Waking State: Rapid Variations Modulate Neural and Behavioral Responses

Inhibitory control of correlated intrinsic variability in cortical networks

Cortical networks exhibit intrinsic dynamics that drive coordinated, large-scale fluctuations across neuronal populations and create noise correlations that impact sensory coding. To investigate the network-level mechanisms that underlie these dynamics, we developed novel computational techniques to fit a deterministic spiking network model directly to multi-neuron recordings from different rodent species, sensory modalities, and behavioral states. The model generated correlated variability without external noise and accurately reproduced the diverse activity patterns in our recordings. Analysis of the model parameters suggested that differences in noise correlations across recordings were due primarily to differences in the strength of feedback inhibition. Further analysis of our recordings confirmed that putative inhibitory neurons were indeed more active during desynchronized cortical states with weak noise correlations. Our results demonstrate that network models with intrinsically-generated variability can accurately reproduce the activity patterns observed in multi-neuron recordings and suggest that inhibition modulates the interactions between intrinsic dynamics and sensory inputs to control the strength of noise correlations.

DOI:http://dx.doi.org/10.7554/eLife.19695.001

Our brains contain billions of neurons, which are continually producing electrical signals to relay information around the brain. Yet most of our knowledge of how the brain works comes from studying the activity of one neuron at a time. Recently, studies of multiple neurons have shown that they tend to be active together in short bursts called “up” states, which are followed by periods in which they are less active called “down” states. When we are sleeping or under a general anesthetic, the neurons may be completely silent during down states, but when we are awake the difference in activity between the two states is usually less extreme. However, it is still not clear how the neurons generate these patterns of activity.

To address this question, Stringer et al. studied the activity of neurons in the brains of awake and anesthetized rats, mice and gerbils. The experiments recorded electrical activity from many neurons at the same time and found a wide range of different activity patterns. A computational model based on these data suggests that differences in the degree to which some neurons suppress the activity of other neurons may account for this variety. Increasing the strength of these inhibitory signals in the model decreased the fluctuations in electrical activity across entire areas of the brain. Further analysis of the experimental data supported the model’s predictions by showing that inhibitory neurons – which act to reduce electrical activity in other neurons – were more active when there were fewer fluctuations in activity across the brain.

The next step following on from this work would be to develop ways to build computer models that can mimic the activity of many more neurons at the same time. The models could then be used to interpret the electrical activity produced by many different kinds of neuron. This will enable researchers to test more sophisticated hypotheses about how the brain works.

DOI:http://dx.doi.org/10.7554/eLife.19695.002

Time to wake up: Studying neurovascular coupling and brain-wide circuit function in the un-anesthetized animal

Functional magnetic resonance imaging (fMRI) has allowed the noninvasive study of task-based and resting-state brain dynamics in humans by inferring neural activity from blood-oxygenation-level dependent (BOLD) signal changes. An accurate interpretation of the hemodynamic changes that underlie fMRI signals depends on the understanding of the quantitative relationship between changes in neural activity and changes in cerebral blood flow, oxygenation and volume. While there has been extensive study of neurovascular coupling in anesthetized animal models, anesthesia causes large disruptions of brain metabolism, neural responsiveness and cardiovascular function. Here, we review work showing that neurovascular coupling and brain circuit function in the awake animal are profoundly different from those in the anesthetized state. We argue that the time is right to study neurovascular coupling and brain circuit function in the awake animal to bridge the physiological mechanisms that underlie animal and human neuroimaging signals, and to interpret them in light of underlying neural mechanisms. Lastly, we discuss recent experimental innovations that have enabled the study of neurovascular coupling and brain-wide circuit function in un-anesthetized and behaving animal models.

Pupil fluctuations track rapid changes in adrenergic and cholinergic activity in cortex

Rapid variations in cortical state during wakefulness have a strong influence on neural and behavioural responses and are tightly coupled to changes in pupil size across species. However, the physiological processes linking cortical state and pupil variations are largely unknown. Here we demonstrate that these rapid variations, during both quiet waking and locomotion, are highly correlated with fluctuations in the activity of corticopetal noradrenergic and cholinergic projections. Rapid dilations of the pupil are tightly associated with phasic activity in noradrenergic axons, whereas longer-lasting dilations of the pupil, such as during locomotion, are accompanied by sustained activity in cholinergic axons. Thus, the pupil can be used to sensitively track the activity in multiple neuromodulatory transmitter systems as they control the state of the waking brain.

In addition to light intensity, changes in pupil diameter are correlated with mental effort, attention and levels of arousal. Reimer et al. report that across behavioural states, fluctuations in pupil diameter are highly correlated with activity of noradrenergic and cholinergic projection neurons.

Pupil Dynamics Reflect Behavioral Choice and Learning in a Go/NoGo Tactile Decision-Making Task in Mice

The eye’s pupil undergoes dynamic changes in diameter associated with cognitive effort, motor activity and emotional state, and can be used to index brain state across mammalian species. Recent studies in head-fixed mice have linked arousal-related pupil dynamics with global neural activity as well as the activity of specific neuronal populations. However, it has remained unclear how pupil dynamics in mice report trial-by-trial performance of behavioral tasks, and change on a longer time scale with learning. We measured pupil dynamics longitudinally as mice learned to perform a Go/NoGo tactile decision-making task. Mice learned to discriminate between two textures presented to the whiskers by licking in response to the Go texture (Hit trial) or withholding licking in response to the NoGo texture (Correct Reject trial, CR). Characteristic pupil dynamics were associated with behavioral choices: large-amplitude pupil dilation prior to and during licking accompanied Hit and False Alarm (FA) responses, while smaller amplitude dilation followed by constriction accompanied CR responses. With learning, the choice-dependent pupil dynamics became more pronounced, including larger amplitude dilations in both Hit and FA trials and earlier onset dilations in Hit and CR trials. A more pronounced constriction was also present in CR trials. Furthermore, pupil dynamics predicted behavioral choice increasingly with learning to greater than 80% accuracy. Our results indicate that pupil dynamics reflect behavioral choice and learning in head-fixed mice, and have implications for understanding decision- and learning-related neuronal activity in pupil-linked neural circuits.

Stereotypic wheel running decreases cortical activity in mice

Prolonged wakefulness is thought to gradually increase ‘sleep need' and influence subsequent sleep duration and intensity, but the role of specific waking behaviours remains unclear. Here we report the effect of voluntary wheel running during wakefulness on neuronal activity in the motor and somatosensory cortex in mice. We find that stereotypic wheel running is associated with a substantial reduction in firing rates among a large subpopulation of cortical neurons, especially at high speeds. Wheel running also has longer-term effects on spiking activity across periods of wakefulness. Specifically, cortical firing rates are significantly higher towards the end of a spontaneous prolonged waking period. However, this increase is abolished when wakefulness is dominated by running wheel activity. These findings indicate that wake-related changes in firing rates are determined not only by wake duration, but also by specific waking behaviours.

Sleep need is thought to accumulate gradually over waking periods and is associated with changes in neuronal activity. Here the authors show that in mice cortical firing rates increase between the beginning and end of wakefulness periods but this increase is not seen in waking periods with voluntary stereotypic wheel running.

The Dynamics of Functional Brain Networks: Integrated Network States during Cognitive Task Performance

Higher brain function relies upon the ability to flexibly integrate information across specialized communities of brain regions; however, it is unclear how this mechanism manifests over time. In this study, we used time-resolved network analysis of fMRI data to demonstrate that the human brain traverses between functional states that maximize either segregation into tight-knit communities or integration across otherwise disparate neural regions. Integrated states enable faster and more accurate performance on a cognitive task, and are associated with dilations in pupil diameter, suggesting that ascending neuromodulatory systems may govern the transition between these alternative modes of brain function. Together, our results confirm a direct link between cognitive performance and the dynamic reorganization of the network structure of the brain.

Monoaminergic control of brain states and sensory processing: Existing knowledge and recent insights obtained with optogenetics

Monoamines are key neuromodulators involved in a variety of physiological and pathological brain functions. Classical studies using physiological and pharmacological tools have revealed several essential aspects of monoaminergic involvement in regulating the sleep-wake cycle and influencing sensory responses but many features have remained elusive due to technical limitations. The application of optogenetic tools led to the ability of monitoring and controlling neuronal populations with unprecedented temporal precision and neurochemical specificity. Here, we focus on recent advances in revealing the roles of some monoamines in brain state control and sensory information processing. We summarize the central position of monoamines in integrating sensory processing across sleep-wake states with an emphasis on research conducted using optogenetic techniques. Finally, we discuss the limitations and perspectives of new integrated experimental approaches in understanding the modulatory mechanisms of monoaminergic systems in the mammalian brain.

The effects of arousal on apical amplification and conscious state

Neocortical pyramidal cells can integrate two classes of input separately and use one to modulate response to the other. Their tuft dendrites are electrotonically separated from basal dendrites and soma by the apical dendrite, and apical hyperpolarization-activated currents (Ih) further isolate subthreshold integration of tuft inputs. When apical depolarization exceeds a threshold, however, it can enhance response to the basal inputs that specify the cell's selective sensitivity. This process is referred to as apical amplification (AA). We review evidence suggesting that, by regulating Ih in the apical compartments, adrenergic arousal controls the coupling between apical and somatic integration zones thus modifying cognitive capabilities closely associated with consciousness. Evidence relating AA to schizophrenia, sleep, and anesthesia is reviewed, and we assess theories that emphasize the relevance of AA to consciousness. Implications for theories of neocortical computation that emphasize context-sensitive modulation are summarized. We conclude that the findings concerning AA and its regulation by arousal offer a new perspective on states of consciousness, the function and evolution of neocortex, and psychopathology. Many issues worthy of closer examination arise.

Prolonged Inner Retinal Photoreception Depends on the Visual Retinoid Cycle

In addition to rods and cones, mammals have inner retinal photoreceptors called intrinsically photosensitive retinal ganglion cells (ipRGCs), which use the photopigment melanopsin and mediate nonimage-forming visual responses, such as pupil reflexes and circadian entrainment. After photic activation, photopigments must be reverted to their dark state to be light-sensitive again. For rods and to some extent cones, photopigment regeneration depends on the retinoid cycle in the adjacent retinal pigment epithelium (RPE). By contrast, ipRGCs are far from the RPE, and previous work suggests that melanopsin is capable of light-dependent self-regeneration. Here, we used in vitro ipRGC recording and in vivo pupillometry to show that the RPE is required for normal melanopsin-based responses to prolonged light, especially at high stimulus intensities. Melanopsin-based photoresponses of rat ipRGCs were remarkably sustained when a functional RPE was attached to the retina, but became far more transient if the RPE was removed, or if the retinoid cycle was inhibited, or when Müller glia were poisoned. Similarly, retinoid cycle inhibition markedly reduced the steady-state amplitude of melanopsin-driven pupil reflexes in both mice and rats. However, melanopsin photoresponses in RPE-separated rat retinas became more sustained in the presence of an 11-cis-retinal analog. In conclusion, during prolonged illumination, melanopsin regeneration depends partly on 11-cis-retinal from the RPE, possibly imported via Müller cells. Implications for RPE-related eye diseases and the acne drug isotretinoin (a retinoid cycle inhibitor) are discussed.

SIGNIFICANCE STATEMENT

Intrinsically photosensitive retinal ganglion cells (ipRGCs) contain the photopigment melanopsin and drive subconscious physiological responses to light, e.g., pupillary constriction and neuroendocrine regulation. In darkness, each photopigment molecule in ipRGCs, as well as rod/cone photoreceptors, contains 11-cis-retinal (a vitamin A derivative) and light isomerizes it to all-trans-retinal, which activates the photopigment. To make this photopigment excitable again,all-trans-retinal must be reisomerized to 11-cis-retinal. For rods and to some extent cones, this reisomerization occurs in the adjacent retinal pigment epithelium (RPE), but because ipRGCs are far from the RPE, they are thought to regenerate excitable melanopsin exclusively through RPE-independent means. Here, we present electrophysiological and behavioral evidence that ipRGCs depend on the RPE to continuously regenerate melanopsin during intense prolonged photostimulation.

Robust modulation of arousal regulation, performance, and frontostriatal activity through central thalamic deep brain stimulation in healthy nonhuman primates

The central thalamus (CT) is a key component of the brain-wide network underlying arousal regulation and sensory-motor integration during wakefulness in the mammalian brain. Dysfunction of the CT, typically a result of severe brain injury (SBI), leads to long-lasting impairments in arousal regulation and subsequent deficits in cognition. Central thalamic deep brain stimulation (CT-DBS) is proposed as a therapy to reestablish and maintain arousal regulation to improve cognition in select SBI patients. However, a mechanistic understanding of CT-DBS and an optimal method of implementing this promising therapy are unknown. Here we demonstrate in two healthy nonhuman primates (NHPs), Macaca mulatta, that location-specific CT-DBS improves performance in visuomotor tasks and is associated with physiological effects consistent with enhancement of endogenous arousal. Specifically, CT-DBS within the lateral wing of the central lateral nucleus and the surrounding medial dorsal thalamic tegmental tract (DTTm) produces a rapid and robust modulation of performance and arousal, as measured by neuronal activity in the frontal cortex and striatum. Notably, the most robust and reliable behavioral and physiological responses resulted when we implemented a novel method of CT-DBS that orients and shapes the electric field within the DTTm using spatially separated DBS leads. Collectively, our results demonstrate that selective activation within the DTTm of the CT robustly regulates endogenous arousal and enhances cognitive performance in the intact NHP; these findings provide insights into the mechanism of CT-DBS and further support the development of CT-DBS as a therapy for reestablishing arousal regulation to support cognition in SBI patients.

Behavioral-state modulation of inhibition is context-dependent and cell type specific in mouse visual cortex

Cortical responses to sensory stimuli are modulated by behavioral state. In the primary visual cortex (V1), visual responses of pyramidal neurons increase during locomotion. This response gain was suggested to be mediated through inhibitory neurons, resulting in the disinhibition of pyramidal neurons. Using in vivo two-photon calcium imaging in layers 2/3 and 4 in mouse V1, we reveal that locomotion increases the activity of vasoactive intestinal peptide (VIP), somatostatin (SST) and parvalbumin (PV)-positive interneurons during visual stimulation, challenging the disinhibition model. In darkness, while most VIP and PV neurons remained locomotion responsive, SST and excitatory neurons were largely non-responsive. Context-dependent locomotion responses were found in each cell type, with the highest proportion among SST neurons. These findings establish that modulation of neuronal activity by locomotion is context-dependent and contest the generality of a disinhibitory circuit for gain control of sensory responses by behavioral state.

DOI:http://dx.doi.org/10.7554/eLife.14985.001

How we perceive what we see depends on the context in which we see it, such as what we are doing at the time. For example, we perceive a park landscape differently when we are running through it than when we are sitting on a park bench. Behavior can also alter neuronal responses in the brain. Indeed, the neurons in the part of the brain that receives information related to vision (known as the visual cortex) respond differently to visual stimuli when an animal is moving compared to when the animal is still. However, while some recent studies revealed that specific types of neurons become more or less responsive during movement, others reported the opposite results.

One hypothesis that would explain these contradictory findings would be if the way that behavior, in this case movement, affects neuronal responses also depends on the external context in which the movement happens. Now, Pakan et al. have tested this hypothesis by imaging the activity of different types of neurons in the primary visual cortex of mice that were either running on a treadmill or staying still. The experiments were conducted in two different contexts: in total darkness (in which the mice could not see) and in the presence of display screens (which provided the mice with visual stimulation).

Pakan et al. confirmed that running does indeed affect the activity of specific neurons in different ways in different contexts. For example, when the mice received visual stimulation, the three main classes of neurons that send inhibitory signals in the visual cortex became more active during running. However, when the mouse ran in the dark, two of these neuron types became more active during running while the third type of neuron was unresponsive. This finding reveals more about the dynamic nature of inhibitory activity that strongly depends on the animal’s behaviour. It also shows how these neurons influence the excitatory neurons in the visual cortex, which send information to the rest of the brain for further processing towards perception.

The next step will be to identify what precise mechanism makes these neurons respond differently in unique contexts, and to tease apart how these movement-dependent signals affect the way animals perceive visual stimuli.

DOI:http://dx.doi.org/10.7554/eLife.14985.002

Sensory hypo-excitability in a rat model of fetal development in Fragile X Syndrome

Fragile X syndrome (FXS) is characterized by sensory hyper-sensitivity, and animal models suggest that neuronal hyper-excitability contributes to this phenotype. To understand how sensory dysfunction develops in FXS, we used the rat model (FMR-KO) to quantify the maturation of cortical visual responses from the onset of responsiveness prior to eye-opening, through age equivalents of human juveniles. Rather than hyper-excitability, visual responses before eye-opening had reduced spike rates and an absence of early gamma oscillations, a marker for normal thalamic function at this age. Despite early hypo-excitability, the developmental trajectory of visual responses in FMR-KO rats was normal, and showed the expected loss of visually evoked bursting at the same age as wild-type, two days before eye-opening. At later ages, during the third and fourth post-natal weeks, signs of mild hyper-excitability emerged. These included an increase in the visually-evoked firing of regular spiking, presumptive excitatory, neurons, and a reduced firing of fast-spiking, presumptive inhibitory, neurons. Our results show that early network changes in the FMR-KO rat arise at ages equivalent to fetal humans and have consequences for excitability that are opposite those found in adults. This suggests identification and treatment should begin early, and be tailored in an age-appropriate manner.

The mechanics of state-dependent neural correlations

Simultaneous recordings from large neural populations are becoming increasingly common. An important feature of population activity is the trial-to-trial correlated fluctuation of spike train outputs from recorded neuron pairs. Similar to the firing rate of single neurons, correlated activity can be modulated by a number of factors, from changes in arousal and attentional state to learning and task engagement. However, the physiological mechanisms that underlie these changes are not fully understood. We review recent theoretical results that identify three separate mechanisms that modulate spike train correlations: changes in input correlations, internal fluctuations and the transfer function of single neurons. We first examine these mechanisms in feedforward pathways and then show how the same approach can explain the modulation of correlations in recurrent networks. Such mechanistic constraints on the modulation of population activity will be important in statistical analyses of high-dimensional neural data.

Adaptive Spike Threshold Enables Robust and Temporally Precise Neuronal Encoding

Neural processing rests on the intracellular transformation of information as synaptic inputs are translated into action potentials. This transformation is governed by the spike threshold, which depends on the history of the membrane potential on many temporal scales. While the adaptation of the threshold after spiking activity has been addressed before both theoretically and experimentally, it has only recently been demonstrated that the subthreshold membrane state also influences the effective spike threshold. The consequences for neural computation are not well understood yet. We address this question here using neural simulations and whole cell intracellular recordings in combination with information theoretic analysis. We show that an adaptive spike threshold leads to better stimulus discrimination for tight input correlations than would be achieved otherwise, independent from whether the stimulus is encoded in the rate or pattern of action potentials. The time scales of input selectivity are jointly governed by membrane and threshold dynamics. Encoding information using adaptive thresholds further ensures robust information transmission across cortical states i.e. decoding from different states is less state dependent in the adaptive threshold case, if the decoding is performed in reference to the timing of the population response. Results from in vitro neural recordings were consistent with simulations from adaptive threshold neurons. In summary, the adaptive spike threshold reduces information loss during intracellular information transfer, improves stimulus discriminability and ensures robust decoding across membrane states in a regime of highly correlated inputs, similar to those seen in sensory nuclei during the encoding of sensory information.

A neuron is a tiny computer that transforms electrical inputs into electrical outputs. While neurons have been investigated and modeled for many decades, some aspects remain elusive. Recently, it was demonstrated that the membrane (voltage) state of a neuron determines its threshold to spiking. In the present study we asked, what are the consequences of this dependence for the computation the neuron performs. We find that this so called adaptive threshold allows neurons to be more focused on inputs which arrive close in time with other inputs. Also, it allows neurons to represent their information more robustly, such that a readout of their activity is less influenced by the state the brain is in. The present use of information theory provides a solid foundation for these results. We obtained the results primarily in detailed simulations, but performed neural recordings to verify these properties in real neurons. In summary, an adaptive spiking threshold allows neurons to specifically compute robustly with a focus on tight temporal correlations in their input.

Local and global contributions to hemodynamic activity in mouse cortex

Imaging techniques such as functional magnetic resonance imaging seek to estimate neural signals in local brain regions through measurements of hemodynamic activity. However, hemodynamic activity is accompanied by large vascular fluctuations of unclear significance. To characterize these fluctuations and their impact on estimates of neural signals, we used optical imaging in visual cortex of awake mice. We found that hemodynamic activity can be expressed as the sum of two components, one local and one global. The local component reflected presumed neural signals driven by visual stimuli in the appropriate retinotopic region. The global component constituted large fluctuations shared by larger cortical regions, which extend beyond visual cortex. These fluctuations varied from trial to trial, but they did not constitute noise; they correlated with pupil diameter, suggesting that they reflect variations in arousal or alertness. Distinguishing local and global contributions to hemodynamic activity may help understand neurovascular coupling and interpret measurements of hemodynamic responses.

Cognitive and Ocular Factors Jointly Determine Pupil Responses under Equiluminance

Changes in pupil diameter can reflect high-level cognitive signals that depend on central neuromodulatory mechanisms. However, brain mechanisms that adjust pupil size are also exquisitely sensitive to changes in luminance and other events that would be considered a nuisance in cognitive experiments recording pupil size. We implemented a simple auditory experiment involving no changes in visual stimulation. Using finite impulse-response fitting we found pupil responses triggered by different types of events. Among these are pupil responses to auditory events and associated surprise: cognitive effects. However, these cognitive responses were overshadowed by pupil responses associated with blinks and eye movements, both inevitable nuisance factors that lead to changes in effective luminance. Of note, these latter pupil responses were not recording artifacts caused by blinks and eye movements, but endogenous pupil responses that occurred in the wake of these events. Furthermore, we identified slow (tonic) changes in pupil size that differentially influenced faster (phasic) pupil responses. Fitting all pupil responses using gamma functions, we provide accurate characterisations of cognitive and non-cognitive response shapes, and quantify each response's dependence on tonic pupil size. These results allow us to create a set of recommendations for pupil size analysis in cognitive neuroscience, which we have implemented in freely available software.

More Gamma More Predictions: Gamma-Synchronization as a Key Mechanism for Efficient Integration of Classical Receptive Field Inputs with Surround Predictions

During visual stimulation, neurons in visual cortex often exhibit rhythmic and synchronous firing in the gamma-frequency (30–90 Hz) band. Whether this phenomenon plays a functional role during visual processing is not fully clear and remains heavily debated. In this article, we explore the function of gamma-synchronization in the context of predictive and efficient coding theories. These theories hold that sensory neurons utilize the statistical regularities in the natural world in order to improve the efficiency of the neural code, and to optimize the inference of the stimulus causes of the sensory data. In visual cortex, this relies on the integration of classical receptive field (CRF) data with predictions from the surround. Here we outline two main hypotheses about gamma-synchronization in visual cortex. First, we hypothesize that the precision of gamma-synchronization reflects the extent to which CRF data can be accurately predicted by the surround. Second, we hypothesize that different cortical columns synchronize to the extent that they accurately predict each other’s CRF visual input. We argue that these two hypotheses can account for a large number of empirical observations made on the stimulus dependencies of gamma-synchronization. Furthermore, we show that they are consistent with the known laminar dependencies of gamma-synchronization and the spatial profile of intercolumnar gamma-synchronization, as well as the dependence of gamma-synchronization on experience and development. Based on our two main hypotheses, we outline two additional hypotheses. First, we hypothesize that the precision of gamma-synchronization shows, in general, a negative dependence on RF size. In support, we review evidence showing that gamma-synchronization decreases in strength along the visual hierarchy, and tends to be more prominent in species with small V1 RFs. Second, we hypothesize that gamma-synchronized network dynamics facilitate the emergence of spiking output that is particularly information-rich and sparse.

The Basal Forebrain and Motor Cortex Provide Convergent yet Distinct Movement-Related Inputs to the Auditory Cortex

Cholinergic inputs to the auditory cortex from the basal forebrain (BF) are important to auditory processing and plasticity, but little is known about the organization of these synapses onto different auditory cortical neuron types, how they influence auditory responsiveness, and their activity patterns during various behaviors. Using intersectional tracing, optogenetic circuit mapping, and in vivo calcium imaging, we found that cholinergic axons arising from the caudal BF target major excitatory and inhibitory auditory cortical cell types, rapidly modulate auditory cortical tuning, and display fast movement-related activity. Furthermore, the BF and the motor cortex-another source of movement-related activity-provide convergent input onto some of the same auditory cortical neurons. Cholinergic and motor cortical afferents to the auditory cortex display distinct activity patterns and presynaptic partners, indicating that the auditory cortex integrates bottom-up cholinergic signals related to ongoing movements and arousal with top-down information concerning impending movements and motor planning.

Computational implications of biophysical diversity and multiple timescales in neurons and synapses for circuit performance

Despite advances in experimental and theoretical neuroscience, we are still trying to identify key biophysical details that are important for characterizing the operation of brain circuits. Biological mechanisms at the level of single neurons and synapses can be combined as 'building blocks' to generate circuit function. We focus on the importance of capturing multiple timescales when describing these intrinsic and synaptic components. Whether inherent in the ionic currents, the neuron's complex morphology, or the neurotransmitter composition of synapses, these multiple timescales prove crucial for capturing the variability and richness of circuit output and enhancing the information-carrying capacity observed across nervous systems.

Correlation between Cortical State and Locus Coeruleus Activity: Implications for Sensory Coding in Rat Barrel Cortex

Cortical state modulates the background activity of cortical neurons, and their evoked response to sensory stimulation. Multiple mechanisms are involved in switching between cortical states including various neuromodulatory systems. Locus Coeruleus (LC) is one of the major neuromodulatory nuclei in the brainstem with widespread projections throughout the brain and modulates the activity of cells and networks. Here, we quantified the link between the LC spontaneous activity, cortical state and sensory processing in the rat vibrissal somatosensory "barrel" cortex (BC). We simultaneously recorded unit activity from LC and BC along with prefrontal electroencephalogram (EEG) while presenting brief whisker deflections under urethane anesthesia. The ratio of low to high frequency components of EEG (referred to as the L/H ratio) was employed to identify cortical state. We found that the spontaneous activity of LC units exhibited a negative correlation with the L/H ratio. Cross-correlation analysis revealed that changes in LC firing preceded changes in the cortical state: the correlation of the LC firing profile with the L/H ratio was maximal at an average lag of -1.2 s. We further quantified BC neuronal responses to whisker stimulation during the synchronized and desynchronized states. In the desynchronized state, BC neurons showed lower stimulus detection threshold, higher response fidelity, and shorter response latency. The most prominent change was observed in the late phase of BC evoked activity (100-400 ms post stimulus onset): almost every BC unit exhibited a greater late response during the desynchronized state. Categorization of the BC evoked responses based on LC activity (into high and low LC discharge rates) resulted in highly similar response profiles compared to categorization based on the cortical state (low and high L/H ratios). These findings provide evidence for the involvement of the LC neuromodulatory system in desynchronization of cortical state and the consequent enhancement of sensory coding efficiency.

Dietary Restriction Affects Neuronal Response Property and GABA Synthesis in the Primary Visual Cortex

Previous studies have reported inconsistent effects of dietary restriction (DR) on cortical inhibition. To clarify this issue, we examined the response properties of neurons in the primary visual cortex (V1) of DR and control groups of cats using in vivo extracellular single-unit recording techniques, and assessed the synthesis of inhibitory neurotransmitter GABA in the V1 of cats from both groups using immunohistochemical and Western blot techniques. Our results showed that the response of V1 neurons to visual stimuli was significantly modified by DR, as indicated by an enhanced selectivity for stimulus orientations and motion directions, decreased visually-evoked response, lowered spontaneous activity and increased signal-to-noise ratio in DR cats relative to control cats. Further, it was shown that, accompanied with these changes of neuronal responsiveness, GABA immunoreactivity and the expression of a key GABA-synthesizing enzyme GAD67 in the V1 were significantly increased by DR. These results demonstrate that DR may retard brain aging by increasing the intracortical inhibition effect and improve the function of visual cortical neurons in visual information processing. This DR-induced elevation of cortical inhibition may favor the brain in modulating energy expenditure based on food availability.

Electrophysiological, transcriptomic and morphologic profiling of single neurons using Patch-seq

Despite the importance of the mammalian neocortex for complex cognitive processes, we still lack a comprehensive description of its cellular components. To improve the classification of neuronal cell types and the functional characterization of single neurons, we present Patch-seq, a method that combines whole-cell electrophysiological patch-clamp recordings, single-cell RNA-sequencing and morphological characterization. Following electrophysiological characterization, cell contents are aspirated through the patch-clamp pipette and prepared for RNA-sequencing. Using this approach, we generate electrophysiological and molecular profiles of 58 neocortical cells and show that gene expression patterns can be used to infer the morphological and physiological properties such as axonal arborization and action potential amplitude of individual neurons. Our results shed light on the molecular underpinnings of neuronal diversity and suggest that Patch-seq can facilitate the classification of cell types in the nervous system.

Reward expectation differentially modulates attentional behavior and activity in visual area V4

Neural activity in visual area V4 is enhanced when attention is directed into neuronal receptive fields. However, the source of this enhancement is unclear, as most physiological studies have manipulated attention by changing the absolute reward associated with a particular location as well as its value relative to other locations. We trained monkeys to discriminate the orientation of two stimuli presented simultaneously in different hemifields while we independently varied the reward magnitude associated with correct discrimination at each location. Behavioral measures of attention were controlled by the relative value of each location. By contrast, neurons in V4 were consistently modulated by absolute reward value, exhibiting increased activity, increased gamma-band power and decreased trial-to-trial variability whenever receptive field locations were associated with large rewards. These data challenge the notion that the perceptual benefits of spatial attention rely on increased signal-to-noise in V4. Instead, these benefits likely derive from downstream selection mechanisms.