Imbalance between excitation and inhibition in the somatosensory cortex produces postadaptation facilitation

Short-term plasticity and context-dependent circuit function: Insights from retinal circuitry

Changes in synaptic strength across timescales are integral to algorithmic operations of neural circuits. However, pinpointing synaptic loci that undergo plasticity in intact brain circuits and delineating contributions of synaptic plasticity to circuit function remain challenging. The whole-mount retina preparation provides an accessible platform for measuring plasticity at specific synapses while monitoring circuit-level behaviors during visual processing ex vivo. In this review, we discuss insights gained from retina studies into the versatile roles of short-term synaptic plasticity in context-dependent circuit functions. Plasticity at single synapse level greatly expands the algorithms of common microcircuit motifs and contributes to diverse circuit-level behaviors such as gain modulation, selective gating, and stimulus-dependent excitatory/inhibitory balance. Examples in retinal circuitry offer unequivocal support that synaptic plasticity increases the computational capacity of hardwired neural circuitry.

Dynamic fading memory and expectancy effects in the monkey primary visual cortex

In order to investigate the involvement of the primary visual cortex (V1) in working memory (WM), parallel, multisite recordings of multi-unit activity were obtained from monkey V1 while the animals performed a delayed match-to-sample (DMS) task. During the delay period, V1 population firing rate vectors maintained a lingering trace of the sample stimulus that could be reactivated by intervening impulse stimuli that enhanced neuronal firing. This fading trace of the sample did not require active engagement of the monkeys in the DMS task and likely reflects the intrinsic dynamics of recurrent cortical networks in lower visual areas. This renders an active, attention-dependent involvement of V1 in the maintenance of WM contents unlikely. By contrast, population responses to the test stimulus depended on the probabilistic contingencies between sample and test stimuli. Responses to tests that matched expectations were reduced which agrees with concepts of predictive coding.

Cell-specific NFIA upregulation promotes epileptogenesis by TRPV4-mediated astrocyte reactivity

BACKGROUND

The astrocytes in the central nervous system (CNS) exhibit morphological and functional diversity in brain region-specific pattern. Functional alterations of reactive astrocytes are commonly present in human temporal lobe epilepsy (TLE) cases, meanwhile the neuroinflammation mediated by reactive astrocytes may advance the development of hippocampal epilepsy in animal models. Nuclear factor I-A (NFIA) may regulate astrocyte diversity in the adult brain. However, whether NFIA endows the astrocytes with regional specificity to be involved in epileptogenesis remains elusive.

METHODS

Here, we utilize an interference RNA targeting NFIA to explore the characteristics of NFIA expression and its role in astrocyte reactivity in a 4-aminopyridine (4-AP)-induced seizure model in vivo and in vitro. Combined with the employment of a HA-tagged plasmid overexpressing NFIA, we further investigate the precise mechanisms how NIFA facilitates epileptogenesis.

RESULTS

4-AP-induced NFIA upregulation in hippocampal region is astrocyte-specific, and primarily promotes detrimental actions of reactive astrocyte. In line with this phenomenon, both NFIA and vanilloid transient receptor potential 4 (TRPV4) are upregulated in hippocampal astrocytes in human samples from the TLE surgical patients and mouse samples with intraperitoneal 4-AP. NFIA directly regulates mouse astrocytic TRPV4 expression while the quantity and the functional activity of TRPV4 are required for 4-AP-induced astrocyte reactivity and release of proinflammatory cytokines in the charge of NFIA upregulation. NFIA deficiency efficiently inhibits 4-AP-induced TRPV4 upregulation, weakens astrocytic calcium activity and specific astrocyte reactivity, thereby mitigating aberrant neuronal discharges and neuronal damage, and suppressing epileptic seizure.

CONCLUSIONS

Our results uncover the critical role of NFIA in astrocyte reactivity and illustrate how epileptogenic brain injury initiates cell-specific signaling pathway to dictate the astrocyte responses.

Recovery kinetics of short-term depression of GABAergic and glutamatergic synapses at layer 2/3 pyramidal cells in the mouse barrel cortex

Introduction

Short-term synaptic plasticity (STP) is a widespread mechanism underlying activity-dependent modifications of cortical networks.

Methods

To investigate how STP influences excitatory and inhibitory synapses in layer 2/3 of mouse barrel cortex, we combined whole-cell patch-clamp recordings from visually identified pyramidal neurons (PyrN) and parvalbumin-positive interneurons (PV-IN) of cortical layer 2/3 in acute slices with electrical stimulation of afferent fibers in layer 4 and optogenetic activation of PV-IN.

Results

These experiments revealed that electrical burst stimulation (10 pulses at 10 Hz) of layer 4 afferents to layer 2/3 neurons induced comparable short-term depression (STD) of glutamatergic postsynaptic currents (PSCs) in PyrN and in PV-IN, while disynaptic GABAergic PSCs in PyrN showed a stronger depression. Burst-induced depression of glutamatergic PSCs decayed within <4 s, while the decay of GABAergic PSCs required >11 s. Optogenetically-induced GABAergic PSCs in PyrN also demonstrated STD after burst stimulation, with a decay of >11 s. Excitatory postsynaptic potentials (EPSPs) in PyrN were unaffected after electrical burst stimulation, while a selective optogenetic STD of GABAergic synapses caused a transient increase of electrically evoked EPSPs in PyrN.

Discussion

In summary, these results demonstrate substantial short-term plasticity at all synapses investigated and suggest that the prominent STD observed in GABAergic synapses can moderate the functional efficacy of glutamatergic STD after repetitive synaptic stimulations. This mechanism may contribute to a reliable information flow toward the integrative layer 2/3 for complex time-varying sensory stimuli.

Sensory adaptation mediates efficient and unambiguous encoding of natural stimuli by vestibular thalamocortical pathways

Sensory systems must continuously adapt to optimally encode stimuli encountered within the natural environment. The prevailing view is that such optimal coding comes at the cost of increased ambiguity, yet to date, prior studies have focused on artificial stimuli. Accordingly, here we investigated whether such a trade-off between optimality and ambiguity exists in the encoding of natural stimuli in the vestibular system. We recorded vestibular nuclei and their target vestibular thalamocortical neurons during naturalistic and artificial self-motion stimulation. Surprisingly, we found no trade-off between optimality and ambiguity. Using computational methods, we demonstrate that thalamocortical neural adaptation in the form of contrast gain control actually reduces coding ambiguity without compromising the optimality of coding under naturalistic but not artificial stimulation. Thus, taken together, our results challenge the common wisdom that adaptation leads to ambiguity and instead suggest an essential role in underlying unambiguous optimized encoding of natural stimuli.

Sensory Adaptation in the Whisker-Mediated Tactile System: Physiology, Theory, and Function

In the natural environment, organisms are constantly exposed to a continuous stream of sensory input. The dynamics of sensory input changes with organism's behaviour and environmental context. The contextual variations may induce >100-fold change in the parameters of the stimulation that an animal experiences. Thus, it is vital for the organism to adapt to the new diet of stimulation. The response properties of neurons, in turn, dynamically adjust to the prevailing properties of sensory stimulation, a process known as "neuronal adaptation." Neuronal adaptation is a ubiquitous phenomenon across all sensory modalities and occurs at different stages of processing from periphery to cortex. In spite of the wealth of research on contextual modulation and neuronal adaptation in visual and auditory systems, the neuronal and computational basis of sensory adaptation in somatosensory system is less understood. Here, we summarise the recent finding and views about the neuronal adaptation in the rodent whisker-mediated tactile system and further summarise the functional effect of neuronal adaptation on the response dynamics and encoding efficiency of neurons at single cell and population levels along the whisker-mediated touch system in rodents. Based on direct and indirect pieces of evidence presented here, we suggest sensory adaptation provides context-dependent functional mechanisms for noise reduction in sensory processing, salience processing and deviant stimulus detection, shift between integration and coincidence detection, band-pass frequency filtering, adjusting neuronal receptive fields, enhancing neural coding and improving discriminability around adapting stimuli, energy conservation, and disambiguating encoding of principal features of tactile stimuli.

The generation of cortical novelty responses through inhibitory plasticity

Animals depend on fast and reliable detection of novel stimuli in their environment. Neurons in multiple sensory areas respond more strongly to novel in comparison to familiar stimuli. Yet, it remains unclear which circuit, cellular, and synaptic mechanisms underlie those responses. Here, we show that spike-timing-dependent plasticity of inhibitory-to-excitatory synapses generates novelty responses in a recurrent spiking network model. Inhibitory plasticity increases the inhibition onto excitatory neurons tuned to familiar stimuli, while inhibition for novel stimuli remains low, leading to a network novelty response. The generation of novelty responses does not depend on the periodicity but rather on the distribution of presented stimuli. By including tuning of inhibitory neurons, the network further captures stimulus-specific adaptation. Finally, we suggest that disinhibition can control the amplification of novelty responses. Therefore, inhibitory plasticity provides a flexible, biologically plausible mechanism to detect the novelty of bottom-up stimuli, enabling us to make experimentally testable predictions.

Rapid Cortical Adaptation and the Role of Thalamic Synchrony during Wakefulness

Rapid sensory adaptation is observed across all sensory systems, and strongly shapes sensory percepts in complex sensory environments. Yet despite its ubiquity and likely necessity for survival, the mechanistic basis is poorly understood. A wide range of primarily in vitro and anesthetized studies have demonstrated the emergence of adaptation at the level of primary sensory cortex, with only modest signatures in earlier stages of processing. The nature of rapid adaptation and how it shapes sensory representations during wakefulness, and thus the potential role in perceptual adaptation, is underexplored, as are the mechanisms that underlie this phenomenon. To address these knowledge gaps, we recorded spiking activity in primary somatosensory cortex (S1) and the upstream ventral posteromedial (VPm) thalamic nucleus in the vibrissa pathway of awake male and female mice, and quantified responses to whisker stimuli delivered in isolation and embedded in an adapting sensory background. We found that cortical sensory responses were indeed adapted by persistent sensory stimulation; putative excitatory neurons were profoundly adapted, and inhibitory neurons only modestly so. Further optogenetic manipulation experiments and network modeling suggest this largely reflects adaptive changes in synchronous thalamic firing combined with robust engagement of feedforward inhibition, with little contribution from synaptic depression. Taken together, these results suggest that cortical adaptation in the regime explored here results from changes in the timing of thalamic input, and the way in which this differentially impacts cortical excitation and feedforward inhibition, pointing to a prominent role of thalamic gating in rapid adaptation of primary sensory cortex.SIGNIFICANCE STATEMENT Rapid adaptation of sensory activity strongly shapes representations of sensory inputs across all sensory pathways over the timescale of seconds, and has profound effects on sensory perception. Despite its ubiquity and theoretical role in the efficient encoding of complex sensory environments, the mechanistic basis is poorly understood, particularly during wakefulness. In this study in the vibrissa pathway of awake mice, we show that cortical representations of sensory inputs are strongly shaped by rapid adaptation, and that this is mediated primarily by adaptive gating of the thalamic inputs to primary sensory cortex and the differential way in which these inputs engage cortical subpopulations of neurons.

Autonomic and Electrophysiological Evidence for Reduced Auditory Habituation in Autism

It is estimated that nearly 90% of children on the autism spectrum exhibit sensory atypicalities. What aspects of sensory processing are affected in autism? Although sensory processing can be studied along multiple dimensions, two of the most basic ones involve examining instantaneous sensory responses and how the responses change over time. These correspond to the dimensions of 'sensitivity' and 'habituation'. Results thus far have indicated that autistic individuals do not differ systematically from controls in sensory acuity/sensitivity. However, data from studies of habituation have been equivocal. We have studied habituation in autism using two measures: galvanic skin response (GSR) and magneto-encephalography (MEG). We report data from two independent studies. The first study, was conducted with 13 autistic and 13 age-matched neurotypical young adults and used GSR to assess response to an extended metronomic sequence. The second study involved 24 participants (12 with an ASD diagnosis), different from those in study 1, spanning the pre-adolescent to young adult age range, and used MEG. Both studies reveal consistent patterns of reduced habituation in autistic participants. These results suggest that autism, through mechanisms that are yet to be elucidated, compromises a fundamental aspect of sensory processing, at least in the auditory domain. We discuss the implications for understanding sensory hypersensitivities, a hallmark phenotypic feature of autism, recently proposed theoretical accounts, and potential relevance for early detection of risk for autism.

Is It Possible to Improve Working Memory With Prefrontal tDCS? Bridging Currents to Working Memory Models

A great deal of research has been performed with the promise of improving such critical cognitive functions as working memory (WM), with transcranial direct current stimulation (tDCS), a well-tolerated, inexpensive, easy-to-use intervention. Under the assumption that by delivering currents through electrodes placed in suitable locations on the scalp, it is possible to increase prefrontal cortex excitability and therefore improve WM. A growing number of studies have led to mixed results, leading to the realization that such oversimplified assumptions need revision. Models spanning currents to behavior have been advocated in order to reconcile and inform neurostimulation investigations. We articulate such multilevel exploration to tDCS/WM by briefly reviewing critical aspects at each level of analysis but focusing on the circuit level and how available biophysical WM models could inform tDCS. Indeed, such models should replace vague reference to cortical excitability changes with relevant tDCS net effects affecting neural computation and behavior in a more predictable manner. We will refer to emerging WM models and explore to what extent the general concept of excitation-inhibition (E/I) balance is a meaningful intermediate level of analysis, its relationship with gamma oscillatory activity, and the extent to which it can index tDCS effects. We will highlight some predictions that appear consistent with empirical evidence – such as non-linearities and trait dependency of effects and possibly a preferential effect on WM control functions – as well as limitations that appear related to the dynamical aspects of coding by persistent activity.

Synaptic Recruitment Enhances Gap Termination Responses in Auditory Cortex

The ability to detect short gaps in noise is an important tool for assessing the temporal resolution in the auditory cortex. However, the mere existence of responses to temporal gaps bounded by two short broadband markers is surprising, because of the expected short-term suppression that is prevalent in auditory cortex. Here, we used in-vivo intracellular recordings in anesthetized rats to dissect the synaptic mechanisms that underlie gap-related responses. When a gap is bounded by two short markers, a gap termination response was evoked by the onset of the second marker with minimal contribution from the offset of the first marker. Importantly, we show that the gap termination response was driven by a different (potentially partially overlapping) synaptic population than that underlying the onset response to the first marker. This recruitment of additional synaptic resources is a novel mechanism contributing to the important perceptual task of gap detection.

Multiple Timescales Account for Adaptive Responses across Sensory Cortices

Sensory systems encounter remarkably diverse stimuli in the external environment. Natural stimuli exhibit timescales and amplitudes of variation that span a wide range. Mechanisms of adaptation, a ubiquitous feature of sensory systems, allow for the accommodation of this range of scales. Are there common rules of adaptation across different sensory modalities? We measured the membrane potential responses of individual neurons in the visual, somatosensory, and auditory cortices of male and female mice to discrete, punctate stimuli delivered at a wide range of fixed and nonfixed frequencies. We find that the adaptive profile of the response is largely preserved across these three areas, exhibiting attenuation and responses to the cessation of stimulation, which are signatures of response to changes in stimulus statistics. We demonstrate that these adaptive responses can emerge from a simple model based on the integration of fixed filters operating over multiple time scales.SIGNIFICANCE STATEMENT Our recent sensations affect our current expectations and perceptions of the environment. Neural correlates of this process exist throughout the brain and are loosely termed adaptation. Adaptive processes have been described across sensory cortices, but direct comparisons of these processes have not been possible because paradigms have been tailored specifically for each modality. We developed a common stimulus set that was used to characterize adaptation in somatosensory, visual, and auditory cortex. We describe here the similarities and differences in adaptation across these cortical areas and demonstrate that adaptive responses may emerge from a set of static filters that operate over a broad range of timescales.

Neural sensitization improves encoding fidelity in the primate retina

An animal’s motion through the environment can induce large and frequent fluctuations in light intensity on the retina. These fluctuations pose a major challenge to neural circuits tasked with encoding visual information, as they can cause cells to adapt and lose sensitivity. Here, we report that sensitization, a short-term plasticity mechanism, solves this difficult computational problem by maintaining neuronal sensitivity in the face of these fluctuations. The numerically dominant output pathway in the macaque monkey retina, the midget (parvocellular-projecting) pathway, undergoes sensitization under specific conditions, including simulated eye movements. Sensitization is present in the excitatory synaptic inputs from midget bipolar cells and is mediated by presynaptic disinhibition from a wide-field mechanism extending >0.5 mm along the retinal surface. Direct physiological recordings and a computational model indicate that sensitization in the midget pathway supports accurate sensory encoding and prevents a loss of responsiveness during dynamic visual processing.

Light intensity on the retina can fluctuate rapidly during natural vision, posing a challenge for encoding visual information. Here, the authors report that mechanisms of sensitization/facilitation maintain the sensitivity of the numerically dominant neural pathway in the primate retina during dynamic vision.

Adaptation of Inhibition Mediates Retinal Sensitization

In response to a changing sensory environment, sensory systems adjust their neural code for a number of purposes, including an enhanced sensitivity for novel stimuli, prediction of sensory features, and the maintenance of sensitivity. Retinal sensitization is a form of short-term plasticity that elevates local sensitivity following strong, local, visual stimulation and has been shown to create a prediction of the presence of a nearby localized object. The neural mechanism that generates this elevation in sensitivity remains unknown. Using simultaneous intracellular and multielectrode recording in the salamander retina, we show that a decrease in tonic amacrine transmission is necessary for and is correlated spatially and temporally with ganglion cell sensitization. Furthermore, introducing a decrease in amacrine transmission is sufficient to sensitize nearby ganglion cells. A computational model accounting for adaptive dynamics and nonlinear pathways confirms a decrease in steady inhibitory transmission can cause sensitization. Adaptation of inhibition enhances the sensitivity to the sensory feature conveyed by an inhibitory pathway, creating a prediction of future input.

Imaging localized neuronal activity at fast time scales through biomechanics

Mapping neuronal activity noninvasively is a key requirement for in vivo human neuroscience. Traditional functional magnetic resonance (MR) imaging, with a temporal response of seconds, cannot measure high-level cognitive processes evolving in tens of milliseconds. To advance neuroscience, imaging of fast neuronal processes is required. Here, we show in vivo imaging of fast neuronal processes at 100-ms time scales by quantifying brain biomechanics noninvasively with MR elastography. We show brain stiffness changes of ~10% in response to repetitive electric stimulation of a mouse hind paw over two orders of frequency from 0.1 to 10 Hz. We demonstrate in mice that regional patterns of stiffness modulation are synchronous with stimulus switching and evolve with frequency. For very fast stimuli (100 ms), mechanical changes are mainly located in the thalamus, the relay location for afferent cortical input. Our results demonstrate a new methodology for noninvasively tracking brain functional activity at high speed.

Short-Term Synaptic Plasticity as a Mechanism for Sensory Timing

The ability to detect time intervals and temporal patterns is critical to some of the most fundamental computations the brain performs, including the ability to communicate and appraise a dynamically changing environment. Many of these computations take place on the scale of tens to hundreds of milliseconds. Electrophysiological evidence shows that some neurons respond selectively to duration, interval, rate, or order. Because the time constants of many time-varying neural and synaptic properties, including short-term synaptic plasticity (STP), are also in the range of tens to hundreds of milliseconds, they are strong candidates to underlie the formation of temporally selective neurons. Neurophysiological studies indicate that STP is indeed one of the mechanisms that contributes to temporal selectivity, and computational models demonstrate that neurons embedded in local microcircuits exhibit temporal selectivity if their synapses undergo STP. Converging evidence suggests that some forms of temporal selectivity emerge from the dynamic changes in the balance of excitation and inhibition imposed by STP.

Imbalanced amplification: A mechanism of amplification and suppression from local imbalance of excitation and inhibition in cortical circuits

Understanding the relationship between external stimuli and the spiking activity of cortical populations is a central problem in neuroscience. Dense recurrent connectivity in local cortical circuits can lead to counterintuitive response properties, raising the question of whether there are simple arithmetical rules for relating circuits’ connectivity structure to their response properties. One such arithmetic is provided by the mean field theory of balanced networks, which is derived in a limit where excitatory and inhibitory synaptic currents precisely balance on average. However, balanced network theory is not applicable to some biologically relevant connectivity structures. We show that cortical circuits with such structure are susceptible to an amplification mechanism arising when excitatory-inhibitory balance is broken at the level of local subpopulations, but maintained at a global level. This amplification, which can be quantified by a linear correction to the classical mean field theory of balanced networks, explains several response properties observed in cortical recordings and provides fundamental insights into the relationship between connectivity structure and neural responses in cortical circuits.

Understanding how the brain represents and processes stimuli requires a quantitative understanding of how signals propagate through networks of neurons. Developing such an understanding is made difficult by the dense interconnectivity of neurons, especially in the cerebral cortex. One approach to quantifying neural processing in the cortex is derived from observations that excitatory (positive) and inhibitory (negative) interactions between neurons tend to balance each other in many brain areas. This balance is achieved under a class of computational models called “balanced networks.” However, previous approaches to the mathematical analysis of balanced network models is not possible under some biologically relevant connectivity structures. We show that, under these structures, balance between excitation and inhibition is necessarily broken and the resulting imbalance causes some stimulus features to be amplified. This “imbalanced amplification” of stimuli can explain several observations from recordings in mouse somatosensory and visual cortical circuits and provides fundamental insights into the relationship between connectivity structure and neural responses in cortical circuits.

Deviant Processing in the Primary Somatosensory Cortex

Stimulus-specific adaptation (SSA) to repetitive stimulation has been proposed to separate behaviorally relevant features from a stream of continuous sensory information. However, the exact mechanisms giving rise to SSA and cortical deviance detection are not well understood. We therefore used an oddball paradigm and multicontact electrodes to characterize single-neuron and local field potential responses to various deviant stimuli across the rat somatosensory cortex. Changing different single-whisker stimulus features evoked robust SSA in individual cortical neurons over a wide range of stimulus repetition rates (0.25-80 Hz). Notably, SSA was weakest in the granular input layer and significantly stronger in the supra- and infragranular layers, suggesting that a major part of SSA is generated within cortex. Moreover, we found a small subset of neurons in the granular layer with a deviant-specific late response, occurring roughly 200 ms after stimulus offset. This late deviant response exhibited true-deviance detection properties that were not explained by depression of sensory inputs. Our results show that deviant responses are actively amplified within cortex and contain an additional late component that is sensitive for context-specific sensory deviations. This strongly implicates deviance detection as a feature of intracortical stimulus processing beyond simple sensory input depression.

Repetition suppression: a means to index neural representations using BOLD?

Understanding how the human brain gives rise to complex cognitive processes remains one of the biggest challenges of contemporary neuroscience. While invasive recording in animal models can provide insight into neural processes that are conserved across species, our understanding of cognition more broadly relies upon investigation of the human brain itself. There is therefore an imperative to establish non-invasive tools that allow human brain activity to be measured at high spatial and temporal resolution. In recent years, various attempts have been made to refine the coarse signal available in functional magnetic resonance imaging (fMRI), providing a means to investigate neural activity at the meso-scale, i.e. at the level of neural populations. The most widely used techniques include repetition suppression and multivariate pattern analysis. Human neuroscience can now use these techniques to investigate how representations are encoded across neural populations and transformed by relevant computations. Here, we review the physiological basis, applications and limitations of fMRI repetition suppression with a brief comparison to multivariate techniques. By doing so, we show how fMRI repetition suppression holds promise as a tool to reveal complex neural mechanisms that underlie human cognitive function.

This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’.

The effects of dynamical synapses on firing rate activity: a spiking neural network model

Accumulating evidence relates the fine-tuning of synaptic maturation and regulation of neural network activity to several key factors, including GABA_A signaling and a lateral spread length between neighboring neurons (i.e., local connectivity). Furthermore, a number of studies consider short-term synaptic plasticity (STP) as an essential element in the instant modification of synaptic efficacy in the neuronal network and in modulating responses to sustained ranges of external Poisson input frequency (IF). Nevertheless, evaluating the firing activity in response to the dynamical interaction between STP (triggered by ranges of IF) and these key parameters in vitro remains elusive. Therefore, we designed a spiking neural network (SNN) model in which we incorporated the following parameters: local density of arbor essences and a lateral spread length between neighboring neurons. We also created several network scenarios based on these key parameters. Then, we implemented two classes of STP: (1) short-term synaptic depression (STD) and (2) short-term synaptic facilitation (STF). Each class has two differential forms based on the parametric value of its synaptic time constant (either for depressing or facilitating synapses). Lastly, we compared the neural firing responses before and after the treatment with STP. We found that dynamical synapses (STP) have a critical differential role on evaluating and modulating the firing rate activity in each network scenario. Moreover, we investigated the impact of changing the balance between excitation (E) and inhibition (I) on stabilizing this firing activity.

Response dynamics of rat barrel cortex neurons to repeated sensory stimulation

Neuronal adaptation is a common feature observed at various stages of sensory processing. Here, we quantified the time course of adaptation in rat somatosensory cortex. Under urethane anesthesia, we juxta-cellularly recorded single neurons (n = 147) while applying a series of whisker deflections at various frequencies (2-32 Hz). For ~90% of neurons, the response per unit of time decreased with frequency. The degree of adaptation increased along the train of deflections and was strongest at the highest frequency. However, a subset of neurons showed facilitation producing higher responses to subsequent deflections. The response latency to consecutive deflections increased both for neurons that exhibited adaptation and for those that exhibited response facilitation. Histological reconstruction of neurons (n = 45) did not reveal a systematic relationship between adaptation profiles and cell types. In addition to the periodic stimuli, we applied a temporally irregular train of deflections with a mean frequency of 8 Hz. For 70% of neurons, the response to the irregular stimulus was greater than that of the 8 Hz regular. This increased response to irregular stimulation was positively correlated with the degree of adaptation. Altogether, our findings demonstrate high levels of diversity among cortical neurons, with a proportion of neurons showing facilitation at specific temporal intervals.

High-velocity stimulation evokes "dense" population response in layer 2/3 vibrissal cortex

Supragranular layers of sensory cortex are known to exhibit sparse firing. In rodent vibrissal cortex, a small fraction of neurons in layer 2 and 3 (L2/3) respond to whisker stimulation. In this study, we combined whole cell recording and two-photon imaging in anesthetized mice and quantified the synaptic response and spiking profile of L2/3 neurons. Previous literature has shown that neurons across layers of vibrissal cortex are tuned to the velocity of whisker movement. We therefore used a broad range of stimuli that included the standard range of velocities (0-1.2 deg/ms) and extended to a "sharp" high-velocity deflection (3.8 deg/ms). Consistent with previous literature, whole cell recording revealed a sparse response to the standard range of velocities: although all recorded cells showed tuning to velocity in their postsynaptic potentials, only a small fraction produced stimulus-evoked spikes. In contrast, the sharp stimulus evoked reliable spiking in the majority of neurons. The action potential threshold of spikes evoked by the sharp stimulus was significantly lower than that of the spontaneous spikes. Juxtacellular recordings confirmed that application of sharp stimulus to single or multiple whiskers produced temporally precise spiking with minimal trial-to-trial spike count variability (Fano factors equal or close to the theoretical minimum). Two-photon imaging further confirmed that most neurons that were not responsive to the standard deflections responded to the sharp stimulus. Altogether, our results indicate that sparseness in L2/3 cortex depends on the choice of stimulus: strong single- or multiwhisker stimulation can induce the transition from sparse to "dense" population response.NEW & NOTEWORTHY In superficial layers of sensory cortex, only a small fraction of neurons fire most of the spontaneous and sensory evoked spikes. However, the functional relevance of such "sparse" activity remains unknown. We found that a "dense" population response is evoked by high-velocity micromotions applied to whiskers. Our results suggest that flashes of precisely timed population response on an almost silent background can provide a high capacity for coding of ecologically salient stimuli.

Rapid Sensory Adaptation Redux: A Circuit Perspective

Adaptation is fundamental to life. All organisms adapt over timescales that span from evolution to generations and lifetimes to moment-by-moment interactions. The nervous system is particularly adept at rapidly adapting to change, and this in fact may be one of its fundamental principles of organization and function. Rapid forms of sensory adaptation have been well documented across all sensory modalities in a wide range of organisms, yet we do not have a comprehensive understanding of the adaptive cellular mechanisms that ultimately give rise to the corresponding percepts, due in part to the complexity of the circuitry. In this Perspective, we aim to build links between adaptation at multiple scales of neural circuitry by investigating the differential adaptation across brain regions and sub-regions and across specific cell types, for which the explosion of modern tools has just begun to enable. This investigation points to a set of challenges for the field to link functional observations to adaptive properties of the neural circuit that ultimately underlie percepts.

Local and thalamic origins of correlated ongoing and sensory-evoked cortical activities

Thalamic inputs of cells in sensory cortices are outnumbered by local connections. Thus, it was suggested that robust sensory response in layer 4 emerges due to synchronized thalamic activity. To investigate the role of both inputs in the generation of correlated cortical activities, we isolated the thalamic excitatory inputs of cortical cells by optogenetically silencing cortical firing. In anaesthetized mice, we measured the correlation between isolated thalamic synaptic inputs of simultaneously patched nearby layer 4 cells of the barrel cortex. Here we report that in contrast to correlated activity of excitatory synaptic inputs in the intact cortex, isolated thalamic inputs exhibit lower variability and asynchronous spontaneous and sensory-evoked inputs. These results are further supported in awake mice when we recorded the excitatory inputs of individual cortical cells simultaneously with the local field potential in a nearby site. Our results therefore indicate that cortical synchronization emerges by intracortical coupling.

Sensory cortices receive input from cortical cells and the thalamus, yet it is unknown how these inputs interact to generate synchronous activity. Here authors show that unlike cortical inputs, thalamic inputs are asynchronous, suggesting that cortical synchronization is due to intracortical coupling.

The Transformation of Adaptation Specificity to Whisker Identity from Brainstem to Thalamus

Stimulus specific adaptation has been studied extensively in different modalities. High specificity implies that deviant stimulus induces a stronger response compared to a common stimulus. The thalamus gates sensory information to the cortex, therefore, the specificity of adaptation in the thalamus must have a great impact on cortical processing of sensory inputs. We studied the specificity of adaptation to whisker identity in the ventral posteromedial nucleus of the thalamus (VPM) in rats using extracellular and intracellular recordings. We found that subsequent to repetitive stimulation that induced strong adaptation, the response to stimulation of the same, or any other responsive whisker was equally adapted, indicating that thalamic adaptation is non-specific. In contrast, adaptation of single units in the upstream brainstem principal trigeminal nucleus (PrV) was significantly more specific. Depolarization of intracellularly recorded VPM cells demonstrated that adaptation is not due to buildup of inhibition. In addition, adaptation increased the probability of observing complete synaptic failures to tactile stimulation. In accordance with short-term synaptic depression models, the evoked synaptic potentials in response to whisker stimulation, subsequent to a response failure, were facilitated. In summary, we show that local short-term synaptic plasticity is involved in the transformation of adaptation in the trigemino-thalamic synapse and that the low specificity of adaptation in the VPM emerges locally rather than cascades from earlier stages. Taken together we suggest that during sustained stimulation, local thalamic mechanisms equally suppress inputs arriving from different whiskers before being gated to the cortex.

Specific Early and Late Oddball-Evoked Responses in Excitatory and Inhibitory Neurons of Mouse Auditory Cortex

A major challenge for sensory processing in the brain is considering stimulus context, such as stimulus probability, which may be relevant for survival. Excitatory neurons in auditory cortex, for example, adapt to repetitive tones in a stimulus-specific manner without fully generalizing to a low-probability deviant tone ("oddball") that breaks the preceding regularity. Whether such stimulus-specific adaptation (SSA) also prevails in inhibitory neurons and how it might relate to deviance detection remains elusive. We obtained whole-cell recordings from excitatory neurons and somatostatin- and parvalbumin-positive GABAergic interneurons in layer 2/3 of mouse auditory cortex and measured tone-evoked membrane potential responses. All cell types displayed SSA of fast ("early") subthreshold and suprathreshold responses with oddball tones of a deviant frequency eliciting enlarged responses compared with adapted standards. SSA was especially strong when oddball frequency matched neuronal preference. In addition, we identified a slower "late" response component (200-400 ms after tone onset), most clearly in excitatory and parvalbumin-positive neurons, which also displayed SSA. For excitatory neurons, this late component reflected genuine deviance detection. Moreover, intracellular blockade of NMDA receptors reduced early and late responses in excitatory but not parvalbumin-positive neurons. The late component in excitatory neurons thus shares time course, deviance detection, and pharmacological features with the deviant-evoked event-related potential known as mismatch negativity (MMN) and provides a potential link between neuronal SSA and MMN. In summary, our results suggest a two-phase cortical activation upon oddball stimulation, with oddball tones first reactivating the adapted auditory cortex circuitry and subsequently triggering delayed reverberating network activity. Significance statement: Understanding how the brain encodes sensory context in addition to stimulus feature has been a main focus in neuroscience. Using in vivo targeted whole-cell recordings from excitatory and inhibitory neurons of mouse primary auditory cortex, we report two temporally distinct components of membrane potential responses encoding oddball tones that break stimulus regularity. Both components display stimulus-specific adaptation upon oddball paradigm stimulation in the three recorded cell types. The late response component, in particular, carries signatures of genuine deviance detection. In excitatory but not parvalbumin-positive inhibitory neurons, both early and late components depend on NMDA receptor-signaling. Our work proposes a potential neuronal substrate of a known deviant-evoked event-related potential, which is of fundamental significance in basic and clinical neuroscience.

Synaptic plasticity as a cortical coding scheme

Processing of auditory information requires constant adjustment due to alterations of the environment and changing conditions in the nervous system with age, health, and experience. Consequently, patterns of activity in cortical networks have complex dynamics over a wide range of timescales, from milliseconds to days and longer. In the primary auditory cortex (AI), multiple forms of adaptation and plasticity shape synaptic input and action potential output. However, the variance of neuronal responses has made it difficult to characterize AI receptive fields and to determine the function of AI in processing auditory information such as vocalizations. Here we describe recent studies on the temporal modulation of cortical responses and consider the relation of synaptic plasticity to neural coding.

Adaptation of the cortical somatosensory evoked potential following pulsed pneumatic stimulation of the lower face in adults

Cortical adaptation to sustained sensory input is a pervasive form of short-term plasticity in neurological systems. Its role in sensory perception in health and disease, or predicting long-term plastic changes resulting from sensory training offers insight into the mechanisms of somatosensory and sensorimotor processing. A 4-channel electroencephalography (EEG) recording montage was placed bilaterally (C3-P3, C4-P4, F7-P3, F8-P4) to characterize the short-term effects of pulsed pneumatic orofacial stimulation on the cortical somatosensory evoked potential (cSEP) in twenty neurotypical adults (mean age=21±2.88 years). A servo-controlled pneumatic amplifier was used to deliver a repetitive series of pneumatic pulse trains (six 50-ms pulses, 5-second intertrain interval) through a linked pair of custom acetal homopolymer probes (aka TAC-Cells) adhered to the nonglabrous skin of the lower face proximal to the right oral angle to synchronously activate mechanoreceptive afferents in the trigeminal nerve. Blocks of pulse trains were counterbalanced among participants and delivered at two rates, 2 and 4Hz. TAC-Cell stimulation of the lower face consistently evoked a series of cSEPs at P7, N20, P28, N38, P75, N85, and P115. The spatial organization and adaptation of the evoked cSEP was dependent on stimulus pulse index (1-6 within the pulse train, p=.012), frequency of stimulus presentation (2 vs 4Hz, p<.001), component (P7-P115, p<.001), and recording montage (channels 1-4, p<.001). Early component latencies (P7-N20) were highly stable in polarity (sign) and latency, and consistent with putative far-field generators (e.g., trigeminal brainstem, ventroposteromedial thalamus).

Faithful Representation of Tactile Intensity under Different Contexts Emerges from the Distinct Adaptive Properties of the First Somatosensory Relay Stations

Adaptation allows neurons to respond to a wide range of stimulus intensities. However, it also leads to ambiguity as the representation of the external world depends on the context. We recorded neurons from Wistar rats' brainstem nuclei belonging to two major somatosensory pathways (lemniscal and paralemniscal) and explored the way in which they encode noisy stimuli under different contexts. We found that although their unadapted intensity-response curves are very similar, the adapted curves of the two pathways are distinctively different as they are optimized for encoding different intensity ranges. Lemniscal neurons most faithfully encoded stimuli when the background intensity was high, whereas paralemniscal cells best encoded stimuli under low intensity context. Intracellular recordings indicate that these differences emerge already at the synaptic level. We suggest that the two pathways synergistically improve the ability of this system to encode a wide range of intensities during natural stimulation, potentially reducing the inherent ambiguity of adaptive coding.

A model of order-selectivity based on dynamic changes in the balance of excitation and inhibition produced by short-term synaptic plasticity

Determining the order of sensory events separated by a few hundred milliseconds is critical to many forms of sensory processing, including vocalization and speech discrimination. Although many experimental studies have recorded from auditory order-sensitive and order-selective neurons, the underlying mechanisms are poorly understood. Here we demonstrate that universal properties of cortical synapses-short-term synaptic plasticity of excitatory and inhibitory synapses-are well suited for the generation of order-selective neural responses. Using computational models of canonical disynaptic circuits, we show that the dynamic changes in the balance of excitation and inhibition imposed by short-term plasticity lead to the generation of order-selective responses. Parametric analyses predict that among the forms of short-term plasticity expressed at excitatory-to-excitatory, excitatory-to-inhibitory, and inhibitory-to-excitatory synapses, the single most important contributor to order-selectivity is the paired-pulse depression of inhibitory postsynaptic potentials (IPSPs). A topographic model of the auditory cortex that incorporates short-term plasticity accounts for both context-dependent suppression and enhancement in response to paired tones. Together these results provide a framework to account for an important computational problem based on ubiquitous synaptic properties that did not yet have a clearly established computational function. Additionally, these studies suggest that disynaptic circuits represent a fundamental computational unit that is capable of processing both spatial and temporal information.

Moving sensory adaptation beyond suppressive effects in single neurons

How an object is perceived depends on the temporal context in which it is encountered. Sensory signals in the brain also depend on temporal context, a phenomenon often referred to as adaptation. Traditional descriptions of adaptation effects emphasize various forms of response fatigue in single neurons, which grow in strength with exposure to a stimulus. Recent work on vision, and other sensory modalities, has shown that this description has substantial shortcomings. Here we review our emerging understanding of how adaptation alters the balance between excitatory and suppressive signals, how effects depend on adaptation duration, and how adaptation influences representations that are distributed within and across multiple brain structures. This work points to a sophisticated set of mechanisms for adjusting to recent sensory experience, and suggests new avenues for understanding their function.

Functional significance of complex fluctuations in brain activity: from resting state to cognitive neuroscience

Behavioral studies have shown that human cognition is characterized by properties such as temporal scale invariance, heavy-tailed non-Gaussian distributions, and long-range correlations at long time scales, suggesting models of how (non observable) components of cognition interact. On the other hand, results from functional neuroimaging studies show that complex scaling and intermittency may be generic spatio-temporal properties of the brain at rest. Somehow surprisingly, though, hardly ever have the neural correlates of cognition been studied at time scales comparable to those at which cognition shows scaling properties. Here, we analyze the meanings of scaling properties and the significance of their task-related modulations for cognitive neuroscience. It is proposed that cognitive processes can be framed in terms of complex generic properties of brain activity at rest and, ultimately, of functional equations, limiting distributions, symmetries, and possibly universality classes characterizing them.

Cellular adaptation facilitates sparse and reliable coding in sensory pathways

Most neurons in peripheral sensory pathways initially respond vigorously when a preferred stimulus is presented, but adapt as stimulation continues. It is unclear how this phenomenon affects stimulus coding in the later stages of sensory processing. Here, we show that a temporally sparse and reliable stimulus representation develops naturally in sequential stages of a sensory network with adapting neurons. As a modeling framework we employ a mean-field approach together with an adaptive population density treatment, accompanied by numerical simulations of spiking neural networks. We find that cellular adaptation plays a critical role in the dynamic reduction of the trial-by-trial variability of cortical spike responses by transiently suppressing self-generated fast fluctuations in the cortical balanced network. This provides an explanation for a widespread cortical phenomenon by a simple mechanism. We further show that in the insect olfactory system cellular adaptation is sufficient to explain the emergence of the temporally sparse and reliable stimulus representation in the mushroom body. Our results reveal a generic, biophysically plausible mechanism that can explain the emergence of a temporally sparse and reliable stimulus representation within a sequential processing architecture.