Shift in the balance between excitation and inhibition during sensory adaptation of S1 neurons

MULTIPLE DISTINCT TIMESCALES OF RAPID SENSORY ADAPATION IN THE THALAMOCORTICAL CIRCUIT

Numerous studies have shown that neuronal representations in sensory pathways are far from static but are instead strongly shaped by the complex properties of the sensory inputs they receive. Adaptation dynamically shapes the neural signaling that underlies our perception of the world yet remains poorly understood. We investigated rapid adaptation across timescales from hundreds of milliseconds to seconds through simultaneous multi-electrode recordings from the ventro-posteromedial nucleus of the thalamus (VPm) and layer 4 of the primary somatosensory cortex (S1) in male and female anesthetized mice in response to controlled, persistent whisker stimulation. Observations in VPm and S1 reveal a degree of adaptation that progresses through the pathway. Signatures of two distinct timescales of rapid adaptation in the firing rates of both thalamic and cortical neuronal populations were revealed, also reflected in the synchrony of the thalamic population and in the thalamocortical synaptic efficacy that was measured in putatively monosynaptically connected thalamocortical pairs. Controlled optogenetic activation of VPm further demonstrated that the longer timescale adaptation observed in S1 is likely inherited from slow decreases in thalamic firing rate and synchrony. Despite the degraded sensory responses, adaptation resulted in a shift in coding strategy that favors theoretical discrimination over detection across the observed timescales of adaptation. Overall, although multiple mechanisms contribute to rapid adaptation at distinct timescales, they support a unifying framework on the role of adaptation in sensory processing.

Adapting and facilitating responses in mouse somatosensory cortex are dynamic and shaped by experience

Sensory adaptation is the process whereby brain circuits adjust neuronal activity in response to redundant sensory stimuli. Although sensory adaptation has been extensively studied for individual neurons on timescales of tens of milliseconds to a few seconds, little is known about it over longer timescales or at the population level. We investigated population-level adaptation in the barrel field of the mouse somatosensory cortex (S1BF) using in vivo two-photon calcium imaging and Neuropixels recordings in awake mice. Among stimulus-responsive neurons, we found both adapting and facilitating neurons, which decreased or increased their firing, respectively, with repetitive whisker stimulation. The former outnumbered the latter by 2:1 in layers 2/3 and 4; hence, the overall population response of mouse S1BF was slightly adapting. We also discovered that population adaptation to one stimulus frequency (5 Hz) does not necessarily generalize to a different frequency (12.5 Hz). Moreover, responses of individual neurons to repeated rounds of stimulation over tens of minutes were strikingly heterogeneous and stochastic, such that their adapting or facilitating response profiles were not stable across time. Such representational drift was particularly striking when recording longitudinally across 8-9 days, as adaptation profiles of most whisker-responsive neurons changed drastically from one day to the next. Remarkably, repeated exposure to a familiar stimulus paradoxically shifted the population away from strong adaptation and toward facilitation. Thus, the adapting vs. facilitating response profile of S1BF neurons is not a fixed property of neurons but rather a highly dynamic feature that is shaped by sensory experience across days.

Spontaneous slow wave oscillations in extracellular field potential recordings reflect the alternating dominance of excitation and inhibition

In the resting state, cortical neurons can fire action potentials spontaneously but synchronously (Up state), followed by a quiescent period (Down state) before the cycle repeats. Extracellular recordings in the infragranular layer of cortex with a micro-electrode display a negative deflection (depth-negative) during Up states and a positive deflection (depth-positive) during Down states. The resulting slow wave oscillation (SWO) has been studied extensively during sleep and under anaesthesia. However, recent research on the balanced nature of synaptic excitation and inhibition has highlighted our limited understanding of its genesis. Specifically, are excitation and inhibition balanced during SWOs? We analyse spontaneous local field potentials (LFPs) during SWOs recorded from anaesthetised rats via a multi-channel laminar micro-electrode and show that the Down state consists of two distinct synaptic states: a Dynamic Down state associated with depth-positive LFPs and a prominent dipole in the extracellular field, and a Static Down state with negligible (≈ 0 mV $ \approx 0{\mathrm{\;mV}}$ ) LFPs and a lack of dipoles extracellularly. We demonstrate that depth-negative and -positive LFPs are generated by a shift in the balance of synaptic excitation and inhibition from excitation dominance (depth-negative) to inhibition dominance (depth-positive) in the infragranular layer neurons. Thus, although excitation and inhibition co-tune overall, differences in their timing lead to an alternation of dominance, manifesting as SWOs. We further show that Up state initiation is significantly faster if the preceding Down state is dynamic rather than static. Our findings provide a coherent picture of the dependence of SWOs on synaptic activity. KEY POINTS: Cortical neurons can exhibit repeated cycles of spontaneous activity interleaved with periods of relative silence, a phenomenon known as 'slow wave oscillation' (SWO). During SWOs, recordings of local field potentials (LFPs) in the neocortex show depth-negative deflection during the active period (Up state) and depth-positive deflection during the silent period (Down state). Here we further classified the Down state into a dynamic phase and a static phase based on a novel method of classification and revealed non-random, stereotypical sequences of the three states occurring with significantly different transitional kinetics. Our results suggest that the positive and negative deflections in the LFP reflect the shift of the instantaneous balance between excitatory and inhibitory synaptic activity of the local cortical neurons. The differences in transitional kinetics may imply distinct synaptic mechanisms for Up state initiation. The study may provide a new approach for investigating spontaneous brain rhythms.

Increased presynaptic excitability in a migraine with aura mutation

Migraine is a common and disabling neurological disorder. The headache and sensory amplifications of migraine are attributed to hyperexcitable sensory circuits, but a detailed understanding remains elusive. A mutation in casein kinase 1 delta (CK1δ) was identified in non-hemiplegic familial migraine with aura and advanced sleep phase syndrome. Mice carrying the CK1δT44A mutation were more susceptible to spreading depolarization (the phenomenon that underlies migraine aura), but mechanisms underlying this migraine-relevant phenotype were not known. We used a combination of whole-cell electrophysiology and multiphoton imaging, in vivo and in brain slices, to compare CK1δT44A mice (adult males) to their wild-type littermates. We found that despite comparable synaptic activity at rest, CK1δT44A neurons were more excitable upon repetitive stimulation than wild-type, with a reduction in presynaptic adaptation at excitatory but not inhibitory synapses. The mechanism of this adaptation deficit was a calcium-dependent enhancement of the size of the readily releasable pool of synaptic vesicles, and a resultant increase in glutamate release, in CK1δT44A compared to wild-type synapses. Consistent with this mechanism, CK1δT44A neurons showed an increase in the cumulative amplitude of excitatory post-synaptic currents, and a higher excitation-to-inhibition ratio during sustained activity compared to wild-type. At a local circuit level, action potential bursts elicited in CK1δT44A neurons triggered an increase in recurrent excitation compared to wild-type, and at a network level, CK1δT44A mice showed a longer duration of 'up state' activity, which is dependent on recurrent excitation. Finally, we demonstrated that the spreading depolarization susceptibility of CK1δT44A mice could be returned to wild-type levels with the same intervention (reduced extracellular calcium) that normalized presynaptic adaptation. Taken together, these findings show a stimulus-dependent presynaptic gain of function at glutamatergic synapses in a genetic model of migraine, that accounts for the increased spreading depolarization susceptibility and may also explain the sensory amplifications that are associated with the disease.

Neuromorphic hardware for somatosensory neuroprostheses

In individuals with sensory-motor impairments, missing limb functions can be restored using neuroprosthetic devices that directly interface with the nervous system. However, restoring the natural tactile experience through electrical neural stimulation requires complex encoding strategies. Indeed, they are presently limited in effectively conveying or restoring tactile sensations by bandwidth constraints. Neuromorphic technology, which mimics the natural behavior of neurons and synapses, holds promise for replicating the encoding of natural touch, potentially informing neurostimulation design. In this perspective, we propose that incorporating neuromorphic technologies into neuroprostheses could be an effective approach for developing more natural human-machine interfaces, potentially leading to advancements in device performance, acceptability, and embeddability. We also highlight ongoing challenges and the required actions to facilitate the future integration of these advanced technologies.

Vasotocin receptor gene genotypes moderate the relationship between cortical thickness and sensory processing

Sensory processing is the process by which the central nervous system gathers, interprets, and regulates sensory stimuli in response to environmental cues. However, our understanding of the genetic factors and neuroanatomical correlations that influence sensory processing is limited. The vasotocin system modulates sensory input responsiveness, making it a potential candidate for further investigation. Additionally, human neuroimaging studies have demonstrated that the ability to modulate sensory stimuli is related to neuroanatomical features such as cortical thickness. Therefore, this study aimed to examine the relationship between functional polymorphisms in vasotocin receptor (VTR) genes, sensory profiles, and neuroanatomical correlations. We used structural magnetic resonance imaging (MRI) and the Adolescent/Adult Sensory Profile (AASP) questionnaire in 98 healthy adult participants to assess sensory processing and identified seven single nucleotide polymorphisms. We found that A-allele carriers of rs1042615 in VTR had higher scores for "sensory sensitivity" and "sensation avoiding". Moreover, higher scores for three AASP subscales were associated with decreased cortical thickness in various regions, including the right precentral, paracentral, and fusiform gyri, as well as bilateral inferior temporal gyri. This study sheds light on the potential role of genetic variations in the VTR in modulating sensory processing and correlation with cortical thickness which has future implications for better understanding sensory abnormalities in neurodevelopmental disorders.

Input-specific synaptic depression shapes temporal integration in mouse visual cortex

Efficient sensory processing requires the nervous system to adjust to ongoing features of the environment. In primary visual cortex (V1), neuronal activity strongly depends on recent stimulus history. Existing models can explain effects of prolonged stimulus presentation but remain insufficient for explaining effects observed after shorter durations commonly encountered under natural conditions. We investigated the mechanisms driving adaptation in response to brief (100 ms) stimuli in L2/3 V1 neurons by performing in vivo whole-cell recordings to measure membrane potential and synaptic inputs. We find that rapid adaptation is generated by stimulus-specific suppression of excitatory and inhibitory synaptic inputs. Targeted optogenetic experiments reveal that these synaptic effects are due to input-specific short-term depression of transmission between layers 4 and 2/3. Thus, brief stimulus presentation engages a distinct adaptation mechanism from that previously reported in response to prolonged stimuli, enabling flexible control of sensory encoding across a wide range of timescales.

Input-specific synaptic depression shapes temporal integration in mouse visual cortex

Efficient sensory processing requires the nervous system to adjust to ongoing features of the environment. In primary visual cortex (V1), neuronal activity strongly depends on recent stimulus history. Existing models can explain effects of prolonged stimulus presentation, but remain insufficient for explaining effects observed after shorter durations commonly encountered under natural conditions. We investigated the mechanisms driving adaptation in response to brief (100 ms) stimuli in L2/3 V1 neurons by performing in vivo whole-cell recordings to measure membrane potential and synaptic inputs. We find that rapid adaptation is generated by stimulus-specific suppression of excitatory and inhibitory synaptic inputs. Targeted optogenetic experiments reveal that these synaptic effects are due to input-specific short-term depression of transmission between layers 4 and 2/3. Thus, distinct mechanisms are engaged following brief and prolonged stimulus presentation and together enable flexible control of sensory encoding across a wide range of time scales.

Context-Dependent Inhibitory Control of Stimulus-Specific Adaptation

Stimulus-specific adaptation (SSA) is the reduction in responses to frequent stimuli (standards) that does not generalize to rare stimuli (deviants). We investigated the contribution of inhibition in auditory cortex to SSA using two-photon targeted cell-attached recordings and optogenetic manipulations in male mice. We characterized the responses of parvalbumin (PV)-, somatostatin (SST)-, and vasoactive intestinal polypeptide (VIP)-expressing interneurons of layer 2/3, and of serotonin receptor 5HT3a-expressing interneurons of layer 1. All populations showed early-onset SSA. Unexpectedly, the PV, SST, and VIP populations exhibited a substantial late component of evoked activity, often stronger for standard than for deviant stimuli. Optogenetic suppression of PV neurons facilitated pyramidal neuron responses substantially more (approximately ×10) for deviants than for standards. VIP suppression decreased responses of putative PV neurons, specifically for standard but not for deviant stimuli. Thus, the inhibitory network does not generate cortical SSA, but powerfully controls its expression by differentially affecting the responses to deviants and to standards.SIGNIFICANCE STATEMENT Stimulus-specific adaptation (SSA) reflects the growing complexity of auditory processing along the ascending auditory system. In the presence of SSA, neuronal responses depend not only on the stimulus itself but also on the history of stimulation. Strong SSA in the fast, ascending auditory pathway first occurs in cortex. Here we studied the role of the cortical inhibitory network in shaping SSA, showing that while cortical inhibition does not generate SSA, it powerfully controls its expression. We deduce that the cortical network contributes in crucial ways to the properties of SSA.

Parvalbumin-Positive Interneurons Regulate Cortical Sensory Plasticity in Adulthood and Development Through Shared Mechanisms

Parvalbumin-positive neurons are the largest class of GABAergic, inhibitory neurons in the central nervous system. In the cortex, these fast-spiking cells provide feedforward and feedback synaptic inhibition onto a diverse set of cell types, including pyramidal cells, other inhibitory interneurons, and themselves. Cortical inhibitory networks broadly, and cortical parvalbumin-expressing interneurons (cPVins) specifically, are crucial for regulating sensory plasticity during both development and adulthood. Here we review the functional properties of cPVins that enable plasticity in the cortex of adult mammals and the influence of cPVins on sensory activity at four spatiotemporal scales. First, cPVins regulate developmental critical periods and adult plasticity through molecular and structural interactions with the extracellular matrix. Second, they activate in precise sequence following feedforward excitation to enforce strict temporal limits in response to the presentation of sensory stimuli. Third, they implement gain control to normalize sensory inputs and compress the dynamic range of output. Fourth, they synchronize broad network activity patterns in response to behavioral events and state changes. Much of the evidence for the contribution of cPVins to plasticity comes from classic models that rely on sensory deprivation methods to probe experience-dependent changes in the brain. We support investigating naturally occurring, adaptive cortical plasticity to study cPVin circuits in an ethologically relevant framework, and discuss recent insights from our work on maternal experience-induced auditory cortical plasticity.

A novel theoretical framework for simultaneous measurement of excitatory and inhibitory conductances

The firing of neurons throughout the brain is determined by the precise relations between excitatory and inhibitory inputs, and disruption of their balance underlies many psychiatric diseases. Whether or not these inputs covary over time or between repeated stimuli remains unclear due to the lack of experimental methods for measuring both inputs simultaneously. We developed a new analytical framework for instantaneous and simultaneous measurements of both the excitatory and inhibitory neuronal inputs during a single trial under current clamp recording. This can be achieved by injecting a current composed of two high frequency sinusoidal components followed by analytical extraction of the conductances. We demonstrate the ability of this method to measure both inputs in a single trial under realistic recording constraints and from morphologically realistic CA1 pyramidal model cells. Future experimental implementation of our new method will facilitate the understanding of fundamental questions about the health and disease of the nervous system.

Most neurons in the brain receive synaptic inputs from both excitatory and inhibitory neurons. Together, these inputs determine neuronal activity: excitatory synapses shift the electrical potential across the membrane towards the threshold for generation of action potentials, whereas inhibitory synapses lower this potential away from the threshold. Action potentials are the rapid electrochemical signals that transmit information to other neurons and they are critical for the information processing abilities of the brain.

Although there are many ways to measure either excitatory or inhibitory inputs, these methods have been unable to measure both at the same time. Measuring both inputs together is essential towards understanding how neurons integrate information. We developed a new analytical method to measure excitatory and inhibitory inputs at the same time from the voltage response to injection of an alternating current into a neuron. We describe the foundation of this new method and find that it works in biologically realistic simulations of neurons. By using this technique in real neurons, scientists could investigate basic principles of information processing in the healthy and diseased brain.

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.

Alternation of Neuronal Feature Selectivity Induced by Paired Optogenetic-Mechanical Stimulation in the Barrel Cortex

Paired stimulation has been applied to modulate neuronal functions in the primary somatosensory cortex but its utility in the alternation of tuning function, such as direction tuning for whisker stimuli, remains unclear. In the present study, we attempted to manipulate feature preferences in barrel cortical neurons using repetitive paired whisker deflection combined with optogenetic stimulation and to obtain optimal parameters that can induce neuroplasticity. We found no significant response changes across stimulus parameters, such as onset asynchronies and paired directions. Only when paired stimulation was applied in the nonpreferred direction of the principal whisker of a neuron, were the neuron’s responses enhanced in that direction. Importantly, this effect was only observed when the optogenetic stimulus preceded the mechanical stimulus. Our findings indicate that repetitive paired optogenetic-mechanical stimulation can induce in vivo neuroplasticity of feature selectivity in limited situations.

Contrast adaptation improves spatial integration

The effects of contrast adaptation and contrast area summation (spatial integration) were investigated using a contrast discrimination task. The task consisted of a target of variable size, and a pedestal with a fixed base contrast. Discrimination performance was examined for a condition in which the pedestal size was fixed, equal to the largest target size, and for a condition in which the pedestal size matched the target size and thus varied with it. Repeated performance of the task produced rapid within-session improvements for both conditions. For stimuli with a matching size of target and pedestal, the performance improved only for the larger targets, indicating the development of spatial integration, which was initially absent for these stimuli. However, the improvements were mostly temporary, and were not fully retained between subsequent daily sessions. The temporary nature of the sensitivity gains implies that they resulted, at least in part, from rapid adaptation to the stimulus contrast. We suggest that adaptation decorrelates and thus reduces the spatial noise generated by a high-contrast pedestal, leading to improved spatial integration (area summation) and better contrast sensitivity. A decorrelation model successfully predicted our experimental results.

EEGs Disclose Significant Brain Activity Correlated with Synaptic Fickleness

We here study a network of synaptic relations mingling excitatory and inhibitory neuron nodes that displays oscillations quite similar to electroencephalogram (EEG) brain waves, and identify abrupt variations brought about by swift synaptic mediations. We thus conclude that corresponding changes in EEG series surely come from the slowdown of the activity in neuron populations due to synaptic restrictions. The latter happens to generate an imbalance between excitation and inhibition causing a quick explosive increase of excitatory activity, which turns out to be a (first-order) transition among dynamic mental phases. Moreover, near this phase transition, our model system exhibits waves with a strong component in the so-called delta-theta domain that coexist with fast oscillations. These findings provide a simple explanation for the observed delta-gamma and theta-gamma modulation in actual brains, and open a serious and versatile path to understand deeply large amounts of apparently erratic, easily accessible brain data.

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.

Balanced networks under spike-time dependent plasticity

The dynamics of local cortical networks are irregular, but correlated. Dynamic excitatory–inhibitory balance is a plausible mechanism that generates such irregular activity, but it remains unclear how balance is achieved and maintained in plastic neural networks. In particular, it is not fully understood how plasticity induced changes in the network affect balance, and in turn, how correlated, balanced activity impacts learning. How do the dynamics of balanced networks change under different plasticity rules? How does correlated spiking activity in recurrent networks change the evolution of weights, their eventual magnitude, and structure across the network? To address these questions, we develop a theory of spike–timing dependent plasticity in balanced networks. We show that balance can be attained and maintained under plasticity–induced weight changes. We find that correlations in the input mildly affect the evolution of synaptic weights. Under certain plasticity rules, we find an emergence of correlations between firing rates and synaptic weights. Under these rules, synaptic weights converge to a stable manifold in weight space with their final configuration dependent on the initial state of the network. Lastly, we show that our framework can also describe the dynamics of plastic balanced networks when subsets of neurons receive targeted optogenetic input.

Animals are able to learn complex tasks through changes in individual synapses between cells. Such changes lead to the coevolution of neural activity patterns and the structure of neural connectivity, but the consequences of these interactions are not fully understood. We consider plasticity in model neural networks which achieve an average balance between the excitatory and inhibitory synaptic inputs to different cells, and display cortical–like, irregular activity. We extend the theory of balanced networks to account for synaptic plasticity and show which rules can maintain balance, and which will drive the network into a different state. This theory of plasticity can provide insights into the relationship between stimuli, network dynamics, and synaptic circuitry.

Cross-Whisker Adaptation of Neurons in Layer 2/3 of the Rat Barrel Cortex

Neurons in the barrel cortex respond preferentially to stimulation of one principal whisker and weakly to several adjacent whiskers. Such integration exists already in layer 4, the pivotal recipient layer of thalamic inputs. Previous studies show that cortical neurons gradually adapt to repeated whisker stimulations and that layer 4 neurons exhibit whisker specific adaptation and no apparent interactions with other whiskers. This study aimed to study the specificity of adaptation of layer 2/3 cortical cells. Towards this aim, we compared the synaptic response of neurons to either repetitive stimulation of one of two responsive whiskers or when repetitive stimulation of the two whiskers was interleaved. We found that in most layer 2/3 cells adaptation is whisker-specific. These findings indicate that despite the multi-whisker receptive fields in the cortex, the adaptation process for each whisker-pathway is mostly independent of other whiskers. A mechanism allowing high responsiveness in complex environments.

Post-stimulatory activity in primate auditory cortex evoked by sensory stimulation during passive listening

Under certain circumstances, cortical neurons are capable of elevating their firing for long durations in the absence of a stimulus. Such activity has typically been observed and interpreted in the context of performance of a behavioural task. Here we investigated whether post-stimulatory activity is observed in auditory cortex and the medial geniculate body of the thalamus in the absence of any explicit behavioural task. We recorded spiking activity from single units in the auditory cortex (fields A1, R and RT) and auditory thalamus of awake, passively-listening marmosets. We observed post-stimulatory activity that lasted for hundreds of milliseconds following the termination of the acoustic stimulus. Post-stimulatory activity was observed following both adapting, sustained and suppressed response profiles during the stimulus. These response types were observed across all cortical fields tested, but were largely absent from the auditory thalamus. As well as being of shorter duration, thalamic post-stimulatory activity emerged following a longer latency than in cortex, indicating that post-stimulatory activity may be generated within auditory cortex during passive listening. Given that these responses were observed in the absence of an explicit behavioural task, post-stimulatory activity in sensory cortex may play a functional role in processes such as echoic memory and temporal integration that occur during passive listening.

Magnitude, time course, and specificity of rapid adaptation across mouse visual areas

Adaptation is a ubiquitous feature of sensory processing whereby recent experience shapes future responses. The mouse primary visual cortex (V1) is particularly sensitive to recent experience, where a brief stimulus can suppress subsequent responses for seconds. This rapid adaptation profoundly impacts perception, suggesting that its effects are propagated along the visual hierarchy. To understand how rapid adaptation influences sensory processing, we measured its effects at key nodes in the visual system: in V1, three higher visual areas (HVAs: lateromedial, anterolateral, and posteromedial), and the superior colliculus (SC) in awake mice of both sexes using single-unit recordings. Consistent with the feed-forward propagation of adaptation along the visual hierarchy, we find that neurons in layer 4 adapt less strongly than those in other layers of V1. Furthermore, neurons in the HVAs adapt more strongly, and recover more slowly, than those in V1. The magnitude and time course of adaptation was comparable in each of the HVAs and in the SC, suggesting that adaptation may not linearly accumulate along the feed-forward visual processing hierarchy. Despite the increase in adaptation in the HVAs compared with V1, the effects were similarly orientation specific across all areas. These data reveal that adaptation profoundly shapes cortical processing, with increasing impact at higher levels in the cortical hierarchy, and also strongly influencing computations in the SC. Thus, we find robust, brain-wide effects of rapid adaptation on sensory processing.NEW & NOTEWORTHY Rapid adaptation dynamically alters sensory signals to account for recent experience. To understand how adaptation affects sensory processing and perception, we must determine how it impacts the diverse set of cortical and subcortical areas along the hierarchy of the mouse visual system. We find that rapid adaptation strongly impacts neurons in primary visual cortex, the higher visual areas, and the colliculus, consistent with its profound effects on behavior.

Frequency-dependent gating of feedforward inhibition in thalamofrontal synapses

Thalamic recruitment of feedforward inhibition is known to enhance the fidelity of the receptive field by limiting the temporal window during which cortical neurons integrate excitatory inputs. Feedforward inhibition driven by the mediodorsal nucleus of the thalamus (MD) has been previously observed, but its physiological function and regulation remain unknown. Accumulating evidence suggests that elevated neuronal activity in the prefrontal cortex is required for the short-term storage of information. Furthermore, the elevated neuronal activity is supported by the reciprocal connectivity between the MD and the medial prefrontal cortex (mPFC). Therefore, detailed knowledge about the synaptic connections during high-frequency activity is critical for understanding the mechanism of short-term memory. In this study, we examined how feedforward inhibition of thalamofrontal connectivity is modulated by activity frequency. We observed greater short-term synaptic depression during disynaptic inhibition than in thalamic excitatory synapses during high-frequency activities. The strength of feedforward inhibition became weaker as the stimulation continued, which, in turn, enhanced the range of firing jitter in a frequency-dependent manner. We postulated that this phenomenon was primarily due to the increased failure rate of evoking action potentials in parvalbumin-expressing inhibitory neurons. These findings suggest that the MD-mPFC pathway is dynamically regulated by an excitatory-inhibitory balance in an activity-dependent manner. During low-frequency activities, excessive excitations are inhibited, and firing is restricted to a limited temporal range by the strong feedforward inhibition. However, during high-frequency activities, such as during short-term memory, the activity can be transferred in a broader temporal range due to the decreased feedforward inhibition.

Enhanced Thalamocortical Synaptic Transmission and Dysregulation of the Excitatory-Inhibitory Balance at the Thalamocortical Feedforward Inhibitory Microcircuit in a Genetic Mouse Model of Migraine

Migraine is a complex brain disorder, characterized by attacks of unilateral headache and global dysfunction in multisensory information processing, whose underlying cellular and circuit mechanisms remain unknown. The finding of enhanced excitatory, but unaltered inhibitory, neurotransmission at intracortical synapses in mouse models of familial hemiplegic migraine (FHM) suggested the hypothesis that dysregulation of the excitatory-inhibitory balance in specific circuits is a key pathogenic mechanism. Here, we investigated the thalamocortical (TC) feedforward inhibitory microcircuit in FHM1 mice of both sexes carrying a gain-of-function mutation in Ca_V2.1. We show that TC synaptic transmission in somatosensory cortex is enhanced in FHM1 mice. Due to similar gain of function of TC excitation of layer 4 excitatory and fast-spiking inhibitory neurons elicited by single thalamic stimulations, neither the excitatory-inhibitory balance nor the integration time window set by the TC feedforward inhibitory microcircuit was altered in FHM1 mice. However, during repetitive thalamic stimulation, the typical shift of the excitatory-inhibitory balance toward excitation and the widening of the integration time window were both smaller in FHM1 compared with WT mice, revealing a dysregulation of the excitatory-inhibitory balance, whereby the balance is relatively skewed toward inhibition. This is due to an unexpected differential effect of the FHM1 mutation on short-term synaptic plasticity at TC synapses on cortical excitatory and fast-spiking inhibitory neurons. Our findings point to enhanced transmission of sensory, including trigeminovascular nociceptive, signals from thalamic nuclei to cortex and TC excitatory-inhibitory imbalance as mechanisms that may contribute to headache, increased sensory gain, and sensory processing dysfunctions in migraine.SIGNIFICANCE STATEMENT Migraine is a complex brain disorder, characterized by attacks of unilateral headache and by global dysfunction in multisensory information processing, whose underlying cellular and circuit mechanisms remain unknown. Here we provide insights into these mechanisms by investigating thalamocortical (TC) synaptic transmission and the function of the TC feedforward inhibitory microcircuit in a mouse model of a rare monogenic migraine. This microcircuit is critical for gating information flow to cortex and for sensory processing. We reveal increased TC transmission and dysregulation of the cortical excitatory-inhibitory balance set by the TC feedforward inhibitory microcircuit, whereby the balance is relatively skewed toward inhibition during repetitive thalamic activity. These alterations may contribute to headache, increased sensory gain, and sensory processing dysfunctions in migraine.

Precise excitation-inhibition balance controls gain and timing in the hippocampus

Excitation-inhibition (EI) balance controls excitability, dynamic range, and input gating in many brain circuits. Subsets of synaptic input can be selected or 'gated' by precise modulation of finely tuned EI balance, but assessing the granularity of EI balance requires combinatorial analysis of excitatory and inhibitory inputs. Using patterned optogenetic stimulation of mouse hippocampal CA3 neurons, we show that hundreds of unique CA3 input combinations recruit excitation and inhibition with a nearly identical ratio, demonstrating precise EI balance at the hippocampus. Crucially, the delay between excitation and inhibition decreases as excitatory input increases from a few synapses to tens of synapses. This creates a dynamic millisecond-range window for postsynaptic excitation, controlling membrane depolarization amplitude and timing via subthreshold divisive normalization. We suggest that this combination of precise EI balance and dynamic EI delays forms a general mechanism for millisecond-range input gating and subthreshold gain control in feedforward networks.

Estrus-Cycle Regulation of Cortical Inhibition

Female mammals experience cyclical changes in sexual receptivity known as the estrus cycle. Little is known about how estrus affects the cortex, although alterations in sensation, cognition and the cyclical occurrence of epilepsy suggest brain-wide processing changes. We performed in vivo juxtacellular and whole-cell recordings in somatosensory cortex of female rats and found that the estrus cycle potently altered cortical inhibition. Fast-spiking interneurons were strongly activated with social facial touch and varied their ongoing activity with the estrus cycle and estradiol in ovariectomized females, while regular-spiking excitatory neurons did not change. In situ hybridization for estrogen receptor β (Esr2) showed co-localization with parvalbumin-positive (PV⁺) interneurons in deep cortical layers, mirroring the laminar distribution of our physiological findings. The fraction of neurons positive for estrogen receptor β (Esr2) and PV co-localization (Esr2⁺PV⁺) in cortical layer V was increased in proestrus. In vivo and in vitro experiments confirmed that estrogen acts locally to increase fast-spiking interneuron excitability through an estrogen-receptor-β-dependent mechanism.

Membrane Potential Correlates of Network Decorrelation and Improved SNR by Cholinergic Activation in the Somatosensory Cortex

The nucleus basalis (NB) projects cholinergic axons to the cortex, where they play a major role in arousal, attention, and learning. Cholinergic inputs shift cortical dynamics from synchronous to asynchronous and improve the signal-to-noise ratio (SNR) of sensory responses. However, the underlying mechanisms of these changes remain unclear. Using simultaneous extracellular and whole-cell patch recordings in layer 4 of the mouse barrel cortex, we show that electrical or optogenetic activation of the cholinergic system has a differential effect on ongoing and sensory evoked activities. Cholinergic activation profoundly reduced the large spontaneous fluctuations in membrane potential and decorrelated ongoing activity. However, NB stimulation had no effect on the response to whisker stimulation or on signal correlations. These effects of cholinergic activation provide a unified explanation for the increased SNR of sensory response and for the reduction in noise correlations and explain the shift into the desynchronized cortical state, which are the hallmarks of arousal and attention.SIGNIFICANCE STATEMENT Attention increases the signal-to-noise ratio (SNR) of cortical sensory response, which may reflect either reduction in background firing rate or increased sensory response. Extracellular recordings showed that attention also reduces the correlation in network activity. These effects are partially mediated by cholinergic axons from the nucleus basalis projecting to the entire cortex. To reveal the cellular and synaptic correlates of these cholinergic effects, we performed simultaneous intracellular and LFP recordings in the somatosensory cortex. Global or local cholinergic activation increased the SNR of sensory response mainly by reducing the rate and amplitude of background synaptic activity and also reduced network correlations. Therefore, coding of sensory information is enhanced by the cholinergic system mainly due to a reduction in spontaneous activity.

Oxytocin Transforms Firing Mode of CA2 Hippocampal Neurons

Oxytocin is an important neuromodulator in the mammalian brain that increases information salience and circuit plasticity, but its signaling mechanisms and circuit effect are not fully understood. Here we report robust oxytocinergic modulation of intrinsic properties and circuit operations in hippocampal area CA2, a region of emerging importance for hippocampal function and social behavior. Upon oxytocin receptor activation, CA2 pyramidal cells depolarize and fire bursts of action potentials, a consequence of phospholipase C signaling to modify two separate voltage-dependent ionic processes. A reduction of potassium current carried by KCNQ-based M channels depolarizes the cell; protein kinase C activity attenuates spike rate of rise and overshoot, dampening after-hyperpolarizations. These actions, in concert with activation of fast-spiking interneurons, promote repetitive firing and CA2 bursting; bursting then governs short-term plasticity of CA2 synaptic transmission onto CA1 and, thus, efficacy of information transfer in the hippocampal network.

The effects of individualised intermittent theta burst stimulation in the prefrontal cortex: A TMS-EEG study

Recent studies have highlighted variability in response to theta burst stimulation (TBS) in humans. TBS paradigm was originally developed in rodents to mimic gamma bursts coupled with theta rhythms, and was shown to elicit long-term potentiation. The protocol was subsequently adapted for humans using standardised frequencies of stimulation. However, each individual has different rhythmic firing pattern. The present study sought to explore whether individualised intermittent TBS (Ind iTBS) could outperform the effects of two other iTBS variants. Twenty healthy volunteers received iTBS over left prefrontal cortex using 30 Hz at 6 Hz, 50 Hz at 5 Hz, or individualised frequency in separate sessions. Ind iTBS was determined using theta-gamma coupling during the 3-back task. Concurrent use of transcranial magnetic stimulation and electroencephalography (TMS-EEG) was used to track changes in cortical plasticity. We also utilised mood ratings using a visual analogue scale and assessed working memory via the 3-back task before and after stimulation. No group-level effect was observed following either 30 or 50 Hz iTBS in TMS-EEG. Ind iTBS significantly increased the amplitude of the TMS-evoked P60, and decreased N100 and P200 amplitudes. A significant positive correlation between neurophysiological change and change in mood rating was also observed. Improved accuracy in the 3-back task was observed following both 50 Hz and Ind iTBS conditions. These findings highlight the critical importance of frequency in the parameter space of iTBS. Tailored stimulation parameters appear more efficacious than standard paradigms in neurophysiological and mood changes. This novel approach presents a promising option and benefits may extend to clinical applications.

Time rescaling reproduces EEG behavior during transition from propofol anesthesia-induced unconsciousness to consciousness

General anesthesia (GA) is a reversible manipulation of consciousness whose mechanism is mysterious at the level of neural networks leaving space for several competing hypotheses. We recorded electrocorticography (ECoG) signals in patients who underwent intracranial monitoring during awake surgery for the treatment of cerebral tumors in functional areas of the brain. Therefore, we recorded the transition from unconsciousness to consciousness directly on the brain surface. Using frequency resolved interferometry; we studied the intermediate ECoG frequencies (4-40 Hz). In the theoretical study, we used a computational Jansen and Rit neuron model to simulate recovery of consciousness (ROC). During ROC, we found that f increased by a factor equal to 1.62 ± 0.09, and δf varied by the same factor (1.61 ± 0.09) suggesting the existence of a scaling factor. We accelerated the time course of an unconscious EEG trace by an approximate factor 1.6 and we showed that the resulting EEG trace match the conscious state. Using the theoretical model, we successfully reproduced this behavior. We show that the recovery of consciousness corresponds to a transition in the frequency (f, δf) space, which is exactly reproduced by a simple time rescaling. These findings may perhaps be applied to other altered consciousness states.

Encoding Time in Feedforward Trajectories of a Recurrent Neural Network Model

Brain activity evolves through time, creating trajectories of activity that underlie sensorimotor processing, behavior, and learning and memory. Therefore, understanding the temporal nature of neural dynamics is essential to understanding brain function and behavior. In vivo studies have demonstrated that sequential transient activation of neurons can encode time. However, it remains unclear whether these patterns emerge from feedforward network architectures or from recurrent networks and, furthermore, what role network structure plays in timing. We address these issues using a recurrent neural network (RNN) model with distinct populations of excitatory and inhibitory units. Consistent with experimental data, a single RNN could autonomously produce multiple functionally feedforward trajectories, thus potentially encoding multiple timed motor patterns lasting up to several seconds. Importantly, the model accounted for Weber's law, a hallmark of timing behavior. Analysis of network connectivity revealed that efficiency-a measure of network interconnectedness-decreased as the number of stored trajectories increased. Additionally, the balance of excitation (E) and inhibition (I) shifted toward excitation during each unit's activation time, generating the prediction that observed sequential activity relies on dynamic control of the E/I balance. Our results establish for the first time that the same RNN can generate multiple functionally feedforward patterns of activity as a result of dynamic shifts in the E/I balance imposed by the connectome of the RNN. We conclude that recurrent network architectures account for sequential neural activity, as well as for a fundamental signature of timing behavior: Weber's law.

Inhibition in Simple Cell Receptive Fields Is Broad and OFF-Subregion Biased

Inhibition in thalamorecipient layer 4 simple cells of primary visual cortex is believed to play important roles in establishing visual response properties and integrating visual inputs across their receptive fields (RFs). Simple cell RFs are characterized by nonoverlapping, spatially restricted subregions in which visual stimuli can either increase or decrease the firing rate of the cell, depending on contrast. Inhibition is believed to be triggered exclusively from visual stimulation of individual RF subregions. However, this view is at odds with the known anatomy of layer 4 interneurons in visual cortex and differs from recent findings in mouse visual cortex. Here we show with in vivo intracellular recordings in cats that while excitation is restricted to RF subregions, inhibition spans the width of simple cell RFs. Consequently, excitatory stimuli within a subregion concomitantly drive excitation and inhibition. Furthermore, we found that the distribution of inhibition across the RF is stronger toward OFF subregions. This inhibitory OFF-subregion bias has a functional consequence on spatial integration of inputs across the RF. A model based on the known anatomy of layer 4 demonstrates that the known proportion and connectivity of inhibitory neurons in layer 4 of primary visual cortex is sufficient to explain broad inhibition with an OFF-subregion bias while generating a variety of phase relations, including antiphase, between excitation and inhibition in response to drifting gratings.SIGNIFICANCE STATEMENT The wiring of excitatory and inhibitory neurons in cortical circuits is key to determining the response properties in sensory cortex. In the visual cortex, the first cells that receive visual input are simple cells in layer 4. The underlying circuitry responsible for the response properties of simple cells is not yet known. In this study, we challenge a long-held view concerning the pattern of inhibitory input and provide results that agree with current known anatomy. We show here that inhibition is evoked broadly across the receptive fields of simple cells, and we identify a surprising bias in inhibition within the receptive field. Our findings represent a step toward a unified view of inhibition across different species and sensory systems.

Laminar-specific encoding of texture elements in rat barrel cortex

KEY POINTS

For rats texture discrimination is signalled by the large face whiskers by stick-slip events. Neural encoding of repetitive stick-slip events will be influenced by intrinsic properties of adaptation. We show that texture coding in the barrel cortex is laminar specific and follows a power function. Our results also show layer 2 codes for novel feature elements via robust firing rates and temporal fidelity. We conclude that texture coding relies on a subtle neural ensemble to provide important object information.

ABSTRACT

Texture discrimination by rats is exquisitely guided by fine-grain mechanical stick-slip motions of the face whiskers as they encounter, stick to and slip past successive texture-defining surface features such as bumps and grooves. Neural encoding of successive stick-slip texture events will be shaped by adaptation, common to all sensory systems, whereby receptor and neural responses to a stimulus are affected by responses to preceding stimuli, allowing resetting to signal novel information. Additionally, when a whisker is actively moved to contact and brush over surfaces, that motion itself generates neural responses that could cause adaptation of responses to subsequent stick-slip events. Nothing is known about encoding in the rat whisker system of stick-slip events defining textures of different grain or the influence of adaptation from whisker protraction or successive texture-defining stick-slip events. Here we recorded responses from halothane-anaesthetized rats in response to texture-defining stimuli applied to passive whiskers. We demonstrate that: across the columnar network of the whisker-recipient barrel cortex, adaptation in response to repetitive stick-slip events is strongest in uppermost layers and equally lower thereafter; neither whisker protraction speed nor stick-slip frequency impede encoding of stick-slip events at rates up to 34.08 Hz; and layer 2 normalizes responses to whisker protraction to resist effects on texture signalling. Thus, within laminar-specific response patterns, barrel cortex reliably encodes texture-defining elements even to high frequencies.

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.

Inverse stochastic resonance in networks of spiking neurons

Inverse Stochastic Resonance (ISR) is a phenomenon in which the average spiking rate of a neuron exhibits a minimum with respect to noise. ISR has been studied in individual neurons, but here, we investigate ISR in scale-free networks, where the average spiking rate is calculated over the neuronal population. We use Hodgkin-Huxley model neurons with channel noise (i.e., stochastic gating variable dynamics), and the network connectivity is implemented via electrical or chemical connections (i.e., gap junctions or excitatory/inhibitory synapses). We find that the emergence of ISR depends on the interplay between each neuron's intrinsic dynamical structure, channel noise, and network inputs, where the latter in turn depend on network structure parameters. We observe that with weak gap junction or excitatory synaptic coupling, network heterogeneity and sparseness tend to favor the emergence of ISR. With inhibitory coupling, ISR is quite robust. We also identify dynamical mechanisms that underlie various features of this ISR behavior. Our results suggest possible ways of experimentally observing ISR in actual neuronal systems.

Mammalian cortical voltage imaging using genetically encoded voltage indicators: a review honoring professor Amiram Grinvald

The pioneering work of Amiram Grinvald established voltage-sensitive dye imaging (VSDI) in the mammalian cortex in the 1980s and inspired decades of cortical voltage imaging and the associated technological developments. The recent conception and development of genetically encoded voltage indicators (GEVIs) overcome many of the limitations of classical VSDI, and open experimental approaches that provide accruing support for orchestrated neuronal circuit dynamics of spatially distributed neuronal circuit underlying behaviors. We will review recent achievements using GEVIs to optically monitor the cortical activity in mammalian brains in vivo and provide a perspective for potential future directions.

Tactile Defensiveness and Impaired Adaptation of Neuronal Activity in the Fmr1 Knock-Out Mouse Model of Autism

Sensory hypersensitivity is a common symptom in autism spectrum disorders (ASDs), including fragile X syndrome (FXS), and frequently leads to tactile defensiveness. In mouse models of ASDs, there is mounting evidence of neuronal and circuit hyperexcitability in several brain regions, which could contribute to sensory hypersensitivity. However, it is not yet known whether or how sensory stimulation might trigger abnormal sensory processing at the circuit level or abnormal behavioral responses in ASD mouse models, especially during an early developmental time when experience-dependent plasticity shapes such circuits. Using a novel assay, we discovered exaggerated motor responses to whisker stimulation in young Fmr1 knock-out (KO) mice (postnatal days 14-16), a model of FXS. Adult Fmr1 KO mice actively avoided a stimulus that was innocuous to wild-type controls, a sign of tactile defensiveness. Using in vivo two-photon calcium imaging of layer 2/3 barrel cortex neurons expressing GCaMP6s, we found no differences between wild-type and Fmr1 KO mice in overall whisker-evoked activity, though 45% fewer neurons in young Fmr1 KO mice responded in a time-locked manner. Notably, we identified a pronounced deficit in neuronal adaptation to repetitive whisker stimulation in both young and adult Fmr1 KO mice. Thus, impaired adaptation in cortical sensory circuits is a potential cause of tactile defensiveness in autism.SIGNIFICANCE STATEMENT We use a novel paradigm of repetitive whisker stimulation and in vivo calcium imaging to assess tactile defensiveness and barrel cortex activity in young and adult Fmr1 knock-out mice, the mouse model of fragile X syndrome (FXS). We describe evidence of tactile defensiveness, as well as a lack of L2/3 neuronal adaptation in barrel cortex, during whisker stimulation. We propose that a defect in sensory adaptation within local neuronal networks, beginning at a young age and continuing into adulthood, likely contributes to sensory overreactivity in FXS and perhaps other ASDs.

Adaptation modulates correlated subthreshold response variability in visual cortex

Cortical sensory responses are highly variable across stimulus presentations. This variability can be correlated across neurons (due to some combination of dense intracortical connectivity, cortical activity level, and cortical state), with fundamental implications for population coding. Yet the interpretation of correlated response variability (or "noise correlation") has remained fraught with difficulty, in part because of the restriction to extracellular neuronal spike recordings. Here, we measured response variability and its correlation at the most microscopic level of electrical neural activity, the membrane potential, by obtaining dual whole cell recordings from pairs of cortical pyramidal neurons during visual processing in the turtle whole brain ex vivo preparation. We found that during visual stimulation, correlated variability adapts toward an intermediate level and that this correlation dynamic is likely mediated by intracortical mechanisms. A model network with external inputs, synaptic depression, and structure reproduced the observed dynamics of correlated variability. These results suggest that intracortical adaptation self-organizes cortical circuits toward a balanced regime at which correlated variability is maintained at an intermediate level.NEW & NOTEWORTHY Correlated response variability has profound implications for stimulus encoding, yet our understanding of this phenomenon is based largely on spike data. Here, we investigate the dynamics and mechanisms of membrane potential-correlated variability (CC) in visual cortex with a combined experimental and computational approach. We observe a visually evoked increase in CC, followed by a fast return to baseline. Our results further suggest a link between this observation and the adaptation-mediated dynamics of emergent network phenomena.

Diverse effects of stimulus history in waking mouse auditory cortex

Responses to auditory stimuli are often strongly influenced by recent stimulus history. For example, in a paradigm called forward suppression, brief sounds can suppress the perception of, and the neural responses to, a subsequent sound, with the magnitude of this suppression depending on both the spectral and temporal distances between the sounds. As a step towards understanding the mechanisms that generate these adaptive representations in awake animals, we quantitatively characterize responses to two-tone sequences in the auditory cortex of waking mice. We find that cortical responses in a forward suppression paradigm are more diverse in waking mice than previously appreciated, that these responses vary between cells with different firing characteristics and waveform shapes, but that the variability in these responses is not substantially related to cortical depth or columnar location. Moreover, responses to the first tone in the sequence are often not linearly related to the suppression of the second tone response, suggesting that spike-frequency adaptation of cortical cells is not a large contributor to forward suppression or its variability. Instead, we use a simple multilayered model to show that cell-to-cell differences in the balance of intracortical inhibition and excitation will naturally produce such a diversity of forward interactions. We propose that diverse inhibitory connectivity allows the cortex to encode spectro-temporally fluctuating stimuli in multiple parallel ways.NEW & NOTEWORTHY Behavioral and neural responses to auditory stimuli are profoundly influenced by recent sounds, yet how this occurs is not known. Here, the authors show in the auditory cortex of awake mice that the quality of history-dependent effects is diverse and related to cell type, response latency, firing rates, and receptive field bandwidth. In a cortical model, differences in excitatory-inhibitory balance can produce this diversity, providing the cortex with multiple ways of representing temporally complex information.

Adaptation towards scale-free dynamics improves cortical stimulus discrimination at the cost of reduced detection

Fundamental to the function of nervous systems is the ability to reorganize to cope with changing sensory input. Although well-studied in single neurons, how such adaptive versatility manifests in the collective population dynamics and function of cerebral cortex remains unknown. Here we measured population neural activity with microelectrode arrays in turtle visual cortex while visually stimulating the retina. First, we found that, following the onset of stimulation, adaptation tunes the collective population dynamics towards a special regime with scale-free spatiotemporal activity, after an initial large-scale transient response. Concurrently, we observed an adaptive tradeoff between two important aspects of population coding-sensory detection and discrimination. As adaptation tuned the cortex toward scale-free dynamics, stimulus discrimination was enhanced, while stimulus detection was reduced. Finally, we used a network-level computational model to show that short-term synaptic depression was sufficient to mechanistically explain our experimental results. In the model, scale-free dynamics emerge only when the model operates near a special regime called criticality. Together our model and experimental results suggest unanticipated functional benefits and costs of adaptation near criticality in visual cortex.

Theory of optimal balance predicts and explains the amplitude and decay time of synaptic inhibition

Synaptic inhibition counterbalances excitation, but it is not known what constitutes optimal inhibition. We previously proposed that perfect balance is achieved when the peak of an excitatory postsynaptic potential (EPSP) is exactly at spike threshold, so that the slightest variation in excitation determines whether a spike is generated. Using simulations, we show that the optimal inhibitory postsynaptic conductance (IPSG) increases in amplitude and decay rate as synaptic excitation increases from 1 to 800 Hz. As further proposed by theory, we show that optimal IPSG parameters can be learned through anti-Hebbian rules. Finally, we compare our theoretical optima to published experimental data from 21 types of neurons, in which rates of synaptic excitation and IPSG decay times vary by factors of about 100 (5–600 Hz) and 50 (1–50 ms), respectively. From an infinite range of possible decay times, theory predicted experimental decay times within less than a factor of 2. Across a distinct set of 15 types of neuron recorded in vivo, theory predicted the amplitude of synaptic inhibition within a factor of 1.7. Thus, the theory can explain biophysical quantities from first principles.

Inhibition and excitation are counterbalanced at synapses, but the conditions that constitute optimal balance are not known. Here the authors show through modelling that the properties of synaptic inhibition are fine-tuned to maintain an optimal balance in which peak excitation reaches precisely to spike threshold.

Simultaneous Bayesian Estimation of Excitatory and Inhibitory Synaptic Conductances by Exploiting Multiple Recorded Trials

Advanced statistical methods have enabled trial-by-trial inference of the underlying excitatory and inhibitory synaptic conductances (SCs) of membrane-potential recordings. Simultaneous inference of both excitatory and inhibitory SCs sheds light on the neural circuits underlying the neural activity and advances our understanding of neural information processing. Conventional Bayesian methods can infer excitatory and inhibitory SCs based on a single trial of observed membrane potential. However, if multiple recorded trials are available, this typically leads to suboptimal estimation because they neglect common statistics (of synaptic inputs (SIs)) across trials. Here, we establish a new expectation maximization (EM) algorithm that improves such single-trial Bayesian methods by exploiting multiple recorded trials to extract common SI statistics across the trials. In this paper, the proposed EM algorithm is embedded in parallel Kalman filters or particle filters for multiple recorded trials to integrate their outputs to iteratively update the common SI statistics. These statistics are then used to infer the excitatory and inhibitory SCs of individual trials. We demonstrate the superior performance of multiple-trial Kalman filtering (MtKF) and particle filtering (MtPF) relative to that of the corresponding single-trial methods. While relative estimation error of excitatory and inhibitory SCs is known to depend on the level of current injection into a cell, our numerical simulations using MtKF show that both excitatory and inhibitory SCs are reliably inferred using an optimal level of current injection. Finally, we validate the robustness and applicability of our technique through simulation studies, and we apply MtKF to in vivo data recorded from the rat barrel cortex.

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.

The neurogenesis of P1 and N1: A concurrent EEG/LFP study

It is generally recognised that event related potentials (ERPs) of electroencephalogram (EEG) primarily reflect summed post-synaptic activity of the local pyramidal neural population(s). However, it is still not understood how the positive and negative deflections (e.g. P1, N1 etc) observed in ERP recordings are related to the underlying excitatory and inhibitory post-synaptic activity. We investigated the neurogenesis of P1 and N1 in ERPs by pharmacologically manipulating inhibitory post-synaptic activity in the somatosensory cortex of rodent, and concurrently recording EEG and local field potentials (LFPs). We found that the P1 wave in the ERP and LFP of the supragranular layers is determined solely by the excitatory post-synaptic activity of the local pyramidal neural population, as is the initial segment of the N1 wave across cortical depth. The later part of the N1 wave was modulated by inhibitory post-synaptic activity, with its peak and the pulse width increasing as inhibition was reduced. These findings suggest that the temporal delay of inhibition with respect to excitation observed in intracellular recordings is also reflected in extracellular field potentials (FPs), resulting in a temporal window during which only excitatory post-synaptic activity and leak channel activity are recorded in the ERP and evoked LFP time series. Based on these findings, we provide clarification on the interpretation of P1 and N1 in terms of the excitatory and inhibitory post-synaptic activities of the local pyramidal neural population(s).

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.

Hypo-excitation across all cortical laminae defines intermediate stages of cortical neuronal dysfunction in diffuse traumatic brain injury

Traumatic brain injury (TBI) is a major cause of morbidity and mortality world-wide and can result in persistent cognitive, sensory and behavioral dysfunction. Understanding the time course of TBI-induced pathology is essential to effective treatment outcomes. We induced TBI in rats using an impact acceleration method and tested for sensorimotor skill and sensory sensitivity behaviors for two weeks to find persistently poor outcomes post-injury. At two weeks post-injury we made high resolution extracellular recordings from barrel cortex neurons, to simple and complex whisker deflections. We found that the supragranular suppression of neural firing (compared to normal) previously seen in the immediate post-TBI aftermath had spread to include suppression of input and infragranular layers at two weeks post-injury; thus, there was suppression of whisker-driven firing rates in all cortical layers to both stimulus types. Further, there were abnormalities in temporal response patterns such that in layers 3-5 there was a temporal broadening of response patterns in response to both whisker deflection stimulus types and in L2 a narrowing of temporal patterns in response to the complex stimulus. Thus, at two weeks post-TBI, supragranular hypo-excitation has evolved to include deep cortical layers likely as a function of progressive atrophy and neurodegeneration. These results are consistent with the hypothesis that TBI alters the delicate excitatory/inhibitory balance in cortex and likely contributes to temporal broadening of responses and restricts the ability to code for complex sensory stimuli.

Presynaptic Adenosine Receptor-Mediated Regulation of Diverse Thalamocortical Short-Term Plasticity in the Mouse Whisker Pathway

Short-term synaptic plasticity (STP) sets the sensitivity of a synapse to incoming activity and determines the temporal patterns that it best transmits. In “driver” thalamocortical (TC) synaptic populations, STP is dominated by depression during stimulation from rest. However, during ongoing stimulation, lemniscal TC connections onto layer 4 neurons in mouse barrel cortex express variable STP. Each synapse responds to input trains with a distinct pattern of depression or facilitation around its mean steady-state response. As a result, in common with other synaptic populations, lemniscal TC synapses express diverse rather than uniform dynamics, allowing for a rich representation of temporally varying stimuli. Here, we show that this STP diversity is regulated presynaptically. Presynaptic adenosine receptors of the A1R type, but not kainate receptors (KARs), modulate STP behavior. Blocking the receptors does not eliminate diversity, indicating that diversity is related to heterogeneous expression of multiple mechanisms in the pathway from presynaptic calcium influx to neurotransmitter release.