Dynamic corticothalamic modulation of the somatosensory thalamocortical circuit during wakefulness

The feedback projections from cortical layer 6 (L6CT) to the sensory thalamus have long been implicated in playing a primary role in gating sensory signaling but remain poorly understood. To causally elucidate the full range of effects of these projections, we targeted silicon probe recordings to the whisker thalamocortical circuit of awake mice selectively expressing Channelrhodopsin-2 in L6CT neurons. Through optogenetic manipulation of L6CT neurons, multi-site electrophysiological recordings, and modeling of L6CT circuitry, we establish L6CT neurons as dynamic modulators of ongoing spiking in the ventral posteromedial nucleus of the thalamus (VPm), either suppressing or enhancing VPm spiking depending on L6CT neurons' firing rate and synchrony. Differential effects across the cortical excitatory and inhibitory sub-populations point to an overall influence of L6CT feedback on cortical excitability that could have profound implications for regulating sensory signaling across a range of ethologically relevant conditions.

Dynamic corticothalamic modulation of the somatosensory thalamocortical circuit during wakefulness

The feedback projections from cortical layer 6 (L6CT) to sensory thalamus have long been implicated in playing a primary role in gating sensory signaling but remain poorly understood. To causally elucidate the full range of effects of these projections, we targeted silicon probe recordings to the whisker thalamocortical circuit of awake mice selectively expressing Channelrhodopsin-2 in L6CT neurons. Through optogenetic manipulation of L6CT neurons, multi-site electrophysiological recordings, and modeling of L6CT circuitry, we establish L6CT neurons as dynamic modulators of ongoing spiking in the ventro-posterior-medial nucleus of thalamus (VPm), either suppressing or enhancing VPm spiking depending on L6CT neurons' firing rate and synchrony. Differential effects across the cortical excitatory and inhibitory sub-populations point to an overall influence of L6CT feedback on cortical excitability that could have profound implications for regulating sensory signaling across a range of ethologically relevant conditions.

A machine learning approach for real-time cortical state estimation

Objective.Cortical function is under constant modulation by internally-driven, latent variables that regulate excitability, collectively known as 'cortical state'. Despite a vast literature in this area, the estimation of cortical state remains relatively ad hoc, and not amenable to real-time implementation. Here, we implement robust, data-driven, and fast algorithms that address several technical challenges for online cortical state estimation.Approach. We use unsupervised Gaussian mixture models to identify discrete, emergent clusters in spontaneous local field potential signals in cortex. We then extend our approach to a temporally-informed hidden semi-Markov model (HSMM) with Gaussian observations to better model and infer cortical state transitions. Finally, we implement our HSMM cortical state inference algorithms in a real-time system, evaluating their performance in emulation experiments.Main results. Unsupervised clustering approaches reveal emergent state-like structure in spontaneous electrophysiological data that recapitulate arousal-related cortical states as indexed by behavioral indicators. HSMMs enable cortical state inferences in a real-time context by modeling the temporal dynamics of cortical state switching. Using HSMMs provides robustness to state estimates arising from noisy, sequential electrophysiological data.Significance. To our knowledge, this work represents the first implementation of a real-time software tool for continuously decoding cortical states with high temporal resolution (40 ms). The software tools that we provide can facilitate our understanding of how cortical states dynamically modulate cortical function on a moment-by-moment basis and provide a basis for state-aware brain machine interfaces across health and disease.

Thalamic bursting and the role of timing and synchrony in thalamocortical signaling in the awake mouse

The thalamus controls transmission of sensory signals from periphery to cortex, ultimately shaping perception. Despite this significant role, dynamic thalamic gating and the consequences for downstream cortical sensory representations have not been well studied in the awake brain. We optogenetically modulated the ventro-posterior-medial thalamus in the vibrissa pathway of the awake mouse and measured spiking activity in the thalamus and activity in primary somatosensory cortex (S1) using extracellular electrophysiology and genetically encoded voltage imaging. Thalamic hyperpolarization significantly enhanced thalamic sensory-evoked bursting; however, surprisingly, the S1 cortical response was not amplified, but instead, timing precision was significantly increased, spatial activation more focused, and there was an increased synchronization of cortical inhibitory neurons. A thalamocortical network model implicates the modulation of precise timing of feedforward thalamic population spiking, presenting a highly sensitive, timing-based gating of sensory signaling to the cortex.

Ipsilateral Stimulus Encoding in Primary and Secondary Somatosensory Cortex of Awake Mice

Lateralization is a hallmark of somatosensory processing in the mammalian brain. However, in addition to their contralateral representation, unilateral tactile stimuli also modulate neuronal activity in somatosensory cortices of the ipsilateral hemisphere. The cellular organization and functional role of these ipsilateral stimulus responses in awake somatosensory cortices, especially regarding stimulus coding, are unknown. Here, we targeted silicon probe recordings to the vibrissa region of primary (S1) and secondary (S2) somatosensory cortex of awake head-fixed mice of either sex while delivering ipsilateral and contralateral whisker stimuli. Ipsilateral stimuli drove larger and more reliable responses in S2 than in S1, and activated a larger fraction of stimulus-responsive neurons. Ipsilateral stimulus-responsive neurons were rare in layer 4 of S1, but were located in equal proportion across all layers in S2. Linear classifier analyses further revealed that decoding of the ipsilateral stimulus was more accurate in S2 than S1, whereas S1 decoded contralateral stimuli most accurately. These results reveal substantial encoding of ipsilateral stimuli in S1 and especially S2, consistent with the hypothesis that higher cortical areas may integrate tactile inputs across larger portions of space, spanning both sides of the body.SIGNIFICANCE STATEMENT Tactile information obtained by one side of the body is represented in the activity of neurons of the opposite brain hemisphere. However, unilateral tactile stimulation also modulates neuronal activity in the other, or ipsilateral, brain hemisphere. This ipsilateral activity may play an important role in the representation and processing of tactile information, in particular when the sense of touch involves both sides of the body. Our work in the whisker system of awake mice reveals that neocortical ipsilateral activity, in particular that of deep layer excitatory neurons of secondary somatosensory cortex (S2), contains information about the presence and the velocity of unilateral tactile stimuli, which supports a key role for S2 in integrating tactile information across both body sides.

Emerging experience-dependent dynamics in primary somatosensory cortex reflect behavioral adaptation

Behavioral experience and flexibility are crucial for survival in a constantly changing environment. Despite evolutionary pressures to develop adaptive behavioral strategies in a dynamically changing sensory landscape, the underlying neural correlates have not been well explored. Here, we use genetically encoded voltage imaging to measure signals in primary somatosensory cortex (S1) during sensory learning and behavioral adaptation in the mouse. In response to changing stimulus statistics, mice adopt a strategy that modifies their detection behavior in a context dependent manner as to maintain reward expectation. Surprisingly, neuronal activity in S1 shifts from simply representing stimulus properties to transducing signals necessary for adaptive behavior in an experience dependent manner. Our results suggest that neuronal signals in S1 are part of an adaptive framework that facilitates flexible behavior as individuals gain experience, which could be part of a general scheme that dynamically distributes the neural correlates of behavior during learning.

Waiblinger et al. investigate the role of primary sensory cortex in flexible behaviors. They show that neuronal signals in S1 are part of an adaptive and dynamic framework that facilitates flexible behavior as an individual gains experience, indicating a role for S1 in long-term adaptive strategies.

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.

Inferring thalamocortical monosynaptic connectivity in vivo

As the tools to simultaneously record electrophysiological signals from large numbers of neurons within and across brain regions become increasingly available, this opens up for the first time the possibility of establishing the details of causal relationships between monosynaptically connected neurons and the patterns of neural activation that underlie perception and behavior. Although recorded activity across synaptically connected neurons has served as the cornerstone for much of what we know about synaptic transmission and plasticity, this has largely been relegated to ex vivo preparations that enable precise targeting under relatively well-controlled conditions. Analogous studies in vivo, where image-guided targeting is often not yet possible, rely on indirect, data-driven measures, and as a result such studies have been sparse and the dependence upon important experimental parameters has not been well studied. Here, using in vivo extracellular single-unit recordings in the topographically aligned rodent thalamocortical pathway, we sought to establish a general experimental and computational framework for inferring synaptic connectivity. Specifically, attacking this problem within a statistical signal detection framework utilizing experimentally recorded data in the ventral-posterior medial (VPm) region of the thalamus and the homologous region in layer 4 of primary somatosensory cortex (S1) revealed a trade-off between network activity levels needed for the data-driven inference and synchronization of nearby neurons within the population that results in masking of synaptic relationships. Here, we provide a framework for establishing connectivity in multisite, multielectrode recordings based on statistical inference, setting the stage for large-scale assessment of synaptic connectivity within and across brain structures.NEW & NOTEWORTHY Despite the fact that all brain function relies on the long-range transfer of information across different regions, the tools enabling us to measure connectivity across brain structures are lacking. Here, we provide a statistical framework for identifying and assessing potential monosynaptic connectivity across neuronal circuits from population spiking activity that generalizes to large-scale recording technologies that will help us to better understand the signaling within networks that underlies perception and behavior.

State-space optimal feedback control of optogenetically driven neural activity

Objective.The rapid acceleration of tools for recording neuronal populations and targeted optogenetic manipulation has enabled real-time, feedback control of neuronal circuits in the brain. Continuously-graded control of measured neuronal activity poses a wide range of technical challenges, which we address through a combination of optogenetic stimulation and a state-space optimal control framework implemented in the thalamocortical circuit of the awake mouse.Approach.Closed-loop optogenetic control of neurons was performed in real-time via stimulation of channelrhodopsin-2 expressed in the somatosensory thalamus of the head-fixed mouse. A state-space linear dynamical system model structure was used to approximate the light-to-spiking input-output relationship in both single-neuron as well as multi-neuron scenarios when recording from multielectrode arrays. These models were utilized to design state feedback controller gains by way of linear quadratic optimal control and were also used online for estimation of state feedback, where a parameter-adaptive Kalman filter provided robustness to model-mismatch.Main results.This model-based control scheme proved effective for feedback control of single-neuron firing rate in the thalamus of awake animals. Notably, the graded optical actuation utilized here did not synchronize simultaneously recorded neurons, but heterogeneity across the neuronal population resulted in a varied response to stimulation. Simulated multi-output feedback control provided better control of a heterogeneous population and demonstrated how the approach generalizes beyond single-neuron applications.Significance.To our knowledge, this work represents the first experimental application of state space model-based feedback control for optogenetic stimulation. In combination with linear quadratic optimal control, the approaches laid out and tested here should generalize to future problems involving the control of highly complex neural circuits. More generally, feedback control of neuronal circuits opens the door to adaptively interacting with the dynamics underlying sensory, motor, and cognitive signaling, enabling a deeper understanding of circuit function and ultimately the control of function in the face of injury or disease.

Thalamic state influences timing precision in the thalamocortical circuit

Sensory signals from the outside world are transduced at the periphery, passing through thalamus before reaching cortex, ultimately giving rise to the sensory representations that enable us to perceive the world. The thalamocortical circuit is particularly sensitive to the temporal precision of thalamic spiking due to highly convergent synaptic connectivity. Thalamic neurons can exhibit burst and tonic modes of firing that strongly influence timing within the thalamus. The impact of these changes in thalamic state on sensory encoding in the cortex, however, remains unclear. Here, we investigated the role of thalamic state on timing in the thalamocortical circuit of the vibrissa pathway in the anesthetized rat. We optogenetically hyperpolarized thalamus while recording single unit activity in both thalamus and cortex. Tonic spike-triggered analysis revealed temporally precise thalamic spiking that was locked to weak white-noise sensory stimuli, whereas thalamic burst spiking was associated with a loss in stimulus-locked temporal precision. These thalamic state-dependent changes propagated to cortex such that the cortical timing precision was diminished during the hyperpolarized (burst biased) thalamic state. Although still sensory driven, the cortical neurons became significantly less precisely locked to the weak white-noise stimulus. The results here suggests a state-dependent differential regulation of spike timing precision in the thalamus that could gate what signals are ultimately propagated to cortex.NEW & NOTEWORTHY The majority of sensory signals are transmitted through the thalamus. There is growing evidence of complex thalamic gating through coordinated firing modes that have a strong impact on cortical sensory representations. Optogenetic hyperpolarization of thalamus pushed it into burst firing that disrupted precise time-locked sensory signaling, with a direct impact on the downstream cortical encoding, setting the stage for a timing-based thalamic gate of sensory signaling.

Compensation of physiological motion enables high-yield whole-cell recording in vivo

BACKGROUND

Whole-cell patch-clamp recording in vivo is the gold-standard method for measuring subthreshold electrophysiology from single cells during behavioural tasks, sensory stimulations, and optogenetic manipulation. However, these recordings require a tight, gigaohm resistance, seal between a glass pipette electrode's aperture and a cell's membrane. These seals are difficult to form, especially in vivo, in part because of a strong dependence on the distance between the pipette aperture and cell membrane.

NEW METHOD

We elucidate and utilize this dependency to develop an autonomous method for placement and synchronization of pipette's tip aperture to the membrane of a nearby, moving neuron, which enables high-yield seal formation and subsequent recordings deep in the brain of the living mouse.

RESULTS

This synchronization procedure nearly doubles the reported gigaseal yield in the thalamus (>3 mm below the pial surface) from 26 % (n = 17/64) to 48 % (n = 32/66). Whole-cell recording yield improved from 10 % (n = 9/88) to 24 % (n = 18/76) when motion compensation was used during the gigaseal formation. As an example of its application, we utilized this system to investigate the role of the sensory environment and ventral posterior medial region (VPM) projection synchrony on intracellular dynamics in the barrel cortex.

COMPARISON WITH EXISTING METHOD(S)

Current methods of in vivo whole-cell patch clamping do not synchronize the position of the pipette to motion of the cell.

CONCLUSIONS

This method results in substantially greater subcortical whole-cell recording yield than previously reported and thus makes pan-brain whole-cell electrophysiology practical in the living mouse brain.

Unilateral Optogenetic Inhibition and Excitation of Basal Ganglia Output Affect Directional Lick Choices and Movement Initiation in Mice

Models of basal ganglia (BG) function predict that tonic inhibitory output to motor thalamus (MT) suppresses unwanted movements, and that a decrease in such activity leads to action selection. Further, for unilateral activity changes in the BG, a lateralized effect on contralateral movements can be expected due to ipsilateral thalamocortical connectivity. However, a direct test of these outcomes of thalamic inhibition has not been performed. To conduct such a direct test, we utilized rapid optogenetic activation and inactivation of the GABAergic output of the substantia nigra pars reticulata (SNr) to MT in male and female mice that were trained in a sensory cued left/right licking task. Directional licking tasks have previously been shown to depend on a thalamocortical feedback loop between ventromedial MT and antero-lateral premotor cortex. In confirmation of model predictions, we found that unilateral optogenetic inhibition of GABAergic output from the SNr, during ipsilaterally cued trials, biased decision making towards a contralateral lick without affecting motor performance. In contrast, optogenetic excitation of SNr terminals in MT resulted in an opposite bias towards the ipsilateral direction confirming a bidirectional effect of tonic nigral output on directional decision making. However, direct optogenetic excitation of neurons in the SNr resulted in bilateral movement suppression, which is in agreement with previous results that show such suppression for nigral terminals in the superior colliculus (SC), which receives a bilateral projection from SNr.

Design strategies for dynamic closed-loop optogenetic neurocontrol in vivo

OBJECTIVE

Controlling neural activity enables the possibility of manipulating sensory perception, cognitive processes, and body movement, in addition to providing a powerful framework for functionally disentangling the neural circuits that underlie these complex phenomena. Over the last decade, optogenetic stimulation has become an increasingly important and powerful tool for understanding neural circuit function, owing to the ability to target specific cell types and bidirectionally modulate neural activity. To date, most stimulation has been provided in open-loop or in an on/off closed-loop fashion, where previously-determined stimulation is triggered by an event. Here, we describe and demonstrate a design approach for precise optogenetic control of neuronal firing rate modulation using feedback to guide stimulation continuously.

APPROACH

Using the rodent somatosensory thalamus as an experimental testbed for realizing desired time-varying patterns of firing rate modulation, we utilized a moving average exponential filter to estimate firing rate online from single-unit spiking measured extracellularly. This estimate of instantaneous rate served as feedback for a proportional integral (PI) controller, which was designed during the experiment based on a linear-nonlinear Poisson (LNP) model of the neuronal response to light.

MAIN RESULTS

The LNP model fit during the experiment enabled robust closed-loop control, resulting in good tracking of sinusoidal and non-sinusoidal targets, and rejection of unmeasured disturbances. Closed-loop control also enabled manipulation of trial-to-trial variability.

SIGNIFICANCE

Because neuroscientists are faced with the challenge of dissecting the functions of circuit components, the ability to maintain control of a region of interest in spite of changes in ongoing neural activity will be important for disambiguating function within networks. Closed-loop stimulation strategies are ideal for control that is robust to such changes, and the employment of continuous feedback to adjust stimulation in real-time can improve the quality of data collected using optogenetic manipulation.

Soft and MRI Compatible Neural Electrodes from Carbon Nanotube Fibers

Soft and magnetic resonance imaging (MRI) compatible neural electrodes enable stable chronic electrophysiological measurements and anatomical or functional MRI studies of the entire brain without electrode interference with MRI images. These properties are important for many studies, ranging from a fundamental neurophysiological study of functional MRI signals to a chronic neuromodulatory effect investigation of therapeutic deep brain stimulation. Here we develop soft and MRI compatible neural electrodes using carbon nanotube (CNT) fibers with a diameter from 20 μm down to 5 μm. The CNT fiber electrodes demonstrate excellent interfacial electrochemical properties and greatly reduced MRI artifacts than PtIr electrodes under a 7.0 T MRI scanner. With a shuttle-assisted implantation strategy, we show that the soft CNT fiber electrodes can precisely target specific brain regions and record high-quality single-unit neural signals. Significantly, they are capable of continuously detecting and isolating single neuronal units from rats for up to 4-5 months without electrode repositioning, with greatly reduced brain inflammatory responses as compared to their stiff metal counterparts. In addition, we show that due to their high tensile strength, the CNT fiber electrodes can be retracted controllably postinsertion, which provides an effective and convenient way to do multidepth recording or potentially selecting cells with particular response properties. The chronic recording stability and MRI compatibility, together with their small size, provide the CNT fiber electrodes unique research capabilities for both basic and applied neuroscience studies.

Stimulus Context and Reward Contingency Induce Behavioral Adaptation in a Rodent Tactile Detection Task

Behavioral adaptation is a prerequisite for survival in a constantly changing sensory environment, but the underlying strategies and relevant variables driving adaptive behavior are not well understood. Many learning models and neural theories consider probabilistic computations as an efficient way to solve a variety of tasks, especially if uncertainty is involved. Although this suggests a possible role for probabilistic inference and expectation in adaptive behaviors, there is little if any evidence of this relationship experimentally. Here, we investigated adaptive behavior in the rat model by using a well controlled behavioral paradigm within a psychophysical framework to predict and quantify changes in performance of animals trained on a simple whisker-based detection task. The sensory environment of the task was changed by transforming the probabilistic distribution of whisker deflection amplitudes systematically while measuring the animal's detection performance and corresponding rate of accumulated reward. We show that the psychometric function deviates significantly and reversibly depending on the probabilistic distribution of stimuli. This change in performance relates to accumulating a constant reward count across trials, yet it is exempt from changes in reward volume. Our simple model of reward accumulation captures the observed change in psychometric sensitivity and predicts a strategy seeking to maintain reward expectation across trials in the face of the changing stimulus distribution. We conclude that rats are able maintain a constant payoff under changing sensory conditions by flexibly adjusting their behavioral strategy. Our findings suggest the existence of an internal probabilistic model that facilitates behavioral adaptation when sensory demands change.SIGNIFICANCE STATEMENT The strategy animals use to deal with a complex and ever-changing world is a key to understanding natural behavior. This study provides evidence that rodent behavioral performance is highly flexible in the face of a changing stimulus distribution, consistent with a strategy to maintain a desired accumulation of reward.

Primary Tactile Thalamus Spiking Reflects Cognitive Signals

Little is known about whether information transfer at primary sensory thalamic nuclei is modified by behavioral context. Here we studied the influence of previous decisions/rewards on current choices and preceding spike responses of ventroposterior medial thalamus (VPm; the primary sensory thalamus in the rat whisker-related tactile system). We trained head-fixed rats to detect a ramp-like deflection of one whisker interspersed within ongoing white noise stimulation. Using generative modeling of behavior, we identify two task-related variables that are predictive of actual decisions. The first reflects task engagement on a local scale ("trial history": defined as the decisions and outcomes of a small number of past trials), whereas the other captures behavioral dynamics on a global scale ("satiation": slow dynamics of the response pattern along an entire session). Although satiation brought about a slow drift from Go to NoGo decisions during the session, trial history was related to local (trial-by-trial) patterning of Go and NoGo decisions. A second model that related the same predictors first to VPm spike responses, and from there to decisions, indicated that spiking, in contrast to behavior, is sensitive to trial history but relatively insensitive to satiation. Trial history influences VPm spike rates and regularity such that a history of Go decisions would predict fewer noise-driven spikes (but more regular ones), and more ramp-driven spikes. Neuronal activity in VPm, thus, is sensitive to local behavioral history, and may play an important role in higher-order cognitive signaling.SIGNIFICANCE STATEMENT It is an important question for perceptual and brain functions to find out whether cognitive signals modulate the sensory signal stream and if so, where in the brain this happens. This study provides evidence that decision and reward history can already be reflected in the ascending sensory pathway, on the level of first-order sensory thalamus. Cognitive signals are relayed very selectively such that only local trial history (spanning a few trials) but not global history (spanning an entire session) are reflected.

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.

Genetically expressed voltage sensor ArcLight for imaging large scale cortical activity in the anesthetized and awake mouse

With the recent breakthrough in genetically expressed voltage indicators (GEVIs), there has been a tremendous demand to determine the capabilities of these sensors in vivo. Novel voltage sensitive fluorescent proteins allow for direct measurement of neuron membrane potential changes through changes in fluorescence. Here, we utilized ArcLight, a recently developed GEVI, and examined the functional characteristics in the widely used mouse somatosensory whisker pathway. We measured the resulting evoked fluorescence using a wide-field microscope and a CCD camera at 200 Hz, which enabled voltage recordings over the entire cortical region with high temporal resolution. We found that ArcLight produced a fluorescent response in the S1 barrel cortex during sensory stimulation at single whisker resolution. During wide-field cortical imaging, we encountered substantial hemodynamic noise that required additional post hoc processing through noise subtraction techniques. Over a period of 28 days, we found clear and consistent ArcLight fluorescence responses to a simple sensory input. Finally, we demonstrated the use of ArcLight to resolve cortical S1 sensory responses in the awake mouse. Taken together, our results demonstrate the feasibility of ArcLight as a measurement tool for mesoscopic, chronic imaging.

Erratum: Genetically expressed voltage sensor ArcLight for imaging large scale cortical activity in the anesthetized and awake mouse (erratum)

[This corrects the article DOI: 10.1117/1.NPh.4.3.031212.].

Robotic navigation to subcortical neural tissue for intracellular electrophysiology in vivo

In vivo studies of neurophysiology using the whole cell patch-clamp technique enable exquisite access to both intracellular dynamics and cytosol of cells in the living brain but are underrepresented in deep subcortical nuclei because of fouling of the sensitive electrode tip. We have developed an autonomous method to navigate electrodes around obstacles such as blood vessels after identifying them as a source of contamination during regional pipette localization (RPL) in vivo. In mice, robotic navigation prevented fouling of the electrode tip, increasing RPL success probability 3 mm below the pial surface to 82% (n = 72/88) over traditional, linear localization (25%, n = 24/95), and resulted in high-quality thalamic whole cell recordings with average access resistance (32.0 MΩ) and resting membrane potential (-62.9 mV) similar to cortical recordings in isoflurane-anesthetized mice. Whole cell yield improved from 1% (n = 1/95) to 10% (n = 9/88) when robotic navigation was used during RPL. This method opens the door to whole cell studies in deep subcortical nuclei, including multimodal cell typing and studies of long-range circuits.NEW & NOTEWORTHY This work represents an automated method for accessing subcortical neural tissue for intracellular electrophysiology in vivo. We have implemented a novel algorithm to detect obstructions during regional pipette localization and move around them while minimizing lateral displacement within brain tissue. This approach leverages computer control of pressure, manipulator position, and impedance measurements to create a closed-loop platform for pipette navigation in vivo. This technique enables whole cell patching studies to be performed throughout the living brain.

Thalamic state control of cortical paired-pulse dynamics

Sensory stimulation drives complex interactions across neural circuits as information is encoded and then transmitted from one brain region to the next. In the highly interconnected thalamocortical circuit, these complex interactions elicit repeatable neural dynamics in response to temporal patterns of stimuli that provide insight into the circuit properties that generated them. Here, using a combination of in vivo voltage-sensitive dye (VSD) imaging of cortex, single-unit recording in thalamus, and optogenetics to manipulate thalamic state in the rodent vibrissa pathway, we probed the thalamocortical circuit with simple temporal patterns of stimuli delivered either to the whiskers on the face (sensory stimulation) or to the thalamus directly via electrical or optogenetic inputs (artificial stimulation). VSD imaging of cortex in response to whisker stimulation revealed classical suppressive dynamics, while artificial stimulation of thalamus produced an additional facilitation dynamic in cortex not observed with sensory stimulation. Thalamic neurons showed enhanced bursting activity in response to artificial stimulation, suggesting that bursting dynamics may underlie the facilitation mechanism we observed in cortex. To test this experimentally, we directly depolarized the thalamus, using optogenetic modulation of the firing activity to shift from a burst to a tonic mode. In the optogenetically depolarized thalamic state, the cortical facilitation dynamic was completely abolished. Together, the results obtained here from simple probes suggest that thalamic state, and ultimately thalamic bursting, may play a key role in shaping more complex stimulus-evoked dynamics in the thalamocortical pathway.

NEW & NOTEWORTHY

For the first time, we have been able to utilize optogenetic modulation of thalamic firing modes combined with optical imaging of cortex in the rat vibrissa system to directly test the role of thalamic state in shaping cortical response properties.

Directional acuity of whole-body perturbations during standing balance

The ability to perceive the direction of whole-body motion during standing may be critical to maintaining balance and preventing a fall. Our first goal was to quantify kinesthetic perception of whole-body motion by estimating directional acuity thresholds of support-surface perturbations during standing. The directional acuity threshold to lateral deviations in backward support-surface motion in healthy, young adults was quantified as 9.5±2.4° using the psychometric method (n=25 subjects). However, inherent limitations in the psychometric method, such as a large number of required trials and the predetermined stimulus set, may preclude wider use of this method in clinical populations. Our second goal was to validate an adaptive algorithm known as parameter estimation by sequential testing (PEST) as an alternative threshold estimation technique to minimize the required trial count without predetermined knowledge of the relevant stimulus space. The directional acuity threshold was estimated at 11.7±3.8° from the PEST method (n=11 of 25 subjects, psychometric threshold=10.1±3.1°) using only one-third the number of trials compared to the psychometric method. Furthermore, PEST estimates of the direction acuity threshold were highly correlated with the psychometric estimates across subjects (r=0.93) suggesting that both methods provide comparable estimates of the perceptual threshold. Computational modeling of both techniques revealed similar variance in the estimated thresholds across simulations of about 1°. Our results suggest that the PEST algorithm can be used to more quickly quantify whole-body directional acuity during standing in individuals with balance impairments.

Response reliability observed with voltage-sensitive dye imaging of cortical layer 2/3: the probability of activation hypothesis

A central assertion in the study of neural processing is that our perception of the environment directly reflects the activity of our sensory neurons. This assertion reinforces the intuition that the strength of a sensory input directly modulates the amount of neural activity observed in response to that sensory feature: an increase in the strength of the input yields a graded increase in the amount of neural activity. However, cortical activity across a range of sensory pathways can be sparse, with individual neurons having remarkably low firing rates, often exhibiting suprathreshold activity on only a fraction of experimental trials. To compensate for this observed apparent unreliability, it is assumed that instead the local population of neurons, although not explicitly measured, does reliably represent the strength of the sensory input. This assumption, however, is largely untested. In this study, using wide-field voltage-sensitive dye (VSD) imaging of the somatosensory cortex in the anesthetized rat, we show that whisker deflection velocity, or stimulus strength, is not encoded by the magnitude of the population response at the level of cortex. Instead, modulation of whisker deflection velocity affects the likelihood of the cortical response, impacting the magnitude, rate of change, and spatial extent of the cortical response. An ideal observer analysis of the cortical response points to a probabilistic code based on repeated sampling across cortical columns and/or time, which we refer to as the probability of activation hypothesis. This hypothesis motivates a range of testable predictions for both future electrophysiological and future behavioral studies.

Information Coding through Adaptive Gating of Synchronized Thalamic Bursting

It has been posited that the regulation of burst/tonic firing in the thalamus could function as a mechanism for controlling not only how much but what kind of information is conveyed to downstream cortical targets. Yet how this gating mechanism is adaptively modulated on fast timescales by ongoing sensory inputs in rich sensory environments remains unknown. Using single-unit recordings in the rat vibrissa thalamus (VPm), we found that the degree of bottom-up adaptation modulated thalamic burst/tonic firing as well as the synchronization of bursting across the thalamic population along a continuum for which the extremes facilitate detection or discrimination of sensory inputs. Optogenetic control of baseline membrane potential in thalamus further suggests that this regulation may result from an interplay between adaptive changes in thalamic membrane potential and synaptic drive from inputs to thalamus, setting the stage for an intricate control strategy upon which cortical computation is built.

Electrical and Optical Activation of Mesoscale Neural Circuits with Implications for Coding

Artificial activation of neural circuitry through electrical microstimulation and optogenetic techniques is important for both scientific discovery of circuit function and for engineered approaches to alleviate various disorders of the nervous system. However, evidence suggests that neural activity generated by artificial stimuli differs dramatically from normal circuit function, in terms of both the local neuronal population activity at the site of activation and the propagation to downstream brain structures. The precise nature of these differences and the implications for information processing remain unknown. Here, we used voltage-sensitive dye imaging of primary somatosensory cortex in the anesthetized rat in response to deflections of the facial vibrissae and electrical or optogenetic stimulation of thalamic neurons that project directly to the somatosensory cortex. Although the different inputs produced responses that were similar in terms of the average cortical activation, the variability of the cortical response was strikingly different for artificial versus sensory inputs. Furthermore, electrical microstimulation resulted in highly unnatural spatial activation of cortex, whereas optical input resulted in spatial cortical activation that was similar to that induced by sensory inputs. A thalamocortical network model suggested that observed differences could be explained by differences in the way in which artificial and natural inputs modulate the magnitude and synchrony of population activity. Finally, the variability structure in the response for each case strongly influenced the optimal inputs for driving the pathway from the perspective of an ideal observer of cortical activation when considered in the context of information transmission.

SIGNIFICANCE STATEMENT

Artificial activation of neural circuitry through electrical microstimulation and optogenetic techniques is important for both scientific discovery and clinical translation. However, neural activity generated by these artificial means differs dramatically from normal circuit function, both locally and in the propagation to downstream brain structures. The precise nature of these differences and the implications for information processing remain unknown. The significance of this work is in quantifying the differences, elucidating likely mechanisms underlying the differences, and determining the implications for information processing.

A regenerative microchannel device for recording multiple single-unit action potentials in awake, ambulatory animals

Despite significant advances in robotics, commercially advanced prosthetics provide only a small fraction of the functionality of the amputated limb that they are meant to replace. Peripheral nerve interfacing could provide a rich controlling link between the body and these advanced prosthetics in order to increase their overall utility. Here, we report on the development of a fully integrated regenerative microchannel interface with 30 microelectrodes and signal extraction capabilities enabling evaluation in an awake and ambulatory rat animal model. In vitro functional testing validated the capability of the microelectrodes to record neural signals similar in size and nature to those that occur in vivo. In vitro dorsal root ganglia cultures revealed striking cytocompatibility of the microchannel interface. Finally, in vivo, the microchannel interface was successfully used to record a multitude of single-unit action potentials through 63% of the integrated microelectrodes at the early time point of 3 weeks. This marks a significant advance in microchannel interfacing, demonstrating the capability of microchannels to be used for peripheral nerve interfacing.

Support for the slip hypothesis from whisker-related tactile perception of rats in a noisy environment

Rodents use active whisker movements to explore their environment. The “slip hypothesis” of whisker-related tactile perception entails that short-lived kinematic events (abrupt whisker movements, called “slips”, due to bioelastic whisker properties that occur during active touch of textures) carry the decisive texture information. Supporting this hypothesis, previous studies have shown that slip amplitude and frequency occur in a texture-dependent way. Further, experiments employing passive pulsatile whisker deflections revealed that perceptual performance based on pulse kinematics (i.e., signatures that resemble slips) is far superior to the one based on time-integrated variables like frequency and intensity. So far, pulsatile stimuli were employed in a noise free environment. However, the realistic scenario involves background noise (e.g., evoked by rubbing across the texture). Therefore, if slips are used for tactile perception, the tactile neuronal system would need to differentiate slip-evoked spikes from those evoked by noise. To test the animals under these more realistic conditions, we presented passive whisker-deflections to head-fixed trained rats, consisting of “slip-like” events (waveforms mimicking slips occurring with touch of real textures) embedded into background noise. Varying the (i) shapes (ramp or pulse); (ii) kinematics (amplitude, velocity, etc.); and (iii) the probabilities of occurrence of slip-like events, we observed that rats could readily detect slip-like events of different shapes against noisy background. Psychophysical curves revealed that the difference of slip event and noise amplitude determined perception, while increased probability of occurrence (frequency) had barely any effect. These results strongly support the notion that encoding of kinematics dominantly determines whisker-related tactile perception while the computation of frequency or intensity plays a minor role.

Optogenetic feedback control of neural activity

Optogenetic techniques enable precise excitation and inhibition of firing in specified neuronal populations and artifact-free recording of firing activity. Several studies have suggested that optical stimulation provides the precision and dynamic range requisite for closed-loop neuronal control, but no approach yet permits feedback control of neuronal firing. Here we present the ‘optoclamp’, a feedback control technology that provides continuous, real-time adjustments of bidirectional optical stimulation in order to lock spiking activity at specified targets over timescales ranging from seconds to days. We demonstrate how this system can be used to decouple neuronal firing levels from ongoing changes in network excitability due to multi-hour periods of glutamatergic or GABAergic neurotransmission blockade in vitro as well as impinging vibrissal sensory drive in vivo. This technology enables continuous, precise optical control of firing in neuronal populations in order to disentangle causally related variables of circuit activation in a physiologically and ethologically relevant manner.

DOI:http://dx.doi.org/10.7554/eLife.07192.001

Cells called neurons use electrical signals to rapidly carry information around the body. When a neuron is activated, it generates (or ‘fires’) a short electrical impulse that travels along the cell to relay a message to other neurons, muscles or organs. Optogenetics is a technique that allows scientists to genetically modify neurons to produce proteins that make them light sensitive.

One of the most commonly used light-sensitive proteins is called channelrhodopsin-2. It is activated by blue light and increases the electrical activity of neurons. Another protein is called halorhodopsin, which responds to yellow light and inhibits the firing of neurons. By shining light of particular colors onto neurons that produce these and other light-sensitive proteins, it is possible to manipulate the activity of large populations of neurons.

Most previous optogenetic experiments have involved altering the activity of neurons and then observing the outcome at a later point in time. However, it would be very useful to be able to alter the amount of optical stimulation to achieve particular levels of neuron activity in real time. To achieve this, the level of neuron activity at any point in time would need to be quickly compared to the desired level, so that optogenetics could be used to increase or decrease the firing of neurons as appropriate.

Newman et al. have now developed an optogenetic system called ‘optoclamp’ that can control the activity of neurons in real time. In neurons grown in cell culture, the optoclamp is able to hold the level of neuron activity at particular values for periods of time ranging from 60 seconds to 24 hours. It can be used to restore and maintain the baseline level of neuron activity in the presence of drugs that would otherwise produce large increases or decreases in the firing of neurons. Moreover, in anaesthetized rats, the optoclamp can prevent some neurons from being activated even when the rats' whiskers move, which would normally change their firing level.

Newman et al.'s findings open the door to a new type of neuroscience experiment where it is possible to manipulate activity patterns as they are produced by the brain. This will help researchers to understand how particular patterns of brain activity are linked to learning, memory, and behavior.

DOI:http://dx.doi.org/10.7554/eLife.07192.002

Adaptive shaping of cortical response selectivity in the vibrissa pathway

One embodiment of context-dependent sensory processing is bottom-up adaptation, where persistent stimuli decrease neuronal firing rate over hundreds of milliseconds. Adaptation is not, however, simply the fatigue of the sensory pathway, but shapes the information flow and selectivity to stimulus features. Adaptation enhances spatial discriminability (distinguishing stimulus location) while degrading detectability (reporting presence of the stimulus), for both the ideal observer of the cortex and awake, behaving animals. However, how the dynamics of the adaptation shape the cortical response and this detection and discrimination tradeoff is unknown, as is to what degree this phenomenon occurs on a continuum as opposed to a switching of processing modes. Using voltage-sensitive dye imaging in anesthetized rats to capture the temporal and spatial characteristics of the cortical response to tactile inputs, we showed that the suppression of the cortical response, in both magnitude and spatial spread, is continuously modulated by the increasing amount of energy in the adapting stimulus, which is nonuniquely determined by its frequency and velocity. Single-trial ideal observer analysis demonstrated a tradeoff between detectability and spatial discriminability up to a moderate amount of adaptation, which corresponds to the frequency range in natural whisking. This was accompanied by a decrease in both detectability and discriminability with high-energy adaptation, which indicates a more complex coupling between detection and discrimination than a simple switching of modes. Taken together, the results suggest that adaptation operates on a continuum and modulates the tradeoff between detectability and discriminability that has implications for information processing in ethological contexts.

Microchannel-based regenerative scaffold for chronic peripheral nerve interfacing in amputees

Neurally controlled prosthetics that cosmetically and functionally mimic amputated limbs remain a clinical need because state of the art neural prosthetics only provide a fraction of a natural limb's functionality. Here, we report on the fabrication and capability of polydimethylsiloxane (PDMS) and epoxy-based SU-8 photoresist microchannel scaffolds to serve as viable constructs for peripheral nerve interfacing through in vitro and in vivo studies in a sciatic nerve amputee model where the nerve lacks distal reinnervation targets. These studies showed microchannels with 100 μm × 100 μm cross-sectional areas support and direct the regeneration/migration of axons, Schwann cells, and fibroblasts through the microchannels with space available for future maturation of the axons. Investigation of the nerve in the distal segment, past the scaffold, showed a high degree of organization, adoption of the microchannel architecture forming 'microchannel fascicles', reformation of endoneurial tubes and axon myelination, and a lack of aberrant and unorganized growth that might be characteristic of neuroma formation. Separate chronic terminal in vivo electrophysiology studies utilizing the microchannel scaffolds with permanently integrated microwire electrodes were conducted to evaluate interfacing capabilities. In all devices a variety of spontaneous, sensory evoked and electrically evoked single and multi-unit action potentials were recorded after five months of implantation. Together, these findings suggest that microchannel scaffolds are well suited for chronic implantation and peripheral nerve interfacing to promote organized nerve regeneration that lends itself well to stable interfaces. Thus this study establishes the basis for the advanced fabrication of large-electrode count, wireless microchannel devices that are an important step towards highly functional, bi-directional peripheral nerve interfaces.

The adaptive trade-off between detection and discrimination in cortical representations and behavior

It has long been posited that detectability of sensory inputs can be sacrificed in favor of improved discriminability and that sensory adaptation may mediate this trade-off. The extent to which this trade-off exists behaviorally and the complete picture of the underlying neural representations that likely subserve the phenomenon remain unclear. In the rodent vibrissa system, an ideal observer analysis of cortical activity measured using voltage-sensitive dye imaging in anesthetized animals was combined with behavioral detection and discrimination tasks, thalamic recordings from awake animals, and computational modeling to show that spatial discrimination performance was improved following adaptation, but at the expense of the ability to detect weak stimuli. Together, these results provide direct behavioral evidence for the trade-off between detectability and discriminability, that this trade-off can be modulated through bottom-up sensory adaptation, and that these effects correspond to important changes in thalamocortical coding properties.

Behavioral and electrophysiological effects of cortical microstimulation parameters

Electrical microstimulation has been widely used to artificially activate neural circuits on fast time scales. Despite the ubiquity of its use, little is known about precisely how it activates neural pathways. Current is typically delivered to neural tissue in a manner that provides a locally balanced injection of positive and negative charge, resulting in negligible net charge delivery to avoid the neurotoxic effects of charge accumulation. Modeling studies have suggested that the most common approach, using a temporally symmetric current pulse waveform as the base unit of stimulation, results in preferential activation of axons, causing diffuse activation of neurons relative to the stimulation site. Altering waveform shape and using an asymmetric current pulse waveform theoretically reverses this bias and preferentially activates cell bodies, providing increased specificity. In separate studies, measurements of downstream cortical activation from sub-cortical microstimulation are consistent with this hypothesis, as are recent measurements of behavioral detection threshold currents from cortical microstimulation. Here, we compared the behavioral and electrophysiological effects of symmetric vs. asymmetric current waveform shape in cortical microstimulation. Using a go/no-go behavioral task, we found that microstimulation waveform shape significantly shifts psychometric performance, where a larger current pulse was necessary when applying an asymmetric waveform to elicit the same behavioral response, across a large range of behaviorally relevant current amplitudes. Using voltage-sensitive dye imaging of cortex in anesthetized animals with simultaneous cortical microstimulation, we found that altering microstimulation waveform shape shifted the cortical activation in a manner that mirrored the behavioral results. Taken together, these results are consistent with the hypothesis that asymmetric stimulation preferentially activates cell bodies, albeit at a higher threshold, as compared to symmetric stimulation. These findings demonstrate the sensitivity of the pathway to varying electrical stimulation parameters and underscore the importance of designing electrical stimuli for optimal activation of neural circuits.

System identification of the nonlinear dynamics in the thalamocortical circuit in response to patterned thalamic microstimulation in vivo

OBJECTIVE

Nonlinear system identification approaches were used to develop a dynamical model of the network level response to patterns of microstimulation in vivo.

APPROACH

The thalamocortical circuit of the rodent vibrissa pathway was the model system, with voltage sensitive dye imaging capturing the cortical response to patterns of stimulation delivered from a single electrode in the ventral posteromedial thalamus. The results of simple paired stimulus experiments formed the basis for the development of a phenomenological model explicitly containing nonlinear elements observed experimentally. The phenomenological model was fit using datasets obtained with impulse train inputs, Poisson-distributed in time and uniformly varying in amplitude.

MAIN RESULTS

The phenomenological model explained 58% of the variance in the cortical response to out of sample patterns of thalamic microstimulation. Furthermore, while fit on trial-averaged data, the phenomenological model reproduced single trial response properties when simulated with noise added into the system during stimulus presentation. The simulations indicate that the single trial response properties were dependent on the relative sensitivity of the static nonlinearities in the two stages of the model, and ultimately suggest that electrical stimulation activates local circuitry through linear recruitment, but that this activity propagates in a highly nonlinear fashion to downstream targets.

SIGNIFICANCE

The development of nonlinear dynamical models of neural circuitry will guide information delivery for sensory prosthesis applications, and more generally reveal properties of population coding within neural circuits.

Reading and writing the neural code

It has been more than 20 years since Bialek and colleagues published a landmark paper asking a seemingly innocuous question: what can we extract about the outside world from the spiking activity of sensory neurons? Can we read the neural code? Although this seemingly simple question has helped us shed light on the neural code, we still do not understand the anatomical and neurophysiological constraints that enable these codes to propagate across synapses and form the basis for computations that we need to interact with our environment. The sensitivity of neuronal activity to the timing of synaptic inputs naturally suggests that synchrony determines the form of the neural code, and, in turn, regulation of synchrony is a critical element in 'writing' the neural code through the artificial control of microcircuits to activate downstream structures. In this way, reading and writing the neural code are inextricably linked.

Detection of tactile inputs in the rat vibrissa pathway

The rapid detection of sensory inputs is crucial for survival. Sensory detection explicitly requires the integration of incoming sensory information and the ability to distinguish between relevant information and ongoing neural activity. In this study, head-fixed rats were trained to detect the presence of a brief deflection of their whiskers resulting from a focused puff of air. The animals showed a monotonic increase in response probability and a decrease in reaction time with increased stimulus strength. High-speed video analysis of whisker motion revealed that animals were more likely to detect the stimulus during periods of reduced self-induced motion of the whiskers, thereby allowing the stimulus-induced whisker motion to exceed the ongoing noise. In parallel, we used voltage-sensitive dye (VSD) imaging of barrel cortex in anesthetized rats receiving the same stimulus set as those in the behavioral portion of this study to assess candidate codes that make use of the full spatiotemporal representation and to compare variability in the trial-by-trial nature of the cortical response and the corresponding variability in the behavioral response. By application of an accumulating evidence framework to the population cortical activity measured in separate animals, a strong correspondence was made between the behavioral output and the neural signaling, in terms of both the response probabilities and the reaction times. Taken together, the results here provide evidence for detection performance that is strongly reliant on the relative strength of signal versus noise, with strong correspondence between behavior and parallel electrophysiological findings.

Voltage-sensitive dye imaging reveals improved topographic activation of cortex in response to manipulation of thalamic microstimulation parameters

Voltage-sensitive dye imaging was used to quantify in vivo, network level spatiotemporal cortical activation in response to electrical microstimulation of the thalamus in the rat vibrissa pathway. Thalamic microstimulation evoked a distinctly different cortical response than natural sensory stimulation, with response to microstimulation spreading over a larger area of cortex and being topographically misaligned with the cortical column to which the stimulated thalamic region projects. Electrical stimulation with cathode-leading asymmetric waveforms reduced this topographic misalignment while simultaneously increasing the spatial specificity of the cortical activation. Systematically increasing the asymmetry of the microstimulation pulses revealed a continuum between symmetric and asymmetric stimulation that gradually reduced the topographic bias. These data strongly support the hypothesis that manipulation of the electrical stimulation waveform can be used to selectively activate specific neural elements. Specifically, our results are consistent with the prediction that cathode-leading asymmetric waveforms preferentially stimulate cell bodies over axons, while symmetric waveforms preferentially activate axons over cell bodies. The findings here provide some initial steps toward the design and optimization of microstimulation of neural circuitry, and open the door to more sophisticated engineering tools, such as nonlinear system identification techniques, to develop technologies for more effective control of activity in the nervous system.

Thalamic synchrony and the adaptive gating of information flow to cortex

Although it has long been posited that sensory adaptation serves to enhance information flow in sensory pathways, the neural basis remains elusive. Simultaneous single–unit recordings in the thalamus and cortex in anesthetized rats reveal that adaptation differentially influences thalamus and cortex in a manner that fundamentally changes the nature of information conveyed about vibrissae motion. Utilizing an ideal observer of cortical activity, performance in detecting vibrissa deflections degrades with adaptation, while performance in discriminating between vibrissa deflections of different velocities is enhanced, a trend not observed in thalamus. Analysis of simultaneously recorded thalamic neurons does reveal, however, an analogous adaptive change in thalamic synchrony that mirrors the cortical response. An integrate–and–fire model using experimentally measured thalamic input reproduces the observed transformations. The results here suggest a shift in coding strategy with adaptation that directly controls information relayed to cortex, which could have implications for encoding velocity signatures of textures.

Modulation of temporal precision in thalamic population responses to natural visual stimuli

Natural visual stimuli have highly structured spatial and temporal properties which influence the way visual information is encoded in the visual pathway. In response to natural scene stimuli, neurons in the lateral geniculate nucleus (LGN) are temporally precise - on a time scale of 10-25 ms - both within single cells and across cells within a population. This time scale, established by non stimulus-driven elements of neuronal firing, is significantly shorter than that of natural scenes, yet is critical for the neural representation of the spatial and temporal structure of the scene. Here, a generalized linear model (GLM) that combines stimulus-driven elements with spike-history dependence associated with intrinsic cellular dynamics is shown to predict the fine timing precision of LGN responses to natural scene stimuli, the corresponding correlation structure across nearby neurons in the population, and the continuous modulation of spike timing precision and latency across neurons. A single model captured the experimentally observed neural response, across different levels of contrasts and different classes of visual stimuli, through interactions between the stimulus correlation structure and the nonlinearity in spike generation and spike history dependence. Given the sensitivity of the thalamocortical synapse to closely timed spikes and the importance of fine timing precision for the faithful representation of natural scenes, the modulation of thalamic population timing over these time scales is likely important for cortical representations of the dynamic natural visual environment.

The episodic nature of spike trains in the early visual pathway

An understanding of the neural code in a given visual area is often confounded by the immense complexity of visual stimuli combined with the number of possible meaningful patterns that comprise the response spike train. In the lateral geniculate nucleus (LGN), visual stimulation generates spike trains comprised of short spiking episodes ("events") separated by relatively long intervals of silence, which establishes a basis for in-depth analysis of the neural code. By studying this event structure in both artificial and natural visual stimulus contexts and at different contrasts, we are able to describe the dependence of event structure on stimulus class and discern which aspects generalize. We find that the event structure on coarse time scales is robust across stimulus and contrast and can be explained by receptive field processing. However, the relationship between the stimulus and fine-time-scale features of events is less straightforward, partially due to a significant amount of trial-to-trial variability. A new measure called "label information" identifies structural elements of events that can contain ≤30% more information in the context of natural movies compared with what is available from the overall event timing. The first interspike interval of an event most robustly conveys additional information about the stimulus and is somewhat more informative than the event spike count and much more informative than the presence of bursts. Nearly every event is preserved across contrast despite changes in their fine-time-scale features, suggesting that--at least on a coarse level--the stimulus selectivity of LGN neurons is contrast invariant. Event-based analysis thus casts previously studied elements of LGN coding such as contrast adaptation and receptive field processing in a new light and leads to broad conclusions about the composition of the LGN neuronal code.

Self-motion and the shaping of sensory signals

Sensory systems must form stable representations of the external environment in the presence of self-induced variations in sensory signals. It is also possible that the variations themselves may provide useful information about self-motion relative to the external environment. Rats have been shown to be capable of fine texture discrimination and object localization based on palpation by facial vibrissae, or whiskers, alone. During behavior, the facial vibrissae brush against objects and undergo deflection patterns that are influenced both by the surface features of the objects and by the animal's own motion. The extent to which behavioral variability shapes the sensory inputs to this pathway is unknown. Using high-resolution, high-speed videography of unconstrained rats running on a linear track, we measured several behavioral variables including running speed, distance to the track wall, and head angle, as well as the proximal vibrissa deflections while the distal portions of the vibrissae were in contact with periodic gratings. The measured deflections, which serve as the sensory input to this pathway, were strongly modulated both by the properties of the gratings and the trial-to-trial variations in head-motion and locomotion. Using presumed internal knowledge of locomotion and head-rotation, gratings were classified using short-duration trials (<150 ms) from high-frequency vibrissa motion, and the continuous trajectory of the animal's own motion through the track was decoded from the low frequency content. Together, these results suggest that rats have simultaneous access to low- and high-frequency information about their environment, which has been shown to be parsed into different processing streams that are likely important for accurate object localization and texture coding.

Timing precision in population coding of natural scenes in the early visual system

The timing of spiking activity across neurons is a fundamental aspect of the neural population code. Individual neurons in the retina, thalamus, and cortex can have very precise and repeatable responses but exhibit degraded temporal precision in response to suboptimal stimuli. To investigate the functional implications for neural populations in natural conditions, we recorded in vivo the simultaneous responses, to movies of natural scenes, of multiple thalamic neurons likely converging to a common neuronal target in primary visual cortex. We show that the response of individual neurons is less precise at lower contrast, but that spike timing precision across neurons is relatively insensitive to global changes in visual contrast. Overall, spike timing precision within and across cells is on the order of 10 ms. Since closely timed spikes are more efficient in inducing a spike in downstream cortical neurons, and since fine temporal precision is necessary to represent the more slowly varying natural environment, we argue that preserving relative spike timing at a ∼10-ms resolution is a crucial property of the neural code entering cortex.

Neurons convey information about the world in the form of trains of action potentials (spikes). These trains are highly repeatable when the same stimulus is presented multiple times, and this temporal precision across repetitions can be as fine as a few milliseconds. It is usually assumed that this time scale also corresponds to the timing precision of several neighboring neurons firing in concert. However, the relative timing of spikes emitted by different neurons in a local population is not necessarily as fine as the temporal precision across repetitions within a single neuron. In the visual system of the brain, the level of contrast in the image entering the retina can affect single-neuron temporal precision, but the effects of contrast on the neural population code are unknown. Here we show that the temporal scale of the population code entering visual cortex is on the order of 10 ms and is largely insensitive to changes in visual contrast. Since closely timed spikes are more efficient in inducing a spike in downstream cortical neurons, and since fine temporal precision is necessary in representing the more slowly varying natural environment, preserving relative spike timing at a ∼10-ms resolution may be a crucial property of the neural code entering cortex.

Early neural representation of visual scenes occurs with a temporal precision on the order of 10 ms, which is precise enough to strongly drive downstream neurons in the visual pathway. Unlike individual neurons, the neural population code is largely insensitive to pronounced changes in visual contrast.

Au naturel

Although adaptation is a ubiquitous property of neurons in the early visual pathway, the functional consequences in the natural visual environment are unknown. In this issue of Neuron, Mante et al. show, through a comprehensive set of in vivo experiments in the visual thalamus, that the basic functional mechanisms of adaptation that have been well studied with artificial probes capture the neuronal response in the natural environment and are predictable from properties of the visual scene that may be represented by local neural ensembles.

Sustained focal cortical compression reduces electrically-induced seizure threshold

Brain injury can often result in the subsequent appearance of seizures, suggesting an alteration in neural excitability associated with the balance between neuronal excitation and inhibition. The process by which this occurs has yet to be fully elucidated. The specific nature of the changes in excitation and inhibition is still unclear, as is the process by which the seizures appear following injury. In this study, we investigated the effects of focal cortical compression on electrically-induced localized seizure threshold in rats. Male Long Evans rats were implanted with stimulating screw electrodes in their motor cortices above the regions controlling forelimb movement. Initial seizure threshold was determined in the animals using a ramped electrical stimulation procedure prior to any compression. Following initial threshold determination, animals underwent sustained cortical compression and then following a 24 h recovery period had their seizure thresholds tested again with electrical stimulation. Reliability of threshold measurements was confirmed through repeated measurements of seizure threshold. Localized seizure threshold was significantly lowered following sustained cortical compression as compared with control cases. Taken together, the results here suggest a change in global brain excitability following localized, focal compression.

Visual adaptation: neural, psychological and computational aspects

The term 'visual adaptation' describes the processes by which the visual system alters its operating properties in response to changes in the environment. These continual adjustments in sensory processing are diagnostic as to the computational principles underlying the neural coding of information and can have profound consequences for our perceptual experience. New physiological and psychophysical data, along with emerging statistical and computational models, make this an opportune time to bring together experimental and theoretical perspectives. Here, we discuss functional ideas about adaptation in the light of recent data and identify exciting directions for future research.

Adaptation to stimulus contrast and correlations during natural visual stimulation

In this study, we characterize the adaptation of neurons in the cat lateral geniculate nucleus to changes in stimulus contrast and correlations. By comparing responses to high- and low-contrast natural scene movie and white noise stimuli, we show that an increase in contrast or correlations results in receptive fields with faster temporal dynamics and stronger antagonistic surrounds, as well as decreases in gain and selectivity. We also observe contrast- and correlation-induced changes in the reliability and sparseness of neural responses. We find that reliability is determined primarily by processing in the receptive field (the effective contrast of the stimulus), while sparseness is determined by the interactions between several functional properties. These results reveal a number of adaptive phenomena and suggest that adaptation to stimulus contrast and correlations may play an important role in visual coding in a dynamic natural environment.