). We discuss optimizations for efficiently selecting and targeting neuronal ensembles for photostimulation sequences, as well as generating photostimulation response maps from the imaging data that can be used to examine the impact of photostimulation on the local circuit. We demonstrate the utility of this strategy in three brain areas by using different experimental setups. This approach can in principle be adapted to any brain area to probe functional connectivity in neural circuits and investigate the relationship between neural circuit activity and behavior.

Fast cortical dynamics encode tactile grating orientation during active touch

Touch-based object recognition relies on perception of compositional tactile features like roughness, shape, and surface orientation. However, besides roughness, it remains unclear how these different tactile features are encoded by neural activity that is linked with perception. Here, we establish a cortex-dependent perceptual task in which mice discriminate tactile gratings on the basis of orientation using only their whiskers. Multielectrode recordings in the barrel cortex reveal weak orientation tuning in average firing rates (500-ms time scale) during grating exploration despite high levels of cortical activity. Just before decision, orientation information extracted from fast cortical dynamics (100-ms time scale) more closely resembles concurrent psychophysical measurements than single neuron orientation tuning curves. This temporal code conveys both stimulus and choice/action-related information, suggesting that fast cortical dynamics during exploration of a tactile object both reflect the physical stimulus and affect the decision.

Neural burst codes disguised as rate codes

The burst coding hypothesis posits that the occurrence of sudden high-frequency patterns of action potentials constitutes a salient syllable of the neural code. Many neurons, however, do not produce clearly demarcated bursts, an observation invoked to rule out the pervasiveness of this coding scheme across brain areas and cell types. Here we ask how detrimental ambiguous spike patterns, those that are neither clearly bursts nor isolated spikes, are for neuronal information transfer. We addressed this question using information theory and computational simulations. By quantifying how information transmission depends on firing statistics, we found that the information transmitted is not strongly influenced by the presence of clearly demarcated modes in the interspike interval distribution, a feature often used to identify the presence of burst coding. Instead, we found that neurons having unimodal interval distributions were still able to ascribe different meanings to bursts and isolated spikes. In this regime, information transmission depends on dynamical properties of the synapses as well as the length and relative frequency of bursts. Furthermore, we found that common metrics used to quantify burstiness were unable to predict the degree with which bursts could be used to carry information. Our results provide guiding principles for the implementation of coding strategies based on spike-timing patterns, and show that even unimodal firing statistics can be consistent with a bivariate neural code.

Variability and Randomness of the Instantaneous Firing Rate

The apparent stochastic nature of neuronal activity significantly affects the reliability of neuronal coding. To quantify the encountered fluctuations, both in neural data and simulations, the notions of variability and randomness of inter-spike intervals have been proposed and studied. In this article we focus on the concept of the instantaneous firing rate, which is also based on the spike timing. We use several classical statistical models of neuronal activity and we study the corresponding probability distributions of the instantaneous firing rate. To characterize the firing rate variability and randomness under different spiking regimes, we use different indices of statistical dispersion. We find that the relationship between the variability of interspike intervals and the instantaneous firing rate is not straightforward in general. Counter-intuitively, an increase in the randomness (based on entropy) of spike times may either decrease or increase the randomness of instantaneous firing rate, in dependence on the neuronal firing model. Finally, we apply our methods to experimental data, establishing that instantaneous rate analysis can indeed provide additional information about the spiking activity.

Impacts of autapse on chaotic resonance in single neurons and small-world neuronal networks

Chaotic resonance (CR) is a new phenomenon induced by an intermediate level of chaotic signal intensity in neuronal systems. In the current study, we investigated the effects of autapse on the CR phenomenon in single neurons and small-world (SW) neuronal networks. In single neurons, we assume that the neuron has only one autapse modelled as electrical, excitatory chemical and inhibitory chemical synapse, respectively. Then, we analysed the effects of each one on the CR, separately. Obtained results revealed that, regardless of its type, autapse significantly increases the chaotic resonance of the appropriate autaptic parameter's values. It is also observed that, at the optimal chaotic current intensity, the multiple CR emerges depending on autaptic time delay for all the autapse types when the autaptic delay time or its integer multiples match the half period or period of the weak signal. In SW networks, we investigated the effects of chaotic activity on the prorogation of pacemaker activity, where pacemaker neurons have different kinds of autapse as considered in single neuron cases. Obtained results revealed that excitatory and electrical autapses prominently increase the prorogation of pacemaker activity, whereas inhibitory autapse reduces or does not change it. Also, the best propagation was obtained when the autapse was excitatory. This article is part of the theme issue 'Vibrational and stochastic resonance in driven nonlinear systems (part 2)'.

4E-BP2-dependent translation in cerebellar Purkinje cells controls spatial memory but not autism-like behaviors

Recent studies have demonstrated that selective activation of mammalian target of rapamycin complex 1 (mTORC1) in the cerebellum by deletion of the mTORC1 upstream repressors TSC1 or phosphatase and tensin homolog (PTEN) in Purkinje cells (PCs) causes autism-like features and cognitive deficits. However, the molecular mechanisms by which overactivated mTORC1 in the cerebellum engenders these behaviors remain unknown. The eukaryotic translation initiation factor 4E-binding protein 2 (4E-BP2) is a central translational repressor downstream of mTORC1. Here, we show that mice with selective ablation of 4E-BP2 in PCs display a reduced number of PCs, increased regularity of PC action potential firing, and deficits in motor learning. Surprisingly, although spatial memory is impaired in these mice, they exhibit normal social interaction and show no deficits in repetitive behavior. Our data suggest that, downstream of mTORC1/4E-BP2, there are distinct cerebellar mechanisms independently controlling social behavior and memory formation.

Microcircuit Rules Governing Impact of Single Interneurons on Purkinje Cell Output In Vivo

The functional impact of single interneurons on neuronal output in vivo and how interneurons are recruited by physiological activity patterns remain poorly understood. In the cerebellar cortex, molecular layer interneurons and their targets, Purkinje cells, receive excitatory inputs from granule cells and climbing fibers. Using dual patch-clamp recordings from interneurons and Purkinje cells in vivo, we probe the spatiotemporal interactions between these circuit elements. We show that single interneuron spikes can potently inhibit Purkinje cell output, depending on interneuron location. Climbing fiber input activates many interneurons via glutamate spillover but results in inhibition of those interneurons that inhibit the same Purkinje cell receiving the climbing fiber input, forming a disinhibitory motif. These interneuron circuits are engaged during sensory processing, creating diverse pathway-specific response functions. These findings demonstrate how the powerful effect of single interneurons on Purkinje cell output can be sculpted by various interneuron circuit motifs to diversify cerebellar computations.

Perirhinal input to neocortical layer 1 controls learning

Hippocampal output influences memory formation in the neocortex, but this process is poorly understood because the precise anatomical location and the underlying cellular mechanisms remain elusive. Here, we show that perirhinal input, predominantly to sensory cortical layer 1 (L1), controls hippocampal-dependent associative learning in rodents. This process was marked by the emergence of distinct firing responses in defined subpopulations of layer 5 (L5) pyramidal neurons whose tuft dendrites receive perirhinal inputs in L1. Learning correlated with burst firing and the enhancement of dendritic excitability, and it was suppressed by disruption of dendritic activity. Furthermore, bursts, but not regular spike trains, were sufficient to retrieve learned behavior. We conclude that hippocampal information arriving at L5 tuft dendrites in neocortical L1 mediates memory formation in the neocortex.

A network model of the barrel cortex combined with a differentiator detector reproduces features of the behavioral response to single-neuron stimulation

The stimulation of a single neuron in the rat somatosensory cortex can elicit a behavioral response. The probability of a behavioral response does not depend appreciably on the duration or intensity of a constant stimulation, whereas the response probability increases significantly upon injection of an irregular current. Biological mechanisms that can potentially suppress a constant input signal are present in the dynamics of both neurons and synapses and seem ideal candidates to explain these experimental findings. Here, we study a large network of integrate-and-fire neurons with several salient features of neuronal populations in the rat barrel cortex. The model includes cellular spike-frequency adaptation, experimentally constrained numbers and types of chemical synapses endowed with short-term plasticity, and gap junctions. Numerical simulations of this model indicate that cellular and synaptic adaptation mechanisms alone may not suffice to account for the experimental results if the local network activity is read out by an integrator. However, a circuit that approximates a differentiator can detect the single-cell stimulation with a reliability that barely depends on the length or intensity of the stimulus, but that increases when an irregular signal is used. This finding is in accordance with the experimental results obtained for the stimulation of a regularly-spiking excitatory cell.

It is widely assumed that only a large group of neurons can encode a stimulus or control behavior. This tenet of neuroscience has been challenged by experiments in which stimulating a single cortical neuron has had a measurable effect on an animal’s behavior. Recently, theoretical studies have explored how a single-neuron stimulation could be detected in a large recurrent network. However, these studies missed essential biological mechanisms of cortical networks and are unable to explain more recent experiments in the barrel cortex. Here, to describe the stimulated brain area, we propose and study a network model endowed with many important biological features of the barrel cortex. Importantly, we also investigate different readout mechanisms, i.e. ways in which the stimulation effects can propagate to other brain areas. We show that a readout network which tracks rapid variations in the local network activity is in agreement with the experiments. Our model demonstrates a possible mechanism for how the stimulation of a single neuron translates into a signal at the population level, which is taken as a proxy of the animal’s response. Our results illustrate the power of spiking neural networks to properly describe the effects of a single neuron’s activity.

How many neurons are sufficient for perception of cortical activity?

Many theories of brain function propose that activity in sparse subsets of neurons underlies perception and action. To place a lower bound on the amount of neural activity that can be perceived, we used an all-optical approach to drive behaviour with targeted two-photon optogenetic activation of small ensembles of L2/3 pyramidal neurons in mouse barrel cortex while simultaneously recording local network activity with two-photon calcium imaging. By precisely titrating the number of neurons stimulated, we demonstrate that the lower bound for perception of cortical activity is ~14 pyramidal neurons. We find a steep sigmoidal relationship between the number of activated neurons and behaviour, saturating at only ~37 neurons, and show this relationship can shift with learning. Furthermore, activation of ensembles is balanced by inhibition of neighbouring neurons. This surprising perceptual sensitivity in the face of potent network suppression supports the sparse coding hypothesis, and suggests that cortical perception balances a trade-off between minimizing the impact of noise while efficiently detecting relevant signals.

Precise Holographic Manipulation of Olfactory Circuits Reveals Coding Features Determining Perceptual Detection

Sensory systems transform the external world into time-varying spike trains. What features of spiking activity are used to guide behavior? In the mouse olfactory bulb, inhalation of different odors leads to changes in the set of neurons activated, as well as when neurons are activated relative to each other (synchrony) and the onset of inhalation (latency). To explore the relevance of each mode of information transmission, we probed the sensitivity of mice to perturbations across each stimulus dimension (i.e., rate, synchrony, and latency) using holographic two-photon optogenetic stimulation of olfactory bulb neurons with cellular and single-action-potential resolution. We found that mice can detect single action potentials evoked synchronously across <20 olfactory bulb neurons. Further, we discovered that detection depends strongly on the synchrony of activation across neurons, but not the latency relative to inhalation.

V1 microcircuits underlying mouse visual behavior

Visual behavior is based on the concerted activity of neurons in visual areas, where sensory signals are integrated with top-down information. In the past decade, the advent of new tools, such as functional imaging of populations of identified single neurons, high-density electrophysiology, virus-assisted circuit mapping, and precisely timed, cell-type specific manipulations, has advanced our understanding of the neuronal microcircuits underlying visual behavior. Studies in head-fixed mice, where such tools can routinely be applied, begin to provide new insights into the neural code of primary visual cortex (V1) underlying visual perception, and the micro-circuits of attention, predictive processing, and learning.

Manipulating Hippocampal Place Cell Activity by Single-Cell Stimulation in Freely Moving Mice

Learning critically depends on the ability to rapidly form and store non-overlapping representations of the external world. In line with their postulated role in episodic memory, hippocampal place cells can undergo a rapid reorganization of their firing fields upon contextual manipulations. To explore the mechanisms underlying such global remapping, we juxtacellularly stimulated 42 hippocampal neurons in freely moving mice during spatial exploration. We found that evoking spike trains in silent neurons was sufficient for creating place fields, while in place cells, juxtacellular stimulation induced a rapid remapping of their place fields to the stimulus location. The occurrence of complex spikes was most predictive of place field plasticity. Our data thus indicate that plasticity-inducing stimuli are able to rapidly bias place cell activity, simultaneously suppressing existing place fields. We propose that such competitive place field dynamics could support the orthogonalization of the hippocampal map during global remapping.

Sensitivity to Stimulus Irregularity Is Inherent in Neural Networks

Behavior is controlled by complex neural networks in which neurons process thousands of inputs. However, even short spike trains evoked in a single cortical neuron were demonstrated to be sufficient to influence behavior in vivo. Specifically, irregular sequences of interspike intervals (ISIs) had a more reliable influence on behavior despite their resemblance to stochastic activity. Similarly, irregular tactile stimulation led to higher rates of behavioral responses. In this study, we identify the mechanisms enabling this sensitivity to stimulus irregularity (SSI) on the neuronal and network levels using simulated spiking neural networks. Matching in vivo experiments, we find that irregular stimulation elicits more detectable network events (bursts) than regular stimulation. Dissecting the stimuli, we identify short ISIs-occurring more frequently in irregular stimulations-as the main drivers of SSI rather than complex irregularity per se. In addition, we find that short-term plasticity modulates SSI. We subsequently eliminate the different mechanisms in turn to assess their role in generating SSI. Removing inhibitory interneurons, we find that SSI is retained, suggesting that SSI is not dependent on inhibition. Removing recurrency, we find that SSI is retained due to the ability of individual neurons to integrate activity over short timescales ("cell memory"). Removing single-neuron dynamics, we find that SSI is retained based on the short-term retention of activity within the recurrent network structure ("network memory"). Finally, using a further simplified probabilistic model, we find that local network structure is not required for SSI. Hence, SSI is identified as a general property that we hypothesize to be ubiquitous in neural networks with different structures and biophysical properties. Irregular sequences contain shorter ISIs, which are the main drivers underlying SSI. The experimentally observed SSI should thus generalize to other systems, suggesting a functional role for irregular activity in cortex.

Assessing the Impact of Single-Cell Stimulation on Local Networks in Rat Barrel Cortex-A Feasibility Study

In contrast to the long-standing notion that the role of individual neurons in population activity is vanishingly small, recent studies have shown that electrical activation of only a single cortical neuron can have measurable effects on global brain state, movement, and perception. Although highly important for understanding how neuronal activity in cortex is orchestrated, the cellular and network mechanisms underlying this phenomenon are unresolved. Here, we first briefly review the current state of knowledge regarding the phenomenon of single-cell induced network modulation and discuss possible underpinnings. Secondly, we show proof of principle for an experimental approach to elucidate the mechanisms of single-cell induced changes in cortical activity. The setup allows simultaneous recordings of the spiking activity of multiple neurons across all layers of the cortex using a multi-electrode array, while manipulating the activity of one individual neuron in close proximity to the array. We demonstrate that single cells can be recorded and stimulated reliably for hundreds of trials, conferring high statistical power even for expectedly small effects of single-neuron spiking on network activity. Preliminary results suggest that single-cell stimulation on average decreases the firing rate of local network units. We expect that characterization of the spatiotemporal spread of single-cell evoked activity across layers and columns will yield novel insights into intracortical processing.

Detecting single-cell stimulation in a large network of integrate-and-fire neurons

Several experiments have shown that the stimulation of a single neuron in the cortex can influence the local network activity and even the behavior of an animal. From the theoretical point of view, it is not clear how stimulating a single cell in a cortical network can evoke a statistically significant change in the activity of a large population. Our previous study considered a random network of integrate-and-fire neurons and proposed a way of detecting the stimulation of a single neuron in the activity of a local network: a threshold detector biased toward a specific subset of neurons. Here, we revisit this model and extend it by introducing a second network acting as a readout. In the simplest scenario, the readout consists of a collection of integrate-and-fire neurons with no recurrent connections. In this case, the ability to detect the stimulus does not improve. However, a readout network with both feed-forward and local recurrent inhibition permits detection with a very small bias, if compared to the readout scheme introduced previously. The crucial role of inhibition is to reduce global input cross correlations, the main factor limiting detectability. Finally, we show that this result is robust if recurrent excitatory connections are included or if a different kind of readout bias (in the synaptic amplitudes instead of connection probability) is used.

Ripple oscillations in the left temporal neocortex are associated with impaired verbal episodic memory encoding

BACKGROUND

We sought to determine if ripple oscillations (80-120 Hz), detected in intracranial electroencephalogram (iEEG) recordings of patients with epilepsy, correlate with an enhancement or disruption of verbal episodic memory encoding.

METHODS

We defined ripple and spike events in depth iEEG recordings during list learning in 107 patients with focal epilepsy. We used logistic regression models (LRMs) to investigate the relationship between the occurrence of ripple and spike events during word presentation and the odds of successful word recall following a distractor epoch and included the seizure onset zone (SOZ) as a covariate in the LRMs.

RESULTS

We detected events during 58,312 word presentation trials from 7630 unique electrode sites. The probability of ripple on spike (RonS) events was increased in the SOZ (p < 0.04). In the left temporal neocortex, RonS events during word presentation corresponded with a decrease in the odds ratio (OR) of successful recall, however, this effect only met significance in the SOZ (OR of word recall: 0.71, 95% confidence interval (CI): 0.59-0.85, n = 158 events, adaptive Hochberg, p < 0.01). Ripple on oscillation (RonO) events that occurred in the left temporal neocortex non-SOZ also correlated with decreased odds of successful recall (OR: 0.52, 95% CI: 0.34-0.80, n = 140, adaptive Hochberg, p < 0.01). Spikes and RonS that occurred during word presentation in the left middle temporal gyrus (MTG) correlated with the most significant decrease in the odds of successful recall, irrespective of the location of the SOZ (adaptive Hochberg, p < 0.01).

CONCLUSION

Ripples and spikes generated in the left temporal neocortex are associated with impaired verbal episodic memory encoding. Although physiological and pathological ripple oscillations were not distinguished during cognitive tasks, our results show an association of undifferentiated ripples with impaired encoding. The effect was sometimes specific to regions outside the SOZ, suggesting that widespread effects of epilepsy outside the SOZ may contribute to cognitive impairment.

Inhibitory connectivity defines the realm of excitatory plasticity

Recent experiments demonstrate substantial volatility of excitatory connectivity in the absence of any learning. This challenges the hypothesis that stable synaptic connections are necessary for long-term maintenance of acquired information. Here we measure ongoing synaptic volatility and use theoretical modeling to study its consequences on cortical dynamics. We show that in the balanced cortex, patterns of neural activity are primarily determined by inhibitory connectivity, despite the fact that most synapses and neurons are excitatory. Similarly, we show that the inhibitory network is more effective in storing memory patterns than the excitatory one. As a result, network activity is robust to ongoing volatility of excitatory synapses, as long as this volatility does not disrupt the balance between excitation and inhibition. We thus hypothesize that inhibitory connectivity, rather than excitatory, controls the maintenance and loss of information over long periods of time in the volatile cortex.

Neural Coding With Bursts-Current State and Future Perspectives

Neuronal action potentials or spikes provide a long-range, noise-resistant means of communication between neurons. As point processes single spikes contain little information in themselves, i.e., outside the context of spikes from other neurons. Moreover, they may fail to cross a synapse. A burst, which consists of a short, high frequency train of spikes, will more reliably cross a synapse, increasing the likelihood of eliciting a postsynaptic spike, depending on the specific short-term plasticity at that synapse. Both the number and the temporal pattern of spikes in a burst provide a coding space that lies within the temporal integration realm of single neurons. Bursts have been observed in many species, including the non-mammalian, and in brain regions that range from subcortical to cortical. Despite their widespread presence and potential relevance, the uncertainties of how to classify bursts seems to have limited the research into the coding possibilities for bursts. The present series of research articles provides new insights into the relevance and interpretation of bursts across different neural circuits, and new methods for their analysis. Here, we provide a succinct introduction to the history of burst coding and an overview of recent work on this topic.

Mild Traumatic Brain Injury Induces Structural and Functional Disconnection of Local Neocortical Inhibitory Networks via Parvalbumin Interneuron Diffuse Axonal Injury

Diffuse axonal injury (DAI) plays a major role in cortical network dysfunction posited to cause excitatory/inhibitory imbalance after mild traumatic brain injury (mTBI). Current thought holds that white matter (WM) is uniquely vulnerable to DAI. However, clinically diagnosed mTBI is not always associated with WM DAI. This suggests an undetected neocortical pathophysiology, implicating GABAergic interneurons. To evaluate this possibility, we used mild central fluid percussion injury to generate DAI in mice with Cre-driven tdTomato labeling of parvalbumin (PV) interneurons. We followed tdTomato+ profiles using confocal and electron microscopy, together with patch-clamp analysis to probe for DAI-mediated neocortical GABAergic interneuron disruption. Within 3 h post-mTBI tdTomato+ perisomatic axonal injury (PSAI) was found across somatosensory layers 2-6. The DAI marker amyloid precursor protein colocalized with GAD67 immunoreactivity within tdTomato+ PSAI, representing the majority of GABAergic interneuron DAI. At 24 h post-mTBI, we used phospho-c-Jun, a surrogate DAI marker, for retrograde assessments of sustaining somas. Via this approach, we estimated DAI occurs in ~9% of total tdTomato+ interneurons, representing ~14% of pan-neuronal DAI. Patch-clamp recordings of tdTomato+ interneurons revealed decreased inhibitory transmission. Overall, these data show that PV interneuron DAI is a consistent and significant feature of experimental mTBI with important implications for cortical network dysfunction.

Testing the Efficacy of Single-Cell Stimulation in Biasing Presubicular Head Direction Activity

To support navigation, the firing of head direction (HD) neurons must be tightly anchored to the external space. Indeed, inputs from external landmarks can rapidly reset the preferred direction of HD cells. Landmark stimuli have often been simulated as excitatory inputs from "visual cells" (encoding landmark information) to the HD attractor network; when excitatory visual inputs are sufficiently strong, preferred directions switch abruptly to the landmark location. In the present work, we tested whether mimicking such inputs via juxtacellular stimulation would be sufficient for shifting the tuning of individual presubicular HD cells recorded in passively rotated male rats. We recorded 81 HD cells in a cue-rich environment, and evoked spikes trains outside of their preferred direction (distance range, 11-178°). We found that HD tuning was remarkably resistant to activity manipulations. Even strong stimulations, which induced seconds-long spike trains, failed to induce a detectable shift in directional tuning. HD tuning curves before and after stimulation remained highly correlated, indicating that postsynaptic activation alone is insufficient for modifying HD output. Our data are thus consistent with the predicted stability of an HD attractor network when anchored to external landmarks. A small spiking bias at the stimulus direction could only be observed in a visually deprived environment in which both average firing rates and directional tuning were markedly reduced. Based on this evidence, we speculate that, when attractor dynamics become unstable (e.g., under disorientation), the output of HD neurons could be more efficiently controlled by strong biasing stimuli.SIGNIFICANCE STATEMENT The activity of head direction (HD) cells is thought to provide the mammalian brain with an internal sense of direction. To support navigation, the firing of HD neurons must be anchored to external landmarks, a process thought to be supported by associative plasticity within the HD system. Here, we investigated these plasticity mechanisms by juxtacellular stimulation of single HD neurons in vivo in awake rats. We found that HD coding is strongly resistant to external manipulations of spiking activity. Only in a visually deprived environment was juxtacellular stimulation able to induce a small activity bias in single presubicular neurons. We propose that juxtacellular stimulation can bias HD tuning only when competing anchoring inputs are reduced or not available.

Single-Cell Stimulation in Barrel Cortex Influences Psychophysical Detection Performance

A single whisker stimulus elicits action potentials in a sparse subset of neurons in somatosensory cortex. The precise contribution of these neurons to the animal's perception of a whisker stimulus is unknown. Here we show that single-cell stimulation in rat barrel cortex of both sexes influences the psychophysical detection of a near-threshold whisker stimulus in a cell type-dependent manner, without affecting false alarm rate. Counterintuitively, stimulation of single fast-spiking putative inhibitory neurons increased detection performance. Single-cell stimulation of putative excitatory neurons failed to change detection performance, except for a small subset of deep-layer neurons that were highly sensitive to whisker stimulation and that had an unexpectedly strong impact on detection performance. These findings indicate that the perceptual impact of excitatory barrel cortical neurons relates to their firing response to whisker stimulation and that strong activity in a single highly sensitive neuron in barrel cortex can already enhance sensory detection. Our data suggest that sensory detection is based on a decoding mechanism that lends a disproportionally large weight to interneurons and to deep-layer neurons showing a strong response to sensory stimulation.SIGNIFICANCE STATEMENT Rat whisker somatosensory cortex contains a variety of neuronal cell types with distinct anatomical and physiological characteristics. How each of these different cell types contribute to the animal's perception of whisker stimuli is unknown. We explored this question by using a powerful electrophysiological stimulation technique that allowed us to target and stimulate single neurons with different sensory response types in whisker cortex. In awake, behaving animals, trained to detect whisker stimulation, only costimulation of single fast-spiking inhibitory neurons or single deep-layer excitatory neurons with strong responses to whisker stimulation enhanced detection performance. Our data demonstrate that single cortical neurons can have measurable impact on the detection of sensory stimuli and suggest a decoding mechanism based on select cell types.

Evoking prescribed spike times in stochastic neurons

Single cell stimulation in vivo is a powerful tool to investigate the properties of single neurons and their functionality in neural networks. We present a method to determine a cell-specific stimulus that reliably evokes a prescribed spike train with high temporal precision of action potentials. We test the performance of this stimulus in simulations for two different stochastic neuron models. For a broad range of parameters and a neuron firing with intermediate firing rates (20-40 Hz) the reliability in evoking the prescribed spike train is close to its theoretical maximum that is mainly determined by the level of intrinsic noise.

Active cortical dendrites modulate perception

There is as yet no consensus concerning the neural basis of perception and how it operates at a mechanistic level. We found that Ca²⁺ activity in the apical dendrites of a subset of layer 5 (L5) pyramidal neurons in primary somatosensory cortex (S1) in mice is correlated with the threshold for perceptual detection of whisker deflections. Manipulating the activity of apical dendrites shifted the perceptual threshold, demonstrating that an active dendritic mechanism is causally linked to perceptual detection.

Noisy Juxtacellular Stimulation In Vivo Leads to Reliable Spiking and Reveals High-Frequency Coding in Single Neurons

Single cells in the motor and somatosensory cortex of rats were stimulated in vivo with broadband fluctuating currents applied juxtacellularly. Unlike the DC current steps used previously, fluctuating stimulation currents reliably evoked spike trains with precise timing of individual spikes. Fluctuating currents resulted in strong cellular responses at stimulation frequencies beyond the inverse membrane time constant and the mean firing rate of the neuron. Neuronal firing was associated with high rates of information transmission, even for the high-frequency components of the stimulus. Such response characteristics were also revealed in additional experiments with sinusoidal juxtacellular stimulation. For selected cells, we could reproduce these statistics with compartmental models of varying complexity. We also developed a method to generate Gaussian stimuli that evoke spike trains with prescribed spike times (under the constraint of a certain rate and coefficient of variation) and exemplify its ability to achieve precise and reliable spiking in cortical neurons in vivo Our results demonstrate a novel method for precise control of spike timing by juxtacellular stimulation, confirm and extend earlier conclusions from ex vivo work about the capacity of cortical neurons to generate precise discharges, and contribute to the understanding of the biophysics of information transfer of single neurons in vivo at high frequencies.

SIGNIFICANCE STATEMENT

Nanostimulation of single identified neurons in vivo can control spike frequency parametrically and, surprisingly, can even bias the animal's behavioral response. Here, we extend this stimulation protocol to time-dependent broadband noise stimulation in sensory and motor cortices of rat. In response to such stimuli, we found increased temporal spike-time reliability. The information transmission properties reveal, both experimentally and theoretically, that the neurons support high-frequency stimulation beyond the inverse membrane time. Generating a stimulus using the neuron's response properties, we could evoke prescribed spike times with high precision. Our work helps to establish a novel method for precise temporal control of single-cell spiking and provides a simplified biophysical description of single-neuron spiking under time-dependent in vivo-like stimulation.

Optimal Detection of a Localized Perturbation in Random Networks of Integrate-and-Fire Neurons

Experimental and theoretical studies suggest that cortical networks are chaotic and coding relies on averages over large populations. However, there is evidence that rats can respond to the short stimulation of a single cortical cell, a theoretically unexplained fact. We study effects of single-cell stimulation on a large recurrent network of integrate-and-fire neurons and propose a simple way to detect the perturbation. Detection rates obtained from simulations and analytical estimates are similar to experimental response rates if the readout is slightly biased towards specific neurons. Near-optimal detection is attained for a broad range of intermediate values of the mean coupling between neurons.

Persistent irregular activity is a result of rebound and coincident detection mechanisms: A computational study

Persistent irregular activity is defined as elevated irregular neural discharges in the brain in such a way that while the average network activity displays high frequency oscillations, the participating neurons display irregular and low frequency oscillations. This type of activity is observed in many brain regions like prefrontal cortex that plays a role in working memory. Previous studies have shown that large networks with sparse connections, networks with strong noise and persistent inhibition and networks with structured synaptic connections display persistent-irregular activity. However, experimental studies show that, not all brain regions obey these assumptions. In this study we show that a small network of excitatory-inhibitory neurons with random synaptic connections can reproduce persistent-irregular activity. In particular, the model shows that less than perfect rebound pattern in excitatory cells, coincident-sensitive inhibitory cells and sparse synaptic inhibition can account for persistent-irregular activity in an excitatory-inhibitory neural network with randomly assigned synaptic connections.

Cracking the Neural Code for Sensory Perception by Combining Statistics, Intervention, and Behavior

The two basic processes underlying perceptual decisions-how neural responses encode stimuli, and how they inform behavioral choices-have mainly been studied separately. Thus, although many spatiotemporal features of neural population activity, or "neural codes," have been shown to carry sensory information, it is often unknown whether the brain uses these features for perception. To address this issue, we propose a new framework centered on redefining the neural code as the neural features that carry sensory information used by the animal to drive appropriate behavior; that is, the features that have an intersection between sensory and choice information. We show how this framework leads to a new statistical analysis of neural activity recorded during behavior that can identify such neural codes, and we discuss how to combine intersection-based analysis of neural recordings with intervention on neural activity to determine definitively whether specific neural activity features are involved in a task.

Temporally precise control of single-neuron spiking by juxtacellular nanostimulation

Temporal patterns of action potentials influence a variety of activity-dependent intra- and intercellular processes and play an important role in theories of neural coding. Elucidating the mechanisms underlying these phenomena requires imposing spike trains with precisely defined patterns, but this has been challenging due to the limitations of existing stimulation techniques. Here we present a new nanostimulation method providing control over the action potential output of individual cortical neurons. Spikes are elicited through the juxtacellular application of short-duration fluctuating currents ("kurzpulses"), allowing for the sub-millisecond precise and reproducible induction of arbitrary patterns of action potentials at all physiologically relevant firing frequencies (<120 Hz), including minute-long spike trains recorded in freely moving animals. We systematically compared our method to whole cell current injection, as well as optogenetic stimulation, and show that nanostimulation performance compares favorably with these techniques. This new nanostimulation approach is easily applied, can be readily performed in awake behaving animals, and thus promises to be a powerful tool for systematic investigations into the temporal elements of neural codes, as well as the mechanisms underlying a wide variety of activity-dependent cellular processes.NEW & NOTEWORTHY Assessing the impact of temporal features of neuronal spike trains requires imposing arbitrary patterns of spiking on individual neurons during behavior, but this has been difficult to achieve due to limitations of existing stimulation methods. We present a technique that overcomes these limitations by using carefully designed short-duration fluctuating juxtacellular current injections, which allow for the precise and reliable evocation of arbitrary patterns of neuronal spikes in single neurons in vivo.

Anti-correlations in the degree distribution increase stimulus detection performance in noisy spiking neural networks

Neuronal circuits in the rodent barrel cortex are characterized by stable low firing rates. However, recent experiments show that short spike trains elicited by electrical stimulation in single neurons can induce behavioral responses. Hence, the underlying neural networks provide stability against internal fluctuations in the firing rate, while simultaneously making the circuits sensitive to small external perturbations. Here we studied whether stability and sensitivity are affected by the connectivity structure in recurrently connected spiking networks. We found that anti-correlation between the number of afferent (in-degree) and efferent (out-degree) synaptic connections of neurons increases stability against pathological bursting, relative to networks where the degrees were either positively correlated or uncorrelated. In the stable network state, stimulation of a few cells could lead to a detectable change in the firing rate. To quantify the ability of networks to detect the stimulation, we used a receiver operating characteristic (ROC) analysis. For a given level of background noise, networks with anti-correlated degrees displayed the lowest false positive rates, and consequently had the highest stimulus detection performance. We propose that anti-correlation in the degree distribution may be a computational strategy employed by sensory cortices to increase the detectability of external stimuli. We show that networks with anti-correlated degrees can in principle be formed by applying learning rules comprised of a combination of spike-timing dependent plasticity, homeostatic plasticity and pruning to networks with uncorrelated degrees. To test our prediction we suggest a novel experimental method to estimate correlations in the degree distribution.

Sparse activity of identified dentate granule cells during spatial exploration

In the dentate gyrus - a key component of spatial memory circuits - granule cells (GCs) are known to be morphologically diverse and to display heterogeneous activity profiles during behavior. To resolve structure-function relationships, we juxtacellularly recorded and labeled single GCs in freely moving rats. We found that the vast majority of neurons were silent during exploration. Most active GCs displayed a characteristic spike waveform, fired at low rates and showed spatial activity. Primary dendritic parameters were sufficient for classifying neurons as active or silent with high accuracy. Our data thus support a sparse coding scheme in the dentate gyrus and provide a possible link between structural and functional heterogeneity among the GC population.

Comment on "Principles of connectivity among morphologically defined cell types in adult neocortex"

Jiang et al (Research Article, 27 November 2015, aac9462) describe detailed experiments that substantially add to the knowledge of cortical microcircuitry and are unique in the number of connections reported and the quality of interneuron reconstruction. The work appeals to experts and laypersons because of the notion that it unveils new principles and provides a complete description of cortical circuits. We provide a counterbalance to the authors' claims to give those less familiar with the minutiae of cortical circuits a better sense of the contributions and the limitations of this study.

The Slip Hypothesis: Tactile Perception and its Neuronal Bases

The slip hypothesis of epicritic tactile perception interprets actively moving sensor and touched objects as a frictional system, known to lead to jerky relative movements called 'slips'. These slips depend on object geometry, forces, material properties, and environmental factors, and, thus, have the power to incorporate coding of the perceptual target, as well as perceptual strategies (sensor movement). Tactile information as transferred by slips will be encoded discontinuously in space and time, because slips sometimes engage only parts of the touching surfaces and appear as discrete and rare events in time. This discontinuity may have forced tactile systems of vibrissae and fingertips to evolve special ways to convert touch signals to a tactile percept.

What single-cell stimulation has told us about neural coding

In recent years, single-cell stimulation experiments have resulted in substantial progress towards directly linking single-cell activity to movement and sensation. Recent advances in electrical recording and stimulation techniques have enabled control of single neuron spiking in vivo and have contributed to our understanding of neuronal coding schemes in the brain. Here, we review single neuron stimulation effects in different brain structures and how they vary with artificially inserted spike patterns. We briefly compare single neuron stimulation with other brain stimulation techniques. A key advantage of single neuron stimulation is the precise control of the evoked spiking patterns. Systematically varying spike patterns and measuring evoked movements and sensations enables 'decoding' of the single-cell spike patterns and provides insights into the readout mechanisms of sensory and motor cortical spikes.

Regulation of Irregular Neuronal Firing by Autaptic Transmission

The importance of self-feedback autaptic transmission in modulating spike-time irregularity is still poorly understood. By using a biophysical model that incorporates autaptic coupling, we here show that self-innervation of neurons participates in the modulation of irregular neuronal firing, primarily by regulating the occurrence frequency of burst firing. In particular, we find that both excitatory and electrical autapses increase the occurrence of burst firing, thus reducing neuronal firing regularity. In contrast, inhibitory autapses suppress burst firing and therefore tend to improve the regularity of neuronal firing. Importantly, we show that these findings are independent of the firing properties of individual neurons, and as such can be observed for neurons operating in different modes. Our results provide an insightful mechanistic understanding of how different types of autapses shape irregular firing at the single-neuron level, and they highlight the functional importance of autaptic self-innervation in taming and modulating neurodynamics.

Cux1 Enables Interhemispheric Connections of Layer II/III Neurons by Regulating Kv1-Dependent Firing

Neuronal subtype-specific transcription factors (TFs) instruct key features of neuronal function and connectivity. Activity-dependent mechanisms also contribute to wiring and circuit assembly, but whether and how they relate to TF-directed neuronal differentiation is poorly investigated. Here we demonstrate that the TF Cux1 controls the formation of the layer II/III corpus callosum (CC) projections through the developmental transcriptional regulation of Kv1 voltage-dependent potassium channels and the resulting postnatal switch to a Kv1-dependent firing mode. Loss of Cux1 function led to a decrease in the expression of Kv1 transcripts, aberrant firing responses, and selective loss of CC contralateral innervation. Firing and innervation were rescued by re-expression of Kv1 or postnatal reactivation of Cux1. Knocking down Kv1 mimicked Cux1-mediated CC axonal loss. These findings reveal that activity-dependent processes are central bona fide components of neuronal TF-differentiation programs and establish the importance of intrinsic firing modes in circuit assembly within the neocortex.

Can Optogenetic Tools Determine the Importance of Temporal Codes to Sensory Information Processing in the Brain?

There is no doubt that optogenetic tools caused a paradigm shift in many fields of neuroscience. These tools enable rapid and reversible intervention with a specific neuronal circuit and then the impact on the remaining circuit and/or behavior can be studied. However, so far the ability of these optogenetic tools to interfere with neuronal signal transmission in the time scale of milliseconds has been used much less frequently although they may help to answer a fundamental question of neuroscience: how important temporal codes are to information processing in the brain. This perspective paper examines why optogenetic tools were used so little to perturb or imitate temporal codes. Although some technical limitations do exist, there is a clear need for a systems approach. More research about action potential pattern formation by interactions between several brain areas is necessary in order to exploit the full potential of optogenetic methods in probing temporal codes.

Mouse V1 population correlates of visual detection rely on heterogeneity within neuronal response patterns

Previous studies have demonstrated the importance of the primary sensory cortex for the detection, discrimination, and awareness of visual stimuli, but it is unknown how neuronal populations in this area process detected and undetected stimuli differently. Critical differences may reside in the mean strength of responses to visual stimuli, as reflected in bulk signals detectable in functional magnetic resonance imaging, electro-encephalogram, or magnetoencephalography studies, or may be more subtly composed of differentiated activity of individual sensory neurons. Quantifying single-cell Ca²⁺ responses to visual stimuli recorded with in vivo two-photon imaging, we found that visual detection correlates more strongly with population response heterogeneity rather than overall response strength. Moreover, neuronal populations showed consistencies in activation patterns across temporally spaced trials in association with hit responses, but not during nondetections. Contrary to models relying on temporally stable networks or bulk signaling, these results suggest that detection depends on transient differentiation in neuronal activity within cortical populations.

DOI:http://dx.doi.org/10.7554/eLife.10163.001

Seeing is not the same as perceiving, where an object is recognized and information about it is interpreted by the brain. Things might be in your field of view, but not actively perceived; for example, when daydreaming with your eyes open. Many researchers have investigated how the brain responds differently to a perceived object compared with something that is seen but not perceived. However, using relatively coarse techniques, only small differences in brain activity have been found.

Many of the techniques used to investigate brain activity only look at the average activity of a group of neurons – the cells in the brain that process information. This raises the possibility that the perception of an object relies on more subtle or complex interactions in brain activity. To investigate this, Montijn et al. trained mice to lick a reward spout that gave out sugar water when they perceived a particular image. A technique called two-photon calcium imaging was then used to simultaneously record the activity of tens to hundreds of neurons in part of the brain called the visual cortex as the mice performed the perception task.

This revealed that the average activation of a group of neurons was only weakly related to whether a mouse had perceived the image. However, differences in the strength of the responses of the individual neurons in the group reflected perception more strongly: when a mouse perceived the image and licked in response, a heterogeneous (non-uniform) set of neuronal responses occurred. The diversity of the neuronal responses could also be used to predict how quickly a mouse would respond to an image. These activity differences would not be picked up by techniques that detect the average activity of many neurons, explaining why these effects had not previously been seen.

These findings shed light on which patterns of activity in the visual region of the brain lead to objects being perceived or not. Whether similar mechanisms operate in different regions of the brain remains to be investigated.

DOI:http://dx.doi.org/10.7554/eLife.10163.002

Behavioral assessment of sensitivity to intracortical microstimulation of primate somatosensory cortex

Intracortical microstimulation (ICMS) is a powerful tool to investigate the functional role of neural circuits and may provide a means to restore sensation for patients for whom peripheral stimulation is not an option. In a series of psychophysical experiments with nonhuman primates, we investigate how stimulation parameters affect behavioral sensitivity to ICMS. Specifically, we deliver ICMS to primary somatosensory cortex through chronically implanted electrode arrays across a wide range of stimulation regimes. First, we investigate how the detectability of ICMS depends on stimulation parameters, including pulse width, frequency, amplitude, and pulse train duration. Then, we characterize the degree to which ICMS pulse trains that differ in amplitude lead to discriminable percepts across the range of perceptible and safe amplitudes. We also investigate how discriminability of pulse amplitude is modulated by other stimulation parameters-namely, frequency and duration. Perceptual judgments obtained across these various conditions will inform the design of stimulation regimes for neuroscience and neuroengineering applications.

GABAergic inhibition shapes interictal dynamics in awake epileptic mice

Epilepsy is characterized by recurrent seizures and brief, synchronous bursts called interictal spikes that are present in-between seizures and observed as transient events in EEG signals. While GABAergic transmission is known to play an important role in shaping healthy brain activity, the role of inhibition in these pathological epileptic dynamics remains unclear. Examining the microcircuits that participate in interictal spikes is thus an important first step towards addressing this issue, as the function of these transient synchronizations in either promoting or prohibiting seizures is currently under debate. To identify the microcircuits recruited in spontaneous interictal spikes in the absence of any proconvulsive drug or anaesthetic agent, we combine a chronic model of epilepsy with in vivo two-photon calcium imaging and multiunit extracellular recordings to map cellular recruitment within large populations of CA1 neurons in mice free to run on a self-paced treadmill. We show that GABAergic neurons, as opposed to their glutamatergic counterparts, are preferentially recruited during spontaneous interictal activity in the CA1 region of the epileptic mouse hippocampus. Although the specific cellular dynamics of interictal spikes are found to be highly variable, they are consistently associated with the activation of GABAergic neurons, resulting in a perisomatic inhibitory restraint that reduces neuronal spiking in the principal cell layer. Given the role of GABAergic neurons in shaping brain activity during normal cognitive function, their aberrant unbalanced recruitment during these transient events could have important downstream effects with clinical implications.

Memory formation and retrieval of neuronal silencing in the auditory cortex

Sensory stimuli not only activate specific populations of cortical neurons but can also silence other populations. However, it remains unclear whether neuronal silencing per se leads to memory formation and behavioral expression. Here we show that mice can report optogenetic inactivation of auditory neuron ensembles by exhibiting fear responses or seeking a reward. Mice receiving pairings of footshock and silencing of a neuronal ensemble exhibited a fear response selectively to the subsequent silencing of the same ensemble. The valence of the neuronal silencing was preserved for at least 30 d and was susceptible to extinction training. When we silenced an ensemble in one side of auditory cortex for conditioning, silencing of an ensemble in another side induced no fear response. We also found that mice can find a reward based on the presence or absence of the silencing. Neuronal silencing was stored as working memory. Taken together, we propose that neuronal silencing without explicit activation in the cerebral cortex is enough to elicit a cognitive behavior.